All recommended articles

164 items found
25 Jan 2023
article picture

Drivers of genomic landscapes of differentiation across Populus divergence gradient

Shedding light on genomic divergence along the speciation continuum

Recommended by based on reviews by Camille Roux, Steven van Belleghem and 1 anonymous reviewer

The article “Drivers of genomic landscapes of differentiation across Populus divergence gradient” by Shang et al. describes an amazing dataset where genomic variations among 21 pairs of diverging poplar species are compared. Such comparisons are still quite rare and are needed to shed light on the processes shaping genomic divergence along the speciation gradient. Relying on two hundred whole-genome resequenced samples from 8 species that diverged from 1.3 to 4.8 million years ago, the authors aim at identifying the key factors involved in the genomic differentiation between species. They carried out a wide range of robust statistical tests aiming at characterizing the genomic differentiation along the genome of these species pairs. They highlight in particular the role of linked selection and gene flow in shaping the divergence along the genomes of species pairs. They also confirm the significance of introgression among species with a net divergence larger than the upper boundaries of the grey zone of speciation previously documented in animals (da from 0.005 to 0.02, Roux et al. 2016). Because these findings pave the way to research about the genomic mechanisms associated with speciation in species with allopatric and parapatric distributions, I warmingly recommend this article.


Roux C, Fraïsse C, Romiguier J, Anciaux Y, Galtier N, Bierne N (2016) Shedding Light on the Grey Zone of Speciation along a Continuum of Genomic Divergence. PLOS Biology, 14, e2000234.

Shang H, Rendón-Anaya M, Paun O, Field DL, Hess J, Vogl C, Liu J, Ingvarsson PK, Lexer C, Leroy T (2023) Drivers of genomic landscapes of differentiation across Populus divergence gradient. bioRxiv, 2021.08.26.457771, ver. 5 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

23 Jan 2023
article picture

The genetic architecture of local adaptation in a cline

Environmental and fitness landscapes matter for the genetic basis of local adaptation

Recommended by based on reviews by 2 anonymous reviewers

Natural landscapes are often composite, with spatial variation in environmental factors being the norm rather than exception. Adaptation to such variation is a major driver of diversity at all levels of biological organization, from genes to phenotypes, species and ultimately ecosystems. While natural selection favours traits that show a better fit to local conditions, the genomic response to such selection is not necessarily straightforward. This is because many quantitative traits are complex and the product of many loci, each with a small to moderate phenotypic contribution. Adapting to environmental challenges that occur in narrow ranges may thus prove difficult as each individual locus is easily swamped by alleles favoured across the rest of the population range. 

To better understand whether and how evolution overcomes such a hurdle, Laroche and Lenormand [1]  combine quantitative genetics and population genetic modelling to track genomic changes that underpin a trait whose fitness optimum differs between a certain spatial range, referred to as a “pocket”, and the rest of the habitat. As it turns out from their analysis, one critical and probably underappreciated factor in determining the type of genetic architecture that evolves is how fitness declines away from phenotypic optima. One classical and popular model of fitness landscape that relates trait value to reproductive success is Gaussian, whereby small trait variations away from the optimum result in even smaller variations in fitness. This facilitates local adaptation via the invasion of alleles of small effects as carriers inside the pocket show a better fit while those outside the pocket only suffer a weak fitness cost. By contrast, when the fitness landscape is more peaked around the optimum, for instance where the decline is linear, adaptation through weak effect alleles is less likely, requiring larger pockets that are less easily swamped by alleles selected in the rest of the range.  

In addition to mathematically investigating the initial emergence of local adaptation, Laroche and Lenormand use computer simulations to look at its long-term maintenance. In principle, selection should favour a genetic architecture that consolidates the phenotype and increases its heritability, for instance by grouping several alleles of large effects close to one another on a chromosome to avoid being broken down by meiotic recombination. Whether or not this occurs also depends on the fitness landscape. When the landscape is Gaussian, the genetic architecture of the trait eventually consists of tightly linked alleles of large effects. The replacement of small effects by large effects loci is here again promoted by the slow fitness decline around the optimum. This is because any shift in architecture in an adapted population requires initially crossing a fitness valley. With a Gaussian landscape, this valley is shallow enough to be crossed, facilitated by a bit of genetic drift. By contrast, when fitness declines linearly around the optimum, genetic architecture is much less evolutionarily labile as any architecture change initially entails a fitness cost that is too high to bear.     

Overall, Laroche and Lenormand provide a careful and thought-provoking analysis of a classical problem in population genetics. In addition to questioning some longstanding modelling assumptions, their results may help understand why differentiated populations are sometimes characterized by “genomic islands” of divergence, and sometimes not. 


[1] Laroche F, Lenormand T (2022) The genetic architecture of local adaptation in a cline. bioRxiv, 2022.06.30.498280, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

18 Jan 2023
article picture

The fate of recessive deleterious or overdominant mutations near mating-type loci under partial selfing

Maintenance of deleterious mutations and recombination suppression near mating-type loci under selfing

Recommended by based on reviews by 3 anonymous reviewers

The causes and consequences of the evolution of sexual reproduction are a major topic in evolutionary biology. With advances in sequencing technology, it becomes possible to compare sexual chromosomes across species and infer the neutral and selective processes shaping polymorphism at these chromosomes. Most sex and mating-type chromosomes exhibit an absence of recombination in large genomic regions around the animal, plant or fungal sex-determining genes. This suppression of recombination likely occurred in several time steps generating stepwise increasing genomic regions starting around the sex-determining genes. This mechanism generates so-called evolutionary strata of differentiation between sex chromosomes (Nicolas et al., 2004, Bergero and Charlesworth, 2009, Hartmann et al. 2021). The evolution of extended regions of recombination suppression is also documented on mating-type chromosomes in fungi (Hartmann et al., 2021) and around supergenes (Yan et al., 2020, Jay et al., 2021). The exact reason and evolutionary mechanisms for this phenomenon are still, however, debated.

Two hypotheses are proposed: 1) sexual antagonism (Charlesworth et al., 2005), which, nevertheless, does explain the observed occurrence of the evolutionary strata, and 2) the sheltering of deleterious alleles by inversions carrying a lower load than average in the population (Charlesworth and Wall, 1999, Antonovics and Abrams, 2004). In the latter, the mechanism is as follows. A genetic inversion or a suppressor of recombination in cis may exhibit some overdominance behaviour. The inversion exhibiting less recessive deleterious mutations (compared to others at the same locus) may increase in frequency, before at higher frequency occurring at the homozygous state, expressing its genetic load. However, the inversion may never be at the homozygous state if it is genetically linked to a gene in a permanently heterozygous state. The inversion can then be advantageous and may reach fixation at the sex chromosome (Charlesworth and Wall, 1999, Antonovics and Abrams, 2004, Jay et al., 2022). These selective mechanisms promote thus the suppression of recombination around the sex-determining gene, and recessive deleterious mutations are permanently sheltered. This hypothesis is corroborated by the sheltering of deleterious mutations observed around loci under balancing selection (Llaurens et al. 2009, Lenz et al. 2016) and around mating-type genes in fungi and supergenes (Jay et al. 2021, Jay et al., 2022).

In this present theoretical study, Tezenas et al. (2022) analyse how linkage to a necessarily heterozygous fungal mating type locus influences the persistence/extinction time of a new mutation at a second selected locus. This mutation can either be deleterious and recessive, or overdominant. There is arbitrary linkage between the two loci, and sexual reproduction occurs either between 1) gametes of different individuals (outcrossing), or 2) by selfing with gametes originating from the same (intra-tetrad) or different (inter-tetrad) tetrads produced by that individual. Note, here, that the mating-type gene does not prevent selfing. The authors study the initial stochastic dynamics of the mutation using a multi-type branching process (and simulations when analytical results cannot be obtained) to compute the extinction time of the deleterious mutation. The main result is that the presence of a mating-type locus always decreases the purging probability and increases the purging time of the mutations under selfing. Ultimately, deleterious mutations can indeed accumulate near the mating-type locus over evolutionary time scales. In a nutshell, high selfing or high intra-tetrad mating do increase the sheltering effect of the mating-type locus. In effect, the outcome of sheltering of deleterious mutations depends on two opposing mechanisms: 1) a higher selfing rate induces a greater production of homozygotes and an increased effect of the purging of deleterious mutations, while 2) a higher intra-tetrad selfing rate (or linkage with the mating-type locus) generates heterozygotes which have a small genetic load (and are favoured). The authors also show that rare events of extremely long maintenance of deleterious mutations can occur.

The authors conclude by highlighting the manifold effect of selfing which reduces the effective population size and thus impairs the efficiency of selection and increases the mutational load, while also favouring the purge of deleterious homozygous mutations. Furthermore, this study emphasizes the importance of studying the maintenance and accumulation of deleterious mutations in the vicinity of heterozygous loci (e.g. under balancing selection) in selfing species.


Antonovics J, Abrams JY (2004) Intratetrad Mating and the Evolution of Linkage Relationships. Evolution, 58, 702–709.

Bergero R, Charlesworth D (2009) The evolution of restricted recombination in sex chromosomes. Trends in Ecology & Evolution, 24, 94–102.

Charlesworth D, Morgan MT, Charlesworth B (1990) Inbreeding Depression, Genetic Load, and the Evolution of Outcrossing Rates in a Multilocus System with No Linkage. Evolution, 44, 1469–1489.

Charlesworth D, Charlesworth B, Marais G (2005) Steps in the evolution of heteromorphic sex chromosomes. Heredity, 95, 118–128.

Charlesworth B, Wall JD (1999) Inbreeding, heterozygote advantage and the evolution of neo–X and neo–Y sex chromosomes. Proceedings of the Royal Society of London. Series B: Biological Sciences, 266, 51–56.

Hartmann FE, Duhamel M, Carpentier F, Hood ME, Foulongne-Oriol M, Silar P, Malagnac F, Grognet P, Giraud T (2021) Recombination suppression and evolutionary strata around mating-type loci in fungi: documenting patterns and understanding evolutionary and mechanistic causes. New Phytologist, 229, 2470–2491.

Jay P, Chouteau M, Whibley A, Bastide H, Parrinello H, Llaurens V, Joron M (2021) Mutation load at a mimicry supergene sheds new light on the evolution of inversion polymorphisms. Nature Genetics, 53, 288–293.

Jay P, Tezenas E, Véber A, Giraud T (2022) Sheltering of deleterious mutations explains the stepwise extension of recombination suppression on sex chromosomes and other supergenes. PLOS Biology, 20, e3001698.

Lenz TL, Spirin V, Jordan DM, Sunyaev SR (2016) Excess of Deleterious Mutations around HLA Genes Reveals Evolutionary Cost of Balancing Selection. Molecular Biology and Evolution, 33, 2555–2564.

Llaurens V, Gonthier L, Billiard S (2009) The Sheltered Genetic Load Linked to the S Locus in Plants: New Insights From Theoretical and Empirical Approaches in Sporophytic Self-Incompatibility. Genetics, 183, 1105–1118.

Nicolas M, Marais G, Hykelova V, Janousek B, Laporte V, Vyskot B, Mouchiroud D, Negrutiu I, Charlesworth D, Monéger F (2004) A Gradual Process of Recombination Restriction in the Evolutionary History of the Sex Chromosomes in Dioecious Plants. PLOS Biology, 3, e4.

Tezenas E, Giraud T, Véber A, Billiard S (2022) The fate of recessive deleterious or overdominant mutations near mating-type loci under partial selfing. bioRxiv, 2022.10.07.511119, ver. 2 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

Yan Z, Martin SH, Gotzek D, Arsenault SV, Duchen P, Helleu Q, Riba-Grognuz O, Hunt BG, Salamin N, Shoemaker D, Ross KG, Keller L (2020) Evolution of a supergene that regulates a trans-species social polymorphism. Nature Ecology & Evolution, 4, 240–249.

05 Jan 2023
article picture

Promoting extinction or minimizing growth? The impact of treatment on trait trajectories in evolving populations

Trait trajectories in evolving populations: insights from mathematical models

Recommended by based on reviews by Rob Noble and 3 anonymous reviewers

The evolution of cells within organisms can be an important determinant of disease. This is especially clear in the emergence of tumors and cancers from the underlying healthy tissue. In the healthy state, homeostasis is maintained through complex regulatory processes that ensure a relatively constant population size of cells, which is required for tissue function. Tumor cells escape this homeostasis, resulting in uncontrolled growth and consequent disease. Disease progression is driven by further evolutionary processes within the tumor, and so is the response of tumors to therapies. Therefore, evolutionary biology is an important component required for a better understanding of carcinogenesis and the treatment of cancers. In particular, evolutionary theory helps define the principles of mutant evolution and thus to obtain a clearer picture of the determinants of tumor emergence and therapy responses.     

The study by Raatz and Traulsen [1] makes an important contribution in this respect. They use mathematical and computational models to investigate trait evolution in the context of evolutionary rescue, motivated by the dynamics of cancer, and also bacterial infections. This study views the establishment of tumors as cell dynamics in harsh environments, where the population is prone to extinction unless mutants emerge that increase evolutionary fitness, allowing them to expand (evolutionary rescue). The core processes of the model include growth, death, and mutations. Random mutations are assumed to give rise to cell lineages with different trait combinations, where the birth and death rates of cells can change.  The resulting evolutionary trajectories are investigated in the models, and interesting new results were obtained. For example, the turnover of the population was identified as an important determinant of trait evolution. Turnover is defined as the balance between birth and death, with large rates corresponding to fast turnover and small rates to slow turnover. It was found that for fast cell turnover, a given adaptive step in the trait space results in a smaller increase in survival probability than for cell populations with slower turnover. In other words, evolutionary rescue is more difficult to achieve for fast compared to slow turnover populations. While more mutants can be produced for faster cell turnover rates, the analysis showed that this is not sufficient to overcome the barrier to the evolutionary rescue. This result implies that aggressive tumors with fast cell birth and death rates are less likely to persist and progress than tumors with lower turnover rates. This work emphasizes the importance of measuring the turnover rate in different tumors to advance our understanding of the determinants of tumor initiation and progression. The authors discuss that the well-documented heterogeneity in tumors likely also applies to cellular turnover. If a tumor consists of sub-populations with faster and slower turnover, it is possible that a slower turnover cell clone (e.g. characterized by a degree of dormancy) would enjoy a selective advantage. Another source of heterogeneity in turnover could be given by the hierarchical organization of tumors. Similar to the underlying healthy tissue, many tumors are thought to be maintained by a population of cancer stem cells, while the tumor bulk is made up of more differentiated cells. Tissue stem cells tend to be characterized by a lower turnover than progenitor or transit-amplifying cells. Depending on the assumptions about the self-renewal capacity of these different cell populations, the potential for evolutionary rescue could be different depending on the cell compartment in which the mutant emerges. This might be interesting to explore in the future.

There are also implications for treatment. Two types of treatment were investigated: density-affecting treatments in which the density of cells is reduced without altering their trait parameters, and trait-affecting treatments in which the birth and/or death rates are altered. Both types of treatment were found to change the trajectories of trait adaptation, which has potentially important practical implications. Interestingly, it was found that competitive release during treatment can result in situations where after treatment cessation, the non-extinct populations recover to reach sizes that were higher than in the absence of treatment. This points towards the potential of adaptive therapy approaches, where sensitive cells are maintained to some extent to suppress resistant clones [2] competitively. In this context, it is interesting that the success of such approaches might also depend on the turnover of the tumor cell population, as shown by a recent mathematical modeling study [3]. In particular, it was found that adaptive therapy is less likely to work for slow compared to fast turnover tumors. Yet, the current study by Raatz and Traulsen [1] suggests that tumors are more likely to evolve in a slow turnover setting.

While there is strong relevance of this analysis for tumor evolution, the results generated in this study have more general relevance. Besides tumors, the paper discusses applications to bacterial disease dynamics in some detail, which is also interesting to compare and contrast to evolutionary processes in cancer. Overall, this study provides insights into the dynamics of evolutionary rescue that represent valuable additions to evolutionary theory.  


[1] Raatz M, Traulsen A (2023) Promoting extinction or minimizing growth? The impact of treatment on trait trajectories in evolving populations. bioRxiv, 2022.06.17.496570, ver. 2 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

[2] Gatenby RA, Silva AS, Gillies RJ, Frieden BR (2009) Adaptive Therapy. Cancer Research, 69, 4894–4903.

[3] Strobl MAR, West J, Viossat Y, Damaghi M, Robertson-Tessi M, Brown JS, Gatenby RA, Maini PK, Anderson ARA (2021) Turnover Modulates the Need for a Cost of Resistance in Adaptive Therapy. Cancer Research, 81, 1135–1147.

20 Dec 2022
article picture

How does the mode of evolutionary divergence affect reproductive isolation?

A general model of fitness effects following hybridisation

Recommended by based on reviews by Luis-Miguel Chevin and Juan Li

Studying the effects of speciation, hybridisation, and evolutionary outcomes following reproduction from divergent populations is a major research area in evolutionary genetics [1]. There are two phenomena that have been the focus of contemporary research. First, a classic concept is the formation of ‘Bateson-Dobzhansky-Muller’ incompatibilities (BDMi) [2–4] that negatively affect hybrid fitness. Here, two diverging populations accumulate mutations over time that are unique to that subpopulation. If they subsequently meet, then these mutations might negatively interact, leading to a loss in fitness or even a complete lack of reproduction. BDMi formation can be complex, involving multiple genes and the fitness changes can depend on the direction of introgression [5]. Second, such secondary contact can instead lead to heterosis, where offspring are fitter than their parental progenitors [6].

Understanding which outcomes are likely to arise require one to know the potential fitness effects of mutations underlying reproductive isolation, to determine whether they are likely to reduce or enhance fitness when hybrids are formed. This is far from an easy task, as it requires one to track mutations at several loci, along with their effects, across a fitness landscape.

The work of De Sanctis et al. [7] neatly fills in this knowledge gap, by creating a general mathematical framework for describing the consequences of a cross from two divergent populations. The derivations are based on Fisher’s Geometric Model, which is widely used to quantify selection acting on a general fitness landscape that is affected by several biological traits [8,9], and has previously been used in theoretical studies of hybridisation [10–12]. By doing so, they are able to decompose how divergence at multiple loci affects offspring fitness through both additive and dominance effects.

A key result arising from their analyses is demonstrating how offspring fitness can be captured by two main functions. The first one is the ‘net effect of evolutionary change’ that, broadly defined, measures how phenotypically divergent two populations are. The second is the ‘total amount of evolutionary change’, which reflects how many mutations contribute to divergence and the effect sizes captured by each of them. The authors illustrate these measurements using simulations covering different scenarios, demonstrating how different parental states can lead to similar fitness outcomes. They also propose experimental methods to measure the underlying mutational effects.

This study neatly demonstrates how complex genetic phenomena underlying hybridisation can be captured using fairly simple mathematical formulae. This powerful approach will thus open the door for future research to investigate hybridisation in more detail, whether it is by expanding on these theoretical models or using the elegant outcomes to quantify fitness effects in experiments.



1. Coyne JA, Orr HA. Speciation. Sunderland, Mass: Sinauer Associates; 2004.
2. Bateson W, Seward A. Darwin and modern science. Heredity and variation in modern lights. 1909;85: 101.
3. Dobzhansky T. Genetics and the Origin of Species. Columbia university press; 1937.
4. Muller HJ. Isolating mechanisms, evolution and temperature. Biol Symp. 1942;6: 71-125.
5. Fraïsse C, Elderfield JAD, Welch JJ. The genetics of speciation: are complex incompatibilities easier to evolve? J Evol Biol. 2014;27: 688-699.
6. Birchler JA, Yao H, Chudalayandi S, Vaiman D, Veitia RA. Heterosis. The Plant Cell. 2010;22: 2105-2112.
7. De Sanctis B, Schneemann H, Welch JJ. How does the mode of evolutionary divergence affect reproductive isolation? bioRxiv. 2022. 2022.03.08.483443 version 4. 
8. Fisher RA. The genetical theory of natural selection. Oxford: The Clarendon Press; 1930. 
9. Tenaillon O. The Utility of Fisher's Geometric Model in Evolutionary Genetics. Annu Rev Ecol Evol Syst. 2014;45: 179-201.
10. Barton NH. The role of hybridization in evolution. Molecular Ecology. 2001;10: 551-568. 
11. Chevin L-M, Decorzent G, Lenormand T. Niche Dimensionality and The Genetics of Ecological Speciation. Evolution. 2014;68: 1244-1256. 
12. Fraïsse C, Gunnarsson PA, Roze D, Bierne N, Welch JJ. The genetics of speciation: Insights from Fisher's geometric model. Evolution. 2016;70: 1450-1464.

16 Dec 2022
article picture

Conditions for maintaining and eroding pseudo-overdominance and its contribution to inbreeding depression

Pseudo-overdominance: how linkage and selection can interact and oppose to purging of deleterious mutations.

Recommended by based on reviews by Yaniv Brandvain, Lei Zhao and 1 anonymous reviewer

Most mutations affecting fitness are deleterious and they have many evolutionary consequences. The dynamics and consequences of deleterious mutations are a long-standing question in evolutionary biology and a strong theoretical background has already been developed, for example, to predict the mutation load, inbreeding depression or background selection. One of the classical results is that inbreeding helps purge partially recessive deleterious mutations by exposing them to selection in homozygotes. However, this mainly results from single-locus considerations. When interactions among several, more or less linked, deleterious mutations are taken into account, peculiar dynamics can emerge. One of them, called pseudo-overdominance (POD), corresponds to the maintenance in a population of two (or more) haplotype blocks composed of several recessive deleterious mutations in repulsion that mimics overdominance. Indeed, homozygote individuals for one of the haplotype blocks expose many deleterious mutations to selection whereas they are reciprocally masked in heterozygotes, leading to higher fitness of heterozygotes compared to both homozygotes. A related process, called associative overdominance (AOD) is the effect of such deleterious alleles in repulsion on the linked neutral variation that can be increased by AOD. Although this possibility has been recognized for a long time (Otha and Kimura 1969), it has been mainly considered an anecdotal process. Recently, both theoretical (Zhao and Charlesworth 2016) and genomic analyses (Gilbert et al. 2020) have renewed interest in such a process, suggesting that it could be important in weakly recombining regions of a genome. Donald Waller (2021) - one of the co-authors of the current work - also recently proposed that POD could be quantitatively important with broad implications, and could resolve some unexplained observations such as the maintenance of inbreeding depression in highly selfing species. Yet, a proper theoretical framework analysing the effect of inbreeding on POD was lacking.

In this theoretical work, Diala Abu Awad and Donald Waller (2022) addressed this question through an elegant combination of analytical predictions and intensive multilocus simulations. They determined the conditions under which POD can be maintained and how long it could resist erosion by recombination, which removes the negative association between deleterious alleles (repulsion) at the core of the mechanism. They showed that under tight linkage, POD regions can persist for a long time and generate substantial segregating load and inbreeding depression, even under inbreeding, so opposing (for a while) to the purging effect. They also showed that background selection can affect the genomic structure of POD regions by rapidly erasing weak POD regions but maintaining strong POD regions (i.e with many tightly linked deleterious alleles).

These results have several implications. They can explain the maintenance of inbreeding depression despite inbreeding (as anticipated by Waller 2021), which has implications for the evolution of mating systems. If POD can hardly emerge under high selfing, it can persist from an outcrossing ancestor long after the transition towards a higher selfing rate and could explain the maintenance of mixed mating systems(which is possible with true overdominance, see Uyenoyama and Waller 1991). The results also have implications for genomic analyses, pointing to regions of low or no recombination where POD could be maintained, generating both higher diversity and heterozygosity than expected and variance in fitness. As structural variations are likely widespread in genomes with possible effects on suppressing recombination (Mérot et al. 2020), POD regions should be checked more carefully in genomic analyses (see also Gilbert et al. 2020).

Overall, this work should stimulate new theoretical and empirical studies, especially to assess how quantitatively strong and widespread POD can be. It also stresses the importance of properly considering genetic linkage genome-wide, and so the role of recombination landscapes in determining patterns of diversity and fitness effects.


Awad DA, Waller D (2022) Conditions for maintaining and eroding pseudo-overdominance and its contribution to inbreeding depression. bioRxiv, 2021.12.16.473022, ver. 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

Gilbert KJ, Pouyet F, Excoffier L, Peischl S (2020) Transition from Background Selection to Associative Overdominance Promotes Diversity in Regions of Low Recombination. Current Biology, 30, 101-107.e3.

Mérot C, Oomen RA, Tigano A, Wellenreuther M (2020) A Roadmap for Understanding the Evolutionary Significance of Structural Genomic Variation. Trends in Ecology & Evolution, 35, 561–572.

Ohta T, Kimura M (1969) Linkage disequilibrium at steady state determined by random genetic drift and recurrent mutation. Genetics, 63, 229–238.

Uyenoyama MK, Waller DM (1991) Coevolution of self-fertilization and inbreeding depression II. Symmetric overdominance in viability. Theoretical Population Biology, 40, 47–77.

Waller DM (2021) Addressing Darwin’s dilemma: Can pseudo-overdominance explain persistent inbreeding depression and load? Evolution, 75, 779–793.

Zhao L, Charlesworth B (2016) Resolving the Conflict Between Associative Overdominance and Background Selection. Genetics, 203, 1315–1334.

29 Nov 2022
article picture

Joint inference of adaptive and demographic history from temporal population genomic data

Inference of genome-wide processes using temporal population genomic data

Recommended by based on reviews by Lawrence Uricchio and 2 anonymous reviewers

Evolutionary genomics, and population genetics in particular, aim to decipher the respective influence of neutral and selective forces shaping genetic polymorphism in a species/population. This is a much-needed requirement before scanning genome data for footprints of species adaptation to their biotic and abiotic environment (Johri et al. 2022). In general, we would like to quantify the proportion of the genome evolving neutrally and under selective (positive, balancing and negative) pressures (Kern and Hahn 2018, Johri et al. 2021). We thus need to understand patterns of linked selection along the genome, that is how the distribution of genetic polymorphisms is shaped by selected sites and the recombination landscape. The present contribution by Pavinato et al. (2022) provides an additional method in the population genomics toolbox to quantify the extent of linked positive and negative selection using temporal data.

The availability of genomics data for model and non-model species has led to improvement of the modeling framework for demography and selection (Johri et al. 2022), but also new inference methods making use of the full genome data based on the Sequential Markovian Coalescent (SMC, Li and Durbin 2011), Approximate Bayesian Computation (ABC, Jay et al. 2019), ABC and machine learning (Pudlo et al. 2016, Raynal et al. 2019) or Deep Learning (Sanchez et al. 2021). These methods are based on one sample in time and the use of the coalescent theory to reconstruct the past (demographic) history. However, it is also possible to obtain for many species temporal data sampled over several time points. For species with short generation time (in experimental evolution or monitored populations), one can sample a population every couple of generations as exemplified with Drosophila melanogaster (Bergland et al. 2010). For species with longer generation times that cannot be easily regularly sampled in time, it becomes possible to sequence available specimens from museums (e.g. Cridland et al. 2018) or ancient DNA samples. Methods using temporal data are based on the classical population genomics assumption that demography (migration, population subdivision, population size changes) leaves a genome-wide signal, while selection leaves a localized signal in the close vicinity of the causal mutation. Several methods do assess the demography of a population (change in effective population size, Ne, in time) using temporal data (e.g. Jorde and Ryman 2007) which can be used to calibrate the detection of loci under strong positive selection (Foll et al. 2014). Recently Buffalo and Coop (2020) used genome-wide covariance between allele frequency changes across time samples (and across replicates) to quantify the effects of linked selection over short timescales. 

In the present contribution, Pavinato et al. (2022) make use of temporal data to draw the joint estimation of demographic and selective parameters using a simulation-based method (ABC-Random Forests). This study by Pavinato et al. (2022) builds a framework allowing to infer the census size of the population in time (N) separately from the effect of genetic drift, which is determined by change in effective population size (Ne) in time, as well estimates of genome-wide parameters of selection. In a nutshell, the authors use a forward simulator and summarize genome data by genomic windows using classic statistics (nucleotide diversity, Tajima’s D, FST, heterozygosity) between time samples and for each sample. They specifically use the distributions (higher moments) of these statistics among all windows. The authors combine as input for the ABC-RF, vectors of summary statistics, model parameters and five latent variables: Ne, the ratio Ne/N, the number of beneficial mutations under strong selection, the average selection coefficient of strongly selected mutations, and the average substitution load. Indeed, the authors are interested in three different types of selection components: 1) the adaptive potential of a population which is estimated as the population mutation rate of beneficial mutations (θb), 2) the number of mutations under strong selection (irrespective of whether they reached fixation or not), and 3) the overall population fitness which is a function of the genetic load. In other words, the novelty of this method is not to focus on the detection of loci under selection, but to infer key parameters/distributions summarizing the genome-wide signal of demography and (positive and negative) selection. As a proof of principle, the authors then apply their method to a dataset of feral populations of honey bees (Apis mellifera) collected in California across many years and recovered from Museum samples (Cridland et al. 2018). The approach yields estimates of Ne which are on the same order of magnitude of previous estimates in hymenopterans, and the authors discuss why the different populations show various values of Ne and N which can be explained by different history of admixture with wild but also domesticated lineages of bees.

This study focuses on quantifying the genome-wide joint footprints of demography, and strong positive and negative selection to determine which proportion of the genome evolves neutrally or not. Further application of this method can be anticipated, for example, to study species with ecological and life-history traits which generate discrepancies between census size and Ne, for example for plants with selfing or seed banking (Sellinger et al. 2020), and for which the genome-wide effect of linked selection is not fully understood.


Johri P, Aquadro CF, Beaumont M, Charlesworth B, Excoffier L, Eyre-Walker A, Keightley PD, Lynch M, McVean G, Payseur BA, Pfeifer SP, Stephan W, Jensen JD (2022) Recommendations for improving statistical inference in population genomics. PLOS Biology, 20, e3001669.

Kern AD, Hahn MW (2018) The Neutral Theory in Light of Natural Selection. Molecular Biology and Evolution, 35, 1366–1371.

Johri P, Riall K, Becher H, Excoffier L, Charlesworth B, Jensen JD (2021) The Impact of Purifying and Background Selection on the Inference of Population History: Problems and Prospects. Molecular Biology and Evolution, 38, 2986–3003.

Pavinato VAC, Mita SD, Marin J-M, Navascués M de (2022) Joint inference of adaptive and demographic history from temporal population genomic data. bioRxiv, 2021.03.12.435133, ver. 6 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

Li H, Durbin R (2011) Inference of human population history from individual whole-genome sequences. Nature, 475, 493–496.

Jay F, Boitard S, Austerlitz F (2019) An ABC Method for Whole-Genome Sequence Data: Inferring Paleolithic and Neolithic Human Expansions. Molecular Biology and Evolution, 36, 1565–1579.

Pudlo P, Marin J-M, Estoup A, Cornuet J-M, Gautier M, Robert CP (2016) Reliable ABC model choice via random forests. Bioinformatics, 32, 859–866.

Raynal L, Marin J-M, Pudlo P, Ribatet M, Robert CP, Estoup A (2019) ABC random forests for Bayesian parameter inference. Bioinformatics, 35, 1720–1728.

Sanchez T, Cury J, Charpiat G, Jay F (2021) Deep learning for population size history inference: Design, comparison and combination with approximate Bayesian computation. Molecular Ecology Resources, 21, 2645–2660.

Bergland AO, Behrman EL, O’Brien KR, Schmidt PS, Petrov DA (2014) Genomic Evidence of Rapid and Stable Adaptive Oscillations over Seasonal Time Scales in Drosophila. PLOS Genetics, 10, e1004775.

Cridland JM, Ramirez SR, Dean CA, Sciligo A, Tsutsui ND (2018) Genome Sequencing of Museum Specimens Reveals Rapid Changes in the Genetic Composition of Honey Bees in California. Genome Biology and Evolution, 10, 458–472.

Jorde PE, Ryman N (2007) Unbiased Estimator for Genetic Drift and Effective Population Size. Genetics, 177, 927–935.

Foll M, Shim H, Jensen JD (2015) WFABC: a Wright–Fisher ABC-based approach for inferring effective population sizes and selection coefficients from time-sampled data. Molecular Ecology Resources, 15, 87–98.

Buffalo V, Coop G (2020) Estimating the genome-wide contribution of selection to temporal allele frequency change. Proceedings of the National Academy of Sciences, 117, 20672–20680.

Sellinger TPP, Awad DA, Moest M, Tellier A (2020) Inference of past demography, dormancy and self-fertilization rates from whole genome sequence data. PLOS Genetics, 16, e1008698.

21 Nov 2022
article picture

Artisanal and farmers bread making practices differently shape fungal species community composition in French sourdoughs

The variety of bread-making practices promotes diversity conservation in food microbial communities

Recommended by and based on reviews by 2 anonymous reviewers

Domesticated organisms are excellent models for understanding ecology and evolution and they are important for our food production and safety. While less studied than plants and animals, micro-organisms have also been domesticated, in particular for food fermentation [1]. The most studied domesticated micro-organism is the yeast used to make wine, beer and bread, Saccharomyces cerevisiae [2, 3, 4].

Filamentous fungi used for cheese-making have recently gained interest, for example Penicillium roqueforti used to make blue cheeses and P. camemberti to make soft cheeses [5, 6, 7, 8]. As for plants and animals, domestication has led to beneficial traits for food production in fermenting fungi, but also to bottlenecks and degeneration [6, 7, 9]; P. camemberti for example does not produce enough spores any more for optimal culture and inoculation and P. roqueforti has lost sexual fertility [9]. The loss of genetic diversity and of species diversity in our food production system is concerning for multiple reasons : i) it jeopardizes future improvement in the face of global changes ; ii) it causes the loss of evolved diversity during centuries under human selection, and therefore of beneficial characteristics and specificities that we may never be able to recover ; iii) it leads to degeneration in the few cultivated strains; iv) it impoverishes the diversity of our food products and local adaptation of production practices. 

The study of domesticated fungi used for food fermentation has focused so far on the evolution of lineages and on their metabolic specificities. Microbiological assemblages and species diversity have been much less studied, while they likely also have a strong impact on the quality and safety of final products. This study by Elisa Michel and colleagues [10] addresses this question, using an interdisciplinary participatory research approach including bakers, psycho-sociologists and microbiologists to analyse bread-making practices and their impact on microbial communities in sourdough. Elisa Michel and colleagues [10] identified two distinct groups of bread-making practices based on interviews and surveys, with farmer-like practices (low bread production, use of ancient wheat populations, manual kneading, working at ambient temperature, long fermentation periods and no use of commercial baker’s yeast) versus more intensive, artisanal-like practices. Metabarcoding and microbial culture-based analyses showed that the well-known baker’s yeast, Saccharomyces cerevisiae, was, surprisingly, not the most common species in French organic sourdoughs. Kazachstania was the most represented yeast genus over all sourdoughs, both in terms of read abundance and of species diversity. Kazachstania species were also often dominant in individual sourdoughs, but Saccharomyces uvarum or Torulaspora delbrueckii could also be the dominant yeast species.

Metabarcoding analyses further revealed that the composition of the fungal communities differed between the farmer-like and more intensive practices, representing the first evidence of the influence of artisanal practices on microbial communities. The fungal communities were impacted by a combination of bread-making variables including the type of wheat varieties, the length of fermentation, the quantity of bread made per week and the use of commercial yeast. Maintaining on farm less intensive bread-making practices, may allow the preservation of typical species and phenotypic diversity in microbial communities in sourdough. Farmer-like practices did not lead to higher diversity within sourdoughs but, overall, the diversity of bread-making practices allow maintaining a larger diversity in sourdoughs. For example, different Kazachstania species were most abundant in sourdoughs from artisanal-like and farmer-like practices. Interviews with the bakers suggested the role of dispersal of Kazachstania species in shaping sourdough microbial communities, dispersal occurring by seed exchanges, sourdough mixing or gifts, bread-making training in common or working in one another’s bakery. Nikolai Vavilov [11] had already highlighted for crops the importance of isolated cultures and selection in different farms for generating and preserving crop diversity, but also the importance of seed exchange for fostering adaptation. 

Furthermore, one of the yeast frequently found in artisanal sourdoughs, Kazachstania humilis, displayed phenotypic differences between sourdough and non-sourdough strains, suggesting domestication. The sourdough strains exhibited significantly higher CO2 production rate and a lower fermentation latency-phase time. 

The study by Elisa Michel and colleagues [10] is thus novel and inspiring in showing the importance of interdisciplinary studies, combining metabarcoding, microbiology and interviews for assessing the composition and diversity of microbial communities in human-made food, and in revealing the impact of artisanal-like bread-making practices in preserving microbial community diversity.

Interdisciplinary studies are still rare but have already shown the importance of combining ethno-ecology, biology and evolution to decipher the role of human practices on genetic diversity in crops, animals and food microorganisms and to help preserving genetic resources [12]. For example, in the case of the bread wheat Triticum aestivum, such interdisciplinary studies have shown that genetic diversity has been shaped by farmers’ seed diffusion and farming practices [13]. We need more of such interdisciplinary studies on the impact of farmer versus industrial agricultural and food-making practices as we urgently need to preserve the diversity of micro-organisms used in food production that we are losing at a rapid pace [6, 7, 14]. 


[1] Dupont J, Dequin S, Giraud T, Le Tacon F, Marsit S, Ropars J, Richard F, Selosse M-A (2017) Fungi as a Source of Food. Microbiology Spectrum, 5, 5.3.09.

[2] Legras J-L, Galeote V, Bigey F, Camarasa C, Marsit S, Nidelet T, Sanchez I, Couloux A, Guy J, Franco-Duarte R, Marcet-Houben M, Gabaldon T, Schuller D, Sampaio JP, Dequin S (2018) Adaptation of S. cerevisiae to Fermented Food Environments Reveals Remarkable Genome Plasticity and the Footprints of Domestication. Molecular Biology and Evolution, 35, 1712–1727.

[3] Bai F-Y, Han D-Y, Duan S-F, Wang Q-M (2022) The Ecology and Evolution of the Baker’s Yeast Saccharomyces cerevisiae. Genes, 13, 230.

[4] Fay JC, Benavides JA (2005) Evidence for Domesticated and Wild Populations of Saccharomyces cerevisiae. PLOS Genetics, 1, e5.

[5] Ropars J, Rodríguez de la Vega RC, López-Villavicencio M, Gouzy J, Sallet E, Dumas É, Lacoste S, Debuchy R, Dupont J, Branca A, Giraud T (2015) Adaptive Horizontal Gene Transfers between Multiple Cheese-Associated Fungi. Current Biology, 25, 2562–2569.

[6] Dumas E, Feurtey A, Rodríguez de la Vega RC, Le Prieur S, Snirc A, Coton M, Thierry A, Coton E, Le Piver M, Roueyre D, Ropars J, Branca A, Giraud T (2020) Independent domestication events in the blue-cheese fungus Penicillium roqueforti. Molecular Ecology, 29, 2639–2660.

[7] Ropars J, Didiot E, Rodríguez de la Vega RC, Bennetot B, Coton M, Poirier E, Coton E, Snirc A, Le Prieur S, Giraud T (2020) Domestication of the Emblematic White Cheese-Making Fungus Penicillium camemberti and Its Diversification into Two Varieties. Current Biology, 30, 4441-4453.e4.

[8] Caron T, Piver ML, Péron A-C, Lieben P, Lavigne R, Brunel S, Roueyre D, Place M, Bonnarme P, Giraud T, Branca A, Landaud S, Chassard C (2021) Strong effect of Penicillium roqueforti populations on volatile and metabolic compounds responsible for aromas, flavor and texture in blue cheeses. International Journal of Food Microbiology, 354, 109174.

[9] Ropars J, Lo Y-C, Dumas E, Snirc A, Begerow D, Rollnik T, Lacoste S, Dupont J, Giraud T, López-Villavicencio M (2016) Fertility depression among cheese-making Penicillium roqueforti strains suggests degeneration during domestication. Evolution, 70, 2099–2109.

[10] Michel E, Masson E, Bubbendorf S, Lapicque L, Nidelet T, Segond D, Guézenec S, Marlin T, Devillers H, Rué O, Onno B, Legrand J, Sicard D, Bakers TP (2022) Artisanal and farmer bread making practices differently shape fungal species community composition in French sourdoughs. bioRxiv, 679472, ver. 6 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

[11] Vavilov NI, Vavylov MI, Dorofeev VF (1992) Origin and Geography of Cultivated Plants. Cambridge University Press.

[12] Saslis-Lagoudakis CH, Clarke AC (2013) Ethnobiology: the missing link in ecology and evolution. Trends in Ecology & Evolution, 28, 67–68.

[13] Thomas M, Demeulenaere E, Dawson JC, Khan AR, Galic N, Jouanne-Pin S, Remoue C, Bonneuil C, Goldringer I (2012) On-farm dynamic management of genetic diversity: the impact of seed diffusions and seed saving practices on a population-variety of bread wheat. Evolutionary Applications, 5, 779–795.

[14] Demeulenaere É, Lagrola M (2021) Des indicateurs pour accompagner “ les éleveurs de microbes” : Une communauté épistémique face au problème des laits “ paucimicrobiens ” dans la production fromagère au lait cru (1995-2015). Revue d’anthropologie des connaissances, 15.

18 Nov 2022
article picture

Fitness costs and benefits in response to artificial artesunate selection in Plasmodium

The importance of understanding fitness costs associated with drug resistance throughout the life cycle of malaria parasites

Recommended by based on reviews by Sarah Reece and Marianna Szucs

Antimalarial resistance is a major hurdle to malaria eradication efforts. The spread of drug resistance follows basic evolutionary principles, with competitive interactions between resistant and susceptible malaria strains being central to the fitness of resistant parasites. These competitive interactions can be used to design resistance management strategies, whereby a fitness cost of resistant parasites can be exploited through maintaining competitive suppression of the more fit drug-susceptible parasites. This can potentially be achieved using lower drug dosages or lower frequency of drug treatments. This approach has been demonstrated to work empirically in a rodent malaria model [1,2] and has been demonstrated to have clinical success in cancer treatments [3]. However, these resistance management approaches assume a fitness cost of the resistant pathogen, and, in the case of malaria parasites in general, and for artemisinin resistant parasites in particular, there is limited information on the presence of such fitness cost. The best suggestive evidence for the presence of fitness costs comes from the discontinuation of the use of the drug, which, in the case of chloroquine, was followed by a gradual drop in resistance frequency over the following decade [see e.g. 4,5]. However, with artemisinin derivative drugs still in use, alternative ways to study the presence of fitness costs need to be undertaken. 
There are several good in vitro studies demonstrating artemisinin resistant parasites being competitively suppressed by wildtype parasites [see e.g. 6–9], however, these have the limitation that they will only be able to detect the fitness cost during the blood stage of the infection and in an artificial environment. So far, there have not been animal models that have thoroughly studied the presence of resistance fitness costs for artemisinin resistant parasites. Moreover, in these types of studies, the focus is mostly on the fitness cost as detected in the vertebrate host. However, malaria parasites spent a significant portion of their life cycle in the mosquito host, where fitness costs could also be expressed. Overall, it is the fitness over the entire life cycle of the parasite that would determine if and to what extent a reduction in resistance frequency would be observed when the use of a drug is stopped. 
Here, Villa and colleagues present a study to quantify such fitness cost of artesunate-resistant parasites, not only in a vertebrate host, but also in the mosquito vector [10]. They used the underutilized model system of avian malaria species Plasmodium relictum in canaries. Villa and colleagues selected for several different resistance strains, which had a similar delayed clearance phenotype as observed in the field. Interestingly, they did not find evidence of a fitness cost in the vertebrate host. In fact, the resistant strains reached greater parasitaemia than the susceptible strains. From this set of experiments it is unclear whether this is an anomaly or a relevant result. Future work should establish this, though fitness benefits associated with drug resistance have been seen before in Leishmania parasites [11]. An important caveat to the present study is that the parasites were grown in the absence of competition and it is feasible that a cost is not detected when growing by themselves, but would become apparent when in competition. However, these types of experiments are technologically more challenging to perform as it would require an accurate quantification methodology able to distinguish based on one SNP. This problem has been circumvented by either using relative peak height in sanger sequencing [12], or via the likely more accurate route of pyrosequencing [7–9], though these methodologies only give relative frequencies rather than absolute densities. 
The most interesting observation in the study by Villa et al is that the authors detected a fitness cost being played out in the mosquito vector, where the resistant strains had a decreased infectivity compared to the susceptible strain. This finding is important because 1) it demonstrates that the whole life cycle needs to be taken into account when understanding fitness costs, 2) resistance management strategies that are based on treatment within the vertebrate host may not have the intended effect if the cost does not play out in this host, and 3) it opens new research avenues to explore the possibility of exploiting fitness costs in mosquito vector. Future research should focus on incorporating these assays on fitness costs in mosquitoes, particularly for P. falciparum parasites. Additionally, it would be interesting to expand this work in a competitive environment, both in the vertebrate host as in the mosquito host. Finally, it would be important to establish the generalizability of such fitness cost in mosquitoes. If it is a significant factor, mathematical models could incorporate this effect in predictions on the spread of resistance.


[1] Huijben S, Bell AS, Sim DG, Tomasello D, Mideo N, Day T, et al. 2013. Aggressive chemotherapy and the selection of drug resistant pathogens. PLoS Pathog. 9(9): e1003578.
[2] Huijben S, Nelson WA, Wargo AR, Sim DG, Drew DR, Read AF. 2010. Chemotherapy, within-host ecology and the fitness of drug-resistant malaria parasites. Evolution (N Y). 64(10): 2952-68.
[3] Zhang J, Cunningham JJ, Brown JS, Gatenby RA. 2017. Integrating evolutionary dynamics into treatment of metastatic castrate-resistant prostate cancer. Nat Commun. 8(1).
[4] Laufer MK, Takala-Harrison S, Dzinjalamala FK, Stine OC, Taylor TE, Plowe C v. 2010. Return of chloroquine-susceptible falciparum malaria in Malawi was a reexpansion of diverse susceptible parasites. J Infect Dis. 202(5): 801-808. 

[5] Mharakurwa S, Matsena-Zingoni Z, Mudare N, Matimba C, Gara TX, Makuwaza A, et al. 2021. Steep rebound of chloroquine-sensitive Plasmodium falciparum in Zimbabwe. J Infect Dis. 223(2): 306-9.
[6] Tirrell AR, Vendrely KM, Checkley LA, Davis SZ, McDew-White M, Cheeseman IH, et al. 2019. Pairwise growth competitions identify relative fitness relationships among artemisinin resistant Plasmodium falciparum field isolates. Malar J. 18: 295.
[7] Hott A, Tucker MS, Casandra D, Sparks K, Kyle DE. 2015. Fitness of artemisinin-resistant Plasmodium falciparum in vitro. J Antimicrob Chemother. 70(10): 2787-2796.
[8] Straimer J, Gnädig NF, Stokes BH, Ehrenberger M, Crane AA, Fidock DA. 2017. Plasmodium falciparum K13 mutations differentially impact ozonide susceptibility and parasite fitness in vitro. mBio. 8(2): e00172-17.
[9] Nair S, Li X, Arya GA, McDew-White M, Ferrari M, Nosten F, et al. 2018. Fitness costs and the rapid spread of kelch13-C580Y substitutions conferring artemisinin resistance. Antimicrob Agents Chemother. 62(9).
[10] Villa M, Berthomieu A, Rivero A. Fitness costs and benefits in response to artificial artesunate selection in Plasmodium. 2022. bioRxiv, 20220128478164, ver 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology.
[11] Vanaerschot M, Decuypere S, Berg M, Roy S, Dujardin JC. 2013. Drug-resistant microorganisms with a higher fitness--can medicines boost pathogens? Crit Rev Microbiol. 39(4): 384-394.
[12] Hassett MR, Roepe PD. In vitro growth competition experiments that suggest consequences of the substandard artemisinin epidemic that may be accelerating drug resistance in P. falciparum malaria. 2021. PLoS One. 16(3): e0248057.

16 Nov 2022
article picture

Divergence of olfactory receptors associated with the evolution of assortative mating and reproductive isolation in mice

Tinder in mice: A match made with the sense of smell

Recommended by based on reviews by Ludovic Claude Maisonneuve, Angeles de Cara and 1 anonymous reviewer

Differentiation-based genome scans lie at the core of speciation and adaptation genomics research. Dating back to Lewontin & Krakauer (1973), they have become very popular with the advent of genomics to identify genome regions of enhanced differentiation relative to neutral expectations. These regions may represent genetic barriers between divergent lineages and are key for studying reproductive isolation. However, genome scan methods can generate a high rate of false positives, primarily if the neutral population structure is not accounted for (Bierne et al. 2013). Moreover, interpreting genome scans can be challenging in the context of secondary contacts between diverging lineages (Bierne et al. 2011), because the coupling between different components of reproductive isolation (local adaptation, intrinsic incompatibilities, mating preferences, etc.) can occur readily, thus preventing the causes of differentiation from being determined.

Smadja and collaborators (2022) applied a sophisticated genome scan for trait association (BAYPASS, Gautier 2015) to underlie the genetic basis of a polygenetic behaviour: assortative mating in hybridizing mice. My interest in this neat study mainly relies on two reasons. First, the authors used an ingenious geographical setting (replicate pairs of “Choosy” versus “Non-Choosy” populations) with multi-way comparisons to narrow down the list of candidate regions resulting from BAYPASS. The latter corrects for population structure, handles cost-effective pool-seq data and allows for gene-based analyses that aggregate SNP signals within a gene. These features reinforce the set of outlier genes detected; however, not all are expected to be associated with mating preference. 

The second reason why this study is valuable to me is that Smadja et al. (2022) complemented the population genomic approach with functional predictions to validate the genetic signal. In line with previous behavioural and chemical assays on the proximal mechanisms of mating preferences, they identified multiple olfactory and vomeronasal receptor genes as highly significant candidates. Therefore, combining genomic signals with functional analyses is a clever way to provide insights into the causes of reproductive isolation, especially when multiple barriers are involved. This is typically true for reinforcement (Butlin & Smadja 2018), suspected to occur in these mice because, in that case, assortative mating (a prezygotic barrier) evolves in response to the cost of hybridization (for example, due to hybrid inviability). 

As advocated by the authors, their study paves the way for future work addressing the genetic basis of reinforcement, a trait of major evolutionary importance for which we lack empirical data. They also make a compelling case using complementary approaches that olfactory and vomeronasal receptors have a central role in mammal speciation.


Bierne N, Welch J, Loire E, Bonhomme F, David P (2011) The coupling hypothesis: why genome scans may fail to map local adaptation genes. Mol Ecol 20: 2044–2072.

Bierne N, Roze D, Welch JJ (2013) Pervasive selection or is it…? why are FST outliers sometimes so frequent? Mol Ecol 22: 2061–2064. 

Butlin RK, Smadja CM (2018) Coupling, Reinforcement, and Speciation. Am Nat 191:155–172. 

Gautier M (2015) Genome-Wide Scan for Adaptive Divergence and Association with Population-Specific Covariates. Genetics 201:1555–1579. 

Lewontin RC, Krakauer J (1973) Distribution of gene frequency as a test of the theory of selective neutrality of polymorphisms. Genetics 74: 175–195. 

Smadja CM, Loire E, Caminade P, Severac D, Gautier M, Ganem G (2022) Divergence of olfactory receptors associated with the evolution of assortative mating and reproductive isolation in mice. bioRxiv, 2022.07.21.500634, ver. 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

02 Nov 2022
article picture

Evolution of immune genes in island birds: reduction in population sizes can explain island syndrome

Demographic effects may affect adaptation to islands

Recommended by based on reviews by Steven Fiddaman and 3 anonymous reviewers

The unique challenges associated with living on an island often result in organisms displaying a specific suite of traits commonly referred to as “island syndrome” (Adler and Levins, 1994; Burns, 2019; Baeckens and Van Damme, 2020). Large phenotypic shifts such as changes in size (e.g. shifts to gigantism or dwarfism, Lomolino, 2005) or coloration (Doutrelant et al., 2016) abound in the literature. However, less obvious phenotypes may also play a key role in adaptation to islands.

One such trait, reduced immune function, has important implications for the future of island populations in the face of anthropogenic-induced changes. Due to lower parasite pressure caused by a less diverse and less virulent parasite population, island hosts may show a decrease in immune defenses (Beadell et al., 2006; Pérez‐Rodríguez et al., 2013). However, this hypothesis has been challenged, as many studies have found ambiguous or conflicting results (Matson, 2006; Illera et al., 2015).

While most previous work has examined various immunological parameters (e.g., antibody concentrations), here, Barthe et al. (2022) take the novel approach of examining molecular signatures of immune genes. Using comparative genomic data from 34 different species of birds the authors examine the ratio of synonymous substitutions (i.e., not changing an amino acid) to non-synonymous substitutions (i.e., changing an amino acid) in innate and acquired immune genes (Pn/Ps ratio). Because population sizes on islands are lower which will affect molecular evolution, they compare these results to data from 97 control genes.  Assuming relaxed selection on islands predicts that the difference between the Pn/Ps ratio of immune genes and of control genes (ΔPn/Ps) is greater in island species compared to mainland ones.

As with previous work the authors found that the results differ depending on the category of immune genes. Both forms of innate defense: beta-defensins and Toll-like receptors did not show higher ΔPn/Ps for island populations. As these genes still have a higher Pn/Ps than control genes, the authors argue these results are in line with these genes being under purifying selection but lacking an “island effect”. Instead, the authors argue that demographic effects (i.e., reductions in Ne) may lead to the decreased immunity documented in other studies. In contrast, there was a reduction in Pn/Ps in MHC II genes, known to be under balancing selection. This reduction was stronger in island species and thus the authors argue that this is the only class of genes where a role for relaxed selection can be invoked. 

Together these results demonstrate that the changes in immunity experienced by island species are complex and that different categories of immune genes can experience different selective pressures. By including control genes in their study, they particularly highlight the importance of accounting for shifts in Ne when examining patterns of island species evolution. Hopefully, this kind of framework will be applied to other taxa to determine if these results are widespread or more specific to birds. 


Adler GH, Levins R (1994) The Island Syndrome in Rodent Populations. The Quarterly Review of Biology, 69, 473–490.

Baeckens S, Van Damme R (2020) The island syndrome. Current Biology, 30, R338–R339.

Barthe M, Doutrelant C, Covas R, Melo M, Illera JC, Tilak M-K, Colombier C, Leroy T, Loiseau C, Nabholz B (2022) Evolution of immune genes in island birds: reduction in population sizes can explain island syndrome. bioRxiv, 2021.11.21.469450, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

Beadell JS, Ishtiaq F, Covas R, Melo M, Warren BH, Atkinson CT, Bensch S, Graves GR, Jhala YV, Peirce MA, Rahmani AR, Fonseca DM, Fleischer RC (2006) Global phylogeographic limits of Hawaii’s avian malaria. Proceedings of the Royal Society B: Biological Sciences, 273, 2935–2944.

Burns KC (2019) Evolution in Isolation: The Search for an Island Syndrome in Plants. Cambridge University Press, Cambridge.

Doutrelant C, Paquet M, Renoult JP, Grégoire A, Crochet P-A, Covas R (2016) Worldwide patterns of bird colouration on islands. Ecology Letters, 19, 537–545.

Illera JC, Fernández-Álvarez Á, Hernández-Flores CN, Foronda P (2015) Unforeseen biogeographical patterns in a multiple parasite system in Macaronesia. Journal of Biogeography, 42, 1858–1870.

Lomolino MV (2005) Body size evolution in insular vertebrates: generality of the island rule. Journal of Biogeography, 32, 1683–1699.

Matson KD (2006) Are there differences in immune function between continental and insular birds? Proceedings of the Royal Society B: Biological Sciences, 273, 2267–2274.

Pérez-Rodríguez A, Ramírez Á, Richardson DS, Pérez-Tris J (2013) Evolution of parasite island syndromes without long-term host population isolation: parasite dynamics in Macaronesian blackcaps Sylvia atricapilla. Global Ecology and Biogeography, 22, 1272–1281.

31 Oct 2022
article picture

Genotypic sex shapes maternal care in the African Pygmy mouse, Mus minutoides

Effect of sex chromosomes on mammalian behaviour: a case study in pygmy mice

Recommended by and based on reviews by Marion Anne-Lise Picard, Caroline Hu and 1 anonymous reviewer

In mammals, it is well documented that sexual dimorphism and in particular sex differences in behaviour are fine-tuned by gonadal hormonal profiles. For example, in lemurs, where female social dominance is common, the level of testosterone in females is unusually high compared to that of other primate females (Petty and Drea 2015). 

Recent studies however suggest that gonadal hormones might not be the only biological factor involved in establishing sexual dimorphism, sex chromosomes might also play a role. The four core genotype (FCG) model and other similar systems allowing to decouple phenotypic and genotypic sex in mice have provided very convincing evidence of such a role (Gatewood et al. 2006; Arnold and Chen 2009; Arnold 2020a, 2020b). This however is a new field of research and the role of sex chromosomes in establishing sexually dimorphic behaviours has not been studied very much yet. Moreover, the FCG model has some limits. Sry, the male determinant gene on the mammalian Y chromosome might be involved in some sex differences in neuroanatomy, but Sry is always associated with maleness in the FCG model, and this potential role of Sry cannot be studied using this system.

Heitzmann et al. have used a natural system to approach these questions. They worked on the African Pygmy mouse, Mus minutoides, in which a modified X chromosome called X* can feminize X*Y individuals, which offers a great opportunity for elegant experiments on the effects of sex chromosomes versus hormones on behaviour. They focused on maternal care and compared pup retrieval, nest quality, and mother-pup interactions in XX, X*X and X*Y females. They found that X*Y females are significantly better at retrieving pups than other females. They are also much more aggressive towards the fathers than other females, preventing paternal care. They build nests of poorer quality but have similar interactions with pups compared to other females. Importantly, no significant differences were found between XX and X*X females for these traits, which points to an effect of the Y chromosome in explaining the differences between X*Y and other females (XX, X*X). Also, another work from the same group showed similar gonadal hormone levels in all the females (Veyrunes et al. 2022). 

Heitzmann et al. made a number of predictions based on what is known about the neuroanatomy of rodents which might explain such behaviours. Using cytology, they looked for differences in neuron numbers in the hypothalamus involved in the oxytocin, vasopressin and dopaminergic pathways in XX, X*X and X*Y females, but could not find any significant effects. However, this part of their work relied on very small sample sizes and they used virgin females instead of mothers for ethical reasons, which greatly limited the analysis. 

Interestingly, X*Y females have a higher reproductive performance than XX and X*X ones, which compensate for the cost of producing unviable YY embryos and certainly contribute to maintaining a high frequency of X* in many African pygmy mice populations (Saunders et al. 2014, 2022). X*Y females are probably solitary mothers contrary to other females, and Heitzmann et al. have uncovered a divergent female strategy in this species. Their work points out the role of sex chromosomes in establishing sex differences in behaviours. 


Arnold AP (2020a) Sexual differentiation of brain and other tissues: Five questions for the next 50 years. Hormones and Behavior, 120, 104691.

Arnold AP (2020b) Four Core Genotypes and XY* mouse models: Update on impact on SABV research. Neuroscience & Biobehavioral Reviews, 119, 1–8.

Arnold AP, Chen X (2009) What does the “four core genotypes” mouse model tell us about sex differences in the brain and other tissues? Frontiers in Neuroendocrinology, 30, 1–9.

Gatewood JD, Wills A, Shetty S, Xu J, Arnold AP, Burgoyne PS, Rissman EF (2006) Sex Chromosome Complement and Gonadal Sex Influence Aggressive and Parental Behaviors in Mice. Journal of Neuroscience, 26, 2335–2342.

Heitzmann LD, Challe M, Perez J, Castell L, Galibert E, Martin A, Valjent E, Veyrunes F (2022) Genotypic sex shapes maternal care in the African Pygmy mouse, Mus minutoides. bioRxiv, 2022.04.05.487174, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

Petty JMA, Drea CM (2015) Female rule in lemurs is ancestral and hormonally mediated. Scientific Reports, 5, 9631.

Saunders PA, Perez J, Rahmoun M, Ronce O, Crochet P-A, Veyrunes F (2014) Xy Females Do Better Than the Xx in the African Pygmy Mouse, Mus Minutoides. Evolution, 68, 2119–2127.

Saunders PA, Perez J, Ronce O, Veyrunes F (2022) Multiple sex chromosome drivers in a mammal with three sex chromosomes. Current Biology, 32, 2001-2010.e3.

Veyrunes F, Perez J, Heitzmann L, Saunders PA, Givalois L (2022) Separating the effects of sex hormones and sex chromosomes on behavior in the African pygmy mouse Mus minutoides, a species with XY female sex reversal. bioRxiv, 2022.07.11.499546.

24 Oct 2022
article picture

Evolutionary responses of energy metabolism, development, and reproduction to artificial selection for increasing heat tolerance in Drosophila subobscura

The other side of the evolution of heat tolerance: correlated responses in metabolism and life-history traits

Recommended by and based on reviews by Marija Savić Veselinović and 1 anonymous reviewer

Understanding how species respond to environmental changes is becoming increasingly important in order to predict the future of biodiversity and species distributions under current global warming conditions (Rezende 2020; Bennett et al 2021). Two key factors to take into account in these predictions are the tolerance of organisms to heat stress and subsequently how they adapt to increasingly warmer temperatures. Coupled with this, one important factor that is often overlooked when addressing the evolution of thermal tolerance, is the correlated responses in traits that are important to fitness, such as life histories, behavior and the underlying metabolic processes.

The rate and intensity of the thermal stress are expected to be major factors in shaping the evolution of heat tolerance and correlated responses in other traits. For instance, lower rates of thermal stress are predicted to select for individuals with a slower metabolism (Santos et al 2012), whereas low metabolism is expected to lead to a lower reproductive rate (Dammhahn et al 2018). To quantify the importance of the rate and intensity of thermal stress on the evolutionary response of heat tolerance and correlated response in behavior, Mesas et al (2021) performed experimental evolution in Drosophila subobscura using selective regimes with slow or fast ramping protocols. Whereas both regimes showed increased heat tolerance with similar evolutionary rates, the correlated responses in thermal performance curves for locomotor behavior differed between selection regimes. These findings suggest that thermal rate and intensity may shape the evolution of correlated responses in other traits, urging the need to understand possible correlated responses at relevant levels such as life history and metabolism. 

In the present contribution, Mesas and Castañeda (2022) investigate whether the disparity in thermal performance curves observed in the previous experiment (Mesas et al 2021) could be explained by differences in metabolic energy production and consumption, and how this correlated with the reproductive output (fecundity and viability). Overall, the authors show some evidence for lowered enzyme activity and increased performance in life-history traits, particularly for the slow-ramping selected flies. Specifically, the authors observe a reduction in glucose metabolism and increased viability when evolving under slow ramping stress. Interestingly, both regimes show a general increase in fecundity, suggesting that adaptation to these higher temperatures is not costly (for reproduction) in the ancestral environment. The evidence for a somewhat lower metabolism in the slow-ramping lines suggests the evolution of a slow “pace of life”. The “pace of life” concept tries to bridge variation across several levels namely metabolism, physiology, behavior and life history, with low “pace of life” organisms presenting lower metabolic rates, later reproduction and higher longevity than fast “pace of life” organisms (Dammhahn et al 2018, Tuzun & Stocks 2022).  As the authors state there is not a clear-cut association with the expectations of the pace of life hypothesis since there was evidence for increased reproductive output under both selection intensity regimes. This suggests that, given sufficient trait genetic variance, positively correlated responses may emerge during some stages of thermal evolution. As fecundity estimates in this study were focussed on early life, the possibility of a decrease in the cumulative reproductive output of the selected flies, even under benign conditions, cannot be excluded. This would help explain the apparent paradox of increased fecundity in selected lines. In this context, it would also be interesting to explore the variation in reproductive output at different temperatures, i.e to obtain thermal performance curves for life histories. 

Mesas and Castañeda (2022) raise important questions to pursue in the future and contribute to the growing evidence that, in order to predict the distribution of ectothermic species under current global warming conditions, we need to expand beyond determining the physiological thermal limits of each organism (Parratt et al 2021). Ultimately, integrating metabolic, life-history and behavioral changes during evolution under different thermal stresses within a coherent framework is key to developing better predictions of temperature effects on natural populations.  


Bennett, J.M., Sunday, J., Calosi, P. et al. The evolution of critical thermal limits of life on Earth. Nat Commun 12, 1198 (2021).

Dammhahn, M., Dingemanse, N.J., Niemelä, P.T. et al. Pace-of-life syndromes: a framework for the adaptive integration of behaviour, physiology and life history. Behav Ecol Sociobiol 72, 62 (2018).

Mesas, A,  Jaramillo, A,  Castañeda, LE.  Experimental evolution on heat tolerance and thermal performance curves under contrasting thermal selection in Drosophila subobscura. J Evol Biol  34, 767– 778 (2021).

Mesas, A, Castañeda, LE Evolutionary responses of energy metabolism, development, and reproduction to artificial selection for increasing heat tolerance in Drosophila subobscura. bioRxiv, 2022.02.03.479001, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

Parratt, S.R., Walsh, B.S., Metelmann, S. et al. Temperatures that sterilize males better match global species distributions than lethal temperatures. Nat. Clim. Chang. 11, 481–484 (2021).

Santos, M, Castañeda, LE, Rezende, EL Keeping pace with climate change: what is wrong with the evolutionary potential of upper thermal limits? Ecology and evolution, 2(11), 2866-2880 (2012).

Tüzün, N, Stoks, R. A fast pace-of-life is traded off against a high thermal performance. Proceedings of the Royal Society B, 289(1972), 20212414 (2022).

Rezende, EL, Bozinovic, F, Szilágyi, A, Santos, M. Predicting temperature mortality and selection in natural Drosophila populations. Science, 369(6508), 1242-1245  (2020).

11 Oct 2022
article picture

The Eukaryotic Last Common Ancestor Was Bifunctional for Hopanoid and Sterol Production

Gene family analysis suggests new evolutionary scenario for sterol and hopanoid biomarkers

Recommended by based on reviews by Samuel Abalde, Denis Baurain and Jose Ramon Pardos-Blas

Sterols and hopanoids are sometimes used as biomarkers to infer the origin of certain groups of organisms. Traditionally, hopanoid-derived products in ancient rocks have been considered to indicate the presence of bacteria, whereas sterol derivatives have been considered to be exclusive to eukaryotes. However, a closer look at the topic reveals a rather complex distribution of either compound in both bacteria and eukaryotes. (1). The known biosynthetic pathways for sterols and hopanoids are similar but diverge at a critical step where two different enzymes are used: squalene-hopene cyclase (SHC) and oxidosqualene cyclase (OSC), the latter requiring oxygen. These two enzymes belong to the same gene family, whose complex evolutionary history is difficult to reconcile with the known species phylogeny.

In this study (2), Dr. Warren R. Francis revisits the evolution of this gene family using an extended dataset with a broader taxonomic representation. In contrast to the traditional representation of the tree rooted between SHC and OSC paralogs (i.e., based on function), the author proposes that rooting the tree within bacterial SHCs and assuming a secondary origin of OSC is more parsimonious. This postulates SHC to be the ancestral function –retained in many extant bacteria and some eukaryotes– and OSC to have emerged later within bacteria –currently being mostly present in eukaryotes–. The reconstructed evolutionary history is arguably complex and can only be reconciled with the species' phylogeny by invoking many secondary losses. These losses are considered likely because many extant species acquire sterols and hopanoids by diet and lack one or both enzymes. Some cases of recent horizontal gene transfer are also proposed.

In contrast to the dichotomy between bacterial SHCs and eukaryote OSCs, the new proposed scenario suggests that the eukaryote ancestor likely inherited both enzymes from bacteria and thus could be able to synthesize both sterols and hopanoids. Under this hypothesis, not only bacteria but also eukaryotes could be responsible for the hopane found in old rocks. This agrees with eukaryote fossils dating back to more than 1 billion years ago (3). Also, the observed increase of sterane levels in rocks ~600-700 million years old cannot be associated with the origin of eukaryotes, which is a much older event, but could rather reflect changes in atmospheric oxygen levels because oxygen is required for the synthesis of sterols by OSC.


1. Santana-Molina C, Rivas-Marin E, Rojas AM, Devos DP (2020) Origin and Evolution of Polycyclic Triterpene Synthesis. Molecular Biology and Evolution, 37, 1925–1941.

2. Francis WR (2022) The Eukaryotic Last Common Ancestor Was Bifunctional for Hopanoid and Sterol Production. Preprints, 2020040186, ver. 5 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

3. Butterfield NJ (2000) Bangiomorpha pubescens n. gen., n. sp.: implications for the evolution of sex, multicellularity, and the Mesoproterozoic/Neoproterozoic radiation of eukaryotes. Paleobiology, 26, 386–404.<0386:BPNGNS>2.0.CO;2

06 Oct 2022
article picture

Evolution of sperm morphology in a crustacean genus with fertilization inside an open brood pouch.

Evolution of sperm morphology in Daphnia within a phyologenetic context

Recommended by based on reviews by Renate Matzke-Karasz and 1 anonymous reviewer

In this study sperm morphology is studied in 15 Daphnia species and the morphological data are mapped on a Daphnia phylogeny. The authors found that despite the internal fertilization mode, Daphnia have among the smallest sperm recorded, as would be expected with external fertilization. The authors also conclude that increase in sperm length has evolved twice, that sperm encapsulation has been lost in a clade, and that this clade has very polymorphic sperm with long, and often numerous, filopodia.

Daphnia is an interesting model to study sperm morphology because the biology of sexual reproduction is often ignored in (cyclical) parthenogenetic species. Daphnia is part of the very diverse and successful group of cladocerans with cyclical parthenogenetic reproduction. The success of this reproduction mode is reflected in the known 620 species that radiated within this order, this is more than half of the known Branchiopod species diversity and the estimated number of cladoceran species is even two to four times higher (Forró et al. 2008). Looking at this particular model with a good phylogeny and some particularity in the mode of fertilization/reproduction, has thus a large value. Most Daphnia species are cyclical parthenogenetic and switch between sexual and asexual reproduction depending on the environmental conditions. Within the genus Daphnia, evolution to obligate asexuality has evolved in at least four independent occasions by three different mechanisms: (i) obligate parthenogenesis through hybridisation with or without polyploidy, (ii) asexuality has been acquired de novo in some populations and (iii) in certain lineages females reproduce by obligate parthenogenesis, whereas the clonally propagated males produce functional haploid sperm that allows them to breed with sexual females of normal cyclically parthenogenetic lineages (more on this in Decaestecker et al. 2009).

This study is made in the context of a body of research on the evolution of one of the most fundamental and taxonomically diverse cell types. There is surprisingly little known about the adaptive value underlying their morphology because it is very difficult to test this experimentally.  Studying sperm morphology across species is interesting to study evolution itself because it is a "simple trait". As the authors state: The understanding of the adaptive value of sperm morphology, such as length and shape, remains largely incomplete (Lüpold & Pitnick, 2018). Based on phylogenetic analyses across the animal kingdom, the general rule seems to be that fertilization mode (i.e. whether eggs are fertilized within or outside the female) is a key predictor of sperm length (Kahrl et al., 2021). There is a trade-off between sperm number and length (Immler et al., 2011). This study reports on one of the smallest sperm recorded despite the fertilization being internal. The brood pouch in Daphnia is an interesting particularity as fertilisation occurs internally, but it is not disconnected from the environment. It is also remarkable that there are two independent evolution lines of sperm size in this group. It suggests that those traits have an adaptive value. 


Decaestecker E, De Meester L, Mergeay J (2009) Cyclical Parthenogenesis in Daphnia: Sexual Versus Asexual Reproduction. In: Lost Sex: The Evolutionary Biology of Parthenogenesis (eds Schön I, Martens K, Dijk P), pp. 295–316. Springer Netherlands, Dordrecht.

Duneau David, Möst M, Ebert D (2022) Evolution of sperm morphology in a crustacean genus with fertilization inside an open brood pouch. bioRxiv, 2020.01.31.929414, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

Forró L, Korovchinsky NM, Kotov AA, Petrusek A (2008) Global diversity of cladocerans (Cladocera; Crustacea) in freshwater. Hydrobiologia, 595, 177–184.

Immler S, Pitnick S, Parker GA, Durrant KL, Lüpold S, Calhim S, Birkhead TR (2011) Resolving variation in the reproductive tradeoff between sperm size and number. Proceedings of the National Academy of Sciences, 108, 5325–5330.

Kahrl AF, Snook RR, Fitzpatrick JL (2021) Fertilization mode drives sperm length evolution across the animal tree of life. Nature Ecology & Evolution, 5, 1153–1164.

Lüpold S, Pitnick S (2018) Sperm form and function: what do we know about the role of sexual selection? Reproduction, 155, R229–R243.

05 Oct 2022
article picture

Do closely related species interact with similar partners? Testing for phylogenetic signal in bipartite interaction networks

Testing for phylogenetic signal in species interaction networks

Recommended by based on reviews by Joaquin Calatayud and Thomas Guillerme

Species are immersed within communities in which they interact mutualistically, as in pollination or seed dispersal, or nonreciprocally, such as in predation or parasitism, with other species and these interactions play a paramount role in shaping biodiversity (Bascompte and Jordano 2013). Researchers have become increasingly interested in the processes that shape these interactions and how these influence community structure and responses to disturbances. Species interactions are often described using bipartite interaction networks and one important question is how the evolutionary history of the species involved influences the network, including whether there is phylogenetic signal in interactions, in other words whether closely related species interact with other closely related species (Bascompte and Jordano 2013, Perez-Lamarque et al. 2022). To address this question different approaches, correlative and model-based, have been developed to test for phylogenetic signal in interactions, although comparative analyses of the performance of these different metrics are lacking. In their article Perez-Lamarque et al. (2022) set out to test the statistical performance of two widely-used methods, Mantel tests and Phylogenetic Bipartite Linear Models (PBLM; Ives and Godfray 2006) using simulations. Phylogenetic signal is measured as the degree to which distance to the nearest common ancestor predicts the observed similarity in trait values among species. In species interaction networks, the data are actually the between-species dissimilarity among interacting species (Perez-Lamarque et al. 2022), and typical approaches to test for phylogenetic signal cannot be used. However, the Mantel test provides a useful means of analyzing the correlation between two distance matrices, the between-species phylogenetic distance and the between-species dissimilarity in interactions. The PBLM approach, on the other hand, assumes that interactions between species are influenced by unobserved traits that evolve along the phylogenies following a given phenotypic evolution model and the parameters of this model are interpreted in terms of phylogenetic signal (Ives and Godfray 2006). Perez-Lamarque et al (2022) found that the model-based PBLM approach has a high type-I error rate, in other words it often detected phylogenetic signal when there was none. The simple Mantel test was found to present a low type-I error rate and moderate statistical power. However, it tended to overestimate the degree to which species interact with dissimilar partners. In addition to the aforementioned analyses, the authors also tested whether the simple Mantel test was able to detect phylogenetic signal in interactions among species within a given clade in the phylogeny, as phylogenetic signal in species interactions may be localized within specific clades. The article concludes with general guidelines for users wishing to test phylogenetic signal in their interaction networks and illustrates them with an example of an orchid-mycorrhizal fungus network from the oceanic island of La Réunion (Martos et al 2012). This broadly accessible article provides a valuable analysis of the performance of tests of phylogenetic signal in interaction networks enabling users to make informed choices of the analytical methods they wish to employ, and provide useful and detailed guidelines. Therefore, the work should be of broad interest to researchers studying species interactions.  


Bascompte J, Jordano P (2013) Mutualistic Networks. Princeton University Press.

Ives AR, Godfray HCJ (2006) Phylogenetic Analysis of Trophic Associations. The American Naturalist, 168, E1–E14.

Martos F, Munoz F, Pailler T, Kottke I, Gonneau C, Selosse M-A (2012) The role of epiphytism in architecture and evolutionary constraint within mycorrhizal networks of tropical orchids. Molecular Ecology, 21, 5098–5109.

