Latest recommendations
| Id | Title | Authors | Abstract | Picture | Thematic fields | Recommender | Reviewers | Submission date | |
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23 Jan 2023
The genetic architecture of local adaptation in a clineEnvironmental and fitness landscapes matter for the genetic basis of local adaptationRecommended by Charles Mullon 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. References [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. https://doi.org/10.1101/2022.06.30.498280 | The genetic architecture of local adaptation in a cline | Fabien Laroche, Thomas Lenormand | <p>Local adaptation is pervasive. It occurs whenever selection favors different phenotypes in different environments, provided that there is genetic variation for the corresponding traits and that the effect of selection is greater than the effect... | | Adaptation, Evolutionary Theory, Genome Evolution, Molecular Evolution, Population Genetics / Genomics, Quantitative Genetics | Charles Mullon | 2022-07-07 08:46:47 | ||
18 Jan 2023
The fate of recessive deleterious or overdominant mutations near mating-type loci under partial selfingMaintenance of deleterious mutations and recombination suppression near mating-type loci under selfingRecommended by Aurelien Tellier based on reviews by 3 anonymous reviewersThe 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. References Antonovics J, Abrams JY (2004) Intratetrad Mating and the Evolution of Linkage Relationships. Evolution, 58, 702–709. https://doi.org/10.1111/j.0014-3820.2004.tb00403.x Bergero R, Charlesworth D (2009) The evolution of restricted recombination in sex chromosomes. Trends in Ecology & Evolution, 24, 94–102. https://doi.org/10.1016/j.tree.2008.09.010 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. https://doi.org/10.1111/j.1558-5646.1990.tb03839.x Charlesworth D, Charlesworth B, Marais G (2005) Steps in the evolution of heteromorphic sex chromosomes. Heredity, 95, 118–128. https://doi.org/10.1038/sj.hdy.6800697 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. https://doi.org/10.1098/rspb.1999.0603 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. https://doi.org/10.1111/nph.17039 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. https://doi.org/10.1038/s41588-020-00771-1 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. https://doi.org/10.1371/journal.pbio.3001698 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. https://doi.org/10.1093/molbev/msw127 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. https://doi.org/10.1534/genetics.109.102707 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. https://doi.org/10.1371/journal.pbio.0030004 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. https://doi.org/10.1101/2022.10.07.511119 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. https://doi.org/10.1038/s41559-019-1081-1 | The fate of recessive deleterious or overdominant mutations near mating-type loci under partial selfing | Emilie Tezenas, Tatiana Giraud, Amandine Veber, Sylvain Billiard | <p style="text-align: justify;">Large regions of suppressed recombination having extended over time occur in many organisms around genes involved in mating compatibility (sex-determining or mating-type genes). The sheltering of deleterious alleles... | | Evolutionary Dynamics, Evolutionary Ecology, Evolutionary Theory, Genome Evolution, Population Genetics / Genomics, Reproduction and Sex | Aurelien Tellier | 2022-10-10 13:50:30 | ||
05 Jan 2023
Promoting extinction or minimizing growth? The impact of treatment on trait trajectories in evolving populationsTrait trajectories in evolving populations: insights from mathematical modelsRecommended by Dominik Wodarz based on reviews by Rob Noble and 3 anonymous reviewersThe 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. References [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. https://doi.org/10.1101/2022.06.17.496570 [2] Gatenby RA, Silva AS, Gillies RJ, Frieden BR (2009) Adaptive Therapy. Cancer Research, 69, 4894–4903. https://doi.org/10.1158/0008-5472.CAN-08-3658 [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. https://doi.org/10.1158/0008-5472.CAN-20-0806 | Promoting extinction or minimizing growth? The impact of treatment on trait trajectories in evolving populations | Michael Raatz, Arne Traulsen | <p style="text-align: justify;">When cancers or bacterial infections establish, small populations of cells have to free themselves from homoeostatic regulations that prevent their expansion. Trait evolution allows these populations to evade this r... | | Evolutionary Dynamics, Evolutionary Ecology, Evolutionary Theory | Dominik Wodarz | 2022-06-18 08:44:37 | ||
20 Dec 2022
How does the mode of evolutionary divergence affect reproductive isolation?A general model of fitness effects following hybridisationRecommended by Matthew Hartfield based on reviews by Luis-Miguel Chevin and Juan LiStudying 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.
