The rate of adaptive molecular evolution in wild and domesticated Saccharomyces cerevisiae populations

Through its fermentative capacities, Saccharomyces cerevisiae was central in the development of civilisation during the Neolithic period, and the yeast remains of importance in industry and biotechnology, giving rise to bona fide domesticated populations. Here, we conduct a population genomic study of domesticated and wild populations of S. cerevisiae. Using coalescent analyses, we report that the effective population size of yeast populations decreased since the divergence with S. paradoxus. We fitted models of distributions of fitness effects to infer the rate of adaptive (ω a ) and non-adaptive (ω na ) non-synonymous substitutions in protein-coding genes. We report an overall limited contribution of positive selection to S. cerevisiae protein evolution, albeit with higher rates of adaptive evolution in wild compared to domesticated populations. Our analyses revealed the signature of background selection and possibly Hill-Robertson interference, as recombination was found to be negatively correlated withω na and positively correlated withω a . However, the effect of recombination onω a was found to be labile, as it is only apparent after removing the impact of codon usage bias on the synonymous site frequency spectrum and disappears if we control for the correlation withω na , suggesting that it could be an artefact of the decreasing population size. Furthermore, the rate of adaptive non-synonymous substitutions is significantly correlated with the residue solvent exposure, a relation that cannot be explained by the population's demography. Together, our results provide a detailed characterisation of adaptive mutations in protein-coding genes across S. cerevisiae populations.

The Promise of Inferring the Past Using the Ancestral Recombination Graph

The ancestral recombination graph (ARG) is a structure that represents the history of coalescent and recombination events connecting a set of sequences (Hudson RR. In: Futuyma D, Antonovics J, editors. Gene genealogies and the coalescent process. In: Oxford Surveys in Evolutionary Biology; 1991. p. 1 to 44.). The full ARG can be represented as a set of genealogical trees at every locus in the genome, annotated with recombination events that change the topology of the trees between adjacent loci and the mutations that occurred along the branches of those trees (Griffiths RC, Marjoram P. An ancestral recombination graph. In: Donnelly P, Tavare S, editors. Progress in population genetics and human evolution. Springer; 1997. p. 257 to 270.). Valuable insights can be gained into past evolutionary processes, such as demographic events or the influence of natural selection, by studying the ARG. It is regarded as the "holy grail" of population genetics (Hubisz M, Siepel A. Inference of ancestral recombination graphs using ARGweaver. In: Dutheil JY, editors. Statistical population genomics. New York, NY: Springer US; 2020. p. 231-266.) since it encodes the processes that generate all patterns of allelic and haplotypic variation from which all commonly used summary statistics in population genetic research (e.g. heterozygosity and linkage disequilibrium) can be derived. Many previous evolutionary inferences relied on summary statistics extracted from the genotype matrix. Evolutionary inferences using the ARG represent a significant advancement as the ARG is a representation of the evolutionary history of a sample that shows the past history of recombination, coalescence, and mutation events across a particular sequence. This representation in theory contains as much information, if not more, than the combination of all independent summary statistics that could be derived from the genotype matrix. Consistent with this idea, some of the first ARG-based analyses have proven to be more powerful than summary statistic-based analyses (Speidel L, Forest M, Shi S, Myers SR. A method for genome-wide genealogy estimation for thousands of samples. Nat Genet. 2019:51(9):1321 to 1329.; Stern AJ, Wilton PR, Nielsen R. An approximate full-likelihood method for inferring selection and allele frequency trajectories from DNA sequence data. PLoS Genet. 2019:15(9):e1008384.; Hubisz MJ, Williams AL, Siepel A. Mapping gene flow between ancient hominins through demography-aware inference of the ancestral recombination graph. PLoS Genet. 2020:16(8):e1008895.; Fan C, Mancuso N, Chiang CWK. A genealogical estimate of genetic relationships. Am J Hum Genet. 2022:109(5):812-824.; Fan C, Cahoon JL, Dinh BL, Ortega-Del Vecchyo D, Huber C, Edge MD, Mancuso N, Chiang CWK. A likelihood-based framework for demographic inference from genealogical trees. bioRxiv. 2023.10.10.561787. 2023.; Hejase HA, Mo Z, Campagna L, Siepel A. A deep-learning approach for inference of selective sweeps from the ancestral recombination graph. Mol Biol Evol. 2022:39(1):msab332.; Link V, Schraiber JG, Fan C, Dinh B, Mancuso N, Chiang CWK, Edge MD. Tree-based QTL mapping with expected local genetic relatedness matrices. bioRxiv. 2023.04.07.536093. 2023.; Zhang BC, Biddanda A, Gunnarsson ÁF, Cooper F, Palamara PF. Biobank-scale inference of ancestral recombination graphs enables genealogical analysis of complex traits. Nat Genet. 2023:55(5):768-776.). As such, there has been significant interest in the field to investigate 2 main problems related to the ARG: (i) How can we estimate the ARG based on genomic data, and (ii) how can we extract information of past evolutionary processes from the ARG? In this perspective, we highlight 3 topics that pertain to these main issues: The development of computational innovations that enable the estimation of the ARG; remaining challenges in estimating the ARG; and methodological advances for deducing evolutionary forces and mechanisms using the ARG. This perspective serves to introduce the readers to the types of questions that can be explored using the ARG and to highlight some of the most pressing issues that must be addressed in order to make ARG-based inference an indispensable tool for evolutionary research.