Perez-Lamarque B, Maliet O, Pichon B, Selosse M-A, Martos F, Morlon H (2022) Do closely related species interact with similar partners? Testing for phylogenetic signal in bipartite interaction networks. bioRxiv, 2021.08.30.458192, ver. 6 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

29 Sep 2022
article picture

How many sirtuin genes are out there? evolution of sirtuin genes in vertebrates with a description of a new family member

Making sense of vertebrate sirtuin genes

Recommended by based on reviews by Filipe Castro, Nicolas Leurs and 1 anonymous reviewer

Sirtuin proteins are class III histone deacetylases that are involved in a variety of fundamental biological functions mostly related to aging. These proteins are located in different subcellular compartments and are associated with different biological functions such as metabolic regulation, stress response, and cell cycle control [1]. In mammals, the sirtuin gene family is composed of seven paralogs (SIRT1-7) grouped into four classes [2]. Due to their involvement in maintaining cell cycle integrity, sirtuins have been studied as a way to understand fundamental mechanisms governing longevity [1]. Indeed, the downregulation of sirtuin genes with aging seems to explain much of the pathophysiology that accumulates with aging [3]. Biomedical studies have thus explored the potential therapeutic implications of sirtuins [4] but whether they can effectively be used as molecular targets for the treatment of human diseases remains to be demonstrated [1]. Despite this biomedical interest and some phylogenetic analyses of sirtuin paralogs mostly conducted in mammals, a comprehensive evolutionary analysis of the sirtuin gene family at the scale of vertebrates was still lacking.

In this preprint, Opazo and collaborators [5] took advantage of the increasing availability of whole-genome sequences for species representing all main groups of vertebrates to unravel the evolution of the sirtuin gene family. To do so, they undertook a phylogenomic approach in its original sense aimed at improving functional predictions by evolutionary analysis [6] in order to inventory the full vertebrate sirtuin gene repertoire and reconstruct its precise duplication history. Harvesting genomic databases, they extracted all predicted sirtuin proteins and performed phylogenetic analyses based on probabilistic inference methods. Maximum likelihood and Bayesian analyses resulted in well-resolved and congruent phylogenetic trees dividing vertebrate sirtuin genes into three major clades. These analyses also revealed an additional eighth paralog that was previously overlooked because of its restricted phyletic distribution. This newly identified sirtuin family member (named SIRT8) was recovered with unambiguous statistical support as a sister-group to the SIRT3 clade. Comparative genomic analyses based on conserved gene synteny confirmed that SIRT8 was present in all sampled non-amniote vertebrate genomes (cartilaginous fish, bony fish, coelacanth, lungfish, and amphibians) except cyclostomes. SIRT8 has thus most likely been lost in the last common ancestor of amniotes (mammals, reptiles, and birds). Discovery of such previously unknown genes in vertebrates is not completely surprising given the plethora of high-quality genomes now available. However, this study highlights the importance of considering a broad taxonomic sampling to infer evolutionary patterns of gene families that have been mostly studied in mammals because of their potential importance for human biology.

Based on its phylogenetic position as closely related to SIRT3 within class I, it could be predicted that the newly identified SIRT8 paralog likely has a deacetylase activity and is probably located in mitochondria. To test these evolutionary predictions, Opazo and collaborators [5] conducted further bioinformatics analyses and functional experiments using the elephant shark (Callorhinchus milii) as a model species. RNAseq expression data were analyzed to determine tissue-specific transcription of sirtuin genes in vertebrates, including SIRT8 found to be mainly expressed in the ovary, which suggests a potential role in biological processes associated with reproduction. The elephant shark SIRT8 protein sequence was used with other vertebrates for comparative analyses of protein structure modeling and subcellular localization prediction both pointing to a probable mitochondrial localization. The protein localization and its function were further characterized by immunolocalization in transfected cells, and enzymatic and functional assays, which all confirmed the prediction that SIRT8 proteins are targeted to the mitochondria and have deacetylase activity. The extensive experimental efforts made in this study to shed light on the function of this newly discovered gene are both rare and highly commendable.

Overall, this work by Opazo and collaborators [5] provides a comprehensive phylogenomic study of the sirtuin gene family in vertebrates based on detailed evolutionary analyses using state-of-the-art phylogenetic reconstruction methods. It also illustrates the power of adopting an integrative comparative approach supplementing the reconstruction of the duplication history of the gene family with complementary functional experiments in order to elucidate the function of the newly discovered SIRT8 family member. These results provide a reference phylogenetic framework for the evolution of sirtuin genes and the further functional characterization of the eight vertebrate paralogs with potential relevance for understanding the cellular biology of aging and its associated diseases in human.


[1] Vassilopoulos A, Fritz KS, Petersen DR, Gius D (2011) The human sirtuin family: Evolutionary divergences and functions. Human Genomics, 5, 485.

[2] Yamamoto H, Schoonjans K, Auwerx J (2007) Sirtuin Functions in Health and Disease. Molecular Endocrinology, 21, 1745–1755.

[3] Morris BJ (2013) Seven sirtuins for seven deadly diseases ofaging. Free Radical Biology and Medicine, 56, 133–171.

[4] Bordo D Structure and Evolution of Human Sirtuins. Current Drug Targets, 14, 662–665.

[5] Opazo JC, Vandewege MW, Hoffmann FG, Zavala K, Meléndez C, Luchsinger C, Cavieres VA, Vargas-Chacoff L, Morera FJ, Burgos PV, Tapia-Rojas C, Mardones GA (2022) How many sirtuin genes are out there? evolution of sirtuin genes in vertebrates with a description of a new family member. bioRxiv, 2020.07.17.209510, ver. 5 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

[6] Eisen JA (1998) Phylogenomics: Improving Functional Predictions for Uncharacterized Genes by Evolutionary Analysis. Genome Research, 8, 163–167.

15 Sep 2022
article picture

Bimodal breeding phenology in the Parsley Frog Pelodytes punctatus as a bet-hedging strategy in an unpredictable environment despite strong priority effects

Spreading the risk of reproductive failure when the environment is unpredictable and ephemeral

Recommended by based on reviews by Thomas Haaland and Zoltan Radai

Many species breed in environments that are unpredictable, for instance in terms of the availability of resources needed to raise the offspring. Organisms might respond to such spatial and temporal unpredictability by adopting plastic responses to adjust their reproductive investment according to perceived cues of environmental quality. Some species such as the amphibians might also face the problem of ephemeral habitats, when the ponds where they breed have a chance of drying up before metamorphosis has occurred. In this case, maximizing long-term fitness might involve a strategy of spreading the risk, even though the reproductive success of a single reproductive bout might be lower. Understanding how animals (and plants) get adapted to stochastic environments is particularly crucial in the current context of rapid environmental changes.

In this article, Jourdan-Pineau et al. report the results of field surveys of the Parsley Frog (Pelodytes punctatus) in Southern France. This frog has peculiar breeding phenology with females breeding in autumn and spring. The authors provide quite an extensive amount of information on the reproductive success of eggs laid in each season and the possible ecological factors accounting for differences between seasons. Although the presence of interspecific competitors and predators does not seem to account for pond-specific reproductive success, the survival of tadpoles hatching from eggs laid in spring is severely impaired when tadpoles from the autumn cohort have managed to survive. This intraspecific competition takes the form of a “priority” effect where tadpoles from the autumn cohort outcompete the smaller larvae from the spring cohort. Given this strong priority effect, one might tentatively predict that females laying in spring should avoid ponds with tadpoles from the autumn cohort. Surprisingly, however, the authors did not find any evidence for such avoidance, which might indicate strong constraints on the availability of ponds where females might possibly lay.

Assuming that each female can indeed lay both in autumn and spring, how is this bimodal phenology maintained? Would not be worthier to allocate all the eggs to the autumn (or the spring) laying season? Eggs laid in autumn and spring have to face different environmental hazards, reducing their hatching success and the probability to produce metamorphs (for instance, tadpoles hatching from eggs laid in autumn have to overwinter which might be a particularly risky phase).             

Jourdan-Pineau and coworkers addressed this question by adapting a bet-hedging model that was initially developed to investigate the strategy of allocation into seed dormancy of annual plants (Cohen 1966) to the case of the bimodal phenology of the Parsley Frog. By feeding the model with the parameter values obtained from the field surveys, they found that the two breeding strategies (laying in autumn and in spring) can coexist as long as the probability of breeding success in the autumn cohort is between 20% and 80% (the range of values allowing the coexistence of a bimodal phenology shrinking a little bit when considering that frogs can reproduce 5 times during their lifespan instead of three times).

This paper provides a very nice illustration of the importance of combining approaches (here field monitoring to gather data that can be used to feed models) to understand the evolution of peculiar breeding strategies. Although future work should attempt to gather individual-based data (in addition to population data), this work shows that spreading the risk can be an adaptive strategy in environments characterized by strong stochastic variation.


Cohen D (1966) Optimizing reproduction in a randomly varying environment. Journal of Theoretical Biology, 12, 119–129.

Jourdan-Pineau H., Crochet P.-A., David P. (2022) Bimodal breeding phenology in the Parsley Frog Pelodytes punctatus as a bet-hedging strategy in an unpredictable environment despite strong priority effects. bioRxiv, 2022.02.24.481784, ver. 5 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

06 Sep 2022
article picture

Masculinization of the X-chromosome in aphid soma and gonads

Sex-biased gene expression is not tissue-specific in Pea Aphids

Recommended by and based on reviews by Ann Kathrin Huylmans and 1 anonymous reviewer

Sexual antagonism (SA), wherein the fitness interests of the sexes do not align, is inherent to organisms with two (or more) sexes.  SA leads to intra-locus sexual conflict, where an allele that confers higher fitness in one sex reduces fitness in the other [1, 2].  This situation leads to what has been referred to as "gender load", resulting from the segregation of SA alleles in the population.  Gender load can be reduced by the evolution of sex-specific (or sex-biased) gene expression.  A specific prediction is that gene-duplication can lead to sub- or neo-functionalization, in which case the two duplicates partition the function in the different sexes.  The conditions for invasion by a SA allele differ between sex-chromosomes and autosomes, leading to the prediction that (in XY or XO systems) the X should accumulate recessive male-favored alleles and dominant female-favored alleles; similar considerations apply in ZW systems ([3, but see 4].

Aphids present an interesting special case, for several reasons: they have XO sex-determination, and three distinct reproductive morphs (sexual females, parthenogenetic females, and males).  Previous theoretical work by the lead author predict that the X should be optimized for male function, which was borne out by whole-animal transcriptome analysis [5].  

Here [6], the authors extend that work to investigate “tissue”-specific (heads, legs and gonads), sex-specific gene expression.  They argue that, if intra-locus SA is the primary driver of sex-biased gene expression, it should be generally true in all tissues.  They set up as an alternative the possibility that sex-biased gene expression could also be driven by dosage compensation.  They cite references supporting their argument that "dosage compensation (could be) stronger in the brain", although the underlying motivation for that argument appears to be based on empirical evidence rather than theoretical predictions.      

At any rate, the results are clear: all tissues investigated show masculinization of the X.  Further, X-linked copies of gene duplicates were more frequently male-biased than duplicated autosomal genes or X-linked single-copy genes.

To sum up, this is a nice empirical study with clearly interpretable (and interpreted) results, the most obvious of which is the greater sex-biased expression in sexually-dimorphic tissues.  Unfortunately, as the authors emphasize, there is no general theory by which SA, variable dosage-compensation, and meiotic sex chromosome inactivation can be integrated in a predictive framework.  It is to be hoped that empirical studies such as this one will motivate deeper and more general theoretical investigations.


[1] Rice WR, Chippindale AK (2001) Intersexual ontogenetic conflict. Journal of Evolutionary Biology 14: 685-693.

[2] Bonduriansky R, Chenoweth SF (2009) Intralocus sexual conflict. Trends Ecol Evol 24: 280-288.

[3] Rice WR. (1984) Sex chromosomes and the evolution of sexual dimorphism. Evolution 38: 735-742.

[4] Fry JD (2010) The genomic location of sexually antagonistic variation: some cautionary comments. Evolution 64: 1510-1516.

[5] Jaquiéry J, Rispe C, Roze D, Legeai F, Le Trionnaire G, Stoeckel S, et al. (2013) Masculinization of the X Chromosome in the Pea Aphid. PLoS Genetics 9.

[6] Jaquiéry J, Simon J-C, Robin S, Richard G, Peccoud J, Boulain H, Legeai F, Tanguy S, Prunier-Leterme N, Le Trionnaire G (2022) Masculinization of the X-chromosome in aphid soma and gonads. bioRxiv, 2021.08.13.453080, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. 

02 Sep 2022
article picture

Introgression between highly divergent sea squirt genomes: an adaptive breakthrough?

A match made in the Anthropocene: human-mediated adaptive introgression across a speciation continuum

Recommended by based on reviews by Michael Westbury, Andrew Foote and Erin Calfee

The long-distance transport and introduction of new species by humans is increasingly leading divergent lineages to interact, and sometimes interbreed, even after thousands or millions of years of separation. It is thus of prime importance to understand the consequences of these contemporary admixture events on the evolutionary fitness of interacting organisms, and their ecological implications.

Ciona robusta and Ciona intestinalis are two species of sea squirts that diverged between 1.5 and 2 million years ago and recently came into contact again. This occurred through human-mediated introduction of C. robusta (native to the Northwest Pacific) into the range of C. intestinalis (the English channeled Northeast Atlantic). In this study, Fraïsse et al. (2022) follow up on earlier work by Le Moan et al. (2021), who had identified a long genomic hotspot of introgression of C. robusta ancestry segments in chromosome 5 of C. intestinalis. The hotspot bears suggestive evidence of positive selection and the authors aimed to investigate this further using fully phased whole-genome sequences.

The authors narrow down on the exact boundaries of the introgressed region, and make a compelling case that it has been the likely target of positive selection after introgression, using various complementary approaches based on patterns of population differentiation, haplotype structure and local levels of diversity in the region. Using extensive demographic modeling, they also show that the introgression event was likely recent (approximately 75 years ago), and distinct from other tracts in the C. intestinalis genome that are likely a product of more ancient episodes of interbreeding in the past 30,000 years. Narrowing down on the potential drivers of selection, the authors show that candidate SNPs in the region overlap with the cytochrome family 2 subfamily U gene - involved in the detoxification of exogenous compounds - potentially reflecting adaptation to chemicals encountered in the sea squirt's environment. There also appears to be copy number variation at the candidate SNPs, which provides clues into the adaptation mechanism in the region.

All reviewers agreed that the work carried out by the authors is elegant and the results are robustly supported and well presented. In a round of reviews, various clarifications of the manuscript were suggested by the reviewers, including on the quality of the newly generated sequencing data, and some suggestions for qualifications on the conclusions reached by the authors as well as changes in the figures to increase their clarity. The authors addressed the different concerns of the reviewers, and the new version is much improved. 

This study into human-mediated introgression and its consequences for adaptation is, in my view, both well thought-out and executed. I therefore provide an enthusiastic recommendation of this manuscript.


Fraïsse C, Le Moan A, Roux C, Dubois G, Daguin-Thiébaut C, Gagnaire P-A, Viard F and Bierne N (2022) Introgression between highly divergent sea squirt genomes: an adaptive breakthrough? bioRxiv, 2022.03.22.485319, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

Le Moan A, Roby C, Fraïsse C, Daguin-Thiébaut C, Bierne N, Viard F (2021) An introgression breakthrough left by an anthropogenic contact between two ascidians. Molecular Ecology, 30, 6718–6732.

24 Aug 2022
article picture

Density dependent environments can select for extremes of body size

A population biological modeling approach for life history and body size evolution

Recommended by based on reviews by Frédéric Guillaume and 2 anonymous reviewers

Body size evolution is a central theme in evolutionary biology. Particularly the question of when and how smaller body sizes can evolve continues to interest evolutionary ecologists, because most life history models, and the empirical evidence, document that large body size is favoured by natural and sexual selection in most (even small) organisms and environments at most times. How, then, can such a large range of body size and life history syndromes evolve and coexist in nature?

The paper by Coulson et al. lifts this question to the level of the population, a relatively novel approach using so-called integral projection (simulation) models (IPMs) (as opposed to individual-based or game theoretical models). As is well outlined by (anonymous) Reviewer 1, and following earlier papers spearheading this approach in other life history contexts, the authors use the well-known carrying capacity (K) of population biology as the ultimate fitness parameter to be maximized or optimized (rather than body size per se), to ultimately identify factors and conditions promoting the evolution of extreme body sizes in nature. They vary (individual or population) size-structured growth trajectories to observe age and size at maturity, surivorship and fecundity/fertility schedules upon evaluating K (see their Fig. 1). Importantly, trade-offs are introduced via density-dependence, either for adult reproduction or for juvenile survival, in two (of several conceivable) basic scenarios (see their Table 2). All other relevant standard life history variables (see their Table 1) are assumed density-independent, held constant or zero (as e.g. the heritability of body size).

The authors obtain evidence for disruptive selection on body size in both scenarios, with small size and a fast life history evolving below a threshold size at maturity (at the lowest K) and large size and a slow life history beyond this threshold (see their Fig. 2). Which strategy wins ultimately depends on the fitness benefits of delaying sexual maturity (at larger size and longer lifespan) at the adult stage relative to the preceeding juvenile mortality costs, in agreement with classic life history theory (Roff 1992, Stearns 1992). The modeling approach can be altered and refined to be applied to other key life history parameters and environments. These results can ultimately explain the evolution of smaller body sizes from large body sizes, or vice versa, and their corresponding life history syndromes, depending on the precise environmental circumstances.

All reviewers agreed that the approach taken is technically sound (as far as it could be evaluated), and that the results are interesting and worthy of publication. In a first round of reviews various clarifications of the manuscript were suggested by the reviewers. The new version was substantially changed by the authors in response, to the extent that it now is a quite different but much clearer paper with a clear message palatable for the general reader. The writing is now to the point, the paper's focus becomes clear in the Introduction, Methods & Results are much less technical, the Figures illustrative, and the descriptions and interpretations in the Discussion are easy to follow.

In general any reader may of course question the choice and realism of the scenarios and underlying assumptions chosen by the authors for simplicity and clarity, for instance no heritability of body size and no cost of reproduction (other than mortality). But this is always the case in modeling work, and the authors acknowledge and in fact suggest concrete extensions and expansions of their approach in the Discussion.


Coulson T., Felmy A., Potter T., Passoni G., Montgomery R.A., Gaillard J.-M., Hudson P.J., Travis J., Bassar R.D., Tuljapurkar S., Marshall D.J., Clegg S.M. (2022) Density-dependent environments can select for extremes of body size. bioRxiv, 2022.02.17.480952, ver. 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

11 Jul 2022
article picture

Mutualists construct the ecological conditions that trigger the transition from parasitism

Give them some space: how spatial structure affects the evolutionary transition towards mutualistic symbiosis

Recommended by based on reviews by Eva Kisdi and 3 anonymous reviewers

The evolution of mutualistic symbiosis is a puzzle that has fascinated evolutionary ecologist for quite a while. Data on transitions between symbiotic bacterial ways of life has evidenced shifts from mutualism towards parasitism and vice versa (Sachs et al., 2011), so there does not seem to be a strong determinism on those transitions. From the host’s perspective, mutualistic symbiosis implies at the very least some form of immune tolerance, which can be costly (e.g. Sorci, 2013). Empirical approaches thus raise very important questions: How can symbiosis turn from parasitism into mutualism when it seemingly needs such a strong alignment of selective pressures on both the host and the symbiont? And yet why is mutualistic symbiosis so widespread and so important to the evolution of macro-organisms (Margulis, 1998)?

While much of the theoretical literature on the evolution of symbiosis and mutualism has focused on either the stability of such relationships when non-mutualists can invade the host-symbiont system (e.g. Ferrière et al., 2007) or the effect of the mode of symbiont transmission on the evolutionary dynamics of mutualism (e.g. Genkai-Kato and Yamamura, 1999), the question remains whether and under which conditions parasitic symbiosis can turn into mutualism in the first place. Earlier results suggested that spatial demographic heterogeneity between host populations could be the leading determinant of evolution towards mutualism or parasitism (Hochberg et al., 2000). Here, Ledru et al. (2022) investigate this question in an innovative way by simulating host-symbiont evolutionary dynamics in a spatially explicit context. Their hypothesis is intuitive but its plausibility is difficult to gauge without a model: Does the evolution towards mutualism depend on the ability of the host and symbiont to evolve towards close-range dispersal in order to maintain clusters of efficient host-symbiont associations, thus outcompeting non-mutualists?

I strongly recommend reading this paper as the results obtained by the authors are very clear: competition strength and the cost of dispersal both affect the likelihood of the transition from parasitism to mutualism, and once mutualism has set in, symbiont trait values clearly segregate between highly dispersive parasites and philopatric mutualists. The demonstration of the plausibility of their hypothesis is accomplished with brio and thoroughness as the authors also examine the conditions under which the transition can be reversed, the impact of the spatial range of competition and the effect of mortality. Since high dispersal cost and strong, long-range competition appear to be the main factors driving the evolutionary transition towards mutualistic symbiosis, now is the time for empiricists to start investigating this question with spatial structure in mind.


Ferrière, R., Gauduchon, M. and Bronstein, J. L. (2007) Evolution and persistence of obligate mutualists and exploiters: competition for partners and evolutionary immunization. Ecology Letters, 10, 115-126.

Genkai-Kato, M. and Yamamura, N. (1999) Evolution of mutualistic symbiosis without vertical transmission. Theoretical Population Biology, 55, 309-323.

Hochberg, M. E., Gomulkiewicz, R., Holt, R. D. and Thompson, J. N. (2000) Weak sinks could cradle mutualistic symbioses - strong sources should harbour parasitic symbioses. Journal of Evolutionary Biology, 13, 213-222.

Ledru L, Garnier J, Rohr M, Noûs C and Ibanez S (2022) Mutualists construct the ecological conditions that trigger the transition from parasitism. bioRxiv, 2021.08.18.456759, ver. 5 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

Margulis, L. (1998) Symbiotic planet: a new look at evolution, Basic Books, Amherst.

Sachs, J. L., Skophammer, R. G. and Regus, J. U. (2011) Evolutionary transitions in bacterial symbiosis. Proceedings of the National Academy of Sciences, 108, 10800-10807.

Sorci, G. (2013) Immunity, resistance and tolerance in bird–parasite interactions. Parasite Immunology, 35, 350-361.

04 Jul 2022
article picture

A genomic assessment of the marine-speciation paradox within the toothed whale superfamily Delphinoidea

Reticulated evolution marks the rapid diversification of the Delphinoidae

Recommended by based on reviews by Christelle Fraïsse, Simon Henry Martin, Andrew Foote and 2 anonymous reviewers

Historically neglected or considered a rare aberration in animals under the biological species concept, interspecific hybridisation has by now been recognised to be taxonomically widespread, particularly in rapidly diversifying groups (Dagilis et al. 2021; Edelman & Mallet 2021; Mallet et al. 2016; Seehausen 2004). Yet the prevalence of introgressive hybridizations, its evolutionary significance, and its impact on species diversification remain a hot topic of research in evolutionary biology. The rapid increase in genomic resources now available for non-model species has significantly contributed to the detection of introgressive hybridization across taxa showing that reticulated evolution is far more common in the animal kingdom than historically considered. Yet, detecting it, quantifying its magnitude, and assessing its evolutionary significance remains a challenging endeavour with constantly evolving methodologies to better explore and exploit genomic data (Blair & Ané 2020; Degnan & Rosenberg 2009; Edelman & Mallet 2021; Hibbins & Hahn 2022).

In the marine realm, the dearth of geographic barriers and the large dispersal abilities of pelagic species like cetaceans have raised the questions of how populations and species can diverge and adapt to distinct ecological conditions in face of potentially large gene-flow, the so-called marine speciation paradox (Bierne et al. 2003). Contemporaneous hybridization among cetacean species has been widely documented in nature despite large phenotypic differences (Crossman et al. 2016). The historical prevalence of reticulated evolution, its evolutionary significance, and how it might have impacted the evolutionary history and diversification of the cetaceans have however remained elusive so far. Recent phylogenomic studies suggested that introgression has been prevalent in cetacean evolutionary history with instances reported among baleen whales (mysticetes) (Árnason et al. 2018) and among toothed whales (odontocetes), especially in the rapidly diversifying dolphins family of the Delphininae (Guo et al. 2021; Moura et al. 2020).

Analysing publicly available whole-genome data from nine cetacean species across three families of Delphinoidae – dolphins, porpoises, and monondontidae – using phylogenomics and demo-genetics approaches, Westbury and colleagues (2022) take a step further in documenting that evolution among these species has been far from a simple bifurcating tree. Instead, their study describes widespread occurrences of introgression among Delphinoidae, drawing a complex picture of reticulated evolutionary history. After describing major topology discordance in phylogenetic gene trees along the genome, the authors use a panel of approaches to disentangle introgression from incomplete lineage sorting (ILS), the two most common causes of tree topology discordances (Hibbins & Hahn 2022). Applying popular tests that separate introgression from ILS, such as the Patterson’s D (a.k.a. ABBA-BABA) test (Durand et al. 2011; Green et al. 2010), QuIBL (Edelman et al. 2019), and D-FOIL (Pease & Hahn 2015), the authors report that signals of introgression are present in the genomes of most (if not all) the cetacean species included in their study. However, this picture needs to be nuanced. Most introgression signals seem to echo old introgression events that occurred primarily among ancestors. This is suggested by the differential signals of topology discordance along the genome when considering sliding windows along the genome of varying sizes (50kb, 100kb, and 1Mb), and by patterns of excess derived allele sharing along branches of the species tree, as captured by the f-branch test (Malinsky et al. 2021; Malinsky et al. 2018). The authors further investigated the dynamic of cessation of gene flow (and/or ILS) between species using the F1 hybrid PSMC (or hPSMC) approach (Cahill et al. 2016). By estimating the cross-coalescent rates (CRR) between species pairs with time in light of previously estimated species divergence times (McGowen et al. 2020), the authors report that gene flow (and/or ILS) most likely has stopped by now among most species, but it may have lasted for more than half of the time since the species split from each other. According to the author, this result may reflect the slow process by which reproductive isolation would have evolved between cetacean lineages, and that species isolation was marked by significant introgression events.

Now, while the present study provides a good overview of how complex is the reticulated evolutionary history of the Delphinoidae, getting a complete picture will require overcoming a few important limitations. The first ones are methodological and related to the phylogenomic analyses. Given the sampling design with one diploid genome per species, the authors could not phase the data into the parental haplotypes, but instead relied on a majority consensus creating mosaic haploidized genomes representing a mixture between the two parental copies. Moreover, by using large genomic windows (≥50kb) that likely span multiple independent loci, phylogenetic analyses in windows encompassed distinct phylogenetic signals, potentially leading to bias and inaccuracy in the inferences. Thawornwattana et al (2018) previously showed that this “concatenation approach”  could significantly impact phylogenetic inferences. They proposed instead to use loci small enough to minimise the risk of intra-locus recombination and to consider them in blocks of non-recombining loci along the genome in order to conduct phylogenetic analysed, ideally under the multi-species coalescent (MSC) that can account for ILS (e.g. BPP; Flouri et al. 2018; Jiao et al. 2020; Yang 2015). Such an approach applied to the diversification of the Delphinidae may reveal substantial changes compared to the currently admitted species tree.

Inaccuracy in the species tree estimation may have a major impact on the introgression analyses conducted in this study since the species tree and branching order must be supplied in the introgression analyses to properly disentangle introgression from ILS. Here, the authors rely on the tree topology that was previously estimated in McGowen et al. (2020), which they also recovered using their consensus estimation from ASTRAL-III (Zhang et al. 2018). While the methodologies accounted to a certain extent for ILS, albeit with potential bias induced by the concatenation approach, they ignore the presumably large amount of introgression among species during the diversification process. Estimating species branching order while ignoring introgression can lead to major bias in the phylogenetic inference and can lead to incorrect topologies. Even if these MSC-based methods account for ILS, inferences can become very inaccurate or even break down as gene flow increases (see for ex. Jiao et al. 2020; Müller et al. in press; Solís-Lemus et al. 2016). Dedicated approaches have been developed to model explicitly introgression together with ILS to estimate phylogenetic networks (Blair & Ané 2020; Rabier et al. 2021) or in isolation-with-migration model (Müller et al. in press; Wang et al. 2020). Future studies revisiting the reticulated evolutionary history of the Delphinoidae with such approaches may not only precise the species branching order, but also deliver a finer view of the magnitude and prevalence of introgression during the evolutionary history of these species.

A final part of Westbury et al. (2022)'s study set out to test whether historical periods of low abundance could have facilitated hybridization among Delphinoidae species. During these periods of low abundance, species may encounter only a limited number of conspecifics and may consider individuals from other species as suitable mating partners, leading to hybridisation (Crossman et al. 2016; Edwards et al. 2011; Westbury et al. 2019). The authors tested this hypothesis by considering genome-wide genetic diversity (or heterozygosity) as a proxy of historical effective population size (Ne), itself as a proxy of the evolution of census size with time. They also try to link historical Ne variation (from PSMC, Li & Durbin 2011) with their estimated time to cessation of gene flow or ILS (from the CRR of hPSMC). However, no straightforward relationship was found between the genetic diversity and the propensity of species to hybridize, nor was there any clear link between Ne variation through time and the cessation of gene flow or ILS. Such a lack of relationship may not come as a surprise, since the determinants of genome-wide genetic diversity and its variation through evolutionary time-scale are far more diverse and complex than just a direct link with hybridization, introgression, or even with the census population size. In fact, genetic diversity results from the balance between all the evolutionary processes at play in the species' evolutionary history (see the review of Ellegren & Galtier 2016). Other important factors can strongly impact genetic diversity, including demography and structure, but also linked selection (Boitard et al. 2022; Buffalo 2021; Ellegren & Galtier 2016). 

All in all, Westbury and coll. (2022) present here an interesting study providing an additional step towards resolving and understanding the complex evolutionary history of the Delphinoidae, and shedding light on the importance of introgression during the diversification of these cetacean species. Prospective work improving upon the taxonomic sampling, with additional genomic data for each species, considered with dedicated approaches tailored at estimating species tree or network while accounting for ILS and introgression will be key for refining the picture depicted in this study. Down the road, altogether these studies will contribute to assessing the evolutionary significance of introgression on the diversification of Delphinoides, and more generally on the diversification of cetacean species, which still remain an open and exciting perspective. 


Árnason Ú, Lammers F, Kumar V, Nilsson MA, Janke A (2018) Whole-genome sequencing of the blue whale and other rorquals finds signatures for introgressive gene flow. Science Advances 4, eaap9873.

Bierne N, Bonhomme F, David P (2003) Habitat preference and the marine-speciation paradox. Proceedings of the Royal Society of London. Series B: Biological Sciences 270, 1399-1406.

Blair C, Ané C (2020) Phylogenetic Trees and Networks Can Serve as Powerful and Complementary Approaches for Analysis of Genomic Data. Systematic Biology 69, 593-601.

Boitard S, Arredondo A, Chikhi L, Mazet O (2022) Heterogeneity in effective size across the genome: effects on the inverse instantaneous coalescence rate (IICR) and implications for demographic inference under linked selection. Genetics 220, iyac008.

Buffalo V (2021) Quantifying the relationship between genetic diversity and population size suggests natural selection cannot explain Lewontin's Paradox. e-Life 10, e67509.

Cahill JA, Soares AE, Green RE, Shapiro B (2016) Inferring species divergence times using pairwise sequential Markovian coalescent modelling and low-coverage genomic data. Philos Trans R Soc Lond B Biol Sci 371, 20150138.

Crossman CA, Taylor EB, Barrett‐Lennard LG (2016) Hybridization in the Cetacea: widespread occurrence and associated morphological, behavioral, and ecological factors. Ecology and Evolution 6, 1293-1303.

Dagilis AJ, Peede D, Coughlan JM, Jofre GI, D’Agostino ERR, Mavengere H, Tate AD, Matute DR (2021) 15 years of introgression studies: quantifying gene flow across Eukaryotes. biorXiv, 2021.1106.1115.448399.

Degnan JH, Rosenberg NA (2009) Gene tree discordance, phylogenetic inference and the multispecies coalescent. Trends Ecol Evol 24, 332-340.

Durand EY, Patterson N, Reich D, Slatkin M (2011) Testing for ancient admixture between closely related populations. Mol Biol Evol 28, 2239-2252.

Edelman NB, Frandsen PB, Miyagi M, Clavijo B, Davey J, Dikow RB, Garcia-Accinelli G, Van Belleghem SM, Patterson N, Neafsey DE, Challis R, Kumar S, Moreira GRP, Salazar C, Chouteau M, Counterman BA, Papa R, Blaxter M, Reed RD, Dasmahapatra KK, Kronforst M, Joron M, Jiggins CD, McMillan WO, Di Palma F, Blumberg AJ, Wakeley J, Jaffe D, Mallet J (2019) Genomic architecture and introgression shape a butterfly radiation. Science 366, 594-599.

Edelman NB, Mallet J (2021) Prevalence and Adaptive Impact of Introgression. Annual Review of Genetics 55, 265-283.

Edwards CJ, Suchard MA, Lemey P, Welch JJ, Barnes I, Fulton TL, Barnett R, O'Connell TC, Coxon P, Monaghan N, Valdiosera CE, Lorenzen ED, Willerslev E, Baryshnikov GF, Rambaut A, Thomas MG, Bradley DG, Shapiro B (2011) Ancient hybridization and an Irish origin for the modern polar bear matriline. Curr Biol 21, 1251-1258.

Ellegren H, Galtier N (2016) Determinants of genetic diversity. Nat Rev Genet 17, 422-433.

Flouri T, Jiao X, Rannala B, Yang Z (2018) Species Tree Inference with BPP Using Genomic Sequences and the Multispecies Coalescent. Mol Biol Evol 35, 2585-2593.

Green RE, Krause J, Briggs AW, Maricic T, Stenzel U, Kircher M, Patterson N, Li H, Zhai W, Fritz MH, Hansen NF, Durand EY, Malaspinas AS, Jensen JD, Marques-Bonet T, Alkan C, Prufer K, Meyer M, Burbano HA, Good JM, Schultz R, Aximu-Petri A, Butthof A, Hober B, Hoffner B, Siegemund M, Weihmann A, Nusbaum C, Lander ES, Russ C, Novod N, Affourtit J, Egholm M, Verna C, Rudan P, Brajkovic D, Kucan Z, Gusic I, Doronichev VB, Golovanova LV, Lalueza-Fox C, de la Rasilla M, Fortea J, Rosas A, Schmitz RW, Johnson PLF, Eichler EE, Falush D, Birney E, Mullikin JC, Slatkin M, Nielsen R, Kelso J, Lachmann M, Reich D, Paabo S (2010) A draft sequence of the Neandertal genome. Science 328, 710-722.

Guo W, Sun D, Cao Y, Xiao L, Huang X, Ren W, Xu S, Yang G (2021) Extensive Interspecific Gene Flow Shaped Complex Evolutionary History and Underestimated Species Diversity in Rapidly Radiated Dolphins. Journal of Mammalian Evolution 29, 353-367.

Hibbins MS, Hahn MW (2022) Phylogenomic approaches to detecting and characterizing introgression. Genetics 220, iyab173.

Jiao X, Flouri T, Rannala B, Yang Z (2020) The Impact of Cross-Species Gene Flow on Species Tree Estimation. Syst Biol 69, 830-847.

Li H, Durbin R (2011) Inference of human population history from individual whole-genome sequences. Nature 475, 493-496.

Malinsky M, Matschiner M, Svardal H (2021) Dsuite - Fast D-statistics and related admixture evidence from VCF files. Mol Ecol Resour 21, 584-595.

Malinsky M, Svardal H, Tyers AM, Miska EA, Genner MJ, Turner GF, Durbin R (2018) Whole-genome sequences of Malawi cichlids reveal multiple radiations interconnected by gene flow. Nature Ecology & Evolution 2, 1940-1955.

Mallet J, Besansky N, Hahn MW (2016) How reticulated are species? Bioessays 38, 140-149. 

McGowen MR, Tsagkogeorga G, Alvarez-Carretero S, Dos Reis M, Struebig M, Deaville R, Jepson PD, Jarman S, Polanowski A, Morin PA, Rossiter SJ (2020) Phylogenomic Resolution of the Cetacean Tree of Life Using Target Sequence Capture. Syst Biol 69, 479-501.

Moura AE, Shreves K, Pilot M, Andrews KR, Moore DM, Kishida T, Möller L, Natoli A, Gaspari S, McGowen M, Chen I, Gray H, Gore M, Culloch RM, Kiani MS, Willson MS, Bulushi A, Collins T, Baldwin R, Willson A, Minton G, Ponnampalam L, Hoelzel AR (2020) Phylogenomics of the genus Tursiops and closely related Delphininae reveals extensive reticulation among lineages and provides inference about eco-evolutionary drivers. Molecular Phylogenetics and Evolution 146,107047.

Müller NF, Ogilvie HA, Zhang C, Fontaine MC, Amaya-Romero JE, Drummond AJ, Stadler T (in press) Joint inference of species histories and gene flow. Syst Biol.

Pease JB, Hahn MW (2015) Detection and Polarization of Introgression in a Five-Taxon Phylogeny. Syst Biol 64, 651-662.

Rabier CE, Berry V, Stoltz M, Santos JD, Wang W, Glaszmann JC, Pardi F, Scornavacca C (2021) On the inference of complex phylogenetic networks by Markov Chain Monte-Carlo. PLoS Comput Biol 17, e1008380.

Seehausen O (2004) Hybridization and adaptive radiation. Trends Ecol Evol 19, 198-207.

Solís-Lemus C, Yang M, Ané C (2016) Inconsistency of Species Tree Methods under Gene Flow. Syst Biol 65, 843-851.

Thawornwattana Y, Dalquen D, Yang Z, Tamura K (2018) Coalescent Analysis of Phylogenomic Data Confidently Resolves the Species Relationships in the Anopheles gambiae Species Complex. Molecular Biology and Evolution 35, 2512-2527.

Wang K, Mathieson I, O’Connell J, Schiffels S (2020) Tracking human population structure through time from whole genome sequences. PLOS Genetics 16, e1008552.

Westbury MV, Cabrera AA, Rey-Iglesia A, Cahsan BD, Duchêne DA, Hartmann S, Lorenzen ED (2022) A genomic assessment of the marine-speciation paradox within the toothed whale superfamily Delphinoidea. bioRxiv, 2020.10.23.352286, ver. 7 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

Westbury MV, Petersen B, Lorenzen ED (2019) Genomic analyses reveal an absence of contemporary introgressive admixture between fin whales and blue whales, despite known hybrids. PLoS ONE 14, e0222004.

Yang Z (2015) The BPP program for species tree estimation and species delimitation. Current Zoology 61, 854-865.

Zhang C, Rabiee M, Sayyari E, Mirarab S (2018) ASTRAL-III: polynomial time species tree reconstruction from partially resolved gene trees. BMC Bioinformatics 19, 153.

01 Jul 2022
article picture

Genomic evidence of paternal genome elimination in the globular springtail Allacma fusca

Pressing NGS data through the mill of Kmer spectra and allelic coverage ratios in order to scan reproductive modes in non-model species

Recommended by based on reviews by Paul Simion and 2 anonymous reviewers

The genomic revolution has given us access to inexpensive genetic data for any species. Simultaneously we have lost the ability to easily identify chimerism in samples or some unusual deviations from standard Mendelian genetics. Methods have been developed to identify sex chromosomes, characterise the ploidy, or understand the exact form of parthenogenesis from genomic data. However, we rarely consider that the tissues we extract DNA from could be a mixture of cells with different genotypes or karyotypes. This can nonetheless happen for a variety of (fascinating) reasons such as somatic chromosome elimination, transmissible cancer, or parental genome elimination. Without a dedicated analysis, it is very easy to miss it.

In this preprint, Jaron et al. (2022) used an ingenious analysis of whole individual NGS data to test the hypothesis of paternal genome elimination in the globular springtail Allacma fusca. The authors suspected that a high fraction of the whole body of males is made of sperm in this species and if this species undergoes paternal genome elimination, we would expect that sperm would only contain maternally inherited chromosomes. Given the reference genome was highly fragmented, they developed a two-tissue model to analyse Kmer spectra and obtained confirmation that around one-third of the tissue was sperm in males. This allowed them to test whether coverage patterns were consistent with the species exhibiting paternal genome elimination. They combined their estimation of the fraction of haploid tissue with allele coverages in autosomes and the X chromosome to obtain support for a bias toward one parental allele, suggesting that all sperm carries the same parental haplotype. It could be the maternal or the paternal alleles, but paternal genome elimination is most compatible with the known biology of Arthropods. SNP calling was used to confirm conclusions based on the analysis of the raw pileups.

I found this study to be a good example of how a clever analysis of Kmer spectra and allele coverages can provide information about unusual modes of reproduction in a species, even though it does not have a well-assembled genome yet. As advocated by the authors, routine inspection of Kmer spectra and allelic read-count distributions should be included in the best practice of NGS data analysis. They provide the method to identify paternal genome elimination but also the way to develop similar methods to detect another kind of genetic chimerism in the avalanche of sequence data produced nowadays.


Jaron KS, Hodson CN, Ellers J, Baird SJ, Ross L (2022) Genomic evidence of paternal genome elimination in the globular springtail Allacma fusca. bioRxiv, 2021.11.12.468426, ver. 5 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

17 Jun 2022
article picture

Spontaneous parthenogenesis in the parasitoid wasp Cotesia typhae: low frequency anomaly or evolving process?

The potential evolutionary importance of low-frequency flexibility in reproductive modes

Recommended by based on reviews by Michael Lattorff and Jens Bast

Occasional events of asexual reproduction in otherwise sexual taxa have been documented since a long time. Accounts range from observations of offspring development from unfertilized eggs in Drosophila to rare offspring production by isolated females in lizards and birds (e.g., Stalker 1954, Watts et al 2006, Ryder et al. 2021). Many more such cases likely await documentation, as rare events are inherently difficult to observe. These rare events of asexual reproduction are often associated with low offspring fitness (“tychoparthenogenesis”), and have mostly been discarded in the evolutionary literature as reproductive accidents without evolutionary significance. Recently, however, there has been an increased interest in the details of evolutionary transitions from sexual to asexual reproduction (e.g., Archetti 2010, Neiman et al.2014, Lenormand et al. 2016), because these details may be key to understanding why successful transitions are rare, why they occur more frequently in some groups than in others, and why certain genetic mechanisms of ploidy maintenance or ploidy restoration are more often observed than others. In this context, the hypothesis has been formulated that regular or even obligate asexual reproduction may evolve from these rare events of asexual reproduction (e.g., Schwander et al. 2010).

A new study by Capdevielle Dulac et al. (2022) now investigates this question in a parasitoid wasp, highlighting also the fact that what is considered rare or occasional may differ from one system to the next. The results show “rare” parthenogenetic production of diploid daughters occurring at variable frequencies (from zero to 2 %) in different laboratory strains, as well as in a natural population. They also demonstrate parthenogenetic production of female offspring in both virgin females and mated ones, as well as no reduced fecundity of parthenogenetically produced offspring. These findings suggest that parthenogenetic production of daughters, while still being rare, may be a more regular and less deleterious reproductive feature in this species than in other cases of occasional asexuality. Indeed, haplodiploid organisms, such as this parasitoid wasp have been hypothesized to facilitate evolutionary transitions to asexuality (Neimann et al. 2014, Van Der Kooi et al. 2017). First, in haploidiploid organisms, females are diploid and develop from normal, fertilized eggs, but males are haploid as they develop parthenogenetically from unfertilized eggs. This means that, in these species, fertilization is not necessarily needed to trigger development, thus removing one of the constraints for transitions to obligate asexuality (Engelstädter 2008, Vorburger 2014). Second, spermatogenesis in males occurs by a modified meiosis that skips the first meiotic division (e.g., Ferree et al. 2019). Haploidiploid organisms may thus have a potential route for an evolutionary transition to obligate parthenogenesis that is not available to organisms: The pathways for the modified meiosis may be re-used for oogenesis, which might result in unreduced, diploid eggs. Third, the particular species studied here regularly undergoes inbreeding by brother-sister mating within their hosts. Homozygosity, including at the sex determination locus (Engelstädter 2008), is therefore expected to have less negative effects in this species compared to many other, non-inbreeding haplodipoids (see also Little et al. 2017). This particular species may therefore be less affected by loss of heterozygosity, which occurs in a fashion similar to self-fertilization under many forms of non-clonal parthenogenesis. 

Indeed, the study also addresses the mechanisms underlying parthenogenesis in the species. Surprisingly, the authors find that parthenogenetically produced females are likely produced by two distinct genetic mechanisms. The first results in clonality (maintenance of the maternal genotype), whereas the second one results in a loss of heterozygosity towards the telomeres, likely due to crossovers occurring between the centromeres and the telomeres. Moreover, bacterial infections appear to affect the propensity of parthenogenesis but are unlikely the primary cause. Together, the finding suggests that parthenogenesis is a variable trait in the species, both in terms of frequency and mechanisms. It is not entirely clear to what degree this variation is heritable, but if it is, then these results constitute evidence for low-frequency existence of variable and heritable parthenogenesis phenotypes, that is, the raw material from which evolutionary transitions to more regular forms of parthenogenesis may occur.



Archetti M (2010) Complementation, Genetic Conflict, and the Evolution of Sex and Recombination. Journal of Heredity, 101, S21–S33.

Capdevielle Dulac C, Benoist R, Paquet S, Calatayud P-A, Obonyo J, Kaiser L, Mougel F (2022) Spontaneous parthenogenesis in the parasitoid wasp Cotesia typhae: low frequency anomaly or evolving process? bioRxiv, 2021.12.13.472356, ver. 6 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

Engelstädter J (2008) Constraints on the evolution of asexual reproduction. BioEssays, 30, 1138–1150.

Ferree PM, Aldrich JC, Jing XA, Norwood CT, Van Schaick MR, Cheema MS, Ausió J, Gowen BE (2019) Spermatogenesis in haploid males of the jewel wasp Nasonia vitripennis. Scientific Reports, 9, 12194.

van der Kooi CJ, Matthey-Doret C, Schwander T (2017) Evolution and comparative ecology of parthenogenesis in haplodiploid arthropods. Evolution Letters, 1, 304–316.

Lenormand T, Engelstädter J, Johnston SE, Wijnker E, Haag CR (2016) Evolutionary mysteries in meiosis. Philosophical Transactions of the Royal Society B: Biological Sciences, 371, 20160001.

Little CJ, Chapuis M-P, Blondin L, Chapuis E, Jourdan-Pineau H (2017) Exploring the relationship between tychoparthenogenesis and inbreeding depression in the Desert Locust, Schistocerca gregaria. Ecology and Evolution, 7, 6003–6011.

Neiman M, Sharbel TF, Schwander T (2014) Genetic causes of transitions from sexual reproduction to asexuality in plants and animals. Journal of Evolutionary Biology, 27, 1346–1359.

Ryder OA, Thomas S, Judson JM, Romanov MN, Dandekar S, Papp JC, Sidak-Loftis LC, Walker K, Stalis IH, Mace M, Steiner CC, Chemnick LG (2021) Facultative Parthenogenesis in California Condors. Journal of Heredity, 112, 569–574.

Schwander T, Vuilleumier S, Dubman J, Crespi BJ (2010) Positive feedback in the transition from sexual reproduction to parthenogenesis. Proceedings of the Royal Society B: Biological Sciences, 277, 1435–1442.

Stalker HD (1954) Parthenogenesis in Drosophila. Genetics, 39, 4–34.

Vorburger C (2014) Thelytoky and Sex Determination in the Hymenoptera: Mutual Constraints. Sexual Development, 8, 50–58.

Watts PC, Buley KR, Sanderson S, Boardman W, Ciofi C, Gibson R (2006) Parthenogenesis in Komodo dragons. Nature, 444, 1021–1022.

16 Jun 2022
article picture

Sensory plasticity in a socially plastic bee

Taking advantage of facultative sociality in sweat bees to study the developmental plasticity of antennal sense organs and its association with social phenotype

Recommended by based on reviews by Michael D Greenfield, Sylvia Anton and Lluís Socias-Martínez

The study of the evolution of sociality is closely associated with the study of the evolution of sensory systems. Indeed, group life and sociality necessitate that individuals recognize each other and detect outsiders, as seen in eusocial insects such as Hymenoptera. While we know that antennal sense organs that are involved in olfactory perception are found in greater densities in social species of that group compared to solitary hymenopterans, whether this among-species correlation represents the consequence of social evolution leading to sensory evolution, or the opposite, is still questioned. Knowing more about how sociality and sensory abilities covary within a species would help us understand the evolutionary sequence. Studying a species that shows social plasticity, that is facultatively social, would further allow disentangling the cause and consequence of social evolution and sensory systems and the implication of plasticity in the process.

Boulton and Field (2022) studied a species of sweat bee that shows social plasticity, Halictus rubicundus. They studied populations at different latitudes in Great Britain: populations in the North are solitary, while populations in the south often show sociality, as they face a longer and warmer growing season, leading to the opportunity for two generations in a single year, a pre-condition for the presence of workers provisioning for the (second) brood. Using scanning electron microscope imaging, the authors compared the density of antennal sensilla types in these different populations (north, mid-latitude, south) to test for an association between sociality and olfactory perception capacities. They counted three distinct types of antennal sensilla: olfactory plates, olfactory hairs, and thermos/hygro-receptive pores, used to detect humidity, temperature and CO2. In addition, they took advantage of facultative sociality in this species by transplanting individuals from a northern population (solitary) to a southern location (where conditions favour sociality), to study how social plasticity is reflected (or not) in the density of antennal sensilla types. They tested the prediction that olfactory sensilla density is also developmentally plastic in this species.

Their results show that antennal sensilla counts differ between the 3 studied regions (north, mid-latitude, south), but not as predicted. Individuals in the southern population were not significantly different from the mid-latitude and northern ones in their count of olfactory plates and they had less, not more, thermos/hygro receptors than mid-latitude and northern individuals. Furthermore, mid-latitude individuals had more olfactory hairs than the ones from the northern population and did not differ from southern ones. The prediction was that the individuals expressing sociality would have the highest count of these olfactory hairs. This unpredicted pattern based on the latitude of sampling sites may be due to the effect of temperature during development, which was higher in the mid-latitude site than in the southern one. It could also be the result of a genotype-by-environment interaction, where the mid-latitude population has a different developmental response to temperature compared to the other populations, a difference that is genetically determined (a different “reaction norm”). Reciprocal transplant experiments coupled with temperature measurements directly on site would provide interesting information to help further dissect this intriguing pattern. 

Interestingly, where a sweat bee developed had a significant effect on their antennal sensilla counts: individuals originating from the North that developed in the south after transplantation had significantly more olfactory hairs on their antenna than individuals from the same Northern population that developed in the North. This is in accordance with the prediction that the characteristics of sensory organs can also be plastic. However, there was no difference in antennal characteristics depending on whether these transplanted bees became solitary or expressed the social phenotype (foundress or worker). This result further supports the hypothesis that temperature affects development in this species and that these sensory characteristics are also plastic, although independently of sociality. Overall, the work of Boulton and Field underscores the importance of including phenotypic plasticity in the study of the evolution of social behaviour and provides a robust and fruitful model system to explore this further.


Boulton RA, Field J (2022) Sensory plasticity in a socially plastic bee. bioRxiv, 2022.01.29.478030, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

31 Mar 2022
article picture

Gene network robustness as a multivariate character

Genetic and environmental robustness are distinct yet correlated evolvable traits in a gene network

Recommended by based on reviews by Diogo Melo, Charles Mullon and Charles Rocabert

Organisms often show robustness to genetic or environmental perturbations. Whether these two components of robustness can evolve separately is the focus of the paper by Le Rouzic [1]. Using theoretical analysis and individual-based computer simulations of a gene regulatory network model, he shows that multiple aspects of robustness can be investigated as a set of pleiotropically linked quantitative traits. While genetically correlated, various robustness components (e.g., mutational, developmental, homeostasis) of gene expression in the regulatory network evolved more or less independently from each other under directional selection. The quantitative approach of Le Rouzic could explain both how unselected robustness components can respond to selection on other components and why various robustness-related features seem to have their own evolutionary history. Moreover, he shows that all components were evolvable, but not all to the same extent. Robustness to environmental disturbances and gene expression stability showed the largest responses while increased robustness to genetic disturbances was slower. Interestingly, all components were positively correlated and remained so after selection for increased or decreased robustness.

This study is an important contribution to the discussion of the evolution of robustness in biological systems. While it has long been recognized that organisms possess the ability to buffer genetic and environmental perturbations to maintain homeostasis (e.g., canalization [2]), the genetic basis and evolutionary routes to robustness and canalization are still not well understood. Models of regulatory gene networks have often been used to address aspects of robustness evolution (e.g., [3]). Le Rouzic [1] used a gene regulatory network model derived from Wagner’s model [4]. The model has as end product the expression level of a set of genes influenced by a set of regulatory elements (e.g., transcription factors). The level and stability of expression are a property of the regulatory interactions in the network.

Le Rouzic made an important contribution to the study of such gene regulation models by using a quantitative genetics approach to the evolution of robustness. He crafted a way to assess the mutational variability and selection response of the components of robustness he was interested in. Le Rouzic’s approach opens avenues to investigate further aspects of gene network evolutionary properties, for instance to understand the evolution of phenotypic plasticity.

Le Rouzic also discusses ways to measure his different robustness components in empirical studies. As the model is about gene expression levels at a set of protein-coding genes influenced by a set of regulatory elements, it naturally points to the possibility of using RNA sequencing to measure the variation of gene expression in know gene networks and assess their robustness. Robustness could then be studied as a multidimensional quantitative trait in an experimental setting.


[1] Le Rouzic, A (2022) Gene network robustness as a multivariate character. arXiv: 2101.01564, ver. 5 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

[2] Waddington CH (1942) Canalization of Development and the Inheritance of Acquired Characters. Nature, 150, 563–565.

[3] Draghi J, Whitlock M (2015) Robustness to noise in gene expression evolves despite epistatic constraints in a model of gene networks. Evolution, 69, 2345–2358.

[4] Wagner A (1994) Evolution of gene networks by gene duplications: a mathematical model and its implications on genome organization. Proceedings of the National Academy of Sciences, 91, 4387–4391.

22 Mar 2022
article picture

Substantial genetic mixing among sexual and androgenetic lineages within the clam genus Corbicula

Strange reproductive modes and population genetics

Recommended by based on reviews by Arnaud Estoup, Simon Henry Martin and 2 anonymous reviewers

There are many organisms that are asexual or have unusual modes of reproduction. One such quasi-sexual reproductive mode is androgenesis, in which the offspring, after fertilization, inherits only the entire paternal nuclear genome. The maternal genome is ditched along the way. One group of organisms which shows this mode of reproduction are clams in the genus Corbicula, some of which are androecious, while others are dioecious and sexual. The study by Vastrade et al. (2022) describes population genetic patterns in these clams, using both nuclear and mitochondrial sequence markers.

In contrast to what might be expected for an asexual lineage, there is evidence for significant genetic mixing between populations. In addition, there is high heterozygosity and evidence for polyploidy in some lineages. Overall, the picture is complicated! However, what is clear is that there is far more genetic mixing than expected. One possible mechanism by which this could occur is 'nuclear capture' where there is a mixing of maternal and paternal lineages after fertilization. This can sometimes occur as a result of hybridization between 'species', leading to further mixing of divergent lineages. Thus the group is clearly far from an ancient asexual lineage - recombination and mixing occur with some regularity.

The study also analyzed recent invasive populations in Europe and America. These had reduced genetic diversity, but also showed complex patterns of allele sharing suggesting a complex origin of the invasive lineages.

In the future, it will be exciting to apply whole genome sequencing approaches to systems such as this. There are challenges in interpreting a handful of sequenced markers especially in a system with polyploidy and considerable complexity, and whole-genome sequencing could clarify some of the outstanding questions,

Overall, this paper highlights the complex genetic patterns that can result through unusual reproductive modes, which provides a challenge for the field of population genetics and for the recognition of species boundaries. 


Vastrade M, Etoundi E, Bournonville T, Colinet M, Debortoli N, Hedtke SM, Nicolas E, Pigneur L-M, Virgo J, Flot J-F, Marescaux J, Doninck KV (2022) Substantial genetic mixing among sexual and androgenetic lineages within the clam genus Corbicula. bioRxiv, 590836, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

12 Nov 2021
article picture

How ancient forest fragmentation and riparian connectivity generate high levels of genetic diversity in a micro-endemic Malagasy tree

An ancient age of open-canopy landscapes in northern Madagascar? Evidence from the population genetic structure of a forest tree

Recommended by based on reviews by Katharina Budde and Yurena Arjona

We currently live in the Anthropocene, the geological age characterized by a profound impact of human populations in the ecosystems and the environment. While there is little doubt about the action of humans in the shaping of present landscapes, it can be difficult to determine what the state of those landscapes was before humans started to modify them. This is the case of the Madagascar grasslands, whose origins have been debated with arguments proposing them either as anthropogenic, created with the arrival of humans around 2000BP, or as ancient features of the natural landscape with a forest fragmentation process due to environmental changes pre-dating human arrival [e.g. 1,2]. One way to clarify this question is through the genetic study of native species. Population continuity and fragmentation along time shape the structure of the genetic diversity in space. Species living in a uniform continuous habitat are expected to show genetic structuring determined only by geographical distance. Recent changes of the habitat can take many generations to reshape that genetic structure [3]. Thus, we expect genetic structure to reflect ancient features of the landscape.

The work by Jordi Salmona and collaborators [4] studies the factors determining the population genetic structure of the Malagasy spiny olive (Noronhia spinifolia). This narrow endemic species is distributed in the discontinuous forest patches of the Loky-Manambato region (northern Madagascar). Jordi Salmona and collaborators genotyped 72 individuals distributed across the species distribution with restriction associated DNA sequencing and organelle microsatellite markers. Then, they studied the population genetic structure of the species. Using isolation-by-resistance models [5], they tested the influence of several landscape features (forest cover, roads, rivers, slope, etc.) on the connectivity between populations. Maternally inherited loci (chloroplast and mitochondria) and bi-parentally inherited loci (nuclear), were analysed separately in an attempt to identify the role of pollen and seed dispersal in the connectivity of populations.

Despite the small distribution of the species, Jordi Salmona and collaborators [4] found remarkable levels of genetic diversity. The spatial structure of this diversity was found to be mainly explained by the forest cover of the landscape, suggesting that the landscape has been composed by patches of forests and grasslands for a long time. The main role of forest cover for the connectivity among populations also highlights the importance of riparian forest as dispersal corridors. Finally, differences between organelle and nuclear markers were not enough to establish any strong conclusion about the differences between pollen and seed dispersal.

The results presented by Jordi Salmona and collaborators [4] contribute to the understanding of the history and ecology of understudied Madagascar ecosystems. Previous population genetic studies  in some forest-dwelling mammals have been interpreted as supporting an old age for the fragmented landscapes in northern Madagascar [e.g. 1,6]. To my knowledge, this is the first study on a tree species. While this work might not completely settle the debate, it emphasizes the importance of studying a diversity of species to understand the biogeographic dynamics of a region.


1. Quéméré, E., X. Amelot, J. Pierson, B. Crouau-Roy, L. Chikhi (2012) Genetic data suggest a natural prehuman origin of open habitats in northern Madagascar and question the deforestation narrative in this region. Proceedings of the National Academy of Sciences of the United States of
America 109: 13028–13033.
2. Joseph, G.S., C.L. Seymour (2020) Madagascan highlands: originally woodland and forest containing endemic grasses, not grazing-adapted grassland. Proceedings of the Royal Society B: Biological Sciences 287: 20201956.
3. Landguth, E.L., S.A. Cushman, M.K. Schwartz, K.S. McKelvey, M. Murphy, G. Luikart (2010) Quantifying the lag time to detect barriers in landscape genetics. Molecular Ecology 19: 4179–
4. Salmona J., Dresen A, Ranaivoson AE, Manzi S, Pors BL, Hong-Wa C, Razanatsoa J, Andriaholinirina NV, Rasoloharijaona S, Vavitsara M-E, Besnard G (2021) How ancient forest fragmentation and riparian connectivity generate high levels of genetic diversity in a micro-endemic Malagasy tree. bioRxiv, 2020.11.25.394544, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology.
5. McRae, B.H. (2006) Isolation by resistance. Evolution 60: 1551–1561.
6. Rakotoarisoa J.-E., M. Raheriarisena, S.M. Goodman (2013) Late Quaternary climatic vegetational shifts in an ecological transition zone of northern Madagascar: insights from genetic analyses of two endemic rodent species. Journal of Evolutionary Biology 26: 1019–1034.

08 Nov 2021
article picture

Dynamics of sex-biased gene expression over development in the stick insect Timema californicum

Sex-biased gene expression in an hemimetabolous insect: pattern during development, extent, functions involved, rate of sequence evolution, and comparison with an holometabolous insect

Recommended by based on reviews by 2 anonymous reviewers

An individual’s sexual phenotype is determined during development. Understanding which pathways are activated or repressed during the developmental stages leading to a sexually mature individual, for example by studying gene expression and how its level is biased between sexes, allows us to understand the functional aspects of dimorphic phenotypes between the sexes.

Several studies have quantified the differences in transcription between the sexes in mature individuals, showing the extent of this sex-bias and which functions are affected. There is, however, less data available on what occurs during the different phases of development leading to this phenotype, especially in species with specific developmental strategies, such as hemimetabolous insects. While many well-studied insects such as the honey bee, drosophila, and butterflies, exhibit an holometabolous development ("holo" meaning "complete" in reference to their drastic metamorphosis from the juvenile to the adult stage), hemimetabolous insects have juvenile stages that look similar to the adult stage (the hemi prefix meaning "half", referring to the more tissue-specific changes during development), as seen in crickets, cockroaches, and stick insects. Learning more about what happens during development in terms of the identity of genes that are sex-biased (are they the same genes at different developmental stages? What are their function? Do they exhibit specific sequence evolution rates? Is one sex over-represented in the sex-biased genes?) and their quantity over developmental time (gradual or abrupt increase in number, if any?) would allow us to better understand the evolution of sexual dimorphism at the gene expression level and how it relates to dimorphism at the organismic level.

Djordjevic et al (2021) studied the transcriptome during development in an hemimetabolous stick insect, to improve our knowledge of this type of development, where the organismic phenotype is already mostly present in the early life stages. To do this, they quantified whole-genome gene expression levels in whole insects, using RNA-seq at three different developmental stages. One of the interesting results presented by Djordjevic and colleagues is that the increase in the number of genes that were sex-biased in expression is gradual over the three stages of development studied and it is mostly the same genes that stay sex-biased over time, reflecting the gradual change in phenotypes between hatchlings, juveniles and adults. Furthermore, male-biased genes had faster sequence divergence rates than unbiased genes and that female-biased genes.

This new information of sex-bias in gene expression in an hemimetabolous insect allowed the authors to do a comparison of sex-biased genes with what has been found in a well-studied holometabolous insect, Drosophila. The gene expression patterns showed that four times more genes were sex-biased in expression in that species than in stick insects. Furthermore, the increase in the number of sex-biased genes during development was quite abrupt and clearly distinct in the adult stage, a pattern that was not seen in stick insects. As pointed out by the authors, this pattern of a "burst" of sex-biased genes at maturity is more common than the gradual increase seen in stick insects.

With this study, we now know more about the evolution of sex-biased gene expression in an hemimetabolous insect and how it relates to their phenotypic dimorphism. Clearly, the next step will be to sample more hemimetabolous species at different life stages, to see how this pattern is widespread or not in this mode of development in insects.


Djordjevic J, Dumas Z, Robinson-Rechavi M, Schwander T, Parker DJ (2021) Dynamics of sex-biased gene expression during development in the stick insect Timema californicum. bioRxiv, 2021.01.23.427895, ver. 6 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

26 Oct 2021
article picture

Large-scale geographic survey provides insights into the colonization history of a major aphid pest on its cultivated apple host in Europe, North America and North Africa

The evolutionary puzzle of the host-parasite-endosymbiont Russian doll for apples and aphids

Recommended by based on reviews by Pedro Simões and 1 anonymous reviewer

Each individual multicellular organism, each of our bodies, is a small universe. Every living surface -skin, cuticle, bark, mucosa- is the home place to milliards of bacteria, fungi and viruses. They constitute our microbiota. Some of them are essential for certain organisms. Other could not live without their hosts. For many species, the relationship between host and microbiota is so close that their histories are inseparable. The recognition of this biological inextricability has led to the notion of holobiont as the organism ensemble of host and microbiota. When individuals of a particular animal or plant species expand their geographical range, it is the holobiont that expands. And these processes of migration, expansion and colonization are often accompanied by evolutionary and ecological innovations in the interspecies relationships, at the macroscopic level (e.g. novel predator-prey or host-parasite interactions) and at the microscopic level (e.g. changes in the microbiota composition). From the human point of view, these novel interactions can be economically disastrous if they involve and threaten important crop or cattle species. And this is especially worrying in the present context of genetic standardization and intensification for mass-production on the one hand, and of climate change on the other.

With this perspective, the international team led by Amandine Cornille presents a study aiming at understanding the evolutionary history of the rosy apple aphid Dysaphis plantaginea Passerini, a major pest of the cultivated apple tree Malus domestica Borkh (1). The apple tree was probably domesticated in Central Asia, and later disseminated by humans over the world in different waves, and it was probably introduced in Europe by the Greeks. It is however unclear when and where D. plantaginea started parasitizing the cultivated apple tree. The ancestral D. plantaginea could have already infected the wild ancestor of current cultivated apple trees, but the aphid is not common in Central Asia. Alternatively, it may have gained access only later to the plant, possibly via a host jump, from Pyrus to Malus that may have occurred in Asia Minor or in the Caucasus. In the present preprint, Olvera-Vázquez and coworkers have analysed over 650 D. plantaginea colonies from 52 orchards in 13 countries, in Western, Central and Eastern Europe as well as in Morocco and the USA. The authors have analysed the genetic diversity in the sampled aphids, and have characterized as well the composition of the associated endosymbiont bacteria. The analyses detect substantial recent admixture, but allow to identify aphid subpopulations slightly but significantly differentiated and isolated by distance, especially those in Morocco and the USA, as well as to determine the presence of significant gene flow. This process of colonization associated to gene flow is most likely indirectly driven by human interactions. Very interestingly, the data show that this genetic diversity in the aphids is not reflected by a corresponding diversity in the associated microbiota, largely dominated by a few Buchnera aphidicola variants. In order to determine polarity in the evolutionary history of the aphid-tree association, the authors have applied approximate Bayesian computing and machine learning approaches. Albeit promising, the results are not sufficiently robust to assess directionality nor to confidently assess the origin of the crop pest. Despite the large effort here communicated, the authors point to the lack of sufficient data (in terms of aphid isolates), especially originating from Central Asia. Such increased sampling will need to be implemented in the future in order to elucidate not only the origin and the demographic history of the interaction between the cultivated apple tree and the rosy apple aphid. This knowledge is needed to understand how this crop pest struggles with the different seasonal and geographical selection pressures while maintaining high genetic diversity, conspicuous gene flow, differentiated populations and low endosymbiontic diversity.


  1. Olvera-Vazquez SG, Remoué C, Venon A, Rousselet A, Grandcolas O, Azrine M, Momont L, Galan M, Benoit L, David GM, Alhmedi A, Beliën T, Alins G, Franck P, Haddioui A, Jacobsen SK, Andreev R, Simon S, Sigsgaard L, Guibert E, Tournant L, Gazel F, Mody K, Khachtib Y, Roman A, Ursu TM, Zakharov IA, Belcram H, Harry M, Roth M, Simon JC, Oram S, Ricard JM, Agnello A, Beers EH, Engelman J, Balti I, Salhi-Hannachi A, Zhang H, Tu H, Mottet C, Barrès B, Degrave A, Razmjou J, Giraud T, Falque M, Dapena E, Miñarro M, Jardillier L, Deschamps P, Jousselin E, Cornille A (2021) Large-scale geographic survey provides insights into the colonization history of a major aphid pest on its cultivated apple host in Europe, North America and North Africa. bioRxiv, 2020.12.11.421644, ver. 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology.


11 Oct 2021
article picture

Landscape connectivity alters the evolution of density-dependent dispersal during pushed range expansions

Phenotypic evolution during range expansions is contingent on connectivity and density dependence

Recommended by based on reviews by 3 anonymous reviewers

Understanding the mechanisms underlying range expansions is key for predicting species distributions in response to environmental changes (such as global warming) and managing the global expansion of invasive species (Parmesan 2006; Suarez & Tsutsui 2008). Traditionally, two types of ecological processes were studied as essential in shaping range expansion: dispersal and population growth. However, ecology and evolution are intertwined in range expansions, as phenotypic evolution of traits involved in demographic and dispersal patterns and processes can affect and be affected by ecological dynamics, representing a full eco-evolutionary loop (Williams et al. 2019; Miller et al. 2020).

Range expansions can be characterized by the type of population growth and dispersal, divided into pushed or pulled range expansions. Species that have high dispersal and high population growth at low densities present pulled range expansions (pulled by individuals from the edge populations). In contrast, populations presenting increased growth rate at intermediate densities (due to Allee effects - Allee & Bowen 1932; i.e. where growth rate decreases at lower densities) and high dispersal at high densities present pushed range expansions (driven by individuals from core and intermediate populations) (Gandhi et al. 2016). Importantly, the type of expansion is expected to have very different consequences on the genetic (and therefore) phenotypic composition of core and edge populations. Specifically, genetic variability is expected to be lower in populations experiencing pulled expansions and higher in populations involved in pushed expansions (Gandhi et al. 2016; Miller et al. 2020). However, it is not always possible to distinguish between pulled and pushed expansions, as variation in speed and shape can overlap between the two types. In addition, it is difficult to experimentally manipulate the strength of the Allee effect to create pushed versus pulled expansions. Thus, several critical predictions regarding the genetic and phenotypic composition of pulled and pushed expansions are lacking empirical tests (but see Gandhi et al. 2016).

In a previous study, Dahirel et al. (2021a) combined simulations and experimental evolution of the small wasps Trichogramma brassicae to show that low connectivity led to more pushed expansions, and higher connectivity generated more pulled expansions. In accordance with theoretical predictions, this led to reduced genetic diversity in pulled expansions, and the reverse pattern in pushed expansions. However, the question of how pulled and pushed expansions affect trait evolution remained unanswered.

In this follow-up study, Dahirel et al. (2021b) tackled this issue and linked the changes in connectivity and type of expansion with the phenotypic evolution of several traits using individuals from their previous experiment. Namely, the authors compared core and edge populations with founder strains to test how evolution in pushed vs. pulled expansions affected wasp size, short movement, fecundity, dispersal, and density dependent dispersal. When density dependence was not accounted for, phenotypic changes in edge populations did not match the expectations from changes in expansion dynamics. This could be due to genetic trade-offs between traits that limit phenotypic evolution (Urquhart & Williams 2021). 

However, when accounting for density dependent dispersal, Dahirel et al. (2021b) observed that more connected landscapes (with pulled expansions) showed positive density dispersal in core populations and negative density dispersal in edge populations, similarly to other studies (e.g. Fronhofer et al. 2017). Interestingly, in pushed (with lower connectivity) landscapes, such shift was not observed. Instead, edge populations maintained positive density dispersal even after 14 generations of expansion, whereas core populations showed higher dispersal at lower density. The authors suggest that this seemingly contradictory result is due to a combination of three processes: 1) the expansion reduced positive density dispersal in edge populations; 2) reduced connectivity directly increased dispersal costs, increasing high density dispersal; and 3) reduced connectivity indirectly caused demographic stochasticity (and reduced temporal variability in patches) leading to higher dispersal at low density in core populations. However, these results must be taken with a grain of salt, since only one of the four experimental replicates were used in the density dependent dispersal experiment. In range expansions experiments, replication is fundamental, since stochastic processes (such as gene surfing, where alleles maybe rise in frequency due by chance) are prevalent (Miller et al. 2020), and results are highly dependent on sample size, or number of replicate populations analysed. 

Having said that, results from Dahirel et al. (2021b) highlight the importance to contextualize the management of invasions and species distribution, since it is thought that pulled expansions are more prevalent in nature, but pushed expansions can be more important in scenarios where patchiness is high, such as urban landscapes. Moreover, Dahirel's et al. (2021b) study is a first step showing that accounting for trait density dependence is crucial when following phenotypic evolution during range expansion, and that evolution of density dependent traits may be constrained by landscape conditions. This highlights the need to account for both connectivity and density dependence to draw more accurate predictions on the evolutionary and ecological outcomes of range expansions. 

Allee WC, Bowen ES (1932) Studies in animal aggregations: Mass protection against colloidal silver among goldfishes. Journal of Experimental Zoology, 61, 185–207.

Dahirel M, Bertin A, Calcagno V, Duraj C, Fellous S, Groussier G, Lombaert E, Mailleret L, Marchand A, Vercken E (2021a) Landscape connectivity alters the evolution of density-dependent dispersal during pushed range expansions. bioRxiv, 2021.03.03.433752, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

Dahirel M, Bertin A, Haond M, Blin A, Lombaert E, Calcagno V, Fellous S, Mailleret L, Malausa T, Vercken E (2021b) Shifts from pulled to pushed range expansions caused by reduction of landscape connectivity. Oikos, 130, 708–724.

Fronhofer EA, Gut S, Altermatt F (2017) Evolution of density-dependent movement during experimental range expansions. Journal of Evolutionary Biology, 30, 2165–2176.

Gandhi SR, Yurtsev EA, Korolev KS, Gore J (2016) Range expansions transition from pulled to pushed waves as growth becomes more cooperative in an experimental microbial population. Proceedings of the National Academy of Sciences, 113, 6922–6927.

Miller TEX, Angert AL, Brown CD, Lee-Yaw JA, Lewis M, Lutscher F, Marculis NG, Melbourne BA, Shaw AK, Szűcs M, Tabares O, Usui T, Weiss-Lehman C, Williams JL (2020) Eco-evolutionary dynamics of range expansion. Ecology, 101, e03139.

Parmesan C (2006) Ecological and Evolutionary Responses to Recent Climate Change. Annual Review of Ecology, Evolution, and Systematics, 37, 637–669.

Suarez AV, Tsutsui ND (2008) The evolutionary consequences of biological invasions. Molecular Ecology, 17, 351–360.

Urquhart CA, Williams JL (2021) Trait correlations and landscape fragmentation jointly alter expansion speed via evolution at the leading edge in simulated range expansions. Theoretical Ecology.

Williams JL, Hufbauer RA, Miller TEX (2019) How Evolution Modifies the Variability of Range Expansion. Trends in Ecology & Evolution, 34, 903–913.

01 Sep 2021
article picture

Connectivity and selfing drives population genetic structure in a patchy landscape: a comparative approach of four co-occurring freshwater snail species

Determinants of population genetic structure in co-occurring freshwater snails

Recommended by and based on reviews by 3 anonymous reviewers

Genetic diversity is a key aspect of biodiversity and has important implications for evolutionary potential and thereby the persistence of species. Improving our understanding of the factors that drive genetic structure within and between populations is, therefore, a long-standing goal in evolutionary biology. However, this is a major challenge, because of the complex interplay between genetic drift, migration, and extinction/colonization dynamics on the one hand, and the biology and ecology of species on the other hand (Romiguier et al. 2014, Ellegren and Galtier 2016, Charlesworth 2003). 

Jarne et al. (2021) studied whether environmental and demographic factors affect the population genetic structure of four species of hermaphroditic freshwater snails in a similar way, using comparative analyses of neutral genetic microsatellite markers. 

Specifically, they investigated microsatellite variability of Hygrophila in almost 280 sites in Guadeloupe, Lesser Antilles, as part of a long-term survey experiment (Lamy et al. 2013). They then modelled the influence of the mating system, local environmental characteristics and demographic factors on population genetic diversity.

Consistent with theoretical predictions (Charlesworth 2003), they detected higher genetic variation in two outcrossing species than in two selfing species, emphasizing the importance of the mating system in maintaining genetic diversity. The study further identified an important role of site connectivity, through its influences on effective population size and extinction/colonisation events. Finally, the study detects an influence of interspecific interactions caused by an ongoing invasion by one of the studied species on genetic structure, highlighting the indirect effect of changes in community composition and demography on population genetics.

Jarne et al. (2021) could address the extent to which genetic structure is determined by demographic and environmental factors in multiple species given the remarkable sampling available. Additionally, the study system is extremely suitable to address this hypothesis as species’ habitats are defined and delineated. Whilst the authors did attempt to test for across-species correlations, further investigations on this matter are required. Moreover, the effect of interactions between factors should be appropriately considered in any modelling between genetic structure and local environmental or demographic features.

The findings in this study contribute to improving our understanding of factors influencing population genetic diversity, and highlights the complexity of interacting factors, therefore also emphasizing the challenges of drawing general implications, additionally hampered by the relatively limited number of species studied. Jarne et al. (2021) provide an excellent showcase of an empirical framework to test determinants of genetic structure in natural populations. As such, this study can be an example for further attempts of comparative analysis of genetic diversity.


