|Id||Title▲||Authors||Abstract||Picture||Thematic fields||Recommender||Reviewers||Submission date|
17 Nov 2017
ABC random forests for Bayesian parameter inferenceLouis Raynal, Jean-Michel Marin, Pierre Pudlo, Mathieu Ribatet, Christian P. Robert, Arnaud Estoup https://arxiv.org/abs/1605.05537
Machine learning methods are useful for Approximate Bayesian Computation in evolution and ecologyRecommended by Michael Blum based on reviews by Dennis Prangle and Michael Blum
It is my pleasure to recommend the paper by Raynal et al.  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  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.
 Raynal L, Marin J-M, Pudlo P, Ribatet M, Robert CP, Estoup A. 2017. ABC random forests for Bayesian parameter inference. arXiv 1605.05537v4, https://arxiv.org/pdf/1605.05537
|ABC random forests for Bayesian parameter inference||Louis Raynal, Jean-Michel Marin, Pierre Pudlo, Mathieu Ribatet, Christian P. Robert, Arnaud Estoup||This preprint has been reviewed and recommended by Peer Community In Evolutionary Biology (http:// dx.doi.org/ 10.24072/ pci.evolbiol.100036). Approximate Bayesian computation (ABC) has grown into a standard methodology that manages Bayesian infer...||Bioinformatics & Computational Biology, Evolutionary Applications, Other, Population Genetics / Genomics||None||2017-07-06 07:42:00||View|
13 Dec 2018
A behavior-manipulating virus relative as a source of adaptive genes for parasitoid waspsD. Di Giovanni, D. Lepetit, M. Boulesteix, M. Ravallec, J. Varaldi https://doi.org/10.1101/342758
Genetic intimacy of filamentous viruses and endoparasitoid waspsRecommended by Ignacio Bravo 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.
 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
|A behavior-manipulating virus relative as a source of adaptive genes for parasitoid wasps||D. Di Giovanni, D. Lepetit, M. Boulesteix, M. Ravallec, J. Varaldi||<p>To circumvent host immune response, numerous hymenopteran endo-parasitoid species produce virus-like structures in their reproductive apparatus that are injected into the host together with the eggs. These viral-like structures are absolutely n...||Adaptation, Behavior & Social Evolution, Genetic conflicts, Genome Evolution||Ignacio Bravo||2018-07-18 15:59:14||View|
11 Jun 2019
A bird’s white-eye view on neosex chromosome evolutionThibault Leroy, Yoann Anselmetti, Marie-Ka Tilak, Sèverine Bérard, Laura Csukonyi, Maëva Gabrielli, Céline Scornavacca, Borja Milá, Christophe Thébaud, Benoit Nabholz https://doi.org/10.1101/505610
Young sex chromosomes discovered in white-eye birdsRecommended by Kateryna Makova 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  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.
 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
|A bird’s white-eye view on neosex chromosome evolution||Thibault Leroy, Yoann Anselmetti, Marie-Ka Tilak, Sèverine Bérard, Laura Csukonyi, Maëva Gabrielli, Céline Scornavacca, Borja Milá, Christophe Thébaud, Benoit Nabholz||<p>Chromosomal organization is relatively stable among avian species, especially with regards to sex chromosomes. Members of the large Sylvioidea clade however have a pair of neo-sex chromosomes which is unique to this clade and originate from a p...||Molecular Evolution, Population Genetics / Genomics||Kateryna Makova||2019-01-24 14:17:15||View|
13 Dec 2016
Addicted? Reduced host resistance in populations with defensive symbiontsMartinez J, Cogni R, Cao C, Smith S, Illingworth CJR & Jiggins FM 10.1098/rspb.2016.0778
Hooked on WolbachiaRecommended by Ana Rivero and Natacha Kremer
This very nice paper by Martinez et al.  provides further evidence, if further evidence was needed, of the extent to which heritable microorganisms run the evolutionary show.