References 1. Coyne JA, Orr HA. Speciation. Sunderland, Mass: Sinauer Associates; 2004. | How does the mode of evolutionary divergence affect reproductive isolation? | Bianca De Sanctis, Hilde Schneemann, John J. Welch | <p>When divergent populations interbreed, the outcome will be affected by the genomic and phenotypic differences that they have accumulated. In this way, the mode of evolutionary divergence between populations may have predictable consequences for... | | Adaptation, Evolutionary Theory, Hybridization / Introgression, Population Genetics / Genomics, Speciation | Matthew Hartfield | 2022-03-30 14:55:46 | ||
16 Dec 2022
Conditions for maintaining and eroding pseudo-overdominance and its contribution to inbreeding depressionPseudo-overdominance: how linkage and selection can interact and oppose to purging of deleterious mutations.Recommended by Sylvain Glémin based on reviews by Yaniv Brandvain, Lei Zhao and 1 anonymous reviewerMost 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. References
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. https://doi.org/10.1101/2021.12.16.473022 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. https://doi.org/10.1016/j.cub.2019.11.063 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. https://doi.org/10.1016/j.tree.2020.03.002 Ohta T, Kimura M (1969) Linkage disequilibrium at steady state determined by random genetic drift and recurrent mutation. Genetics, 63, 229–238. https://doi.org/10.1093/genetics/63.1.229 Uyenoyama MK, Waller DM (1991) Coevolution of self-fertilization and inbreeding depression II. Symmetric overdominance in viability. Theoretical Population Biology, 40, 47–77. https://doi.org/10.1016/0040-5809(91)90046-I Waller DM (2021) Addressing Darwin’s dilemma: Can pseudo-overdominance explain persistent inbreeding depression and load? Evolution, 75, 779–793. https://doi.org/10.1111/evo.14189 Zhao L, Charlesworth B (2016) Resolving the Conflict Between Associative Overdominance and Background Selection. Genetics, 203, 1315–1334. https://doi.org/10.1534/genetics.116.188912 | Conditions for maintaining and eroding pseudo-overdominance and its contribution to inbreeding depression | Diala Abu Awad, Donald Waller | <p style="text-align: justify;">Classical models that ignore linkage predict that deleterious recessive mutations should purge or fix within inbred populations, yet inbred populations often retain moderate to high segregating load. True overdomina... | | Evolutionary Dynamics, Evolutionary Theory, Genome Evolution, Hybridization / Introgression, Population Genetics / Genomics, Reproduction and Sex | Sylvain Glémin | 2022-01-04 12:15:35 | ||
29 Nov 2022
Joint inference of adaptive and demographic history from temporal population genomic dataInference of genome-wide processes using temporal population genomic dataRecommended by Aurelien Tellier based on reviews by Lawrence Uricchio and 2 anonymous reviewersEvolutionary 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. References 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. https://doi.org/10.1371/journal.pbio.3001669 Kern AD, Hahn MW (2018) The Neutral Theory in Light of Natural Selection. Molecular Biology and Evolution, 35, 1366–1371. https://doi.org/10.1093/molbev/msy092 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. https://doi.org/10.1093/molbev/msab050 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. https://doi.org/10.1101/2021.03.12.435133 Li H, Durbin R (2011) Inference of human population history from individual whole-genome sequences. Nature, 475, 493–496. https://doi.org/10.1038/nature10231 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. https://doi.org/10.1093/molbev/msz038 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. https://doi.org/10.1093/bioinformatics/btv684 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. https://doi.org/10.1093/bioinformatics/bty867 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. https://doi.org/10.1111/1755-0998.13224 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. https://doi.org/10.1371/journal.pgen.1004775 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. https://doi.org/10.1093/gbe/evy007 