Charlesworth, D. (2003) Effects of inbreeding on the genetic diversity of populations. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 358, 1051-1070. doi:

Ellegren, H. and Galtier, N. (2016) Determinants of genetic diversity. Nature Reviews Genetics, 17, 422-433. doi:

Jarne, P., Lozano del Campo, A., Lamy, T., Chapuis, E., Dubart, M., Segard, A., Canard, E., Pointier, J.-P. and David, P. (2021) Connectivity and selfing drives population genetic structure in a patchy landscape: a comparative approach of four co-occurring freshwater snail species. HAL, hal-03295242, ver. 2 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

Lamy, T., Gimenez, O., Pointier, J. P., Jarne, P. and David, P. (2013). Metapopulation dynamics of species with cryptic life stages. The American Naturalist, 181, 479-491. doi:

Romiguier, J., Gayral, P., Ballenghien, M. et al. (2014) Comparative population genomics in animals uncovers the determinants of genetic diversity. Nature, 515, 261-263. doi:

30 Aug 2021
article picture

The quasi-universality of nestedness in the structure of quantitative plant-parasite interactions

Nestedness and modularity in plant-parasite infection networks

Recommended by based on reviews by Rubén González and 2 anonymous reviewers

In a landmark paper, Flores et al. (2011) showed that the interactions between bacteria and their viruses could be nicely described using a bipartite infection networks.  Two quantitative properties of these networks were of particular interest, namely modularity and nestedness.  Modularity emerges when groups of host species (or genotypes) shared groups of viruses.  Nestedness provided a view of the degree of specialization of both partners: high nestedness suggests that hosts differ in their susceptibility to infection, with some highly susceptible host genotypes selecting for very specialized viruses while strongly resistant host genotypes select for generalist viruses.  Translated to the plant pathology parlance, this extreme case would be equivalent to a gene-for-gene infection model (Flor 1956): new mutations confer hosts with resistance to recently evolved viruses while maintaining resistance to past viruses.  Likewise, virus mutations for expanding host range evolve without losing the ability to infect ancestral host genotypes.  By contrast, a non-nested network would represent a matching-allele infection model (Frank 2000) in which each interacting organism evolves by losing its capacity to resist/infect its ancestral partners, resembling a Red Queen dynamic.  Obviously, the reality is more complex and may lie anywhere between these two extreme situations.

Recently, Valverde et al. (2020) developed a model to explain the emergence of nestedness and modularity in plant-virus infection networks across diverse habitats.  They found that local modularity could coexist with global nestedness and that intraspecific competition was the main driver of the evolution of ecosystems in a continuum between nested-modular and nested networks.  These predictions were tested with field data showing the association between plant host species and different viruses in different agroecosystems (Valverde et al. 2020).  The effect of interspecific competition in the structure of empirical plant host-virus infection networks was also tested by McLeish et al. (2019).  Besides data from agroecosystems, evolution experiments have also shown the pervasive emergence of nestedness during the diversification of independently-evolved lineages of potyviruses in Arabidopsis thaliana genotypes that differ in their susceptibility to infection (Hillung et al. 2014; González et al. 2019; Navarro et al. 2020).

In their study, Moury et al. (2021) have expanded all these previous observations to a diverse set of pathosystems that range from viruses, bacteria, oomycetes, fungi, nematodes to insects.  While modularity was barely seen in only a few of the systems, nestedness was a common trend (observed in ~94% of all systems).  This nestedness, as seen in previous studies and as predicted by theory, emerged as a consequence of the existence of generalist and specialist strains of the parasites that differed in their capacity to infect more or less resistant plant genotypes.

As pointed out by Moury et al. (2021) in their conclusions, the ubiquity of nestedness in plant-parasite infection matrices has strong implications for the evolution and management of infectious diseases.


Flor, H. H. (1956). The complementary genic systems in flax and flax rust. In Advances in genetics, 8, 29-54.

Flores, C. O., Meyer, J. R., Valverde, S., Farr, L., and Weitz, J. S. (2011). Statistical structure of host–phage interactions. Proceedings of the National Academy of Sciences, 108, E288-E297.

Frank, S. A. (2000). Specific and non-specific defense against parasitic attack. Journal of Theoretical Biology, 202, 283-304.

González, R., Butković, A., and Elena, S. F. (2019). Role of host genetic diversity for susceptibility-to-infection in the evolution of virulence of a plant virus. Virus evolution, 5(2), vez024.

Hillung, J., Cuevas, J. M., Valverde, S., and Elena, S. F. (2014). Experimental evolution of an emerging plant virus in host genotypes that differ in their susceptibility to infection. Evolution, 68, 2467-2480.

McLeish, M., Sacristán, S., Fraile, A., and García-Arenal, F. (2019). Coinfection organizes epidemiological networks of viruses and hosts and reveals hubs of transmission. Phytopathology, 109, 1003-1010.

Moury B, Audergon J-M, Baudracco-Arnas S, Krima SB, Bertrand F, Boissot N, Buisson M, Caffier V, Cantet M, Chanéac S, Constant C, Delmotte F, Dogimont C, Doumayrou J, Fabre F, Fournet S, Grimault V, Jaunet T, Justafré I, Lefebvre V, Losdat D, Marcel TC, Montarry J, Morris CE, Omrani M, Paineau M, Perrot S, Pilet-Nayel M-L and Ruellan Y (2021) The quasi-universality of nestedness in the structure of quantitative plant-parasite interactions. bioRxiv, 2021.03.03.433745, ver. 4 recommended and peer-reviewed by PCI Evolutionary Biology.

Navarro, R., Ambros, S., Martinez, F., Wu, B., Carrasco, J. L., and Elena, S. F. (2020). Defects in plant immunity modulate the rates and patterns of RNA virus evolution. bioRxiv. doi:

Valverde, S., Vidiella, B., Montañez, R., Fraile, A., Sacristán, S., and García-Arenal, F. (2020). Coexistence of nestedness and modularity in host–pathogen infection networks. Nature ecology & evolution, 4, 568-577.

26 Aug 2021
article picture

Impact of ploidy and pathogen life cycle on resistance durability

Durability of plant resistance to diploid pathogen

Recommended by based on reviews by Loup Rimbaud and 1 anonymous reviewer

​​Durability of plant resistance to diploid pathogen Hirohisa Kishino Based on the population genetic and epidemiologic model, Saubin et al. (2021) report that the resistant hosts generated by the breeding based on the gene-for-gene interaction is durable much longer against diploid pathogens than haploid pathogens. The avr allele of pathogen that confers the resistance is genetically recessive. The heterozygotes are not recognized by the resistant hosts and only the avr/avr homozygote is adaptive. As a result, the trajectory of avr allele frequency becomes more stochastic due to genetic drift. Although the paper focuses on the evolution of standing polymorphism, it seems obvious that the adaptive mutations in pathogen have much larger probability of being deleted from the population because the individuals own the avr allele mostly in the form of heterozygote at the initial phase after the mutation. Since only few among many models of plant resistance deployment study the case of diploid pathogen and the contribution of the pathogen life cycle, this work will add an important intellect to the literature (Rimbaud et al. 2021).

From the study of host-parasite interaction in flax rust Melampsora lini, Flor (1942, 1955) showed that the host resistance is formed by the interaction of a host resistance gene and a corresponding pathogen gene. This gene-for-gene hypothesis has been supported by experimental evidence and has served as a basis of the methods of molecular breeding targeting the dominant R genes. However, modern agriculture provides the pathogen populations with the homogeneous environments and laid strong selection pressure on them. As a result, the newly developed resistant plants face the risk of immediate resistance breakdown (Möller and Stukenbrock 2017).

Currently, quantitative resistance is getting attention as characters as a potential target for long-life (mild) resistant breeds (Lannou, 2012). They are polygenic and controlled partly by the same genes that mediate qualitative resistance but mostly by the genes that encode defense-related outputs such as strengthening of the cell wall or defense compound biosynthesis (Corwin and Kliebenstein, 2017). Progress of molecular genetics may overcome the technical difficulty (Bakkeren and Szabo, 2020). Saubin et al. (2021) notes that the pattern of genetic inheritance of the pathogen counterparts that respond to the host traits is crucial regarding with the durability of the resistant hosts. The resistance traits for which avr alleles are predicted to be recessive may be the targets of breeding.


Bakkeren, G., and Szabo, L. J. (2020) Progress on molecular genetics and manipulation of rust fungi. Phytopathology, 110, 532-543.

Corwin, J. A., and Kliebenstein, D. J. (2017) Quantitative resistance: more than just perception of a pathogen. The Plant Cell, 29, 655-665.

Flor, H. H. (1942) Inheritance of pathogenicity in a cross between physiological races 22 and 24 of Melampsova lini. Phytopathology, 35. Abstract.

Flor, H. H. (1955) Host-parasite interactions in flax rust-its genetics and other implications. Phytopathology, 45, 680-685.

Lannou, C. (2012) Variation and selection of quantitative traits in plant pathogens. Annual review of phytopathology, 50, 319-338.

Möller, M. and Stukenbrock, E. H. (2017) Evolution and genome architecture in fungal plant pathogens. Nature Reviews Microbiology. 15, 756–771.

Rimbaud, L., Fabre, F., Papaïx, J., Moury, B., Lannou, C., Barrett, L. G., and Thrall, P. H. (2021) Models of Plant Resistance Deployment. Annual Review of Phytopathology, 59.

Saubin, M., De Mita, S., Zhu, X., Sudret, B. and Halkett, F. (2021) Impact of ploidy and pathogen life cycle on resistance durability. bioRxiv, 2021.05.28.446112, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

19 Jul 2021
article picture

Host phenology can drive the evolution of intermediate virulence strategies in some obligate-killer parasites

Modelling parasitoid virulence evolution with seasonality

Recommended by based on reviews by Alex Best and 2 anonymous reviewers

The harm most parasites cause to their host, i.e. the virulence, is a mystery because host death often means the end of the infectious period. For obligate killer parasites, or “parasitoids”, that need to kill their host to transmit to other hosts the question is reversed. Indeed, more rapid host death means shorter generation intervals between two infections and mathematical models show that, in the simplest settings, natural selection should always favour more virulent strains (Levin and Lenski, 1983). Adding biological details to the model modifies this conclusion and, for instance, if the relationship between the infection duration and the number of parasites transmission stages produced in a host is non-linear, strains with intermediate levels of virulence can be favoured (Ebert and Weisser 1997). Other effects, such as spatial structure, could yield similar effects (Lion and van Baalen, 2007).

In their study, MacDonald et al. (2021) explore another type of constraint, which is seasonality. Earlier studies, such as that by Donnelly et al. (2013) showed that this constraint can affect virulence evolution but they had focused on directly transmitted parasites. Using a mathematical model capturing the dynamics of a parasitoid, MacDonald et al. (2021) show if two main assumptions are met, namely that at the end of the season only transmission stages (or “propagules”) survive and that there is a constant decay of these propagules with time, then strains with intermediate levels of virulence are favoured.

Practically, the authors use delay differential equations and an adaptive dynamics approach to identify evolutionary stable strategies. As expected, the longer the short the season length, the higher the virulence (because propagule decay matters less). The authors also identify a non-linear relationship between the variation in host development time and virulence. Generally, the larger the variation, the higher the virulence because the parasitoid has to kill its host before the end of the season. However, if the variation is too wide, some hosts become physically impossible to use for the parasite, whence a decrease in virulence.

Finally, MacDonald et ali. (2021) show that the consequence of adding trade-offs between infection duration and the number of propagules produced is in line with earlier studies (Ebert and Weisser 1997). These mathematical modelling results provide testable predictions for using well-described systems in evolutionary ecology such as daphnia parasitoids, baculoviruses, or lytic phages.


Donnelly R, Best A, White A, Boots M (2013) Seasonality selects for more acutely virulent parasites when virulence is density dependent. Proc R Soc B, 280, 20122464.

Ebert D, Weisser WW (1997) Optimal killing for obligate killers: the evolution of life histories and virulence of semelparous parasites. Proc R Soc B, 264, 985–991.

Levin BR, Lenski RE (1983) Coevolution in bacteria and their viruses and plasmids. In: Futuyma DJ, Slatkin M eds. Coevolution. Sunderland, MA, USA: Sinauer Associates, Inc., 99–127.

Lion S, van Baalen M (2008) Self-structuring in spatial evolutionary ecology. Ecol. Lett., 11, 277–295.

MacDonald H, Akçay E, Brisson D (2021) Host phenology can drive the evolution of intermediate virulence strategies in some obligate-killer parasites. bioRxiv, 2021.03.13.435259, ver. 8 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

23 Jun 2021
article picture

Evolution of flowering time in a selfing annual plant: Roles of adaptation and genetic drift

Separating adaptation from drift: A cautionary tale from a self-fertilizing plant

Recommended by based on reviews by Pierre Olivier Cheptou, Jon Agren and Stefan Laurent

In recent years many studies have documented shifts in phenology in response to climate change, be it in arrival times in migrating birds, budset in trees, adult emergence in butterflies, or flowering time in annual plants (Coen et al. 2018; Piao et al. 2019). While these changes are, in part, explained by phenotypic plasticity, more and more studies find that they involve also genetic changes, that is, they involve evolutionary change (e.g., Metz et al. 2020). Yet, evolutionary change may occur through genetic drift as well as selection. Therefore, in order to demonstrate adaptive evolutionary change in response to climate change, drift has to be excluded as an alternative explanation (Hansen et al. 2012). A new study by Gay et al. (2021) shows just how difficult this can be. 

The authors investigated a recent evolutionary shift in flowering time by in a population an annual plant that reproduces predominantly by self-fertilization. The population has recently been subjected to increased temperatures and reduced rainfalls both of which are believed to select for earlier flowering times. They used a “resurrection” approach (Orsini et al. 2013; Weider et al. 2018): Genotypes from the past (resurrected from seeds) were compared alongside more recent genotypes (from more recently collected seeds) under identical conditions in the greenhouse. Using an experimental design that replicated genotypes, eliminated maternal effects, and controlled for microenvironmental variation, they found said genetic change in flowering times: Genotypes obtained from recently collected seeds flowered significantly (about 2 days) earlier than those obtained 22 generations before. However, neutral markers (microsatellites) also showed strong changes in allele frequencies across the 22 generations, suggesting that effective population size, Ne, was low (i.e., genetic drift was strong), which is typical for highly self-fertilizing populations. In addition, several multilocus genotypes were present at high frequencies and persisted over the 22 generations, almost as in clonal populations (e.g., Schaffner et al. 2019). The challenge was thus to evaluate whether the observed evolutionary change was the result of an adaptive response to selection or may be explained by drift alone. 

Here, Gay et al. (2021) took a particularly careful and thorough approach. First, they carried out a selection gradient analysis, finding that earlier-flowering plants produced more seeds than later-flowering plants. This suggests that, under greenhouse conditions, there was indeed selection for earlier flowering times. Second, investigating other populations from the same region (all populations are located on the Mediterranean island of Corsica, France), they found that a concurrent shift to earlier flowering times occurred also in these populations. Under the hypothesis that the populations can be regarded as independent replicates of the evolutionary process, the observation of concurrent shifts rules out genetic drift (under drift, the direction of change is expected to be random). 

The study may well have stopped here, concluding that there is good evidence for an adaptive response to selection for earlier flowering times in these self-fertilizing plants, at least under the hypothesis that selection gradients estimated in the greenhouse are relevant to field conditions. However, the authors went one step further. They used the change in the frequencies of the multilocus genotypes across the 22 generations as an estimate of realized fitness in the field and compared them to the phenotypic assays from the greenhouse. The results showed a tendency for high-fitness genotypes (positive frequency changes) to flower earlier and to produce more seeds than low-fitness genotypes. However, a simulation model showed that the observed correlations could be explained by drift alone, as long as Ne is lower than ca. 150 individuals. The findings were thus consistent with an adaptive evolutionary change in response to selection, but drift could only be excluded as the sole explanation if the effective population size was large enough. 

The study did provide two estimates of Ne (19 and 136 individuals, based on individual microsatellite loci or multilocus genotypes, respectively), but both are problematic. First, frequency changes over time may be influenced by the presence of a seed bank or by immigration from a genetically dissimilar population, which may lead to an underestimation of Ne (Wang and Whitlock 2003). Indeed, the low effective size inferred from the allele frequency changes at microsatellite loci appears to be inconsistent with levels of genetic diversity found in the population. Moreover, high self-fertilization reduces effective recombination and therefore leads to non-independence among loci. This lowers the precision of the Ne estimates (due to a higher sampling variance) and may also violate the assumption of neutrality due to the possibility of selection (e.g., due to inbreeding depression) at linked loci, which may be anywhere in the genome in case of high degrees of self-fertilization. 

There is thus no definite answer to the question of whether or not the observed changes in flowering time in this population were driven by selection. The study sets high standards for other, similar ones, in terms of thoroughness of the analyses and care in interpreting the findings. It also serves as a very instructive reminder to carefully check the assumptions when estimating neutral expectations, especially when working on species with complicated demographies or non-standard life cycles. Indeed the issues encountered here, in particular the difficulty of establishing neutral expectations in species with low effective recombination, may apply to many other species, including partially or fully asexual ones (Hartfield 2016). Furthermore, they may not be limited to estimating Ne but may also apply, for instance, to the establishment of neutral baselines for outlier analyses in genome scans (see e.g, Orsini et al. 2012). 


Cohen JM, Lajeunesse MJ, Rohr JR (2018) A global synthesis of animal phenological responses to climate change. Nature Climate Change, 8, 224–228.

Gay L, Dhinaut J, Jullien M, Vitalis R, Navascués M, Ranwez V, Ronfort J (2021) Evolution of flowering time in a selfing annual plant: Roles of adaptation and genetic drift. bioRxiv, 2020.08.21.261230, ver. 4 recommended and peer-reviewed by Peer Community in Evolutionary Biology.

Hansen MM, Olivieri I, Waller DM, Nielsen EE (2012) Monitoring adaptive genetic responses to environmental change. Molecular Ecology, 21, 1311–1329.

Hartfield M (2016) Evolutionary genetic consequences of facultative sex and outcrossing. Journal of Evolutionary Biology, 29, 5–22.

Metz J, Lampei C, Bäumler L, Bocherens H, Dittberner H, Henneberg L, Meaux J de, Tielbörger K (2020) Rapid adaptive evolution to drought in a subset of plant traits in a large-scale climate change experiment. Ecology Letters, 23, 1643–1653.

Orsini L, Schwenk K, De Meester L, Colbourne JK, Pfrender ME, Weider LJ (2013) The evolutionary time machine: using dormant propagules to forecast how populations can adapt to changing environments. Trends in Ecology & Evolution, 28, 274–282.

Orsini L, Spanier KI, Meester LD (2012) Genomic signature of natural and anthropogenic stress in wild populations of the waterflea Daphnia magna: validation in space, time and experimental evolution. Molecular Ecology, 21, 2160–2175.

Piao S, Liu Q, Chen A, Janssens IA, Fu Y, Dai J, Liu L, Lian X, Shen M, Zhu X (2019) Plant phenology and global climate change: Current progresses and challenges. Global Change Biology, 25, 1922–1940.

Schaffner LR, Govaert L, De Meester L, Ellner SP, Fairchild E, Miner BE, Rudstam LG, Spaak P, Hairston NG (2019) Consumer-resource dynamics is an eco-evolutionary process in a natural plankton community. Nature Ecology & Evolution, 3, 1351–1358.

Wang J, Whitlock MC (2003) Estimating Effective Population Size and Migration Rates From Genetic Samples Over Space and Time. Genetics, 163, 429–446. PMID: 12586728

Weider LJ, Jeyasingh PD, Frisch D (2018) Evolutionary aspects of resurrection ecology: Progress, scope, and applications—An overview. Evolutionary Applications, 11, 3–10.

17 May 2021
article picture

Relative time constraints improve molecular dating

Dating with constraints

Recommended by based on reviews by David Duchêne and 1 anonymous reviewer

Estimating the absolute age of diversification events is challenging, because molecular sequences provide timing information in units of substitutions, not years. Additionally, the rate of molecular evolution (in substitutions per year) can vary widely across lineages. Accurate dating of speciation events traditionally relies on non-molecular data. For very fast-evolving organisms such as SARS-CoV-2, for which samples are obtained over a time span, the collection times provide this external information from which we can learn the rate of molecular evolution and date past events (Boni et al. 2020). In groups for which the fossil record is abundant, state-of-the-art dating methods use fossil information to complement molecular data, either in the form of a prior distribution on node ages (Nguyen & Ho 2020), or as data modelled with a fossilization process (Heath et al. 2014).

Dating is a challenge in groups that lack fossils or other geological evidence, such as very old lineages and microbial lineages. In these groups, horizontal gene transfer (HGT) events have been identified as informative about relative dates: the ancestor of the gene's donor must be older than the descendants of the gene's recipient. Previous work using HGTs to date phylogenies have used methodologies that are ad-hoc (Davín et al 2018) or employ a small number of HGTs only (Magnabosco et al. 2018, Wolfe & Fournier 2018).

Szöllősi et al. (2021) present and validate a Bayesian approach to estimate the age of diversification events based on relative information on these ages, such as implied by HGTs. This approach is flexible because it is modular: constraints on relative node ages can be combined with absolute age information from fossil data, and with any substitution model of molecular evolution, including complex state-of-art models. To ease the computational burden, the authors also introduce a two-step approach, in which the complexity of estimating branch lengths in substitutions per site is decoupled from the complexity of timing the tree with branch lengths in years, accounting for uncertainty in the first step. Currently, one limitation is that the tree topology needs to be known, and another limitation is that constraints need to be certain. Users of this method should be mindful of the latter when hundreds of constraints are used, as done by Szöllősi et al. (2021) to date the trees of Cyanobacteria and Archaea.

Szöllősi et al. (2021)'s method is implemented in RevBayes, a highly modular platform for phylogenetic inference, rapidly growing in popularity (Höhna et al. 2016). The RevBayes tutorial page features a step-by-step tutorial "Dating with Relative Constraints", which makes the method highly approachable.


Boni MF, Lemey P, Jiang X, Lam TT-Y, Perry BW, Castoe TA, Rambaut A, Robertson DL (2020) Evolutionary origins of the SARS-CoV-2 sarbecovirus lineage responsible for the COVID-19 pandemic. Nature Microbiology, 5, 1408–1417.

Davín AA, Tannier E, Williams TA, Boussau B, Daubin V, Szöllősi GJ (2018) Gene transfers can date the tree of life. Nature Ecology & Evolution, 2, 904–909.

Heath TA, Huelsenbeck JP, Stadler T (2014) The fossilized birth–death process for coherent calibration of divergence-time estimates. Proceedings of the National Academy of Sciences, 111, E2957–E2966.

Höhna S, Landis MJ, Heath TA, Boussau B, Lartillot N, Moore BR, Huelsenbeck JP, Ronquist F (2016) RevBayes: Bayesian Phylogenetic Inference Using Graphical Models and an Interactive Model-Specification Language. Systematic Biology, 65, 726–736.

Magnabosco C, Moore KR, Wolfe JM, Fournier GP (2018) Dating phototrophic microbial lineages with reticulate gene histories. Geobiology, 16, 179–189.

Nguyen JMT, Ho SYW (2020) Calibrations from the Fossil Record. In: The Molecular Evolutionary Clock: Theory and Practice  (ed Ho SYW), pp. 117–133. Springer International Publishing, Cham.

Szollosi, G.J., Hoehna, S., Williams, T.A., Schrempf, D., Daubin, V., Boussau, B. (2021) Relative time constraints improve molecular dating. bioRxiv, 2020.10.17.343889, ver. 8  recommended and peer-reviewed by Peer Community in Evolutionary Biology.

Wolfe JM, Fournier GP (2018) Horizontal gene transfer constrains the timing of methanogen evolution. Nature Ecology & Evolution, 2, 897–903.

11 May 2021
article picture

Wolbachia load variation in Drosophila is more likely caused by drift than by host genetic factors

Drift rather than host or parasite control can explain within-host Wolbachia growth

Recommended by and based on reviews by Simon Fellous and 1 anonymous reviewer

Within-host parasite density is tightly linked to parasite fitness often determining both transmission success and virulence (parasite-induced harm to the host) (Alizon et al., 2009, Anderson & May, 1982). Parasite density may thus be controlled by selection balancing these conflicting pressures. Actual within-host density regulation may be under host or parasite control, or due to other environmental factors (Wale et al., 2019, Vale et al., 2011, Chrostek et al., 2013). Vertically transmitted parasites may also be more vulnerable to drift associated with bottlenecks between generations, which may also determine within-host population size (Mathe-Hubert et al., 2019, Mira & Moran, 2002).

Bénard et al. (2021) use 3 experiments to disentangle the role of drift versus host factors in the control of within-host Wolbachia growth in Drosophila melanogaster. They use the wMelPop Wolbachia strain in which virulence (fly longevity) and within-host growth correlate positively with copy number in the genomic region Octomom (Chrostek et al., 2013, Chrostek & Teixeira, 2015). Octomom copy number can be used as a marker for different genetic lineages within the wMelPop strain.

In a first experiment, they introgressed and backcrossed this Wolbachia strain into 6 different host genetic backgrounds and show striking differences in within-host symbiont densities which correlate positively with Octomom copy number. This is consistent with host genotype selecting different Wolbachia strains, but also with bottlenecks and drift between generations. To distinguish between these possibilities, they perform 2 further experiments. 

A second experiment repeated experiment 1, but this time introgression was into 3 independent lines of the Bolivia and USA Drosophila populations; those that, respectively, exhibited the lowest and highest Wolbachia density and Octomom copy number. In this experiment, growth and Octomom copy number were measured across the 3 lines, for each population, after 1, 13 and 25 generations. Although there were little differences between replicates at generation 1, there were differences at generations 13 and 25 among the replicates of both the Bolivia and USA lines. These results are indicative of parasite control, or drift being responsible for within-host growth rather than host factors. 

A third experiment tested whether Wolbachia density and copy number were under host or parasite control. This was done, again using the USA and Bolivia lines, but this time those from the first experiment, several generations following the initial introgression and backcrossing. The newly introgressed lines were again followed for 25 generations. At generation 1, Wolbachia phenotypes resembled those of the donor parasite population and not the recipient host population indicating a possible maternal effect, but a lack of host control over the parasite. Furthermore, Wolbachia densities and Octomom number differed among replicate lines through time for Bolivia populations and from the donor parasite lines for both populations. These differences among replicate lines that share both host and parasite origins suggest that drift and/or maternal effects are responsible for within-host Wolbachia density and Octomom number. 

These findings indicate that drift appears to play a role in shaping Wolbachia evolution in this system. Nevertheless, completely ruling out the role of the host or parasite in controlling densities will require further study. The findings of Bénard and coworkers (2021) should stimulate future work on the contribution of drift to the evolution of vertically transmitted parasites.


Alizon S, Hurford A, Mideo N, Baalen MV (2009) Virulence evolution and the trade-off hypothesis: history, current state of affairs and the future. Journal of Evolutionary Biology, 22, 245–259.

Anderson RM, May RM (1982) Coevolution of hosts and parasites. Parasitology, 85, 411–426.

Bénard A, Henri H, Noûs C, Vavre F, Kremer N (2021) Wolbachia load variation in Drosophila is more likely caused by drift than by host genetic factors. bioRxiv, 2020.11.29.402545, ver. 4  recommended and peer-reviewed by Peer Community in Evolutionary Biology.

Chrostek E, Marialva MSP, Esteves SS, Weinert LA, Martinez J, Jiggins FM, Teixeira L (2013) Wolbachia Variants Induce Differential Protection to Viruses in Drosophila melanogaster: A Phenotypic and Phylogenomic Analysis. PLOS Genetics, 9, e1003896.

Chrostek E, Teixeira L (2015) Mutualism Breakdown by Amplification of Wolbachia Genes. PLOS Biology, 13, e1002065.

Mathé‐Hubert H, Kaech H, Hertaeg C, Jaenike J, Vorburger C (2019) Nonrandom associations of maternally transmitted symbionts in insects: The roles of drift versus biased cotransmission and selection. Molecular Ecology, 28, 5330–5346.

Mira A, Moran NA (2002) Estimating Population Size and Transmission Bottlenecks in Maternally Transmitted Endosymbiotic Bacteria. Microbial Ecology, 44, 137–143.

Vale PF, Wilson AJ, Best A, Boots M, Little TJ (2011) Epidemiological, Evolutionary, and Coevolutionary Implications of Context-Dependent Parasitism. The American Naturalist, 177, 510–521.

Wale N, Jones MJ, Sim DG, Read AF, King AA (2019) The contribution of host cell-directed vs. parasite-directed immunity to the disease and dynamics of malaria infections. Proceedings of the National Academy of Sciences, 116, 22386–22392.


14 Apr 2021
article picture

Parasitic success and venom composition evolve upon specialization of parasitoid wasps to different host species

What makes a parasite successful? Parasitoid wasp venoms evolve rapidly in a host-specific manner

Recommended by based on reviews by Simon Fellous, alexandre leitão and 1 anonymous reviewer

Parasitoid wasps have developed different mechanisms to increase their parasitic success, usually at the expense of host survival (Fellowes and Godfray, 2000). Eggs of these insects are deposited inside the juvenile stages of their hosts, which in turn deploy several immune response strategies to eliminate or disable them (Yang et al., 2020). Drosophila melanogaster protects itself against parasitoid attacks through the production of specific elongated haemocytes called lamellocytes which form a capsule around the invading parasite (Lavine and Strand, 2002; Rizki and Rizki, 1992) and the subsequent activation of the phenol-oxidase cascade leading to the release of toxic radicals (Nappi et al., 1995). On the parasitoid side, robust responses have evolved to evade host immune defenses as for example the Drosophila-specific endoparasite Leptopilina boulardi, which releases venom during oviposition that modifies host behaviour (Varaldi et al., 2006) and inhibits encapsulation (Gueguen et al., 2011; Martinez et al., 2012).
Studies have shown that the wasp parasitic capacity is correlated to venom presence and its content (Colinet et al., 2009; Poirié et al., 2014), including that evolution of venom protein composition is driven by different levels of host susceptibility to infection (Cavigliasso et al., 2019). However, it had not been determined to this day, if and how parasitic range can affect venom protein composition and to which extent host specialization requires broad-spectrum factors or a plethora of specialized components.
These outstanding questions are now approached in a study by Cavigliasso and colleagues (Cavigliasso et al., 2021), where they perform experimental evolution of L. boulardi for 9 generations exposing it to different Drosophila host species and genetic backgrounds (two strains of D. melanogaster, D. simulans and D. yakuba). The authors tested whether the parasitic success of each selection regime was host-specific and how they influenced venom composition in parasitoids. For the first part, infection outcomes were assayed for each selection regime when cross-infecting different hosts. To get a finer measurement of the mechanisms under selection, the authors differentiated three phenotypes: overall parasitic success, encapsulation inhibition and escape from capsule. Throughout the course of experimental evolution, only encapsulation inhibition did not show an improved response upon selection on any host. Importantly, the cross-infection scenario revealed a clear specificity to the selected host for each evolved resistance.
As for venom composition, a trend of differential evolution was detected between host species, although a significant part of that was due to a larger differentiation in the D. yakuba regime, which showed a completely different directionality. Importantly, the authors could identify some of the specific proteins targeted by the several selection regimes, whether selected or counter-selected for. Interestingly, the D. yakuba regime is the only case where the key parasitoid protein LbSPNy (Colinet et al., 2009) was not counter-selected and the only regime in which the overall venom composition did not evolve towards the Ism strain, one of the two ancestral strains of L. boulardi used in the study. It is possible that these two results are correlated, since LbSPNy has been described to inhibit activation of the phenoloxidase cascade in D. yakuba and is one of the most abundant proteins in the ISy venom, making it a good target for selection (Colinet et al., 2013). The authors also discuss the possibility that this difference is related to the geographical distribution of the strains of L. boulardi, since each coincide with either D. melanogaster or D. yakuba.
This methodologically broad work by Cavigliasso and colleagues constitutes an important experimental contribution towards the understanding of how parasitoid adaptation to specific hosts is achieved at different phenotypic and mechanistic levels. It provides compelling evidence that venom composition evolves differently in response to specific parasitic ranges, particularly considering the evolutionary difference between the selective hosts. In line with this result, it is also concluded that the majority of venom proteins selected are lineage-specific, although a few broad-spectrum factors could also be detected. 
The question of whether parasitic range can affect venom composition and parasitic success is still open to more contributions. A potentially interesting long-term direction will be to use a similar setup of experimental evolution on the generalist L. heterotoma (Schlenke et al., 2007) . On a more immediate horizon, comparing the venom evolution of both L. heterotoma and L. boulardi under selection with different hosts and under cross-infection scenarios could reveal interesting patterns. The recent sequencing of the L. boulardi genome together with the vast number of studies addressing mechanisms of Drosophila resistance to parasitoid infection, will enable the thorough characterization of the genetic basis of host-parasitoid interactions and the deeper understanding of these ubiquitous and economically-relevant relationships.
*This recommendation text has been co-written with Tânia F. Paulo who is not a recommender of PCI Evol Biol



Cavigliasso, F., Mathé-Hubert, H., Gatti, J.-L., Colinet, D. and Poirié, M. (2021) Parasitic success and venom composition evolve upon specialization of parasitoid wasps to different host species. bioRxiv, 2020.10.24.353417, ver. 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology.

Cavigliasso, F., Mathé-Hubert, H., Kremmer, L., Rebuf, C., Gatti, J.-L., Malausa, T., Colinet, D., Poiré, M. and  Léne. (2019). Rapid and Differential Evolution of the Venom Composition of a Parasitoid Wasp Depending on the Host Strain. Toxins, 11(629).

Colinet, D., Deleury, E., Anselme, C., Cazes, D., Poulain, J., Azema-Dossat, C., Belghazi, M., Gatti, J. L. and  Poirié, M. (2013). Extensive inter- and intraspecific venom variation in closely related parasites targeting the same host: The case of Leptopilina parasitoids of Drosophila. Insect Biochemistry and Molecular Biology, 43(7), 601–611.

Colinet, D., Dubuffet, A., Cazes, D., Moreau, S., Drezen, J. M. and  Poirié, M. (2009). A serpin from the parasitoid wasp Leptopilina boulardi targets the Drosophila phenoloxidase cascade. Developmental and Comparative Immunology, 33(5), 681–689.

Fellowes, M. D. E. and  Godfray, H. C. J. (2000). The evolutionary ecology of resistance to parasitoids by Drosophila. Heredity, 84(1), 1–8.

Gueguen, G., Rajwani, R., Paddibhatla, I., Morales, J. and  Govind, S. (2011). VLPs of Leptopilina boulardi share biogenesis and overall stellate morphology with VLPs of the heterotoma clade. Virus Research, 160(1–2), 159–165.

Lavine, M. D. and  Strand, M. R. (2002). Insect hemocytes and their role in immunity. Insect Biochemistry and Molecular Biology, 32(10), 1295–1309.

Martinez, J., Duplouy, A., Woolfit, M., Vavre, F., O’Neill, S. L. and  Varaldi, J. (2012). Influence of the virus LbFV and of Wolbachia in a host-parasitoid interaction. PloS One, 7(4), e35081.

Nappi, A. J., Vass, E., Frey, F. and  Carton, Y. (1995). Superoxide anion generation in Drosophila during melanotic encapsulation of parasites. European Journal of Cell Biology, 68(4), 450–456.

Poirié, M., Colinet, D. and  Gatti, J. L. (2014). Insights into function and evolution of parasitoid wasp venoms. Current Opinion in Insect Science, 6, 52–60.

Rizki, T. M. and  Rizki, R. M. (1992). Lamellocyte differentiation in Drosophila larvae parasitized by Leptopilina. Developmental and Comparative Immunology, 16(2–3), 103–110.

Schlenke, T. A., Morales, J., Govind, S. and  Clark, A. G. (2007). Contrasting infection strategies in generalist and specialist wasp parasitoids of Drosophila melanogaster. PLoS Pathogens, 3(10), 1486–1501.

Varaldi, J., Petit, S., Boulétreau, M. and  Fleury, F. (2006). The virus infecting the parasitoid Leptopilina boulardi exerts a specific action on superparasitism behaviour. Parasitology, 132(Pt 6), 747–756.

Yang, L., Qiu, L., Fang, Q., Stanley, D. W. and  Gong‐Yin, Y. (2020). Cellular and humoral immune interactions between Drosophila and its parasitoids. Insect Science.


06 Apr 2021
article picture

How robust are cross-population signatures of polygenic adaptation in humans?

Be careful when studying selection based on polygenic score overdispersion

Recommended by based on reviews by Lawrence Uricchio, Mashaal Sohail, Barbara Bitarello and 1 anonymous reviewer

The advent of genome-wide association studies (GWAS) has been a great promise for our understanding of the connection between genotype and phenotype. Today, the NHGRI-EBI GWAS catalog contains 251,401 associations from 4,961 studies (1). This wealth of studies has also generated interest to use the summary statistics beyond the few top hits in order to make predictions for individuals without known phenotype, e.g. to predict polygenic risk scores or to study polygenic selection by comparing different groups. For instance, polygenic selection acting on the most studied polygenic trait, height, has been subject to multiple studies during the past decade (e.g. 2–6). They detected north-south gradients in Europe which were consistent with expectations. However, their GWAS summary statistics were based on the GIANT consortium data set, a meta-analysis of GWAS conducted in different European cohorts (7,8). The availability of large data sets with less stratification such as the UK Biobank (9) has led to a re-evaluation of those results. The nature of the GIANT consortium data set was realized to represent a potential problem for studies of polygenic adaptation which led several of the authors of the original articles to caution against the interpretations of polygenic selection on height (10,11). This was a great example on how the scientific community assessed their own earlier results in a critical way as more data became available. At the same time it left the question whether there is detectable polygenic selection separating populations more open than ever.

Generally, recent years have seen several articles critically assessing the portability of GWAS results and risk score predictions to other populations (12–14). Refoyo-Martínez et al. (15) are now presenting a systematic assessment on the robustness of cross-population signatures of polygenic adaptation in humans. They compiled GWAS results for complex traits which have been studied in more than one cohort and then use allele frequencies from the 1000 Genomes Project data (16) set to detect signals of polygenic score overdispersion. As the source for the allele frequencies is kept the same across all tests, differences between the signals must be caused by the underlying GWAS. The results are concerning as the level of overdispersion largely depends on the choice of GWAS cohort. Cohorts with homogenous ancestries show little to no overdispersion compared to cohorts of mixed ancestries such as meta-analyses. It appears that the meta-analyses fail to fully account for stratification in their data sets.

The authors based most of their analyses on the heavily studied trait height. Additionally, they use educational attainment (measured as the number of school years of an individual) as an example. This choice was due to the potential over- or misinterpretation of results by the media, the general public and by far right hate groups. Such traits are potentially confounded by unaccounted cultural and socio-economic factors. Showing that previous results about polygenic selection on educational attainment are not robust is an important result that needs to be communicated well. This forms a great example for everyone working in human genomics. We need to be aware that our results can sometimes be misinterpreted. And we need to make an effort to write our papers and communicate our results in a way that is honest about the limitations of our research and that prevents the misuse of our results by hate groups.

This article represents an important contribution to the field. It is cruicial to be aware of potential methodological biases and technical artifacts. Future studies of polygenic adaptation need to be cautious with their interpretations of polygenic score overdispersion. A recommendation would be to use GWAS results obtained in homogenous cohorts. But even if different biobank-scale cohorts of homogeneous ancestry are employed, there will always be some remaining risk of unaccounted stratification. These conclusions may seem sobering but they are part of the scientific process. We need additional controls and new, different methods than polygenic score overdispersion for assessing polygenic selection. Last year also saw the presentation of a novel approach using sequence data and GWAS summary statistics to detect directional selection on a polygenic trait (17). This new method appears to be robust to bias stemming from stratification in the GWAS cohort as well as other confounding factors. Such new developments show light at the end of the tunnel for the use of GWAS summary statistics in the study of polygenic adaptation.


1. Buniello A, MacArthur JAL, Cerezo M, Harris LW, Hayhurst J, Malangone C, et al. The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019. Nucleic Acids Research. 2019 Jan 8;47(D1):D1005–12. doi:

2. Turchin MC, Chiang CW, Palmer CD, Sankararaman S, Reich D, Hirschhorn JN. Evidence of widespread selection on standing variation in Europe at height-associated SNPs. Nature Genetics. 2012 Sep;44(9):1015–9. doi:

3. Berg JJ, Coop G. A Population Genetic Signal of Polygenic Adaptation. PLOS Genetics. 2014 Aug 7;10(8):e1004412. doi:

4. Robinson MR, Hemani G, Medina-Gomez C, Mezzavilla M, Esko T, Shakhbazov K, et al. Population genetic differentiation of height and body mass index across Europe. Nature Genetics. 2015 Nov;47(11):1357–62. doi:

5. Mathieson I, Lazaridis I, Rohland N, Mallick S, Patterson N, Roodenberg SA, et al. Genome-wide patterns of selection in 230 ancient Eurasians. Nature. 2015 Dec;528(7583):499–503. doi:

6. Racimo F, Berg JJ, Pickrell JK. Detecting polygenic adaptation in admixture graphs. Genetics. 2018. Arp;208(4):1565–1584. doi:

7. Lango Allen H, Estrada K, Lettre G, Berndt SI, Weedon MN, Rivadeneira F, et al. Hundreds of variants clustered in genomic loci and biological pathways affect human height. Nature. 2010 Oct;467(7317):832–8. doi:

8. Wood AR, Esko T, Yang J, Vedantam S, Pers TH, Gustafsson S, et al. Defining the role of common variation in the genomic and biological architecture of adult human height. Nat Genet. 2014 Nov;46(11):1173–86. doi:

9. Bycroft C, Freeman C, Petkova D, Band G, Elliott LT, Sharp K, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature. 2018 Oct;562(7726):203–9. doi:

10. Berg JJ, Harpak A, Sinnott-Armstrong N, Joergensen AM, Mostafavi H, Field Y, et al. Reduced signal for polygenic adaptation of height in UK Biobank. eLife. 2019 Mar 21;8:e39725. doi:

11. Sohail M, Maier RM, Ganna A, Bloemendal A, Martin AR, Turchin MC, et al. Polygenic adaptation on height is overestimated due to uncorrected stratification in genome-wide association studies. eLife. 2019 Mar 21;8:e39702. doi:

12. Martin AR, Kanai M, Kamatani Y, Okada Y, Neale BM, Daly MJ. Clinical use of current polygenic risk scores may exacerbate health disparities. Nature Genetics. 2019 Apr;51(4):584–91. doi:

13. Bitarello BD, Mathieson I. Polygenic Scores for Height in Admixed Populations. G3: Genes, Genomes, Genetics. 2020 Nov 1;10(11):4027–36. doi:

14. Uricchio LH, Kitano HC, Gusev A, Zaitlen NA. An evolutionary compass for detecting signals of polygenic selection and mutational bias. Evolution Letters. 2019;3(1):69–79. doi:

15. Refoyo-Martínez A, Liu S, Jørgensen AM, Jin X, Albrechtsen A, Martin AR, Racimo F. How robust are cross-population signatures of polygenic adaptation in humans? bioRxiv, 2021, 2020.07.13.200030, version 5 peer-reviewed and recommended by Peer community in Evolutionary Biology. doi:

16. Auton A, Abecasis GR, Altshuler DM, Durbin RM, Abecasis GR, Bentley DR, et al. A global reference for human genetic variation. Nature. 2015 Sep 30;526(7571):68–74. doi:

17. Stern AJ, Speidel L, Zaitlen NA, Nielsen R. Disentangling selection on genetically correlated polygenic traits using whole-genome genealogies. bioRxiv. 2020 May 8;2020.05.07.083402. doi:

04 Mar 2021
article picture

Simulation of bacterial populations with SLiM

Simulating bacterial evolution forward-in-time

Recommended by based on reviews by 3 anonymous reviewers

Jean Cury and colleagues (2021) have developed a protocol to simulate bacterial evolution in SLiM. In contrast to existing methods that depend on the coalescent, SLiM simulates evolution forward in time. SLiM has, up to now, mostly been used to simulate the evolution of eukaryotes (Haller and Messer 2019), but has been adapted here to simulate evolution in bacteria. Forward-in-time simulations are usually computationally very costly. To circumvent this issue, bacterial population sizes are scaled down. One would now expect results to become inaccurate, however, Cury et al. show that scaled-down forwards simulations provide very accurate results (similar to those provided by coalescent simulators) that are consistent with theoretical expectations. Simulations were analyzed and compared to existing methods in simple and slightly more complex scenarios where recombination affects evolution. In all scenarios, simulation results from coalescent methods (fastSimBac (De Maio and Wilson 2017), ms (Hudson 2002)) and scaled-down forwards simulations were very similar, which is very good news indeed.

A biologist not aware of the complexities of forwards, backwards simulations and the coalescent, might now naïvely ask why another simulation method is needed if existing methods perform just as well. To address this question the manuscript closes with a very neat example of what exactly is possible with forwards simulations that cannot be achieved using existing methods. The situation modeled is the growth and evolution of a set of 50 bacteria that are randomly distributed on a petri dish. One side of the petri dish is covered in an antibiotic the other is antibiotic-free. Over time, the bacteria grow and acquire antibiotic resistance mutations until the entire artificial petri dish is covered with a bacterial lawn. This simulation demonstrates that it is possible to simulate extremely complex (e.g. real world) scenarios to, for example, assess whether certain phenomena are expected with our current understanding of bacterial evolution, or whether there are additional forces that need to be taken into account. Hence, forwards simulators could significantly help us to understand what current models can and cannot explain in evolutionary biology.  



Cury J, Haller BC, Achaz G, Jay F (2021) Simulation of bacterial populations with SLiM. bioRxiv, 2020.09.28.316869, version 5 peer-reviewed and recommended by Peer community in Evolutionary Biology.

De Maio N, Wilson DJ (2017) The Bacterial Sequential Markov Coalescent. Genetics, 206, 333–343.

Haller BC, Messer PW (2019) SLiM 3: Forward Genetic Simulations Beyond the Wright–Fisher Model. Molecular Biology and Evolution, 36, 632–637.

Hudson RR (2002) Generating samples under a Wright–Fisher neutral model of genetic variation. Bioinformatics, 18, 337–338.

01 Mar 2021
article picture

Social Conflicts in Dictyostelium discoideum : A Matter of Scales

The cell-level perspective in social conflicts in Dictyostelium discoideum

Recommended by based on reviews by Peter Conlin and Matthew Herron

The social amoeba Dictyostelium discoideum is an important model system for the study of cooperation and multicellularity as is has both unicellular and aggregative life phases. In the aggregative phase, which typically occurs when nutrients are limiting, individual cells eventually gather together to form a fruiting bodies whose spores may be dispersed to another, better, location and whose stalk cells, which support the spores, die. This extreme form of cooperation has been the focus of numerous studies that have revealed the importance genetic relatedness and kin selection (Hamilton 1964; Lehmann and Rousset 2014) in explaining the maintenance of this cooperative collective behavior (Strassmann et al. 2000; Kuzdzal-Fick et al. 2011; Strassmann and Queller 2011). However, much remains unknown with respect to how the interactions between individual cells, their neighbors, and their environment produce cooperative behavior at the scale of whole groups or collectives. In this preprint, Forget et al. (2021) describe how the D. discoideum system is crucial in this respect because it allows these cellular-level interactions to be studied in a systematic and tractable manner.
Spore bias, which is the tendency of a particular genotype or strain to disproportionately migrate to the spore instead of the stalk, is often used to define which strains are "cheaters" (positive spore bias) and which are "cooperative" (negative spore bias). Forget et al. (2021) note that spore bias depends on a number of stochastic factors including external drivers such as variation in environmental (or nutrient) quality and internal drivers like cell-cycle phase at the time of starvation. Spore bias is also affected by the social environment where the fraction of cheater strains in a spore may be limited by the ability of the remaining stalk cells to support the spore. The social environment can also affect cells through their differential responsiveness to the chemical factors that induce differentiation into stalk cells; responsiveness is partly a function of nutrient quality (Thompson and Kay 2000), which in turn can be a function of cell density. Thus, Forget et al. (2021) highlight a number of mechanisms that could generate frequency-dependent selection that would lead to the stable maintenance of multiple strains with different spore biases; in other words, both cheater and cooperative strains might stably coexist due to these cellular-level interactions.
The cellular-level interactions that Forget et al. (2021) highlight are particularly important because they pose a challenge evolutionary theory: some evolutionary models of social and collective behavior neglect or simplify these interactions. For example, Forget et al. (2021) note that the developmental, behavior, and environmental timescales relevant for Dictyostelium fruiting body formation all overlap. Evolutionary analyses often assume some of these timescales, for example developmental and behavior, are separate in order to simplify the analysis of any interactions. Thus, new theoretical work that allows these timescales to overlap may shed light on how cellular-level interactions can produce environmental, physiological, and behavioral feedbacks that drive the evolution of cooperation and other collective behaviors.


Forget, M., Adiba, S. and De Monte, S.(2021) Social conflicts in *Dictyostelium discoideum *: a matter of scales. HAL, hal-03088868, ver. 2 peer-reviewed and recommended by PCI Evolutionary Biology.

Hamilton, W. D. (1964). The genetical evolution of social behaviour. II. Journal of theoretical biology, 7(1), 17-52. doi:

Kuzdzal-Fick, J. J., Fox, S. A., Strassmann, J. E., and Queller, D. C. (2011). High relatedness is necessary and sufficient to maintain multicellularity in Dictyostelium. Science, 334(6062), 1548-1551. doi:

Lehmann, L., and Rousset, F. (2014). The genetical theory of social behaviour. Philosophical Transactions of the Royal Society B: Biological Sciences, 369(1642), 20130357. doi:

Strassmann, J. E., and Queller, D. C. (2011). Evolution of cooperation and control of cheating in a social microbe. Proceedings of the National Academy of Sciences, 108(Supplement 2), 10855-10862. doi:

Strassmann, J. E., Zhu, Y., & Queller, D. C. (2000). Altruism and social cheating in the social amoeba Dictyostelium discoideum. Nature, 408(6815), 965-967. doi:

Thompson, C. R., & Kay, R. R. (2000). Cell-fate choice in Dictyostelium: intrinsic biases modulate sensitivity to DIF signaling. Developmental biology, 227(1), 56-64. doi:

25 Feb 2021
article picture

Alteration of gut microbiota with a broad-spectrum antibiotic does not impair maternal care in the European earwig

Assessing the role of host-symbiont interactions in maternal care behaviour

Recommended by based on reviews by Nadia Aubin-Horth, Gabrielle Davidson and 1 anonymous reviewer

The role of microbial symbionts in governing social traits of their hosts is an exciting and developing research area. Just like symbionts influence host reproductive behaviour and can cause mating incompatibilities to promote symbiont transmission through host populations (Engelstadter and Hurst 2009; Correa and Ballard 2016; Johnson and Foster 2018) (see also discussion on conflict resolution in Johnsen and Foster 2018), microbial symbionts could enhance transmission by promoting the social behaviour of their hosts (Ezenwa et al. 2012; Lewin-Epstein et al. 2017; Gurevich et al. 2020). Here I apply the term ‘symbiosis’ in the broad sense, following De Bary 1879 as “the living together of two differently named organisms“ independent of effects on the organisms involved (De Bary 1879), i.e. the biological interaction between the host and its symbionts may include mutualism, parasitism and commensalism.
So far, we have relative few studies that explore the role of symbionts in promoting social behaviours such as parental care. Clearly, disentangling cause and effect when assessing the functional significance of symbiotic relationships in general is extremely challenging, and perhaps even more caution is needed when assessing the role of symbionts in the evolution of parental care, given the high fitness benefits to the offspring of receiving care. An interesting study on the symbiotic relationship between termites and their eukaryotic gut symbionts proposes a role of gut flagellates in the origin of subsocial behaviour (extended offspring care) in the termites through proctodeal trophallaxis (i.e. anus-to-mouth feeding), driven by mutualistic beneficial interactions (Nalepa 2020). Van Meyel et al. (2021) hypothesized a role of gut symbionts in promoting maternal care behaviour in the European earwig, and set out to test this idea in a carefully executed experimental study. They used a broad-spectrum antibiotic treatment to alter gut microbiota in mothers and examined its effect on maternal care provisioning. While the antibiotic treatment altered the gut microbiome, no effect on pre- or post-hatching maternal care was detected. The authors also investigated a broad range of physiological and reproductive traits measured over a major part of a female’s lifetime, and detected no effect of microbiome alteration on these traits. The study therefore does not provide evidence for a direct role of the gut microbiome in shaping offspring care in this population of European earwigs.
Within populations, earwigs show inter-individual variation in the expression of maternal care (Meunier et al. 2012; Ratz et al. 2016), and there is evidence that genetic and environmental factors contribute to this this variation (Meunier and Kolliker 2012; Kramer et al. 2017). The study by Van Meyel et al. (2021) is the first to analyse microbiome composition of the European earwig, and they study host-symbiont associations in a single population. A next step could be to explore among population variation in the gut microbiome, to achieve a better understanding on host-microbiome variation and dynamics in wild populations. Depending on the nature of host-symbiont associations across populations, new perspectives on their functional significance may arise (Hird 2017; Johnson and Foster 2018). It is therefore too early to conclusively confirm or reject the role of microbial symbionts in the expression of parental care in this system.


Correa, C. C., and Ballard, J. W. O. (2016). Wolbachia associations with insects: winning or losing against a master manipulator. Frontiers in Ecology and Evolution, 3, 153. doi:

De Bary, A. (1879). Die Erscheinung der Symbiose. Verlag von Karl J. Trubner, Strassburg.

Engelstädter, J., and Hurst, G. D. (2009). The ecology and evolution of microbes that manipulate host reproduction. Annual Review of Ecology, Evolution, and Systematics, 40, 127-149. doi:

Ezenwa, V. O., Gerardo, N. M., Inouye, D. W., Medina, M., and Xavier, J. B. (2012). Animal behavior and the microbiome. Science, 338(6104), 198-199. doi:

Gurevich, Y., Lewin-Epstein, O., and Hadany, L. (2020). The evolution of paternal care: a role for microbes?. Philosophical Transactions of the Royal Society B, 375(1808), 20190599. doi:

Hird, S. M. (2017). Evolutionary biology needs wild microbiomes. Frontiers in microbiology, 8, 725. doi:

Johnson, K. V. A., and Foster, K. R. (2018). Why does the microbiome affect behaviour?. Nature reviews microbiology, 16(10), 647-655. doi:

Kramer et al. (2017). When earwig mothers do not care to share: parent–offspring competition and the evolution of family life. Functional Ecology, 31(11), 2098-2107. doi:

Lewin-Epstein, O., Aharonov, R., and Hadany, L. (2017). Microbes can help explain the evolution of host altruism. Nature communications, 8(1), 1-7. doi:

Meunier, J., and Kölliker, M. (2012). Parental antagonism and parent–offspring co-adaptation interact to shape family life. Proceedings of the Royal Society B: Biological Sciences, 279(1744), 3981-3988. doi:

Meunier, J., Wong, J. W., Gómez, Y., Kuttler, S., Röllin, L., Stucki, D., and Kölliker, M. (2012). One clutch or two clutches? Fitness correlates of coexisting alternative female life-histories in the European earwig. Evolutionary Ecology, 26(3), 669-682. doi:

Nalepa, C. A. (2020). Origin of mutualism between termites and flagellated gut protists: transition from horizontal to vertical transmission. Frontiers in Ecology and Evolution, 8, 14. doi:

Ratz, T., Kramer, J., Veuille, M., and Meunier, J. (2016). The population determines whether and how life-history traits vary between reproductive events in an insect with maternal care. Oecologia, 182(2), 443-452. doi:

Van Meyel, S., Devers, S., Dupont, S., Dedeine, F. and Meunier, J. (2021) Alteration of gut microbiota with a broad-spectrum antibiotic does not impair maternal care in the European earwig. bioRxiv, 2020.10.08.331363. ver. 5 peer-reviewed and recommended by PCI Evol Biol.

05 Feb 2021
article picture

Relaxation of purifying selection suggests low effective population size in eusocial Hymenoptera and solitary pollinating bees

Multi-gene and lineage comparative assessment of the strength of selection in Hymenoptera

Recommended by based on reviews by Michael Lattorff and 1 anonymous reviewer

Genetic variation is the raw material for selection to act upon and the amount of genetic variation present within a population is a pivotal determinant of a population’s evolutionary potential. A large effective population size, i.e., the ideal number of individuals experiencing the same amount of genetic drift and inbreeding as an actual population, Ne (Wright 1931, Crow 1954), thus increases the probability of long-term survival of a population. However, natural populations, as opposed to theoretical ones, rarely adhere to the requirements of an ideal panmictic population (Sjödin et al. 2005). A range of circumstances can reduce Ne, including the structuring of populations (through space and time, as well as age and developmental stages) and inbreeding (Charlesworth 2009). In mammals, species with a larger body mass (as a proxy for lower Ne) were found to have a higher rate of nonsynonymous nucleotide substitutions (that alter the amino acid sequence of a protein), as well as radical amino acid substitutions (altering the physicochemical properties of a protein) (Popadin et al. 2007). In general, low effective population sizes increase the chance of mutation accumulation and drift, while reducing the strength of selection (Sjödin et al. 2005).
In this paper, Weyna and Romiguier (2021) set out to test if parasitism, body size, geographic range, and/or eusociality affect the strength of selection in Hymenoptera. Hymenoptera include the bees, wasps and ants and is an extraordinarily diverse order within the insects. It was recently estimated that Hymenoptera is the most speciose order of the animal kingdom (Forbes et al. 2018). Hymenoptera are further characterized by an impressive radiation of parasitic species, mainly parasitoids, that feed in or on a single host individual to complete their own development (Godfray 1994). All hymenopterans share the same sex determination system: haplo-diploidy, where unfertilized eggs are haploid males and fertilized eggs are diploid females. Compared to other animals, Hymenoptera further contain an impressive number of clades that evolved eusociality (Rehan and Toth 2015), in which societies show a clear division of labor for reproduction (i.e., castes) and cooperative brood care. Hymenopterans thus represent a diverse and interesting group of insects to investigate potential factors affecting strength of selection and Ne.
Using a previously published phylogenomic dataset containing 3256 genes and 169 hymenopteran species (Peters et al. 2017), Weyna and Romiguier (2021) estimated mean genomic dN/dS ratios (nonsynonymous to synonymous substitution rates) for each species and compared these values between parasitic and non-parasitic species, eusocial and solitary species, and in relation to body size, parasitoid-specific traits and geographic range, thought to affect the effective population size and strength of selection. The use of a large number of species, as well as several distinct traits is a clear asset of this study. The authors found no effect of body size, geographic range or parasitism (including a range of parasitoid-specific traits). There was an effect, however, of eusociality where dN/dS increased in three out of four eusocial lineages. Future studies including more independent evolutionary transitions to eusociality can lend further support that eusocial species indeed reduces the efficiency of selection. The most intriguing result was that for solitary and social bees, with high dN/dS ratios and a strong signature of relaxed selection (i.e., the elimination or reduction of a source of selection (Lahti et al. 2009). The authors suggest that the pollen-collecting behaviors of these species can constrain Ne, as pollen availability varies at both a spatial and temporal scale, requiring a large investment in foraging that may in turn limit reproductive output. It would be interesting to see if other pollen feeders, such as certain beetles, flies, butterflies and moths, as well as mites and spiders, experience relaxed selection as a consequence of the trade-off between energy investment in pollen foraging versus fecundity.


Charlesworth, B. (2009). Effective population size and patterns of molecular evolution and variation. Nature Reviews Genetics, 10(3), 195-205. doi:
Crow, J. F. (1954) Statistics and Mathematics in Biology (eds Kempthorne, O., Bancroft, T. A., Gowen, J. W. & Lush, J. L.) 543–556 (Iowa State Univ. Press, Ames, Iowa)
Forbes, A. A., Bagley, R. K., Beer, M. A., Hippee, A. C., and Widmayer, H. A. (2018). Quantifying the unquantifiable: why Hymenoptera, not Coleoptera, is the most speciose animal order. BMC ecology, 18(1), 1-11. doi:
Godfray, H. C. J. (1994) Parasitoids: Behavioral and Evolutionary Ecology. Vol. 67, Princeton University Press, 1994. doi:
Lahti et al. (2009). Relaxed selection in the wild. Trends in ecology & evolution, 24(9), 487-496. doi:
Peters et al. (2017). Evolutionary history of the Hymenoptera. Current Biology, 27(7), 1013-1018. doi:
Popadin, K., Polishchuk, L. V., Mamirova, L., Knorre, D., and Gunbin, K. (2007). Accumulation of slightly deleterious mutations in mitochondrial protein-coding genes of large versus small mammals. Proceedings of the National Academy of Sciences, 104(33), 13390-13395. doi:
Rehan, S. M., and Toth, A. L. (2015). Climbing the social ladder: the molecular evolution of sociality. Trends in ecology & evolution, 30(7), 426-433. doi:
Sjödin, P., Kaj, I., Krone, S., Lascoux, M., and Nordborg, M. (2005). On the meaning and existence of an effective population size. Genetics, 169(2), 1061-1070. doi:
Weyna, A., and Romiguier, J. (2021) Relaxation of purifying selection suggests low effective population size in eusocial Hymenoptera and solitary pollinating bees. bioRxiv, 2020.04.14.038893, ver. 5 peer-reviewed and recommended by PCI Evol Biol. doi:
Wright, S. (1931). Evolution in Mendelian populations. Genetics, 16(2), 97-159.

18 Jan 2021
article picture

Trait plasticity and covariance along a continuous soil moisture gradient

Another step towards grasping the complexity of the environmental response of traits

Recommended by based on reviews by 2 anonymous reviewers

One can only hope that one day, we will be able to evaluate how the ecological complexity surrounding natural populations affects their ability to adapt. This is more like a long term quest than a simple scientific aim. Many steps are heading in the right direction. This paper by Monroe and colleagues (2021) is one of them.
Many ecological and genetic mechanisms shape the evolutionary potential of phenotypic trait variation and many of them involve environmental heterogeneity (Pujol et al 2018). To date, we cannot look into these ecological and genetic mechanisms without oversimplifying their effects. We often look into trait variation one trait at a time albeit the variation of multiple phenotypic traits is often linked at the genetic or environmental level. As a consequence, we put our conclusions at risk by not accounting for the reciprocal impacts of trait changes upon each other (Teplitsky et al 2014). We also usually restrict the study of a continuous gradient of environmental conditions to a few conditions because it would otherwise be impossible to model its environmental effect. As a consequence, we miss the full picture of the continuous often nonlinear phenotypic plastic response. Whether the trait undergo threshold effect changes thereby remains obscured to us. Collectively, these issues impede our ability to understand how selection shapes the ecological strategy of organisms under variable environments.
In this paper, Monroe and colleagues (2021) propose an original approach that raised to these two challenges. They analysed phenotypic plastic changes in response to a continuous environment in a multidimensional trait space, namely the response of Brachypodium plant developmental and physiological traits to a continuous gradient of soil moisture. They used dry down experimental treatments to produce the continuous soil moisture gradient and compared the plant capacity to use water between annual B. distachyon and perennial B. sylvaticum. Their results revealed the best mathematical functions that model the nonlinear curvature of the continuous plastic response of Brachypodium plants. This work reinforces our view that nonlinear plastic responses can result in greater or lesser trait values at any stage of the environmental gradient that were unexpected on the basis of linear predictors (Gienapp and Brommer 2014). Their findings also imply that different threshold responses characterize different genotypes. These could otherwise have been missed by a classical approach. By shedding light on unforeseen interactions between traits that make their correlation vary along the nonlinear response, they were able to describe more accurately Brachypodium ecological strategies and the changes in evolutionary constraints along the soil moisture gradient.
Their empirical approach allows to test what environmental conditions maximises the opportunity for selection to shape trait variation. For example, it revealed unforeseen divergence in potentially adaptive mechanisms or life history strategies – and not just trait values – between annual and perennial species of Brachypodium. Behind every environmental variation of the constraints to the future evolutionary change of multiple traits, we can expect that the evolutionary history of the populations shaped their trait genetic correlations. Investigating the nonlinear signature of adaptive evolution across continuous environments will get us into uncharted territory.
Our ability to predict the adaptive potential of species is limited. With their approach of continuous environmental gradients beyond linearity, Monroe and collaborators (2021) improve our understanding of plant phenotypic responses and open a brand new range of exciting developments. As they mention: "the opportunity for scaling up" their approach is big. To illustrate this prospect, I can easily think of an example: the quantitative genetic random regression model. This model allows to use any degree of genetic relatedness in a wild population to estimate the genetic variation of phenotypic plastic reaction norms (Nussey et al 2007, Pujol and Galaud 2013). However, in this approach, only a few modalities of the environmental gradient are used to model nonlinear phenotypic plastic responses. From there, it is rather intuitive. Combining the best of these two approaches (continuity of genetic relatedness in the wild & continuity of environmental gradient in experiments) could open ground breaking new perspectives in research.


Gienapp P. & J.E. Brommer. 2014. Evolutionary dynamics in response to climate change. In: Charmentier A, Garant D, Kruuk LEB, editors. Quantitative genetics in the wild. Oxford: Oxford University Press, Oxford. pp. 254–273. doi:
Monroe, J. G., Cai, H., and Des Marais, D. L. (2020). Trait plasticity and covariance along a continuous soil moisture gradient. bioRxiv, 2020.02.17.952853, ver. 5 peer-reviewed and recommended by PCI Evol Biol. doi:
Pujol et al. (2018). The missing response to selection in the wild. Trends in ecology & evolution, 33(5), 337-346. doi:
Pujol, B., and Galaud, J. P. (2013). A practical guide to quantifying the effect of genes underlying adaptation in a mixed genomics and evolutionary ecology approach. Botany Letters, 160(3-4), 197-204. doi:
Nussey, D. H., Wilson, A. J., and Brommer, J. E. (2007). The evolutionary ecology of individual phenotypic plasticity in wild populations. Journal of evolutionary biology, 20(3), 831-844. doi:
Teplitsky et al. (2014). Assessing multivariate constraints to evolution across ten long-term avian studies. PLoS One, 9(3), e90444. doi:

16 Dec 2020
article picture

Shifts from pulled to pushed range expansions caused by reduction of landscape connectivity

The push and pull between theory and data in understanding the dynamics of invasion

Recommended by based on reviews by Laura Naslund and 2 anonymous reviewers

Exciting times are afoot for those of us interested in the ecology and evolution of invasive populations. Recent years have seen evolutionary process woven firmly into our understanding of invasions (Miller et al. 2020). This integration has inspired a welter of empirical and theoretical work. We have moved from field observations and verbal models to replicate experiments and sophisticated mathematical models. Progress has been rapid, and we have seen science at its best; an intimate discussion between theory and data.
An area currently under very active development is our understanding of pushed invasions. Here a population spreads through space driven, not by dispersal and growth originating at the leading tip of the invasion, but by dispersal and growth originating deeper in the bulk of the population. These pushed invasions may be quite common – they result when per capita growth and dispersal rates are higher in the bulk of the wave than at the leading tip. They result from a range of well-known phenomena, including Allee effects and density-dependent dispersal (Gandhi et al. 2016; Bîrzu et al. 2019). Pushed invasions travel faster than we would expect given growth and dispersal rates on the leading tip, and they lose genetic diversity more slowly than classical pulled invasions (Roques et al. 2012; Haond et al. 2018; Bîrzu et al. 2019).
Well… in theory, anyway. The theory on pushed waves has momentarily streaked ahead of the empirical work, because empirical systems for studying pushed invasions are rare (though see Gandhi et al. 2016; Gandhi, Korolev, and Gore 2019). In this paper, Dahirel and colleagues (2020) make the argument that we may be able to generate pushed invasions in laboratory systems simply by reducing the connectedness of our experimental landscapes. If true, we might have a simple tool for turning many of our established experimental systems into systems for studying pushed dynamics.
It’s a nice idea, and the paper goes to careful lengths to explore the possibility in their lab system (a parasitoid wasp, Trichogramma). They run experiments on replicate wasp populations comparing strongly- v poorly-connected arrays, and estimate the resulting invasion speeds and rate of diversity loss. They also build a simulation model of the system, allowing them to explore in-silico a range of possible processes underlying their results.
As well as developing these parallel systems, Dahirel and colleagues (2020) go to careful lengths to develop statistical analyses that allow inference on key parameters, and they apply these analyses to both the experimental and simulation data. They have been motivated to apply methods that might be used in both laboratory and field settings to help classify invasions.
Ultimately, they found reasonable evidence that their poorly-connected habitat did induce a pushed dynamic. Their poorly connected invasions travelled faster than they should have if they were pulled, they lost diversity more slowly than the highly connected habitat, and replicates with a higher carrying capacity tended to have higher invasion speeds. All in line with expectations of a pushed dynamic. Interestingly, however, their simulation results suggest that they probably got this perfect result for unexpected reasons. The strong hint is that their poorly-connected habitat induced density dependent dispersal in the wasps. Without this effect, their simulations suggest they should have seen diversity decreasing much more rapidly than it did.
There is a nuanced, thoughtful, and carefully argued discussion about all this in the paper, and it is worth reading. There is much of value in this paper. Theirs is not a perfect empirical system in which all the model assumptions are met and in which huge population sizes make stochastic effects negligible. Here is a system one step closer to the messy reality of biology. The struggle to align this system with new theory has been worth the effort. Not only does it give us hope that we might usefully be able to discriminate between classes of invasions using real-world data, but it hints at a rule that Tolstoy might have expressed this way: all pulled invasions are alike, each pushed invasion is pushed in its own way.


Bîrzu, G., Matin, S., Hallatschek, O., and Korolev, K. S. (2019). Genetic drift in range expansions is very sensitive to density dependence in dispersal and growth. Ecology Letters, 22(11), 1817-1827. doi:
Dahirel, M., Bertin, A., Haond, M., Blin, A., Lombaert, E., Calcagno, V., Fellous, S., Mailleret, L., Malausa, T., and Vercken, E. (2020). Shifts from pulled to pushed range expansions caused by reduction of landscape connectivity. bioRxiv, 2020.05.13.092775, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology.
Gandhi, S. R., Korolev, K. S., and Gore, J. (2019). Cooperation mitigates diversity loss in a spatially expanding microbial population. Proceedings of the National Academy of Sciences, 116(47), 23582-23587. doi:
Gandhi, S. R., Yurtsev, E. A., Korolev, K. S., and Gore, J. (2016). Range expansions transition from pulled to pushed waves as growth becomes more cooperative in an experimental microbial population. Proceedings of the National Academy of Sciences, 113(25), 6922-6927. doi:
Haond, M., Morel-Journel, T., Lombaert, E., Vercken, E., Mailleret, L. and Roques, L. (2018). When higher carrying capacities lead to faster propagation (2018), bioRxiv, 307322, ver. 4 peer-reviewed and recommended by Peer Community in Ecology.
Miller et al. (2020). Eco‐evolutionary dynamics of range expansion. Ecology, 101(10), e03139. doi:
Roques, L., Garnier, J., Hamel, F., and Klein, E. K. (2012). Allee effect promotes diversity in traveling waves of colonization. Proceedings of the National Academy of Sciences, 109(23), 8828-8833. doi:

11 Dec 2020
article picture

Quantifying transmission dynamics of acute hepatitis C virus infections in a heterogeneous population using sequence data

Phylodynamics of hepatitis C virus reveals transmission dynamics within and between risk groups in Lyon

Recommended by based on reviews by Chris Wymant and Louis DuPlessis

Genomic epidemiology seeks to better understand the transmission dynamics of infectious pathogens using molecular sequence data. Phylodynamic methods have given genomic epidemiology new power to track the transmission dynamics of pathogens by combining phylogenetic analyses with epidemiological modeling. In recent year, applications of phylodynamics to chronic viral infections such as HIV and hepatitis C virus (HVC) have provided some of the best examples of how phylodynamic inference can provide valuable insights into transmission dynamics within and between different subpopulations or risk groups, allowing for more targeted interventions.
However, conducting phylodynamic inference under complex epidemiological models comes with many challenges. In some cases, it is not always straightforward or even possible to perform likelihood-based inference. Structured SIR-type models where infected individuals can belong to different subpopulations provide a classic example. In this case, the model is both nonlinear and has a high-dimensional state space due to tracking different types of hosts. Computing the likelihood of a phylogeny under such a model involves complex numerical integration or data augmentation methods [1]. In these situations, Approximate Bayesian Computation (ABC) provides an attractive alternative, as Bayesian inference can be performed without computing likelihoods as long as one can efficiently simulate data under the model to compare against empirical observations [2].
Previous work has shown how ABC approaches can be applied to fit epidemiological models to phylogenies [3,4]. Danesh et al. [5] further demonstrate the real world merits of ABC by fitting a structured SIR model to HCV data from Lyon, France. Using this model, they infer viral transmission dynamics between “classical” hosts (typically injected drug users) and “new” hosts (typically young MSM) and show that a recent increase in HCV incidence in Lyon is due to considerably higher transmission rates among “new” hosts . This study provides another great example of how phylodynamic analysis can help epidemiologists understand transmission patterns within and between different risk groups and the merits of expanding our toolkit of statistical methods for phylodynamic inference.


[1] Rasmussen, D. A., Volz, E. M., and Koelle, K. (2014). Phylodynamic inference for structured epidemiological models. PLoS Comput Biol, 10(4), e1003570. doi:
[2] Beaumont, M. A., Zhang, W., and Balding, D. J. (2002). Approximate Bayesian computation in population genetics. Genetics, 162(4), 2025-2035.
[3] Ratmann, O., Donker, G., Meijer, A., Fraser, C., and Koelle, K. (2012). Phylodynamic inference and model assessment with approximate bayesian computation: influenza as a case study. PLoS Comput Biol, 8(12), e1002835. doi:
[4] Saulnier, E., Gascuel, O., and Alizon, S. (2017). Inferring epidemiological parameters from phylogenies using regression-ABC: A comparative study. PLoS computational biology, 13(3), e1005416. doi:
[5] Danesh, G., Virlogeux, V., Ramière, C., Charre, C., Cotte, L. and Alizon, S. (2020) Quantifying transmission dynamics of acute hepatitis C virus infections in a heterogeneous population using sequence data. bioRxiv, 689158, ver. 5 peer-reviewed and recommended by PCI Evol Biol. doi:

23 Nov 2020
article picture

Wolbachia and host intrinsic reproductive barriers contribute additively to post-mating isolation in spider mites

Speciation in spider mites: disentangling the roles of Wolbachia-induced vs. nuclear mating incompatibilities

Recommended by based on reviews by Wolfgang Miller and 1 anonymous reviewer

Cytoplasmic incompatibility (CI) is a mating incompatibility that is induced by maternally inherited endosymbionts in many arthropods. These endosymbionts include, most famously, the alpha-proteobacterium Wolbachia pipientis (Yen & Barr 1971; Werren et al. 2008) but also the Bacteroidetes bacterium Cardinium hertigii (Zchori-Fein et al. 2001), a gamma-proteobacterium of the genus Rickettsiella (Rosenwald et al. 2020) and another, as yet undescribed alpha-proteobacterium (Takano et al. 2017). CI manifests as embryonic mortality in crosses between infected males and females that are uninfected or infected with a different strain, whereas embryos develop normally in all other crosses. This phenotype may enable the endosymbionts to spread rapidly within their host population. Exploiting this, CI-inducing Wolbachia are being harnessed to control insect-borne diseases (e.g., O'Neill 2018). Much progress elucidating the genetic basis and developmental mechanism of CI has been made in recent years, but many open questions remain (Shropshire et al. 2020).
Immediately following the discovery and early study of CI in mosquitoes, Laven (1959, 1967) proposed that CI could be an important driver of speciation. Indeed, bi-directional CI can strongly reduce gene flow between two populations due to the elimination of F1 embryos, so that CI can act as a trigger for genetic differentiation in the host (Telschow et al. 2002, 2005). This idea has received much attention, and a potential role for CI in incipient speciation has been demonstrated in several species (e.g., Bordenstein et al. 2001; Jaenike et al. 2006). However, we still don’t know how commonly CI actually triggers speciation, rather than being merely a minor player or secondary phenomenon. The problem is that in addition to CI, postzygotic reproductive isolation can also be caused by host-induced, nuclear incompatibilities. Determining the relative contributions of these two causes of isolation is difficult and has rarely been done.
The study by Cruz et al. (2020) addresses this problem head-on, using a study system of Tetranychus urticae spider mites. These cosmopolitan mites are infected with different strains of Wolbachia. They come in two different colour forms (red and green) that can co-occur sympatrically on the same host plant but exhibit various degrees of reproductive isolation. A complicating factor in spider mites is that they are haplodiploid: unfertilised eggs develop into haploid males and are therefore not affected by any postzygotic incompatibilities, whereas fertilised eggs normally develop into diploid females. In haplodiploids, Wolbachia-induced CI can either kill diploid embryos (as in diplodiploid species), or turn them into haploid males. In their study, Cruz et al. used three different populations (one of the green and two of the red form) and employed a full factorial experiment involving all possible combinations of crosses of Wolbachia infected or uninfected males and females. For each cross, they measured F1 embryonic and juvenile mortality as well as sex ratio, and they also measured F1 fertility and F2 viability. Their results showed that there is strong reduction in hybrid female production caused by Wolbachia-induced CI. However, independent of this and through a different mechanism, there is an even stronger reduction in hybrid production caused by host-associated incompatibilities. In combination with the also observed near-complete sterility of F1 hybrid females and full F2 hybrid breakdown (neither of which is caused by Wolbachia), the results indicate essentially complete reproductive isolation between the green and red forms of T. urticae.
Overall, this is an elegant study with an admirably clean and comprehensive experimental design. It demonstrates that Wolbachia can contribute to reproductive isolation between populations, but that host-induced mechanisms of reproductive isolation predominate in these spider mite populations. Further studies in this exiting system would be useful that also investigate the contribution of pre-zygotic isolation mechanisms such as assortative mating, ascertain whether the results can be generalised to other populations, and – most challengingly – establish the order in which the different mechanisms of reproductive isolation evolved.