Demogenomic inference from spatially and temporally heterogeneous samples

Modern and ancient genomes are not necessarily drawn from homogeneous populations, as they may have been collected from different places and at different times. This heterogeneous sampling can be an issue for demographic inferences and results in biased demographic parameters and incorrect model choice if not properly considered. When explicitly accounted for, it can result in very complex models and high data dimensionality that are difficult to analyse. In this paper, we formally study the impact of such spatial and temporal sampling heterogeneity on demographic inference, and we introduce a way to circumvent this problem. To deal with structured samples without increasing the dimensionality of the site frequency spectrum (SFS), we introduce a new structured approach to the existing program fastsimcoal2. We assess the efficiency and relevance of this methodological update with simulated and modern human genomic data. We particularly focus on spatial and temporal heterogeneities to evidence the interest of this new SFS-based approach, which can be especially useful when handling scattered and ancient DNA samples, as in conservation genetics or archaeogenetics.

Integrating Pool-seq uncertainties into demographic inference

Next-generation sequencing of pooled samples (Pool-seq) is a popular method to assess genome-wide diversity patterns in natural and experimental populations. However, Pool-seq is associated with specific sources of noise, such as unequal individual contributions. Consequently, using Pool-seq for the reconstruction of evolutionary history has remained underexplored. Here we describe a novel Approximate Bayesian Computation (ABC) method to infer demographic history, explicitly modelling Pool-seq sources of error. By jointly modelling Pool-seq data, demographic history and the effects of selection due to barrier loci, we obtain estimates of demographic history parameters accounting for technical errors associated with Pool-seq. Our ABC approach is computationally efficient as it relies on simulating subsets of loci (rather than the whole-genome) and on using relative summary statistics and relative model parameters. Our simulation study results indicate Pool-seq data allows distinction between general scenarios of ecotype formation (single versus parallel origin) and to infer relevant demographic parameters (e.g. effective sizes and split times). We exemplify the application of our method to Pool-seq data from the rocky-shore gastropod Littorina saxatilis, sampled on a narrow geographical scale at two Swedish locations where two ecotypes (Wave and Crab) are found. Our model choice and parameter estimates show that ecotypes formed before colonization of the two locations (i.e. single origin) and are maintained despite gene flow. These results indicate that demographic modelling and inference can be successful based on pool-sequencing using ABC, contributing to the development of suitable null models that allow for a better understanding of the genetic basis of divergent adaptation.

Methods for Assessing Population Relationships and History Using Genomic Data

Genetic data contain a record of our evolutionary history. The availability of large-scale datasets of human populations from various geographic areas and timescales, coupled with advances in the computational methods to analyze these data, has transformed our ability to use genetic data to learn about our evolutionary past. Here, we review some of the widely used statistical methods to explore and characterize population relationships and history using genomic data. We describe the intuition behind commonly used approaches, their interpretation, and important limitations. For illustration, we apply some of these techniques to genome-wide autosomal data from 929 individuals representing 53 worldwide populations that are part of the Human Genome Diversity Project. Finally, we discuss the new frontiers in genomic methods to learn about population history. In sum, this review highlights the power (and limitations) of DNA to infer features of human evolutionary history, complementing the knowledge gleaned from other disciplines, such as archaeology, anthropology, and linguistics.