Jorde PE, Ryman N (2007) Unbiased Estimator for Genetic Drift and Effective Population Size. Genetics, 177, 927–935. https://doi.org/10.1534/genetics.107.075481 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. https://doi.org/10.1111/1755-0998.12280 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. https://doi.org/10.1073/pnas.1919039117 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. https://doi.org/10.1371/journal.pgen.1008698 | Joint inference of adaptive and demographic history from temporal population genomic data | Vitor A. C. Pavinato, Stéphane De Mita, Jean-Michel Marin, Miguel de Navascués | <p style="text-align: justify;">Disentangling the effects of selection and drift is a long-standing problem in population genetics. Simulations show that pervasive selection may bias the inference of demography. Ideally, models for the inference o... | | Adaptation, Population Genetics / Genomics | Aurelien Tellier | 2021-10-20 09:41:26 | ||
21 Nov 2022
Artisanal and farmers bread making practices differently shape fungal species community composition in French sourdoughsThe variety of bread-making practices promotes diversity conservation in food microbial communitiesRecommended by Tatiana Giraud and Jeanne Ropars based on reviews by 2 anonymous reviewersDomesticated 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]. References [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. https://doi.org/10.1128/microbiolspec.FUNK-0030-2016 [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. https://doi.org/10.1093/molbev/msy066 [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. https://doi.org/10.3390/genes13020230 [4] Fay JC, Benavides JA (2005) Evidence for Domesticated and Wild Populations of Saccharomyces cerevisiae. PLOS Genetics, 1, e5. https://doi.org/10.1371/journal.pgen.0010005 [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. https://doi.org/10.1016/j.cub.2015.08.025 [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. https://doi.org/10.1111/mec.15359 [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. https://doi.org/10.1016/j.cub.2020.08.082 [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. https://doi.org/10.1016/j.ijfoodmicro.2021.109174 [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. https://doi.org/10.1111/evo.13015 [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. https://doi.org/10.1101/679472 [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. https://doi.org/10.1016/j.tree.2012.10.017 [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. https://doi.org/10.1111/j.1752-4571.2012.00257.x [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. http://journals.openedition.org/rac/24953 | Artisanal and farmers bread making practices differently shape fungal species community composition in French sourdoughs | Elisa Michel, Estelle Masson, Sandrine Bubbendorf, Leocadie Lapicque, Thibault Nidelet, Diego Segond, Stephane Guezenec, Therese Marlin, Hugo deVillers, Olivier Rue, Bernard Onno, Judith Legrand, Delphine Sicard | <p style="text-align: justify;">Preserving microbial diversity in food systems is one of the many challenges to be met to achieve food security and quality. Although industrialization led to the selection and spread of specific fermenting microbia... | | Adaptation, Evolutionary Applications, Evolutionary Ecology | Tatiana Giraud | 2022-01-27 14:53:08 | ||
18 Nov 2022
Fitness costs and benefits in response to artificial artesunate selection in PlasmodiumThe importance of understanding fitness costs associated with drug resistance throughout the life cycle of malaria parasitesRecommended by Silvie Huijben based on reviews by Sarah Reece and Marianna SzucsAntimalarial 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. References [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. https://doi.org/10.1371/journal.ppat.1003578 [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. https://doi.org/10.1093/infdis/jiaa368 | Fitness costs and benefits in response to artificial artesunate selection in Plasmodium | Villa M, Berthomieu A, Rivero A | <p style="text-align: justify;">Drug resistance is a major issue in the control of malaria. Mutations linked to drug resistance often target key metabolic pathways and are therefore expected to be associated with biological costs. The spread of dr... | | Evolutionary Applications, Life History | Silvie Huijben | 2022-01-31 13:01:16 | ||