Bordenstein, S. R., O'Hara, F. P., and Werren, J. H. (2001). Wolbachia-induced incompatibility precedes other hybrid incompatibilities in Nasonia. Nature, 409(6821), 707-710. doi:
Cruz, M. A., Magalhães, S., Sucena, É., and Zélé, F. (2020) Wolbachia and host intrinsic reproductive barriers contribute additively to post-mating isolation in spider mites. bioRxiv, 2020.06.29.178699, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. doi:
Jaenike, J., Dyer, K. A., Cornish, C., and Minhas, M. S. (2006). Asymmetrical reinforcement and Wolbachia infection in Drosophila. PLoS Biol, 4(10), e325. doi:
Laven, H. (1959). SPECIATION IN MOSQUITOES Speciation by Cytoplasmic Isolation in the Culex Pipiens-Complex. In Cold Spring Harbor Symposia on Quantitative Biology (Vol. 24, pp. 166-173). Cold Spring Harbor Laboratory Press.
Laven, H. (1967). A possible model for speciation by cytoplasmic isolation in the Culex pipiens complex. Bulletin of the World Health Organization, 37(2), 263-266.
O’Neill S.L. (2018) The Use of Wolbachia by the World Mosquito Program to Interrupt Transmission of Aedes aegypti Transmitted Viruses. In: Hilgenfeld R., Vasudevan S. (eds) Dengue and Zika: Control and Antiviral Treatment Strategies. Advances in Experimental Medicine and Biology, vol 1062. Springer, Singapore. doi:
Rosenwald, L.C., Sitvarin, M.I. and White, J.A. (2020). Endosymbiotic Rickettsiella causes cytoplasmic incompatibility in a spider host. doi:
Shropshire, J. D., Leigh, B., and Bordenstein, S. R. (2020). Symbiont-mediated cytoplasmic incompatibility: what have we learned in 50 years?. Elife, 9, e61989. doi:
Takano et al. (2017). Unique clade of alphaproteobacterial endosymbionts induces complete cytoplasmic incompatibility in the coconut beetle. Proceedings of the National Academy of Sciences, 114(23), 6110-6115. doi:
Telschow, A., Hammerstein, P., and Werren, J. H. (2002). The effect of Wolbachia on genetic divergence between populations: models with two-way migration. the american naturalist, 160(S4), S54-S66. doi:
Telschow, A., Hammerstein, P., and Werren, J. H. (2005). The effect of Wolbachia versus genetic incompatibilities on reinforcement and speciation. Evolution, 59(8), 1607-1619. doi:
Werren, J. H., Baldo, L., and Clark, M. E. (2008). Wolbachia: master manipulators of invertebrate biology. Nature Reviews Microbiology, 6(10), 741-751. doi:
Yen, J. H., and Barr, A. R. (1971). New hypothesis of the cause of cytoplasmic incompatibility in Culex pipiens L. Nature, 232(5313), 657-658. doi:
Zchori-Fein, E., Gottlieb, Y., Kelly, S. E., Brown, J. K., Wilson, J. M., Karr, T. L., and Hunter, M. S. (2001). A newly discovered bacterium associated with parthenogenesis and a change in host selection behavior in parasitoid wasps. Proceedings of the National Academy of Sciences, 98(22), 12555-12560. doi:

18 Nov 2020
article picture

A demogenetic agent based model for the evolution of traits and genome architecture under sexual selection

Sexual selection goes dynamic

Recommended by based on reviews by Frédéric Guillaume and 1 anonymous reviewer

150 years after Darwin published ‘Descent of man and selection in relation to sex’ (Darwin, 1871), the evolutionary mechanism that he laid out in his treatise continues to fascinate us. Sexual selection is responsible for some of the most spectacular traits among animals, and plants, and it appeals to our interest in all things reproductive and sexual (Bell, 1982). In addition, sexual selection poses some of the more intractable problems in evolutionary biology: Its realm encompasses traits that are subject to markedly different selection pressures, particularly when distinct, yet associated, traits tend to be associated with males, e.g. courtship signals, and with females, e.g. preferences (cf. Ah-King & Ahnesjo, 2013). While separate, such traits cannot evolve independently of each other (Arnqvist & Rowe, 2005), and complex feedback loops and correlations between them are predicted (Greenfield et al., 2014). Traditionally, sexual selection has been modelled under simplifying assumptions, and quantitative genetic approaches that avoided evolutionary dynamics have prevailed. New computing methods may be able to free the field from these constraints, and a trio of theoreticians (Chevalier, De Coligny & Labonne 2020) describe here a novel application of a ‘demo-genetic agent (or individual) based model’, a mouthful hereafter termed DG-ABM, for arriving at a holistic picture of the sexual selection trajectory. The application is built on the premise that traits, e.g. courtship, preference, gamete investment, competitiveness for mates, can influence the genetic architecture, e.g. correlations, of those traits. In turn, the genetic architecture can influence the expression and evolvability of the traits. Much of this influence occurs via demographic features, i.e. social environment, generated by behavioral interactions during sexual advertisement, courtship, mate guarding, parental care, post-mating dispersal, etc.
The authors provide a lengthy verbal description of their model, specifying the genomic and behavioral parameters that can be set and how a ‘run’ may be initialized. There is a link to an internet site where users can then enter their own parameter values and begin exploring hypotheses. Back in the article several simulations illustrate simple tests; e.g. how gamete investment and preference jointly evolve given certain survival costs. One obvious test would have been the preference – courtship genetic correlation that represents the core of Fisherian runaway selection, and it is regrettable that it was not examined under a range of demographic parameters. As presented the author’s DG-ABM appears particularly geared toward mating systems in ‘higher’ vertebrates, where couples form during a discrete mating season and are responsible for most reproduction. It is not clear how applicable the model could be to a full range of mating systems and nuances, including those in arthropods and other invertebrates as well as plants.
What is the likely value of the DG-ABM for sexual selection researchers? We will not be able to evaluate its potential impact until readers with specialized understanding of a question and taxon begin exploring and comparing their results with prior expectations. Of course, lack of congruence with earlier predictions would not invalidate the model. Hopefully, some of these specialists will have opportunities for comparing results with pertinent empirical data.


Ah-King, M. and Ahnesjo, I. 2013. The ‘sex role’ concept: An overview and evaluation Evolutionary Biology, 40, 461-470. doi:
Arnqvist, G. and Rowe, L. 2005. Sexual Conflict. Princeton University Press, Princeton. doi:
Bell, G. 1982. The Masterpiece of Nature: The Evolution and Genetics of Sexuality. University of California Press, Berkeley.
Chevalier, L., De Coligny, F. and Labonne, J. (2020) A demogenetic individual based model for the evolution of traits and genome architecture under sexual selection. bioRxiv, 2020.04.01.014514, ver. 4 peer-reviewed and recommended by PCI Evol Biol. doi:
Darwin, C. 1871. The Descent of Man and Selection in Relation to Sex. J. Murray, London.
Greenfield, M.D., Alem, S., Limousin, D. and Bailey, N.W. 2014. The dilemma of Fisherian sexual selection: Mate choice for indirect benefits despite rarity and overall weakness of trait-preference genetic correlation. Evolution, 68, 3524-3536. doi:

12 Nov 2020
article picture

Limits and Convergence properties of the Sequentially Markovian Coalescent

Review and Assessment of Performance of Genomic Inference Methods based on the Sequentially Markovian Coalescent

Recommended by based on reviews by 3 anonymous reviewers

The human genome not only encodes for biological functions and for what makes us human, it also encodes the population history of our ancestors. Changes in past population sizes, for example, affect the distribution of times to the most recent common ancestor (tMRCA) of genomic segments, which in turn can be inferred by sophisticated modelling along the genome.
A key framework for such modelling of local tMRCA tracts along genomes is the Sequentially Markovian Coalescent (SMC) (McVean and Cardin 2005, Marjoram and Wall 2006) . The problem that the SMC solves is that the mosaic of local tMRCAs along the genome is unknown, both in their actual ages and in their positions along the genome. The SMC allows to effectively sum across all possibilities and handle the uncertainty probabilistically. Several important tools for inferring the demographic history of a population have been developed built on top of the SMC, including PSMC (Li and Durbin 2011), diCal (Sheehan et al 2013), MSMC (Schiffels and Durbin 2014), SMC++ (Terhorst et al 2017), eSMC (Sellinger et al. 2020) and others.
In this paper, Sellinger, Abu Awad and Tellier (2020) review these SMC-based methods and provide a coherent simulation design to comparatively assess their strengths and weaknesses in a variety of demographic scenarios (Sellinger, Abu Awad and Tellier 2020). In addition, they used these simulations to test how breaking various key assumptions in SMC methods affects estimates, such as constant recombination rates, or absence of false positive SNP calls.
As a result of this assessment, the authors not only provide practical guidance for researchers who want to use these methods, but also insights into how these methods work. For example, the paper carefully separates sources of error in these methods by observing what they call “Best-case convergence” of each method if the data behaves perfectly and separating that from how the method applies with actual data. This approach provides a deeper insight into the methods than what we could learn from application to genomic data alone.
In the age of genomics, computational tools and their development are key for researchers in this field. All the more important is it to provide the community with overviews, reviews and independent assessments of such tools. This is particularly important as sometimes the development of new methods lacks primary visibility due to relevant testing material being pushed to Supplementary Sections in papers due to space constraints. As SMC-based methods have become so widely used tools in genomics, I think the detailed assessment by Sellinger et al. (2020) is timely and relevant.
In conclusion, I recommend this paper because it bridges from a mere review of the different methods to an in-depth assessment of performance, thereby addressing both beginners in the field who just seek an initial overview, as well as experienced researchers who are interested in theoretical boundaries and assumptions of the different methods.


[1] Li, H., and Durbin, R. (2011). Inference of human population history from individual whole-genome sequences. Nature, 475(7357), 493-496. doi:
[2] Marjoram, P., and Wall, J. D. (2006). Fast"" coalescent"" simulation. BMC genetics, 7(1), 16. doi:
[3] McVean, G. A., and Cardin, N. J. (2005). Approximating the coalescent with recombination. Philosophical Transactions of the Royal Society B: Biological Sciences, 360(1459), 1387-1393. doi:
[4] Schiffels, S., and Durbin, R. (2014). Inferring human population size and separation history from multiple genome sequences. Nature genetics, 46(8), 919-925. doi:
[5] Sellinger, T. P. P., Awad, D. A., Moest, M., and Tellier, A. (2020). Inference of past demography, dormancy and self-fertilization rates from whole genome sequence data. PLoS Genetics, 16(4), e1008698. doi:
[6] Sellinger, T. P. P., Awad, D. A. and Tellier, A. (2020) Limits and Convergence properties of the Sequentially Markovian Coalescent. bioRxiv, 2020.07.23.217091, ver. 3 peer-reviewed and recommended by PCI Evolutionary Biology. doi:
[7] Sheehan, S., Harris, K., and Song, Y. S. (2013). Estimating variable effective population sizes from multiple genomes: a sequentially Markov conditional sampling distribution approach. Genetics, 194(3), 647-662. doi:
[8] Terhorst, J., Kamm, J. A., and Song, Y. S. (2017). Robust and scalable inference of population history from hundreds of unphased whole genomes. Nature genetics, 49(2), 303-309. doi:

05 Nov 2020
article picture

A genomic amplification affecting a carboxylesterase gene cluster confers organophosphate resistance in the mosquito Aedes aegypti: from genomic characterization to high-throughput field detection

Identification of a gene cluster amplification associated with organophosphate insecticide resistance: from the diversity of the resistance allele complex to an efficient field detection assay

Recommended by based on reviews by Diego Ayala and 2 anonymous reviewers

The emergence and spread of insecticide resistance compromises the efficiency of insecticides as prevention tool against the transmission of insect-transmitted diseases (Moyes et al. 2017). In this context, the understanding of the genetic mechanisms of resistance and the way resistant alleles spread in insect populations is necessary and important to envision resistance management policies. A common and important mechanism of insecticide resistance is gene amplification and in particular amplification of insecticide detoxification genes, which leads to the overexpression of these genes (Bass & Field, 2011). Cattel and coauthors (2020) adopt a combination of experimental approaches to study the role of gene amplification in resistance to organophosphate insecticides in the mosquito Aedes aegypti and its occurrence in populations of South East Asia and to develop a molecular test to track resistance alleles.
Their first approach consists in performing an artificial selection on laboratory Ae. Aegypti populations started with individuals collected in Laos. In the selected population, an initial 90% mortality by adult exposure to the organophosphate insecticide malathion is imposed. This population shows a steep increase in resistance to malathion and other organophosphate insecticides, which is absent in the paired control population. The transcriptomic patterns of the control and the evolved populations as well as of a reference sensitive population reveals, among other differences, the over-expression of five carboxy/choline esterase (CCE) genes in the insecticide selected population. These five genes happen to be clustered in the Ae. aegypti genome and whole genome sequencing of a highly resistant population combined to qPCR test on genomic DNA showed that the overexpression of these genes is due to gene amplification. Although it would have been more elegant to have replicate selected and control populations and to perform the transcriptomic and the genomic analyses directly on the experimental populations, the authors gather a set of experimental evidence which combined to previous knowledge on the function of the amplified and over-expressed genes and on their implication in organophosphate insecticide resistance in other species allow to discard the possibility that this gene amplification spread by drift in the selected population.
In a second part of the paper, copy number variation for CCE genes is checked in field sample populations. This test reveals the presence of resistance alleles in half of the fourteen South East Asia populations sampled. Very interestingly, it also reveals a high level of complexity and diversity among the resistance alleles: it shows first the existence, both in the experimental and the field populations, of at least two amplified alleles (differing by the number of genes amplified) and second a high variation in the copy number of amplified genes. This indicates that gene amplification as a molecular resistance mechanism has actually lead to a high diversity of resistance alleles. These alleles are likely to differ both by the level of resistance conferred and the fitness cost imposed in the absence of the insecticide and these two values are affecting the evolution of their frequency in the field and ultimately the spread of resistance.
The last part of the paper is devoted to the development of a high-throughput Taqman assay which allows to determine rapidly the copy number of one of the esterase genes amplified in the resistance alleles described earlier. This assay is nicely validated and will definitely be a useful tool to determine the occurrence of these resistance alleles in field population. The fact that it gives access to the copy number will also allow to follow its copy number across time and get insight into the complexity of resistance evolution by gene amplification.
To sum up, this paper studies the implication of carboxy/choline esterase genes amplification in organophosphate resistance evolution in Ae. aegypti, reveals the diversity among individuals and populations of this resistance mechanism, because of variation both in the identity of the genes amplified and in their copy number and sets up a fast and efficient tool to detect and follow the spread of these resistant alleles in the field. Additionally, the different experimental approaches adopted have generated genomic and transcriptomic data, of which only the part related to CCE gene amplification has been exploited. These data are very likely to reveal other genomic and expression determinants of resistance that will give access to an extra degree of complexity in organophosphate insecticide resistance determinism and evolution.


Bass C, Field LM (2011) Gene amplification and insecticide resistance. Pest Management Science, 67, 886–890.
Cattel J, Haberkorn C, Laporte F, Gaude T, Cumer T, Renaud J, Sutherland IW, Hertz JC, Bonneville J-M, Arnaud V, Nous C, Fustec B, Boyer S, Marcombe S, David J-P (2020) A genomic amplification affecting a carboxylesterase gene cluster confers organophosphate resistance in the mosquito Aedes aegypti: from genomic characterization to high-throughput field detection. bioRxiv, 2020.06.08.139741, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology.
Moyes CL, Vontas J, Martins AJ, Ng LC, Koou SY, Dusfour I, Raghavendra K, Pinto J, Corbel V, David J-P, Weetman D (2017) Contemporary status of insecticide resistance in the major Aedes vectors of arboviruses infecting humans. PLOS Neglected Tropical Diseases, 11, e0005625.

04 Nov 2020
article picture

Treating symptomatic infections and the co-evolution of virulence and drug resistance

More intense symptoms, more treatment, more drug-resistance: coevolution of virulence and drug-resistance

Recommended by based on reviews by 3 anonymous reviewers

Mathematical models play an essential role in current evolutionary biology, and evolutionary epidemiology is not an exception [1]. While the issues of virulence evolution and drug-resistance evolution resonate in the literature for quite some time [2, 3], the study by Alizon [4] is one of a few that consider co-evolution of both these traits [5]. The idea behind this study is the following: treating individuals with more severe symptoms at a higher rate (which appears to be quite natural) leads to an appearance of virulent drug-resistant strains, via treatment failure. The author then shows that virulence in drug-resistant strains may face different selective pressures than in drug-sensitive strains and hence proceed at different rates. Hence, treatment itself modulates evolution of virulence. As one of the reviewers emphasizes, the present manuscript offers a mathematical view on why the resistant and more virulent strains can be selected in epidemics. Also, we both find important that the author highlights that the topic and results of this study can be attributed to public health policies and development of optimal treatment protocols [6].
Mathematical models are simplified representations of reality, created with a particular purpose. It can be simple as well as complex, but even simple models can produce relatively complex and knitted results. The art of modelling thus lies not only in developing a model, but also in interpreting and unknitting the results. And this is what Alizon [4] indeed does carefully and exhaustively. Using two contrasting theoretical approaches to study co-evolution, the Price equation approach to study short-term evolution and the adaptive dynamics approach to study long-term evolution, Alizon [4] shows that a positive correlation between the rate of treatment and infection severity causes virulence in drug-sensitive strains to decrease. Clearly, no single model can describe and explain an examined system in its entirety, and even this aspect of the work is taken seriously. Many possible extensions of the study are laid out, providing a wide opportunity to pursue this topic even further. Personally, I have had an opportunity to read many Alizon’s papers and use, teach or discuss many of his models and results. All, including the current one, keep high standard and pursue the field of theoretical (evolutionary) epidemiology.


[1] Gandon S, Day T, Metcalf JE, Grenfell BT (2016) Forecasting epidemiological and evolutionary dynamics of infectious diseases. Trends Ecol Evol 31: 776-788. doi:
[2] Berngruber TW, Froissart R, Choisy M, Gandon S (2013) Evolution of virulence in emerging epidemics. PLoS Pathog 9(3): e1003209. doi:
[3] Spicknall IH, Foxman B, Marrs CF, Eisenberg JNS (2013) A modeling framework for the evolution and spread of antibiotic resistance: literature review and model categorization. Am J Epidemiol 178: 508-520. doi:
[4] Alizon S (2020) Treating symptomatic infections and the co-evolution of virulence and drug resistance. bioRxiv, 2020.02.29.970905, ver. 3 peer-reviewed and recommended by PCI Evol Biol. doi:
[5] Carval D, Ferriere R (2010) A unified model for the coevolution of resistance, tolerance, and virulence. Evolution 64: 2988–3009. doi:
[6] Read AF, T Day, and S Huijben (2011). The evolution of drug resistance and the curious orthodoxy of aggressive chemotherapy. Proc Natl Acad Sci USA 108 Suppl 2, 10871–7. doi:

02 Nov 2020
article picture

Experimental evolution of virulence and associated traits in a Drosophila melanogaster – Wolbachia symbiosis

Temperature effects on virulence evolution of wMelPop Wolbachia in Drosophila melanogaster

Recommended by based on reviews by Shira Houwenhuyse and 3 anonymous reviewers

Monnin et al. [1] here studied how Drosophila populations are affected when exposed to a high virulent endosymbiotic wMelPop Wolbachia strain and why virulent vertically transmitting endosymbionts persist in nature. This virulent wMelPop strain has been described to be a blocker of dengue and other arboviral infections in arthropod vector species, such as Aedes aegypti. Whereas it can thus function as a mutualistic symbiont, it here acts as an antagonist along the mutualism-antagonism continuum symbionts operate. The wMelPop strain is not a natural occurring strain in Drosophila melanogaster and thus the start of this experiment can be seen as a novel host-pathogen association. Through experimental evolution of 17 generations, the authors studied how high temperature affects wMelPop Wolbachia virulence and Drosophila melanogaster survival. The authors used Drosophila strains that were selected for late reproduction, given that this should favor evolution to a lower virulence. Assumptions for this hypothesis are not given in the manuscript here, but it can indeed be assumed that energy that is assimilated to symbiont tolerance instead of reproduction may lead to reduced virulence evolution. This has equally been suggested by Reyserhove et al. [2] in a dynamics energy budget model tailored to Daphnia magna virulence evolution upon a viral infection causing White fat Cell disease, reconstructing changing environments through time.
Contrary to their expectations for vertically transmitting symbionts, the authors did not find a reduction in wMelPop Wolbachia virulence during the course of the experimental evolution experiment under high temperature. Important is what this learns for virulence evolution, also for currently horizontal transmitting disease epidemics (such as COVID-19). It mainly reflects that evolution of virulence for new host-pathogen associations is difficult to predict and that it may take multiple generations before optimal levels of virulence are reached [3,4]. These optimal levels of virulence will depend on trade-offs with other life history traits of the symbiont, but also on host demography, host heterogeneity, amongst others [5,6]. Multiple microbial interactions may affect the outcome of virulence evolution [7]. Given that no germ-free individuals were used, it can be expected that other components of the Drosophila microbiome may have played a role in the virulence evolution. In most cases, microbiota have been described as defensive or protective for virulent symbionts [8], but they may also have stimulated the high levels of virulence. Especially, given that upon higher temperatures, Wolbachia growth may have been increased, host metabolic demands increased [9], host immune responses affected and microbial communities changed [10]. This may have resulted in increased competitive interactions to retrieve host resources, sustaining high virulence levels of the symbiont.
A nice asset of this study is that the phenotypic results obtained in the experimental evolution set-up were linked with wMelPop density measurement and octomom copy number quantifications. Octomom is a specific 8-n genes region of the Wolbachia genome responsible for wMelPop virulence, so there is a link between the phenotypic and molecular functions of the involved symbiont. The authors found that density, octomom copy number and virulence were correlated to each other. An important note the authors address in their discussion is that, to exclude the possibility that octomom copy number has an effect on density, and density on virulence, the effect of these variables should be assessed independently of temperature and age. The obtained results are a valuable contribution to the ongoing debate on the relationship between wMelPop octomom copy number, density and virulence.


[1] Monnin, D., Kremer, N., Michaud, C., Villa, M., Henri, H., Desouhant, E. and Vavre, F. (2020) Experimental evolution of virulence and associated traits in a Drosophila melanogaster – Wolbachia symbiosis. bioRxiv, 2020.04.26.062265, ver. 4 peer-reviewed and recommended by PCI Evol Biol. doi:
[2] Reyserhove, L., Samaey, G., Muylaert, K., Coppé, V., Van Colen, W., and Decaestecker, E. (2017). A historical perspective of nutrient change impact on an infectious disease in Daphnia. Ecology, 98(11), 2784-2798. doi:
[3] Ebert, D., and Bull, J. J. (2003). Challenging the trade-off model for the evolution of virulence: is virulence management feasible?. Trends in microbiology, 11(1), 15-20. doi:
[4] Houwenhuyse, S., Macke, E., Reyserhove, L., Bulteel, L., and Decaestecker, E. (2018). Back to the future in a petri dish: Origin and impact of resurrected microbes in natural populations. Evolutionary Applications, 11(1), 29-41. doi:
[5] Day, T., and Gandon, S. (2007). Applying population‐genetic models in theoretical evolutionary epidemiology. Ecology Letters, 10(10), 876-888. doi:
[6] Alizon, S., Hurford, A., Mideo, N., and Van Baalen, M. (2009). Virulence evolution and the trade‐off hypothesis: history, current state of affairs and the future. Journal of evolutionary biology, 22(2), 245-259. doi:
[7] Alizon, S., de Roode, J. C., and Michalakis, Y. (2013). Multiple infections and the evolution of virulence. Ecology letters, 16(4), 556-567. doi:
[8] Decaestecker, E., and King, K. (2019). Red queen dynamics. Reference module in earth systems and environmental sciences, 3, 185-192. doi:
[9] Kirk, D., Jones, N., Peacock, S., Phillips, J., Molnár, P. K., Krkošek, M., and Luijckx, P. (2018). Empirical evidence that metabolic theory describes the temperature dependency of within-host parasite dynamics. PLoS biology, 16(2), e2004608. doi:
[10] Frankel-Bricker, J., Song, M. J., Benner, M. J., and Schaack, S. (2019). Variation in the microbiota associated with Daphnia magna across genotypes, populations, and temperature. Microbial ecology, 1-12. doi:

26 Oct 2020
article picture

Power and limits of selection genome scans on temporal data from a selfing population

Detecting loci under natural selection from temporal genomic data of selfing populations

Recommended by based on reviews by Christian Huber and 2 anonymous reviewers

The observed levels of genomic diversity in contemporary populations are the result of changes imposed by several evolutionary processes. Among them, natural selection is known to dramatically shape the genetic diversity of loci associated with phenotypes which affect the fitness of carriers. As such, many efforts have been dedicated towards developing methods to detect signatures of natural selection from genomes of contemporary samples [1].
Recent technological advances made the generation of large-scale genomic data from temporal samples, either from experimental populations or historical or ancient samples, accessible to a wide scientific community [2]. Notably, temporal population genomic data allow for a direct observation and study of how, for instance, allele frequencies change through time in response to evolutionary stimuli. Such information can be exploited to detect loci under natural selection, either via mathematical modelling or by investigating empirical distributions [3].
However, most of current methods to detect selection from temporal genomic data have largely ignored selfing populations, despite the latter comprising a significant proportion of species with social and economic importance. Selfing changes genomic patterns by reducing the effective recombination rate, which makes distinguishing between neutral evolution and natural selection even more challenging than for the case of outcrossing populations [4]. Nevertheless, an outlier-approach based on temporal genomic data for the selfing Arabidopsis thaliana population revealed loci under selection [5].
This study suggested the promise of detecting selection for selfing populations and encouraged further investigations to test the power of selection scans under different mating systems.
To address this question, Navascués et al. [6] extended a previously proposed approach for temporal genome scan [7] to incorporate partial self-fertilization. In the original implementation [7], it is assumed that, under neutrality, all loci provide levels of genetic differentiation drawn from the same distribution. If some of the loci are under selection, such distribution should show heterogeneity. Navascués et al. [6] proposed a test for the homogeneity between loci-specific and genome-wide differentiation by deriving a null distribution of FST via simulations using SLiM [8]. After filtering for low-frequency variants and correct for multiple tests, authors derived a statistical test for selection and assess its power under a wide range of scenarios of selfing rate, selection coefficient, duration and type of selection [6].
The newly proposed test achieved good performance to distinguish between neutral and selected loci in most tested scenarios.
As expected, the test's performance significantly drops for scenarios of high selfing rates and selection from standing variation. Additionally, the probability to correctly detect selection decreases with increasing distance from the causal variant. Intriguingly, the test showed high power when the selected ancestral allele had an initial low frequency, and when the selected derived allele had a high initial frequency. When applied to a data set of around 1,000 SNPs from the highly selfing Medicago truncatula population, an annual plant of the legume family [9], the test did not provide any candidate loci under selection [6].
In summary, the detection of loci under selection in selfing populations is and largely remains a challenging task even when explictly account for the different mating system. However, recombination events that occurred before the selective pressure allow ancestral beneficial alleles to exhibit a detectable pattern of non-neutrality. As such, in partially selfing populations, the strength of the footprint of selection depends on several factors, mostly on the selfing rate, the time of onset and type of selection.
One major assumption of this study is that the model implies unstructured population and continuity between samples obtained from the same geographical location over time. As such assumptions are typically violated in real populations, further research into the effect of more complex demographic scenarios is desired to fully understand the power to detect selection in selfing populations. Furthermore, more power could be gained by including additional genomic information at each time point. In this context, recent approaches that make full use of genomic data based on deep learning [10] may contribute significantly towards this goal. Similarly, the effect of data filtering on the power to detect selection should be further explored, especially in the context of DNA resequencing experiments. These analyses will help elucidate the power offered by selection scans from temporal genomic data in selfing populations.


[1] Stern AJ, Nielsen R (2019) Detecting Natural Selection. In: Handbook of Statistical Genomics , pp. 397–40. John Wiley and Sons, Ltd.
[2] Leonardi M, Librado P, Der Sarkissian C, Schubert M, Alfarhan AH, Alquraishi SA, Al-Rasheid KAS, Gamba C, Willerslev E, Orlando L (2017) Evolutionary Patterns and Processes: Lessons from Ancient DNA. Systematic Biology, 66, e1–e29.
[3] Dehasque M, Ávila‐Arcos MC, Díez‐del‐Molino D, Fumagalli M, Guschanski K, Lorenzen ED, Malaspinas A-S, Marques‐Bonet T, Martin MD, Murray GGR, Papadopulos AST, Therkildsen NO, Wegmann D, Dalén L, Foote AD (2020) Inference of natural selection from ancient DNA. Evolution Letters, 4, 94–108.
[4] Vitalis R, Couvet D (2001) Two-locus identity probabilities and identity disequilibrium in a partially selfing subdivided population. Genetics Research, 77, 67–81.
[5] Frachon L, Libourel C, Villoutreix R, Carrère S, Glorieux C, Huard-Chauveau C, Navascués M, Gay L, Vitalis R, Baron E, Amsellem L, Bouchez O, Vidal M, Le Corre V, Roby D, Bergelson J, Roux F (2017) Intermediate degrees of synergistic pleiotropy drive adaptive evolution in ecological time. Nature Ecology and Evolution, 1, 1551–1561.
[6] Navascués M, Becheler A, Gay L, Ronfort J, Loridon K, Vitalis R (2020) Power and limits of selection genome scans on temporal data from a selfing population. bioRxiv, 2020.05.06.080895, ver. 4 peer-reviewed and recommended by PCI Evol Biol.
[7] Goldringer I, Bataillon T (2004) On the Distribution of Temporal Variations in Allele Frequency: Consequences for the Estimation of Effective Population Size and the Detection of Loci Undergoing Selection. Genetics, 168, 563–568.
[8] Messer PW (2013) SLiM: Simulating Evolution with Selection and Linkage. Genetics, 194, 1037–1039.
[9] Siol M, Prosperi JM, Bonnin I, Ronfort J (2008) How multilocus genotypic pattern helps to understand the history of selfing populations: a case study in Medicago truncatula. Heredity, 100, 517–525.
[10] Sanchez T, Cury J, Charpiat G, Jay F Deep learning for population size history inference: Design, comparison and combination with approximate Bayesian computation. Molecular Ecology Resources, n/a.

28 Sep 2020
article picture

Evolution and genetic architecture of disassortative mating at a locus under heterozygote advantage

Evolutionary insights into disassortative mating and its association to an ecologically relevant supergene

Recommended by based on reviews by Tom Van Dooren and 2 anonymous reviewers

Heliconius butterflies are famous for their colorful wing patterns acting as a warning of their chemical defenses [1]. Most species are involved in Müllerian mimicry assemblies, as predators learn to associate common wing patterns with unpalatability and preferentially target rare variants. Such positive-frequency dependent selection homogenizes wing patterns at different localities, and in several species, all individuals within a community belong to the same morph [2]. In this respect, H. numata stands out. This species shows stable local polymorphism across multiple localities, with local populations home to up to seven distinct morphs [2]. Although a balance between migration and local positive-frequency dependent selection can allow some degree of local polymorphism, theory suggests that this occurs only when migration is within a narrow window [3].
One factor that potentially enhances local polymorphism in H. numata is disassortative mating. Mate choice assays have in fact revealed that females of this species tend to reject males with the same wing pattern [4]. However the evolution of such mating behavior and its effect on polymorphism remain unclear when selection is locally positive-frequency dependent. Using a mathematical model, Maisonneuve et al. [5] clarify the conditions that favor the evolution of disassortative mating in the complicated system of H. numata. In particular, they investigate whether the genetic basis of wing colour can favor the emergence of disassortative mating. Variation in wing pattern in H. numata is controlled by the supergene P, which is a single genomic region harboring multiple protein coding genes that have ceased to recombine due to chromosomal inversions [6]. If such remarkable genetic configuration allows for the co-adaptation of multiple loci participating to a complex phenotype such as wing color pattern, the absence of recombination can also result in the accumulation of deleterious mutations [7]. In fact, alleles at the P locus have been associated with a recessive genetic load, leading to a fitness advantage for heterozygotes at this locus [8]. Can this fitness advantage to heterozygotes lead to the evolution of disassortative mating? And if so, can such evolution lead to the maintenance of local polymorphism in spite of strong positive frequency-dependent selection?
To investigate these questions, Maisonneuve et al. [5] model evolution at two loci, one is the P locus for wing pattern, and the other influences mating behavior. The population is divided among two connected patches that differ in their butterfly communities, so that different alleles at the P locus are favored by positive frequency-dependent selection in different patches. The different alleles at the P locus are ordered in dominance relationships such that the most dominant over wing color pattern are also those with the highest load. By tracking the dynamics of haplotype frequencies in the population, the authors first show that disassortative mating readily evolves via the invasion of an allele causing females carrying it to reject males that resemble them phenotypically. Such “self-referencing” mechanism of mate choice, however, has never been reported and has been argued to be rare due to its complicated nature [9].
Maisonneuve et al. [5] then compare the evolution of disassortative mating via two alternative mechanisms: attraction and rejection. In these cases, alleles at the mating locus determine attraction to or rejection of specific phenotypes (e.g., under attraction rule, allele “B” encodes attraction to males with phenotype B). With the P and mating loci fully linked, disassortative mating can evolve under all three mechanisms (self-referencing, attraction and rejection), but tends to be less prevalent at equilibrium under attraction rule. This in turn results in the maintenance of less genetic variation under attraction compared to the other mating mechanisms. The loss of variation that occurs under attraction rules is due to a combination of dominance relationships between alleles at the P locus and the searching cost to females in finding rare types of males. When a particular wing pattern, say B, is only expressed in homozygotic form, B males are relatively rare. Females that carry the allele at the mating locus causing them to be attracted to such males then suffer a fitness cost due to lost mating opportunities. This mating allele is therefore purged, and in turn so is the recessive allele for B phenotype at the P locus. Under self-referencing and rejection rules, however, choosy females only reject males of a specific phenotype. They can therefore potentially mate with larger pool of males than females attracted to a single type. As a result, self-referencing and rejection rules are less sensitive to demographic effects and so are more conducive to disassortative mating evolution.
In their final analysis, Maisonneuve et al. [5] investigate the influence of recombination among the P and mating loci. They show that recombination has different effects on disassortative mating evolution depending on the mechanism of mate choice. Under the self-referencing rule, loose linkage leads to higher levels of disassortative mating and polymorphism than when linkage is tight. Under attraction or rejection rule, however, even very limited recombination completely inhibits the evolution of disassortative mating. This is because, with alleles at the mating locus coding for attraction/rejection to specific males, recombination breaks the association between the P and mating loci necessary for disassortative mating. By contrast, disassortative mating via a self-referencing rule does not depend on the linkage among the P and mating loci: females choose males that are different to themselves independently from the alleles they carry at the P locus.
Taken together, Maisonneuve et al.’s analyses [5] show that disassortative mating can readily evolve in a system like H. numata, but that this evolution depends on the genetic architecture of mating behavior. The architectures that are more conducive to the evolution of disassortative mating are: (1) epistatic interactions among the P and mating loci such that females are able to recognize their own phenotype and base their mating decision upon this information (self-referencing rule); and (2) full linkage among the P supergene and a mating locus that triggers rejection of a specific color pattern. While the mechanisms behind disassortative mating remain to be elucidated, assortative mating seems to rely on alleles triggering attraction to specific cues with variation in attraction and cues linked together [10]. These observations support the notion that disassortative mating is due to alleles causing rejection, in tight linkage to the P locus. If so, mating loci would in fact be part of the P supergene, thus controlling not only intricate wing color pattern but also mating behavior.
Beyond the specific system of H. numata, Maisonneuve et al.’s study [5] helps understand the evolution of disassortative mating and its association with the genetic architecture of correlated traits. In particular, Maisonneuve et al. [5] expands the role of supergenes for ecologically relevant traits to mating behavior, further bolstering the relevance of these remarkable genetic elements in the maintenance of variation in complex and elaborate phenotypes.


[1] Merrill, R M, K K Dasmahapatra, J W Davey, D D Dell'Aglio, J J Hanly, B Huber, C D Jiggins, et al. (2015). The Diversification of Heliconius butterflies: What Have We Learned in 150 Years? Journal of Evolutionary Biology 28 (8), 1417–38.
[2] Joron M, IR Wynne, G Lamas, and J Mallet (1999). Variable selection and the coexistence of multiple mimetic forms of the butterfly Heliconius numata. Evolutionary Ecology 13, 721– 754.
[3] Joron M and Y Iwasa (2005). The evolution of a Müllerian mimic in a spatially distributed community. Journal of Theoretical Biology 237, 87–103.
[4] Chouteau M, V Llaurens, F Piron-Prunier, and M Joron (2017). Polymorphism at a mimicry su- pergene maintained by opposing frequency-dependent selection pressures. Proceedings of the National Academy of Sciences 114, 8325–8329.
[5] Maisonneuve, L, Chouteau, M, Joron, M and Llaurens, V. (2020). Evolution and genetic architecture of disassortative mating at a locus under heterozygote advantage. bioRxiv, 616409, ver. 9 peer-reviewed and recommended by PCI Evolutionary Biology.
[6] Joron M, L Frezal, RT Jones, NL Chamberlain, SF Lee, CR Haag, A Whibley, M Becuwe, SW Baxter, L Ferguson, et al. (2011). Chromosomal rearrangements maintain a polymorphic super- gene controlling butterfly mimicry. Nature 477, 203.
[7] Schwander T, R Libbrecht, and L Keller (2014). Supergenes and Complex Phenotypes.” Current Biology. 24 (7), 288–94.
[8] Jay P, M Chouteau, A Whibley, H Bastide, V Llaurens, H Parrinello, and M Joron (2019). Mutation accumulation in chromosomal inversions maintains wing pattern polymorphism in a butterfly. bioRxiv. 10.1101/736504.
[9] Kopp M, MR Servedio, TC Mendelson, RJ Safran, RL Rodrıguez, ME Hauber, EC Scordato, LB Symes, CN Balakrishnan, DM Zonana, et al. (2018). Mechanisms of assortative mating in speciation with gene flow: connecting theory and empirical research. The American Naturalist 191, 1–20.
[10] Merrill RM, P Rastas, SH Martin, MC Melo, S Barker, J Davey, WO McMillan, and CD Jiggins (2019). Genetic dissection of assortative mating behavior. PLoS biology 17, e2005902.

22 Sep 2020
article picture

Evolutionary stasis of the pseudoautosomal boundary in strepsirrhine primates

Studying genetic antagonisms as drivers of genome evolution

Recommended by based on reviews by Qi Zhou and 3 anonymous reviewers

Sex chromosomes are special in the genome because they are often highly differentiated over much of their lengths and marked by degenerative evolution of their gene content. Understanding why sex chromosomes differentiate requires deciphering the forces driving their recombination patterns. Suppression of recombination may be subject to selection, notably because of functional effects of locking together variation at different traits, as well as longer-term consequences of the inefficient purge of deleterious mutations, both of which may contribute to patterns of differentiation [1]. As an example, male and female functions may reveal intrinsic antagonisms over the optimal genotypes at certain genes or certain combinations of interacting genes. As a result, selection may favour the recruitment of rearrangements blocking recombination and maintaining the association of sex-antagonistic allele combinations with the sex-determining locus.
The hypothesis that sexually antagonistic selection might drive recombination suppression along the sex chromosomes is not new, but there are surprisingly few studies examining this empirically [1]. Support mainly comes from the study of guppy populations Poecilia reticulata in which the level of sexual dimorphism (notably due to male ornaments, subject to sexual selection) varies among populations, and was found to correlate with the length of the non-recombining region on the sex chromosome [2]. But the link is not always that clear. For instance in the fungus Microbotryum violaceum, the mating type loci is characterized by adjacent segments with recombination suppression, despite the near absence of functional differentiation between mating types [3].
In this study, Shearn and colleagues [4] explore the patterns of recombination suppression on the sex chromosomes of primates. X and Y chromosomes are strongly differentiated, except in a small region where they recombine with each other, the pseudoautosomal region (PAR). In the clade of apes and monkeys, including humans, large rearrangements have extended the non recombining region stepwise, eroding the PAR. Could this be driven by sexually antagonistic selection in a clade showing strong sexual differentiation?
To evaluate this idea, Shearn et al. have compared the structure of recombination in apes and monkeys to their sister clade with lower levels of sexual dimorphism, the lemurs and the lorises. If sexual antagonism was important in shaping recombination suppression, and assuming lower measures of sexual dimorphism reflect lower sexual antagonism [5], then lemurs and lorises would be predicted to show a shorter non-recombining region than apes and monkeys.
Lemurs and lorises were terra incognita in terms of genomic research on the sex chromosomes, so Shearn et al. have sequenced the genomes of males and females of different species. To assess whether sequences came from a recombining or non-recombining segment, they used coverage information in males vs females to identify sequences on the X whose copy on the Y is absent or too divergent to map, indicating long-term differentiation (absence of recombination). This approach reveals that the two lineages have undergone different recombination dynamics since they split from their common ancestor: regions which have undergone further structural rearrangements extending the non-recombining region in apes and monkeys, have continued to recombine normally in lemurs and lorises. Consistent with the prediction, macroevolutionary variation in the differentiation of males and females is indeed accompanied by variation in the size of the non-recombining region on the sex chromosome.
Sex chromosomes are excellent examples of how genomes are shaped by selection. By directly exploring recombination patterns on the sex chromosome across all extant primate groups, this study comes as a nice addition to the short series of empirical studies evaluating whether sexual antagonism may drive certain aspects of genome structure. The sexual selection causing sometimes spectacular morphological or behavioural differences between sexes in many animals may be the visible tip of the iceberg of all the antagonisms that characterise male vs. female functions generally [5]. Further research should bring insight into how different flavours or intensities of antagonistic selection can contribute to shape genome variation.


[1] Charlesworth D (2017) Evolution of recombination rates between sex chromosomes. Philosophical Transactions of the Royal Society B: Biological Sciences, 372, 20160456.
[2] Wright AE, Darolti I, Bloch NI, Oostra V, Sandkam B, Buechel SD, Kolm N, Breden F, Vicoso B, Mank JE (2017) Convergent recombination suppression suggests role of sexual selection in guppy sex chromosome formation. Nature Communications, 8, 14251.
[3] Branco S, Badouin H, Vega RCR de la, Gouzy J, Carpentier F, Aguileta G, Siguenza S, Brandenburg J-T, Coelho MA, Hood ME, Giraud T (2017) Evolutionary strata on young mating-type chromosomes despite the lack of sexual antagonism. Proceedings of the National Academy of Sciences, 114, 7067–7072.
[4] Shearn R, Wright AE, Mousset S, Régis C, Penel S, Lemaitre J-F, Douay G, Crouau-Roy B, Lecompte E, Marais GAB (2020) Evolutionary stasis of the pseudoautosomal boundary in strepsirrhine primates. bioRxiv, 445072.
[5] Connallon T, Clark AG (2014) Evolutionary inevitability of sexual antagonism. Proceedings of the Royal Society B: Biological Sciences, 281, 20132123.

18 Aug 2020
article picture

Early phylodynamics analysis of the COVID-19 epidemics in France

SARS-Cov-2 genome sequence analysis suggests rapid spread followed by epidemic slowdown in France

Recommended by based on reviews by Luca Ferretti and 2 anonymous reviewers

Sequencing and analyzing SARS-Cov-2 genomes in nearly real time has the potential to quickly confirm (and inform) our knowledge of, and response to, the current pandemic [1,2]. In this manuscript [3], Danesh and colleagues use the earliest set of available SARS-Cov-2 genome sequences available from France to make inferences about the timing of the major epidemic wave, the duration of infections, and the efficacy of lockdown measures. Their phylodynamic estimates -- based on fitting genomic data to molecular clock and transmission models -- are reassuringly close to estimates based on 'traditional' epidemiological methods: the French epidemic likely began in mid-January or early February 2020, and spread relatively rapidly (doubling every 3-5 days), with people remaining infectious for a median of 5 days [4,5]. These transmission parameters are broadly in line with estimates from China [6,7], but are currently unknown in France (in the absence of contact tracing data). By estimating the temporal reproductive number (Rt), the authors detected a slowing down of the epidemic in the most recent period of the study, after mid-March, supporting the efficacy of lockdown measures.
Along with the three other reviewers of this manuscript, I was impressed with the careful and exhaustive phylodynamic analyses reported by Danesh et al. [3]. Notably, they take care to show that the major results are robust to the choice of priors and to sampling. The authors are also careful to note that the results are based on a limited sample size of SARS-Cov-2 genomes, which may not be representative of all regions in France. Their analysis also focused on the dominant SARS-Cov-2 lineage circulating in France, which is also circulating in other countries. The variations they inferred in epidemic growth in France could therefore be reflective on broader control policies in Europe, not only those in France. Clearly more work is needed to fully unravel which control policies (and where) were most effective in slowing the spread of SARS-Cov-2, but Danesh et al. [3] set a solid foundation to build upon with more data. Overall this is an exemplary study, enabled by rapid and open sharing of sequencing data, which provides a template to be replicated and expanded in other countries and regions as they deal with their own localized instances of this pandemic.


[1] Grubaugh, N. D., Ladner, J. T., Lemey, P., Pybus, O. G., Rambaut, A., Holmes, E. C., & Andersen, K. G. (2019). Tracking virus outbreaks in the twenty-first century. Nature microbiology, 4(1), 10-19. doi: 10.1038/s41564-018-0296-2
[2] Fauver et al. (2020) Coast-to-Coast Spread of SARS-CoV-2 during the Early Epidemic in the United States. Cell, 181(5), 990-996.e5. doi: 10.1016/j.cell.2020.04.021
[3] Danesh, G., Elie, B., Michalakis, Y., Sofonea, M. T., Bal, A., Behillil, S., Destras, G., Boutolleau, D., Burrel, S., Marcelin, A.-G., Plantier, J.-C., Thibault, V., Simon-Loriere, E., van der Werf, S., Lina, B., Josset, L., Enouf, V. and Alizon, S. and the COVID SMIT PSL group (2020) Early phylodynamics analysis of the COVID-19 epidemic in France. medRxiv, 2020.06.03.20119925, ver. 3 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/2020.06.03.20119925
[4] Salje et al. (2020) Estimating the burden of SARS-CoV-2 in France.
[5] Sofonea, M. T., Reyné, B., Elie, B., Djidjou-Demasse, R., Selinger, C., Michalakis, Y. and Samuel Alizon, S. (2020) Epidemiological monitoring and control perspectives: application of a parsimonious modelling framework to the COVID-19 dynamics in France. medRxiv, 2020.05.22.20110593. doi: 10.1101/2020.05.22.20110593
[6] Rambaut, A. (2020) Phylogenetic analysis of nCoV-2019 genomes.
[7] Li et al. (2020) Early transmission dynamics in Wuhan, China, of novel coronavirus–infected pneumonia. N Engl J Med, 382: 1199-1207. doi: 10.1056/NEJMoa2001316

05 Aug 2020
article picture

Transposable Elements are an evolutionary force shaping genomic plasticity in the parthenogenetic root-knot nematode Meloidogyne incognita

DNA transposons drive genome evolution of the root-knot nematode Meloidogyne incognita

Recommended by based on reviews by Daniel Vitales and 2 anonymous reviewers

Duplications, mutations and recombination may be considered the main sources of genomic variation and evolution. In addition, sexual recombination is essential in purging deleterious mutations and allowing advantageous allelic combinations to occur (Glémin et al. 2019). However, in parthenogenetic asexual organisms, variation cannot be explained by sexual recombination, and other mechanisms must account for it. Although it is known that transposable elements (TE) may influence on genome structure and gene expression patterns, their role as a primary source of genomic variation and rapid adaptability has received less attention. An important role of TE on adaptive genome evolution has been documented for fungal phytopathogens (Faino et al. 2016), suggesting that TE activity might explain the evolutionary dynamics of this type of organisms.
The phytopathogen nematode Meloidogyne incognita is one of the worst agricultural pests in warm climates (Savary et al. 2019). This species, as well as other root-knot nematodes (RKN), shows a wide geographical distribution range infecting diverse groups of plants. Although allopolyploidy may have played an important role on the wide adaptation of this phytopathogen, it may not explain by itself the rapid changes required to overcome plant resistance in a few generations. Paradoxically, M. incognita reproduces asexually via mitotic parthenogenesis (Trudgill and Blok 2001; Castagnone-Sereno and Danchin 2014) and only few single nucleotide variations were identified between different host races isolates (Koutsovoulos et al. 2020). Therefore, this is an interesting model to explore other sources of genomic variation such the TE activity and its role on the success and adaptability of this phytopathogen.
To address these questions, Kozlowski et al. (2020) estimated the TE mobility across 12 geographical isolates that presented phenotypic variations in Meloidogyne incognita, concluding that recent activity of TE in both genic and regulatory regions might have given rise to relevant functional differences between genomes. This was the first estimation of TE activity as a mechanism probably involved in genome plasticity of this root-knot nematode. This study also shed light on evolutionary mechanisms of asexual organisms with an allopolyploid origin. These authors re-annotated the 185 Mb triploid genome of M. incognita for TE content analysis using stringent filters (Kozlowski 2020a), and estimated activity by their distribution using a population genomics approach including isolates from different crops and locations. Canonical TE represented around 4.7% of the M. incognita genome of which mostly correspond to TIR (Terminal Inverted Repeats) and MITEs (Miniature Inverted repeat Transposable Elements) followed by Maverick DNA transposons and LTR (Long Terminal Repeats) retrotransposons. The result that most TE found were represented by DNA transposons is similar to the previous studies with the nematode species model Caenorhabditis elegans (Bessereau 2006; Kozlowski 2020b) and other nematodes as well. Canonical TE annotations were highly similar to their consensus sequences containing transposition machinery when TE are autonomous, whereas no genes involved in transposition were found in non-autonomous ones. These findings suggest recent activity of TE in the M. incognita genome. Other relevant result was the significant variation in TE presence frequencies found in more than 3,500 loci across isolates, following a bimodal distribution within isolates. However, variation in TE frequencies was low to moderate between isolates recapitulating the phylogenetic signal of isolates DNA sequences polymorphisms. A detailed analysis of TE frequencies across isolates allowed identifying polymorphic TE loci, some of which might be neo-insertions mostly of TIRs and MITEs (Kozlowski 2020c). Interestingly, the two thirds of the fixed neo-insertions were located in coding regions or in regulatory regions impacting expression of specific genes in M. incognita. Future research on proteomics is needed to evaluate the functional impact that these insertions have on adaptive evolution in M. incognita. In this line, this pioneer research of Kozlowski et al. (2020) is a first step that is also relevant to remark the role that allopolyploidy and reproduction have had on shaping nematode genomes.


[1] Bessereau J-L. 2006. Transposons in C. elegans. WormBook. 10.1895/wormbook.1.70.1
[2] Castagnone-Sereno P, Danchin EGJ. 2014. Parasitic success without sex - the nematode experience. J. Evol. Biol. 27:1323-1333. 10.1111/jeb.12337
[3] Faino L, Seidl MF, Shi-Kunne X, Pauper M, Berg GCM van den, Wittenberg AHJ, Thomma BPHJ. 2016. Transposons passively and actively contribute to evolution of the two-speed genome of a fungal pathogen. Genome Res. 26:1091-1100. 10.1101/gr.204974.116
[4] Glémin S, François CM, Galtier N. 2019. Genome Evolution in Outcrossing vs. Selfing vs. Asexual Species. In: Anisimova M, editor. Evolutionary Genomics: Statistical and Computational Methods. Methods in Molecular Biology. New York, NY: Springer. p. 331-369. 10.1007/978-1-4939-9074-0_11
[5] Koutsovoulos GD, Marques E, Arguel M-J, Duret L, Machado ACZ, Carneiro RMDG, Kozlowski DK, Bailly-Bechet M, Castagnone-Sereno P, Albuquerque EVS, et al. 2020. Population genomics supports clonal reproduction and multiple independent gains and losses of parasitic abilities in the most devastating nematode pest. Evol. Appl. 13:442-457. 10.1111/eva.12881
[6] Kozlowski D. 2020a. Transposable Elements prediction and annotation in the M. incognita genome. Portail Data INRAE. 10.15454/EPTDOS
[7] Kozlowski D. 2020b. Transposable Elements prediction and annotation in the C. elegans genome. Portail Data INRAE. 10.15454/LQCIW0
[8] Kozlowski D. 2020c. TE polymorphisms detection and analysis with PopoolationTE2. Portail Data INRAE. 10.15454/EWJCT8
[9] Kozlowski DK, Hassanaly-Goulamhoussen R, Da Rocha M, Koutsovoulos GD, Bailly-Bechet M, Danchin EG (2020) Transposable Elements are an evolutionary force shaping genomic plasticity in the parthenogenetic root-knot nematode Meloidogyne incognita. bioRxiv, 2020.04.30.069948, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. 10.1101/2020.04.30.069948
[10] Savary S, Willocquet L, Pethybridge SJ, Esker P, McRoberts N, Nelson A. 2019. The global burden of pathogens and pests on major food crops. Nat. Ecol. Evol. 3:430-439. 10.1038/s41559-018-0793-y
[11] Trudgill DL, Blok VC. 2001. Apomictic, polyphagous root-knot nematodes: exceptionally successful and damaging biotrophic root pathogens. Annu Rev Phytopathol 39:53-77. 10.1146/annurev.phyto.39.1.53

29 Jul 2020
article picture

The Y chromosome may contribute to sex-specific ageing in Drosophila

Y chromosome makes fruit flies die younger

Recommended by , and

In most animal species, males and females display distinct survival prospect, a phenomenon known as sex gap in longevity (SGL, Marais et al. 2018). The study of SGLs is crucial not only for having a full picture of the causes underlying organisms’ health, aging and death but also to initiate the development of sex-specific anti-aging interventions in humans (Austad and Bartke 2015). Three non-mutually evolutionary causes have been proposed to underlie SGLs (Marais et al. 2018). First, SGLs could be the consequences of sex-differences in life history strategies. For example, evolving dimorphic traits (e.g. body size, ornaments or armaments) may imply unequal physiological costs (e.g. developmental, maintenance) between the sexes and this may result in differences in longevity and aging. Second, mitochondria are usually transmitted by the mother and thus selection is blind to mitochondrial deleterious mutations affecting only males. Such mutations can freely accumulate in the mitochondrial genome and may reduce male longevity, a phenomenon called the mother’s curse (Frank and Hurst 1996). Third, in species with sex chromosomes, all recessive deleterious mutations will be expressed on the single X chromosome in XY males and may reduce their longevity (the unguarded X effect). In addition, the numerous transposable elements (TEs) on the Y chromosome may affect aging. TE activity is normally repressed by epigenetic regulation (DNA methylation, histone modifications and small RNAs). However, it is known that this regulation is disrupted with increasing age. Because of the TE-rich Y chromosome, more TEs may become active in old males than in old females, generating more somatic mutations, accelerating aging and reducing longevity in males (the toxic Y effect, Marais et al. 2018).
The relative contributions of these different effects to SGLs remain unknown. Sex-differences in life history strategies have been considered as the most important cause of SGLs for long (Tidière et al. 2015) but this effect remain equivocal (Lemaître et al. 2020) and cannot explain alone the diversity of patterns observed across species (Marais et al. 2018). Similarly, while studies in Drosophila and humans have shown that the mother’s curse contributes to SGLs in those organisms (e.g. Milot et al. 2007), its contribution may not be strong. Recently, two large-scale comparative analyses have shown that in species with XY chromosomes males show a shorter lifespan compared to females, while in species with ZW chromosomes (a system in which the female are the heterogametic sex and are ZW, and the males ZZ) the opposite pattern is observed (Pipoly et al. 2015; Xirocostas et al. 2020). Apart from these correlational studies, very little experimental tests of the effect of sex chromosomes on longevity have been conducted. In Drosophila, the evidence suggests that the unguarded X effect does not contribute to SGLs (Brengdahl et al. 2018). Whether a toxic Y effect exists in this species was unknown.
In a very elegant study, Brown et al. (2020) provided strong evidence for such a toxic Y effect in Drosophila melanogaster. First, they checked that in the D. melanogaster strain that they were studying (Canton-S), males were indeed dying younger than females. They also confirmed that in this strain, as in others, the male genomes include more repeats and heterochromatin than the female ones using cytometry. A careful analysis of the heterochromatin (using H3K9me2, a repressive histone modification typical of heterochromatin, as a proxy) in old flies revealed that heterochromatin loss was much more important in males than in females, in particular on the Y chromosome (but also to a lesser extent at the pericentromric regions of the autosomes). This change in heterochromatin had two outputs, they found. First, the expression of the genes in those regions was affected. They highlighted that many of such genes are involved in immunity and regulation with a potential impact on longevity. Second, they found a striking TE reactivation. These two effects were stronger in males. While females showed clear reactivation of 6 TEs, with the total fraction of repeats in the transcriptome going from 2% (young females) to 4.6% (old females), males experienced the reactivation of 32 TEs, with the total fraction of repeats in the transcriptome going from 1.6% (young males) to 5.8% (old males). It appeared that most of these TEs are Y-linked. And when focusing on Y-linked repeats, they found that 32 Y-linked TEs became upregulated during male aging and the fraction of Y-linked TEs in the transcriptome increased ninefold.
All these observations clearly suggested that male longevity was decreased because of a toxic Y effect. To really uncover a causal relationship between having a Y chromosome and shorter longevity, Brown et al. (2020) artificially produced flies with atypical karyotypes: X0 males, XXY females and XYY males. This is very interesting as they could uncouple the effect of the phenotypical sex (being male or female) and having a Y chromosome or not, as in fruit flies sex is determined not by the Y chromosome but by the X/autosome ratio. Their results are striking. They found that longevity of the X0 males was the highest (higher than XX females in fact), and that of the XYY males the lowest. Females XXY had intermediate longevities. Importantly, this was found to be robust to genomic background as results were the same using crosses from different strains. When analysing TEs of these flies, they found a particularly strong expression of the Y-linked TEs in old XXY and XYY flies. Interestingly, in young XXY and XYY flies Y-linked TEs expression was also strong, suggesting the chromatin regulation of the Y chromosome is disrupted in these flies.
This work points to the idea that SGLs in D. melanogaster are mainly explained by the toxic Y effect. The molecular details however remain to be elucidated. The effect of the Y chromosome on aging might be more complex than envisioned in the toxic Y model presented above. Brown et al. (2020) indeed found that heterochromatin loss was globally faster in males, both at the Y chromosome and the autosomes. The organisation of the nucleus, in particular of the nucleolus, which is involved in heterochromatin maintenance, involves the sex chromosomes in D. melanogaster as discussed in the paper, and may explain this observation. The epigenetic status of the Y chromosome is known to affect that of all the autosomes in Drosophila (Lemos et al. 2008). Also, in Brown et al. (2020) most of the work (in particular the genomic part) has been done on Canton-S. Only D. melanogaster was studied but limited data suggest different Drosophila species may have different SGLs. The TE analysis is known to be tricky, different tools to analyse TE expression exist (e.g. Lerat et al. 2017; Lanciano and Cristofari 2020). Future work should focus on testing the toxic Y effect on other D. melanogaster strains and other Drosophila species, using different tools to study TE expression, and on dissecting the molecular details of the toxic Y effect.


Austad, S. N., and Bartke, A. (2015). Sex differences in longevity and in responses to anti-aging interventions: A Mini-Review. Gerontology, 62(1), 40–46. 10.1159/000381472
Brengdahl, M., Kimber, C. M., Maguire-Baxter, J., and Friberg, U. (2018). Sex differences in life span: Females homozygous for the X chromosome do not suffer the shorter life span predicted by the unguarded X hypothesis. Evolution; international journal of organic evolution, 72(3), 568–577. 10.1111/evo.13434
Brown, E. J., Nguyen, A. H., and Bachtrog, D. (2020). The Y chromosome may contribute to sex-specific ageing in Drosophila. Nature ecology and evolution, 4(6), 853–862. 10.1038/s41559-020-1179-5 or preprint link on bioRxiv
Frank, S. A., and Hurst, L. D. (1996). Mitochondria and male disease. Nature, 383(6597), 224. 10.1038/383224a0
Lanciano, S., and Cristofari, G. (2020). Measuring and interpreting transposable element expression. Nature reviews. Genetics, 10.1038/s41576-020-0251-y. Advance online publication. 10.1038/s41576-020-0251-y
Lemaître, J. F., Ronget, V., Tidière, M., Allainé, D., Berger, V., Cohas, A., Colchero, F., Conde, D. A., Garratt, M., Liker, A., Marais, G., Scheuerlein, A., Székely, T., and Gaillard, J. M. (2020). Sex differences in adult lifespan and aging rates of mortality across wild mammals. Proceedings of the National Academy of Sciences of the United States of America, 117(15), 8546–8553. 10.1073/pnas.1911999117
Lemos, B., Araripe, L. O., and Hartl, D. L. (2008). Polymorphic Y chromosomes harbor cryptic variation with manifold functional consequences. Science (New York, N.Y.), 319(5859), 91–93. 10.1126/science.1148861
Lerat, E., Fablet, M., Modolo, L., Lopez-Maestre, H., and Vieira, C. (2017). TEtools facilitates big data expression analysis of transposable elements and reveals an antagonism between their activity and that of piRNA genes. Nucleic acids research, 45(4), e17. 10.1093/nar/gkw953
Marais, G., Gaillard, J. M., Vieira, C., Plotton, I., Sanlaville, D., Gueyffier, F., and Lemaitre, J. F. (2018). Sex gap in aging and longevity: can sex chromosomes play a role?. Biology of sex differences, 9(1), 33. 10.1186/s13293-018-0181-y
Milot, E., Moreau, C., Gagnon, A., Cohen, A. A., Brais, B., and Labuda, D. (2017). Mother's curse neutralizes natural selection against a human genetic disease over three centuries. Nature ecology and evolution, 1(9), 1400–1406. 10.1038/s41559-017-0276-6
Pipoly, I., Bókony, V., Kirkpatrick, M., Donald, P. F., Székely, T., and Liker, A. (2015). The genetic sex-determination system predicts adult sex ratios in tetrapods. Nature, 527(7576), 91–94. 10.1038/nature15380
Tidière, M., Gaillard, J. M., Müller, D. W., Lackey, L. B., Gimenez, O., Clauss, M., and Lemaître, J. F. (2015). Does sexual selection shape sex differences in longevity and senescence patterns across vertebrates? A review and new insights from captive ruminants. Evolution; international journal of organic evolution, 69(12), 3123–3140. 10.1111/evo.12801
Xirocostas, Z. A., Everingham, S. E., and Moles, A. T. (2020). The sex with the reduced sex chromosome dies earlier: a comparison across the tree of life. Biology letters, 16(3), 20190867. 10.1098/rsbl.2019.0867

27 Jul 2020
article picture

Evolution of the DAN gene family in vertebrates

An evolutionary view of a biomedically important gene family

Recommended by based on reviews by 2 anonymous reviewers

This manuscript [1] investigates the evolutionary history of the DAN gene family—a group of genes important for embryonic development of limbs, kidneys, and left-right axis speciation. This gene family has also been implicated in a number of diseases, including cancer and nephropathies. DAN genes have been associated with the inhibition of the bone morphogenetic protein (BMP) signaling pathway. Despite this detailed biochemical and functional knowledge and clear importance for development and disease, evolution of this gene family has remained understudied. The diversification of this gene family was investigated in all major groups of vertebrates. The monophyly of the gene members belonging to this gene family was confirmed. A total of five clades were delineated, and two novel lineages were discovered. The first lineage was only retained in cephalochordates (amphioxus), whereas the second one (GREM3) was retained by cartilaginous fish, holostean fish, and coelanth. Moreover, the patterns of chromosomal synteny in the chromosomal regions harboring DAN genes were investigated. Additionally, the authors reconstructed the ancestral gene repertoires and studied the differential retention/loss of individual gene members across the phylogeny. They concluded that the ancestor of gnathostome vertebrates possessed eight DAN genes that underwent differential retention during the evolutionary history of this group. During radiation of vertebrates, GREM1, GREM2, SOST, SOSTDC1, and NBL1 were retained in all major vertebrate groups. At the same time, GREM3, CER1, and DAND5 were differentially lost in some vertebrate lineages. At least two DAN genes were present in the common ancestor of vertebrates, and at least three DAN genes were present in the common ancestor of chordates. Therefore the patterns of retention and diversification in this gene family appear to be complex. Evolutionary slowdown for the DAN gene family was observed in mammals, suggesting selective constraints. Overall, this article puts the biomedical importance of the DAN family in the evolutionary perspective.


[1] Opazo JC, Hoffmann FG, Zavala K, Edwards SV (2020) Evolution of the DAN gene family in vertebrates. bioRxiv, 794404, ver. 3 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/794404

25 Jun 2020
article picture

Transcriptional differences between the two host strains of Spodoptera frugiperda (Lepidoptera: Noctuidae)

Speciation through selection on mitochondrial genes?

Recommended by based on reviews by Heiko Vogel and Sabine Haenniger

Whether speciation through ecological specialization occurs has been a thriving research area ever since Mayr (1942) stated this to play a central role. In herbivorous insects, ecological specialization is most likely to happen through host plant differentiation (Funk et al. 2002). Therefore, after Dorothy Pashley had identified two host strains in the Fall armyworm (FAW), Spodoptera frugiperda, in 1988 (Pashley 1988), researchers have been trying to decipher the evolutionary history of these strains, as this seems to be a model species in which speciation is currently occurring through host plant specialization. Even though FAW is a generalist, feeding on many different host plant species (Pogue 2002) and a devastating pest in many crops, Pashley identified a so-called corn strain and a so-called rice strain in Puerto Rico. Genetically, these strains were found to differ mostly in an esterase, although later studies showed additional genetic differences and markers, mostly in the mitochondrial COI and the nuclear TPI. Recent genomic studies showed that the two strains are overall so genetically different (2% of their genome being different) that these two strains could better be called different species (Kergoat et al. 2012). So far, the most consistent differences between the strains have been their timing of mating activities at night (Schoefl et al. 2009, 2011; Haenniger et al. 2019) and hybrid incompatibilities (Dumas et al. 2015; Kost et al. 2016). Whether and to what extent host plant preference or performance contributed to the differentiation of these sympatrically occurring strains has remained unclear.
In the current study, Orsucci et al. (2020) performed oviposition assays and reciprocal transplant experiments with both strains to measure fitness effects, in combination with a comprehensive RNAseq experiment, in which not only lab reared larvae were analysed, but also field-collected larvae. When testing preference and performance on the two host plants corn and rice, the authors did not find consistent fitness differences between the two strains, with both strains performing less on rice plants, although larvae from the corn strain survived more on corn plants than those from the rice strain. These results mostly confirm findings of a number of investigations over the past 30 years, where no consistent differences on the two host plants were observed (reviewed in Groot et al. 2016). However, the RNAseq experiments did show some striking differences between the two strains, especially in the reciprocally transplanted larvae, where both strains had been reared on rice or on corn plants for one generation: both strains showed transcriptional responses that correspond to their respective putative host plants, i.e. overexpression of genes involved in digestion and metabolic activity, and underexpression of genes involved in detoxification, in the corn strain on corn and in the rice strain on rice. Interestingly, similar sets of genes were found to be overexpressed in the field-collected larvae with which a RNAseq experiment was conducted as well.
The most interesting result of the study performed by Orsucci et al. (2020) is the underexpression in the corn strain of so-called numts, small genomic sequences that corresponded to fragments of the mitochondrial COI and COIII. These two numts were differentially expressed in the two strains in all RNAseq experiments analysed. This result coincides with the fact that the COI is one of the main diagnostic markers to distinguish these two strains. The authors suggestion that a difference in energy production between these two strains may be linked to a shift in host plant preference matches their finding that rice plants seem to be less suitable host plants than corn plants. However, as the lower suitability of rice plants was true for both strains, it remains unclear whether and how this difference could be linked to possible host plant differentiation between the strains. The authors also suggest that COI and potentially other mitochondrial genes may be the original target of selection between these two strains. This is especially interesting in light of the fact that field-collected larvae have frequently been found to have a rice strain mitochondrial genotype and a corn strain nuclear genotype, also in this study, while in the lab (female rice strain x male corn strain) hybrid females (i.e. females with a rice strain mitochondrial genotype and a corn strain nuclear genotype) are behaviorally sterile (Kost et al. 2016). Whether and how selection on mitochondrial genes or on mitonuclear interactions has indeed affected the evolution of these strains in the New world, and will affect the evolution of FAW in newly invaded habitats in the Old world, including Asia and Australia – where, so far, only corn strain and (female rice strain x male corn strain) hybrids have been found (Nagoshi 2019), will be a challenging research question for the coming years.


[1] Dumas, P. et al. (2015). Spodoptera frugiperda (Lepidoptera: Noctuidae) host-plant variants: two host strains or two distinct species?. Genetica, 143(3), 305-316. doi: 10.1007/s10709-015-9829-2
[2] Funk, D. J., Filchak, K. E. and Feder J. L. (2002) Herbivorous insects: model systems for the comparative study of speciation ecology. In: Etges W.J., Noor M.A.F. (eds) Genetics of Mate Choice: From Sexual Selection to Sexual Isolation. Contemporary Issues in Genetics and Evolution, vol 9. Springer, Dordrecht. doi: 10.1007/978-94-010-0265-3_10
[3] Groot, A. T., Unbehend, M., Hänniger, S., Juárez, M. L., Kost, S. and Heckel D. G.(2016) Evolution of reproductive isolation of Spodoptera frugiperda. In Allison, J. and Cardé, R. (eds) Sexual communication in moths. Chapter 20: 291-300.
[4] Hänniger, S. et al. (2017). Genetic basis of allochronic differentiation in the fall armyworm. BMC evolutionary biology, 17(1), 68. doi: 10.1186/s12862-017-0911-5
[5] Kost, S., Heckel, D. G., Yoshido, A., Marec, F., and Groot, A. T. (2016). AZ‐linked sterility locus causes sexual abstinence in hybrid females and facilitates speciation in Spodoptera frugiperda. Evolution, 70(6), 1418-1427. doi: 10.1111/evo.12940
[6] Mayr, E. (1942) Systematics and the origin of species. Columbia University Press, New York.
[7] Nagoshi, R. N. (2019). Evidence that a major subpopulation of fall armyworm found in the Western Hemisphere is rare or absent in Africa, which may limit the range of crops at risk of infestation. PloS one, 14(4). doi: 10.1371/journal.pone.0208966
[8] Orsucci, M., Moné, Y., Audiot, P., Gimenez, S., Nhim, S., Naït-Saïdi, R., Frayssinet, M., Dumont, G., Boudon, J.-P., Vabre, M., Rialle, S., Koual, R., Kergoat, G. J., Nagoshi, R. N., Meagher, R. L., d’Alençon, E. and Nègre N. (2020) Transcriptional differences between the two host strains of Spodoptera frugiperda (Lepidoptera: Noctuidae). bioRxiv, 263186, ver. 2 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/263186
[9] Pashley, D. P. (1988) Current Status of Fall Armyworm Host Strains. Florida Entomologist 71 (3): 227–34. doi: 10.2307/3495425
[10] Pogue, M. (2002). A World Revision of the Genus Spodoptera Guenée (Lepidoptera: Noctuidae). American Entomological Society.
[11] Schöfl, G., Heckel, D. G., and Groot, A. T. (2009). Time‐shifted reproductive behaviours among fall armyworm (Noctuidae: Spodoptera frugiperda) host strains: evidence for differing modes of inheritance. Journal of Evolutionary Biology, 22(7), 1447-1459. doi: 10.1111/j.1420-9101.2009.01759.x
[12] Schöfl, G., Dill, A., Heckel, D. G., and Groot, A. T. (2011). Allochronic separation versus mate choice: nonrandom patterns of mating between fall armyworm host strains. The American Naturalist, 177(4), 470-485. doi: 10.1086/658904

18 Jun 2020
article picture

Towards an improved understanding of molecular evolution: the relative roles of selection, drift, and everything in between

Molecular evolution through the joint lens of genomic and population processes.

Recommended by based on reviews by Benoit Nabholz and 1 anonymous reviewer

In their perspective article, F Pouyet and KJ Gilbert (2020), propose an interesting overview of all the processes that sculpt patterns of molecular evolution. This well documented article covers most (if not all) important facets of the recurrent debate that has marked the history of molecular evolution: the relative importance of natural selection and neutral processes (i.e. genetic drift). I particularly enjoyed reading this review, that instead of taking a clear position on the debate, catalogs patiently every pieces of information that can help understand how patterns we observed at the genome level, can be understood from a selectionnist point of view, from a neutralist one, and, to quote their title, from "everything in between". The review covers the classical objects of interest in population genetics (genetic drift, selection, demography and structure) but also describes several genomic processes (meiotic drive, linked selection, gene conversion and mutation processes) that obscure the interpretation of these population processes. The interplay between all these processes is very complex (to say the least) and have resulted in many cases in profound confusions while analyzing data. It is always very hard to fully acknowledge our ignorance and we have many times payed the price of model misspecifications. This review has the grand merit to improve our awareness in many directions. Being able to cover so many aspects of a wide topic, while expressing them simply and clearly, connecting concepts and observations from distant fields, is an amazing "tour de force". I believe this article constitutes an excellent up-to-date introduction to the questions and problems at stake in the field of molecular evolution and will certainly also help established researchers by providing them a stimulating overview supported with many relevant references.


[1] Pouyet F, Gilbert KJ (2020) Towards an improved understanding of molecular evolution: the relative roles of selection, drift, and everything in between. arXiv:1909.11490 [q-bio]. ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. url:

20 May 2020
article picture

How much does Ne vary among species?

Further questions on the meaning of effective population size

Recommended by based on reviews by 3 anonymous reviewers

In spite of its name, the effective population size, Ne, has a complex and often distant relationship to census population size, as we usually understand it. In truth, it is primarily an abstract concept aimed at measuring the amount of genetic drift occurring in a population at any given time. The standard way to model random genetic drift in population genetics is the Wright-Fisher model and, with a few exceptions, definitions of the effective population size stems from it: “a certain model has effective population size, Ne, if some characteristic of the model has the same value as the corresponding characteristic for the simple Wright-Fisher model whose actual size is Ne” (Ewens 2004). Since Sewall Wright introduced the concept of effective population size in 1931 (Wright 1931), it has flourished and there are today numerous definitions of it depending on the process being examined (genetic diversity, loss of alleles, efficacy of selection) and the characteristic of the model that is considered. These different definitions of the effective population size were generally introduced to address specific aspects of the evolutionary process. One aspect that has been hotly debated since the first estimates of genetic diversity in natural populations were published is the so-called Lewontin’s paradox (1974). Lewontin noted that the observed variation in heterozygosity across species was much smaller than one would expect from the neutral expectations calculated with the actual size of the species.
In essence, what Galtier and Rousselle propose in their clever paper is to introduce a new approach to compare effective population sizes across species and thereby a new way to address Lewontin’s paradox. Classically, the effective population size in this type of comparative genomic studies is simply estimated from nucleotide diversity at putatively neutral sites using the equation relating levels of diversity (θ) to mutation rate per generation (μ) and effective population size, Ne, θ = 4Neμ. As Galtier and Rousselle point out there are many issues with this approach. In particular, although we can now estimate θ very precisely, we generally do not have a reliable estimate of the mutation rate, and the method rests on many, unwarranted, assumptions; for example that the population is at mutation-drift equilibrium. Instead they propose to estimate the effective population size from the load of segregating deleterious mutations which can be summarized by the ratio of nonsynonymous to synonymous mutations, πN/πS: small-Ne species are expected to accumulate more deleterious mutations and carry a higher load than large-Ne ones at selection/drift equilibrium (Ohta et al. 1973; Welch et al. 2008). At first glance, this suggestion seems counterintuitive since considering sites under selection undoubtedly adds a new layer of complexity to an already intricate situation. Indeed, one is now bringing to the brew another elusive object, namely, the Distribution of Fitness Effect of mutations (DFE). However, estimating Ne from the load of segregating deleterious mutations may actually simplify the situation in two important ways. First, using πN/πS does not require assumption about μ (as the mutation rate will cancel out in the ratio). Second, the ratio of nonsynonymous to synonymous nucleotide diversity, reaches equilibrium faster than the nucleotide diversity at synonymous site after a change in population size, so we can hope for less sensitivity to (often unknown) recent demographic history (Brandvain and Wright 2016).
Extending recent developments in the estimation of the DFE, Galtier and Rousselle eventually obtain estimates of the average deleterious effect, , where Ne is the effective population size and is the mean fitness effect of non-synonymous mutations. Assuming further that distinct species share a common DFE and therefore a common , they obtain estimates of the between species ratio of Ne from the between species ratio of . Applying their newly developed approach to various datasets they conclude that the power of drift varies by a factor of at least 500 between large-Ne (Drosophila) and small-Ne species (H. sapiens). This is an order of magnitude larger than what would be obtained by comparing estimates of the variation in neutral diversity. Hence the proposed approach seems to have gone some way in making Lewontin’s paradox less paradoxical. But, perhaps more importantly, as the authors tersely point out at the end of the abstract their results further questions the meaning of Ne parameters in population genetics. And arguably this could well be the most important contribution of their study and something that is badly needed.