 Martinez J, Cogni R, Cao C, Smith S, Illingworth CJR & Jiggins FM. 2016. Addicted? Reduced host resistance in populations with defensive symbionts. Proceedings of the Royal Society of London B 283:20160778. doi: 10.1098/rspb.2016.0778
|Addicted? Reduced host resistance in populations with defensive symbionts||Martinez J, Cogni R, Cao C, Smith S, Illingworth CJR & Jiggins FM||Heritable symbionts that protect their hosts from pathogens have been described in a wide range of insect species. By reducing the incidence or severity of infection, these symbionts have the potential to reduce the strength of selection on genes ...||Adaptation, Evolutionary Applications, Evolutionary Ecology, Experimental Evolution, Life History||Ana Rivero||2016-12-13 20:08:37||View|
18 Nov 2020
A demogenetic agent based model for the evolution of traits and genome architecture under sexual selectionLouise Chevalier, François de Coligny, Jacques Labonne https://doi.org/10.1101/2020.04.01.014514
Sexual selection goes dynamicRecommended by Michael D Greenfield 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.
Ah-King, M. and Ahnesjo, I. 2013. The ‘sex role’ concept: An overview and evaluation Evolutionary Biology, 40, 461-470. doi: https://doi.org/10.1007/s11692-013-9226-7
|A demogenetic agent based model for the evolution of traits and genome architecture under sexual selection||Louise Chevalier, François de Coligny, Jacques Labonne||<p>Sexual selection has long been known to favor the evolution of mating behaviors such as mate preference and competitiveness, and to affect their genetic architecture, for instance by favoring genetic correlation between some traits. Reciprocall...||Adaptation, Behavior & Social Evolution, Evolutionary Dynamics, Evolutionary Theory, Life History, Population Genetics / Genomics, Sexual Selection||Michael D Greenfield||2020-04-02 14:44:25||View|
05 Nov 2020
A genomic amplification affecting a carboxylesterase gene cluster confers organophosphate resistance in the mosquito Aedes aegypti: from genomic characterization to high-throughput field detectionJulien Cattel, Chloé Haberkorn, Fréderic Laporte, Thierry Gaude, Tristan Cumer, Julien Renaud, Ian W. Sutherland, Jeffrey C. Hertz, Jean-Marc Bonneville, Victor Arnaud, Camille Noûs, Bénédicte Fustec, Sébastien Boyer, Sébastien Marcombe, Jean-Philippe David https://doi.org/10.1101/2020.06.08.139741
Identification of a gene cluster amplification associated with organophosphate insecticide resistance: from the diversity of the resistance allele complex to an efficient field detection assayRecommended by Stephanie Bedhomme 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.
Bass C, Field LM (2011) Gene amplification and insecticide resistance. Pest Management Science, 67, 886–890. https://doi.org/10.1002/ps.2189
|A genomic amplification affecting a carboxylesterase gene cluster confers organophosphate resistance in the mosquito Aedes aegypti: from genomic characterization to high-throughput field detection||Julien Cattel, Chloé Haberkorn, Fréderic Laporte, Thierry Gaude, Tristan Cumer, Julien Renaud, Ian W. Sutherland, Jeffrey C. Hertz, Jean-Marc Bonneville, Victor Arnaud, Camille Noûs, Bénédicte Fustec, Sébastien Boyer, Sébastien Marcombe, Jean-Phil...||<p>By altering gene expression and creating paralogs, genomic amplifications represent a key component of short-term adaptive processes. In insects, the use of insecticides can select gene amplifications causing an increased expression of detoxifi...||Adaptation, Evolutionary Applications, Experimental Evolution, Genome Evolution, Molecular Evolution||Stephanie Bedhomme||2020-06-09 13:27:18||View|
04 Jul 2022
A genomic assessment of the marine-speciation paradox within the toothed whale superfamily DelphinoideaMichael V Westbury, Andrea A Cabrera, Alba Rey-Iglesia, Binia De Cahsan, David A. Duchêne, Stefanie Hartmann, Eline D Lorenzen https://doi.org/10.1101/2020.10.23.352286
Reticulated evolution marks the rapid diversification of the DelphinoidaeRecommended by Michael C. Fontaine 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. https://doi.org/10.1126/sciadv.aap9873
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. https://doi.org/10.1098/rspb.2003.2404
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. https://doi.org/10.1093/sysbio/syz056
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. https://doi.org/10.1093/genetics/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. https://doi.org/10.7554/eLife.67509