Developing an evolutionary baseline model for humans: jointly inferring purifying selection with population history

Building evolutionarily appropriate baseline models for natural populations is not only important for answering fundamental questions in population genetics - including quantifying the relative contributions of adaptive vs. non-adaptive processes - but it is also essential for identifying candidate loci experiencing relatively rare and episodic forms of selection (e.g., positive or balancing selection). Here, a baseline model was developed for a human population of West African ancestry, the Yoruba, comprising processes constantly operating on the genome (i.e., purifying and background selection, population size changes, recombination rate heterogeneity, and gene conversion). Specifically, to perform joint inference of selective effects with demography, an approximate Bayesian approach was employed that utilizes the decay of background selection effects around functional elements, taking into account genomic architecture. This approach inferred a recent 6-fold population growth together with a distribution of fitness effects that is skewed towards effectively neutral mutations. Importantly, these results further suggest that, while strong and/or frequent recurrent positive selection is inconsistent with observed data, weak to moderate positive selection is consistent but unidentifiable if rare.

Chromosome Fissions and Fusions Act as Barriers to Gene Flow between Brenthis Fritillary Butterflies

Chromosome rearrangements are thought to promote reproductive isolation between incipient species. However, it is unclear how often, and under what conditions, fission and fusion rearrangements act as barriers to gene flow. Here we investigate speciation between two largely sympatric fritillary butterflies, Brenthis daphne and Brenthis ino. We use a composite likelihood approach to infer the demographic history of these species from whole-genome sequence data. We then compare chromosome-level genome assemblies of individuals from each species and identify a total of nine chromosome fissions and fusions. Finally, we fit a demographic model where effective population sizes and effective migration rate vary across the genome, allowing us to quantify the effects of chromosome rearrangements on reproductive isolation. We show that chromosomes involved in rearrangements experienced less effective migration since the onset of species divergence and that genomic regions near rearrangement points have a further reduction in effective migration rate. Our results suggest that the evolution of multiple rearrangements in the B. daphne and B. ino populations, including alternative fusions of the same chromosomes, have resulted in a reduction in gene flow. Although fission and fusion of chromosomes are unlikely to be the only processes that have led to speciation between these butterflies, this study shows that these rearrangements can directly promote reproductive isolation and may be involved in speciation when karyotypes evolve quickly.

Phylogenomic inference and demographic model selection suggest peripatric separation of the cryptic steppe ant species Plagiolepis pyrenaica stat. rev

The ant Plagiolepis taurica Santschi, 1920 (Hymenoptera, Formicidae) is a typical species of the Eurasian steppes, a large grassland dominated biome that stretches continuously from Central Asia to Eastern Europe and is represented by disjunct outposts also in Central and Western Europe. The extent of this biome has been influenced by the Pleistocene climate, and steppes expanded recurrently during cold stages and contracted in warm stages. Consequently, stenotopic steppe species such as P. taurica repeatedly went through periods of demographic expansion and severe isolation. Here, we explore the impact of these dynamics on the genetic diversification within P. taurica. Delimitation of P. taurica from other Plagiolepis species has been unclear since its initial description, which raised questions on both its classification and its spatiotemporal diversification early on. We re-evaluate species limits and explore underlying mechanisms driving speciation by using an integrative approach based on genomic and morphometric data. We found large intraspecific divergence within P. taurica and resolved geographically coherent western and eastern genetic groups, which likewise differed morphologically. A morphometric survey of type material showed that Plagiolepis from the western group were more similar to P. barbara pyrenaica Emery, 1921 than to P. taurica; we thus lift the former from synonymy and establish it as separate species, P. pyrenaica stat. rev. Explicit evolutionary model testing based on genomic data supported a peripatric speciation for the species pair, probably as a consequence of steppe contraction and isolation during the mid-Pleistocene. We speculate that this scenario could be exemplary for many stenotopic steppe species, given the emphasized dynamics of Eurasian steppes.