Brandvain Y, Wright SI (2016) The Limits of Natural Selection in a Nonequilibrium World. Trends in Genetics, 32, 201–210. doi: 10.1016/j.tig.2016.01.004
Ewens WJ (2010) Mathematical Population Genetics: Theoretical Introduction. Springer-Verlag New York Inc., New York, NY. doi: 10.1007/978-0-387-21822-9
Galtier N, Rousselle M (2020) How much does Ne vary among species? bioRxiv, 861849, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/861849
Lewontin RC (1974) The genetic basis of evolutionary change. Columbia University Press, New York. Ohta T (1973) Slightly Deleterious Mutant Substitutions in Evolution. Nature, 246, 96–98. doi: 10.1038/246096a0
Welch JJ, Eyre-Walker A, Waxman D (2008) Divergence and Polymorphism Under the Nearly Neutral Theory of Molecular Evolution. Journal of Molecular Evolution, 67, 418–426. doi: 10.1007/s00239-008-9146-9
Wright S (1931) Evolution in Mendelian Populations. Genetics, 16, 97–159. url:

18 May 2020
article picture

The insertion of a mitochondrial selfish element into the nuclear genome and its consequences

Some evolutionary insights into an accidental homing endonuclease passage from mitochondria to the nucleus

Recommended by based on reviews by Jan Engelstaedter and Yannick Wurm

Not all genetic elements composing genomes are there for the benefit of their carrier. Many have no consequences on fitness, or too mild ones to be eliminated by selection, and thus stem from neutral processes. Many others are indeed the product of selection, but one acting at a different level, increasing the fitness of some elements of the genome only, at the expense of the “organism” as a whole. These can be called selfish genetic elements, and come into a wide variety of flavours [1], illustrating many possible means to cheat with “fair” reproductive processes such as meiosis, and thus get overrepresented in the offspring of their hosts. Producing copies of itself through transposition is one such strategy; a very successful one indeed, explaining a large part of the genomic content of many organisms. Killing non carrier gametes following meiosis in heterozygous carriers is another one. Less know and less common is the ability of some elements to turn heterozygous carriers into homozygous ones, that will thus transmit the selfish elements to all offspring instead of half. This is achieved by nucleic sequences encoding so-called “Homing endonucleases” (HEs). These proteins tend to induce double strand breaks of DNA specifically in regions homologous to their own insertion sites. The recombination machinery is such that the intact homologous region, that is, the one carrying the HE sequence, is then used as a template for the reparation of the break, resulting in the effective conversion of a non-carrier allele into a carrier allele. Such elements can also occur in the mitochondrial genomes of organisms where mitochondria are not strictly transmitted by one parent only, offering mitochondrial HEs some opportunities for “homing” into new non carrier genomes. This is the case in yeasts, where HEs were first reported [2,3].
In this new study, based on genomic experimental data from the fungal maize pathogen Ustilago maydis, Julien Dutheil and colleagues [4] document one possible evolutionary pathway for which little evidence existed before: the passage of a mitochondrial HE into the nuclear genome. The GC content of this region leaves little doubt on its mitochondrial origin, and homologs can indeed be found in the mitochondrial genomes of close relatives. Strangely enough, U. maydis itself does not appear to carry this selfish element in its own mitochondria, suggesting it may have been acquired from a different species, or be subject to a sufficiently rapid turnover to have been recently lost.
Many elements of the story uncovered by this study remain mysterious. How, in the first place, was this HE gene inserted in a nuclear genomic region that shows no apparent homology with its original insertion site, making typical “homing” a not-so-likely explanation? This question may in fact be generalised to many HE systems: is the first insertion into a homing site always the product of a typical homing event, which implies the presence of an homologous template DNA fragment, or can HE genes insert through other means? But then, why specifically in regions that would be targeted by the nuclease they encode? What is the evolutionary fate of this newly inserted element? The new gene may well be on its way to pseudogenisation, as suggested by the truncation of its upper part, precluding its functioning as a HE, and the lack of evidence of selective constraints through dN/dS analysis; but the mutation generated by the insertion event may have phenotypic implications, possibly through the partial truncation of another gene, encoding a helicase. How old is this insertion? The fact that it has accumulated some mutations makes a very recent event rather unlikely, but this insertion has been detected in only one isolate of U. maydis, suggesting it is not so frequent in natural populations.
Whatever the answers to these open questions, that will hopefully be addressed by further work on this system, the present study has revealed that horizontal transmission enlarges the scope of possible evolutionary consequences of HE genes, that may move not only between mitochondrial genomes, but also occasionally into a nucleus.


[1] Burt, A., and Trivers, R. (2006). Genes in Conflict: The Biology of Selfish Genetic Elements. Belknap Press.
[2] Coen, D., Deutch, J., Netter, P., Petrochillo, E., and Slonimski, P. (1970). Mitochondrial genetics. I. Methodology and phenomenology. Symposia of the Society for Experimental Biology, 24, 449-496.
[3] Colleaux, L., D’Auriol, L., Betermier, M., Cottarel, G., Jacquier, A., Galibert, F., and Dujon, B. (1986). Universal code equivalent of a yeast mitochondrial intron reading frame is expressed into E. coli as a specific double strand endonuclease. Cell, 44, 521–533. doi: 10.1016/0092-8674(86)90262-X
[4] Dutheil, J. Y., Münch, K., Schotanus, K., Stukenbrock, E. H., and Kahmann, R. (2020). The insertion of a mitochondrial selfish element into the nuclear genome and its consequences. bioRxiv, 787044, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/787044

14 May 2020
article picture

Potential adaptive divergence between subspecies and populations of snapdragon plants inferred from QST – FST comparisons

From populations to subspecies… to species? Contrasting patterns of local adaptation in closely-related taxa and their potential contribution to species divergence

Recommended by based on reviews by Sophie Karrenberg, Santiago C. Gonzalez-Martinez and 1 anonymous reviewer

Elevation gradients are convenient and widely used natural setups to study local adaptation, particularly in these times of rapid climate change [e.g. 1]. Marin and her collaborators [2] did not follow the mainstream, however. Instead of tackling adaptation to climate change, they used elevation gradients to address another crucial evolutionary question [3]: could adaptation to altitude lead to ecological speciation, i.e. reproductive isolation between populations in spite of gene flow? More specifically, they examined how much local adaptation to environmental variation differed among closely-related, recently diverged subspecies. They studied several populations of two subspecies of snapdragon (Antirrhinum majus), with adjacent geographical distributions. Using common garden experiments and the classical, but still useful, QST-FST comparison, they demonstrate contrasting patterns of local adaptation to altitude between the two subspecies, with several traits under divergent selection in A. majus striatum but none in A. majus pseudomajus. These differences in local adaptation may contribute to species divergence, and open many stimulating questions on the underlying mechanisms, such as the identity of environmental drivers or contribution of reproductive isolation involving flower color polymorphism.


[1] Anderson, J. T., and Wadgymar, S. M. (2020). Climate change disrupts local adaptation and favours upslope migration. Ecology letters, 23(1), 181-192. doi: 10.1111/ele.13427
[2] Marin, S., Gibert, A., Archambeau, J., Bonhomme, V., Lascoste, M., and Pujol, B. (2020). Potential adaptive divergence between subspecies and populations of snapdragon plants inferred from QST – FST comparisons. Zenodo, 3628168, ver. 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology. doi: 10.5281/zenodo.3628168
[3] Schluter, D. (2009). Evidence for ecological speciation and its alternative. Science, 323(5915), 737-741. doi: 10.1126/science.1160006

05 May 2020
article picture

Meta-population structure and the evolutionary transition to multicellularity

The ecology of evolutionary transitions to multicellularity

Recommended by based on reviews by 2 anonymous reviewers

The evolutionary transition to multicellular life from free-living, single-celled ancestors has occurred independently in multiple lineages [1-5]. This evolutionary transition to cooperative group living can be difficult to explain given the fitness advantages enjoyed by the non-cooperative, single-celled organisms that still numerically dominate life on earth [1,6,7]. Although several hypotheses have been proposed to explain the transition to multicellularity, a common theme is the abatement of the efficacy of natural selection among the single cells during the free-living stage and the promotion of the efficacy of selection among groups of cells during the cooperative stage, an argument reminiscent of those from George Williams’ seminal book [8,9]. The evolution of life cycles appears to be a key step in the transition to multicellularity as it can align fitness advantages of the single-celled 'reproductive' stage with that of the cooperative 'organismal' stage [9-12]. That is, the evolution of life cycles allows natural selection to operate over timescales longer than that of the doubling time of the free-living cells [13]. Despite the importance of this issue, identifying the range of ecological conditions that reduce the importance of natural selection at the single-celled, free-living stage and increase the importance of selection among groups of cooperating cells has not been addressed empirically.
Rose et al [14] addressed this issue in a series of real time evolution experiments with bacteria in which they varied the intensity of between-group versus individual-level selection. Central to the experiment is an ecological scaffold that requires lineages to switch between free-living (reproductive) and group-living (organismal) life-stages. One ecological scenario severely limited natural selection at the single-celled, free-living stage by maintaining separation among the reproductive propagules originating from different organisms (groups of cells derived from a single ancestral cell). A second ecological scenario mixed the reproductive propagules from different organisms, leading to severe competition between single cells derived from both the same and other 'organisms'. These ecological scenarios lead to very different evolutionary outcomes. Limiting competition, and thus natural selection, at the reproductive propagule stage promoted traits that favored organismal fitness at the expense of cell division, while competition among single-cells favored traits that promote cell-level traits at the expense of group-level traits. The authors investigate a range of measures of cell and group-level performance in order to understand the mechanisms favoring organismal versus single-cell fitness. Importantly, an evolutionary trade-off between traits promoting organismal fitness and single-cell fitness appears to constrain maximizing fitness of both phases, especially when strong natural selection acts on the single-cell stage.
This article is incredibly thorough and utilizes multiple experiments and levels of argument in order to support the conclusions. The authors include considerable discussion of broader topics surrounding the immediate hypotheses throughout the article, which add both clarity and complexity. The complexity of the experiments, results, and the topic itself lead to a thought-heavy article in a throwback to the monographs of old; expect to read each section multiple times.


[1] Maynard Smith, J. and Szathmáry, E. (1995). The Major Transitions in Evolution. Oxford, UK: Freeman. p 346.
[2] Bonner, J. T. (1998). The origins of multicellularity. Integrative Biology: Issues, News, and Reviews: Published in Association with The Society for Integrative and Comparative Biology, 1(1), 27-36. doi: 10.1002/(SICI)1520-6602(1998)1:1<27::AID-INBI4>3.0.CO;2-6
[3] Kaiser, D. (2001). Building a multicellular organism. Annual review of genetics, 35(1), 103-123. doi: 10.1146/annurev.genet.35.102401.090145
[4] Medina, M., Collins, A. G., Taylor, J. W., Valentine, J. W., Lipps, J. H., Amaral-Zettler, L., and Sogin, M. L. (2003). Phylogeny of Opisthokonta and the evolution of multicellularity and complexity in Fungi and Metazoa. International Journal of Astrobiology, 2(3), 203-211. doi: 10.1017/S1473550403001551
[5] King, N. (2004). The unicellular ancestry of animal development. Developmental cell, 7(3), 313-325. doi: 10.1016/j.devcel.2004.08.010
[6] Michod R. E. (1999). Darwinian Dynamics. Evolutionary Transitions in Fitness and Individuality. Princeton, NJ: Princeton Univ. Press. p 262.
[7] Lynch, M. (2007). The frailty of adaptive hypotheses for the origins of organismal complexity. Proceedings of the National Academy of Sciences, 104(suppl 1), 8597-8604. doi: 10.1073/pnas.0702207104
[8] Williams, G. C. (1996). Adaptation and Natural Selection, Reprint edition. Princeton, NJ: Princeton Univ. Press.
[9] Grosberg, R. K., and Strathmann, R. R. (2007). The evolution of multicellularity: a minor major transition?. Annu. Rev. Ecol. Evol. Syst., 38, 621-654. doi: 10.1146/annurev.ecolsys.36.102403.114735
[10] Buss, L. W. (1987). The Evolution of Individuality. Princeton, NJ: Princeton Univ. Press.
[11] Godfrey-Smith, P. (2009). Darwinian Populations and Natural Selection. Oxford University Press, USA.
[12] Van Gestel, J., and Tarnita, C. E. (2017). On the origin of biological construction, with a focus on multicellularity. Proceedings of the National Academy of Sciences, 114(42), 11018-11026. doi: 10.1073/pnas.1704631114
[13] Black, A. J., Bourrat, P., and Rainey, P. B. (2020). Ecological scaffolding and the evolution of individuality. Nature Ecology & Evolution, 4(3), 426-436. doi: 10.1038/s41559-019-1086-9
[14] Rose, C. J., Hammerschmidt, K., Pichugin, Y. and Rainey, P. B. (2020). Meta-population structure and the evolutionary transition to multicellularity. bioRxiv, 407163, ver. 5 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/407163

03 May 2020
article picture

When does gene flow facilitate evolutionary rescue?

Reconciling the upsides and downsides of migration for evolutionary rescue

Recommended by based on reviews by 3 anonymous reviewers

The evolutionary response of populations to changing or novel environments is a topic that unites the interests of evolutionary biologists, ecologists, and biomedical researchers [1]. A prominent phenomenon in this research area is evolutionary rescue, whereby a population that is otherwise doomed to extinction survives due to the spread of new or pre-existing mutations that are beneficial in the new environment. Scenarios of evolutionary rescue require a specific set of parameters: the absolute growth rate has to be negative before the rescue mechanism spreads, upon which the growth rate becomes positive. However, potential examples of its relevance exist (e.g., [2]). From a theoretical point of view, the technical challenge but also the beauty of evolutionary rescue models is that they combine the study of population dynamics (i.e., changes in the size of populations) and population genetics (i.e., changes in the frequencies in the population). Together, the potential relevance of evolutionary rescue in nature and the models' theoretical appeal has resulted in a suite of modeling studies on the subject in recent years.
In this manuscript [3], Tomasini and Peischl address a question that has been contentiously discussed in the literature: when does migration favor evolutionary rescue? They expand on past work (specifically, [4, 5]) by studying the influence of the interaction of the speed and severity of environmental change and the amount of dispersal on the probability of evolutionary rescue. They develop simple analytical results (complemented by simulations) for a haploid one-locus model of two populations connected by gene flow, where both populations deteriorate successively such that evolutionary rescue is required for the metapopulation to survive. For example, the authors derive a simple analytical condition demonstrating that migration between the subpopulations favors evolutionary rescue if environmental change occurs slowly across the two populations (which leaves time for the second population to serve as an immigration source), if the new environment is very harsh and/or if rescue mutations are strongly beneficial in the new environment. The latter conditions ensure that the rescue mutations can spread easily in the new environment without much competition with immigrating, maladapted, genotypes. This result is intuitive and connects between traditional single and multiple-deme models.
Altogether, Tomasini and Peischl present an extensive theoretical study and address also the effect of various tweaks to the model assumptions, such as asymmetries in gene flow and/or carrying capacities, and the effects of different density regulation and local growth rates. They successfully made an effort to explain and interpret their results for a general audience, such that also non-theoreticians should not be afraid to take a look at this manuscript.


[1] Bell, G. (2017). Evolutionary Rescue. Annual Review of Ecology, Evolution, and Systematics 48(1), 605-627. doi: 10.1146/annurev-ecolsys-110316-023011
[2] Oziolor, E. M., Reid, N. M., Yair, S. et al. (2019). Adaptive introgression enables evolutionary rescue from extreme environmental pollution. Science, 364(6439), 455-457. doi: 10.1126/science.aav4155
[3] Tomasini, M. and Peischl, S. (2020) When does gene flow facilitate evolutionary rescue? bioRxiv, 622142, ver. 5 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/622142
[4] Uecker, H., Otto, S. P., and Hermisson, J. (2014). Evolutionary rescue in structured populations. The American Naturalist, 183(1), E17-E35. doi: 10.1086/673914
[5] Tomasini, M., and Peischl, S. (2018). Establishment of locally adapted mutations under divergent selection. Genetics, 209(3), 885-895. doi: 10.1534/genetics.118.301104

23 Apr 2020
article picture

How do invasion syndromes evolve? An experimental evolution approach using the ladybird Harmonia axyridis

Selection on a single trait does not recapitulate the evolution of life-history traits seen during an invasion

Recommended by and based on reviews by 2 anonymous reviewers

Biological invasions are natural experiments, and often show that evolution can affect dynamics in important ways [1-3]. While we often think of invasions as a conservation problem stemming from anthropogenic introductions [4,5], biological invasions are much more commonplace than this, including phenomena as diverse as natural range shifts, the spread of novel pathogens, and the growth of tumors. A major question across all these settings is which set of traits determine the ability of a population to invade new space [6,7]. Traits such as: increased growth or reproductive rate, dispersal ability and ability to defend from predation often show large evolutionary shifts across invasion history [1,6,8]. Are such multi-trait shifts driven by selection on multiple traits, or a correlated response by multiple traits to selection on one? Resolving this question is important for both theoretical and practical reasons [9,10]. But despite the importance of this issue, it is not easy to perform the necessary manipulative experiments [9].
Foucaud et al. [11] tackled this issue by performing experimental evolution on source populations of the invasive ladybug Harmonia axyridis. The authors tested if selection on a single trait could generate correlated responses in other life history traits. Specifically, they used experimental evolution to impose divergent selection on female mass, and reproductive timing. After ten generations, they found that selection for weight did not affect almost any other life history trait. However, nine generations of selection for faster reproduction led to correlated phenotypic changes in developmental, reproduction and survival rate of populations, although not always in the direction we might have expected. Despite this correlated response, none of their selected lines were able to fully recapitulate the trait shifts seen in natural invasions of this species. This implies that selection during natural invasions is operating on multiple traits; a finding in agreement with our growing understanding of how selection acts during introduction and invasion [12,13].
Populations undergoing a colonization process may also be subject to a multitude of different selective pressures [14,15]. The authors expanded their work in this direction by testing whether food availability alters the observed correlations between life history traits. The pervasiveness of genotype by environment interactions observed also points to a role for multiple selective pressures in shaping the suite of life-history shifts observed in wild ladybug populations. The work from Foucaud and colleagues [11] adds to a small but growing list of important studies that use experimental evolution to investigate how life-history traits evolve, and how they evolve during invasions in particular.


[1] Sakai, A.K., Allendorf, F.W., Holt, J.S. et al. (2001). The population biology of invasive species. Annual review of ecology and systematics, 32(1), 305-332. doi: 10.1146/annurev.ecolsys.32.081501.114037
[2] Hairston Jr, N. G., Ellner, S. P., Geber, M. A., Yoshida, T. and Fox, J. A. (2005). Rapid evolution and the convergence of ecological and evolutionary time. Ecology letters, 8(10), 1114-1127. doi: 10.1111/j.1461-0248.2005.00812.x
[3] Chuang, A. and Peterson, C. R. (2016). Expanding population edges: theories, traits, and trade‐offs. Global change biology, 22(2), 494-512. doi: 10.1111/gcb.13107
[4] Whitney, K. D. and Gabler, C. A. (2008). Rapid evolution in introduced species,‘invasive traits’ and recipient communities: challenges for predicting invasive potential. Diversity and Distributions, 14(4), 569-580. doi: 10.1111/j.1472-4642.2008.00473.x
[5] Catullo, R. A., Llewelyn, J., Phillips, B. L. and Moritz, C. C. (2019). The Potential for Rapid Evolution under Anthropogenic Climate Change. Current Biology, 29(19), R996-R1007. doi: 10.1016/j.cub.2019.08.028
[6] Suarez, A. V. and Tsutsui, N. D. (2008). The evolutionary consequences of biological invasions. Molecular Ecology, 17(1), 351-360. doi: 10.1111/j.1365-294X.2007.03456.x
[7] Deforet, M., Carmona-Fontaine, C., Korolev, K. S. and Xavier, J. B. (2019). Evolution at the edge of expanding populations. The American Naturalist, 194(3), 291-305. doi: 10.1086/704594
[8] Phillips, B. L., Brown, G. P., and Shine, R. (2010). Life‐history evolution in range‐shifting populations. Ecology, 91(6), 1617-1627. doi: 10.1890/09-0910.1
[9] Colautti, R. I. and Lau, J. A. (2015). Contemporary evolution during invasion: evidence for differentiation, natural selection, and local adaptation. Molecular ecology, 24(9), 1999-2017. doi: 10.1111/mec.13162
[10] Szűcs, M., Melbourne, B. A., Tuff, T., Weiss‐Lehman, C. and Hufbauer, R. A. (2017). Genetic and demographic founder effects have long‐term fitness consequences for colonising populations. Ecology Letters, 20(4), 436-444. doi: 10.1111/ele.12743
[11] Foucaud, J., Hufbauer, R. A., Ravigné, V., Olazcuaga, L., Loiseau, A., Ausset, A., Wang, S., Zang, L.-S., Lemenager, N., Tayeh, A., Weyna, A., Gneux, P., Bonnet, E., Dreuilhe, V., Poutout, B., Estoup, A. and Facon, B. (2020). How do invasion syndromes evolve? An experimental evolution approach using the ladybird Harmonia axyridis. bioRxiv, 849968 ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/849968
[12] Simons, A. M. (2003). Invasive aliens and sampling bias. Ecology Letters, 6(4), 278-280. doi: 10.1046/j.1461-0248.2003.00430.x
[13] Phillips, B. L. and Perkins, T. A. (2019). Spatial sorting as the spatial analogue of natural selection. Theoretical Ecology, 12(2), 155-163. doi: 10.1007/s12080-019-0412-9
[14] Lavergne, S. and Molofsky, J. (2007). Increased genetic variation and evolutionary potential drive the success of an invasive grass. Proceedings of the National Academy of Sciences, 104(10), 3883-3888. doi: 10.1073/pnas.0607324104
[15] Moran, E. V. and Alexander, J. M. (2014). Evolutionary responses to global change: lessons from invasive species. Ecology Letters, 17(5), 637-649. doi: 10.1111/ele.12262

03 Apr 2020
article picture

Evolution at two time-frames: ancient and common origin of two structural variants involved in local adaptation of the European plaice (Pleuronectes platessa)

Genomic structural variants involved in local adaptation of the European plaice

Recommended by based on reviews by 3 anonymous reviewers

Awareness has been growing that structural variants in the genome of species play a fundamental role in adaptive evolution and diversification [1]. Here, Le Moan and co-authors [2] report empirical genomic-wide SNP data on the European plaice (Pleuronectes platessa) across a major environmental transmission zone, ranging from the North Sea to the Baltic Sea. Regions of high linkage disequilibrium suggest the presence of two structural variants that appear to have evolved 220 kya. These two putative structural variants show weak signatures of isolation by distance when contrasted against the rest of the genome, but the frequency of the different putative structural variants appears to co-vary in some parts of the studied range with the environment, indicating the involvement of both selective and neutral processes. This study adds to the mounting body of evidence that structural genomic variants harbour significant information that allows species to respond and adapt to the local environmental context.


[1] Wellenreuther, M., Mérot, C., Berdan, E., & Bernatchez, L. (2019). Going beyond SNPs: the role of structural genomic variants in adaptive evolution and species diversification. Molecular ecology, 28(6), 1203-1209. doi: 10.1111/mec.15066
[2] Le Moan, A. Bekkevold, D. & Hemmer-Hansen J. (2020). Evolution at two time-frames: ancient and common origin of two structural variants involved in local adaptation of the European plaice (Pleuronectes platessa). bioRxiv, 662577, ver. 5 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/662577

11 Mar 2020
article picture

Phylogenomic approaches reveal how a climatic inversion and glacial refugia shape patterns of diversity in an African rain forest tree species

Remarkable insights into processes shaping African tropical tree diversity

Recommended by based on reviews by Miguel de Navascués, Lars Chatrou and Oscar Vargas

Tropical biodiversity is immense, under enormous threat, and yet still poorly understood. Global climatic breakdown and habitat destruction are impacting on and removing this diversity before we can understand how the biota responds to such changes, or even fully appreciate what we are losing [1]. This is particularly the case for woody shrubs and trees [2] and for the flora of tropical Africa [3].  

Helmstetter et al. [4] have taken a significant step to improve our understanding of African tropical tree diversity in the context of past climatic change. They have done so by means of a remarkably in-depth analysis of one species of the tropical plant family Annonaceae: Annickia affinis [5]. A. affinis shows a distribution pattern in Africa found in various plant (but interestingly not animal) groups: a discontinuity between north and south of the equator [6]. There is no obvious physical barrier to cause this discontinuity, but it does correspond with present day distinct northern and southern rainy seasons. Various explanations have been proposed for this discontinuity, set out as hypotheses to be tested in this paper: climatic fluctuations resulting in changes in plant distributions in the Pleistocene, or differences in flowering times or in ecological niche between northerly and southerly populations. These explanations are not mutually exclusive, but they can be tested using phylogenetic inference – if you can sample variable enough sequence data from enough individuals – complemented with analysis of ecological niches and traits.  

Using targeted sequence capture, the authors amassed a dataset representing 351 nuclear markers for 112 individuals of A. affinis. This dataset is impressive for a number of reasons: First, sampling such a species across such a wide range in tropical Africa presents numerous challenges of itself. Second, the technical achievement of using this still relatively new sequencing technique with a custom set of baits designed specifically for this plant family [7] is also considerable. The result is a volume of data that just a few years ago would not have been feasible to collect, and which now offers the possibility to meaningfully analyse DNA sequence variation within a species across numerous independent loci of the nuclear genome. This is the future of our research field, and the authors have ably demonstrated some of its possibilities.  

Using this data, they performed on the one hand different population genetic clustering approaches, and on the other, different phylogenetic inference methods. I would draw attention to their use and comparison of coalescence and network-based approaches, which can account for the differences between gene trees that might be expected between populations of a single species. The results revealed four clades and a consistent sequence of divergences between them. The authors inferred past shifts in geographic range (using a continuous state phylogeographic model), depicting a biogeographic scenario involving a dispersal north over the north/south discontinuity; and demographic history, inferring in some (but not all) lineages increases in effective population size around the time of the last glacial maximum, suggestive of expansion from refugia. Using georeferenced specimen data, they compared ecological niches between populations, discovering that overlap was indeed smallest comparing north to south. Just the phenology results were effectively inconclusive: far better data on flowering times is needed than can currently be harvested from digitised herbarium specimens.  

Overall, the results add to the body of evidence for the impact of Pleistocene climatic changes on population structure, and for niche differences contributing to the present day north/south discontinuity. However, they also paint a complex picture of idiosyncratic lineage-specific responses, even within a single species. With the increasing accessibility of the techniques used here we can look forward to more such detailed analyses of independent clades necessary to test and to expand on these conclusions, better to understand the nature of our tropical plant diversity while there is still opportunity to preserve it for future generations.  


[1] Mace, G. M., Gittleman, J. L., and Purvis, A. (2003). Preserving the Tree of Life. Science, 300(5626), 1707–1709. doi: 10.1126/science.1085510
[2] Humphreys, A. M., Govaerts, R., Ficinski, S. Z., Nic Lughadha, E., and Vorontsova, M. S. (2019). Global dataset shows geography and life form predict modern plant extinction and rediscovery. Nature Ecology and Evolution, 3(7), 1043–1047. doi: 10.1038/s41559-019-0906-2
[3] Stévart, T., Dauby, G., Lowry, P. P., Blach-Overgaard, A., Droissart, V., Harris, D. J., Mackinder, B. A., Schatz, G. E., Sonké, B., Sosef, M. S. M., Svenning, J. C., Wieringa, J. J., and Couvreur, T. L. P. (2019). A third of the tropical African flora is potentially threatened with extinction. Science Advances, 5(11), eaax9444. doi: 10.1126/sciadv.aax9444
[4] Helmstetter, A. J., Amoussou, B. E. N., Bethune, K., Kandem, N. G., Kakaï, R. G., Sonké, B., and Couvreur, T. L. P. (2020). Phylogenomic approaches reveal how a climatic inversion and glacial refugia shape patterns of diversity in an African rain forest tree species. BioRxiv, 807727, ver. 3 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/807727
[5] Versteegh, C. P. C., and Sosef, M. S. M. (2007). Revision of the African genus Annickia (Annonaceae). Systematics and Geography of Plants, 77, 91–118.
[6] Hardy, O. J., Born, C., Budde, K., Daïnou, K., Dauby, G., Duminil, J., Ewédjé, E.-E. B. K., Gomez, C., Heuertz, M., Koffi, G. K., Lowe, A. J., Micheneau, C., Ndiade-Bourobou, D., Piñeiro, R., and Poncet, V. (2013). Comparative phylogeography of African rain forest trees: A review of genetic signatures of vegetation history in the Guineo-Congolian region. Comptes Rendus Geoscience, 345(7), 284-296. doi: 10.1016/j.crte.2013.05.001
[7] Couvreur, T. L. P., Helmstetter, A. J., Koenen, E. J. M., Bethune, K., Brandão, R. D., Little, S. A., Sauquet, H., and Erkens, R. H. J. (2019). Phylogenomics of the Major Tropical Plant Family Annonaceae Using Targeted Enrichment of Nuclear Genes. Frontiers in Plant Science, 9. doi: 10.3389/fpls.2018.01941

17 Feb 2020
article picture

Epistasis, inbreeding depression and the evolution of self-fertilization

Epistasis and the evolution of selfing

Recommended by based on reviews by Nick Barton and 1 anonymous reviewer

The evolution of selfing results from a balance between multiple evolutionary forces. Selfing provides an "automatic advantage" due to the higher efficiency of selfers to transmit their genes via selfed and outcrossed offspring. Selfed offspring, however, may suffer from inbreeding depression. In principle the ultimate evolutionary outcome is easy to predict from the relative magnitude of these two evolutionary forces [1,2]. Yet, several studies explicitly taking into account the genetic architecture of inbreeding depression noted that these predictions are often too restrictive because selfing can evolve in a broader range of conditions [3,4].
The present work by Abu Awad and Roze [5] provides an analytic understanding of these results. Abu Awad and Roze analyse the evolution of selfing in a multilocus model where some loci are coding for selfing while others are under direct selection. The evolution of selfing depends on (i) the classical benefit of selfing (automatic advantage), (ii) the cost of selfing due to inbreeding depression, (iii) the association between the loci coding for selfing and the loci under direct selection (likely to be positive because selfing is expected to be found in better purged genetic backgrounds) and (iv) the association between the loci coding for selfing and the linkage between loci under selection (this final term depends on the magnitude and the type of epistasis). Because these last two terms depend on genetic associations they are expected to play in when selection is strong and recombination is small. These last two terms explain why selfing is evolving under a range of conditions which is broader than predicted by earlier theoretical models. The match between the approximations for the different terms acting on the evolution of selfing and individual based simulations (for different fitness landscapes) is very convincing. In particular, this analysis also yields new results on the effect of different types of epistasis on inbreeding depression.
Another remarkable and important feature of this work is its readability. The analysis of multilocus models rely on several steps and approximations that often result in overwhelmingly complex papers. Abu Awad and Roze’s paper [5] is dense but it provides a very clear and comprehensive presentation of the interplay between multiple evolutionary forces acting on the evolution of selfing.


[1] Holsinger, K. E., Feldman, M. W., and Christiansen, F. B. (1984). The evolution of self-fertilization in plants: a population genetic model. The American Naturalist, 124(3), 446-453. doi: 10.1086/284287
[2] Lande, R., and Schemske, D. W. (1985). The evolution of self‐fertilization and inbreeding depression in plants. I. Genetic models. Evolution, 39(1), 24-40. doi: 10.1111/j.1558-5646.1985.tb04077.x
[3] Charlesworth, D., Morgan, M. T., and Charlesworth, B. (1990). Inbreeding depression, genetic load, and the evolution of outcrossing rates in a multilocus system with no linkage. Evolution, 44(6), 1469-1489. doi: 10.1111/j.1558-5646.1990.tb03839.x
[4] Uyenoyama, M. K., and Waller, D. M. (1991). Coevolution of self-fertilization and inbreeding depression I. Mutation-selection balance at one and two loci. Theoretical population biology, 40(1), 14-46. doi: 10.1016/0040-5809(91)90045-H
[5] Abu Awad, D. and Roze, D. (2020). Epistasis, inbreeding depression and the evolution of self-fertilization. bioRxiv, 809814, ver. 4 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/809814

23 Jan 2020
article picture

A novel workflow to improve multi-locus genotyping of wildlife species: an experimental set-up with a known model system

Improving the reliability of genotyping of multigene families in non-model organisms

Recommended by based on reviews by Sebastian Ernesto Ramos-Onsins, Helena Westerdahl and Thomas Bigot

The reliability of published scientific papers has been the topic of much recent discussion, notably in the biomedical sciences [1]. Although small sample size is regularly pointed as one of the culprits, big data can also be a concern. The advent of high-throughput sequencing, and the processing of sequence data by opaque bioinformatics workflows, mean that sequences with often high error rates are produced, and that exact but slow analyses are not feasible.
The troubles with bioinformatics arise from the increased complexity of the tools used by scientists, and from the lack of incentives and/or skills from authors (but also reviewers and editors) to make sure of the quality of those tools. As a much discussed example, a bug in the widely used PLINK software [2] has been pointed as the explanation [3] for incorrect inference of selection for increased height in European Human populations [4].
High-throughput sequencing often generates high rates of genotyping errors, so that the development of bioinformatics tools to assess the quality of data and correct them is a major issue. The work of Gillingham et al. [5] contributes to the latter goal. In this work, the authors propose a new bioinformatics workflow (ACACIA) for performing genotyping analysis of multigene complexes, such as self-incompatibility genes in plants, major histocompatibility genes (MHC) in vertebrates, and homeobox genes in animals, which are particularly challenging to genotype in non-model organisms. PCR and sequencing of multigene families generate artefacts, hence spurious alleles. A key to Gillingham et al.‘ s method is to call candidate genes based on Oligotyping, a software pipeline originally conceived for identifying variants from microbiome 16S rRNA amplicons [6]. This allows to reduce the number of false positives and the number of dropout alleles, compared to previous workflows.
This method is not based on an explicit probability model, and thus it is not conceived to provide a control of the rate of errors as, say, a valid confidence interval should (a confidence interval with coverage c for a parameter should contain the parameter with probability c, so the error rate 1- c is known and controlled by the user who selects the value of c). However, the authors suggest a method to adapt the settings of ACACIA to each application.
To compare and validate the new workflow, the authors have constructed new sets of genotypes representing different extents copy number variation, using already known genotypes from chicken MHC. In such conditions, it was possible to assess how many alleles are not detected and what is the rate of false positives. Gillingham et al. additionally investigated the effect of using non-optimal primers. They found better performance of ACACIA compared to a preexisting pipeline, AmpliSAS [7], for optimal settings of both methods. However, they do not claim that ACACIA will always be better than AmpliSAS. Rather, they warn against the common practice of using the default settings of the latter pipeline. Altogether, this work and the ACACIA workflow should allow for better ascertainment of genotypes from multigene families.


[1] Ioannidis, J. P. A, Greenland, S., Hlatky, M. A., Khoury, M. J., Macleod, M. R., Moher, D., Schulz, K. F. and Tibshirani, R. (2014) Increasing value and reducing waste in research design, conduct, and analysis. The Lancet, 383, 166-175. doi: 10.1016/S0140-6736(13)62227-8
[2] Chang, C. C., Chow, C. C., Tellier, L. C. A. M., Vattikuti, S., Purcell, S. M. and Lee, J. J. (2015) Second-generation PLINK: rising to the challenge of larger and richer datasets. GigaScience, 4, 7, s13742-015-0047-8. doi: 10.1186/s13742-015-0047-8
[3] Robinson, M. R. and Visscher, P. (2018) Corrected sibling GWAS data release from Robinson et al.
[4] Field, Y., Boyle, E. A., Telis, N., Gao, Z., Gaulton, K. J., Golan, D., Yengo, L., Rocheleau, G., Froguel, P., McCarthy, M.I . and Pritchard J. K. (2016) Detection of human adaptation during the past 2000 years. Science, 354(6313), 760-764. doi: 10.1126/science.aag0776
[5] Gillingham, M. A. F., Montero, B. K., Wihelm, K., Grudzus, K., Sommer, S. and Santos P. S. C. (2020) A novel workflow to improve multi-locus genotyping of wildlife species: an experimental set-up with a known model system. bioRxiv 638288, ver. 3 peer-reviewed and recommended by Peer Community In Evolutionary Biology. doi: 10.1101/638288
[6] Eren, A. M., Maignien, L., Sul, W. J., Murphy, L. G., Grim, S. L., Morrison, H. G., and Sogin, M.L. (2013) Oligotyping: differentiating between closely related microbial taxa using 16S rRNA gene data. Methods in Ecology and Evolution 4(12), 1111-1119. doi: 10.1111/2041-210X.12114
[7] Sebastian, A., Herdegen, M., Migalska, M. and Radwan, J. (2016) AMPLISAS: a web server for multilocus genotyping using next‐generation amplicon sequencing data. Mol Ecol Resour, 16, 498-510. doi: 10.1111/1755-0998.12453

20 Jan 2020
article picture

A young age of subspecific divergence in the desert locust Schistocerca gregaria, inferred by ABC Random Forest

Estimating recent divergence history: making the most of microsatellite data and Approximate Bayesian Computation approaches

Recommended by and based on reviews by Michael D Greenfield and 2 anonymous reviewers

The present-day distribution of extant species is the result of the interplay between their past population demography (e.g., expansion, contraction, isolation, and migration) and adaptation to the environment. Shedding light on the timing and magnitude of key demographic events helps identify potential drivers of such events and interaction of those drivers, such as life history traits and past episodes of environmental shifts.

The understanding of the key factors driving species evolution gives important insights into how the species may respond to changing conditions, which can be particularly relevant for the management of harmful species, such as agricultural pests (e.g. [1]). Meaningful demographic inferences present major challenges. These include formulating evolutionary scenarios fitting species biology and the eco-geographical context and choosing informative molecular markers and accurate quantitative approaches to statistically compare multiple demographic scenarios and estimate the parameters of interest. A further issue comes with result interpretation. Accurately dating the inferred events is far from straightforward since reliable calibration points are necessary to translate the molecular estimates of the evolutionary time into absolute time units (i.e. years). This can be attempted in different ways, such as by using fossil and archaeological records, heterochronous samples (e.g. ancient DNA), and/or mutation rate estimated from independent data (e.g. [2], [3] for review). Nonetheless, most experimental systems rarely meet these conditions, hindering the comprehensive interpretation of results.

The contribution of Chapuis et al. [4] addresses these issues to investigate the recent history of the African insect pest Schistocerca gregaria (desert locust). They apply Approximate Bayesian Computation-Random Forest (ABC-RF) approaches to microsatellite markers. Owing to their fast mutation rate microsatellite markers offer at least two advantages: i) suitability for analyzing recently diverged populations, and ii) direct estimate of the germline mutation rate in pedigree samples. The work of Chapuis et al. [4] benefits of both these advantages, since they have estimates of mutation rate and allele size constraints derived from germline mutations in the species [5].

The main aim of the study is to infer the history of divergence of the two subspecies of the desert locust, which have spatially disjoint distribution corresponding to the dry regions of North and West-South Africa. They first use paleo-vegetation maps to formulate hypotheses about changes in species range since the last glacial maximum. Based on them, they generate 12 divergence models. For the selection of the demographic model and parameter estimation, they apply the recently developed ABC-RF approach, a powerful inferential tool that allows optimizing the use of summary statistics information content, among other advantages [6]. Some methodological novelties are also introduced in this work, such as the computation of the error associated with the posterior parameter estimates under the best scenario. The accuracy of timing estimate is assured in two ways: i) by the use of microsatellite markers with known evolutionary dynamics, as underlined above, and ii) by assessing the divergence time threshold above which posterior estimates are likely to be biased by size homoplasy and limits in allele size range [7]. The best-supported model suggests a recent divergence event of the subspecies of S. gregaria (around 2.6 kya) and a reduction of populations size in one of the subspecies (S. g. flaviventris) that colonized the southern distribution area. As such, results did not support the hypothesis that the southward colonization was driven by the expansion of African dry environments associated with the last glacial maximum, as it has been postulated for other arid-adapted species with similar African disjoint distributions [8]. The estimated time of divergence points at a much more recent origin for the two subspecies, during the late Holocene, in a period corresponding to fairly stable arid conditions similar to current ones [9,10].

Although the authors cannot exclude that their microsatellite data bear limited information on older colonization events than the last one, they bring arguments in favour of alternative explanations. The hypothesis privileged does not involve climatic drivers, but the particularly efficient dispersal behaviour of the species, whose individuals are able to fly over long distances (up to thousands of kilometers) under favourable windy conditions. A single long-distance dispersal event by a few individuals would explain the genetic signature of the bottleneck. There is a growing number of studies in phylogeography in arid regions in the Southern hemisphere, but the impact of past climate changes on the species distribution in this region remains understudied relative to the Northern hemisphere [11,12].

The study presented by Chapuis et al. [4] offers several important insights into demographic changes and the evolutionary history of an agriculturally important pest species in Africa, which could also mirror the history of other organisms in the continent. As the authors point out, there are necessarily some uncertainties associated with the models of past ecosystems and climate, especially for Africa. Interestingly, the authors argue that the information on paleo-vegetation turnover was more informative than climatic niche modeling for the purpose of their study since it made them consider a wider range of bio-geographical changes and in turn a wider range of evolutionary scenarios (see discussion in Supplementary Material). Microsatellite markers have been offering a useful tool in population genetics and phylogeography for decades, but their popularity is perhaps being taken over by single nucleotide polymorphism (SNP) genotyping and whole-genome sequencing (WGS) (the peak year of the number of the publication with “microsatellite” is in 2012 according to PubMed).

This study reaffirms the usefulness of these classic molecular markers to estimate past demographic events, especially when species- and locus-specific microsatellite mutation features are available and a powerful inferential approach is adopted. Nonetheless, there are still hurdles to overcome, such as the limitations in scenario choice associated with the simulation software used (e.g. not allowing for continuous gene flow in this particular case), which calls for further improvement of simulation tools allowing for more flexible modeling of demographic events and mutation patterns. In sum, this work not only contributes to our understanding of the makeup of the African biodiversity but also offers a useful statistical framework, which can be applied to a wide array of species and molecular markers (microsatellites, SNPs, and WGS).


[1] Lehmann, P. et al. (2018). Complex responses of global insect pests to climate change. bioRxiv, 425488. doi:

[2] Donoghue, P. C., & Benton, M. J. (2007). Rocks and clocks: calibrating the Tree of Life using fossils and molecules. Trends in Ecology & Evolution, 22(8), 424-431. doi:

[3] Ho, S. Y., Lanfear, R., Bromham, L., Phillips, M. J., Soubrier, J., Rodrigo, A. G., & Cooper, A. (2011). Time‐dependent rates of molecular evolution. Molecular ecology, 20(15), 3087-3101. doi:

[4] Chapuis, M.-P., Raynal, L., Plantamp, C., Meynard, C. N., Blondin, L., Marin, J.-M. and Estoup, A. (2020). A young age of subspecific divergence in the desert locust Schistocerca gregaria, inferred by ABC Random Forest. bioRxiv, 671867, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. doi:

5] Chapuis, M.-P., Plantamp, C., Streiff, R., Blondin, L., & Piou, C. (2015). Microsatellite evolutionary rate and pattern in Schistocerca gregaria inferred from direct observation of germline mutations. Molecular ecology, 24(24), 6107-6119. doi:

[6] Raynal, L., Marin, J. M., Pudlo, P., Ribatet, M., Robert, C. P., & Estoup, A. (2018). ABC random forests for Bayesian parameter inference. Bioinformatics, 35(10), 1720-1728. doi:

[7] Estoup, A., Jarne, P., & Cornuet, J. M. (2002). Homoplasy and mutation model at microsatellite loci and their consequences for population genetics analysis. Molecular ecology, 11(9), 1591-1604. doi:

[8] Moodley, Y. et al. (2018). Contrasting evolutionary history, anthropogenic declines and genetic contact in the northern and southern white rhinoceros (Ceratotherium simum). Proceedings of the Royal Society B, 285(1890), 20181567. doi:

[9] Kröpelin, S. et al. (2008). Climate-driven ecosystem succession in the Sahara: the past 6000 years. science, 320(5877), 765-768. doi:

[10] Maley, J. et al. (2018). Late Holocene forest contraction and fragmentation in central Africa. Quaternary Research, 89(1), 43-59. doi:

[11] Beheregaray, L. B. (2008). Twenty years of phylogeography: the state of the field and the challenges for the Southern Hemisphere. Molecular Ecology, 17(17), 3754-3774. doi:

[12] Dubey, S., & Shine, R. (2012). Are reptile and amphibian species younger in the Northern Hemisphere than in the Southern Hemisphere?. Journal of evolutionary biology, 25(1), 220-226. doi:


A video about this preprint is available here:

10 Jan 2020
article picture

Probabilities of tree topologies with temporal constraints and diversification shifts

Fitting diversification models on undated or partially dated trees

Recommended by based on reviews by Amaury Lambert, Dominik Schrempf and 1 anonymous reviewer

Phylogenetic trees can be used to extract information about the process of diversification that has generated them. The most common approach to conduct this inference is to rely on a likelihood, defined here as the probability of generating a dated tree T given a diversification model (e.g. a birth-death model), and then use standard maximum likelihood. This idea has been explored extensively in the context of the so-called diversification studies, with many variants for the models and for the questions being asked (diversification rates shifting at certain time points or in the ancestors of particular subclades, trait-dependent diversification rates, etc).
However, all this assumes that the dated tree T is known without error. In practice, trees (that is, both the tree topology and the divergence times) are inferred based on DNA sequences, possibly combined with fossil information for calibrating and informing the divergence times. Molecular dating is a delicate exercise, however, and much more so in fact than reconstructing the tree topology. In particular, a mis-specificied model for the relaxed molecular clock, or a mis-specifiied prior, can have a substantial impact on the estimation of divergence dates - which in turn could severely mislead the inference about the underlying diversification process. This thus raises the following question: would that be possible to conduct inference and testing of diversification models without having to go through the dangerous step of molecular dating?
In his article ""Probabilities of tree topologies with temporal constraints and diversification shifts"" [1], Gilles Didier introduces a recursive method for computing the probability of a tree topology under some diversification model of interest, without knowledge of the exact dates, but only interval constraints on the dates of some of the nodes of the tree. Such interval constraints, which are derived from fossil knowledge, are typically used for molecular dating: they provide the calibrations for the relaxed clock analysis. Thus, what is essentially proposed by Gilles Didier is to use them in combination with the tree topology only, thus bypassing the need to estimates divergence times first, before fitting a diversification model to a phylogenetic tree.
This article, which is primarily a mathematical and algorithmic contribution, is then complemented with several applications: testing for a diversification shift in a given subclade of the phylogeny, just based on the (undated) tree topology, with interval constraints on some of its internal nodes; but also, computing the age distribution of each node and sampling on the joint distribution on node ages, conditional on the interval constraints. The test for the presence of a diversification shift is particularly interesting: an application to simulated data (and without any interval constraint in that case) suggests that the method based on the undated tree performs about as well as the classical method based on a dated tree, and this, even granting the classical approach a perfect knowledge of the dates - given that, in practice, one in fact relies on potentially biased estimates. Finally, an application to a well-known example (rate shifts in cetacean phylogeny) is presented.
This article thus represents a particularly meaningful contribution to the methodology for diversification studies; but also, for molecular dating itself: it is a well known problem in molecular dating that computing and sampling from the conditional distributions on node ages, given fossil constraints, and more generally understanding and visualizing how interval constraints on some nodes of the tree impact the distribution at other nodes, is a particularly difficult exercise. For that reason, the algorithmic routines presented in the present article will be useful in this context as well.


[1] Didier, G. (2020) Probabilities of tree topologies with temporal constraints and diversification shifts. bioRxiv, 376756, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/376756

09 Dec 2019
article picture

Systematics and geographical distribution of Galba species, a group of cryptic and worldwide freshwater snails

The challenge of delineating species when they are hidden

Recommended by based on reviews by Pavel Matos, Christelle Fraïsse and Niklas Wahlberg

The science of naming species (taxonomy) has been renewed with the developments of molecular sequencing, digitization of museum specimens, and novel analytical tools. However, naming species can be highly subjective, sometimes considered as an art [1], because it is based on human-based criteria that vary among taxonomists. Nonetheless, taxonomists often argue that species names are hypotheses, which are therefore testable and refutable as new evidence is provided. This challenge comes with a more and more recognized and critical need for rigorously delineated species not only for producing accurate species inventories, but more importantly many questions in evolutionary biology (e.g. speciation), ecology (e.g. ecosystem structure and functioning), conservation biology (e.g. targeting priorities) or biogeography (e.g. diversification processes) depend in part on those species inventories and our knowledge of species [2-3]. Inaccurate species boundaries or diversity estimates may lead us to deliver biased answers to those questions, exactly as phylogenetic trees must be reconstructed rigorously and analyzed critically because they are a first step toward discussing broader questions [2-3]. In this context, biological diversity needs to be studied from multiple and complementary perspectives requiring the collaboration of morphologists, molecular biologists, biogeographers, and modelers [4-5]. Integrative taxonomy has been proposed as a solution to tackle the challenge of delimiting species [2], especially in highly diverse and undocumented groups of organisms.
In an elegant study that harbors all the characteristics of an integrative approach, Alda et al. [6] tackle the delimitation of species within the snail genus Galba (Lymnaeidae). Snails of this genus represent a peculiar case study for species delineation with a long and convoluted taxonomic history in which previous works recognized a number of species ranging from 4 to 30. The confusion is likely due to a loose morphology (labile shell features and high plasticity), which makes the identification and naming of species very unstable and likely subjective. An integrative taxonomic approach was needed. After two decades of taxon sampling and visits of type localities, the authors present an impressively dense taxon sampling at a global scale for the genus, which includes all described species. When it comes to delineate species, taxon sampling is often the key if we want to embrace the genetic and morphological diversity. Molecular data was obtained for several types of markers (microsatellites and DNA sequences for four genes), which were combined to morphology of shell and of internal organs, and to geographic distribution. All the data are thoroughly analyzed with cutting-edge methods starting from Bayesian phylogenetic reconstructions using multispecies coalescent models, followed by models of species delimitation based on the molecular specimen-level phylogeny, and then Bayesian divergence time estimates. They also used probabilistic models of ancestral state estimation to infer the ancestral phenotypic state of the Galba ancestors.
Their numerous phylogenetic and delimitation analyses allow to redefine the species boundaries that indicate that the genus Galba comprises six species. Interestingly, four of these species are morphologically cryptic and likely constitute species with extensive genetic diversity and widespread geographic distribution. The other two species have more geographically restricted distributions and exhibit an alternative morphology that is more phylogenetically derived than the cryptic one. Although further genomic studies would be required to strengthen some species status, this novel delimitation of Galba species has important implications for our understanding of convergence and morphological stasis, or the role for stabilizing selection in amphibious habitats; topics that are rarely addressed with invertebrate groups. For instance, in terms of macroevolutionary history, it is striking that an invertebrate clade of that age (22 million years ago) has only given birth to six species today. Including 30 (ancient taxonomy) or 6 (integrative taxonomy) species in a similar amount of evolutionary time does not tell us the same story when studying the diversification processes [7]. Here, Alda et al. [6] present a convincing case study that should foster similar studies following their approach, which will provide stimulating perspectives for testing the concepts of species and their effects on evolutionary biology.


[1] Ohl, M. (2018). The art of naming. MIT Press.
[2] Dayrat, B. (2005). Towards integrative taxonomy. Biological Journal of the Linnean Society, 85(3), 407–415. doi: 10.1111/j.1095-8312.2005.00503.x
[3] De Queiroz, K. (2007). Species concepts and species delimitation. Systematic Biology, 56(6), 879–886. doi: 10.1080/10635150701701083
[4] Padial, J. M., Miralles, A., De la Riva, I., and Vences, M. (2010). The integrative future of taxonomy. Frontiers in Zoology, 7(1), 16. doi: 10.1186/1742-9994-7-16
[5] Schlick-Steiner, B. C., Steiner, F. M., Seifert, B., Stauffer, C., Christian, E., and Crozier, R. H. (2010). Integrative taxonomy: A multisource approach to exploring biodiversity. Annual Review of Entomology, 55(1), 421–438. doi: 10.1146/annurev-ento-112408-085432
[6] Alda, P. et al. (2019). Systematics and geographical distribution of Galba species, a group of cryptic and worldwide freshwater snails. BioRxiv, 647867, v3 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/647867
[7] Ruane, S., Bryson, R. W., Pyron, R. A., and Burbrink, F. T. (2014). Coalescent species delimitation in milksnakes (Genus Lampropeltis) and impacts on phylogenetic comparative analyses. Systematic Biology, 63(2), 231–250. doi: 10.1093/sysbio/syt099

09 Dec 2019
article picture

Trait-specific trade-offs prevent niche expansion in two parasites

Trade-offs in fitness components and ecological source-sink dynamics affect host specialisation in two parasites of Artemia shrimps

Recommended by based on reviews by Anne Duplouy, Seth Barribeau and Cindy Gidoin

Ecological specialisation, especially among parasites infecting a set of host species, is ubiquitous in nature. Host specialisation can be understood as resulting from trade-offs in parasite infectivity, virulence and growth. However, it is not well understood how variation in these trade-offs shapes the overall fitness trade-off a parasite faces when adapting to multiple hosts. For instance, it is not clear whether a strong trade-off in one fitness component may sufficiently constrain the evolution of a generalist parasite despite weak trade-offs in other components. A second mechanism explaining variation in specialisation among species is habitat availability and quality. Rare habitats or habitats that act as ecological sinks will not allow a species to persist and adapt, preventing a generalist phenotype to evolve. Understanding the prevalence of those mechanisms in natural systems is crucial to understand the emergence and maintenance of host specialisation, and biodiversity in general.
In their study "Trait-specific trade-offs prevent niche expansion in two parasites", Lievens et al. [1] report the results of an evolution experiment involving two parasitic microsporidians, Anostracospora rigaudi and Enterocytospora artemiae, infecting two sympatric species of brine shrimp, Artemia franciscana and Artemia parthenogenetica. The two parasites were originally specialised on their primary host: A. rigaudi on A. parthenogenetica and E. artemiae on A. franciscana, although they encounter both species in the wild but at different rates. After passaging each parasite on each single host and on both hosts alternatively, Lievens et al. asked how host specialisation evolved. They found no change in specialisation at the fitness level in A. rigaudi in either treatment, while E. artemiae became more of a generalist after having been exposed to its secondary host, A. parthenogenetica. The most interesting part of the study is the decomposition of the fitness trade-off into its underlying trade-offs in spore production, infectivity and virulence. Both species remained specialised for spore production on their primary host, interpreted as caused by a strong trade-off between hosts preventing improvements on the secondary host. A. rigaudi evolved reduced virulence on its primary host without changes in the overall fitness trad-off, while E. artemiae evolved higher infectivity on its secondary host making it a more generalist parasite and revealing a weak trade-off for this trait and for fitness. Nevertheless, both parasites retained higher fitness on their primary host because of the lack of an evolutionary response in spore production.
This study made two important points. First, it showed that despite apparent strong trade-off in spore production, a weak trade-off in infectivity allowed E. artemiae to become less specialised. In contrast, A. rigaudi remained specialised, presumably because the strong trade-off in spore production was the overriding factor. The fitness trade-off that results from the superposition of multiple underlying trade-offs is thus difficult to predict, yet crucial to understand potential evolutionary outcomes. A second insight is related to the ecological context of the evolution of specialisation. The results showed that E. artemiae should be less specialised than observed, which points to a role played by source-sink dynamics on A. parthenogenetica in the wild. The experimental approach of Lievens et al. thus allowed them to nicely disentangle the various sources of constraints on the evolution of host adaptation in the Artemia system.


[1] Lievens, E.J.P., Michalakis, Y. and Lenormand, T. (2019). Trait-specific trade-offs prevent niche expansion in two parasites. bioRxiv, 621581, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/621581

26 Nov 2019
article picture

Pleiotropy or linkage? Their relative contributions to the genetic correlation of quantitative traits and detection by multi-trait GWA studies

Understanding the effects of linkage and pleiotropy on evolutionary adaptation

Recommended by based on reviews by Pär Ingvarsson and 1 anonymous reviewer

Genetic correlations among traits are ubiquitous in nature. However, we still have a limited understanding of the genetic architecture of trait correlations. Some genetic correlations among traits arise because of pleiotropy - single mutations or genotypes that have effects on multiple traits. Other genetic correlations among traits arise because of linkage among mutations that have independent effects on different traits. Teasing apart the differential effects of pleiotropy and linkage on trait correlations is difficult, because they result in very similar genetic patterns. However, understanding these differential effects gives important insights into how ubiquitous pleiotropy may be in nature.
In the preprint "Pleiotropy or linkage? Their relative contributions to the genetic correlation of quantitative traits and detection by multi-trait GWA studies", Chebib and Guillaume [1] explore the conditions under which trait correlations caused by pleiotropy result in similar and different genetic patterns than trait correlations caused by linkage. Their main finding is that pleiotropic architectures result in higher trait correlations than do architectures in which completely linked mutations affect different traits. This results clarifies and goes against a previous theoretical study that predicted that pleiotropic architectures could not be distinguished from completely linked mutations that affect independent traits.
In genome-wide association studies (GWAS), it is difficult to know if a significant signal is a causal variant that truly affects the trait, a false positive neutral variant linked to a causal variant, or a false positive causal variant that affects a different trait but is significant because of trait correlations. In their study, Chebib and Guillaume [1] show that this latter category can be a common source of false positives in GWAS studies when mutations affecting different traits are linked. One of the main limitation of this aspect of their analysis is the lack of simulation of neutral loci, which would likely show even higher rates of false positives than reported in their study.
The main limitation in their study is the restrictive assumptions about the genetic architectures (e.g. all pairs of loci have a fixed recombination rate among them). In reality, new causal mutations that arise near another causal mutation may have higher or lower establishment probabilities depending on the direction of effects on the trait and the parameters for selection and demography. Their study still deserves a recommendation, however, because of the new insights it gives into the genetic architecture of trait correlations.


[1] Chebib, J. and Guillaume, F. (2019). Pleiotropy or linkage? Their relative contributions to the genetic correlation of quantitative traits and detection by multi-trait GWA studies. bioRxiv, 656413, v3 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/656413

21 Nov 2019
article picture

Environmental specificity in Drosophila-bacteria symbiosis affects host developmental plasticity

Nutrition-dependent effects of gut bacteria on growth plasticity in Drosophila melanogaster

Recommended by based on reviews by Pedro Simões and 1 anonymous reviewer

It is well known that the rearing environment has strong effects on life history and fitness traits of organisms. Microbes are part of every environment and as such likely contribute to such environmental effects. Gut bacteria are a special type of microbe that most animals harbor, and as such they are part of most animals’ environment. Such microbial symbionts therefore likely contribute to local adaptation [1]. The main question underlying the laboratory study by Guilhot et al. [2] was: How much do particular gut bacteria affect the organismal phenotype, in terms of life history and larval foraging traits, of the fruit fly Drosophila melanogaster, a common laboratory model species in biology?
To investigate the above question, the authors isolated 4 taxa of bacteria from the gut of a (randomly picked) Drosophila melanogaster lab strain, and subsequently let Drosophila melanogaster eggs and larvae (stemming from their own, different lab strain) develop both in the typical artificial laboratory medium as well as in grapes, a natural “new” habitat for Drosophila larvae, inoculated with theses bacteria, singly and in combination, also including a bacteria-free control. By investigating various relevant developmental and size traits, the authors found that adding particularly Enterobacteria had some visible effects on several traits, both upward (indicting improvement) and downward (being detrimental) (with three other types of bacteria showing only minor or even no effects). In general, the grape medium reduced performance relative to the standard lab medium. Strongest interactive effects occurred for development time and body size, together making up growth plasticity [3], with lesser such effects on some related behavioral (feeding) traits (Figs. 2,3).
The study premise is interesting, its general objectives are clearly laid out, and the practical work was conducted correctly as far as I can evaluate. The study remains largely descriptive in that no particular a priori hypotheses or predictions in relation to the specific bacteria isolated were formulated, not least because the bacteria were necessarily somewhat arbitrarily chosen and there were apparently no prior studies from which to derive concrete predictions. Overall, the results of this study should be of interest to the community of evolutionary ecologists, especially those working on nutritional and microbiome effects on animal life histories. I consider this work to be primarily ecological, with limited evolutionary content (e.g. no genetics) though some evolutionary implications, as mentioned in the paper’s Conclusions. So this paper would best fit in a microbial or physiological ecology outlet/journal.
The inclusion of a natural medium (grapes) must be commended because this permits inferences and conclusions for at least one natural environment, whereas inferences drawn from laboratory studies in the artificial medium that most Drosophila researchers seem to use are typically limited. Unsurprisingly perhaps, the study showed that Drosophila melanogaster fared generally better in the artificial than the chosen natural medium (grape). Crucially, however, the bacterial symbionts modified both media differentially. Although common bacterial taxa were chosen, the particular bacteria isolated and used remain arbitrary, as there are many. I note that the main and strongest interactive effects between medium and bacterial type are apparent for the Enterobacteria, and they probably also strongly, if not exclusively, mediate the overall effect of the bacterial mixture.
While these specific data are novel, they are not very surprising. If we grow animals in different environments we can expect some detectable effects of these environments, including the bacterial (microbiome) environment, on the hosts life history. The standard and predicted [4] life history response of Drosophila melanogaster (but not all insects [3]) facing stressful nutritional environments, as apparently created by the Enterobacteria, is to extend development but come out smaller in the end. This is what happened here for the laboratory medium ([2]: Fig. 5). The biological interpretation is that individuals have more trouble ingesting and/or digesting the nutrients available (thus prolonging their foraging period and development), yet cannot convert the nutrients effectively into body size increments (hence emerging smaller). This is what the authors here refer to as developmental plasticity, which is ultimately nutritionally mediated. However, interestingly, a signal in the opposite direction was indicated for the bacterial mixture in the grape medium (flies emerging larger after accelerated development: Fig. 5), suggesting some positive effects on growth rate of the natural medium, perhaps related to grapes being a limited resource that needs to be escaped quickly [3]? The reversal of sexual size dimorphism across bacterial treatments in the grape environment detectable in Fig. 4 is interesting, too, though I don’t understand why this happens, and this is not discussed.
In general, more encompassing and increased questions in this context to be researched in the future could be: 1) are these effects predictable (not (yet) at this point, or so it seems); and 2) how strong are these environmental bacterial effects relative to other, more standard effects (e.g. relative to genetic variation, population variation, etc., or relative to other types of environmental effects like, say, temperature)? (3) It could further be asked why not natural but laboratory populations of Drosophila were used for this experiment, if the aim was to draw inferences for the wild situation. (4) Although Genotype x Environment effects are invoked in the Discussion, they were not tested here, lacking genetically different Drosophila families or populations. From an evolutionary standpoint, I consider this the greatest weakness of the study. I was also not too thrilled by the particular statistical analyses employed, though this ultimately does not negate the results. Nevertheless, this work is a good start in this huge field investigating the microbiome. In conclusion, I can recommend this paper after review by PCI Evol Biol.


[1] Kawecki, T. J. and Ebert, D. (2004) Conceptual issues in local adaptation. Ecology Letters 7: 1225-1241. doi: 10.1111/j.1461-0248.2004.00684.x
[2] Guilhot, R., Rombaut, A., Xuéreb, A., Howell, K. and Fellous, S. (2019). Environmental specificity in Drosophila-bacteria symbiosis affects host developmental plasticity. BioRxiv, 717702, v3 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/717702
[3] Blanckenhorn, W.U. (1999) Different growth responses to temperature and resource limitation in three fly species with similar life histories. Evolutionary Ecology 13: 395-409. doi: 10.1023/A:1006741222586
[4] Stearns, S. C. and Koella, J. (1986) The evolution of phenotypic plasticity in life history traits: predictions of reaction norms for age and size at maturity. Evolution 40: 893-914. doi: 10.1111/j.1558-5646.1986.tb00560.x

20 Nov 2019
article picture

Distribution of iridescent colours in hummingbird communities results from the interplay between selection for camouflage and communication

Feathers iridescence sheds light on the assembly rules of humingbirds communities

Recommended by based on reviews by 2 anonymous reviewers

Ecology needs rules stipulating how species distributions and ecological communities should be assembled along environmental gradients, but few rules have yet emerged in the ecological literature. The search of ecogeographical rules governing the spatial variation of birds colours has recently known an upsurge of interest in the litterature [1]. Most studies have, however, looked at pigmentary colours and not structural colours (e.g. iridescence), although it is know that color perception by animals (both birds and their predators) can be strongly influenced by light diffraction causing iridescence patterns on feathers.
In the present study [2], the authors study ca. 190 ecological communities of hummingbirds as a function of their iridescent colors, in a large study zone spanning varied habitats across Ecuador. They show that colour composition of local hummingbirds communities are shaped by two main processes :
(i) phenotyping clustering of birds with similar dorsal colours, due to local selection of species with similar camouflages against predators (i.e. some sort of mimetic circles).
(ii) phenotypic overdispersion of birds with distinct facial and ventral colours, resulting from character displacement and limiting reproductive interference.
I found this second result particularly interesting because it adds to the mounting evidence that character displacement (also for songs or olfactory signaling) allow local coexistence between closely-related bird species once they have reached secondary sympatry. It is important to note that not all color patches though to be involved in sexual selection followed this overdispersion rule -- throat and crown color patches were not found overdispersed. This suggests that further investigation is needed to determine how color variation shape the structure of hummingbird communities, or bird communities in general.
Another notable quality of the present study is that it is making extensive use of museum specimens and thus shows that very innovative research can be performed with museum collections.


[1] Delhey, K. (2019). A review of Gloger’s rule, an ecogeographical rule of colour: definitions, interpretations and evidence. Biological Reviews, 94(4), 1294–1316. doi: 10.1111/brv.12503
[2] Gruson, H., Elias, M., Parra, J. L., Andraud, C., Berthier, S., Doutrelant, C., & Gomez, D. (2019). Distribution of iridescent colours in hummingbird communities results from the interplay between selection for camouflage and communication. BioRxiv, 586362, v5 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/586362

07 Nov 2019
article picture

New insights into the population genetics of partially clonal organisms: when seagrass data meet theoretical expectations

Inferring rates of clonal versus sexual reproduction from population genetics data

Recommended by based on reviews by Ludwig TRIEST, Stacy Krueger-Hadfield and 1 anonymous reviewer

In partially clonal organisms, genetic markers are often used to characterize the genotypic diversity of populations and infer thereof the relative importance of clonal versus sexual reproduction. Most studies report a measure of genotypic diversity based on a ratio, R, of the number of distinct multilocus genotypes over the sample size, and qualitatively interpret high / low R as indicating the prevalence of sexual / clonal reproduction. However, a theoretical framework allowing to quantify the relative rates of clonal versus sexual reproduction from genotypic diversity is still lacking, except using temporal sampling. Moreover, R is intrinsically highly dependent on sample size and sample design, while alternative measures of genotypic diversity are more robust to sample size, like D*, which is equivalent to the Gini-Simpson diversity index applied to multilocus genotypes. Another potential indicator of reproductive strategies is the inbreeding coefficient, Fis, because population genetics theory predicts that clonal reproduction should lead to negative Fis, at least when the sexual reproduction component occurs through random mating. Taking advantage of this prediction, Arnaud-Haond et al. [1] reanalysed genetic data from 165 populations of four partially clonal seagrass species sampled in a standardized way. They found positive correlations between Fis and both R and D* within each species, reflecting variation in the relative rates of sexual versus clonal reproduction among populations. Moreover, the differences of mean genotypic diversity and Fis values among species were also consistent with their known differences in reproductive strategies. Arnaud-Haond et al. [1] also conclude that previous works based on the interpretation of R generally lead to underestimate the prevalence of clonality in seagrasses. Arnaud-Haond et al. [1] confirm experimentally that Fis merits to be interpreted more properly than usually done when inferring rates of clonal reproduction from population genetics data of species reproducing both sexually and clonally. An advantage of Fis is that it is much less affected by sample size than R, and thus should be more reliable when comparing studies differing in sample design. Hence, when the rate of clonal reproduction becomes significant, we expect Fis < 0 and D* < 1. I expect these two indicators of clonality to be complementary because they rely on different consequences of clonality on pattern of genetic variation. Nevertheless, both measures can be affected by other factors. For example, null alleles, selfing or biparental inbreeding can pull Fis upwards, potentially eliminating the signature of clonal reproduction. Similarly, D* (and other measures of genotypic diversity) can be low because the polymorphism of the genetic markers used is too limited or because sexual reproduction often occurs through selfing, eventually resulting in highly similar homozygous genotypes.
The work of Arnaud-Haond et al. [1] shows that the populations genetics of partially clonal organisms should be better studied, an endeavour encompassed in a companion paper using numerical simulations [2]. A further step that remains to be accomplished is to build a mathematical framework for developing estimators of rates of clonal versus sexual reproduction based on genotypic diversity.


[1] Arnaud-Haond, S., Stoeckel, S., and Bailleul, D. (2019). New insights into the population genetics of partially clonal organisms: when seagrass data meet theoretical expectations. ArXiv:1902.10240 [q-Bio], v6 peer-reviewed and recommended by Peer Community in Evolutionary Biology. Retrieved from
[2] Stoeckel, S., Porro, B., and Arnaud-Haond, S. (2019). The discernible and hidden effects of clonality on the genotypic and genetic states of populations: improving our estimation of clonal rates. ArXiv:1902.09365 [q-Bio], v4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. Retrieved from

24 Oct 2019
article picture

Testing host-plant driven speciation in phytophagous insects : a phylogenetic perspective

Phylogenetic approaches for reconstructing macroevolutionary scenarios of phytophagous insect diversification

Recommended by based on reviews by Brian O'Meara and 1 anonymous reviewer

Plant-animal interactions have long been identified as a major driving force in evolution. However, only in the last two decades have rigorous macroevolutionary studies of the topic been made possible, thanks to the increasing availability of densely sampled molecular phylogenies and the substantial development of comparative methods. In this extensive and thoughtful perspective [1], Jousselin and Elias thoroughly review current hypotheses, data, and available macroevolutionary methods to understand how plant-insect interactions may have shaped the diversification of phytophagous insects. First, the authors review three main hypotheses that have been proposed to lead to host-plant driven speciation in phytophagous insects: the ‘escape and radiate’, ‘oscillation’, and ‘musical chairs’ scenarios, each with their own set of predictions. Jousselin and Elias then synthesize a vast core of recent studies on different clades of insects, where explicit phylogenetic approaches have been used. In doing so, they highlight heterogeneity in both the methods being used and predictions being tested across these studies and warn against the risk of subjective interpretation of the results. Lastly, they advocate for standardization of phylogenetic approaches and propose a series of simple tests for the predictions of host-driven speciation scenarios, including the characterization of host-plant range history and host breadth history, and diversification rate analyses. This helpful review will likely become a new point of reference in the field and undoubtedly help many researchers formalize and frame questions of plant-insect diversification in future studies of phytophagous insects.


[1] Jousselin, E., Elias, M. (2019). Testing Host-Plant Driven Speciation in Phytophagous Insects: A Phylogenetic Perspective. arXiv, 1910.09510, ver. 1 peer-reviewed and recommended by PCI Evol Biol.

22 Oct 2019
article picture

Geographic variation in adult and embryonic desiccation tolerance in a terrestrial-breeding frog

Tough as old boots: amphibians from drier habitats are more resistant to desiccation, but less flexible at exploiting wet conditions

Recommended by based on reviews by Jennifer Nicole Lohr, Juan Diego Gaitan-Espitia and 1 anonymous reviewer

Species everywhere are facing rapid climatic change, and we are increasingly asking whether populations will adapt, shift, or perish [1]. There is a growing realisation that, despite limited within-population genetic variation, many species exhibit substantial geographic variation in climate-relevant traits. This geographic variation might play an important role in facilitating adaptation to climate change [2,3].
Much of our understanding of geographic variation in climate-relevant traits comes from model organisms [e.g. 4]. But as our concern grows, we make larger efforts to understand geographic variation in non-model organisms also. If we understand what adaptive geographic variation exists within a species, we can make management decisions around targeted gene flow [5]. And as empirical examples accumulate, we can look for generalities that can inform management of unstudied species [e.g. 6,7]. Rudin-Bitterli’s paper [8] is an excellent contribution in this direction.
Rudin-Bitterli and her co-authors [8] sampled six frog populations distributed across a strong rainfall gradient. They then assayed these frogs and their offspring for a battery of fitness-relevant traits. The results clearly show patterns consistent with local adaptation to water availability, but they also reveal trade-offs. In their study, frogs from the driest source populations were resilient to the hydric environment: it didn’t really affect them very much whether they were raised in wet or dry environments. By contrast, frogs from wet source areas did better in wet environments, and they tended to do better in these wet environments than did animals from the dry-adapted populations. Thus, it appears that the resilience of the dry-adapted populations comes at a cost: frogs from these populations cannot ramp up performance in response to ideal (wet) conditions.
These data have been carefully and painstakingly collected, and they are important. They reveal not only important geographic variation in response to hydric stress (in a vertebrate), but they also adumbrate a more general trade-off: that the jack of all trades might be master of none. Specialist-generalist trade-offs are often argued (and regularly observed) to exist [e.g. 9,10], and here we see them arise in climate-relevant traits also. Thus, Rudin-Bitterli’s paper is an important piece of the empirical puzzle, and one that points to generalities important for both theory and management.


[1] Hoffmann, A. A., and Sgrò, C. M. (2011). Climate change and evolutionary adaptation. Nature, 470(7335), 479–485. doi: 10.1038/nature09670
[2] Aitken, S. N., and Whitlock, M. C. (2013). Assisted Gene Flow to Facilitate Local Adaptation to Climate Change. Annual Review of Ecology, Evolution, and Systematics, 44(1), 367–388. doi: 10.1146/annurev-ecolsys-110512-135747
[3] Kelly, E., and Phillips, B. L. (2016). Targeted gene flow for conservation. Conservation Biology, 30(2), 259–267. doi: 10.1111/cobi.12623
[4] Sgrò, C. M., Overgaard, J., Kristensen, T. N., Mitchell, K. A., Cockerell, F. E., and Hoffmann, A. A. (2010). A comprehensive assessment of geographic variation in heat tolerance and hardening capacity in populations of Drosophila melanogaster from eastern Australia. Journal of Evolutionary Biology, 23(11), 2484–2493. doi: 10.1111/j.1420-9101.2010.02110.x
[5] Macdonald, S. L., Llewelyn, J., and Phillips, B. L. (2018). Using connectivity to identify climatic drivers of local adaptation. Ecology Letters, 21(2), 207–216. doi: 10.1111/ele.12883
[6] Hoffmann, A. A., Chown, S. L., and Clusella‐Trullas, S. (2012). Upper thermal limits in terrestrial ectotherms: how constrained are they? Functional Ecology, 27(4), 934–949. doi: 10.1111/j.1365-2435.2012.02036.x
[7] Araújo, M. B., Ferri‐Yáñez, F., Bozinovic, F., Marquet, P. A., Valladares, F., and Chown, S. L. (2013). Heat freezes niche evolution. Ecology Letters, 16(9), 1206–1219. doi: 10.1111/ele.12155
[8] Rudin-Bitterli, T. S., Evans, J. P., and Mitchell, N. J. (2019). Geographic variation in adult and embryonic desiccation tolerance in a terrestrial-breeding frog. BioRxiv, 314351, ver. 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology. doi: 10.1101/314351
[9] Kassen, R. (2002). The experimental evolution of specialists, generalists, and the maintenance of diversity. Journal of Evolutionary Biology, 15(2), 173–190. doi: 10.1046/j.1420-9101.2002.00377.x
[10] Angilletta, M. J. J. (2009). Thermal Adaptation: A theoretical and empirical synthesis. Oxford University Press, Oxford.