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. https://doi.org/10.1098/rstb.2015.0138
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. https://doi.org/10.1002/ece3.1913
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. https://doi.org/10.1101/2021.06.15.448399
Degnan JH, Rosenberg NA (2009) Gene tree discordance, phylogenetic inference and the multispecies coalescent. Trends Ecol Evol 24, 332-340. https://doi.org/10.1016/j.tree.2009.01.009
Durand EY, Patterson N, Reich D, Slatkin M (2011) Testing for ancient admixture between closely related populations. Mol Biol Evol 28, 2239-2252. https://doi.org/10.1093/molbev/msr048
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. https://doi.org/10.1126/science.aaw2090
Edelman NB, Mallet J (2021) Prevalence and Adaptive Impact of Introgression. Annual Review of Genetics 55, 265-283. https://doi.org/10.1146/annurev-genet-021821-020805
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. https://doi.org/10.1016/j.cub.2011.05.058
Ellegren H, Galtier N (2016) Determinants of genetic diversity. Nat Rev Genet 17, 422-433. https://doi.org/10.1038/nrg.2016.58
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. https://doi.org/10.1093/molbev/msy147
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. https://doi.org/10.1126/science.1188021
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. https://doi.org/10.1007/s10914-021-09581-6
Hibbins MS, Hahn MW (2022) Phylogenomic approaches to detecting and characterizing introgression. Genetics 220, iyab173. https://doi.org/10.1093/genetics/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. https://doi.org/10.1093/sysbio/syaa001
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
Malinsky M, Matschiner M, Svardal H (2021) Dsuite - Fast D-statistics and related admixture evidence from VCF files. Mol Ecol Resour 21, 584-595. https://doi.org/10.1111/1755-0998.13265
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. https://doi.org/10.1038/s41559-018-0717-x
Mallet J, Besansky N, Hahn MW (2016) How reticulated are species? Bioessays 38, 140-149. https://doi.org/10.1002/bies.201500149
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. https://doi.org/10.1093/sysbio/syz068
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. https://doi.org/10.1016/j.ympev.2020.106756
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. https://doi.org/10.1093/sysbio/syv023
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. https://doi.org/10.1371/journal.pcbi.1008380
Seehausen O (2004) Hybridization and adaptive radiation. Trends Ecol Evol 19, 198-207. https://doi.org/10.1016/j.tree.2004.01.003
Solís-Lemus C, Yang M, Ané C (2016) Inconsistency of Species Tree Methods under Gene Flow. Syst Biol 65, 843-851. https://doi.org/10.1093/sysbio/syw030
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. https://doi.org/10.1093/molbev/msy158
Wang K, Mathieson I, O’Connell J, Schiffels S (2020) Tracking human population structure through time from whole genome sequences. PLOS Genetics 16, e1008552. https://doi.org/10.1371/journal.pgen.1008552
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. https://doi.org/10.1101/2020.10.23.352286
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. https://doi.org/10.1371/journal.pone.0222004
Yang Z (2015) The BPP program for species tree estimation and species delimitation. Current Zoology 61, 854-865. https://doi.org/10.1093/czoolo/61.5.854
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. https://doi.org/10.1186/s12859-018-2129-y
|A genomic assessment of the marine-speciation paradox within the toothed whale superfamily Delphinoidea||Michael V Westbury, Andrea A Cabrera, Alba Rey-Iglesia, Binia De Cahsan, David A. Duchêne, Stefanie Hartmann, Eline D Lorenzen||<p>The importance of post-divergence gene flow in speciation has been documented across a range of taxa in recent years, and may have been especially widespread in highly mobile, wide-ranging marine species, such as cetaceans. Here, we studied ind...||Evolutionary Dynamics, Hybridization / Introgression, Molecular Evolution, Phylogenetics / Phylogenomics, Speciation||Michael C. Fontaine||2020-10-25 08:55:50||View|
25 Feb 2021
Alteration of gut microbiota with a broad-spectrum antibiotic does not impair maternal care in the European earwigSophie Van Meyel, Séverine Devers, Simon Dupont, Franck Dedeine and Joël Meunier https://doi.org/10.1101/2020.10.08.331363
Assessing the role of host-symbiont interactions in maternal care behaviourRecommended by Trine Bilde 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.