Cultural transmission of reproductive success impacts genomic diversity, coalescent tree topologies and demographic inferences

Cultural transmission of reproductive success (CTRS) has been observed in many human populations as well as other animals. CTRS consists of a positive correlation of nongenetic origin between the progeny size of parents and children. This correlation can result from various factors, such as the social influence of parents on their children, the increase of children's survival through allocare from uncles and aunts, or the transmission of resources. Here, we study the evolution of genomic diversity over time under CTRS. CTRS has a threefold impact on population genetics: (1) the effective population size decreases when CTRS starts, mimicking a population contraction, and increases back to its original value when CTRS stops; (2) coalescent tree topologies are distorted under CTRS, with higher imbalance and a higher number of polytomies; and (3) branch lengths are reduced nonhomogeneously, with a higher impact on older branches. Under long-lasting CTRS, the effective population size stabilizes but the distortion of tree topology and the nonhomogeneous branch length reduction remain, yielding U-shaped site frequency spectra (SFS) under a constant population size. We show that this yields a bias in SFS-based demographic inference. Considering that CTRS was detected in numerous human and animal populations worldwide, one should be cautious because inferring population past histories from genomic data can be biased by this cultural process.

The demographic history of house mice (Mus musculus domesticus) in eastern North America

The Western European house mouse (Mus musculus domesticus) is a widespread human commensal that has recently been introduced to North America. Its introduction to the Americas is thought to have resulted from the transatlantic movements of Europeans that began in the early 16th century. To study the details of this colonization history, we examine population structure, explore relevant demographic models, and infer the timing of divergence among house mouse populations in the eastern United States using published exome sequences from five North American populations and two European populations. For North American populations of house mice, levels of nucleotide variation were lower, and low-frequency alleles were less common than for European populations. These patterns provide evidence of a mild bottleneck associated with the movement of house mice into North America. Several analyses revealed that one North American population is genetically admixed, which indicates at least two source populations from Europe were independently introduced to eastern North America. Estimated divergence times between North American and German populations ranged between ∼1,000 and 7,000 years ago and overlapped with the estimated divergence time between populations from Germany and France. Demographic models comparing different North American populations revealed that these populations diverged from each other mostly within the last 500 years, consistent with the timing of the arrival of Western European settlers to North America. Together, these results support a recent introduction of Western European house mice to eastern North America, highlighting the effects of human migration and colonization on the spread of an invasive human commensal.

The redlegged earth mite draft genome provides new insights into pesticide resistance evolution and demography in its invasive Australian range

Genomic data provide valuable insights into pest management issues such as resistance evolution, historical patterns of pest invasions and ongoing population dynamics. We assembled the first reference genome for the redlegged earth mite, Halotydeus destructor (Tucker, 1925), to investigate adaptation to pesticide pressures and demography in its invasive Australian range using whole-genome pool-seq data from regionally distributed populations. Our reference genome comprises 132 autosomal contigs, with a total length of 48.90 Mb. We observed a large complex of ace genes, which has presumably evolved from a long history of organophosphate selection in H. destructor and may contribute towards organophosphate resistance through copy number variation, target-site mutations and structural variants. In the putative ancestral H. destructor ace gene, we identified three target-site mutations (G119S, A201S and F331Y) segregating in organophosphate-resistant populations. Additionally, we identified two new para sodium channel gene mutations (L925I and F1020Y) that may contribute to pyrethroid resistance. Regional structuring observed in population genomic analyses indicates that gene flow in H. destructor does not homogenize populations across large geographic distances. However, our demographic analyses were equivocal on the magnitude of gene flow; the short invasion history of H. destructor makes it difficult to distinguish scenarios of complete isolation vs. ongoing migration. Nonetheless, we identified clear signatures of reduced genetic diversity and smaller inferred effective population sizes in eastern vs. western populations, which is consistent with the stepping-stone invasion pathway of this pest in Australia. These new insights will inform development of diagnostic genetic markers of resistance, further investigation into the multifaceted organophosphate resistance mechanism and predictive modelling of resistance evolution and spread.

GADMA2: more efficient and flexible demographic inference from genetic data

BACKGROUND

Inference of complex demographic histories is a source of information about events that happened in the past of studied populations. Existing methods for demographic inference typically require input from the researcher in the form of a parameterized model. With an increased variety of methods and tools, each with its own interface, the model specification becomes tedious and error-prone. Moreover, optimization algorithms used to find model parameters sometimes turn out to be inefficient, for instance, by being not properly tuned or highly dependent on a user-provided initialization. The open-source software GADMA addresses these problems, providing automatic demographic inference. It proposes a common interface for several likelihood engines and provides global parameters optimization based on a genetic algorithm.