08 Oct 2019
article picture

Strong habitat and weak genetic effects shape the lifetime reproductive success in a wild clownfish population

Habitat variation of wild clownfish population shapes selfrecruitment more than genetic effects

Recommended by based on reviews by Juan Diego Gaitan-Espitia and Loeske Kruuk

Estimating the genetic and environmental components of variation in reproductive success is crucial to understanding the adaptive potential of populations to environmental change. To date, the heritability of lifetime reproductive success (fitness) has been estimated in a handful of wild animal population, mostly in mammals and birds, but has never been estimated for a marine species. The primary reason that such estimates are lacking in marine species is that most marine organisms have a dispersive larval phase, making it extraordinarily difficult to track the fate of offspring from one generation to the next.
In this study, Salles et al. [1] use an unprecedented 10 year data set for a wild population of orange clownfish (Amphiprion percula) to estimate the environmental, maternal and additive genetic components of life time reproductive success for the self-recruiting portion of the local population. Previous studies show that over 50% of juvenile clownfish recruiting to the population of clownfish at Kimbe Island (Kimbe Bay, PNG) are natal to the population. In other words, >50% of the juveniles recruiting to the population at Kimbe Island are offspring of parents from Kimbe Island. The identity and location of every adult clownfish in the Kimbe Island population was tracked over 10 years. At the same time newly recruiting juveniles were collected at regular intervals (biennially) and their parentage assigned with high confidence by 22 polymorphic microsatellite loci. Salles et al. then used a pedigree comprising 1735 individuals from up to 5 generations of clownfish at Kimbe Island to assess the contribution of every breeding pair of clownfish to self-recruitment within the local population. Because clownfish are site attached and live in close association with a host sea anemone, it was also possible to examine the contribution of reef location and host anemones species (either Heteractis magnifica or Stichodactyla gigantea) to reproductive success within the local population.
The study found that breeders from the eastern side of Kimbe Island, and mostly inhabiting S. gigantea sea anemones, produced more juveniles that recruited to the local population than breeders from other location around the island, or inhabiting H. magnifica. In fact, host anemone species and geographic location explained about 97% of the variance in reproductive success within the local population (i.e. excluding successful recruitment to other populations). By contrast, maternal and additive genetic effects explained only 1.9% and 1.3% of the variance, respectively. In other words, reef location and the species of host anemone inhabited had an overwhelming influence on the long-term contribution of breeding pairs of clownfish to replenishment of the local population. This overwhelming effect of the local habitat on reproductive success means that the population is potentially susceptible to rapid environmental changes - for example if S. giganta sea anemones are disproportionately susceptible to global warming, or reef habitats on the eastern side of the island are more susceptible to disturbance. By contrast, the small component of additive genetic variance in local reproductive success translated into low heritability and evolvability of lifetime reproductive success within the local population, as predicted by theory [2] and observed in some terrestrial species. Consequently, fitness would evolve slowly to environmental change.
Establishing the components of variation in fitness in a wild population of marine fishes is an astonishing achievement, made possible by the unprecedented long-term individual-level monitoring of the entire population of clownfish at Kimbe Island. A next step in this research would be to include other clownfish populations that are demographically and genetically connected to the Kimbe Island population through larval dispersal. It would be intriguing to establish the environmental, maternal and additive genetic components of reproductive success in the dispersing part of the Kimbe Island population, to see if this potentially differs among breeders who contribute more or less to replenishment within the local population.


[1] Salles, O. C., Almany, G. R., Berumen, M.L., Jones, G. P., Saenz-Agudelo, P., Srinivasan, M., Thorrold, S. R., Pujol, B., Planes, S. (2019). Strong habitat and weak genetic effects shape the lifetime reproductive success in a wild clownfish population. Zenodo, 3476529, ver. 3 peer-reviewed and recommended by Peer Community In Evolutionary Biology. doi: 10.5281/zenodo.3476529
[2] Fisher, R.A. (1930). The genetical theory of natural selection. Clarendon Press, Oxford, U.K.

13 Sep 2019
article picture

Deceptive combined effects of short allele dominance and stuttering: an example with Ixodes scapularis, the main vector of Lyme disease in the U.S.A.

New curation method for microsatellite markers improves population genetics analyses

Recommended by based on reviews by Eric Petit, Martin Husemann and 2 anonymous reviewers

Genetic markers are used for in modern population genetics/genomics to uncover the past neutral and selective history of population and species. Besides Single Nucleotide Polymorphisms (SNPs) obtained from whole genome data, microsatellites (or Short Tandem Repeats, SSR) have been common markers of choice in numerous population genetics studies of non-model species with large sample sizes [1]. Microsatellites can be used to uncover and draw inference of the past population demography (e.g. expansion, decline, bottlenecks…), population split, population structure and gene flow, but also life history traits and modes of reproduction (e.g. [2,3]). These markers are widely used in conservation genetics [4] or to study parasites or disease vectors [5]. Microsatellites do show higher mutation rate than SNPs increasing, on the one hand, the statistical power to infer recent events (for example crop domestication, [2,3]), while, on the other hand, decreasing their statistical power over longer time scales due to homoplasy [6].
To perform such analyses, however, an excellent and reliable quality of data is required. As emphasized in the article by De Meeûs et al. [7] three main issues do bias the observed heterozygosity at microsatellites: null alleles, short allele dominance (SAD) and stuttering. These originates from poor PCR amplification. As a result, an excess of homozygosity is observed at the microsatellite loci leading to overestimation of the variation statistics FIS and FST as well as increased linage disequilibrium (LD). For null alleles, several methods and software do help to reduce the bias, and in the present study, De Meeûs et al. [7] propose a way to tackle issues with SAD and stuttering.
The authors study a dataset consisting of 387 samples from 61 subsamples genotyped at nine loci of the species Ixodes scapularis, i.e. ticks transmitting the Lyme disease. Based on correlation methods and FST, FIS they can uncover null alleles and SAD. Stuttering is detected by evaluating the heterozygote deficit between alleles displaying a single repeat difference. Without correction, six loci are affected by one of these amplification problems generating a large deficit of heterozygotes (measured by significant FIS and FST) remaining so after correction for the false discovery rate (FDR). These results would be classically interpreted as a strong Wahlund effect and/or selection at several loci.
After correcting for null alleles, the authors apply two novel corrections: 1) a re-examination of the chromatograms reveals previously disregarded larger alleles thus decreasing SAD, and 2) pooling alleles close in size decreasing stuttering. The corrected dataset shows then a significant excess of heterozygotes as could be expected in a dioecious species with strong population structure. The FDR correction removes then the significant excess of homozygotes and LD between pairs of loci. FST on the cured dataset is used to demonstrate the strong population structure and small effective subpopulation sizes. This is confirmed by a clustering analysis using discriminant analysis of principal components (DAPC).
While based on a specific dataset of ticks from different populations sampled across the USA, the generality of the authors’ approach is presented in Figure 6 in which they provide a step by step flowchart to cure microsatellite datasets from null alleles, SAD and stuttering. Several criteria based on FIS, FST and LD between loci are used as decision keys in the flowchart. An excel file is also provided as help for the curation steps. This study and the proposed methodology are thus extremely useful for all population geneticists working on non-model species with large number of samples genotyped at microsatellite markers. The method not only allows more accurate estimates of heterozygosity but also prevents the thinning of datasets due to the removal of problematic loci. As a follow-up and extension of this work, an exhaustive simulation study could investigate the influence of these data quality issues on past demographic and population structure inference under a wide range of scenarios. This would allow to quantify the current biases in the literature and the robustness of the methodology devised by De Meeûs et al. [7].


[1] Jarne, P., and Lagoda, P. J. (1996). Microsatellites, from molecules to populations and back. Trends in ecology & evolution, 11(10), 424-429. doi: 10.1016/0169-5347(96)10049-5
[2] Cornille, A., Giraud, T., Bellard, C., Tellier, A., Le Cam, B., Smulders, M. J. M., Kleinschmit, J., Roldan-Ruiz, I. and Gladieux, P. (2013). Postglacial recolonization history of the E uropean crabapple (Malus sylvestris M ill.), a wild contributor to the domesticated apple. Molecular Ecology, 22(8), 2249-2263. doi: 10.1111/mec.12231
[3] Parat, F., Schwertfirm, G., Rudolph, U., Miedaner, T., Korzun, V., Bauer, E., Schön C.-C. and Tellier, A. (2016). Geography and end use drive the diversification of worldwide winter rye populations. Molecular ecology, 25(2), 500-514. doi: 10.1111/mec.13495
[4] Broquet, T., Ménard, N., & Petit, E. (2007). Noninvasive population genetics: a review of sample source, diet, fragment length and microsatellite motif effects on amplification success and genotyping error rates. Conservation Genetics, 8(1), 249-260. doi: 10.1007/s10592-006-9146-5
[5] Koffi, M., De Meeûs, T., Séré, M., Bucheton, B., Simo, G., Njiokou, F., Salim, B., Kaboré, J., MacLeod, A., Camara, M., Solano, P., Belem, A. M. G. and Jamonneau, V. (2015). Population genetics and reproductive strategies of African trypanosomes: revisiting available published data. PLoS neglected tropical diseases, 9(10), e0003985. doi: 10.1371/journal.pntd.0003985
[6] Estoup, A., Jarne, P., & Cornuet, J. M. (2002). Homoplasy and mutation model at microsatellite loci and their consequences for population genetics analysis. Molecular ecology, 11(9), 1591-1604. doi: 10.1046/j.1365-294X.2002.01576.x
[7] De Meeûs, T., Chan, C. T., Ludwig, J. M., Tsao, J. I., Patel, J., Bhagatwala, J., and Beati, L. (2019). Deceptive combined effects of short allele dominance and stuttering: an example with Ixodes scapularis, the main vector of Lyme disease in the USA. bioRxiv, 622373, ver. 4 peer-reviewed and recommended by Peer Community In Evolutionary Biology. doi: 10.1101/622373

04 Sep 2019
article picture

The discernible and hidden effects of clonality on the genotypic and genetic states of populations: improving our estimation of clonal rates

How to estimate clonality from genetic data: use large samples and consider the biology of the species

Recommended by based on reviews by David Macaya-Sanz, Marcela Van Loo and 1 anonymous reviewer

Population geneticists frequently use the genetic and genotypic information of a population sample of individuals to make inferences on the reproductive system of a species. The detection of clones, i.e. individuals with the same genotype, can give information on whether there is clonal (vegetative) reproduction in the species. If clonality is detected, population geneticists typically use genotypic richness R, the number of distinct genotypes relative to the sample size, to estimate the rate of clonality c, which can be defined as the proportion of reproductive events that are clonal. Estimating the rate of clonality based on genotypic richness is however problematic because, to date, there is no analytical, nor simulation-based, characterization of this relationship. Furthermore, the effect of sampling on this relationship has never been critically examined.
The paper by Stoeckel, Porro and Arnaud-Haond [1] contributes significantly to the characterization of the relationship between rate of clonality and genetic and genotypic parameters in a population. The authors use an extensive individual-based simulation approach to assess the effects of rate of clonality (fully sexual, fully clonal and a range of intermediate levels of clonality, i.e., partial clonality) on genetic and genotypic parameters, considering variable population size, sample size, and numbers of generations elapsed since population initiation. Based on their simulations, they derive empirical formulae that link for the first time the rate of clonality to the genotypic richness and to the size distribution of clones (genotypic parameters), as well as to the population inbreeding coefficient and to a metric of linkage disequilibrium (genetic parameters). They then use the simulated data to assess the accuracy of their predictions. In a second phase, the authors use a Bayesian supervised learning algorithm to estimate rates of clonality from the simulated data.
The authors show that the relationship between rate of clonality and genotypic richness is not linear: genotypic richness decreases slowly with increasing clonality, a large drop in genotypic richness is only seen for rates of clonality ≥ 0.90. Genetic parameters are only sensitive to high rates of clonality. The practical implications of these results are that genotypic and genetic parameters can complement each other for the estimation of rates of clonality, with genotypic parameters most useful throughout most of the range of clonality values and with genetic parameters complementing them meaningfully at higher values. The most meaningful practical result of the paper is the demonstration of sampling bias on the estimation of genotypic richness. Commonly used population sample sizes in population genetics studies (n ≤ 50) lead to great overestimation of genotypic richness, which consequently leads to a severe underestimation of the rate of clonality in most systems, irrespectively of whether they have reached stationary equilibrium. Only in small populations, these effects are attenuated.
Biologists interested in the estimation of the rate of clonality will find this paper highly useful to design their sampling, and to choose their statistics for inference in a meaningful way. This paper also calls for a careful reappraisal of previously published works that infer rates of clonality from genetic data, and highlights the prime importance of complementary information on species life history data for a correct understanding of partial clonality.


[1] Stoeckel, S., Porro, B., and Arnaud-Haond, S. (2019). The discernible and hidden effects of clonality on the genotypic and genetic states of populations: improving our estimation of clonal rates. ArXiv:1902.09365 [q-Bio] v4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. Retrieved from

28 Aug 2019
article picture

Is adaptation limited by mutation? A timescale-dependent effect of genetic diversity on the adaptive substitution rate in animals

To tinker, evolution needs a supply of spare parts

Recommended by based on reviews by Konstantin Popadin, David Enard and 1 anonymous reviewer

Is evolution adaptive? Not if there is no variation for natural selection to work with. Theory predicts that how fast a population can adapt to a new environment can be limited by the supply of new mutations coming into it. This supply, in turn, depends on two things: how often mutations occur and in how many individuals. If there are few mutations, or few individuals in whom they can originate, individuals will be mostly identical in their DNA, and natural selection will be impotent.
This theoretical prediction has been hard to test. The rate at which new mutations arise in a population can be manipulated experimentally, and some work has shown that the fitness of a population increases more rapidly if more new mutations appear per generation, lending support to the mutation-limitation hypothesis [1]. However, the question remains whether this limitation has played a role in the history of life over the evolutionary timescale. Maybe all natural populations are so large, the mutation rate so high, and/or the environment changes so slowly, that any novel variant required for adaptation is already there when selection starts to act? Some recent work does suggest that when strong selection begins to favor a certain phenotype, multiple distinct genetic variants producing this phenotype spread; this is what has happened, for instance, at the origin of insecticide resistance in wild populations of Drosophila melanogaster [2] or lactose persistence in humans [3]. In many other cases, though, adaptations seem to originate through a single mutation event, suggesting that the time needed for this mutation to arise may be important.
To complicate things, adaptation is hard to quantify. It leaves a trace in differences between individuals of the same species as well as of different species. However, this trace is often masked or confounded by other processes, including natural selection disfavoring newly arising deleterious variants, interference from selection acting at linked sites, and changes in population size. In 1991, McDonald and Kreitman [4] have come up with a method to infer the rate of adaptation in the presence of strong negative selection, and later work has developed upon it to control for some of the other confounders. Still, the method is data-intensive, and previous attempts to employ it to compare the rates of adaptation between species have yielded somewhat contradictory results.
The new paper by Rousselle et al. recommended by PCI Evol Biol [5] fills this gap. The authors use published data as well as their own newly generated dataset to analyze, in a McDonald and Kreitman-like framework, both closely and distantly related species. Importantly, these comparisons cover species with very different polymorphism levels, spanning two orders of magnitude of difference levels.
So is adaptation in fact limited by supply of new mutations? The answer is, it depends. It does indeed seem that the species with a lower level of polymorphism adapt at a lower rate, consistent with the mutation-limitation hypothesis. However, this only is true for those groups of species in which the variability is low. Therefore, if a population is very small or the mutation rate very low, there may be in fact not enough mutations to secure its need to adapt.
In more polymorphic species, and in comparisons of distant species, the data hint instead at the opposite relationship: the rate of adaptations declines with variability. This is consistent with a different explanation: when a population is small, it needs to adapt more frequently, repairing the weakly deleterious mutations that can’t be prevented by selection under small population sizes.
There are quite a few problems small populations have to deal with. Some of them are ecological: e.g., small numbers make populations more vulnerable to stochastic fluctuations in size or sex ratio. Others, however, are genetic. Small populations are prone to inbreeding depression and have an increased rate of genetic drift, leading to spread of deleterious alleles. Indeed, selection against deleterious mutations is less efficient when populations are small, and less numerable species accumulate more of such mutations over the course of evolution [6]. The work by Rouselle et al. [5] suggests that small populations also face an additional burden: a reduced ability to adapt.
Has the rate of adaptation in our own species also been limited by our deficit of diversity? The data hints at this. Homo sapiens, as well as the two other studied extinct representatives of the genus Homo, Neanderthals and Denisovans, belong to the domain of relatively low polymorphism levels, where an increase in polymorphism matters for the rate at which adaptive substitutions accumulate. Perhaps, if our ancestors were more numerous or more mutable, they would have been able to get themselves out of trouble, and there would be multiple human species still alive rather than just one.


[1] G, J. A., Visser, M. de, Zeyl, C. W., Gerrish, P. J., Blanchard, J. L., and Lenski, R. E. (1999). Diminishing Returns from Mutation Supply Rate in Asexual Populations. Science, 283(5400), 404–406. doi: 10.1126/science.283.5400.404
[2] Karasov, T., Messer, P. W., and Petrov, D. A. (2010). Evidence that Adaptation in Drosophila Is Not Limited by Mutation at Single Sites. PLOS Genetics, 6(6), e1000924. doi: 10.1371/journal.pgen.1000924
[3] Jones, B. L., Raga, T. O., Liebert, A., Zmarz, P., Bekele, E., Danielsen, E. T., Olsen, A. K., Bradman, N., Troelsen, J. T., and Swallow, D. M. (2013). Diversity of Lactase Persistence Alleles in Ethiopia: Signature of a Soft Selective Sweep. The American Journal of Human Genetics, 93(3), 538–544. doi: 10.1016/j.ajhg.2013.07.008
[4] McDonald, J. H., and Kreitman, M. (1991). Adaptive protein evolution at the Adh locus in Drosophila. Nature, 351(6328), 652–654. doi: 10.1038/351652a0
[5] Rousselle, M., Simion, P., Tilak, M. K., Figuet, E., Nabholz, B., and Galtier, N. (2019). Is adaptation limited by mutation? A timescale-dependent effect of genetic diversity on the adaptive substitution rate in animals. BioRxiv, 643619, ver 4 peer-reviewed and recommended by Peer Community In Evolutionary Biology. doi: 10.1101/643619
[6] Popadin, K., Polishchuk, L. V., Mamirova, L., Knorre, D., and Gunbin, K. (2007). Accumulation of slightly deleterious mutations in mitochondrial protein-coding genes of large versus small mammals. Proceedings of the National Academy of Sciences, 104(33), 13390–13395. doi: 10.1073/pnas.0701256104

22 Jul 2019
article picture

Transgenerational plasticity of inducible defenses: combined effects of grand-parental, parental and current environments

Transgenerational plasticity through three generations

Recommended by based on reviews by Stewart Plaistow and 1 anonymous reviewer

Organisms very often display phenotypic plasticity, whereby the expression of trait (or suite of traits) changes in a consistent way as a function of some environmental variable. Sometimes this plastic response remains labile and so the trait continues to respond to the environment throughout an organism’s life, but there are also many examples in which environmental conditions during a critical developmental window irreversibly set the stage for how a trait will be expressed later in life.
Traditionally, most studies of phenotypic plasticity have considered how an organism’s phenotype is altered by the environment that it experiences (called within-generation plasticity) but there is growing interest in how an organism’s phenotype is altered by the environment experienced by its ancestors (called transgenerational plasticity) [1]. In the simplest cases an organism’s phenotype might be affected by the environmental conditions experienced by its parents. There are several examples of this phenomenon as well, including interesting cases where predator cues experiences by an organism’s parents dictate the extent to which it displays a defensive phenotype.
Tariel et al. [2] present a study that takes these ideas to the next logical step and examines transgenerational plasticity through three generations. They used a well-studied system of snails (Physa acuta) that display inducible defences in response to predator (crayfish) cues. The authors exposed three generations of snails to one of two treatments: the presence or absence of predator cues, and then examined a suite of behavioural and morphological traits associated with predator defence. This allowed them to determine if and how offspring, parental, and grandparental environment influence offspring phenotype.
Interestingly, their results do show that transgenerational plasticity can act across multiple generations. The patterns found were complex though and it is difficult at this stage to assess how likely it is that these responses are adaptive. For example, a behavioural trait appears to respond to grandparental but not parental environment, shell thickness responds to both, and snail weight and a composite index of morphology respond to neither. Exactly what this means in terms of an offspring’s fitness, however, is unclear. It is also not immediately clear from the study how predictive a grandparent’s environment is of the conditions likely to be faced by an individual. Further work will be needed on these issues to better interpret what this transgenerational plasticity means and to assess if it might be an evolved response to cope with varying predation pressure. It would also be useful to delve more deeply into the developmental mechanisms throughout which this plasticity occurs. Irrespective of these issues, however, the study does reveal that transgenerational plasticity across multiple generations can indeed occur and so cannot be ignored as a source of phenotypic variation.


[1] West-Eberhard, M. J. (2003). Developmental plasticity and evolution. Oxford University Press.
[2] Tariel, J., Plenet, S., and Luquet, E. (2019). Transgenerational plasticity of inducible defenses: combined effects of grand-parental, parental and current environments. bioRxiv, 589945, ver. 3, peer-reviewed and recommended by Peer Community in Evolutionary Biology. doi: 10.1101/589945

10 Jul 2019
article picture

Population genomics supports clonal reproduction and multiple gains and losses of parasitic abilities in the most devastating nematode plant pest

The scandalous pest

Recommended by based on reviews by 2 anonymous reviewers

Koutsovoulos et al. [1] have generated and analysed the first population genomic dataset in root-knot nematode Meloidogyne incognita. Why is this interesting? For two major reasons. First, M. incognita has been documented to be apomictic, i.e., to lack any form of sex. This is a trait of major evolutionary importance, with implications on species adaptive potential. The study of genome evolution in asexuals is fascinating and has the potential to inform on the forces governing the evolution of sex and recombination. Even small amounts of sex, however, are sufficient to restore most of the population genetic properties of true sexuals [2]. Because rare events of sex can remain undetected in the field, to confirm asexuality in M. incognita using genomic data is an important step. The second reason why M. incognita is of interest is that this nematode is one of the most harmful pests currently living on earth. M. incognita feeds on the roots of many cultivated plants, including tomato, bean, and cotton, and has been of major agricultural importance for decades. A number of races were defined based on host specificity. These have played a key role in attempts to control the dynamic of M. incognita populations via crop rotations. Races and management strategies so far lack any genetic basis, hence the second major interest of this study.
The authors newly sequenced the full genome of eleven strains from Brazil and added nine already available samples from Africa and North-America. They report that, in all likelihood, M. incognita is indeed a purely asexual species. This is supported by (i) the confirmation that the genome is in its major part haploid, and (ii) a spectacularly high level of linkage disequilibrium, which does not decline with genetic distance between loci at a 100kb scale. The absence of sex and recombination is associated in M. incognita with a remarkably low amount of genetic diversity - one order of magnitude less than in typical sexual nematodes - and an heavy load of deleterious mutations, as measured by the ratio of non-synonymous (=amino-acid changing) to synonymous (=amino-acid conservative) diversity in coding sequences. The other important result of this study is that the population substructure in M. incognita is in no way related to host races or geography. The tree genetic clusters that are identified include strains from several continents and feeding on a diversity of host plants.
The implications of this work are numerous. First, the results suggest that M. incognita is an ancient asexual. Asexuality, which was here demonstrated via linkage disequilibrium analysis, must be ancient enough for diploidy (or, in this case, maybe triploidy) to have been lost - i.e., formerly homologous chromosomes have accumulated enough mutations to be assembled as distinct entities. So we are not talking about a highly successful clone having recently spread the world - rather a long-term obligate parthenogen. Asexual organisms are deprived of the source of genetic variation offered by recombination, which is why asexuality is thought to be an evolutionary dead-end. Long-term asexuals are uncommon and even the most famous ones, bdelloid rotifers, are suspected to experience between-individual genetic transfers [3]. M. incognita is apparently a true 'evolutionary scandal', and as such deserves particular attention from molecular evolutionary geneticists.
The lack of any host race effect on the genetic diversity of M. incognita is another important finding. So-called 'races' have largely contributed to shape researchers' view of the structure of the species so far. This study demonstrates that a mental effort is now needed to forget about races, and consider host-specificity for what it is - a phenotypic trait. This result implies that many host shifts must have independently occurred in the three M. incognita genetic lineages, suggesting an arms race between plants and nematodes, which in the absence of sex and recombination must be entirely mutation-driven on the nematode side. Genes functionally involved in the arms race might therefore be expected to have experienced convergent evolution, if distinct M. incognita lineages have adopted the same solutions to overcome plant defenses. The present study paves the way for such a genome scan. The authors rightly discuss that the strong adaptive potential of M. incognita, at least in terms of host shift, despite no sex and tiny amounts of genetic diversity, is a paradox that would deserve to be further investigated.


[1] Koutsovoulos, G. D., Marques, E., Arguel, M. J., Duret, L., Machado, A. C. Z., Carneiro, R. M. D. G., Kozlowski, D. K., Bailly-Bechet, M., Castagnone-Sereno, P., Albuquerque, E. V., & Danchin, E. G. J. (2019). Population genomics supports clonal reproduction and multiple gains and losses of parasitic abilities in the most devastating nematode plant pest. bioRxiv, 362129, ver. 5, peer-reviewed and recommended by Peer Community in Evolutionary Biology. doi: 10.1101/362129
[2] Hartfield, M. (2016). Evolutionary genetic consequences of facultative sex and outcrossing. Journal of evolutionary biology, 29(1), 5-22. doi: 10.1111/jeb.12770
[3] Debortoli, N., Li, X., Eyres, I., Fontaneto, D., Hespeels, B., Tang, C. Q., Flot, J. F. & Van Doninck, K. (2016). Genetic exchange among bdelloid rotifers is more likely due to horizontal gene transfer than to meiotic sex. Current Biology, 26(6), 723-732. doi: 10.1016/j.cub.2016.01.031

11 Jun 2019
article picture

A bird’s white-eye view on neosex chromosome evolution

Young sex chromosomes discovered in white-eye birds

Recommended by based on reviews by Gabriel Marais, Melissa Wilson and 1 anonymous reviewer

Recent advances in next-generation sequencing are allowing us to uncover the evolution of sex chromosomes in non-model organisms. This study [1] represents an example of this application to birds of two Sylvioidea species from the genus Zosterops (commonly known as white-eyes). The study is exemplary in the amount and types of data generated and in the thoroughness of the analysis applied. Both male and female genomes were sequenced to allow the authors to identify sex-chromosome specific scaffolds. These data were augmented by generating the transcriptome (RNA-seq) data set. The findings after the analysis of these extensive data are intriguing: neoZ and neoW chromosome scaffolds and their breakpoints were identified. Novel sex chromosome formation appears to be accompanied by translocation events. The timing of formation of novel sex chromosomes was identified using molecular dating and appears to be relatively recent. Yet first signatures of distinct evolutionary patterns of sex chromosomes vs. autosomes could be already identified. These include the accumulation of transposable elements and changes in GC content. The changes in GC content could be explained by biased gene conversion and altered recombination landscape of the neo sex chromosomes. The authors also study divergence and diversity of genes located on the neo sex chromosomes. Here their findings appear to be surprising and need further exploration. The neoW chromosome already shows unique patterns of divergence and diversity at protein-coding genes as compared with genes on either neoZ or autosomes. In contrast, the genes on the neoZ chromosome do not display divergence or diversity patterns different from those for autosomes. This last observation is puzzling and I believe should be explored in further studies. Overall, this study significantly advances our knowledge of the early stages of sex chromosome evolution in vertebrates, provides an example of how such a study could be conducted in other non-model organisms, and provides several avenues for future work.


[1] Leroy T., Anselmetti A., Tilak M.K., Bérard S., Csukonyi L., Gabrielli M., Scornavacca C., Milá B., Thébaud C. and Nabholz B. (2019). A bird’s white-eye view on neo-sex chromosome evolution. bioRxiv, 505610, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/505610

06 Jun 2019
article picture

Multi-model inference of non-random mating from an information theoretic approach

Tell me who you mate with, I’ll tell you what’s going on

Recommended by and based on reviews by Alexandre Courtiol and 2 anonymous reviewers

The study of sexual selection goes as far as Darwin himself. Since then, elaborate theories concerning both intra- and inter-sexual sexual have been developed, and elegant experiments have been designed to test this body of theory. It may thus come as a surprise that the community is still debating on the correct way to measure simple components of sexual selection, such as the Bateman gradient (i.e., the covariance between the number of matings and the number of offspring)[1,2], or to quantify complex behaviours such as mate choice (the non-random choice of individuals with particular characters as mates)[3,4] and their consequences.
One difficulty in the study of sexual selection is evaluating the consequences of non-random mating. Indeed, when non-random mating is observed in a population, it is often difficult to establish whether such mating pattern leads to i) sexual selection per se (selection pressures favouring certain phenotypes), and/or ii) the non-random association of parental genes in their offspring or not. These two processes differ. In particular, assortative (and disassortative) mating can shape genetic covariances without leading to changes in gene frequencies in the population. Their distinction matters because these two processes lead to different evolutionary outcomes, which can have large ripple effects in the evolution of sexual behaviours, sexual ornamentation, and speciation.
In his paper, entitled “Multi-model inference of non-random mating from an information theoretic approach” [5], Carvajal-Rodríguez tackled this issue. The author generated a simple model in which the consequences of non-random mating can be inferred from information on the population frequencies before and after mating. The procedure is as follows: from the initial population frequencies of phenotypes (or genotypes) of both sexes, the model generates predictions on the frequencies after mating, assuming that particular mating patterns have occurred. This leads to different predictions for the phenotypic (or genotypic) frequencies after mating. The particular mating pattern leading to the best fit with the real frequencies is then identified via a model selection procedure (performing model averaging to combine different mating patterns is also possible).
This study builds on a framework introduced by Carvajal-Rodríguez’s colleagues [6] and encompasses later methodological developments involving the author himself [7]. Compared to early work, the new method proposed by the author builds on the relationship between mating pattern and information [8] to distinguish among scenarios that would lead to non-random mating due to different underlying processes, using simple model selection criterion such as the AICc.
The great asset of the proposed method is that it can be applied to the study of natural populations in which the study of mate choice and sexual selection is notoriously difficult. In the manuscript, the procedure is tested on a population of marine gastropods (Littorina saxatilis). This allows the reader to grasp how the method can be applied to a real system. In fact, anyone can try out the method thanks to the freely available software InfoMating programmed by the author. One important assumption underlying the current method is that the frequencies of unmated individuals do not change during the mating season. If this is not the case, the reader may refer to another publication of the same author which relaxes this assumption [9]. These papers are both instrumental for empiricists interested in testing sexual selection theory.


[1] Bateman, A. J. (1948). Intra-sexual selection in Drosophila. Heredity, 2(3), 349-368. doi: 10.1038/hdy.1948.21
[2] Jones, A. G. (2009). On the opportunity for sexual selection, the Bateman gradient and the maximum intensity of sexual selection. Evolution: International Journal of Organic Evolution, 63(7), 1673-1684. doi: 10.1111/j.1558-5646.2009.00664.x
[3] Andersson, M., & Simmons, L. W. (2006). Sexual selection and mate choice. Trends in ecology & evolution, 21(6), 296-302. doi: 10.1016/j.tree.2006.03.015
[4] Kuijper, B., Pen, I., & Weissing, F. J. (2012). A guide to sexual selection theory. Annual Review of Ecology, Evolution, and Systematics, 43, 287-311. doi: 10.1146/annurev-ecolsys-110411-160245
[5] Carvajal-Rodríguez, A. (2019). Multi-model inference of non-random mating from an information theoretic approach. bioRxiv, 305730, ver. 5 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/305730
[6] Rolán‐Alvarez, E., & Caballero, A. (2000). Estimating sexual selection and sexual isolation effects from mating frequencies. Evolution, 54(1), 30-36. doi: 10.1111/j.0014-3820.2000.tb00004.x
[7] Carvajal-Rodríguez, A., & Rolan-Alvarez, E. (2006). JMATING: a software for the analysis of sexual selection and sexual isolation effects from mating frequency data. BMC Evolutionary Biology, 6(1), 40. doi: 10.1186/1471-2148-6-40
[8] Carvajal-Rodríguez, A. (2018). Non-random mating and information theory. Theoretical population biology, 120, 103-113. doi: 10.1016/j.tpb.2018.01.003
[9] Carvajal-Rodríguez, A. (2019). A generalization of the informational view of non-random mating: Models with variable population frequencies. Theoretical population biology, 125, 67-74. doi: 10.1016/j.tpb.2018.12.004

04 Jun 2019
article picture

Thermal regimes, but not mean temperatures, drive patterns of rapid climate adaptation at a continent-scale: evidence from the introduced European earwig across North America

Temperature variance, rather than mean, drives adaptation to local climate

Recommended by based on reviews by Ben Phillips and Eric Gangloff

Climate change is impacting eco-systems worldwide and driving many populations to move, adapt or go extinct. It is increasingly appreciated, for example, that species may adjust their phenology in response to climate change, although empirical data is scarce. In this preprint [1], Tourneur and Meunier report an impressive sampling effort in which life-history traits were measured across introduced populations of earwig in North America. The authors examine whether variation in life-history across populations is correlated with aspects of the thermal climate experienced by each population: mean temperature and seasonality of temperature. They find some fascinating correlations between life-history and thermal climate; correlations with the seasonality of temperature, but not with mean temperature. This study provides relatively uncommon data, in the sense that where most of the literature looking at adaptation in animals in response to climate change has focused on physiological traits [2, 3], this study examines changes in life-history traits with time scales relevant to impending climate change, and provides a reasonable argument that this is adaptation, not just constraint.


[1] Tourneur, J.-C. and Meunier, J. (2019). Thermal regimes, but not mean temperatures, drive patterns of rapid climate adaptation at a continent-scale: evidence from the introduced European earwig across North America. BioRxiv, 550319, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/550319
[2] Kellermann, V., Overgaard, J., Hoffmann, A. A., Fløjgaard, C., Svenning, J. C., & Loeschcke, V. (2012). Upper thermal limits of Drosophila are linked to species distributions and strongly constrained phylogenetically. Proceedings of the National Academy of Sciences, 109(40), 16228-16233. doi: 10.1073/pnas.1207553109
[3] Hoffmann, A. A., & Sgro, C. M. (2011). Climate change and evolutionary adaptation. Nature, 470(7335), 479. doi: 10.1038/nature09670

03 Jun 2019
article picture

Transcriptomic response to divergent selection for flowering time in maize reveals convergence and key players of the underlying gene regulatory network

Early and late flowering gene expression patterns in maize

Recommended by based on reviews by Laura Shannon and 2 anonymous reviewers

Artificial selection experiments are key experiments in evolutionary biology. The demonstration that application of selective pressure across multiple generations results in heritable phenotypic changes is a tangible and reproducible proof of the evolution by natural selection.
Artificial selection experiments are used to evaluate the joint effects of selection on multiple traits, their genetic covariances and differences in responses in different environments. Most studies on artificial selection experiments report and base their analyses on phenotypic changes [1]. More recently, changes in allele frequency and other patterns of molecular genetic diversity have been used to identify genomic locations where selection has had an effect. However, so far the changes in gene expression have not been in the focus of artificial selection experiment studies (see [2] for an example though).
In plants, one of the most famous artificial selection experiments is the Illinois Corn Experiment where maize (Zea mays) is selected for oil and protein content [3], but in addition, similar experiments have been conducted also for other traits in maize. In Saclay divergent selection experiment [4] two maize inbred lines (F252 and MBS847) have been selected for early and late flowering for 13 generations, resulting in two week difference in flowering time.
In ”Transcriptomic response to divergent selection for flowering time in maize reveals convergence and key players of the underlying gene regulatory network ” [5] Maud Tenaillon and her coworkers study the gene expression differences among these two independently selected maize populations. Their experiments cover two years in field conditions and they use samples of shoot apical meristem at three different developmental stages: vegetative, transitioning and reproductive. They use RNA-seq transcriptome level differences and qRT-PCR for gene expression pattern investigation. The work is continuation to earlier genetic and phenotypic studies on the same material [4, 6].
The reviewers and I agree that dataset is unique and its major benefit is that it has been obtained from field conditions similar to those that species may face under natural setting during selection. Their tissue sampling is supported by flowering time phenotypic observations and covers the developmental transition stage, making a good effort to identify key transcriptional and phenotypic changes and their timing affected by selection.
Tenaillon et al. [5] identify more than 2000 genes that are differentially expressed among early and late flowering populations. Expectedly, they are enriched for known flowering time genes. As they point out, differential expression of thousands of genes does not mean that they all were independently affected by selection, but rather that the whole transcriptional network has shifted, possibly due to just few upstream or hub-genes. Also, the year-to-year variation had smaller effect in gene expression compared to developmental stage or genetic background, possibly indicating selection for stability across environmental fluctuation for such an important phenotype as flowering time.
Another noteworthy observation is that they find convergent patterns of transcriptional changes among the two selected lines. 115 genes expression patterns are shifted due to selection in both genetic backgrounds. This convergent pattern can be a result of either selection on standing variation or de novo mutations. The data does not allow testing which process is underlying the observed convergence. However, their results show that this is an interesting future question that can be addressed using genotype and gene expression data from the same ancestral and derived material and possibly their hybrids.


[1] Hill, W. G., & Caballero, A. (1992). Artificial selection experiments. Annual Review of Ecology and Systematics, 23(1), 287-310. doi: 10.1146/
[2] Konczal, M., Babik, W., Radwan, J., Sadowska, E. T., & Koteja, P. (2015). Initial molecular-level response to artificial selection for increased aerobic metabolism occurs primarily through changes in gene expression. Molecular biology and evolution, 32(6), 1461-1473. doi: 10.1093/molbev/msv038
[3] Moose, S. P., Dudley, J. W., & Rocheford, T. R. (2004). Maize selection passes the century mark: a unique resource for 21st century genomics. Trends in plant science, 9(7), 358-364. doi: 10.1016/j.tplants.2004.05.005
[4] Durand, E., Tenaillon, M. I., Ridel, C., Coubriche, D., Jamin, P., Jouanne, S., Ressayre, A., Charcosset, A. and Dillmann, C. (2010). Standing variation and new mutations both contribute to a fast response to selection for flowering time in maize inbreds. BMC evolutionary biology, 10(1), 2. doi: 10.1186/1471-2148-10-2
[5] Tenaillon, M. I., Seddiki, K., Mollion, M., Le Guilloux, M., Marchadier, E., Ressayre, A. and Dillmann C. (2019). Transcriptomic response to divergent selection for flowering time in maize reveals convergence and key players of the underlying gene regulatory network. BioRxiv, 461947 ver. 5 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/461947
[6] Durand, E., Tenaillon, M. I., Raffoux, X., Thépot, S., Falque, M., Jamin, P., Bourgais A., Ressayre, A. and Dillmann, C. (2015). Dearth of polymorphism associated with a sustained response to selection for flowering time in maize. BMC evolutionary biology, 15(1), 103. doi: 10.1186/s12862-015-0382-5

06 May 2019
article picture

When sinks become sources: adaptive colonization in asexuals

Fisher to the rescue

Recommended by and based on reviews by 3 anonymous reviewers

The ability of a population to adapt to a new niche is an important phenomenon in evolutionary biology. The colonisation of a new volcanic island by plant species; the colonisation of a host treated by antibiotics by a-resistant strain; the Ebola virus transmitting from bats to humans and spreading epidemically in Western Africa, are all examples of a population invading a new niche, adapting and eventually establishing in this new environment.

Adaptation to a new niche can be studied using source-sink models. In the original environment —the “source”—, the population enjoys a positive growth-rate and is self-sustaining, while in the new environment —the “sink”— the population has a negative growth rate and is able to sustain only by the continuous influx of migrants from the source. Understanding the dynamics of adaptation to the sink environment is challenging from a theoretical standpoint, because it requires modelling the demography of the sink as well as the transient dynamics of adaptation. Moreover, local selection in the sink and immigration from the source create distributions of genotypes that complicate the use of many common mathematical approaches.

In their paper, Lavigne et al. [1], develop a new deterministic model of adaptation to a harsh sink environment in an asexual species. The fitness of an individual is maximal when a number of phenotypes are tuned to an optimal value, and declines monotonously as phenotypes are further away from this optimum. This model —called Fisher’s Geometric Model— generates a GxE interaction for fitness because the phenotypic optimum in the sink environment is distinct from that in the source environment [2]. The authors circumvent mathematical difficulties by developing an original approach based on tracking the deterministic dynamics of the cumulant generating function of the fitness distribution in the sink. They derive a number of important results on the dynamics of adaptation to the sink:

  • From the point where immigration from the source to the sink starts, four phases of adaptation are observed. After a short transient phase (phase 1), a migration-selection balance is reached in the sink (phase 2). After a while, thanks to the immigration of rare adapted migrants and mutation in the sink, a small fraction of the sink population exhibits a close-to-optimal phenotype. This small adapted fraction grows in frequency and mean fitness rapidly increases in the sink (phase 3). Finally, the population settles around the sink optimum (phase 4) and, hurray, the sink is now a source!

  • Interestingly, in this model the evolutionary dynamics do not depend on the immigration rate. In other words, adaptation will proceed at the same rate regardless of how many immigrants invade the sink. This is because the impact of immigration on adaptation depends on the rate of immigration relative to the sink density. This ratio is actually independent of immigration in a model where the sink is initially empty, migration from the sink back to the source is negligible and without density-dependence in the sink.

  • In this model, mutation is a double-edged sword. Adapted phenotypes emerge from new mutations, and under this effect alone a higher mutation rate would translate into a shorter time to establishment in the sink. However, mutations may also have deleterious effects by displacing the phenotype away from the optimum. This mutation load will be greater when individuals need to simultaneously tune a large number of phenotypes. As a consequence of these two effects of mutations, time to establishment is minimal for an intermediate mutation rate. This result emerges from Fisher’s Geometric Model, but may hold more generally for biologically plausible fitness landscapes where mutations generates both beneficial (allowing adaptation to the sink) and deleterious genotypes.

  • Lastly, in Fisher’s Geometric Model, the time to establishment increases superlinearly with harshness of the sink when the sink is too harsh, and establishment may occur only after a very long time. In these harsh sinks, the adapted genotypes are very few and increase very slowly in frequency, making the second phase of adaptation much longer. Thus, and as a direct consequence of Fisher’s Geometric Model, adding a “stepping stone” intermediate environment would allow faster adaptation to the extreme environment.

In conclusion, this theoretical work presents a method based on Fisher’s Geometric Model and the use of cumulant generating functions to resolve some aspects of adaptation to a sink environment. It generates a number of theoretical predictions for the adaptive colonisation of a sink by an asexual species with some standing genetic variation. It will be a fascinating task to examine whether these predictions hold in experimental evolution systems: will we observe the four phases of the dynamics of mean fitness in the sink environment? Will the rate of adaptation indeed be independent of the immigration rate? Is there an optimal rate of mutation for adaptation to the sink? Such critical tests of the theory will greatly improve our understanding of adaptation to novel environments.


[1] Lavigne, F., Martin, G., Anciaux, Y., Papaïx, J., and Roques, L. (2019). When sinks become sources: adaptive colonization in asexuals. bioRxiv, 433235, ver. 5 peer-reviewed and recommended by PCI Evolutionary Biology. doi: 10.1101/433235
[2] Martin, G., and Lenormand, T. (2006). A general multivariate extension of Fisher's geometrical model and the distribution of mutation fitness effects across species. Evolution, 60, 893-907. doi: 10.1111/j.0014-3820.2006.tb01169.x

28 Mar 2019
article picture

Ancient tropical extinctions contributed to the latitudinal diversity gradient

One (more) step towards a dynamic view of the Latitudinal Diversity Gradient

Recommended by and based on reviews by Juan Arroyo, Joaquín Hortal, Arne Mooers, Joaquin Calatayud and 2 anonymous reviewers

The Latitudinal Diversity Gradient (LDG) has fascinated natural historians, ecologists and evolutionary biologists ever since [1] described it about 200 years ago [2]. Despite such interest, agreement on the origin and nature of this gradient has been elusive. Several tens of hypotheses and models have been put forward as explanations for the LDG [2-3], that can be grouped in ecological, evolutionary and historical explanations [4] (see also [5]). These explanations can be reduced to no less than 26 hypotheses, which account for variations in ecological limits for the establishment of progressively larger assemblages, diversification rates, and time for species accumulation [5]. Besides that, although in general the tropics hold more species, different taxa show different shapes and rates of spatial variation [6], and a considerable number of groups show reverse patterns, with richer assemblages in cold temperate regions (see e.g. [7-9]).
Understanding such complexity needs integrating ecological and evolutionary research into the wide temporal and spatial perspectives provided by the burgeoning field of biogeography. This integrative discipline ¬–that traces back to Humboldt himself (e.g. [10])– seeks to put together historical and functional explanations to explain the complex dynamics of Earth’s biodiversity. Different to quantum physicists, biogeographers cannot pursue the ultimate principle behind the patterns we observe in nature due to the interplay of causes and effects, which in fact tell us that there is not such a single principle. Rather, they need to identify an array of basic principles coming from different perspectives, to then integrate them into models that provide realistic –but never simple– explanations to biodiversity gradients such as LDG (see, e.g., [5; 11]). That is, rather than searching for a sole explanation, research on the LDG must aim to identify as many signals hidden in the pattern as possible, and provide hypotheses or models that account for these signals. To later integrate them and, whenever possible, to validate them with empirical data on the organisms’ distribution, ecology and traits, phylogenies, fossils, etc.
Within this context, Meseguer & Condamine [12] provide a novel perspective to LDG research using phylogenetic and fossil evidence on the origin and extinction of taxa within the turtle, crocodile and lizard (i.e. squamate) lineages. By digging into deep time down to the Triassic (about 250 Myr ago) they are able to identify several episodes of flattening and steepening of the LDG for these three clades. Strikingly, their results show similar diversification rates in the northern hemisphere and in the equator during the over 100 Myr long global greenhouse period that extends from the late Jurassic to the Cretaceous and early Neogene. During this period, the LDG for these three groups would have appeared quite even across a mainly tropical Globe, although the equatorial regions were apparently much more evolutionarily dynamic. The equator shows much higher rates of origination and extinction of branches throughout the Cretaceous, but they counteract each other so net diversification is similar to that of the northern hemisphere in all three groups. The transition to a progressively colder Earth in the Paleogene (starting around 50 Myr ago) provokes a mass extinction in the three clades, which is compensated in the equator by the dispersal of many taxa from the areas that currently pertain to the Holarctic biogeographical realm. Finally, during the coldhouse Earth’s climatic conditions of the Neogene only squamates show significant positive diversification rates in extratropical areas, while the diversity of testudines remains, and crocodiles continue declining progressively towards oblivion in the whole world.
Meseguer & Condamine [12] attribute these temporal patterns to the so-called asymmetric gradient of extinction and dispersal (AGED) framework. Here, the dynamics of extinction-at and dispersal-from high latitudes during colder periods increase the steepness of the LDG. Whereas the gradient flattens when Earth warms up as a result of dispersal from the equator followed by increased diversification in extratropical regions. This idea in itself is not new, for the influence of climatic oscillations on diversification rates is well known, at least for the Pleistocene Ice Ages [13], as is the effect of niche conservatism on the LDG [14]. Nevertheless, Meseguer & Condamine’s AGED provides a synthetic verbal model that could allow integrating the three main types of processes behind the LDG into a single framework. To do this it would be necessary to combine AGED’s cycles of dispersal and diversification with realistic models of: (1) the ecological limits to host rich assemblages in the colder and less productive temperate climatic domains; (2) the variations in diversification rates with shifts in temperature and/or energy regimes; and (3) the geographical patterns of climatic oscillation through time that determine the time for species accumulation in each region.
Integrating these models may allow transposing Meseguer & Condamine’s [12] framework into the more mechanistic macroecological models advocated by Pontarp et al. [5]. This type of mechanistic models has been already used to understand the development of biodiversity gradients through the climatic oscillations of the Pleistocene and the Quaternary (e.g. [11]). So the challenge in this case would be to generate a realistic scenario of geographical dynamics that accounts for plate tectonics and long-term climatic oscillations. This is still a major gap and we would benefit from the integrated work by historical geologists and climatologists here. For instance, there is little doubt about the progressive cooling through the Cenozoic based in isotope recording in sea floor sediments [15]. Meseguer & Condamine [12] use this evidence for separating greenhouse, transition and coldhouse world scenarios, which should not be a problem for these rough classes. However, a detailed study of the evolutionary correlation of true climate variables across the tree of life is still pending, as temperature is inferred only for sea water in an ice-free ocean, say earlier half of the Cenozoic [15]. Precipitation regime is even less known. Such scenario would provide a scaffold upon which the temporal dynamics of several aspects of the generation and loss of biodiversity can be modelled. Additionally, one of the great advantages of selecting key clades to study the LDG would be to determine the functional basis of diversification. There are species traits that are well known to affect speciation and extinction probabilities, such as reproductive strategies or life histories (e.g. [16]). Whereas these traits might also be a somewhat redundant effect of climatic causes, they might foster (i.e. “extended reinforcement”, [17]) or slow diversification. Even so, it is unlikely that such a model would account for all the latitudinal variation in species richness. But it will at least provide a baseline for the main latitudinal variations in the diversity of the regional communities (sensu [18]) worldwide. Within this context the effects of recent ecological, evolutionary and historical processes, such as environmental heterogeneity, current diversification rates or glacial cycles, will only modify the general LDG pattern resulting from the main processes contained in Meseguer & Condamine’s AGED, thereby providing a more comprehensive understanding of the geographical gradients of diversity.

[1] Humboldt, A. v. (1808). Ansichten der Natur, mit wissenschaftlichen Erläuterungen. J. G. Cotta, Tübingen.
[2] Hawkins, B. A. (2001). Ecology's oldest pattern? Trends in Ecology & Evolution, 16, 470. doi: 10.1016/S0169-5347(01)02197-8
[3] Lomolino, M. V., Riddle, B. R. & Whittaker, R. J. (2017). Biogeography. Fifth Edition. Sinauer Associates, Inc., Sunderland, Massachussets.
[4] Mittelbach, G. G., Schemske, D. W., Cornell, H. V., Allen, A. P., Brown, J. M., Bush, M. B., Harrison, S. P., Hurlbert, A. H., Knowlton, N., Lessios, H. A., McCain, C. M., McCune, A. R., McDade, L. A., McPeek, M. A., Near, T. J., Price, T. D., Ricklefs, R. E., Roy, K., Sax, D. F., Schluter, D., Sobel, J. M. & Turelli, M. (2007). Evolution and the latitudinal diversity gradient: speciation, extinction and biogeography. Ecology Letters, 10, 315-331. doi: 10.1111/j.1461-0248.2007.01020.x
[5] Pontarp, M., Bunnefeld L., Cabral, J. S., Etienne, R. S., Fritz, S. A., Gillespie, R. Graham, C. H., Hagen, O., Hartig, F., Huang, S., Jansson, R., Maliet, O., Münkemüller, T., Pellissier, L., Rangel, T. F., Storch, D., Wiegand, T. & Hurlbert, A. H. (2019). The latitudinal diversity gradient: novel understanding through mechanistic eco-evolutionary models. Trends in ecology & evolution, 34, 211-223. doi: 10.1016/j.tree.2018.11.009
[6] Hillebrand, H. (2004). On the generality of the latitudinal diversity gradient. The American Naturalist, 163, 192-211. doi: 10.1086/381004
[7] Santos, A. M. C. & Quicke, D. L. J. (2011). Large-scale diversity patterns of parasitoid insects. Entomological Science, 14, 371-382. doi: 10.1111/j.1479-8298.2011.00481.x
[8] Morinière, J., Van Dam, M. H., Hawlitschek, O., Bergsten, J., Michat, M. C., Hendrich, L., Ribera, I., Toussaint, E. F. A. & Balke, M. (2016). Phylogenetic niche conservatism explains an inverse latitudinal diversity gradient in freshwater arthropods. Scientific Reports, 6, 26340. doi: 10.1038/srep26340
[9] Weiser, M. D., Swenson, N. G., Enquist, B. J., Michaletz, S. T., Waide, R. B., Zhou, J. & Kaspari, M. (2018). Taxonomic decomposition of the latitudinal gradient in species diversity of North American floras. Journal of Biogeography, 45, 418-428. doi: 10.1111/jbi.13131
[10] Humboldt, A. v. (1805). Essai sur la geographie des plantes; accompagné d'un tableau physique des régions equinoxiales. Levrault, Paris.
[11] Rangel, T. F., Edwards, N. R., Holden, P. B., Diniz-Filho, J. A. F., Gosling, W. D., Coelho, M. T. P., Cassemiro, F. A. S., Rahbek, C. & Colwell, R. K. (2018). Modeling the ecology and evolution of biodiversity: Biogeographical cradles, museums, and graves. Science, 361, eaar5452. doi: 10.1126/science.aar5452
[12] Meseguer, A. S. & Condamine, F. L. (2019). Ancient tropical extinctions contributed to the latitudinal diversity gradient. bioRxiv, 236646, ver. 4 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/236646
[13] Jansson, R., & Dynesius, M. (2002). The fate of clades in a world of recurrent climatic change: Milankovitch oscillations and evolution. Annual review of ecology and systematics, 33(1), 741-777. doi: 10.1146/annurev.ecolsys.33.010802.150520
[14] Wiens, J. J., & Donoghue, M. J. (2004). Historical biogeography, ecology and species richness. Trends in ecology & evolution, 19, 639-644. doi: 10.1016/j.tree.2004.09.011
[15] Zachos, J. C., Dickens, G. R., & Zeebe, R. E. (2008). An early Cenozoic perspective on greenhouse warming and carbon-cycle dynamics. Nature, 451, 279-283. doi: 10.1038/nature06588
[16] Zúñiga-Vega, J. J., Fuentes-G, J. A., Ossip-Drahos, A. G., & Martins, E. P. (2016). Repeated evolution of viviparity in phrynosomatid lizards constrained interspecific diversification in some life-history traits. Biology letters, 12, 20160653. doi: 10.1098/rsbl.2016.0653
[17] Butlin, R. K., & Smadja, C. M. (2018). Coupling, reinforcement, and speciation. The American Naturalist, 191, 155-172. doi: 10.1086/695136
[18] Ricklefs, R. E. (2015). Intrinsic dynamics of the regional community. Ecology letters, 18, 497-503. doi: 10.1111/ele.12431

25 Mar 2019
article picture

The joint evolution of lifespan and self-fertilisation

Evolution of selfing & lifespan 2.0

Recommended by based on reviews by 2 anonymous reviewers

Flowering plants display a staggering diversity of both mating systems and life histories, ranging from almost exclusively selfers to obligate outcrossers, very short-lived annual herbs to super long lived trees. One pervasive pattern that has attracted considerable attention is the tight correlation that is found between mating systems and lifespan [1]. Until recently, theoretical explanations for these patterns have relied on static models exploring the consequences of several non-mutually exclusive important process: levels of inbreeding depression and ability to successfully were center stage. This make sense: successful colonization after long‐distance dispersal is far more likely to happen for self‐compatible than for self‐incompatible individuals in a sexually reproducing species. Furthermore, inbreeding depression (essentially a genetically driven phenomenon) and reproductive insurance are expected to shape the evolution of both mating system and lifespan.
But modelling jointly several processes and how their interplay to shape the evolution of a trait is challenging enough so models for the evolution of mating system tend invariably – for mathematical convenience and tractability – to fix lifespan [2].
However, comparative analysis of between species variations that map traits transitions among sister species in phylogenetic trees reveals a pervasive pattern: frequent transitions from a state outcrossing perennial to selfing annuals. This beg the question: is one transition triggering the other and if so, what comes first or are these transitions happening together? In this work, Lesaffre and Billiard use a very sophisticated machinery developed by Kirkpatrick et al. [3] and consider a general class of so-called modifiers models [4]. They study jointly the evolution of life span and mating system. They do so by using models where different life stages are tracked with life stage having some (fixed for once) amount of inbreeding depression. Their paper is technically demanding, mixing analytics and computer simulations, and along the way generates several important findings that are expected to stimulate further empirical and theoretical studies: (1) pure selfing versus pure outcrossing is the expected stable evolutionary outcomes (despite observation that mixed mating systems can be regularly met in nature), (2) increasing life-span drastically reduces the scope for the evolution of selfing, conversely (3) transition to selfing will also select for shorter life span as a way to mitigate the cumulative effects of inbreeding depression on adult life stages.
As usual there is room for future work, in particular the authors’ model assumes fixed inbreeding depression in the different life stages and this highlights the need for models that explore how inbreeding depression, a pivotal quantity in these models, can itself be molded by both mating system and lifespan. A third-generation of models should be “soon” on the way!

[1] Grossenbacher D, Briscoe Runquist R, Goldberg EE, and Brandvain Y. (2015) Geographic range size is predicted by plant mating system. Ecology Letters 18, 706–713. doi: 10.1111/ele.12449
[2] Morgan MT, Schoen DJ, and Bataillon T. (1997) The evolution of self-fertilization in perennials. The American Naturalist 150, 618–638. doi: 10.1086/286085
[3] Kirkpatrick M, Johnson T, and Barton N. (2002) General models of multilocus evolution. Genetics 161, 1727–1750.
[4] Lesaffre, T, and Billiard S. (2019) The joint evolution of lifespan and self-fertilisation. bioRxiv, 420877, ver. 3 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/420877

15 Feb 2019
article picture

Architectural traits constrain the evolution of unisexual flowers and sexual segregation within inflorescences: an interspecific approach

Sometimes, sex is in the head

Recommended by based on reviews by 3 anonymous reviewers

Plants display an amazing diversity of reproductive strategies with and without sex. This diversity is particularly remarkable in flowering plants, as highlighted by Charles Darwin, who wrote several botanical books scrutinizing plant reproduction. One particularly influential work concerned floral variation [1]. Darwin recognized that flowers may present different forms within a single population, with or without sex specialization. The number of species concerned is small, but they display recurrent patterns, which made it possible for Darwin to invoke natural and sexual selection to explain them. Most of early evolutionary theory on the evolution of reproductive strategies was developed in the first half of the 20th century and was based on animals. However, the pioneering work by David Lloyd from the 1970s onwards excited interest in the diversity of plant sexual strategies as models for testing adaptive hypotheses and predicting reproductive outcomes [2]. The sex specialization of individual flowers and plants has since become one of the favorite topics of evolutionary biologists. However, attention has focused mostly on cases related to sex differentiation (dioecy and associated conditions [3]). Separate unisexual flower types on the same plant (monoecy and related cases, rendering the plant functionally hermaphroditic) have been much less studied, apart from their possible role in the evolution of dioecy [4] or their association with particular modes of pollination [5].
Two specific non-mutually exclusive hypotheses on the evolution of separate sexes in flowers (dicliny) have been proposed, both anchored in Lloyd’s views and Darwin’s legacy, with selfing avoidance and optimal limited resource allocation. Intermediate sex separation, in which sex morphs have different combinations of unisexual and hermaphrodite flowers, has been crucial for testing these hypotheses through comparative analyses of optimal conditions in suggested transitions. Again, cases in which floral unisexuality does not lead to sex separation have been studied much less than dioecious plants, at both the microevolutionary and macroevolutionary levels. It is surprising that the increasing availability of plant phylogenies and powerful methods for testing evolutionary transitions and correlations have not led to more studies, even though the frequency of monoecy is probably highest among diclinous species (those with unisexual flowers in any distribution among plants within a population [6]).
The study by Torices et al. [7] aims to fill this gap, offering a different perspective to that provided by Diggle & Miller [8] on the evolution of monoecious conditions. The authors use heads of a number of species of the sunflower family (Asteraceae) to test specifically the effect of resource limitation on the expression of sexual morphs within the head. They make use of the very particular and constant architecture of inflorescences in these species (the flower head or “capitulum”) and the diversity of sexual conditions (hermaphrodite, gynomonoecious, monoecious) and their spatial pattern within the flower head in this plant family to develop an elegant means of testing this hypothesis. Their results are consistent with their expectations on the effect of resource limitation on the head, as determined by patterns of fruit size within the head, assuming that female fecundity is more strongly limited by resource availability than male function.
The authors took on a huge challenge in choosing to study the largest plant family (about 25 thousand species). Their sample was limited to only about a hundred species, but species selection was very careful, to ensure that the range of sex conditions and the available phylogenetic information were adequately represented. The analytical methods are robust and cast no doubt on the reported results. However, I can’t help but wonder what would happen if the antiselfing hypothesis was tested simultaneously. This would require self-incompatibility (SI) data for the species sample, as the presence of SI is usually invoked as a powerful antiselfing mechanism, rendering the unisexuality of flowers unnecessary. However, SI is variable and frequently lost in the sunflower family [9]. I also wonder to what extent the very specific architecture of flower heads imposes an idiosyncratic resource distribution that may have fixed these sexual systems in species and lineages of the family. Although not approached in this study, intraspecific variation seems to be low. It would be very interesting to use similar approaches in other plant groups in which inflorescence architecture is lax and resource distribution may differ. A whole-plant approach might be required, rather than investigations of single inflorescences as in this study. This study has no flaws, but instead paves the way for further testing of a long-standing dual hypothesis, probably with different outcomes in different ecological and evolutionary settings. In the end, sex is not only in the head.


[1] Darwin, C. (1877). The different forms of flowers on plants of the same species. John Murray.
[2] Barrett, S. C. H., and Harder, L. D. (2006). David G. Lloyd and the evolution of floral biology: from natural history to strategic analysis. In L.D. Harder, L. D., and Barrett, S. C. H. (eds) Ecology and Evolution of Flowers. OUP, Oxford. Pp 1-21.
[3] Geber, M. A., Dawson, T. E., and Delph, L. F. (eds) (1999). Gender and sexual dimorphism in flowering plants. Springer, Berlin.
[4] Charlesworth, D. (1999). Theories of the evolution of dioecy. In Geber, M. A., Dawson T. E. and Delph L. F. (eds) (1999). Gender and sexual dimorphism in flowering plants. Springer, Berlin. Pp. 33-60.
[5] Friedman, J., and Barrett, S. C. (2008). A phylogenetic analysis of the evolution of wind pollination in the angiosperms. International Journal of Plant Sciences, 169(1), 49-58. doi: 10.1086/523365
[6] Renner, S. S. (2014). The relative and absolute frequencies of angiosperm sexual systems: dioecy, monoecy, gynodioecy, and an updated online database. American Journal of botany, 101(10), 1588-1596. doi: 10.3732/ajb.1400196
[7] Torices, R., Afonso, A., Anderberg, A. A., Gómez, J. M., and Méndez, M. (2019). Architectural traits constrain the evolution of unisexual flowers and sexual segregation within inflorescences: an interspecific approach. bioRxiv, 356147, ver. 3 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/356147
[8] Diggle, P. K., and Miller, J. S. (2013). Developmental plasticity, genetic assimilation, and the evolutionary diversification of sexual expression in Solanum. American journal of botany, 100(6), 1050-1060. doi: 10.3732/ajb.1200647
[9] Ferrer, M. M., and Good‐Avila, S. V. (2007). Macrophylogenetic analyses of the gain and loss of self‐incompatibility in the Asteraceae. New Phytologist, 173(2), 401-414. doi: 10.1111/j.1469-8137.2006.01905.x

08 Feb 2019
article picture

Genome plasticity in Papillomaviruses and de novo emergence of E5 oncogenes

E5, the third oncogene of Papillomavirus

Recommended by based on reviews by Leonardo de Oliveira Martins and 1 anonymous reviewer

Papillomaviruses (PVs) infect almost all mammals and possibly amniotes and bony fishes. While most of them have no significant effects on the hosts, some induce physical lesions. Phylogeny of PVs consists of a few crown groups [1], among which AlphaPVs that infect primates including human have been well studied. They are associated to largely different clinical manifestations: non-oncogenic PVs causing anogenital warts, oncogenic and non-oncogenic PVs causing mucosal lesions, and non-oncogenic PVs causing cutaneous warts.
The PV genome consists of a double stranded circular DNA genome, roughly organized into three parts: an early region coding for six open reading frames (ORFs: E1, E2, E4, E5, E6 and E7) involved in multiple functions including viral replication and cell transformation; a late region coding for structural proteins (L1 and L2); and a non-coding regulatory region (URR) that contains the cis-elements necessary for replication and transcription of the viral genome.
The E5, E6, and E7 are known to act as oncogenes. The E6 protein binds to the cellular p53 protein [2]. The E7 protein binds to the retinoblastoma tumor suppressor gene product, pRB [3]. However, the E5 has been poorly studied, even though a high correlation between the type of E5 protein and the infection phenotype is observed. E5s, being present on the E2/L2 intergenic region in the genomes of a few polyphyletic PV lineages, are so diverged and can only be characterized by high hydrophobicity. No similar sequences have been found in the sequence database.
Willemsen et al. [4] provide valuable evidence on the origin and evolutionary history of E5 genes and their genomic environments. First, they tested common ancestry vs independent origins [5]. Because alignment can lead to biased testing toward the hypothesis of common ancestry [6], they took full account of alignment uncertainty [7] and conducted random permutation test [8]. Although the strong chemical similarity hampered decisive conclusion on the test, they could confirm that E5 may do code proteins, and have unique evolutionary history with far different topology from the neighboring genes.
Still, there is mysteries with the origin and evolution of E5 genes. One of the largest interest may be the evolution of hydrophobicity, because it may be the main cause of variable infection phenotype. The inference has some similarity in nature with the inference of evolutionary history of G+C contents in bacterial genomes [9]. The inference may take account of possible opportunity of convergent or parallel evolution by setting an anchor to the topologies of neighboring genes.


[1] Bravo, I. G., & Alonso, Á. (2004). Mucosal human papillomaviruses encode four different E5 proteins whose chemistry and phylogeny correlate with malignant or benign growth. Journal of virology, 78, 13613-13626. doi: 10.1128/JVI.78.24.13613-13626.2004
[2] Werness, B. A., Levine, A. J., & Howley, P. M. (1990). Association of human papillomavirus types 16 and 18 E6 proteins with p53. Science, 248, 76-79. doi: 10.1126/science.2157286
[3] Dyson, N., Howley, P. M., Munger, K., & Harlow, E. D. (1989). The human papilloma virus-16 E7 oncoprotein is able to bind to the retinoblastoma gene product. Science, 243, 934-937. doi: 10.1126/science.2537532
[4] Willemsen, A., Félez-Sánchez, M., & Bravo, I. G. (2019). Genome plasticity in Papillomaviruses and de novo emergence of E5 oncogenes. bioRxiv, 337477, ver. 3 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/337477
[5] Theobald, D. L. (2010). A formal test of the theory of universal common ancestry. Nature, 465, 219–222. doi: 10.1038/nature09014
[6] Yonezawa, T., & Hasegawa, M. (2010). Was the universal common ancestry proved?. Nature, 468, E9. doi: 10.1038/nature09482
[7] Redelings, B. D., & Suchard, M. A. (2005). Joint Bayesian estimation of alignment and phylogeny. Systematic biology, 54(3), 401-418. doi: 10.1080/10635150590947041
[8] de Oliveira Martins, L., & Posada, D. (2014). Testing for universal common ancestry. Systematic biology, 63(5), 838-842. doi: 10.1093/sysbio/syu041
[9] Galtier, N., & Gouy, M. (1998). Inferring pattern and process: maximum-likelihood implementation of a nonhomogeneous model of DNA sequence evolution for phylogenetic analysis. Molecular biology and evolution, 15(7), 871-879. doi: 10.1093/oxfordjournals.molbev.a025991

05 Feb 2019
article picture

The quiescent X, the replicative Y and the Autosomes

Replication-independent mutations: a universal signature ?

Recommended by based on reviews by Marc Robinson-Rechavi and Robert Lanfear

Mutations are the primary source of genetic variation, and there is an obvious interest in characterizing and understanding the processes by which they appear. One particularly important question is the relative abundance, and nature, of replication-dependent and replication-independent mutations - the former arise as cells replicate due to DNA polymerization errors, whereas the latter are unrelated to the cell cycle. A recent experimental study in fission yeast identified a signature of mutations in quiescent (=non-replicating) cells: the spectrum of such mutations is characterized by an enrichment in insertions and deletions (indels) compared to point mutations, and an enrichment of deletions compared to insertions [2].
What Achaz et al. [1] report here is that the very same signature is detectable in humans. This time the approach is indirect and relies on two key aspects of mammalian reproduction biology: (1) oocytes remain quiescent over most of a female's lifespan, whereas spermatocytes keep dividing after male puberty, and (2) X chromosome, Y chromosome and autosomes spend different amounts of time in a female vs. male context. In agreement with the yeast study, Achaz et al. show that in humans the male-associated Y chromosome, for which quiescence is minimal, has by far the lowest ratios of indels to point mutations and of deletions to insertions, whereas the female-associated X chromosome has the highest. This is true both of variants that are polymorphic among humans and of fixed differences between humans and chimpanzees.
So we appear to be here learning about an important and general aspect of the mutation process. The authors suggest that, to a large extent, chromosomes tend to break in pieces at a rate that is proportional to absolute time - because indels in quiescent stage presumably result from double-strand DNA breaks. A very recent analysis of numerous mother-father-child trios in humans confirms this prediction in demonstrating an effect of maternal age, but not of paternal age, on the recombination rate [3]. This result also has important implications with respect to the interpretation of substitution rate variation among taxa and genomic compartments, particularly mitochondrial vs. nuclear, and their relationship with the generation time and longevity of organisms (e.g. [4]).


[1] Achaz, G., Gangloff, S., and Arcangioli, B. (2019). The quiescent X, the replicative Y and the Autosomes. BioRxiv, 351288, ver. 3 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/351288
[2] Gangloff, S., Achaz, G., Francesconi, S., Villain, A., Miled, S., Denis, C., and Arcangioli, B. (2017). Quiescence unveils a novel mutational force in fission yeast. eLife, 6:e27469. doi: 10.7554/eLife.27469
[3] Halldorsson, B. V., Palsson, G., Stefansson, O. A., Jonsson, H., Hardarson, M. T., Eggertsson, H. P., … Stefansson, K. (2019). Characterizing mutagenic effects of recombination through a sequence-level genetic map. Science, 363: eaau1043. doi: 10.1126/science.aau1043
[4] Saclier, N., François, C. M., Konecny-Dupré, L., Lartillot, N., Guéguen, L., Duret, L., … Lefébure, T. (2019). Life History Traits Impact the Nuclear Rate of Substitution but Not the Mitochondrial Rate in Isopods. Molecular Biology and Evolution, in press. doi: 10.1093/molbev/msy247

13 Jan 2019
article picture

Why cooperation is not running away

A nice twist on partner choice theory

Recommended by based on reviews by 2 anonymous reviewers

In this paper, Geoffroy et al. [1] deal with partner choice as a mechanism of maintaining cooperation, and argues that rather than being unequivocally a force towards improved payoffs to everyone through cooperation, partner choice can lead to “over-cooperation” where individuals can evolve to invest so much in cooperation that the costs of cooperating partially or fully negate the benefits from it. This happens when partner choice is consequential and effective, i.e., when interactions are long (so each decision to accept or reject a partner is a bigger stake) and when meeting new partners is frequent when unpaired (so that when one leaves an interaction one can find a new partner quickly). Geoffroy et al. [1] show that this tendency to select for overcooperation under such regimes can be counteracted if individuals base their acceptance-rejection of partners not just on the partner cooperativeness, but also on their own. By using tools from matching theory in economics, they show that plastic partner choice generates positive assortment between cooperativeness of the partners, and in the extreme case of perfectly assortative pairings, makes the pair the unit of selection, which selects for maximum total payoff.
This study is a nice contribution to the literature that illustrates potential complexities with partner choice as a mechanism for cooperation, including how the proximate mechanisms of partner choice can significantly alter the evolutionary trajectory of cooperation. Modeling choice as a reaction norm that depends on one’s own traits also adds a layer of realism to partner choice theory.
The authors are also to be commended for the revisions they made through the review process. Earlier versions of the model somewhat overstated the tendency for fixed partner choice strategies to lead to over cooperation, missing some of the important features in previous models, notably McNamara et al. [2] that can counter this tendency. In this version, the authors acknowledge these factors, mainly, mortality during partner choice (which increases the opportunity cost of forgoing a current partner) and also the fact that endogenous distribution of alternative partners (which will tend to be worse than the overall population distribution, because more cooperative types spend more time attached and less cooperative types more time unattached). These two factors can constrain cooperation from “running away” as the authors put it, but the main point of Geoffroy et al. [1] that plastic choice can create selection against inefficient cooperation stands.
I think the paper will be very stimulating to theoretical and empirical researchers working on partner choice and social behaviors, and happy to recommend it.


[1] Geoffroy, F., Baumard, N., & Andre, J.-B. (2019). Why cooperation is not running away. bioRxiv, ver. 5 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/316117
[2] McNamara, J. M., Barta, Z., Fromhage, L., & Houston, A. I. (2008). The coevolution of choosiness and cooperation. Nature, 451, 189–192. doi: 10.1038/nature06455

10 Jan 2019
article picture

Genomic data provides new insights on the demographic history and the extent of recent material transfers in Norway spruce

Disentangling the recent and ancient demographic history of European spruce species

Recommended by based on reviews by 1 anonymous reviewer

Genetic diversity in temperate and boreal forests tree species has been strongly affected by late Pleistocene climate oscillations [2,3,5], but also by anthropogenic forces. Particularly in Europe, where a long history of human intervention has re-distributed species and populations, it can be difficult to know if a given forest arose through natural regeneration and gene flow or through some combination of natural and human-mediated processes. This uncertainty can confound inferences of the causes and consequences of standing genetic variation, which may impact our interpretation of demographic events that shaped species before humans became dominant on the landscape. In their paper entitled "Genomic data provides new insights on the demographic history and the extent of recent material transfers in Norway spruce", Chen et al. [1] used a genome-wide dataset of 400k SNPs to infer the demographic history of Picea abies (Norway spruce), the most widespread and abundant spruce species in Europe, and to understand its evolutionary relationship with two other spruces (Picea obovata [Siberian spruce] and P. omorika [Serbian spruce]). Three major Norway spruce clusters were identified, corresponding to central Europe, Russia and the Baltics, and Scandinavia, which agrees with previous studies. The density of the SNP data in the present paper enabled inference of previously uncharacterized admixture between these groups, which corresponds to the timing of postglacial recolonization following the last glacial maximum (LGM). This suggests that multiple migration routes gave rise to the extant distribution of the species, and may explain why Chen et al.'s estimates of divergence times among these major Norway spruce groups were older (15mya) than those of previous studies (5-6mya) – those previous studies may have unknowingly included admixed material [4]. Treemix analysis also revealed extensive admixture between Norway and Siberian spruce over the last ~100k years, while the geographically-restricted Serbian spruce was both isolated from introgression and had a dramatically smaller effective population size (Ne) than either of the other two species. This small Ne resulted from a bottleneck associated with the onset of the iron age ~3000 years ago, which suggests that anthropogenic depletion of forest resources has severely impacted this species. Finally, ancestry of Norway spruce samples collected in Sweden and Denmark suggest their recent transfer from more southern areas of the species range. This northward movement of genotypes likely occurred because the trees performed well relative to local provenances, which is a common observation when trees from the south are planted in more northern locations (although at the potential cost of frost damage due to inappropriate phenology). While not the reason for the transfer, the incorporation of southern seed sources into the Swedish breeding and reforestation program may lead to more resilient forests under climate change. Taken together, the data and analysis presented in this paper allowed inference of the intra- and interspecific demographic histories of a tree species group at a very high resolution, and suggest caveats regarding sampling and interpretation of data from areas with a long history of occupancy by humans.