16 Nov 2022
Divergence of olfactory receptors associated with the evolution of assortative mating and reproductive isolation in miceTinder in mice: A match made with the sense of smellRecommended by Christelle Fraïsse based on reviews by Angeles de Cara, Ludovic Claude Maisonneuve 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. https://doi.org/10.1111/j.1365-294X.2011.05080.x Bierne N, Roze D, Welch JJ (2013) Pervasive selection or is it…? why are FST outliers sometimes so frequent? Mol Ecol 22: 2061–2064. https://doi.org/10.1111/mec.12241 Butlin RK, Smadja CM (2018) Coupling, Reinforcement, and Speciation. Am Nat 191:155–172. https://doi.org/10.1086/695136 Gautier M (2015) Genome-Wide Scan for Adaptive Divergence and Association with Population-Specific Covariates. Genetics 201:1555–1579. https://doi.org/10.1534/genetics.115.181453 Lewontin RC, Krakauer J (1973) Distribution of gene frequency as a test of the theory of selective neutrality of polymorphisms. Genetics 74: 175–195. https://doi.org/10.1093/genetics/74.1.175 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. https://doi.org/10.1101/2022.07.21.500634 | Divergence of olfactory receptors associated with the evolution of assortative mating and reproductive isolation in mice | Carole M. Smadja, Etienne Loire, Pierre Caminade, Dany Severac, Mathieu Gautier, Guila Ganem | <p>Deciphering the genetic bases of behavioural traits is essential to understanding how they evolve and contribute to adaptation and biological diversification, but it remains a substantial challenge, especially for behavioural traits with polyge... | | Adaptation, Behavior & Social Evolution, Genotype-Phenotype, Speciation | Christelle Fraïsse | 2022-07-25 11:54:52 | ||
02 Nov 2022
Evolution of immune genes in island birds: reduction in population sizes can explain island syndromeDemographic effects may affect adaptation to islandsRecommended by Emma Berdan based on reviews by Steven Fiddaman and 3 anonymous reviewersThe 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. References Adler GH, Levins R (1994) The Island Syndrome in Rodent Populations. The Quarterly Review of Biology, 69, 473–490. https://doi.org/10.1086/418744 Baeckens S, Van Damme R (2020) The island syndrome. Current Biology, 30, R338–R339. https://doi.org/10.1016/j.cub.2020.03.029 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. https://doi.org/10.1101/2021.11.21.469450 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. https://doi.org/10.1098/rspb.2006.3671 Burns KC (2019) Evolution in Isolation: The Search for an Island Syndrome in Plants. Cambridge University Press, Cambridge. https://doi.org/10.1017/9781108379953 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. https://doi.org/10.1111/ele.12588 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. https://doi.org/10.1111/jbi.12548 Lomolino MV (2005) Body size evolution in insular vertebrates: generality of the island rule. Journal of Biogeography, 32, 1683–1699. https://doi.org/10.1111/j.1365-2699.2005.01314.x 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. https://doi.org/10.1098/rspb.2006.3590 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. https://doi.org/10.1111/geb.12084 | Evolution of immune genes in island birds: reduction in population sizes can explain island syndrome | Mathilde BARTHE, Claire DOUTRELANT, Rita COVAS, Martim MELO, Juan Carlos ILLERA, Marie-Ka TILAK, Constance COLOMBIER, Thibault LEROY , Claire LOISEAU , Benoit NABHOLZ | <p style="text-align: justify;">Shared ecological conditions encountered by species that colonize islands often lead to the evolution of convergent phenotypes, commonly referred to as “island syndrome”. Reduced immune functions have been previousl... | | Adaptation, Molecular Evolution, Population Genetics / Genomics | Emma Berdan | 2021-11-28 11:01:31 |