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: https://doi.org/10.3389/fevo.2015.00153
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: https://doi.org/10.1146/annurev.ecolsys.110308.120206
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: https://doi.org/10.1126/science.1227412
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: https://doi.org/10.1098/rstb.2019.0599
Hird, S. M. (2017). Evolutionary biology needs wild microbiomes. Frontiers in microbiology, 8, 725. doi: https://doi.org/10.3389/fmicb.2017.00725
Johnson, K. V. A., and Foster, K. R. (2018). Why does the microbiome affect behaviour?. Nature reviews microbiology, 16(10), 647-655. doi: https://doi.org/10.1038/s41579-018-0014-3
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: https://doi.org/10.1111/1365-2435.12915
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: https://doi.org/10.1038/ncomms14040
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: https://doi.org/10.1098/rspb.2012.1416
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: https://doi.org/10.1007/s10682-011-9510-x
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: https://doi.org/10.3389/fevo.2020.00014
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: https://doi.org/10.1007/s00442-016-3685-3
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. https://doi.org/10.1101/2020.10.08.331363
|Alteration of gut microbiota with a broad-spectrum antibiotic does not impair maternal care in the European earwig||Sophie Van Meyel, Séverine Devers, Simon Dupont, Franck Dedeine and Joël Meunier||<p>The microbes residing within the gut of an animal host often increase their own fitness by modifying their host’s physiological, reproductive, and behavioural functions. Whereas recent studies suggest that they may also shape host sociality and...||Behavior & Social Evolution, Evolutionary Ecology, Experimental Evolution, Life History, Species interactions||Trine Bilde||2020-10-09 14:07:47||View|
28 Mar 2019
Ancient tropical extinctions contributed to the latitudinal diversity gradientAndrea S. Meseguer, Fabien Condamine https://doi.org/10.1101/236646
One (more) step towards a dynamic view of the Latitudinal Diversity GradientRecommended by Joaquín Hortal and Juan Arroyo 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  described it about 200 years ago . 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  (see also ). 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 . Besides that, although in general the tropics hold more species, different taxa show different shapes and rates of spatial variation , and a considerable number of groups show reverse patterns, with richer assemblages in cold temperate regions (see e.g. [7-9]).
|Ancient tropical extinctions contributed to the latitudinal diversity gradient||Andrea S. Meseguer, Fabien Condamine||<p>Biodiversity currently peaks at the equator, decreasing toward the poles. Growing fossil evidence suggest that this hump-shaped latitudinal diversity gradient (LDG) has not been persistent through time, with similar species diversity across lat...||Evolutionary Dynamics, Evolutionary Ecology, Macroevolution, Paleontology, Phylogenetics / Phylogenomics, Phylogeography & Biogeography||Joaquín Hortal||2017-12-20 14:58:01||View|
16 May 2023
A new and almost perfectly accurate approximation of the eigenvalue effective population size of a dioecious population: comparisons with other estimates and detailed proofsThierry de Meeûs and Camille Noûs https://doi.org/10.5281/zenodo.7927968
All you ever wanted to know about Ne in one handy placeRecommended by Charles Baer based on reviews by Jesse ("Jay") Taylor and 1 anonymous reviewer
Of the four evolutionary forces, three can be straightforwardly summarized both conceptually and mathematically in the context of an allele at a genomic locus. Mutation (the mutation rate, μ) is simply captured by the per-site, per-generation probability that an allele mutates into a different allele. Recombination (the recombination rate, r) is captured as the probability of recombination between two sites, wherein alleles that are in different genomes in one generation come together in the same genome in the next generation. Natural selection (the selection coefficient, s) is captured by the probability that an allele is present in the next generation, relative to some reference.
Random genetic drift – the random fluctuation in allele frequency due to sampling in a finite population - is not so straightforwardly summarized. The first, and most common way of characterizing evolutionary dynamics in a finite population is the Wright-Fisher model, in which the only deviation from the assumptions of Hardy-Weinberg conditions is finite population size. Importantly, in a W-F population, mating between diploid individuals is random, which implies self-fertile monoecy, and generations are non-overlapping. In an ideal W-F population, the probability that a gene copy leaves i descendants in the next generation is the result of binomial sampling of uniting gametes (if the locus is biallelic). The – and the next word is meaningful – magnitude/strength/rate/power/amount of genetic drift is proportional to 1/2N, where N is the size of the population. All of the following are affected by genetic drift: (1) the probability that a neutral allele ultimately reaches fixation, (2) the rate of loss of genetic variation within a population, (3) the rate of increase of genetic variance among populations, (4) the amount of genetic variation segregating in a population, (5) the probability of fixation/loss of a weakly selected variant.