[1] Chen, J., Milesi, P., Jansson, G., Berlin, M., Karlsson, B., Aleksić, J. M., Vendramin, G. G., Lascoux, M. (2018). Genomic data provides new insights on the demographic history and the extent of recent material transfers in Norway spruce. BioRxiv, 402016. ver. 3 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/402016
[2] Holliday, J. A., Yuen, M., Ritland, K., & Aitken, S. N. (2010). Postglacial history of a widespread conifer produces inverse clines in selective neutrality tests. Molecular Ecology, 19(18), 3857–3864. doi: 10.1111/j.1365-294X.2010.04767.x
[3] Ingvarsson, P. K. (2008). Multilocus patterns of nucleotide polymorphism and the demographic history of Populus tremula. Genetics, 180, 329-340. doi: 10.1534/genetics.108.090431
[4] Lockwood, J. D., Aleksić, J. M., Zou, J., Wang, J., Liu, J., & Renner, S. S. (2013). A new phylogeny for the genus Picea from plastid, mitochondrial, and nuclear sequences. Molecular Phylogenetics and Evolution, 69(3), 717–727. doi: 10.1016/j.ympev.2013.07.004
[5] Pyhäjärvi, T., Garcia-Gil, M. R., Knürr, T., Mikkonen, M., Wachowiak, W., & Savolainen, O. (2007). Demographic history has influenced nucleotide diversity in European Pinus sylvestris populations. Genetics, 177(3), 1713–1724. doi: 10.1534/genetics.107.077099 "

02 Jan 2019
article picture

Leaps and bounds: geographical and ecological distance constrained the colonisation of the Afrotemperate by Erica

The colonization history of largely isolated habitats

Recommended by based on reviews by Simon Joly, Florian Boucher and 2 anonymous reviewers

The build-up of biodiversity is the result of in situ speciation and immigration, with the interplay between geographical distance and ecological suitability determining the probability of an organism to establish in a new area. The relative contribution of these factors have long interested biogeographers, in particular to explain the distribution of organisms adapted to habitats that remained largely isolated, such as the colonization of oceanic islands or land waters. The focus of this study is the formation of the afrotemperate flora; patches of temperate vegetation separated by thousands of kilometers in Africa, with high levels of endemism described in the Cape region, the Drakensberg range and the high mountains of tropical east Africa [1]. The floristic affinities between these centers of endemism have frequently been explored but the origin of many afrotemperate lineages remains enigmatic [2].
To identify the biogeographic history and drivers of biogeographic movements of the large afrotemperate genus Erica, the study of Pirie and colleagues [3] develops a robust hypothesis-testing approach relying on historical biogeographic models, phylogenetic and species occurrence data. Specifically, the authors test the directionality of migrations through Africa and address the general question on whether geographic proximity or climatic niche similarity constrained the colonization of the Afrotemperate by Erica. They found that the distribution of Erica species in Africa is the result of infrequent colonization events and that both geographic proximity and niche similarity limited geographic movements (with the model that incorporates both factors fitting the data better than null models). Unfortunately, the correlation between geographic and environmental distances found in this study limited the potential evaluation of their roles individually. They also found that species of Erica have dispersed from Europe to African regions, with the Drakensberg Mountains representing a colonization sink, rather than acting as a “stepping stone” between the Cape and Tropical African regions.
Advances in historical biogeography have been recently questioned by the difficulty to compare biogeographic models emphasizing long distance dispersal (DEC+J) versus vicariance (DEC) using statistical methods, such as AIC, as well as by questioning the own performance of DEC+J models [4]. Behind Pirie et al. main conclusions prevails the assumption that patterns of concerted long distance dispersal are more realistic than vicariance scenarios, such that a widespread afrotemperate flora that receded with climatic changes never existed. Pirie et al. do not explicitly test for this scenario based on the idea that these habitats remained largely isolated over time and our current knowledge on African paleoclimates and vegetation, emphasizing the value of arguments based on empirical (biological, geographic) considerations in model comparisons. I, however, appreciate from this study that the results of the biogeographic models emphasizing long distance dispersal, vicariance, and the unconstrained models are congruent with each other and presented together.
Pirie and colleagues [3] bring a nice study on the importance of long distance dispersal and biome shift in structuring the regional floras of Africa. They evidence outstanding examples of radiations in Erica resulting from single dispersal events over long distances and between ecologically dissimilar areas, which highlight the importance of niche evolution and biome shifts in the assembly of diversity. Although we still face important limitations in data availability and model realism, the last decade has witnessed an improvement of our understanding of how historical and environmental triggers are intertwined on shaping biological diversity. I found Pirie et al.’s approach (and analytical framework) very stimulating and hope that will help movement in that direction, providing interesting perspectives for future investigations of other regions.


[1] Linder, H.P. 1990. On the relationship between the vegetation and floras of the Afromontane and the Cape regions of Africa. Mitteilungen aus dem Institut für Allgemeine Botanik Hamburg 23b:777–790.
[2] Galley, C., Bytebier, B., Bellstedt, D. U., & Peter Linder, H. (2006). The Cape element in the Afrotemperate flora: from Cape to Cairo?. Proceedings of the Royal Society B: Biological Sciences, 274(1609), 535-543. doi: 10.1098/rspb.2006.0046
[3] Pirie, M. D., Kandziora, M., Nuerk, N. M., Le Maitre, N. C., de Kuppler, A. L. M., Gehrke, B., Oliver, E. G. H., & Bellstedt, D. U. (2018). Leaps and bounds: geographical and ecological distance constrained the colonisation of the Afrotemperate by Erica. bioRxiv, 290791. ver. 5 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/290791
[4] Ree, R. H., & Sanmartín, I. (2018). Conceptual and statistical problems with the DEC+ J model of founder‐event speciation and its comparison with DEC via model selection. Journal of Biogeography, 45(4), 741-749. doi: 10.1111/jbi.13173

13 Dec 2018
article picture

A behavior-manipulating virus relative as a source of adaptive genes for parasitoid wasps

Genetic intimacy of filamentous viruses and endoparasitoid wasps

Recommended by based on reviews by Alejandro Manzano-Marín and 1 anonymous reviewer

Viruses establish intimate relationships with the cells they infect. The virocell is a novel entity, different from the original host cell and beyond the mere combination of viral and cellular genetic material. In these close encounters, viral and cellular genomes often hybridise, combine, recombine, merge and excise. Such chemical promiscuity leaves genomics scars that can be passed on to descent, in the form of deletions or duplications and, importantly, insertions and back and forth exchange of genetic material between viruses and their hosts.
In this preprint [1], Di Giovanni and coworkers report the identification of 13 genes present in the extant genomes of members of the Leptopilina wasp genus, bearing sound signatures of having been horizontally acquired from an ancestral virus. Importantly the authors identify Leptopilina boulardi filamentous virus (LbFV) as an extant relative of the ancestral virus that served as donor for the thirteen horizontally transferred genes. While pinpointing genes with a likely possible viral origin in eukaryotic genomes is only relatively rare, identifying an extant viral lineage related to the ancestral virus that continues to infect an extant relative of the ancestral host is remarkable. But the amazing evolutionary history of the Leptopilina hosts and these filamentous viruses goes beyond this shared genes. These wasps are endoparasitoids of Drosophila larvae, the female wasp laying the eggs inside the larvae and simultaneously injecting venom that hinders the immune response. The composition of the venoms is complex, varies between wasp species and also between individuals within a species, but a central component of all these venoms are spiked structures that vary in morphology, symmetry and size, often referred to as virus-like particles (VLPs).
In this preprint, the authors convincingly show that the expression pattern in the Leptopilina wasps of the thirteen genes identified to have been horizontally acquired from the LbFV ancestor coincides with that of the production of VLPs in the female wasp venom gland. Based on this spatio-temporal match, the authors propose that these VLPs have a viral origin. The data presented in this preprint will undoubtedly stimulate further research on the composition, function, origin, evolution and diversity of these VLP structures, which are highly debated (see for instance [2] and [3]).


[1] Di Giovanni, D., Lepetit, D., Boulesteix, M., Ravallec, M., & Varaldi, J. (2018). A behavior-manipulating virus relative as a source of adaptive genes for parasitoid wasps. bioRxiv, 342758, ver. 5 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/342758
[2] Poirié, M., Colinet, D., & Gatti, J. L. (2014). Insights into function and evolution of parasitoid wasp venoms. Current Opinion in Insect Science, 6, 52-60. doi: 10.1016/j.cois.2014.10.004
[3] Heavner, M. E., Ramroop, J., Gueguen, G., Ramrattan, G., Dolios, G., Scarpati, M., ... & Govind, S. (2017). Novel organelles with elements of bacterial and eukaryotic secretion systems weaponize parasites of Drosophila. Current Biology, 27(18), 2869-2877. doi: 10.1016/j.cub.2017.08.019

13 Dec 2018
article picture

Separate the wheat from the chaff: genomic analysis of local adaptation in the red coral Corallium rubrum

Pros and Cons of local adaptation scans

Recommended by based on reviews by Lucas Gonçalves da Silva and 1 anonymous reviewer

The preprint by Pratlong et al. [1] is a well thought quest for genomic regions involved in local adaptation to depth in a species a red coral living the Mediterranean Sea. It first describes a pattern of structuration and then attempts to find candidate genes involved in local adaptation by contrasting deep with shallow populations. Although the pattern of structuration is clear and meaningful, the candidate genomic regions involved in local adaptation remain to be confirmed. Two external reviewers and myself found this preprint particularly interesting regarding the right-mindedness of the authors in front of the difficulties they encounter during their experiments. The discussions on the pros and cons of the approach are very sound and can be easily exported to a large number of studies that hunt for local adaptation. In this sense, the lessons one can learn by reading this well documented manuscript are certainly valuable for a wide range of evolutionary biologists.
More precisely, the authors RAD-sequenced 6 pairs of 'shallow vs deep' samples located in 3 geographical sea areas (Banyuls, Corsica and Marseilles). They were hoping to detect genes involved in the adaptation to depth, if there were any. They start by assessing the patterns of structuration of the 6 samples using PCA and AMOVA [2] and also applied the STRUCTURE [3] assignment software. They show clearly that the samples were mostly differentiated between geographical areas and that only 1 out the 3 areas shows a pattern of isolation by depth (i.e. Marseille). They nevertheless went on and scanned for variants that are highly differentiated in the deep samples when compared to the shallow paired samples in Marseilles, using an Fst outliers approach [4] implemented in the BayeScEnv software [5]. No clear functional signal was in the end detected among the highly differentiated SNPs, leaving a list of candidates begging for complementary data.
The scan for local adaptation using signatures of highly divergent regions is a classical problem of population genetics. It has been applied on many species with various degrees of success. This study is a beautiful example of a well-designed study that did not give full satisfactory answers. Readers will especially appreciate the honesty and the in-depth discussions of the authors while exposing their results and their conclusions step by step.


[1] Pratlong, M., Haguenauer, A., Brener, K., Mitta, G., Toulza, E., Garrabou, J., Bensoussan, N., Pontarotti P., & Aurelle, D. (2018). Separate the wheat from the chaff: genomic scan for local adaptation in the red coral Corallium rubrum. bioRxiv, 306456, ver. 3 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/306456
[2] Excoffier, L., Smouse, P. E. & Quattro, J. M. (1992). Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics, 131(2), 479-491.
[3] Pritchard, J. K., Stephens, M., & Donnelly, P. (2000). Inference of population structure using multilocus genotype data. Genetics, 155(2), 945-959.
[4] Lewontin, R. C., & Krakauer, J. (1973). Distribution of gene frequency as a test of the theory of the selective neutrality of polymorphisms. Genetics, 74(1), 175-195.
[5] de Villemereuil, P., & Gaggiotti, O. E. (2015). A new FST‐based method to uncover local adaptation using environmental variables. Methods in Ecology and Evolution, 6(11), 1248-1258. doi: 10.1111/2041-210X.12418

21 Nov 2018
article picture

Convergent evolution as an indicator for selection during acute HIV-1 infection

Is convergence an evidence for positive selection?

Recommended by based on reviews by Jeffrey Townsend and 1 anonymous reviewer

The preprint by Bertels et al. [1] reports an interesting application of the well-accepted idea that positively selected traits (here variants) can appear several times independently; think about the textbook examples of flight capacity. Hence, the authors assume that reciprocally convergence implies positive selection. The methodology becomes then, in principle, straightforward as one can simply count variants in independent datasets to detect convergent mutations.
In this preprint, the authors have applied this counting strategy on 95 available sequence alignments of the env gene of HIV-1 [2,3] that corresponds to samples taken in different patients during the early phase of infection, at the very beginning of the onset of the immune system. They have compared the number and nature of the convergent mutations to a "neutral" model that assumes (a) a uniform distribution of mutations and (b) a substitution matrix estimated from the data. They show that there is an excess of convergent mutations when compared to the “neutral” expectations, especially for mutations that have arisen in 4+ patients. They also show that the gp41 gene is enriched in these convergent mutations. The authors then discuss in length the potential artifacts that could have given rise to the observed pattern.
I think that this preprint is remarkable in the proposed methodology. Samples are taken in different individuals, whose viral populations were founded by a single particle. Thus, there is no need for phylogenetic reconstruction of ancestral states that is the typical first step of trait convergent analyses. It simply becomes counting variants. This simple counting procedure needs nonetheless to be compared to a “neutral” expectation (a reference model), which includes the mutational process. In this article, the poor predictions of a specifically designed reference model is interpreted as an evidence for positive selection.
Whether the few mutations that are convergent in 4-7 samples out of 95 were selected or not is hard to assess with certainty. The authors have provided good evidence that they are, but only experimental validations will strengthen the claim. Nonetheless, beyond a definitive clue to the implication of selection on these particular mutations, I found the methodological strategy and the discussions on the potential biases highly stimulating. This article is an excellent starting point for further methodological developments that could be then followed by large-scale analyses of convergence in many different organisms and case studies.


[1] Bertels, F., Metzner, K. J., & Regoes R. R. (2018). Convergent evolution as an indicator for selection during acute HIV-1 infection. BioRxiv, 168260, ver. 4 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/168260
[2] Keele, B. F., Giorgi, E. E., Salazar-Gonzalez, J. F., Decker, J. M., Pham, K.T., Salazar, M. G., Sun, C., Grayson, T., Wang, S., Li, H. et al. (2008). Identification and characterization of transmitted and early founder virus envelopes in primary HIV-1 infection. Proc Natl Acad Sci USA 105: 7552–7557. doi: 10.1073/pnas.0802203105
[3] Li, H., Bar, K. J., Wang, S., Decker, J. M., Chen, Y., Sun, C., Salazar-Gonzalez, J.F., Salazar, M.G., Learn, G.H., Morgan, C. J. et al. (2010). High multiplicity infection by HIV-1 in men who have sex with men. PLoS Pathogens 6:e1000890. doi: 10.1371/journal.ppat.1000890

16 Nov 2018
article picture

Fine-grained habitat-associated genetic connectivity in an admixed population of mussels in the small isolated Kerguelen Islands

Introgression from related species reveals fine-scale structure in an isolated population of mussels and causes patterns of genetic-environment associations

Recommended by based on reviews by Thomas Broquet and Tatiana Giraud

Assessing population connectivity is central to understanding population dynamics, and is therefore of great importance in evolutionary biology and conservation biology. In the marine realm, the apparent absence of physical barriers, large population sizes and high dispersal capacities of most organisms often result in no detectable structure, thereby hindering inferences of population connectivity. In a review paper, Gagnaire et al. [1] propose several ideas to improve detection of population connectivity. Notably, using simulations they show that under certain circumstances introgression from one species into another may reveal cryptic population structure within that second species.
The isolated Kerguelen archipelago in the south of Indian Ocean represents a typical situation where the structure of coastal marine organisms is expected to be difficult to detect. In an elegant genomic study, Fraïsse et al. [2] take advantage of introgression from foreign lineages to infer fine-grained population structure in a population of mussels around the Kerguelen archipelago, and investigate its association with environmental variables. Using a large panel of genome-wide markers (GBS) and applying a range of methods that unravel patterns of divergence and gene flow among lineages, they first find that the Kerguelen population is highly admixed, with a major genetic background corresponding to the southern mussel lineage Mytilus platensis introgressed by three northern lineages. By selecting a panel of loci enriched in ancestry-informative SNPs (ie, SNPs highly differentiated among northern lineages) they then detect a fine-scale genetic structure around the Kerguelen archipelago, and identify a major connectivity break. They further show an associating between the genetic structure and environmental variables, particularly the presence of Macrocystis kelp, a marker of habitat exposure to waves (a feature repeatedly evidenced to be important for mussels). While such association pattern could lead to the interpretation that differentiated SNPs correspond to loci directly under selection or linked with such loci, and even be considered as support for adaptive introgression, Fraïsse et al. [2] convincingly show by performing simulations that the genetic-environment association detected can be entirely explained by dispersal barriers associated with environmental variables (habitat-associated connectivity). They also explain why the association is better detected by ancestry-informative SNPs as predicted by Gagnaire et al. [1]. In addition, intrinsic genetic incompatibilities, which reduce gene flow, tend to become trapped at ecotones due to ecological selection, even when loci causing genetic incompatibilities are unlinked with loci involved in adaption to local ecological conditions (Bierne et al. [3]’s coupling hypothesis), leading to correlations between environmental variables and loci not involved in local adaptation. Notably, in Fraïsse et al. [2]’s study, the association between the kelp and ancestry-informative alleles is not consistent throughout the archipelago, casting further doubt on the implication of these alleles in local adaptation.
The study of Fraïsse et al. [2] is therefore an important contribution to evolutionary biology because 1) it provides an empirical demonstration that alleles of foreign origin can be pivotal to detect fine-scale connectivity patterns and 2) it represents a test case of Bierne et al. [3]’s coupling hypothesis, whereby introgressed alleles also enhance patterns of genetic-environment associations. Since genomic scan or GWAS approaches fail to clearly reveal loci involved in local adaptation, how can we disentangle environment-driven selection from intrinsic reproductive barriers and habitat-associated connectivity? A related question is whether we can reliably identify cases of adaptive introgression, which have increasingly been put forward as a mechanism involved in adaptation [4]. Unfortunately, there is no easy answer, and the safest way to go is to rely – where possible – on independent information [5], in particular functional studies of the detected loci, as is for example the case in the mimetic butterfly Heliconius literature (e. g., [6]) where several loci controlling colour pattern variation are well characterized.


[1] Gagnaire, P.-A., Broquet, T., Aurelle, D., Viard, F., Souissi, A., Bonhomme, F., Arnaud-Haond, S., & Bierne, N. (2015). Using neutral, selected, and hitchhiker loci to assess connectivity of marine populations in the genomic era. Evolutionary Applications, 8, 769–786. doi: 10.1111/eva.12288
[2] Fraïsse, C., Haguenauer, A., Gerard, K., Weber, A. A.-T., Bierne, N., & Chenuil, A. (2018). Fine-grained habitat-associated genetic connectivity in an admixed population of mussels in the small isolated Kerguelen Islands. bioRxiv, 239244, ver. 4 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/239244
[3] Bierne, N., Welch, J., Loire, E., Bonhomme, F., & David, P. (2011). The coupling hypothesis: why genome scans may fail to map local adaptation genes. Molecular Ecology, 20, 2044–2072. doi: 10.1111/j.1365-294X.2011.05080.x
[4] Hedrick, P. W. (2013). Adaptive introgression in animals: examples and comparison to new mutation and standing variation as sources of adaptive variation. Molecular Ecology, 22, 4606–4618. doi: 10.1111/mec.12415
[5] Ravinet, M., Faria, R., Butlin, R. K., Galindo, J., Bierne, N., Rafajlović, M., Noor, M. A. F., Mehlig, B., & Westram, A. M. (2017). Interpreting the genomic landscape of speciation: a road map for finding barriers to gene flow. Journal of Evolutionary Biology, 30, 1450–1477. doi: 10.1111/jeb.13047.
[6] Jay, P., Whibley, A., Frézal, L., Rodríguez de Cara, M. A., Nowell, R. W., Mallet, J., Dasmahapatra, K. K., & Joron, M. (2018). Supergene evolution triggered by the introgression of a chromosomal inversion. Current Biology, 28, 1839–1845.e3. doi: 10.1016/j.cub.2018.04.072

09 Nov 2018
article picture

Field evidence for manipulation of mosquito host selection by the human malaria parasite, Plasmodium falciparum

Malaria host manipulation increases probability of mosquitoes feeding on humans

Recommended by based on reviews by Olivier Restif, Ricardo S. Ramiro and 1 anonymous reviewer

Parasites can manipulate their host’s behaviour to ensure their own transmission. These manipulated behaviours may be outside the range of ordinary host activities [1], or alter the crucial timing and/or location of a host’s regular activity. Vantaux et al show that the latter is true for the human malaria parasite, Plasmodium falciparum [2]. They demonstrate that three species of Anopheles mosquito were 24% more likely to choose human hosts, rather than other vertebrates, for their blood feed when they harboured transmissible stages (sporozoites) compared to when they were uninfected, or infected with non-transmissible malaria parasites [2]. Host choice is crucial for the malaria parasite Plasmodium falciparum to complete its life-cycle, as their host range is much narrower than the mosquito’s for feeding; P. falciparum can only develop in hominids, or closely related apes [3].
The study only shows this stage-dependent parasite manipulation retrospectively (by identifying host type and parasite stage in mosquitoes after their blood feed [2]). There was no difference in the preferences of infectious (with sporozoites) or un-infectious (infected without sporozoites, or uninfected) mosquitoes between human versus cow hosts in a choice test [2]. This suggests that the final decision about whether to feed occurs when the mosquito is in close range of the host.
This, coupled with previous findings, shows that vector manipulation is a fine-tuned business, that can act at multiple stages of the parasite life-cycle and on many behaviours [4]. Indeed, mosquitoes with non-transmissible Plasmodium stages (oocysts) are more reluctant to feed than sporozoite-infected mosquitoes [5] as vectors can be killed by their host whilst feeding, doing so before they are ready to transmit is risky for the malaria parasite. Thus, it seems that Plasmodium is, to some extent, master of its vector; commanding it not to feed when it cannot be transmitted, to feed when it is ready to be transmitted and to feed on the right type of host. What does this mean for our understanding of malaria transmission and epidemics?
Vantaux et al use a mathematical model, parameterised using data from this experiment, to highlight the consequences of this 24% increase in feeding on humans for P. falciparum transmission. They show that this increase raises the number of infectious bites humans receive from 4 (if sporozoite-infected mosquitoes had the same probability as uninfected mosquitoes) to 14 (an increase in 250%), for mosquitoes with a 15-day life-span, at ratios of 1:1 mosquitoes to humans. Longer mosquito life-spans and higher ratios of mosquitoes to humans further increases the number of infectious bites.
These results [2] have important implications for epidemiological forecasting and disease management. Public health strategies could focus on possible ways to trap sporozoite-infected mosquitoes, mimicking cues they use to locate their human hosts, or identify the behaviour of mosquitoes harbouring non-yet infectious Plasmodium, and trap them before they bite. Moreover, the results of the model show that failing to take into account the preference for humans of sporozoite-infected mosquitoes could underestimate the size of pending epidemics.
An important question previously raised is whether Plasmodium-induced alteration in host behaviour really is manipulation, or just a side-effect of being infected [4,5]. The fact that Vantaux et al show that these altered feeding behaviours increases the likelihood of transmission, in that a sporozoite-infected mosquito is more likely to feed on a human, strongly suggests that it is adaptive for the parasite [2]. Ultimately, to show that it is manipulation would require the identification of molecular factors released by Plasmodium that are responsible for physiological changes in the mosquito [6].


[1] Thomas, F., Schmidt-Rhaesa, A., Martin, G., Manu, C., Durand, P., & Renaud, F. (2002). Do hairworms (Nematomorpha) manipulate the water seeking behaviour of their terrestrial hosts? Journal of Evolutionary Biology, 15(3), 356–361. doi: 10.1046/j.1420-9101.2002.00410.x
[2] Vantaux, A., Yao, F., Hien, D. F., Guissou, E., Yameogo, B. K., Gouagna, L.-C., … Lefevre, T. (2018). Field evidence for manipulation of mosquito host selection by the human malaria parasite, Plasmodium falciparum. BioRxiv, 207183 ver 6. doi: 10.1101/207183
[3] Prugnolle, F., Durand, P., Ollomo, B., Duval, L., Ariey, F., Arnathau, C., … Renaud, F. (2011). A Fresh Look at the Origin of Plasmodium falciparum, the Most Malignant Malaria Agent. PLOS Pathogens, 7(2), e1001283. doi: 10.1371/journal.ppat.1001283
[4] Cator, L. J., Lynch, P. A., Read, A. F., & Thomas, M. B. (2012). Do malaria parasites manipulate mosquitoes? Trends in Parasitology, 28(11), 466–470. doi: 10.1016/
[5] Cator, L. J., George, J., Blanford, S., Murdock, C. C., Baker, T. C., Read, A. F., & Thomas, M. B. (2013). “Manipulation” without the parasite: altered feeding behaviour of mosquitoes is not dependent on infection with malaria parasites. Proceedings. Biological Sciences, 280(1763), 20130711. doi: 10.1098/rspb.2013.0711
[6] Herbison, R., Lagrue, C., & Poulin, R. (2018). The missing link in parasite manipulation of host behaviour. Parasites & Vectors, 11. doi: 10.1186/s13071-018-2805-9

03 Oct 2018
article picture

Range size dynamics can explain why evolutionarily age and diversification rate correlate with contemporary extinction risk in plants

Are both very young and the very old plant lineages at heightened risk of extinction?

Recommended by based on reviews by Dan Greenberg and 1 anonymous reviewer

Human economic activity is responsible for the vast majority of ongoing extinction, but that does not mean lineages are being affected willy-nilly. For amphibians [1] and South African flowering plants [2], young species have a somewhat higher than expected chance of being threatened with extinction. In contrast, older Australian marsupial lineages seem to be more at risk [3]. Both of the former studies suggested that situations leading to peripheral isolation might simultaneously increase ongoing speciation and current threat via small geographic range, while the authors of the latter study suggested that older species might have evolved increasingly narrow niches. Here, Andrew Tanentzap and colleagues [4] dig deeper into the putative links between species age, niche breadth and threat status. Across 500-some plant genera worldwide, they find that, indeed, ""younger"" species (i.e. from younger and faster-diversifying genera) were more likely to be listed as imperiled by the IUCN, consistent with patterns for amphibians and African plants. Given this, results from their finer-level analyses of conifers are initially bemusing: here, ""older"" (i.e., on longer terminal branches) species were at higher risk. This would make conifers more like Australian marsupials, with the rest of the plants being more like amphibians. However, here where the data were more finely grained, the authors detected a second interesting pattern: using an intriguing matched-pair design, they detect a signal of conifer species niches seemingly shrinking as a function of age. The authors interpret this as consistent with increasing specialization, or loss of ancestral warm wet habitat, over paleontological time. It is true that conifers in general are older than plants more generally, with some species on branches that extend back many 10s of millions of years, and so a general loss of suitable habitat makes some sense. If so, both the pattern for all plants (small initial ranges heightening extinction) and the pattern for conifers (eventual increasing specialization or habitat contraction heightening extinction) could occur, each on a different time scale. As a coda, the authors detected no effect of age on threat status in palms; however, this may be both because palms have already lost species to climate-change induced extinction, and because they are thought to speciate more via long-distance dispersal and adaptive divergence then via peripheral isolation.
Given how quickly ranges can change, how hard it is to measure niche breadth, and the qualitatively different time scales governing past diversification and present-day extinction drivers, this is surely not the last word on the subject, even for plants. However, even the hint of a link between drivers of extinction in the Anthropocene and drivers of diversification through the ages is intellectually exciting and, perhaps, even, somehow, of practical importance.


[1] Greenberg, D. A., & Mooers, A. Ø. (2017). Linking speciation to extinction: Diversification raises contemporary extinction risk in amphibians. Evolution Letters, 1, 40–48. doi: 10.1002/evl3.4
[2] Davies, T. J., Smith, G. F., Bellstedt, D. U., Boatwright, J. S., Bytebier, B., Cowling, R. M., Forest, F., et al. (2011). Extinction risk and diversification are linked in a plant biodiversity hotspot. PLoS Biology, 9:e1000620. doi: 10.1371/journal.pbio.1000620
[3] Johnson, C. N., Delean S., & Balmford, A. (2002). Phylogeny and the selectivity of extinction in Australian marsupials. Animal Conservation, 5, 135–142. doi: 10.1017/S1367943002002196
[4] Tanentzap, A. J., Igea, J., Johnston, M. G., & Larcombe, M. G. (2018). Range size dynamics can explain why evolutionarily age and diversification rate correlate with contemporary extinction risk in plants. bioRxiv, 152215, ver. 5 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/152215

07 Sep 2018
article picture

Parallel pattern of differentiation at a genomic island shared between clinal and mosaic hybrid zones in a complex of cryptic seahorse lineages

Genomic parallelism in adaptation to orthogonal environments in sea horses

Recommended by based on reviews by 2 anonymous reviewers

Studies in speciation genomics have revealed that gene flow is quite common, and that despite this, species can maintain their distinct environmental adaptations. Although researchers are still elucidating the genomic mechanisms by which species maintain their adaptations in the face of gene flow, this often appears to involve few diverged genomic regions in otherwise largely undifferentiated genomes. In this preprint [1], Riquet and colleagues investigate the genetic structuring and patterns of parallel evolution in the long-snouted seahorse.
Before investigating specific SNPs plausibly associated with adaptation, the authors first describe genome-wide population structure in the long-snouted seahorse. This species is split into five phenotypically similar, but genetically distinct populations. Two populations reside in the Atlantic Ocean and are geographically structured with one north of the Iberian peninsula and the other around the Iberian peninsula. Two other populations are found in the Mediterranean Sea and are structured by the environment as they correspond to marine and lagoon environments. The genetic clustering of lagoon populations in the Mediterranean, despite the substantial geographic distance between them is quite impressive, and worthy of further study. Finally, a fifth population resides in a lagoon-like habitat in the Black Sea.
The authors then investigate patterns of extreme genomic differentiation among populations, and uncover a remarkable pattern of parallel differentiation in these populations. In an outlier scan, Riquet and colleagues find numerous SNPs in one genomic region that separates northern and southern Atlantic populations. Quiet surprisingly, this same genomic region appears to differentiate populations living in marine and lagoon habitats in the Mediterranean. The idea that parallel patterns of genomic differentiation may underlie adaptation to differing environmental scenarios has not yet received much attention. This paper should change that. This paper is particularity impressive in that the authors uncovered this intriguing pattern with under three hundred SNPs. Future genome scale studies will uncover the genomic basis behind this unusual case of parallelism.


[1] Riquet, F., Liautard-Haag, C., Woodall, L., Bouza, C., Louisy, P., Hamer, B., Otero-Ferrer, F., Aublanc, P., Béduneau, V., Briard, O., El Ayari, T., Hochscheid, S. Belkhir, K., Arnaud-Haond, S., Gagnaire, P.-A., Bierne, N. (2018). Parallel pattern of differentiation at a genomic island shared between clinal and mosaic hybrid zones in a complex of cryptic seahorse lineages. bioRxiv, 161786, ver. 4 recommended and peer-reviewed by PCI Evol Biol. doi: 10.1101/161786

08 Aug 2018
article picture

Sexual selection and inbreeding: two efficient ways to limit the accumulation of deleterious mutations

Inbreeding compensates for reduced sexual selection in purging deleterious mutations

Recommended by based on reviews by 2 anonymous reviewers

Two evolutionary processes have been shown in theory to enhance the effects of natural selection in purging deleterious mutations from a population (here ""natural"" selection is defined as ""selection other than sexual selection""). First, inbreeding, especially self-fertilization, facilitates the removal of deleterious recessive alleles, the effects of which are largely hidden from selection in heterozygotes when mating is random. Second, sexual selection can facilitate the removal of deleterious alleles of arbitrary dominance, with little or no demographic cost, provided that deleterious effects are greater in males than in females (""genic capture""). Inbreeding (especially selfing) and sexual selection are often negatively correlated in nature. Empirical tests of the role of sexual selection in purging deleterious mutations have been inconsistent, potentially due to the positive relationship between sexual selection and intersexual genetic conflict.
In their preprint, Noël et al. [1] report a cleverly designed, and impressively long-term, experimental evolution study designed to tease apart the relative contributions of selfing and sexual selection in purging deleterious mutations, using the self-compatible hermaphroditic snail Physa acuta. Hermaphroditism relieves at least some of the potential conflict between males and females because each individual expresses traits of each sex. The authors report a 50-generation (ten years!) evolution experiment with four experimental treatments: Control (C), in which snails reproduced by mass mating (allowing sexual selection) and the next generation was sampled randomly from offspring in proportion to maternal family size; Male-selection (M) in which snails reproduced by mass mating but maternal family size was held constant, removing the opportunity for fertility selection; Female fertility selection (F) in which snails mated monogamously but fertility selection was imposed, and selfing (S), in which snails reproduced by selfing every other generation, alternating with monogamy + fertility selection. Juvenile survival was taken as the proxy for fitness and was measured for offspring of self-fertilization and of outcross matings. Each line type (C, M, F, S) was replicated twice.
The results are enviably clear-cut: after 50 generations of evolution, outcross fitness dropped precipitously in the F treatment (monogamy+female fertility selection) and remained at ancestral levels in the other three treatments. Clearly, sexual selection in males is more efficient at purging deleterious alleles than is female fertility selection. Similarly, inbreeding depression was reduced in the S lines relative to the other treatments, indicating that, unsurprisingly, deleterious recessive mutations of large effect are purged under strong inbreeding. Outcross fitness in the S lines did not decline, in contrast to the F lines, which indicates that deleterious mutations are on average slightly recessive.
Taken as a whole, this study by Noël et al. [1] provides a compelling empirical demonstration of the efficacy of both sexual selection and strong inbreeding as mechanisms of purging, and implicates sexual conflict as a potentially important factor in studies in which relaxation of sexual selection fails to result in purging.


[1] Noël, E., Fruitet, E., Lelaurin, D., Bonel, N., Segard, A., Sarda, V., Jarne, P., & David P. (2018). Sexual selection and inbreeding: two efficient ways to limit the accumulation of deleterious mutations. bioRxiv, 273367, ver. 3 recommended and peer-reviewed by PCI Evol Biol. doi: 10.1101/273367

06 Jul 2018
article picture

Variation in competitive ability with mating system, ploidy and range expansion in four Capsella species

When ecology meets genetics: Towards an integrated understanding of mating system transitions and diversity

Recommended by and based on reviews by Yaniv Brandvain, Henrique Teotonio and 1 anonymous reviewer

In the 19th century, C. Darwin and F. Delpino engaged in a debate about the success of species with different reproduction modes, with the later favouring the idea that monoecious plants capable of autonomous selfing could spread more easily than dioecious plants (or self-incompatible hermaphroditic plants) if cross-pollination opportunities were limited [1]. Since then, debate has never faded about how natural selection is responsible for transitions to selfing and can explain the diversity and distribution of reproduction modes we observe in the natural world [2, 3].
Explanations for mating systems diversity, and transitions to selfing in particular, generally fall into two categories: either genetic or ecological. On the genetic side, many theoretical works showed a critical role for mutation load and inbreeding depression, transmission advantage and reproductive assurance in the evolution of selfing, e.g. [4]. Many experimental works were conducted to test theoretical hypotheses and predictions, especially regarding the magnitude of inbreeding depression; see [5] for a review. Ecologically, the presence of selfing populations is usually correlated with fragmented and harsh habitats, on the periphery of ancestral outcrossing populations. The cause of this distribution could be that selfers are better dispersers and colonizers than outcrossers, or variations in other life-history traits [6]. Yet, few experiments were run to assess whether selfing species or populations have effectively different ecological characteristics, and even scarcer are experiments evaluating both the roles of mutational load and life-history traits evolution. This is the aim of the present study by X. Yang et al [7].
The study of Yang et al [7], together with that of Petrone Mendoza et al. [8], supervised by S. Glémin and M. Lascoux, is probably one of the first to conduct experiments where the competitive abilities are compared between and within species. Using 4 species of the Capsella genus, annual plants from the mustard family, they tested the theoretical predictions that i) the transition from outcrossing to selfing resulted in reduced competitive ability at higher densities, because of the accumulation of deleterious mutations and/or the evolution of life-history traits in an open habitat and a colonization/dispersal trade-off; ii) that reduced competitive ability of selfers should be less pronounced in polyploid then diploid species because the effect of partially recessive deleterious mutations would be buffered; and iii) that competitive ability of selfers should decline with historical range expansion because of the expansion load [9].
Of the 4 Capsella species studied, only one of them, presumably the ancestral, is a diploid outcrosser with a small distribution but large population sizes. The three other species are selfers, two diploids with independent histories of transitions from outcrossing, and another, tetraploid, resulting from a recent hybridization between one of the diploid selfer and the diploid outcrossing ancestor. Many accessions from each species were sampled and individuals assayed for their competitive ability against a tester species or alone, for vegetative and reproductive traits. The measured vegetative traits (rosette surface at two stages, growth rate and flowering probability) showed no differentiation between selfers and outcrossers. To the contrary, reproductive traits (number of flowers) followed theoretical predictions: selfing species are more sensitive to competition than the outcrossing species, with polyploid selfing species being intermediate between the diploid selfers and the diploid outcrosser, and within the tetraploid selfing species (where sampling was quite significant across a large geographical range) sensitivity to competition increased with range expansion.
The study of Yang et al. [7] suffers from several limitations, such that alternative explanations cannot be discarded in the absence of further experimental data. They nonetheless provide the reader with a nice discussion and prospects on how to untwine the causes and the consequences of transitions to selfing. Their study also brings up to date questions about the joint evolution of mating system and life-history traits, which needs a renewed interest from an empirical and theoretical point of view. The results of Yang et al. raise for instance the question of whether it is indeed expected that only reproductive traits, and not vegetative traits, should evolve with the transition to selfing.
The recommandation and evaluation of this paper have been made in collaboration with Thomas Lesaffre.


[1] Darwin, C. R. (1876). The effects of cross and self fertilization in the vegetable kingdom. London: Murray. [2] Stebbins, G. L. (1957). Self fertilization and population variability in the higher plants. The American Naturalist, 91, 337-354. doi: 10.1086/281999
[3] Harder, L.D. & Barrett, S. C. H. (2006). Ecology and evolution of flowers. Oxford: Oxford University Press. [4] Porcher, E. & Lande, R. (2005). The evolution of self-fertilization and inbreeding depression under pollen discounting and pollen limitation. Journal of Evolutionary Biology, 18(3), 497-508. doi: 10.1111/j.1420-9101.2005.00905.x
[5] Winn, A.A., et al. (2011). Analysis of inbreeding depression in mixed-mating plants provides evidence for selective interference and stable mixed mating. Evolution, 65(12), 3339-3359. doi: 10.1111/j.1558-5646.2011.01462.x
[6] Munoz, F., Violle, C. & Cheptou, P.-O. (2016). CSR ecological strategies and plant mating systems: outcrossing increases with competitiveness but stress-tolerance is related to mixed mating. Oikos, 125(9), 1296-1303. doi: 10.1111/oik.02328
[7] Yang, X., Lascoux, M. & Glémin, S (2018). Variation in competitive ability with mating system, ploidy and range expansion in four Capsella species. bioRxiv, 214866, ver. 5 recommended and peer-reviewed by PCI Evol Biol. doi: 10.1101/214866
[8] Petrone Mendoza, S., Lascoux, M. & Glémin, S. (2018). Competitive ability of Capsella species with different mating systems and ploidy levels. Annals of Botany 121(6), 1257-1264. doi: 10.1093/aob/mcy014
[9] Peischl, S. & Excoffier, L. (2015). Expansion load: recessive mutations and the role of standing genetic variation. Molecular Ecology, 24(9): 2084-2094. doi: 10.1111/mec.13154

12 Jun 2018
article picture

Transgenerational cues about local mate competition affect offspring sex ratios in the spider mite Tetranychus urticae

Maternal effects in sex-ratio adjustment

Recommended by based on reviews by 2 anonymous reviewers

Optimal sex ratios have been topic of extensive studies so far. Fisherian 1:1 proportions of males and females are known to be optimal in most (diploid) organisms, but many deviations from this golden rule are observed. These deviations not only attract a lot of attention from evolutionary biologists but also from population ecologists as they eventually determine long-term population growth. Because sex ratios are tightly linked to fitness, they can be under strong selection or plastic in response to changing demographic conditions. Hamilton [1] pointed out that an equality of the sex ratio breaks down when there is local competition for mates. Competition for mates can be considered as a special case of local resource competition. In short, this theory predicts females to adjust their offspring sex ratio conditional on cues indicating the level of local mate competition that their sons will experience. When cues indicate high levels of LMC mothers should invest more resources in the production of daughters to maximise their fitness, while offspring sex ratios should be closer to 50:50 when cues indicate low levels of LMC.
In isolated populations, Macke et al. [2] found sex ratio to evolve fast in response to changes in population sex-structure in the spider mite Tetranychus urticae. Spider mites are becoming top-models in evolutionary biology because of their easy housekeeping, fast generation times and well-studied genome [3]. The species is known to respond fast to changes in relatedness and kin-structure by changing its mating strategy [4], but also dispersal [5]. Sex ratio adjustments are likely mediated by differential investments in egg size, with small eggs possibly experiencing lower chances of fertilization, and thus to develop in haploid males [4].
Alison Duncan and colleagues [6] asked the question whether sex ratios change plastically in response to changes in the local population structure. They additionally questioned whether maternal effects could drive changes in sex-allocation of spider mite mothers. Indeed, theory predicts that if environmental changes are predictable across generations, intergenerational plasticity might be more adaptive than intragenerational plasticity [7]. Especially in spatially structured and highly dynamics populations, female spider mites may experience highly variable demographic conditions from one generation to another. During range expansions, spatial variation in local relatedness and inbreeding are documented to change and to impact eco-evolutionary trajectories as well (e.g. [8]).
Duncan et al. [6] specifically investigate whether the offspring sex ratio of T. urticae females changes in response to 1) the current number of females in the same patch, 2) the number of females in the patches of their mothers and 3) their relatedness to their mate. They surprisingly find the maternal environment to be more important than the actual experienced sex-ratio conditions. These insights thus show the maternal environment to be a reliable predictor of LMC experienced by grand-children. Maternal effects have been found to impact many traits, but this study is the first to convincingly demonstrate maternal effects in sex allocation. It therefore provides an alternative explanation of the apparent fast evolved responses under constant demographic conditions [2], and adds evidence to the importance of non-genetic trait changes for adaptation towards changing demographic and environmental conditions.


[1] Hamilton, W. D. (1967). Extraordinary Sex Ratios. Science, 156(3774), 477–488. doi: 10.1126/science.156.3774.477
[2] Macke, E., Magalhães, S., Bach, F., & Olivieri, I. (2011). Experimental evolution of reduced sex ratio adjustment under local mate competition. Science, 334(6059), 1127–1129. doi: 10.1126/science.1212177
[3] Grbić, M., Van Leeuwen, T., Clark, R. M., et al. (2011). The genome of Tetranychus urticae reveals herbivorous pest adaptations. Nature, 479(7374), 487–492. doi: 10.1038/nature10640
[4] Macke, E., Magalhães, S., Bach, F., & Olivieri, I. (2012). Sex-ratio adjustment in response to local mate competition is achieved through an alteration of egg size in a haplodiploid spider mite. Proceedings of the Royal Society B: Biological Sciences, 279(1747), 4634–4642. doi: 10.1098/rspb.2012.1598
[5] Bitume, E. V., Bonte, D., Ronce, O., Bach, F., Flaven, E., Olivieri, I., & Nieberding, C. M. (2013). Density and genetic relatedness increase dispersal distance in a subsocial organism. Ecology Letters, 16(4), 430–437. doi: 10.1111/ele.12057
[6] Duncan, A., Marinosci, C., Devaux, C., Lefèvre, S., Magalhães, S., Griffin, J., Valente, A., Ronce, O., Olivieri, I. (2018). Transgenerational cues about local mate competition affect offspring sex ratios in the spider mite Tetranychus urticae. BioRxiv, 240127, ver. 3. doi: 10.1101/240127
[7] Petegem, K. V., Moerman, F., Dahirel, M., Fronhofer, E. A., Vandegehuchte, M. L., Leeuwen, T. V., Wybouw, N., Stoks, R., Bonte, D. (2018). Kin competition accelerates experimental range expansion in an arthropod herbivore. Ecology Letters, 21(2), 225–234. doi: 10.1111/ele.12887
[8] Marshall, D. J., & Uller, T. (2007). When is a maternal effect adaptive? Oikos, 116(12), 1957–1963. doi: 10.1111/j.2007.0030-1299.16203.x

05 Jun 2018
article picture

Pleistocene climate change and the formation of regional species pools

Recent assembly of European biogeographic species pool

Recommended by based on reviews by 3 anonymous reviewers

Biodiversity is unevenly distributed over time, space and the tree of life [1]. The fact that regions are richer than others as exemplified by the latitudinal diversity gradient has fascinated biologists as early as the first explorers travelled around the world [2]. Provincialism was one of the first general features of land biotic distributions noted by famous nineteenth century biologists like the phytogeographers J.D. Hooker and A. de Candolle, and the zoogeographers P.L. Sclater and A.R. Wallace [3]. When these explorers travelled among different places, they were struck by the differences in their biotas (e.g. [4]). The limited distributions of distinctive endemic forms suggested a history of local origin and constrained dispersal. Much biogeographic research has been devoted to identifying areas where groups of organisms originated and began their initial diversification [3]. Complementary efforts found evidence of both historical barriers that blocked the exchange of organisms between adjacent regions and historical corridors that allowed dispersal between currently isolated regions. The result has been a division of the Earth into a hierarchy of regions reflecting patterns of faunal and floral similarities (e.g. regions, subregions, provinces). Therefore a first ensuing question is: “how regional species pools have been assembled through time and space?”, which can be followed by a second question: “what are the ecological and evolutionary processes leading to differences in species richness among species pools?”.

To address these questions, the study of Calatayud et al. [5] developed and performed an interesting approach relying on phylogenetic data to identify regional and sub-regional pools of European beetles (using the iconic ground beetle genus Carabus). Specifically, they analysed the processes responsible for the assembly of species pools, by comparing the effects of dispersal barriers, niche similarities and phylogenetic history. They found that Europe could be divided in seven modules that group zoogeographically distinct regions with their associated faunas, and identified a transition zone matching the limit of the ice sheets at Last Glacial Maximum (19k years ago). Deviance of species co-occurrences across regions, across sub-regions and within each region was significantly explained, primarily by environmental niche similarity, and secondarily by spatial connectivity, except for northern regions. Interestingly, southern species pools are mostly separated by dispersal barriers, whereas northern species pools are mainly sorted by their environmental niches. Another important finding of Calatayud et al. [5] is that most phylogenetic structuration occurred during the Pleistocene, and they show how extreme recent historical events (Quaternary glaciations) can profoundly modify the composition and structure of geographic species pools, as opposed to studies showing the role of deep-time evolutionary processes.

The study of biogeographic assembly of species pools using phylogenies has never been more exciting and promising than today. Catalayud et al. [5] brings a nice study on the importance of Pleistocene glaciations along with geographical barriers and niche-based processes in structuring the regional faunas of European beetles. The successful development of powerful analytical tools in recent years, in conjunction with the rapid and massive increase in the availability of biological data (including molecular phylogenies, fossils, georeferrenced occurrences and ecological traits), will allow us to disentangle complex evolutionary histories. Although we still face important limitations in data availability and methodological shortcomings, the last decade has witnessed an improvement of our understanding of how historical and biotic triggers are intertwined on shaping the Earth’s stupendous biological diversity. I hope that the Catalayud et al.’s approach (and analytical framework) will help movement in that direction, and that it will provide interesting perspectives for future investigations of other regions. Applied to a European beetle radiation, they were able to tease apart the relative contributions of biotic (niche-based processes) versus abiotic (geographic barriers and climate change) factors.


[1] Rosenzweig ML. 1995. Species diversity in space and time. Cambridge: Cambridge University Press.
[2] Mittelbach GG, Schemske DW, Cornell HV, Allen AP, Brown JM et al. 2007. Evolution and the latitudinal diversity gradient: speciation, extinction and biogeography. Ecology Letters. 10: 315–331. doi: 10.1111/j.1461-0248.2007.01020.x
[3] Lomolino MV, Riddle BR, Whittaker RJ and Brown JH. 2010. Biogeography, 4th edn. Sinauer Associates, Inc., Sunderland, MA.
[4] Wallace AR. 1876. The geographical distribution of animals: with a study of the relations of living and extinct faunas as elucidating the past changes of the earth's surface. New York: Harper and Brothers, Publishers.
[5] Calatayud J, Rodríguez MÁ, Molina-Venegas R, Leo M, Hórreo JL and Hortal J. 2018. Pleistocene climate change and the formation of regional species pools. bioRxiv 149617 ver. 4 peer-reviewed by Peer Community In Evolutionary Biology. doi: 10.1101/149617

05 Jun 2018
article picture

The dynamics of preferential host switching: host phylogeny as a key predictor of parasite prevalence and distribution

Shift or stick? Untangling the signatures of biased host switching, and host-parasite co-speciation

Recommended by based on reviews by Damien de Vienne and Nathan Medd

Many emerging diseases arise by parasites switching to new host species, while other parasites seem to remain with same host lineage for very long periods of time, even over timescales where an ancestral host species splits into two or more new species. The ability to understand these dynamics would form an important part of our understanding of infectious disease.

Experiments are clearly important for understanding these processes, but so are comparative studies, investigating the variation that we find in nature. Such comparative data do show strong signs of non-randomness, and this suggests that the epidemiological and ecological processes might be predictable, at least in part. For example, when we map patterns of parasite presence/absence onto host phylogenies, we often find that certain host clades harbour many more parasites than expected, or that closely-related hosts harbour closely-related parasites. Nevertheless, it remains difficult to interpret these patterns to make inferences about ecological and epidemiological processes. This is partly because non-random associations can arise in multiple ways. For example, parasites might be inherited from the common ancestor of related hosts, or might switch to new hosts, but preferentially establish on novel hosts that are closely related to their existing host. Infection might also influence the shape of host phylogeny, either by increasing the rate of host extinction or, conversely, increasing the rate of speciation (as with manipulative symbionts that might induce reproductive isolation).

These various processes have, by and large, been studied in isolation, but the model introduced by Engelstädter and Fortuna [1], makes an important first step towards studying them together. Without such combined analyses, we will not be able to tell if the processes have their own unique signatures, or whether the same sort of non-randomness can arise in multiple ways.

A major finding of the work is that the size of a host clade can be an important determinant of its overall infection level. This had been shown in previous work, assuming that the host phylogeny was fixed, but the current paper shows that it extends also to situations where host extinction and speciation takes place at a comparable rate to host shifting. This finding, then, calls into question the natural assumption that a clade of host species that is highly parasite ridden, must have some genetic or ecological characteristic that makes them particularly prone to infection, arguing that the clade size, rather than any characteristic of the clade members, might be the important factor. It will be interesting to see whether this prediction about clade size is borne out with comparative studies.

Another feature of the study is that the framework is naturally extendable, to include further processes, such as the influence of parasite presence on extinction or speciation rates. No doubt extensions of this kind will form the basis of important future work.


[1] Engelstädter J and Fortuna NZ. 2018. The dynamics of preferential host switching: host phylogeny as a key predictor of parasite prevalence and distribution. bioRxiv 209254 ver. 5 peer-reviewed by Peer Community In Evolutionary Biology. doi: 10.1101/209254

03 Jun 2018
article picture

Cost of resistance: an unreasonably expensive concept

Let’s move beyond costs of resistance!

Recommended by and based on reviews by Danna Gifford, Helen Alexander and 1 anonymous reviewer

The increase in the prevalence of (antibiotic) resistance has become a major global health concern and is an excellent example of the impact of real-time evolution on human society. This has led to a boom of studies that investigate the mechanisms and factors involved in the evolution of resistance, and to the spread of the concept of "costs of resistance". This concept refers to the relative fitness disadvantage of a drug-resistant genotype compared to a non-resistant reference genotype in the ancestral (untreated) environment.

In their paper, Lenormand et al. [1] discuss the history of this concept and highlight its caveats and limitations. The authors address both practical and theoretical problems that arise from the simplistic view of "costly resistance" and argue that they can be prejudicial for antibiotic resistance studies. For a better understanding, they visualize their points of critique by means of Fisher's Geometric model.

The authors give an interesting historical overview of how the concept arose and speculate that it emerged (during the 1980s) in an attempt by ecologists to spread awareness that fitness can be environment-dependent, and because of the concept's parallels to trade-offs in life-history evolution. They then identify several problems that arise from the concept, which, besides the conceptual misunderstandings that they can cause, are important to keep in mind when designing experimental studies.

The authors highlight and explain the following points:
1. Costs of resistance do not necessarily imply pleiotropic effects of a resistance mutation, and pleiotropy is not necessarily the cause of fitness trade-offs.
2. Any non-treated environment and any treatment dose can result in a different cost.
3. Different reference genotypes may result in different costs. Specifically, the reference genotype has to be "optimally" adapted to the reference environment to provide an accurate measurement of costs.

Lenormand et al.'s paper [1] is a timely perspective piece in light of the ever-increasing efforts to understand and tackle resistance evolution [2]. Although some readers may shy away from the rather theoretical presentation of the different points of concern, it will be useful for both theoretical and empirical readers by illustrating the misconceptions that can arise from the concept of the cost of resistance. Ultimately, the main lesson to be learned from this paper may not be to ban the term "cost of resistance" from one's vocabulary, but rather to realize that the successful fight against drug resistance requires more differential information than the measurement of fitness effects in a drug-treated vs. non-treated environment in the lab [3-4]. Specifically, a better integration of the ecological aspects of drug resistance evolution and maintenance is needed [5], and we are far from a general understanding of how environmental factors interact and influence an organism's (absolute and relative) fitness and the effect of resistance mutations.


[1] Lenormand T, Harmand N, Gallet R. 2018. Cost of resistance: an unreasonably expensive concept. bioRxiv 276675, ver. 3 peer-reviewed by Peer Community In Evolutionary Biology. doi: 10.1101/276675
[2] Andersson DI and Hughes D. Persistence of antibiotic resistance in bacterial populations. 2011. FEMS Microbiology Reviews, 35: 901-911. doi: 10.1111/j.1574-6976.2011.00289.x
[3] Chevereau G, Dravecká M, Batur T, Guvenek A, Ayhan DH, Toprak E, Bollenbach T. 2015. Quantifying the determinants of evolutionary dynamics leading to drug resistance. PLoS biology 13, e1002299. doi: 10.1371/journal.pbio.1002299
[4] Bengtsson-Palme J, Kristiansson E, Larsson DGJ. 2018. Environmental factors influencing the development and spread of antibiotic resistance. FEMS Microbiology Reviews 42: 68–80. doi: 10.1093/femsre/fux053
[5] Hiltunen T, Virta M, Laine AL. 2017. Antibiotic resistance in the wild: an eco-evolutionary perspective. Philosophical Transactions of the Royal Society B: Biological Sciences 372: 20160039. doi: 10.1098/rstb.2016.0039

18 May 2018
article picture

Modularity of genes involved in local adaptation to climate despite physical linkage

Differential effect of genes in diverse environments, their role in local adaptation and the interference between genes that are physically linked

Recommended by based on reviews by Tanja Pyhäjärvi and 1 anonymous reviewer

The genome of eukaryotic species is a complex structure that experience many different interactions within itself and with the surrounding environment. The genetic architecture of a phenotype (that is, the set of genetic elements affecting a trait of the organism) plays a fundamental role in understanding the adaptation process of a species to, for example, different climate environments, or to its interaction with other species. Thus, it is fundamental to study the different aspects of the genetic architecture of the species and its relationship with its surronding environment. Aspects such as modularity (the number of genetic units and the degree to which each unit is affecting a trait of the organism), pleiotropy (the number of different effects that a genetic unit can have on an organism) or linkage (the degree of association between the different genetic units) are essential to understand the genetic architecture and to interpret the effects of selection on the genome. Indeed, the knowledge of the different aspects of the genetic architecture could clarify whether genes are affected by multiple aspects of the environment or, on the contrary, are affected by only specific aspects [1,2].

The work performed by Lotterhos et al. [3] sought to understand the genetic architecture of the adaptation to different environments in lodgepole pine (Pinus contorta), considering as candidate SNPs those previously detected as a result of its extreme association patterns to different environmental variables or to extreme population differentiation. This consideration is very important because the study is only relevant if the studied markers are under the effect of selection. Otherwise, the genetic architecture of the adaptation to different environments would be masked by other (neutral) kind of associations that would be difficult to interpret [4,5]. In order to understand the relationship between genetic architecture and adaptation, it is relevant to detect the association networks of the candidate SNPs with climate variables (a way to measure modularity) and if these SNPs (and loci) are affected by single or multiple environments (a way to measure pleiotropy).

The authors used co-association networks, an innovative approach in this field, to analyse the interaction between the environmental information and the genetic polymorphism of each individual. This methodology is more appropriate than other multivariate methods - such as analysis based on principal components - because it is possible to cluster SNPs based on associations with similar environmental variables. In this sense, the co-association networks allowed to both study the genetic and physical linkage between different co-associations modules but also to compare two different models of evolution: a Modular environmental response architecture (specific genes are affected by specific aspects of the environment) or a Universal pleiotropic environmental response architecture (all genes are affected by all aspects of the environment). The representation of different correlations between allelic frequency and environmental factors (named galaxy biplots) are especially informative to understand the effect of the different clusters on specific aspects of the environment (for example, the co-association network ‘Aridity’ shows strong associations with hot/wet versus cold/dry environments).

The analysis performed by Lotterhos et al. [3], although it has some unavoidable limitations (e.g., only extreme candidate SNPs are selected, limiting the results to the stronger effects; the genetic and physical map is incomplete in this species), includes relevant results and also implements new methodologies in the field. To highlight some of them: the preponderance of a Modular environmental response architecture (evolution in separated modules), the detection of physical linkage among SNPs that are co-associated with different aspects of the environment (which was unexpected a priori), the implementation of co-association networks and galaxy biplots to see the effect of modularity and pleiotropy on different aspects of environment. Finally, this work contains remarkable introductory Figures and Tables explaining unambiguously the main concepts [6] included in this study. This work can be treated as a starting point for many other future studies in the field.


[1] Hancock AM, Brachi B, Faure N, Horton MW, Jarymowycz LB, Sperone FG, Toomajian C, Roux F & Bergelson J. 2011. Adaptation to climate across the Arabidopsis thaliana genome. Science 334: 83–86. doi: 10.1126/science.1209244
[2] Wagner GP & Zhang J. The pleiotropic structure of the genotype­phenotype map: the evolvability of complex organisms. Nature Review Genetics 12: 204–213. doi: 10.1038/nrg2949
[3] Lotterhos KE, Yeaman S, Degner J, Aitken S, Hodgins K. 2018. Modularity of genes involved in local adaptation to climate despite physical linkage. bioRxiv 202481, ver. 4 peer-reviewed by Peer Community In Evolutionary Biology. doi: 10.1101/202481
[4] Lotterhos KE & Whitlock MC. 2014. Evaluation of demographic history and neutral parameterization on the performance of FST outlier tests. Molecular Ecology 23: 2178–2192. doi: 10.1111/mec.12725
[5] Lotterhos KE & Whitlock MC. 2015. The relative power of genome scans to detect local adaptation depends on sampling design and statistical method. Molecular Ecology 24: 1031–1046. doi: 10.1111/mec.13100
[6] Paaby AB & Rockman MV. 2013. The many faces of pleiotropy. Trends in Genetics 29: 66-73. doi: 10.1016/j.tig.2012.10.010

19 Mar 2018
article picture

Natural selection on plasticity of thermal traits in a highly seasonal environment

Is thermal plasticity itself shaped by natural selection? An assessment with desert frogs

Recommended by based on reviews by Dries Bonte, Wolf Blanckenhorn and Nadia Aubin-Horth

It is well known that climatic factors – most notably temperature, season length, insolation and humidity – shape the thermal niche of organisms on earth through the action of natural selection. But how is this achieved precisely? Much of thermal tolerance is actually mediated by phenotypic plasticity (as opposed to genetic adaptation). A prominent expectation is that environments with greater (daily and/or annual) thermal variability select for greater plasticity, i.e. better acclimation capacity. Thus, plasticity might be selected per se.

A Chilean group around Leonardo Bacigalupe assessed natural selection in the wild in one marginal (and extreme) population of the four-eyed frog Pleurodema thaul (Anura: Leptodactylidae) in an isolated oasis in the Atacama Desert, permitting estimation of mortality without much potential of confounding it with migration [1]. Several thermal traits were considered: CTmax – the critical maximal temperature; CTmin – the critical minimum temperature; Tpref – preferred temperature; Q10 – thermal sensitivity of metabolism; and body mass. Animals were captured in the wild and subsequently assessed for thermal traits in the laboratory at two acclimation temperatures (10° & 20°C), defining the plasticity in all traits as the difference between the traits at the two acclimation temperatures. Thereafter the animals were released again in their natural habitat and their survival was monitored over the subsequent 1.5 years, covering two breeding seasons, to estimate viability selection in the wild. The authors found and conclude that, aside from larger body size increasing survival (an unsurprising result), plasticity does not seem to be systematically selected directly, while some of the individual traits show weak signs of selection.

Despite limited sample size (ca. 80 frogs) investigated in only one marginal but very seasonal population, this study is interesting because selection on plasticity in physiological thermal traits, as opposed to selection on the thermal traits themselves, is rarely investigated. The study thus also addressed the old but important question of whether plasticity (i.e. CTmax-CTmin) is a trait by itself or an epiphenomenon defined by the actual traits (CTmax and CTmin) [2-5]. Given negative results, the main question could not be ultimately solved here, so more similar studies should be performed.


[1] Bacigalupe LD, Gaitan-Espitia, JD, Barria AM, Gonzalez-Mendez A, Ruiz-Aravena M, Trinder M & Sinervo B. 2018. Natural selection on plasticity of thermal traits in a highly seasonal environment. bioRxiv 191825, ver. 5 peer-reviewed by Peer Community In Evolutionary Biology. doi: 10.1101/191825
[2] Scheiner SM. 1993. Genetics and evolution of phenotypic plasticity. Annual Review in Ecology and Systematics 24: 35–68. doi: 10.1146/
[3] Scheiner SM. 1993. Plasticity as a selectable trait: Reply to Via. The American Naturalist. 142: 371–373. doi: 10.1086/285544
[4] Via S. 1993. Adaptive phenotypic plasticity - Target or by-product of selection in a variable environment? The American Naturalist. 142: 352–365. doi: 10.1086/285542
[5] Via S. 1993. Regulatory genes and reaction norms. The American Naturalist. 142: 374–378. doi: 10.1086/285542

28 Feb 2018
article picture

Insects and incest: sib-mating tolerance in natural populations of a parasitoid wasp

Incestuous insects in nature despite occasional fitness costs

Recommended by and based on reviews by 2 anonymous reviewers

Inbreeding, or mating between relatives, generally lowers fitness [1]. Mating between genetically similar individuals can result in higher levels of homozygosity and consequently a higher frequency with which recessive disease alleles may be expressed within a population. Reduced fitness as a consequence of inbreeding, or inbreeding depression, can vary between individuals, sexes, populations and species [2], but remains a pervasive challenge for many organisms with small local population sizes, including humans [3]. But all is not lost for individuals within small populations, because an array of mechanisms can be employed to evade the negative effects of inbreeding [4], including sib-mating avoidance and dispersal [5, 6].

Despite thorough investigation of inbreeding and sib-mating avoidance in the laboratory, only very few studies have ventured into the field besides studies on vertebrates and eusocial insects. The study of Collet et al. [7] is a surprising exception, where the effect of male density and frequency of relatives on inbreeding avoidance was tested in the laboratory, after which robust field collections and microsatellite genotyping were used to infer relatedness and dispersal in natural populations. The parasitic wasp Venturia canescens is an excellent model system to study inbreeding, because mating success was previously found to decrease with increasing relatedness between mates in the laboratory [8] and this species thus suffers from inbreeding depression [9–11]. The authors used an elegant design combining population genetics and model simulations to estimate relatedness of mating partners in the field and compared that with a theoretical distribution of potential mate encounters when random mating is assumed. One of the most important findings of this study is that mating between siblings is not avoided in this species in the wild, despite negative fitness effects when inbreeding does occur. Similar findings were obtained for another insect species, the field cricket Gryllus campestris [12], which leaves us to wonder whether inbreeding tolerance could be more common in nature than currently appreciated.

The authors further looked into sex-specific dispersal patterns between two patches located a few hundred meters apart. Females were indeed shown to be more related within a patch, but no genetic differences were observed between males, suggesting that V. canescens males more readily disperse. Moreover, microsatellite data at 18 different loci did not reveal genetic differentiation between populations approximately 300 kilometers apart. Gene flow is thus occurring over considerable distances, which could play an important role in the ability of this species to avoid negative fitness consequences of inbreeding in nature.

Another interesting aspect of this work is that discrepancies were found between laboratory- and field-based data. What is the relevance of laboratory-based experiments if they cannot predict what is happening in the wild? Many, if not most, biologists (including us) bring our model system into the laboratory to control, at least to some extent, the plethora of environmental factors that could potentially affect our system (in ways that we do not want). Most behavioral studies on mating patterns and sexual selection are conducted in standardized laboratory conditions, but sexual selection is in essence social selection, because an individual’s fitness is partly determined by the phenotype of its social partners (i.e. the social environment) [13]. The social environment may actually dictate the expression of female mate choice and it is unclear how potential laboratory-induced social biases affect mating outcome. In V. canescens, findings using field-caught individuals paint a completely opposite picture of what was previously shown in the laboratory, i.e. sib-avoidance is not taking place in the field. It is likely that density, level of relatedness, sex ratio in the field, and/or the size of experimental arenas in the lab are all factors affecting mate selectivity, as we have previously shown in a butterfly [14–16]. If females, for example, typically only encounter a few males in sequence in the wild, it may be problematic for them to express choosiness when confronted simultaneously with two or more males in the laboratory. A recent study showed that, in the wild, female moths take advantage of staying in groups to blur male choosiness [17]. It is becoming more and more clear that what we observe in the laboratory may not actually reflect what is happening in nature [18]. Instead of ignoring the species-specific life history and ecological features of our favorite species when conducting lab experiments, we suggest that it is time to accept that we now have the theoretical foundations to tease apart what in this “environmental noise” actually shapes sexual selection in nature. Explicitly including ecology in studies on sexual selection will allow us to make more meaningful conclusions, i.e. rather than “this is what may happen in the wild”, we would be able to state “this is what often happens in nature”.


[1] Charlesworth D & Willis JH. 2009. The genetics of inbreeding depression. Nat. Rev. Genet. 10: 783–796. doi: 10.1038/nrg2664
[2] Hedrick PW & Garcia-dorado A. 2016. Understanding inbreeding depression, purging, and genetic rescue. Trends Ecol. Evol. 31: 940–952. doi: 10.1016/j.tree.2016.09.005
[3] Bittles AH & Black ML. 2010. Consanguinity, human evolution, and complex diseases. Proc. Natl. Acad. Sci. United States Am. 107: 1779–1786. doi: 10.1073/pnas.0906079106
[4] Pusey A & Wolf M. 1996. Inbreeding avoidance in animals. Trends Ecol. Evol. 11: 201–206. doi: 10.1016/0169-5347(96)10028-8
[5] Greenwood PJ & Harvey PH. 1978. Inbreeding and dispersal in the great tit. Nature 271: 52–54. doi: 10.1038/271052a0
[6] Szulkin M & Sheldon BC. 2008. Dispersal as a means of inbreeding avoidance in a wild bird population. Proc. R. Soc. B 275: 703–711. doi: 10.1098/rspb.2007.0989
[7] Collet M, Amat I, Sauzet S, Auguste A, Fauvergue X, Mouton L, Desouhant E. 2018. Insects and incest: sib-mating tolerance in natural populations of a parasitoid wasp. bioRxiv 169268, ver. 4 peer-reviewed by Peer Community In Evolutionary Biology. doi: 10.1101/169268
[8] Metzger M, Bernstein C, Hoffmeister TS & Desouhant E. 2010. Does kin recognition and sib-mating avoidance limit the risk of genetic incompatibility in a parasitic wasp ? PLoS One 5: e13505. doi: 10.1371/journal.pone.0013505
[9] Beukeboom LW. 2001. Single-locus complementary sex determination in the Ichneumonid Venturia canescens. Netherlands J. Zool. 51: 1–15. doi: 10.1163/156854201X00017
[10] Vayssade C, de Fazio C, Quaglietti B, Auguste A, Ris N, Fauvergue X. 2014. Inbreeding depression in a parasitoid wasp with single- locus complementary sex determination. PLoS One 9: 1–8. doi: 10.1371/journal.pone.0097733
[11] Chuine A, Sauzet S, Debias F & Desouhant E. 2015. Consequences of genetic incompatibility on fitness and mate choice: the male point of view. Biol. J. Linn. Soc. 114: 279–286. doi: 10.1111/bij.12421
[12] Bretman A, Rodri R & Tregenza T. 2011. Fine-scale population structure , inbreeding risk and avoidance in a wild insect population. Mol. Ecol. 20: 3045–3055. doi: 10.1111/j.1365-294X.2011.05140.x
[13] West-Eberhard MJ. 2014. Darwin’s forgotten idea: The social essence of sexual selection. Neurosci. Biobehav. Rev. 46: 501–508. doi: 10.1016/j.neubiorev.2014.06.015
[14] Holveck M-J, Gauthier A-L & Nieberding CM 2015. Dense, small and male-biased cages exacerbate male-male competition and reduce female choosiness in Bicyclus anynana. Anim. Behav. 104: 229–245. doi: 10.1016/j.anbehav.2015.03.025
[15] Nieberding, CM & Holveck M-J 2017. Laboratory social environment biases mating outcome: a first quantitative synthesis in a butterfly. Behav. Ecol. Sociobiol. 71: 117. doi: 10.1007/s00265-017-2346-9
[16] Nieberding CM & Holveck M-J. (In prep). Comentary on Kehl et al. 2018: "Young male mating success is associated with sperm number but not with male sex pheromone titres". Front. Ecol. Evol.
[17] Wijk M Van, Heath J, Lievers R, Schal C & Groot AT. 2017. Proximity of signallers can maintain sexual signal variation under stabilizing selection. Sci. Rep. 7: 18101. doi: 10.1038/s41598-017-17327-9
[18] Miller CW & Svensson EI. 2014. Sexual selection in complex environments. Annu. Rev. Entomol. 59: 427–445. doi: 10.1146/annurev-ento-011613-162044

19 Feb 2018
article picture

Genomic imprinting mediates dosage compensation in a young plant XY system

Dosage compensation by upregulation of maternal X alleles in both males and females in young plant sex chromosomes

Recommended by and based on reviews by 3 anonymous reviewers

Sex chromosomes evolve as recombination is suppressed between the X and Y chromosomes. The loss of recombination on the sex-limited chromosome (the Y in mammals) leads to degeneration of both gene expression and gene content for many genes [1]. Loss of gene expression or content from the Y chromosome leads to differences in gene dose between males and females for X-linked genes. Because expression levels are often correlated with gene dose [2], these hemizygous genes have a lower expression levels in the heterogametic sex. This in turn disrupts the stoichiometric balance among genes in protein complexes that have components on both the sex chromosomes and autosomes [3], which could have serious deleterious consequences for the heterogametic sex.
To overcome these deleterious effects of degeneration, the expression levels of dosage sensitive X-linked genes, and in some organisms, entire X chromosomes, are compensated, the expression of the single copy of in the heterogametic sex being increased. Dosage compensation for such genes has evolved in several species, restoring similar expression levels as in the ancestral state in males and/or equal gene expression in males and females [4-8]. The mechanisms for dosage compensation are variable among species and their evolutionary paths are not fully understood, as the few model sex chromosomes studied so far have old, and highly degenerate sex chromosomes [4-7].
Muyle et al. [9] studied the young sex chromosomes of the plant Silene latifolia, which has young sex chromosomes (4 MY) and highly variable dosage compensation [10, 11]. The authors used both an outgroup species without sex chromosomes for obtaining a proxy for ancestral expression levels before Y degeneration, and implemented methods to identify sex-linked genes and disentangle paternal versus maternal allele expression [12]. Using these elements, Muyle et al. [9] reveal upregulation of maternal X alleles in both males and females in the young S. latifolia sex chromosomes [9], possibly by genomic imprinting. The upregulation in both sexes of the maternal X alleles likely yields non-optimal gene expression in females, which is strikingly consistent with the theoretical first step of dosage compensation as postulated by Ohno [8], which predicts restoration of ancestral expression in males, over-expression in females, and unequal expression in the two sexes. These findings provide surprising insight into the earliest stages of dosage compensation, one of the most intriguing aspects of evolutionary biology.

[1] Bachtrog D. 2013. Y chromosome evolution: emerging insights into processes of Y-chromosome degeneration? Nature Reviews Genetics 14: 113–124. doi: 10.1038/nrg3366
[2] Malone JH, Cho D-Y, Mattiuzzo NR, Artieri CG, Jiang L, Dale RK, Smith HE, McDaniel J, Munro S, Salit M, Andrews J, Przytycka TM and Oliver B. 2012. Mediation of Drosophila autosomal dosage effects and compensation by network interactions. Genome Biology 13: R28. doi: 10.1186/gb-2012-13-4-r28
[3] Pessia E, Makino T, Bailly-Bechet M, McLysaght A and Marais GAB. 2012. Mammalian X chromosome inactivation evolved as a dosage-compensation mechanism for dosage-sensitive genes on the X chromosome. Proceedings of the National Academy of Sciences of the United States of America. 109: 5346–5351. doi: 10.1073/pnas.1116763109.
[4] Graves JAM. 2016. Evolution of vertebrate sex chromosomes and dosage compensation. Nature Reviews Genetics 17: 33–46. doi: 10.1038/nrg.2015.2
[5] Mank JE. 2013. Sex chromosome dosage compensation: definitely not for everyone. Trends in Genetics 12: 677–683. doi: 10.1016/j.tig.2013.07.005
[6] Pessia E and Engelstädter J. 2014. The evolution of X chromosome inactivation in mammals: the demise of Ohno’s hypothesis? Cellular and Molecular Life Sciences 71: 1383–1394. doi: 10.1007/s00018-013-1499-6
[7] Muyle A, Shearn R and Marais GAB. 2017. The evolution of sex chromosomes and dosage compensation in plants. Genome Biology and Evolution 9: 627–645. doi: 10.1093/gbe/evw282
[8] Ohno S. 1967. Sex chromosomes and sex linked genes. Springer, Berlin Heidelberg New York.
[9] Muyle A, Zemp N, Fruchard C, Cegan R, Vrana J, Deschamps C, Tavares R, Picard F, Hobza R, Widmer A and Marais GAB. 2018. Genomic imprinting mediates dosage compensation in a young plant XY system. bioRxiv 118695, ver. 6 peer-reviewed by Peer Community In Evolutionary Biology. doi: 10.1101/179044
[10] Papadopulos AST, Chester M, Ridout K and Filatov DA. 2015. Rapid Y degeneration and dosage compensation in plant sex chromosomes. Proceedings of the National Academy of Sciences of the United States of America 112: 13021–13026. doi: 10.1073/pnas.1508454112
[11] Bergero R, Qiu S and Charlesworth D. 2015. Gene loss from a plant sex chromosome system. Current Biology 25: 1234–1240. doi: 10.1016/j.cub.2015.03.015
[12] Muyle A, Kafer J, Zemp N, Mousset S, Picard F and Marais GAB. 2016. SEX-DETector: a probabilistic approach to study sex chromosomes in non-model organisms. Genome Biology and Evolution 8: 2530–2543. doi: 10.1093/gbe/evw172

09 Feb 2018
article picture

Phylodynamic assessment of intervention strategies for the West African Ebola virus outbreak

Simulating the effect of public health interventions using dated virus sequences and geographical data

Recommended by based on reviews by Christian Althaus, Chris Wymant and 1 anonymous reviewer

Perhaps because of its deadliness, the 2013-2016 Ebola Virus (EBOV) epidemics in West-Africa has led to unprecedented publication and sharing of full virus genome sequences. This was both rapid (90 full genomes were shared within weeks [1]) and important (more than 1500 full genomes have been released overall [2]). Furthermore, the availability of the metadata (especially GPS location) has led to depth analyses of the geographical spread of the epidemics [3].
In their work, Dellicour et al. [4] pursue earlier phylogeographical investigations in an original and yet simple approach to address questions of key public health importance. The originality of the approach is dual. First, from a technical standpoint, they capture the spread of infectious diseases in a continuous framework using a novel model that allows for rare long-distance dispersal events. Second, in a more classical discrete meta-population framework, they simulate the effect of public health interventions by pruning the phylogenetic tree and assessing how this affects key parameters. For instance, to simulate the effect of closing borders they remove subsets of the phylogeny that involved dispersal between countries and to simulate the effect of protecting a region by quarantine they remove all the leaves (i.e. the infections sampled) from this region. This phylogeny pruning is both original and simple. It is however limited because it currently assumes that policies are 100% effective and earlier modelling work on human influenza showed that long distance travel bans had to be implemented with >99% efficiency in order to slow epidemic growth from a time scale of days to weeks [5].
From a biological standpoint, Dellicour et al. [4] corroborate earlier findings that highly populated locations (>1,000,000 inhabitants) were crucial in explaining the magnitude of the epidemics but also show the importance of the transmission between the three capital cities. They also show that rare long-distance dispersing events of the virus are not key to explaining the magnitude of the epidemics (even though they assume 100% efficiency of suppressing long-distance event). Finally, thanks to their continuous model they estimate the speed of spread of the epidemics and are able to detect the effect of border closing on this speed.
Overall, this study [4], which involves state-of-the-art Bayesian inference methods of infection phylogenies using MCMC, stands out because of its effort to simulate public health interventions. It stands as an encouragement for the development of intervention models with increased realism and for even faster and larger virus sequence data sharing.


[1] Gire et al. 2014. Genomic surveillance elucidates Ebola virus origin and transmission during the 2014 outbreak. Science 345: 1369–1372. doi: 10.1126/science.1259657.
[2] Holmes EC, Dudas G, Rambaut A and Andersen KG. 2016. The evolution of Ebola virus: insights from the 2013-2016 epidemic. Nature 538: 193–200. doi: 10.1038/nature19790.
[3] Dudas et al. 2017. Virus genomes reveal factors that spread and sustained the Ebola epidemic. Nature 544: 309–315 (2017). doi: 10.1038/nature22040.
[4] Dellicour S, Baele G, Dudas G, Faria NR, Pybus OG, Suchard MA, Rambaud A and Lemey P. 2018. Phylodynamic assessment of intervention strategies for the West African Ebola virus outbreak. bioRxiv, 163691, ver. 3 peer-reviewed by Peer Community In Evolutionary Biology. doi: 10.1101/163691.
[5] Hollingsworth TD, Ferguson NM and Anderson RM. 2006. Will travel restrictions control the international spread of pandemic influenza? Nature Medicine 12, 497–499. doi: 10.1038/nm0506-497.

31 Jan 2018
article picture

Identifying drivers of parallel evolution: A regression model approach

A new statistical tool to identify the determinant of parallel evolution

Recommended by based on reviews by Bastien Boussau and 1 anonymous reviewer

In experimental evolution followed by whole genome resequencing, parallel evolution, defined as the increase in frequency of identical changes in independent populations adapting to the same environment, is often considered as the product of similar selection pressures and the parallel changes are interpreted as adaptive.
However, theory predicts that heterogeneity both in mutation rate and selection intensity across the genome can trigger patterns of parallel evolution. It is thus important to evaluate and quantify the contribution of both mutation and selection in determining parallel evolution to interpret more accurately experimental evolution genomic data and also potentially improve our capacity to predict the genes that will respond to selection.
In their manuscript, Bailey, Guo and Bataillon [1] derive a framework of statistical models to partition the role of mutation and selection in determining patterns of parallel evolution at the gene level. The rationale is to use the synonymous mutations dataset as a baseline to characterize the mutation rate heterogeneity, assuming a negligible impact of selection on synonymous mutations and then analyse the non-synonymous dataset to identify additional source(s) of heterogeneity, by examining the proportion of the variation explained by a number of genomic variables.
This framework is applied to a published data set of resequencing of 40 Saccharomyces cerevisiae populations adapting to a laboratory environment [2]. The model explaining at best the synonymous mutations dataset is one of homogeneous mutation rate along the genome with a significant positive effect of gene length, likely reflecting variation in the size of the mutational target. For the non-synonymous mutations dataset, introducing heterogeneity between sites for the probability of a change to increase in frequency is improving the model fit and this heterogeneity can be partially explained by differences in gene length, recombination rate and number of functional protein domains.
The application of the framework to an experimental data set illustrates its capacity to disentangle the role of mutation and selection and to identify genomic variables explaining heterogeneity in parallel evolution probability but also points to potential limits, cautiously discussed by the authors: first, the number of mutations in the dataset analysed needs to be sufficient, in particular to establish the baseline on the synonymous dataset. Here, despite a high replication (40 populations evolved in the exact same conditions), the total number of synonymous mutations that could be analysed was not very high and there was only one case of a gene with synonymous mutation in two independent populations. Second, although the models are able to identify factors affecting the mutation counts, the proportion of the variation explained is quite low. The consequence is that the models correctly predicts the mutation count distribution but the objective of predicting on which genes the response to selection will occur still seems quite far away.
The framework developed in this manuscript [1] clearly represents a very useful tool for the analysis of large “evolve and resequence” data sets and to gain a better understanding of the determinants of parallel evolution in general. The extension of its application to mutations others than SNPs would provide the possibility to get a more complete picture of the differences in contributions of mutation and selection intensity heterogeneities depending on the mutation types.


[1] Bailey SF, Guo Q and Bataillon T (2018) Identifying drivers of parallel evolution: A regression model approach. bioRxiv 118695, ver. 4 peer-reviewed by Peer Community In Evolutionary Biology. doi: 10.1101/118695

[2] Lang GI, Rice DP, Hickman, MJ, Sodergren E, Weinstock GM, Botstein D, and Desai MM (2013) Pervasive genetic hitchhiking and clonal interference in forty evolving yeast populations. Nature 500: 571–574. doi: 10.1038/nature12344

20 Dec 2017
article picture

Renewed diversification following Miocene landscape turnover in a Neotropical butterfly radiation

The influence of environmental change over geological time on the tempo and mode of biological diversification, revealed by Neotropical butterflies

Recommended by based on reviews by Delano Lewis and 1 anonymous reviewer

The influence of environmental change over geological time on the tempo and mode of biological diversification is a hot topic in biogeography. Of central interest are questions about where, when, and how fast lineages proliferated, suffered extinction, and migrated in response to tectonic events, the waxing and waning of dominant biomes, etc. In this context, the dynamic conditions of the Miocene have received much attention, from studies of many clades and biogeographic regions. Here, Chazot et al. [1] present an exemplary analysis of butterflies (tribe Ithomiini) in the Neotropics, examining their diversification across the Andes and Amazon. They infer sharp contrasts between these regions in the late Miocene: accelerated diversification during orogeny of the Andes, and greater extinction in the Amazon associated during the Pebas system, with interchange and local diversification increasing following the Pebas during the Pliocene.
Two features of this study stand out. First is the impressive taxon sampling (340 out of 393 extant species). Second is the use of ancestral range reconstructions to compute per-lineage rates of colonization between regions, and rates of speciation within regions, through time. The latter allows for relatively fine-grained comparisons across the 2 fundamental dimensions of historical biogeography, space and time, and is key to the main results. The method resonated with me because I performed a similar analysis in a study showing evidence for uplift-driven diversification in the Hengduan Mountains of China [2]. This analysis is complemented by a variety of other comparative methods for inferring variable diversification across clades, through time, and in response to external factors. Overall, it represents a very nice contribution to our understanding of the effects of Miocene/Pliocene environmental change on the evolution of Neotropical biodiversity.


[1] Chazot N, Willmott KR, Lamas G, Freitas AVL, Piron-Prunier F, Arias CF, Mallet J, De-Silva DL and Elias M. 2017. Renewed diversification following Miocene landscape turnover in a Neotropical butterfly radiation. BioRxiv 148189, ver 4 of 19th December 2017. doi: 10.1101/148189

[2] Xing Y, and Ree RH. 2017. Uplift-driven diversification in the Hengduan Mountains, a temperate biodiversity hotspot. Proceedings of the National Academy of Sciences of the United States of America, 114: E3444-E3451. doi: 10.1073/pnas.1616063114

18 Dec 2017
article picture

Co-evolution of virulence and immunosuppression in multiple infections

Two parasites, virulence and immunosuppression: how does the whole thing evolve?

Recommended by based on reviews by 2 anonymous reviewers

How parasite virulence evolves is arguably the most important question in both the applied and fundamental study of host-parasite interactions. Typically, this research area has been progressing through the formalization of the problem via mathematical modelling. This is because the question is a complex one, as virulence is both affected and affects several aspects of the host-parasite interaction. Moreover, the evolution of virulence is a problem in which ecology (epidemiology) and evolution (changes in trait values through time) are tightly intertwined, generating what is now known as eco-evolutionary dynamics. Therefore, intuition is not sufficient to address how virulence may evolve.
In their classical model, Anderson and May [1] predict that the optimal virulence level results from a trade-off between increasing parasite load within hosts and promoting transmission between hosts. Although very useful and foundational, this model incurs into several simplifying assumptions. One of the most obvious is that it considers that hosts are infected by a single parasite strain/species. Some subsequent models have thus accounted for multiple infections, generally predicting that this will select for higher virulence, because it increases the strength of selection in the within-host compartment.
Usually, when attacked, hosts deploy defences to combat their parasites. In many systems, however, parasites can suppress the immune response of their hosts. This leads to prolonged infection, which is beneficial for the parasite. However, immunosuppressed hosts are also more prone to infection. Thus, multiple infections are more likely in a population of immunosuppressed hosts, leading to higher virulence, hence a shorter infection period. Thus, the consequences of immunosuppression for the evolution of virulence in a system allowing for multiple infections are not straightforward.
Kamiya et al.[2] embrace this challenge. They create an epidemiological model in which the probability of co-infection trades off with the rate of recovery from infection, via immunosuppression. They then use adaptive dynamics to study how either immunosuppression or virulence evolve in response to one another, to then establish what happens when they both coevolve. They find that when virulence only evolves, its evolutionary equilibrium increases as immunosuppression levels increase. In the reverse case, that is, when virulence is set to a fixed value, the evolutionarily stable immunosuppression varies non-linearly with virulence, with first a decrease, but then an increase at high levels of virulence. The initial decrease of immunosuppression may be due to (a) a decrease in infection duration and/or (b) a decrease in the proportion of double infections, caused by increased levels of virulence. However, as virulence increases, the probability of double infections decreases even in non-immunosuppressed hosts, hence increased immunosuppression is selected for.
The combination of both Evolutionary Stable Strategies (ESSs) yields intermediate levels of virulence and immunosuppression. The authors then address how this co-ESS varies with host mortality and with the shape of the trade-off between the probability of co-infection and the rate of recovery. They find that immunosuppression always decreases with increased host mortality, as it becomes not profitable to invest on this trait. In contrast, virulence peaks at intermediate values of host mortality, unlike the monotonical decrease that is found in absence of immunosuppression. Also, this relationship is predicted to vary with the shape of the trade-off underlying the costs and benefits of immunosuppression.
In sum, Kamiya et al. [2] provide a comprehensive analysis of an important problem in the evolution of host-parasite interactions. The model provides clear predictions, and thus can now be tested using the many systems in which immunosuppression has been detected, provided that the traits that compose the model can be measured.


[1] Anderson RM and May RM. 1982. Coevolution of hosts and parasites. Parasitology, 1982. 85: 411–426. doi: 10.1017/S0031182000055360

[2] Kamiya T, Mideo N and Alizon S. 2017. Coevolution of virulence and immunosuppression in multiple infections. bioRxiv, ver. 7 peer-reviewed by PCI Evol Biol, 149211. doi: 10.1101/139147

05 Dec 2017
article picture

Reconstruction of body mass evolution in the Cetartiodactyla and mammals using phylogenomic data

Predicting small ancestors using contemporary genomes of large mammals

Recommended by based on reviews by Bruce Rannala and 1 anonymous reviewer

Recent methodological developments and increased genome sequencing efforts have introduced the tantalizing possibility of inferring ancestral phenotypes using DNA from contemporary species. One intriguing application of this idea is to exploit the apparent correlation between substitution rates and body size to infer ancestral species' body sizes using the inferred patterns of substitution rate variation among species lineages based on genomes of extant species [1].
The recommended paper by Figuet et al. [2] examines the utility of such approaches by analyzing the Cetartiodactyla, a clade of large mammals that have mostly well resolved phylogenetic relationships and a reasonably good fossil record. This combination of genomic data and fossils allows a direct comparison between body size predictions obtained from the genomic data and empirical evidence from the fossil record. If predictions seem good in groups such as the Cetartiodactyla, where there is independent evidence from the fossil record, this would increase the credibility of predictions made for species with less abundant fossils.
Figuet et al. [2] analyze transcriptome data for 41 species and report a significant effect of body mass on overall substitution rate, synonymous vs. non-synonymous rates, and the dynamics of GC-content, thus allowing a prediction of small ancestral body size in this group despite the fact that the extant species that were analyzed are nearly all large.
A comparative method based solely on morphology and phylogenetic relationships would be very unlikely to make such a prediction. There are many sources of uncertainty in the variables and parameters associated with these types of approaches: phylogenetic uncertainty (topology and branch lengths), uncertainty about inferred substitution rates, and so on. Although the authors do not account for all these sources of uncertainty the fact that their predicted body sizes appear sensible is encouraging and undoubtedly the methods will become more statistically sophisticated over time.


[1] Romiguier J, Ranwez V, Douzery EJP and Galtier N. 2013. Genomic evidence for large, long-lived ancestors to placental mammals. Molecular Biology and Evolution 30: 5–13. doi: 10.1093/molbev/mss211

[2] Figuet E, Ballenghien M, Lartillot N and Galtier N. 2017. Reconstruction of body mass evolution in the Cetartiodactyla and mammals using phylogenomic data. bioRxiv, ver. 3 of 4th December 2017. 139147. doi: 10.1101/139147

20 Nov 2017
article picture

Effects of partial selfing on the equilibrium genetic variance, mutation load and inbreeding depression under stabilizing selection

Understanding genetic variance, load, and inbreeding depression with selfing

Recommended by based on reviews by Frédéric Guillaume and 1 anonymous reviewer

A classic problem in evolutionary biology is to understand the genetic variance in fitness. The simplest hypothesis is that variation exists, even in well-adapted populations, as a result of the balance between mutational input and selective elimination. This variation causes a reduction in mean fitness, known as the mutation load. Though mutation load is difficult to quantify empirically, indirect evidence of segregating genetic variation in fitness is often readily obtained by comparing the fitness of inbred and outbred offspring, i.e., by measuring inbreeding depression. Mutation-selection balance models have been studied as a means of understanding the genetic variance in fitness, mutation load, and inbreeding depression. Since their inception, such models have increased in sophistication, allowing us to ask these questions under more realistic and varied scenarios. The new theoretical work by Abu Awad and Roze [1] is a substantial step forward in understanding how arbitrary levels of self-fertilization affect variation, load and inbreeding depression under mutation-selection balance.
It has never been entirely clear how selfing should affect these population genetic properties in a multi-locus model. From the single-locus perspective, selfing increases homozygosity, which allows for more efficient purging leading to a prediction of less variance and lower load. On the other hand, selfing directly and indirectly affects several types of multilocus associations, which tend to make selection less efficient. Though this is certainly not the first study to consider mutation-selection balance in species with selfing (e.g., [2-5]), it is perhaps the most biologically realistic. The authors consider a model where n traits are under stabilizing selection and where each locus affects an arbitrary subset of these traits. As others have argued [6-7], this type of fitness landscape model “naturally” gives rise to dominance and epistatic effects. Abu Awad and Roze [1] thoroughly investigate this model both with analytical approximations and stochastic simulations (incorporating the effects of drift).
Their analysis reveals three major parameter regimes. The first regime occurs under low mutation rates, when segregating deleterious alleles are sufficiently rare across the genome that multi-locus genetic associations (disequilibria) can be ignored. As expected, in this regime, increased selfing facilitates purging, thereby leading to less standing genetic variation, lower load and less inbreeding depression.
In the second regime, mutation rates are higher and segregating deleterious alleles are more common. Though the effects of multilocus genetic associations cannot be ignored, Abu Awad and Roze [1] show that a good approximation can be obtained by considering only two-locus associations (ignoring the multitude of higher order associations). This is where the sophistication of their analysis yields the greatest insights. Their analysis shows that two different types of interlocus associations are important. First, selfing directly generates identity disequilibrium (correlation in homozygosity between two loci) that occurs because individuals produced through outbreeding tend to be heterozygous across multiple loci whereas individuals produced by selfing tend to be homozygous across multiple loci. These correlations reduce the efficiency of selection when deleterious effects are partially recessive [5]. Second, selfing indirectly affects traditional linkage disequilibrium. Epistatic selection resulting from the fitness landscape generates negative linkage disequilibrium between alleles at different loci that cause the same direction of deviation in a trait from its optimum. Because selfing reduces the effective rate of recombination, linkage disequilibrium reaches higher levels. Because selection tends to generate compensatory combinations of alleles, partially masking their deleterious effects, these associations also make purging less efficient. Their analysis shows the strength of the effect from identity disequilibrium scales with U, the genome-wide rate of deleterious mutations, but the effect of linkage disequilibrium scales with U/n because with more traits (higher n) two randomly chosen alleles are less likely to affect the same trait and so be subject to epistatic selection. Together, the effects of multilocus associations increase the load and can, in some cases, cause the load to increase as selfing increase from moderate to high levels.
However, their analytical approximations become inaccurate under conditions when the number of epistatically interacting segregating mutations (proportional to U/n) becomes large relative to the effective recombination rate (dependent on outcrossing and recombination rates). In this third regime, higher order genetic associations become important. In the limit of no recombination, model behaves as if the whole genome is a single locus with a very large number of alleles, becoming equivalent to previous studies [2-3].
The study by Abu Awad and Roze [1] helps us better understand the “simplest” explanation for genetic variance in fitness—mutation-selection balance—in a model of considerable complexity involving multiple traits under stabilizing selection, which ‘naturally’ allows for pleiotropy and epistasis. Their model tends to confirm the classic prediction of lower variation in fitness, less load, and inbreeding depression in species with higher levels of selfing. However, their careful analysis provides a clearer picture of how (and by how much) epistasis and selfing affect key population genetic properties.


[1] Abu Awad D and Roze D. 2017. Effects of partial selfing on the equilibrium genetic variance, mutation load and inbreeding depression under stabilizing selection. bioRxiv, 180000, ver. 4 of 17th November 2017. doi: 10.1101/180000

[2] Lande R. 1977. The influence of the mating system on the maintenance of genetic variability in polygenic characters. Genetics 86: 485–498.

[3] Charlesworth D and Charlesworth B. 1987. Inbreeding depression and its evolutionary consequences. Annual Review of Ecology and Systematics. 18: 237–268. doi: 10.1111/10.1146/

[4] Lande R and Porcher E. 2015. Maintenance of quantitative genetic variance under partial self-fertilization, with implications for the evolution of selfing. Genetics 200: 891–906. doi: 10.1534/genetics.115.176693

[5] Roze D. 2015. Effects of interference between selected loci on the mutation load, inbreeding depression, and heterosis. Genetics 201: 745–757. doi: 10.1534/genetics.115.178533

[6] Martin G and Lenormand T. 2006. A general multivariate extension of Fisher's geometrical model and the distribution of mutation fitness effects across species. Evolution 60: 893–907. doi: 10.1111/j.0014-3820.2006.tb01169.x

[7] Martin G, Elena SF and Lenormand T. 2007. Distributions of epistasis in microbes fit predictions from a fitness landscape model. Nature Genetics 39: 555–560. doi: 10.1038/ng1998

17 Nov 2017
article picture

ABC random forests for Bayesian parameter inference

Machine learning methods are useful for Approximate Bayesian Computation in evolution and ecology

Recommended by based on reviews by Michael Blum and Dennis Prangle

It is my pleasure to recommend the paper by Raynal et al. [1] about using random forest for parameter inference. There are two reviews about the paper, one review written by Dennis Prangle and another review written by myself. Both reviews were positive and included comments that have been addressed in the current version of the preprint.

The paper nicely shows that modern machine learning approaches are useful for Approximate Bayesian Computation (ABC) and more generally for simulation-driven parameter inference in ecology and evolution.

The authors propose to consider the random forest approach, proposed by Meinshausen [2] to perform quantile regression. The numerical implementation of ABC with random forest, available in the abcrf package, is based on the RANGER R package that provides a fast implementation of random forest for high-dimensional data.

According to my reading of the manuscript, there are 3 main advantages when using random forest (RF) for parameter inference with ABC. The first advantage is that RF can handle many summary statistics and that dimension reduction is not needed when using RF.

The second advantage is very nicely displayed in Figure 5, which shows the main result of the paper. If correct, 95% posterior credibility intervals (C.I.) should contain 95% of the parameter values used in simulations. Figure 5 shows that posterior C.I. obtained with rejection are too large compared to other methods. By contrast, C.I. obtained with regression methods have been shrunken. However, the shrinkage can be excessive for the smallest tolerance rates, with coverage values that can be equal to 85% instead of the expected 95% value. The attractive property of RF is that C.I. have been shrunken but the coverage is of 100% resulting in a conservative decision about parameter values.

The last advantage is that no hyperparameter should be chosen. It is a parameter free approach, which is desirable because of the potential difficulty of choosing an appropriate acceptance rate.

The main drawback of the proposed approach concerns joint parameter inference. There are many settings where the joint parameter distribution is of interest and the proposed RF approach cannot handle that. In population genetics for example, estimation of the severity and of the duration of the bottleneck should be estimated jointly because of identifiability issues. The challenge of performing joint parameter inference with RF might constitute a useful research perspective.


[1] Raynal L, Marin J-M, Pudlo P, Ribatet M, Robert CP, Estoup A. 2017. ABC random forests for Bayesian parameter inference. arXiv 1605.05537v4,
[2] Meinshausen N. 2006. Quantile regression forests. Journal of Machine Learning Research 7: 983-999.

13 Nov 2017
article picture

Epidemiological trade-off between intra- and interannual scales in the evolution of aggressiveness in a local plant pathogen population

The pace of pathogens’ adaptation to their host plants

Recommended by based on reviews by Benoit Moury and 1 anonymous reviewer

Because of their shorter generation times and larger census population sizes, pathogens are usually ahead in the evolutionary race with their hosts. The risks linked to pathogen adaptation are still exacerbated in agronomy, where plant and animal populations are not freely evolving but depend on breeders and growers, and are usually highly genetically homogeneous. As a consequence, the speed of pathogen adaptation is crucial for agriculture sustainability. Unraveling the time scale required for pathogens’ adaptation to their hosts would notably greatly improve our estimation of the risks of pathogen emergence, the efficiency of disease control strategies and the design of epidemiological surveillance schemes. However, the temporal scale of pathogen evolution has received much less attention than its spatial scale [1]. In their study of a wheat fungal disease, Suffert et al. [2] reached contrasting conclusions about the pathogen adaptation depending on the time scale (intra- or inter-annual) and on the host genotype (sympatric or allopatric) considered, questioning the experimental assessment of this important problem.

Suffert et al. [2] sampled two pairs of Zymoseptoria tritici (the causal agent of septoria leaf blotch) sub-populations in a bread wheat field plot, representing (i) isolates collected at the beginning or at the end of an epidemic in a single growing season (2009-2010 intra-annual sampling scale) and (ii) isolates collected from plant debris at the end of growing seasons in 2009 and in 2015 (inter-annual sampling scale). Then, they measured in controlled conditions two aggressiveness traits of the isolates of these four Z. tritici sub-populations, the latent period and the lesion size on leaves, on two wheat cultivars. One of the cultivars was considered as "sympatric" because it was at the source of the studied isolates and was predominant in the growing area before the experiment, whereas the other cultivar was considered as "allopatric" since it replaced the previous one and became predominant in the growing area during the sampling period.

On the sympatric host, at the intra-annual scale, they observed a marginally-significant decrease in latent period and a significant decrease of the between-isolate variance for this trait, which are consistent with a selection of pathogen variants with an enhanced aggressiveness. In contrast, at the inter-annual scale, no difference in the mean or variance of aggressiveness trait values was observed on the sympatric host, suggesting a lack of pathogen adaptation. They interpreted the contrast between observations at the two time scales as the consequence of a trade-off for the pathogen between a gain of aggressiveness after several generations of asexual reproduction at the intra-annual scale and a decrease of the probability to reproduce sexually and to be transmitted from one growing season to the next. Indeed, at the end of the growing season, the most aggressive isolates are located on the upper leaves of plants, where the pathogen density and hence probably also the probability to reproduce sexually, is lower. On the allopatric host, the conclusion about the pathogen stability at the inter-annual scale was somewhat different, since a significant increase in the mean lesion size was observed (isolates corresponding to the intra-annual scale were not checked on the allopatric host). This shows the possibility for the pathogen to evolve at the inter-annual scale, for a given aggressiveness trait and on a given host.

In conclusion, Suffert et al.’s [2] study emphasizes the importance of the experimental design in terms of sampling time scale and host genotype choice to analyze the pathogen adaptation to its host plants. It provides also an interesting scenario, at the crossroad of the pathogen’s reproduction regime, niche partitioning and epidemiological processes, to interpret these contrasted results. Pathogen adaptation to plant cultivars with major-effect resistance genes is usually fast, including in the wheat-Z. tritici system [3]. Therefore, this study will be of great help for future studies on pathogen adaptation to plant partial resistance genes and on strategies of deployment of such resistance at the landscape scale.

[1] Penczykowski RM, Laine A-L and Koskella B. 2016. Understanding the ecology and evolution of host–parasite interactions across scales. Evolutionary Applications, 9: 37–52. doi: 10.1111/eva.12294

[2] Suffert F, Goyeau H, Sache I, Carpentier F, Gelisse S, Morais D and Delestre G. 2017. Epidemiological trade-off between intra- and interannual scales in the evolution of aggressiveness in a local plant pathogen population. bioRxiv, 151068, ver. 3 of 12th November 2017. doi: 10.1101/151068

[3] Brown JKM, Chartrain L, Lasserre-Zuber P and Saintenac C. 2015. Genetics of resistance to Zymoseptoria tritici and applications to wheat breeding. Fungal Genetics and Biology, 79: 33–41. doi: 10.1016/j.fgb.2015.04.017

10 Nov 2017
article picture

Rates of Molecular Evolution Suggest Natural History of Life History Traits and a Post-K-Pg Nocturnal Bottleneck of Placentals

A new approach to DNA-aided ancestral trait reconstruction in mammals

Recommended by and

Reconstructing ancestral character states is an exciting but difficult problem. The fossil record carries a great deal of information, but it is incomplete and not always easy to connect to data from modern species. Alternatively, ancestral states can be estimated by modelling trait evolution across a phylogeny, and fitting to values observed in extant species. This approach, however, is heavily dependent on the underlying assumptions, and typically results in wide confidence intervals.

An alternative approach is to gain information on ancestral character states from DNA sequence data. This can be done directly when the trait of interest is known to be determined by a single, or a small number, of major effect genes. In some of these cases it can even be possible to investigate an ancestral trait of interest by inferring and resurrecting ancestral sequences in the laboratory. Examples where this has been successfully used to address evolutionary questions range from the nocturnality of early mammals [1], to the loss of functional uricases in primates, leading to high rates of gout, obesity and hypertension in present day humans [2]. Another possibility is to rely on correlations between species traits and the genome average substitution rate/process. For instance, it is well established that the ratio of nonsynonymous to synonymous substitution rate, dN/dS, is generally higher in large than in small species of mammals, presumably due to a reduced effective population size in the former. By estimating ancestral dN/dS, one can therefore gain information on ancestral body mass (e.g. [3-4]).

The interesting paper by Wu et al. [5] further develops this second possibility of incorporating information on rate variation derived from genomic data in the estimation of ancestral traits. The authors analyse a large set of 1185 genes in 89 species of mammals, without any prior information on gene function. The substitution rate is estimated for each gene and each branch of the mammalian tree, and taken as an indicator of the selective constraint applying to a specific gene in a specific lineage – more constraint, slower evolution. Rate variation is modelled as resulting from a gene effect, a branch effect, and a gene X branch interaction effect, which captures lineage-specific peculiarities in the distribution of functional constraint across genes. The interaction term in terminal branches is regressed to observed trait values, and the relationship is used to predict ancestral traits from interaction terms in internal branches. The power and accuracy of the estimates are convincingly assessed via cross validation. Using this method, the authors were also able to use an unbiased approach to determine which genes were the main contributors to the evolution of the life-history traits they reconstructed.

The ancestors to current placental mammals are predicted to have been insectivorous - meaning that the estimated distribution of selective constraint across genes in basal branches of the tree resembles that of extant insectivorous taxa - consistent with the mainstream palaeontological hypothesis. Another interesting result is the prediction that only nocturnal lineages have passed the Cretaceous/Tertiary boundary, so that the ancestors of current orders of placentals would all have been nocturnal. This suggests that the so-called "nocturnal bottleneck hypothesis" should probably be amended. Similar reconstructions are achieved for seasonality, sociality and monogamy – with variable levels of uncertainty.

The beauty of the approach is to analyse the variance, not only the mean, of substitution rate across genes, and their methods allow for the identification of the genes contributing to trait evolution without relying on functional annotations. This paper only analyses discrete traits, but the framework can probably be extended to continuous traits as well.


[1] Bickelmann C, Morrow JM, Du J, Schott RK, van Hazel I, Lim S, Müller J, Chang BSW, 2015. The molecular origin and evolution of dim-light vision in mammals. Evolution 69: 2995-3003. doi:

[2] Kratzer, JT, Lanaspa MA, Murphy MN, Cicerchi C, Graves CL, Tipton PA, Ortlund EA, Johnson RJ, Gaucher EA, 2014. Evolutionary history and metabolic insights of ancient mammalian uricases. Proceedings of the National Academy of Science, USA 111:3763-3768. doi:

[3] Lartillot N, Delsuc F. 2012. Joint reconstruction of divergence times and life-history evolution in placental mammals using a phylogenetic covariance model. Evolution 66:1773-1787. doi:

[4] Romiguier J, Ranwez V, Douzery EJ, Galtier N. 2013. Genomic evidence for large, long-lived ancestors to placental mammals. Molecular Biology and Evolution 30:5-13. doi:

[5] Wu J, Yonezawa T, Kishino H. 2016. Rates of Molecular Evolution Suggest Natural History of Life History Traits and a Post-K-Pg Nocturnal Bottleneck of Placentals. Current Biology 27: 3025-3033. doi:

07 Nov 2017
article picture

MaxTiC: Fast ranking of a phylogenetic tree by Maximum Time Consistency with lateral gene transfers

Dating nodes in a phylogeny using inferred horizontal gene transfers

Recommended by and based on reviews by Alexandros Stamatakis, Mukul Bansal and 2 anonymous reviewers

Dating nodes in a phylogeny is an important problem in evolution and is typically performed by using molecular clocks and fossil age estimates [1]. The manuscript by Chauve et al. [2] reports a novel method, which uses lateral gene transfers to help ordering nodes in a species tree. The idea is that a lateral gene transfer can only occur between two species living at the same time, which indirectly informs on node relative ages in a phylogeny: the donor species cannot be more recent than the recipient species. Horizontal gene transfers are increasingly recognized as frequent, even in eukaryotes, and especially in micro-organisms that have little fossil records [3-7]. Yet, such an important source of information has been very rarely used so far for inferring relative node ages in phylogenies. In this context, the method by Chauve et al. [2] represents an innovative and original approach to a difficult problem. An obvious limitation of the approach is that it relies on inferences of horizontal transfers, which detection is in itself a difficult problem. Incomplete taxon sampling, or the extinction of the true donor lineage may render patterns difficult to interpret in a temporary fashion. Yet, for clades with no fossils this may be the only piece of information we have at hand, and the growing amount of sequence data is likely to minimize issues derived from incomplete sampling.

The developed method, MaxTiC (for Maximal Time Consistency) [2], represents a very nice application of theoretical developments on the well-known « Feedback Arc Set » computer science problem to the evolutionary question of ordering nodes in a phylogeny. MaxTiC uses as input a species tree and a set of time constraints based on lateral gene transfers inferred using other softwares, and minimizes conflicts between node ordering and these time constraints. The application of MaxTiC on simulated datasets indicated that node ordering was fairly accurate [2]. MaxTiC is implemented in a freely available software, which represents original and relevant contribution to the field of evolutionary biology.


[1] Donoghue P and Smith M, editors. 2003. Telling the evolutionary time. CRC press.

[2] Chauve C, Rafiey A, Davin AA, Scornavacca C, Veber P, Boussau B, Szöllősi GJ, Daubin V and Tannier E. 2017. MaxTiC: Fast ranking of a phylogenetic tree by Maximum Time Consistency with lateral gene transfers. bioRxiv 127548, ver. 6 of 6th November 2017. doi: 10.1101/127548

[3] Ropars J, Rodríguez de la Vega RC, Lopez-Villavicencio M, Gouzy J, Sallet E, Debuchy R, Dupont J, Branca A and Giraud T. 2015. Adaptive horizontal gene transfers between multiple cheese-associated fungi. Current Biology 19, 2562–2569. doi: 10.1016/j.cub.2015.08.025

[4] Novo M, Bigey F, Beyne E, Galeote V, Gavory F, Mallet S, Cambon B, Legras JL, Wincker P, Casaregola S and Dequin S. 2009. Eukaryote-to-eukaryote gene transfer events revealed by the genome sequence of the wine yeast Saccharomyces cerevisiae EC1118. Proceeding of the National Academy of Science USA, 106, 16333–16338. doi: 10.1073/pnas.0904673106

[5] Naranjo-Ortíz MA, Brock M, Brunke S, Hube B, Marcet-Houben M, Gabaldón T. 2016. Widespread inter- and intra-domain horizontal gene transfer of d-amino acid metabolism enzymes in Eukaryotes. Frontiers in Microbiology 7, 2001. doi: 10.3389/fmicb.2016.02001

[6] Alexander WG, Wisecaver JH, Rokas A, Hittinger CT. 2016. Horizontally acquired genes in early-diverging pathogenic fungi enable the use of host nucleosides and nucleotides. Proceeding of the National Academy of Science USA. 113, 4116–4121. doi: 10.1073/pnas.1517242113

[7] Marcet-Houben M, Gabaldón T. 2010. Acquisition of prokaryotic genes by fungal genomes. Trends in Genetics. 26, 5–8. doi: 10.1016/j.tig.2009.11.007

06 Oct 2017
article picture

Evolutionary analysis of candidate non-coding elements regulating neurodevelopmental genes in vertebrates

Combining molecular information on chromatin organisation with eQTLs and evolutionary conservation provides strong candidates for the evolution of gene regulation in mammalian brains

Recommended by based on reviews by Marc Robinson-Rechavi and Charles Danko

In this manuscript [1], Francisco J. Novo proposes candidate non-coding genomic elements regulating neurodevelopmental genes.

What is very nice about this study is the way in which public molecular data, including physical interaction data, is used to leverage recent advances in our understanding to molecular mechanisms of gene regulation in an evolutionary context. More specifically, evolutionarily conserved non coding sequences are combined with enhancers from the FANTOM5 project, DNAse hypersensitive sites, chromatin segmentation, ChIP-seq of transcription factors and of p300, gene expression and eQTLs from GTEx, and physical interactions from several Hi-C datasets. The candidate regulatory regions thus identified are linked to candidate regulated genes, and the author shows their potential implication in brain development.

While the results are focused on a small number of genes, this allows to verify features of these candidates in great detail. This study shows how functional genomics is increasingly allowing us to fulfill the promises of Evo-Devo: understanding the molecular mechanisms of conservation and differences in morphology.


[1] Novo, FJ. 2017. Evolutionary analysis of candidate non-coding elements regulating neurodevelopmental genes in vertebrates. bioRxiv, 150482, ver. 4 of Sept 29th, 2017. doi: 10.1101/150482

05 Oct 2017
article picture

Using Connectivity To Identify Climatic Drivers Of Local Adaptation

A new approach to identifying drivers of local adaptation

Recommended by based on reviews by Ruth Arabelle Hufbauer and Thomas Lenormand

Local adaptation, the higher fitness a population achieves in its local “home” environment relative to other environments is a crucial phase in the divergence of populations, and as such both generates and maintains diversity. Local adaptation is enhanced by selection and genetic variation in the relevant traits, and decreased by gene flow and genetic drift.

Demonstrating local adaptation is laborious, and is typically done with a reciprocal transplant design [1], documenting repeated geographic clines [e.g. 2, 3] also provides strong evidence of local adaptation. Even when well documented, it is often unknown which aspects of the environment impose selection. Indeed, differences in environment between different sites that are measured during studies of local adaptation explain little of the variance in the degree of local adaptation [4]. This poses a problem to population management. Given climate change and habitat destruction, understanding the environmental drivers of local adaptation can be crucially important to conducting successful assisted migration or targeted gene flow.

In this manuscript, Macdonald et al. [5] propose a means of identifying which aspects of the environment select for local adaptation without conducting a reciprocal transplant experiment. The idea is that the strength of relationships between traits and environmental variables that are due to plastic responses to the environment will not be influenced by gene flow, but the strength of trait-environment relationships that are due to local adaptation should decrease with gene flow. This then can be used to reduce the somewhat arbitrary list of environmental variables on which data are available down to a targeted list more likely to drive local adaptation in specific traits. To perform such an analysis requires three things: 1) measurements of traits of interest in a species across locations, 2) an estimate of gene flow between locations, which can be replaced with a biologically meaningful estimate of how well connected those locations are from the point of view of the study species, and 3) data on climate and other environmental variables from across a species’ range, many of which are available on line.

Macdonald et al. [5] demonstrate their approach using a skink (Lampropholis coggeri). They collected morphological and physiological data on individuals from multiple populations. They estimated connectivity among those locations using information on habitat suitability and dispersal potential [6], and gleaned climatic data from available databases and the literature. They find that two physiological traits, the critical minimum and maximum temperatures, show the strongest signs of local adaptation, specifically local adaptation to annual mean precipitation, precipitation of the driest quarter, and minimum annual temperature. These are then aspects of skink phenotype and skink habitats that could be explored further, or could be used to provide background information if migration efforts, for example for genetic rescue [7] were initiated. The approach laid out has the potential to spark a novel genre of research on local adaptation. It its simplest form, knowing that local adaptation is eroded by gene flow, it is intuitive to consider that if connectivity reduces the strength of the relationship between an environmental variable and a trait, that the trait might be involved in local adaptation. The approach is less intuitive than that, however – it relies not connectivity per-se, but the interaction between connectivity and different environmental variables and how that interaction alters trait-environment relationships. The authors lay out a number of useful caveats and potential areas that could use further development. It will be interesting to see how the community of evolutionary biologists responds.


[1] Blanquart F, Kaltz O, Nuismer SL and Gandon S. 2013. A practical guide to measuring local adaptation. Ecology Letters, 16: 1195-1205. doi: 10.1111/ele.12150

[2] Huey RB, Gilchrist GW, Carlson ML, Berrigan D and Serra L. 2000. Rapid evolution of a geographic cline in size in an introduced fly. Science, 287: 308-309. doi: 10.1126/science.287.5451.308

[3] Milesi P, Lenormand T, Lagneau C, Weill M and Labbé P. 2016. Relating fitness to long-term environmental variations in natura. Molecular Ecology, 25: 5483-5499. doi: 10.1111/mec.13855

[4] Hereford, J. 2009. A quantitative survey of local adaptation and fitness trade-offs. The American Naturalist 173: 579-588. doi: 10.1086/597611

[5] Macdonald SL, Llewelyn J and Phillips BL. 2017. Using connectivity to identify climatic drivers of local adaptation. bioRxiv, ver. 4 of October 4, 2017. doi: 10.1101/145169

[6] Macdonald SL, Llewelyn J, Moritz C and Phillips BL. 2017. Peripheral isolates as sources of adaptive diversity under climate change. Frontiers in Ecology and Evolution, 5:88. doi: 10.3389/fevo.2017.00088

[7] Whiteley AR, Fitzpatrick SW, Funk WC and Tallmon DA. 2015. Genetic rescue to the rescue. Trends in Ecology & Evolution, 30: 42-49. doi: 10.1016/j.tree.2014.10.009

29 Sep 2017
article picture

Parallel diversifications of Cremastosperma and Mosannona (Annonaceae), tropical rainforest trees tracking Neogene upheaval of the South American continent

Unravelling the history of Neotropical plant diversification

Recommended by based on reviews by Thomas Couvreur and Hervé Sauquet

South American rainforests, particularly the Tropical Andes, have been recognized as the hottest spot of plant biodiversity on Earth, while facing unprecedented threats from human impact [1,2]. Considerable research efforts have recently focused on unravelling the complex geological, bioclimatic, and biogeographic history of the region [3,4]. While many studies have addressed the question of Neotropical plant diversification using parametric methods to reconstruct ancestral areas and patterns of dispersal, Pirie et al. [5] take a distinct, complementary approach. Based on a new, near-complete molecular phylogeny of two Neotropical genera of the flowering plant family Annonaceae, the authors modelled the ecological niche of each species and reconstructed the history of niche differentiation across the region. The main conclusion is that, despite similar current distributions and close phylogenetic distance, the two genera experienced rather distinct processes of diversification, responding differently to the major geological events marking the history of the region in the last 20 million years (Andean uplift, drainage of Lake Pebas, and closure of the Panama Isthmus).

As a researcher who has not personally worked on Neotropical biogeography, I found this paper captivating and especially enjoyed very much reading the Introduction, which sets out the questions very clearly. The strength of this paper is the near-complete diversity of species the authors were able to sample in each clade and the high-quality data compiled for the niche models. I would recommend this paper as a nice example of a phylogenetic study aimed at unravelling the detailed history of Neotropical plant diversification. While large, synthetic meta-analyses of many clades should continue to seek general patterns [4,6], careful studies restricted on smaller, but well controlled and sampled datasets such as this one are essential to really understand tropical plant diversification in all its complexity.


[1] Antonelli A, and Sanmartín I. 2011. Why are there so many plant species in the Neotropics? Taxon 60, 403–414.

[2] Mittermeier RA, Robles-Gil P, Hoffmann M, Pilgrim JD, Brooks TB, Mittermeier CG, Lamoreux JL and Fonseca GAB. 2004. Hotspots revisited: Earths biologically richest and most endangered ecoregions. CEMEX, Mexico City, Mexico 390pp

[3] Antonelli A, Nylander JAA, Persson C and Sanmartín I. 2009. Tracing the impact of the Andean uplift on Neotropical plant evolution. Proceedings of the National Academy of Science of the USA 106, 9749–9754. doi: 10.1073/pnas.0811421106

[4] Hoorn C, Wesselingh FP, ter Steege H, Bermudez MA, Mora A, Sevink J, Sanmartín I, Sanchez-Meseguer A, Anderson CL, Figueiredo JP, Jaramillo C, Riff D, Negri FR, Hooghiemstra H, Lundberg J, Stadler T, Särkinen T and Antonelli A. 2010. Amazonia through time: Andean uplift, climate change, landscape evolution, and biodiversity. Science 330, 927–931. doi: 10.1126/science.1194585

[5] Pirie MD, Maas PJM, Wilschut R, Melchers-Sharrott H and Chatrou L. 2017. Parallel diversifications of Cremastosperma and Mosannona (Annonaceae), tropical rainforest trees tracking Neogene upheaval of the South American continent. bioRxiv, 141127, ver. 3 of 28th Sept 2017. doi: 10.1101/141127

[6] Bacon CD, Silvestro D, Jaramillo C, Tilston Smith B, Chakrabartye P and Antonelli A. 2015. Biological evidence supports an early and complex emergence of the Isthmus of Panama. Proceedings of the National Academy of Science of the USA 112, 6110–6115. doi: 10.1073/pnas.1423853112

26 Sep 2017
article picture

Lacking conservation genomics in the giant Galápagos tortoise

A genomic perspective is needed for the re-evaluation of species boundaries, evolutionary trajectories and conservation strategies for the Galápagos giant tortoises

Recommended by based on reviews by 4 anonymous reviewers

Genome-wide data obtained from even a small number of individuals can provide unprecedented levels of detail about the evolutionary history of populations and species [1], determinants of genetic diversity [2], species boundaries and the process of speciation itself [3]. Loire and Galtier [4] present a clear example, using the emblematic Galápagos giant tortoise (Chelonoidis nigra), of how multi-species comparative population genomic approaches can provide valuable insights about population structure and species delimitation even when sample sizes are limited but the number of loci is large and distributed across the genome.

Galápagos giant tortoises are endemic to the Galápagos Islands and are currently recognized as an endangered, multi-species complex including both extant and extinct taxa. Taxonomic definitions are based on morphology, geographic isolation and population genetic evidence based on short DNA sequences of the mitochondrial genome (mtDNA) and/or a dozen or so nuclear microsatellite loci [5-8]. The species complex enjoys maximal protection. Population recoveries have been quite successful and spectacular conservation programs based on mitochondrial genes and microsatellites are ongoing. This includes for example individual translocations, breeding program, “hybrid” sterilization or removal, and resurrection of extinct lineages).

In 2013, Loire et al. [9] provided the first population genomic analyses based on genome scale data (~1000 coding loci derived from blood-transcriptomes) from five individuals, encompassing three putative “species”: Chelonnoidis becki, C. porteri and C. vandenburghi. Their results raised doubts about the validity/accuracy of the currently accepted designations of “genetic distinctiveness”. However, the implications for conservation and management have remained unnoticed.

In 2017, Loire and Galtier [4] have re-appraised this issue using an original multi-species comparative population genomic analysis of their previous data set [9]. Based on a comparison of 53 animal species, they show that both the level of genome-wide neutral diversity (πS) and level of population structure estimated using the inbreeding coefficient (F) are much lower than would be expected from a sample covering multiple species. The observed values are more comparable to those typically reported at the “among population” level within a single species such as human (Homo sapiens). The authors go to great length to assess the sensitivity of their method to detect population structure (or lack thereof) and show that their results are robust to potential issues, such as contamination and sequencing errors that can occur with Next Generation Sequencing techniques; and biases related to the small sample size and sub-sampling of individuals. They conclude that published mtDNA and microsatellite-based assessment of population structure and species designations may be biased towards over-splitting.

This manuscript is a very good read as it shows the potential of the now relatively affordable genome-wide data for helping to both resolve and clarify population and species boundaries, illuminate demographic trends, evolutionary trajectories of isolated groups, patterns of connectivity among them, and test for evidence of local adaptation and even reproductive isolation. The comprehensive information provided by genome-wide data can critically inform and assist the development of the best strategies to preserve endangered populations and species. Loire and Galtier [4] make a strong case for applying genomic data to the Galápagos giant tortoises, which is likely to redirect conservation efforts more effectively and at lower cost. The case of the Galápagos giant tortoises is certainly a very emblematic example, which will find an echo in many other endangered species conservation programs.


[1] Li H and Durbin R. 2011. Inference of human population history from individual whole-genome sequences. Nature, 475: 493–496. doi: 10.1038/nature10231

[2] Romiguier J, Gayral P, Ballenghien M, Bernard A, Cahais V, Chenuil A, Chiari Y, Dernat R, Duret L, Faivre N, Loire E, Lourenco JM, Nabholz B, Roux C, Tsagkogeorga G, Weber AA-T, Weinert LA, Belkhir K, Bierne N, Glémin S and Galtier N. 2014. Comparative population genomics in animals uncovers the determinants of genetic diversity. Nature, 515: 261–263. doi: 10.1038/nature13685

[3] Roux C, Fraïsse C, Romiguier J, Anciaux Y, Galtier N and Bierne N. 2016. Shedding light on the grey zone of speciation along a continuum of genomic divergence. PLoS Biology, 14: e2000234. doi: 10.1371/journal.pbio.2000234

[4] Loire E and Galtier N. 2017. Lacking conservation genomics in the giant Galápagos tortoise. bioRxiv 101980, ver. 4 of September 26, 2017. doi: 10.1101/101980

[5] Beheregaray LB, Ciofi C, Caccone A, Gibbs JP and Powell JR. 2003. Genetic divergence, phylogeography and conservation units of giant tortoises from Santa Cruz and Pinzón, Galápagos Islands. Conservation Genetics, 4: 31–46. doi: 10.1023/A:1021864214375

[6] Ciofi C, Milinkovitch MC, Gibbs JP, Caccone A and Powell JR. 2002. Microsatellite analysis of genetic divergence among populations of giant Galápagos tortoises. Molecular Ecology, 11: 2265–2283. doi: 10.1046/j.1365-294X.2002.01617.x

[7] Garrick RC, Kajdacsi B, Russello MA, Benavides E, Hyseni C, Gibbs JP, Tapia W and Caccone A. 2015. Naturally rare versus newly rare: demographic inferences on two timescales inform conservation of Galápagos giant tortoises. Ecology and Evolution, 5: 676–694. doi: 10.1002/ece3.1388

[8] Poulakakis N, Edwards DL, Chiari Y, Garrick RC, Russello MA, Benavides E, Watkins-Colwell GJ, Glaberman S, Tapia W, Gibbs JP, Cayot LJ and Caccone A. 2015. Description of a new Galápagos giant tortoise species (Chelonoidis; Testudines: Testudinidae) from Cerro Fatal on Santa Cruz island. PLoS ONE, 10: e0138779. doi: 10.1371/journal.pone.0138779

[9] Loire E, Chiari Y, Bernard A, Cahais V, Romiguier J, Nabholz B, Lourenço JM and Galtier N. 2013. Population genomics of the endangered giant Galápagos tortoise. Genome Biology, 14: R136. doi: 10.1186/gb-2013-14-12-r136

20 Sep 2017
article picture

An interaction between cancer progression and social environment in Drosophila

Cancer and loneliness in Drosophila

Recommended by based on reviews by Ana Rivero and Silvie Huijben

Drosophila flies may not be perceived as a quintessentially social animal, particularly when compared to their eusocial hymenopteran cousins. Although they have no parental care, division of labour or subfertile caste, fruit flies nevertheless exhibit an array of social phenotypes that are potentially comparable to those of their highly social relatives. In the wild, Drosophila adults cluster around food resources where courtship, mating activity and oviposition occur. Recent work has shown not only that social interactions in these clusters condition many aspects of the behaviour and physiology of the flies [1] but also, and perhaps more unexpectedly, that social isolation has a negative impact on their fitness [2].

Many studies in humans point to the role of social isolation as a source of stress that can induce and accelerate disease progression. The ultimate proof of the connection between social interaction and disease is however mired in confounding variables and alternative explanations so the subject, though crucial, remains controversial. With a series of elegant experiments using Drosophila flies that develop an inducible form of intestinal cancer, Dawson et al [3] show that cancer progresses more rapidly in flies maintained in isolation than in flies maintained with other cancerous flies. Further, cancerous flies kept with non-cancerous flies, fare just as badly as when kept alone. Their experiments suggest that this is due to the combined effect of healthy flies avoiding contact with cancerous flies (even though this is a non-contagious disease), and of cancerous flies having higher quality interactions with other cancerous flies than with healthy ones. Perceived isolation is therefore as pernicious as real isolation when it comes to cancer progression in these flies. Like all good research, this study opens up as many questions as it answers, in particular the why and wherefores of the flies’ extraordinary social behaviour in the face of disease.


[1] Camiletti AL and Thompson GJ. 2016. Drosophila as a genetically tractable model for social insect behavior. Frontiers in Ecology and Evolution, 4: 40. doi: 10.3389/fevo.2016.00040

[2] Ruan H and Wu C-F. 2008. Social interaction-mediated lifespan extension of Drosophila Cu/Zn superoxide dismutase mutants. Proceedings of the National Academy of Sciences, USA, 105: 7506-7510. doi: 10.1073/pnas.0711127105

[3] Dawson E, Bailly T, Dos Santos J, Moreno C, Devilliers M, Maroni B, Sueur C, Casali A, Ujvari B, Thomas F, Montagne J, Mery F. 2017. An interaction between cancer progression and social environment in Drosophila. BiorXiv, 143560, ver. 3 of 19th September 2017. doi: 10.1101/143560

11 Sep 2017
article picture

Less effective selection leads to larger genomes

Colonisation of subterranean ecosystems leads to larger genome in waterlouse (Aselloidea)

Recommended by and

The total amount of DNA utilized to store hereditary information varies immensely among eukaryotic organisms. Single copy genome sizes – disregarding differences due to ploidy - differ by more than three orders of magnitude ranging from a few million nucleotides (Mb) to hundreds of billions (Gb). With the ever-increasing availability of fully sequenced genomes we now know that most of the difference is due either to whole genome duplication or to variation in the abundance of repetitive elements. Regarding repetitive elements, the evolutionary forces underlying the large variation 'allowing' more or less elements in a genome remain largely elusive. A tentative correlation between an organism's complexity (however this may be adequately measured) and genome size, the so called C-value paradox [1], has long been dismissed. Studies testing for selection on secondary phenotypic effects associated with genome size (cell size, metabolic rates, nutrient availability) have yielded mixed results. Nonadaptive theories capitalizing on a role of deleterious insertion-deletion mutations and genetic drift as the main drivers have likewise received mixed support [2-3]. Overall, most evidence was derived from analyses across broad taxonomical scales [4-6].

Lefébure and colleagues [7] take a different approach. They confine their considerations to a homogeneous, restricted taxonomical group, isopod crustaceans of the superfamily Aselloidea. This taxonomic focus allows the authors to circumvent many of the confounding factors such as phylogenetic inertia, life history divergence and mutation rate variation that tend to trouble analyses across broad taxonomic timescales. Another important feature of the chosen system is the evolutionary independent transition of habitat use that has occurred at least 11 times. One group of species inhabits subterranean ecosystems (groundwater), another group thrives on surface water. Populations of the former live in low-energy habitats and are expected to be outnumbered by their surface dwelling relatives. Interestingly – and a precondition for the study - the groundwater species have significantly larger genomes (up to 137%). With this unique set-up, the authors are able to investigate the link between genome size and evolutionary forces related to a proxy of long-term population size by removing many of the confounding factors a priori.

Upfront, we learn that the dN/dS ratio is higher in the groundwater species. This may either suggest prevalent positive selection or lower efficacy of purifying selection (relaxed constraint) in the group of species in which population sizes are expected to be low. Using a series of population genetic analyses the authors provide compelling evidence for the latter. Analyses are carefully conducted and include models for estimating the intensity and frequency of purifying and positive selection, the DoS (direction of selection) and α statistic. Next the authors also exclude the possibility that increased dN/dS of the subterranean groundwater species may be due to nonfunctionalization, which may result from the subterranean lifestyle.

Overall, these analyses suggest relaxed constraint in smaller populations as the most plausible alternative to explain increased dN/dS ratios. In addition to the efficacy of selection, the authors estimate the timing of the ecological transition under the rationale that the amount of time a species may have been exposed to the subterranean habitat may reflect long term population sizes. To calibrate the 'colonization clock' they apply a neat trick based on the degree of degeneration of the opsin gene (as vision tends to get lost in these habitats). When finally testing which parameters may explain differences in genome size all factors – ecological status, selection efficiency as measured by dN/dS and colonization time - turned out to be significant predictors. Direct estimates of the short term effective population size Ne from polymorphism data, however, did not correlate with genome size. Ruling out the effect of other co-variates such as body size and growth rate the authors conclude that genome size was overall best predicted by long-term population size change upon habitat shift. In that the authors provide convincing evidence that the increase in genome size is linked to a decrease in long-term reduction of selection efficiency of subterranean species. Assuming a bias for insertion mutations over deletion mutations (which is usually the case in eukaryotes) this result is in agreement with the theory of mutational hazard [4-6]. This theory proposed by Michael Lynch postulates that the accumulation of non-functional DNA has a weak deleterious effect that can only be efficiently opposed by natural selection in species with high Ne.

In conclusion, Lefébure and colleagues provide novel and welcome evidence supporting a 'neutralist' hypothesis of genome size evolution without the need to invoke an adaptive component. Methodologically, the study cautions against the common use of polymorphism-based estimates of Ne which are often obfuscated by transitory demographic change. Instead, alternative measures of selection efficacy linked to long-term population size may serve as better predictors of genome size. We hope that this study will stimulate additional work testing the link between Ne and genome size variation in other taxonomical groups [8-9]. Using genome sequences instead of the transcriptome approach applied here may concomitantly further our understanding of the molecular mechanisms underlying genome size change.


[1] Thomas, CA Jr. 1971. The genetic organization of chromosomes. Annual Review of Genetics 5: 237–256. doi: 10.1146/

[2] Ågren JA, Greiner S, Johnson MTJ, Wright SI. 2015. No evidence that sex and transposable elements drive genome size variation in evening primroses. Evolution 69: 1053–1062. doi: 10.1111/evo.12627

[3] Bast J, Schaefer I, Schwander T, Maraun M, Scheu S, Kraaijeveld K. 2016. No accumulation of transposable elements in asexual arthropods. Molecular Biology and Evolution 33: 697–706. doi: 10.1093/molbev/msv261

[4] Lynch M. 2007. The Origins of Genome Architecture. Sinauer Associates.

[5] Lynch M, Bobay LM, Catania F, Gout JF, Rho M. 2011. The repatterning of eukaryotic genomes by random genetic drift. Annual Review of Genomics and Human Genetics 12: 347–366. doi: 10.1146/annurev-genom-082410-101412

[6] Lynch M, Conery JS. 2003. The origins of genome complexity. Science 302: 1401–1404. doi: 10.1126/science.1089370

[7] Lefébure T, Morvan C, Malard F, François C, Konecny-Dupré L, Guéguen L, Weiss-Gayet M, Seguin-Orlando A, Ermini L, Der Sarkissian C, Charrier NP, Eme D, Mermillod-Blondin F, Duret L, Vieira C, Orlando L, and Douady CJ. 2017. Less effective selection leads to larger genomes. Genome Research 27: 1016-1028. doi: 10.1101/gr.212589.116

[8] Lower SS, Johnston JS, Stanger-Hall KF, Hjelmen CE, Hanrahan SJ, Korunes K, Hall D. 2017. Genome size in North American fireflies: Substantial variation likely driven by neutral processes. Genome Biolology and Evolution 9: 1499–1512. doi: 10.1093/gbe/evx097

[9] Sessegolo C, Burlet N, Haudry A. 2016. Strong phylogenetic inertia on genome size and transposable element content among 26 species of flies. Biology Letters 12: 20160407. doi: 10.1098/rsbl.2016.0407

03 Aug 2017
article picture

Fisher's geometrical model and the mutational patterns of antibiotic resistance across dose gradients

What doesn’t kill us makes us stronger: can Fisher’s Geometric model predict antibiotic resistance evolution?

Recommended by and

The increasing number of reported cases of antibiotic resistance is one of today’s major public health concerns. Dealing with this threat involves understanding what drives the evolution of antibiotic resistance and investigating whether we can predict (and subsequently avoid or circumvent) it [1].
One of the most illustrative and common models of adaptation (and, hence, resistance evolution) is Fisher’s Geometric Model (FGM). The original model maps phenotypes to fitness, meaning that each point in the fitness landscape corresponds to a phenotype rather than a genotype. However, it has been shown that when mutations are numerous enough, FGM can also describe adaptive walks in genotype space [2]. Nevertheless, limitations have been highlighted, particularly when trying to study complex scenarios such as antibiotic resistance evolution [3].
Harmand et al. [4] incorporated three extensions to the FGM, which allowed them to match the mutational patterns of antibiotic resistance that they obtained from a screen across a gradient of drug concentrations. The implemented extensions took into account that: 1) only a subset of mutations may contribute to traits under selection, reflecting that not all regions in the genome affect the ability to resist antibiotics; 2) mutations that confer a fitness increase in one environment may not reflect a similar increase in others, if the selective constraints are different; and 3) different antibiotic concentrations may either constrain the maximum fitness that populations can reach (changing the height of the fitness peak) or change the rate of fitness increase with each mutation (changing the width/slope of the peak).
Traditionally, most empirical fitness landscape studies have focused on a subset of mutations obtained after laboratory evolution in specific conditions [5, 6]. The results obtained in Harmand et al. [4] indicate a potential shortcoming of studying these small fitness landscapes: rather than having a constrained evolutionary path to a resistant phenotype, as previously observed, their results suggest that antibiotic resistance can be the product of mutations in different regions of the genome. Returning to the fitness landscape perspective, this indicates that there are many alternative paths that can lead to the evolution of antibiotic resistance. This comparison points at a difficult challenge when aiming at developing a predictive framework for evolution: real-time experiments may indicate that evolution is likely to take similar and predictable paths because the strongest and most frequent mutations dictate the outcome, whereas systematic screens of mutants potentially indicate several paths, that may, however, not be relevant in nature. Only a combination of different experimental approaches with motivated theory as presented in Harmand et al. [4] will allow for a better understanding of where in this continuum evolution is taking place in nature, and to which degree we are able to interfere with it in order to slow down adaptation.


[1] Palmer AC, and Kishony R. 2013. Understanding, predicting and manipulating the genotypic evolution of antibiotic resistance. Nature Review Genetics 14: 243—248. doi: 10.1038/nrg3351

[2] Tenaillon O. 2014. The utility of Fisher’s geometric model in evolutionary genetics. Annual Review of Ecology, Evolution and Systematics 45: 179—201. doi: 10.1146/annurev-ecolsys-120213-091846

[3] Blanquart F and Bataillon T. 2016. Epistasis and the structure of fitness landscapes: are experimental fitness landscapes compatible with Fisher’s geometric model? Genetics 203: 847—862. doi: 10.1534/genetics.115.182691

[4] Harmand N, Gallet R, Jabbour-Zahab R, Martin G and Lenormand T. 2017. Fisher’s geometrical model and the mutational patterns of antibiotic resistance across dose gradients. Evolution 71: 23—37. doi: 10.1111/evo.13111

[5] de Visser, JAGM, and Krug J. 2014. Empirical fitness landscapes and the predictability of evolution. Nature 15: 480—490. doi: 10.1038/nrg3744

[6] Palmer AC, Toprak E, Baym M, Kim S, Veres A, Bershtein S and Kishony R. 2015. Delayed commitment to evolutionary fate in antibiotic resistance fitness landscapes. Nature Communications 6: 1—8. doi: 10.1038/ncomms8385

31 Jul 2017
article picture

Selection on morphological traits and fluctuating asymmetry by a fungal parasite in the yellow dung fly

Parasite-mediated selection promotes small body size in yellow dung flies

Recommended by based on reviews by Rodrigo Medel and 1 anonymous reviewer

Body size has long been considered as one of the most important organismic traits influencing demographical processes, population size, and evolution of life history strategies [1, 2]. While many studies have reported a selective advantage of large body size, the forces that determine small-sized organisms are less known, and reports of negative selection coefficients on body size are almost absent at present. This lack of knowledge is unfortunate as climate change and energy demands in stressful environments, among other factors, may produce new selection scenarios and unexpected selection surfaces [3]. In this manuscript, Blanckenhorn [4] reports on a potential explanation for the surprising 10% body size decrease observed in a Swiss population of yellow dung flies during 1993 - 2009. The author took advantage of a fungus outbreak in 2002 to assess the putative role of the fungus Entomopthora scatophagae, a specific parasite of adult yellow dung flies, as selective force acting upon host body size. His findings indicate that, as expected by sexual selection theory, large males experience a mating advantage. However, this positive sexual selection is opposed by a strong negative selection on male and female body size through the viability fitness component. This study provides the first evidence of parasite-mediated disadvantage of large adult body size in the field. While further experimental work is needed to elucidate the exact causes of body size reduction in the population, the author proposes a variation of the trade-off hypothesis raised by Rantala & Roff [5] that large-sized individuals face an immunity cost due to their high absolute energy demands in stressful environments.


[1] Peters RH. 1983. The ecological implications of body size. Cambridge University Press, Cambridge.

[2] Schmidt-Nielsen K. 1984. Scaling: why is animal size so important? Cambridge University Press, Cambridge.

[3] Ohlberger J. 2013. Climate warming and ectotherm body size: from individual physiology to community ecology. Functional Ecology 27: 991-1001. doi: 10.1111/1365-2435.12098

[4] Blanckenhorn WU. 2017. Selection on morphological traits and fluctuating asymmetry by a fungal parasite in the yellow dung fly. bioRxiv 136325, ver. 2 of 29th June 2017. doi: 10.1101/136325

[5] Rantala MJ & Roff DA. 2005. An analysis of trade-offs in immune function, body size and development time in the Mediterranean field cricket, Gryllus bimaculatus. Functional Ecology 19: 323-330. doi: 10.1111/j.1365-2435.2005.00979.x

12 Jul 2017
article picture

Assortment of flowering time and defense alleles in natural Arabidopsis thaliana populations suggests co-evolution between defense and vegetative lifespan strategies

Towards an integrated scenario to understand evolutionary patterns in A. thaliana

Recommended by based on reviews by Rafa Rubio de Casas and Xavier Picó

Nobody can ignore that a full understanding of evolution requires an integrated approach from both conceptual and methodological viewpoints. Although some life-history traits, e.g. flowering time, have long been receiving more attention than others, in many cases because the former are more workable than the latter, we must acknowledge that our comprehension about how evolution works is strongly biased and limited. In the Arabidopsis community, such an integration is making good progress as an increasing number of research groups worldwide are changing the way in which evolution is put to the test.

This manuscript [1] is a good example of that as the authors raise an important issue in evolutionary biology by combining gene expression and flowering time data from different sources. In particular, the authors explore how variation in flowering time, which determines lifespan, and host immunity defenses co-vary, which is interpreted in terms of co-evolution between the two traits. Interestingly, the authors go beyond that pattern by separating lifespan-dependent from lifespan–independent defense genes, and by showing that defense genes with variants known to impact fitness in the field are among the genes whose expression co-varies most strongly with flowering time. Finally, these results are supported by a simple mathematical model indicating that such a relationship can also be expected theoretically.

Overall, the readers will find many conceptual and methodological elements of interest in this manuscript. The idea that evolution is better understood under the scope of life history variation is really exciting and challenging, and in my opinion on the right track for disentangling the inherent complexities of evolutionary research. However, only when we face complexity, we also face its costs and burdens. In this particular case, the well-known co-variation between seed dormancy and flowering time is a missing piece, as well as the identification of (variation in) putative selective pressures accounting for the co-evolution between defense mechanisms and life history (seed dormancy vs. flowering time) along environmental gradients. More intellectual, technical and methodological challenges that with no doubt are totally worth it.


[1] Glander S, He F, Schmitz G, Witten A, Telschow A, de Meaux J. 2017. Assortment of flowering time and defense alleles in natural Arabidopsis thaliana populations suggests co-evolution between defense and vegetative lifespan strategies. bioRxiv ver.1 of June 19, 2017. doi: 10.1101/131136

12 Jul 2017
article picture

Despite reproductive interference, the net outcome of reproductive interactions among spider mite species is not necessarily costly

The pros and cons of mating with strangers

Recommended by based on reviews by Joël Meunier and Michael D Greenfield


Interspecific matings are by definition rare events in nature, but when they occur they can be very important, and not only because they might condition gene flow between species. Even when such matings have no genetic consequence, for instance if they do not yield any fertile hybrid offspring, they can still have an impact on the population dynamics of the species involved [1]. Such atypical pairings between heterospecific partners are usually regarded as detrimental or undesired; as they interfere with the occurrence or success of intraspecific matings, they are expected to cause a decline in absolute fitness.
The story is not always so simple however, and it might all depend on the timing of events and on the identity of the partners. Using the herbivorous mite Tetranychus urticae as a model, Clemente et al. [2] experimentally arranged matings with two other Tetranychus species that commonly share the same host plants as T. urticae. They carefully controlled the history of events: heterospecific matings could occur just before, just after, 24h before, or 24h after, a conspecific mating. Interestingly, the oviposition rate (total fecundity) of females was increased when mating with a heterospecific individual. This suggests that heterospecic sperm can stimulate oogenesis just as conspecific sperm does. Such a positive effect was observed for matings involving T. ludeni females and T. urticae males, but a negative effect is found in the interaction with T. evansi. Sex-ratio (fertilization success in those species) could also be impacted but, unlike fertilization, this occurred when the mating events were distant in time. This is is at odds with what is observed in conspecific matings, where sperm displacement occurs only if mating events are temporally close. Overall, the effects of heterospecific mating were quite variable and it is challenging to predict a single, general, effect of interspecific matings. The net effect will likely be context-dependent, depending on the relative frequency of the difference mating sequences and on how fecundity and sex-ratio contribute to overall fitness, both aspect strongly influenced by the population dynamics and structure.


[1] Gröning J. & Hochkirch A. 2008. Reproductive interference between animal species. The Quarterly Review of Biology 83: 257-282. doi: 10.1086/590510

[2] Clemente SH, Santos I, Ponce AR, Rodrigues LR, Varela SAM & Magalhaes S. 2017 Despite reproductive interference, the net outcome of reproductive interactions among spider mite species is not necessarily costly. bioRxiv 113274, ver. 4 of the 30th of June 2017. doi: 10.1101/113274

07 Jul 2017
article picture

Negative frequency-dependent selection is frequently confounding

Unmasking the delusive appearance of negative frequency-dependent selection

Recommended by based on reviews by David Baltrus and 2 anonymous reviewers

Explaining the processes that maintain polymorphisms in a population has been a fundamental line of research in evolutionary biology. One of the main mechanisms identified that preserves genetic diversity is negative frequency-dependent selection (NFDS), which constitutes a powerful framework for interpreting the presence of persistent polymorphisms. Nevertheless, a number of patterns that are often explained by invoking NFDS may also be compatible with, and possibly more easily explained by, different processes.
In the present manuscript [1], Brisson acknowledges first that genuine NFDS has been instrumental for our understanding on the dynamics that perpetuate polymorphisms, and that the power and importance of NFDS cannot be disregarded. Second, the author aims at identifying certain of the processes that may result in maintenance of genetic diversity, and whose outcome may be mistaken for NFDS, namely directional selection in changing environments, density-dependent fitness, multiple niche selection and community diversity. The author claims that systematic resort to NFDS as explanatory device may have lead to its application to systems where it does not apply or that do not fulfil the basic assumptions of NFDS. The author struggles in the text to provide with a precise, verbal definition of NFDS, and the exchanges with the reviewers during the recommendation process show that agreeing on such a verbal definition of NFDS is not trivial. Probably a profound mathematical formulation of the varying value of a genotype’s fitness relative to other competing ones as a function of their frequency (developing further the synthesis by Heino [2]) may still be wanting. Indeed, the text is intended for a broad audience of evolutionary biologists with operational mathematical knowledge and interest in models, rather than for modellers or biomathematicians. Nevertheless, the manuscript is rich in references to original literature, elaborates on interesting lines of thought and discussion and will hopefully trigger novel experimental and formal research to clarify the role of NFDS and to discern between alternative mechanisms that may render similar patterns of maintenance of genetic diversity.


[1] Brisson D. 2017. Negative frequency-dependent selection is frequently confounding. bioRxiv 113324, ver. 3 of 20th June 2017. doi: 10.1101/113324

[2] Heino M, Metz JAJ and Kaitala V. 1998. The enigma of frequency-dependent selection. Trends in Ecology & Evolution 13: 367-370. doi: 1016/S0169-5347(98)01380-9

12 Jun 2017
article picture

Evolution and manipulation of vector host choice

Modelling the evolution of how vector-borne parasites manipulate the vector's host choice

Recommended by based on reviews by Samuel Alizon and Nicole Mideo

Many parasites can manipulate their hosts, thus increasing their transmission to new hosts [1]. This is particularly the case for vector-borne parasites, which can alter the feeding behaviour of their hosts. However, predicting the optimal strategy is not straightforward because three actors are involved and the interests of the parasite may conflict with that of the vector. There are few models that consider the evolution of host manipulation by parasites [but see 2-4], but there are virtually none that investigated how parasites can manipulate the host choice of vectors. Even on the empirical side, many aspects of this choice remain unknown. Gandon [5] develops a simple evolutionary epidemiology model that allows him to formulate clear and testable predictions. These depend on which actor controls the trait (the vector or the parasite) and, when there is manipulation, whether it is realised via infected hosts (to attract vectors) or infected vectors (to change host choice). In addition to clarifying the big picture, Gandon [5] identifies some nice properties of the model, for instance an independence of the density/frequency-dependent transmission assumption or a backward bifurcation at R0=1, which suggests that parasites could persist even if their R0 is driven below unity. Overall, this study calls for further investigation of the different scenarios with more detailed models and experimental validation of general predictions.


[1] Hughes D, Brodeur J, Thomas F. 2012. Host manipulation by parasites. Oxford University Press.

[2] Brown SP. 1999. Cooperation and conflict in host-manipulating parasites. Proceedings of the Royal Society of London B: Biological Sciences 266: 1899–1904. doi: 10.1098/rspb.1999.0864

[3] Lion S, van Baalen M, Wilson WG. 2006. The evolution of parasite manipulation of host dispersal. Proceedings of the Royal Society of London B: Biological Sciences. 273: 1063–1071. doi: 10.1098/rspb.2005.3412

[4] Vickery WL, Poulin R. 2010. The evolution of host manipulation by parasites: a game theory analysis. Evolutionary Ecology 24: 773–788. doi: 10.1007/s10682-009-9334-0

[5] Gandon S. 2017. Evolution and manipulation of vector host choice. bioRxiv 110577, ver. 3 of 7th June 2017. doi: 10.1101/110577

22 May 2017
article picture

Can Ebola Virus evolve to be less virulent in humans?

A new hypothesis to explain Ebola's high virulence

Recommended by and based on reviews by Virginie Ravigné and François Blanquart


The tragic 2014-2016 Ebola outbreak that resulted in more than 28,000 cases and 11,000 deaths in West Africa [1] has been a surprise to the scientific community. Before 2013, the Ebola virus (EBOV) was known to produce recurrent outbreaks in remote villages near tropical rainforests in Central Africa, never exceeding a few hundred cases with very high virulence. Both EBOV’s ability to circulate for several months in large urban human populations and its important mutation rate suggest that EBOV’s virulence could evolve and to some extent adapt to human hosts [2]. Up to now, the high virulence of EBOV in humans was generally thought to be maladaptive, the virus being adapted to circulating in wild animal populations (e.g. fruit bats [3]). As a logical consequence, EBOV virulence could be expected to decrease during long epidemics in humans. The present paper by Sofonea et al. [4] challenges this view and explores how, given EBOV’s life cycle and known epidemiological parameters, virulence is expected to evolve in the human host during long epidemics. The main finding of the paper is that there is no chance that EBOV’s virulence decreases in the short and long terms. The main underlying mechanism is that EBOV is also transmitted by dead bodies, which limits the cost of virulence. In itself the idea that selection should select for higher virulence in diseases that are also transmitted after host death will sound intuitive for most evolutionary epidemiologists. The accomplishment of the paper is to make a very strong case that the parameter range where virulence could decrease is very small. The paper further provides scientifically grounded arguments in favor of the safe management of corpses. Safe burial of corpses is culturally difficult to impose. The present paper shows that in addition to instantaneously decreasing the spread of the virus, safe burial may limit virulence increase in the short term and favor of less virulent strains in the long term. Altogether these results make a timely and important contribution to the knowledge and understanding of EBOV.


[1] World Health Organization. 2016. WHO: Ebola situation report - 10 June 2016.

[2] Kupferschmidt K. 2014. Imagining Ebola’s next move. Science 346: 151–152. doi: 10.1126/science.346.6206.151

[3] Leroy EM, Kumulungui B, Pourrut X, Rouquet P, Hassanin A, Yaba P, Délicat A, Paweska, Gonzalez JP and Swanepoel R. 2005. Fruit bats as reservoirs of Ebola virus. Nature 438: 575–576. doi: 10.1038/438575a

[4] Sofonea MT, Aldakak L, Boullosa LFVV and Alizon S. 2017. Can Ebola Virus evolve to be less virulent in humans? bioRxiv 108589, ver. 3 of 19th May 2017; doi: 10.1101/108589

12 Apr 2017
article picture

Genetic drift, purifying selection and vector genotype shape dengue virus intra-host genetic diversity in mosquitoes

Vectors as motors (of virus evolution)

Recommended by and

Many viruses are transmitted by biological vectors, i.e. organisms that transfer the virus from one host to another. Dengue virus (DENV) is one of them. Dengue is a mosquito-borne viral disease that has rapidly spread around the world since the 1940s. One recent estimate indicates 390 million dengue infections per year [1]. As many arthropod-borne vertebrate viruses, DENV has to cross several anatomical barriers in the vector, to multiply in its body and to invade its salivary glands before getting transmissible. As a consequence, vectors are not