Presumably no real population adheres to ideal W-F conditions, which leads to the notion of "effective population size", Ne (Wright 1931), loosely defined as "the size of an ideal W-F population that experiences an equivalent strength of genetic drift". Almost always, Ne<N, and any violation of W-F assumptions can affect Ne. Importantly, Ne can be defined in different ways, and the specific formulation of Ne can have different implications for evolution. Ne was initially defined in terms of the rate of decrease of heterozygosity (inbreeding effective size) and increase in variance among populations (variance effective size). Ewens (1979) defined the Eigenvalue effective size (equivalent to the "random extinction" effective size) and elaborated on the conditions under which the various formulations of Ne differ (Ewens 1982). Nordborg and Krone (2002) defined the effective size in terms of the coalescent, and they identified conditions in which genetic drift cannot be described in terms of a W-F model (Sjodin et al. 2005); also see Karasov et al. (2010); Neher and Shraiman (2011).
Distinct from the issue of defining Ne is the issue of calculating Ne from data, which is the focus of this paper by De Meeus and Noûs (2023). Pudovkin et al. (1996) showed that the Eigenvalue effective size in a dioecious population can be formulated in terms of excess heterozygosity, which the current authors note is equivalent to formulating Ne in terms of Wright's FIS statistic. As emphasized by the title, the marquee contribution of this paper is to provide a better approximation of the Eigenvalue effective size in a dioecious population. Science marches onward, although the empirical utility of this advance is obviously limited, given the tremendous inherent sources of uncertainty in real-world estimates of Ne. Perhaps more valuable, however, is the extensive set of appendixes, in which detailed derivations are provided for the various formulations of effective size. By way of analogy, the material presented here can be thought of as an extension of the material presented in section 7.6 of Crow and Kimura (1970), in which the Inbreeding and Variance effective population sizes are derived and compared. The appendixes should serve as a handy go-to source of detailed theoretical information with respect to the different formulations of effective population size.
Crow, J. F. and M. Kimura. 1970. An Introduction to Population Genetics Theory. The Blackburn Press, Caldwell, NJ.
De Meeûs, T. and Noûs, C. 2023. A new and almost perfectly accurate approximation of the eigenvalue effective population size of a dioecious population: comparisons with other estimates and detailed proofs. Zenodo, ver. 6 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.5281/zenodo.7927968
Ewens, W. J. 1979. Mathematical Population Genetics. Springer-Verlag, Berlin.
Ewens, W. J. 1982. On the concept of the effective population size. Theoretical Population Biology 21:373-378. https://doi.org/10.1016/0040-5809(82)90024-7
Karasov, T., P. W. Messer, and D. A. Petrov. 2010. Evidence that adaptation in Drosophila Is not limited by mutation at single sites. Plos Genetics 6. https://doi.org/10.1371/journal.pgen.1000924
Neher, R. A. and B. I. Shraiman. 2011. Genetic Draft and Quasi-Neutrality in Large Facultatively Sexual Populations. Genetics 188:975-U370. https://doi.org/10.1534/genetics.111.128876
Nordborg, M. and S. M. Krone. 2002. Separation of time scales and convergence to the coalescent in structured populations. Pp. 194–232 in M. Slatkin, and M. Veuille, eds. Modern Developments in Theoretical Population Genetics: The Legacy of Gustave Malécot. Oxford University Press, Oxford. https://www.webpages.uidaho.edu/~krone/malecot.pdf
Pudovkin, A. I., D. V. Zaykin, and D. Hedgecock. 1996. On the potential for estimating the effective number of breeders from heterozygote-excess in progeny. Genetics 144:383-387. https://doi.org/10.1093/genetics/144.1.383
Sjodin, P., I. Kaj, S. Krone, M. Lascoux, and M. Nordborg. 2005. On the meaning and existence of an effective population size. Genetics 169:1061-1070. https://doi.org/10.1534/genetics.104.026799
Wright, S. 1931. Evolution in Mendelian populations. Genetics 16:0097-0159. https://doi.org/10.1093/genetics/16.2.97
|A new and almost perfectly accurate approximation of the eigenvalue effective population size of a dioecious population: comparisons with other estimates and detailed proofs||Thierry de Meeûs and Camille Noûs||<p>The effective population size is an important concept in population genetics. It corresponds to a measure of the speed at which genetic drift affects a given population. Moreover, this is most of the time the only kind of population size that e...||Bioinformatics & Computational Biology, Evolutionary Ecology, Evolutionary Theory, Population Genetics / Genomics, Reproduction and Sex||Charles Baer||2023-02-22 16:53:49||View|
Michael David Pirie
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