RESULTS

Here, we introduce the new GADMA2 software and provide a detailed description of the added and expanded features. It has a renovated core code base, new likelihood engines, an updated optimization algorithm, and a flexible setup for automatic model construction. We provide a full overview of GADMA2 enhancements, compare the performance of supported likelihood engines on simulated data, and demonstrate an example of GADMA2 usage on 2 empirical datasets.

CONCLUSIONS

We demonstrate the better performance of a genetic algorithm in GADMA2 by comparing it to the initial version and other existing optimization approaches. Our experiments on simulated data indicate that GADMA2's likelihood engines are able to provide accurate estimations of demographic parameters even for misspecified models. We improve model parameters for 2 empirical datasets of inbred species.

Genome-wide data from medieval German Jews show that the Ashkenazi founder event pre-dated the 14(th) century

We report genome-wide data from 33 Ashkenazi Jews (AJ), dated to the 14^th century, obtained following a salvage excavation at the medieval Jewish cemetery of Erfurt, Germany. The Erfurt individuals are genetically similar to modern AJ, but they show more variability in Eastern European-related ancestry than modern AJ. A third of the Erfurt individuals carried a mitochondrial lineage common in modern AJ and eight carried pathogenic variants known to affect AJ today. These observations, together with high levels of runs of homozygosity, suggest that the Erfurt community had already experienced the major reduction in size that affected modern AJ. The Erfurt bottleneck was more severe, implying substructure in medieval AJ. Overall, our results suggest that the AJ founder event and the acquisition of the main sources of ancestry pre-dated the 14^th century and highlight late medieval genetic heterogeneity no longer present in modern AJ.

Ten years of demographic modelling of divergence and speciation in the sea

Understanding population divergence that eventually leads to speciation is essential for evolutionary biology. High species diversity in the sea was regarded as a paradox when strict allopatry was considered necessary for most speciation events because geographical barriers seemed largely absent in the sea, and many marine species have high dispersal capacities. Combining genome-wide data with demographic modelling to infer the demographic history of divergence has introduced new ways to address this classical issue. These models assume an ancestral population that splits into two subpopulations diverging according to different scenarios that allow tests for periods of gene flow. Models can also test for heterogeneities in population sizes and migration rates along the genome to account, respectively, for background selection and selection against introgressed ancestry. To investigate how barriers to gene flow arise in the sea, we compiled studies modelling the demographic history of divergence in marine organisms and extracted preferred demographic scenarios together with estimates of demographic parameters. These studies show that geographical barriers to gene flow do exist in the sea but that divergence can also occur without strict isolation. Heterogeneity of gene flow was detected in most population pairs suggesting the predominance of semipermeable barriers during divergence. We found a weak positive relationship between the fraction of the genome experiencing reduced gene flow and levels of genome-wide differentiation. Furthermore, we found that the upper bound of the 'grey zone of speciation' for our dataset extended beyond that found before, implying that gene flow between diverging taxa is possible at higher levels of divergence than previously thought. Finally, we list recommendations for further strengthening the use of demographic modelling in speciation research. These include a more balanced representation of taxa, more consistent and comprehensive modelling, clear reporting of results and simulation studies to rule out nonbiological explanations for general results.

The genomic origins of the world's first farmers

The precise genetic origins of the first Neolithic farming populations in Europe and Southwest Asia, as well as the processes and the timing of their differentiation, remain largely unknown. Demogenomic modeling of high-quality ancient genomes reveals that the early farmers of Anatolia and Europe emerged from a multiphase mixing of a Southwest Asian population with a strongly bottlenecked western hunter-gatherer population after the last glacial maximum. Moreover, the ancestors of the first farmers of Europe and Anatolia went through a period of extreme genetic drift during their westward range expansion, contributing highly to their genetic distinctiveness. This modeling elucidates the demographic processes at the root of the Neolithic transition and leads to a spatial interpretation of the population history of Southwest Asia and Europe during the late Pleistocene and early Holocene.

Whole-genome analysis of multiple wood ant population pairs supports similar speciation histories, but different degrees of gene flow, across their European ranges

The application of demographic history modelling and inference to the study of divergence between species has become a cornerstone of speciation genomics. Speciation histories are usually reconstructed by analysing single populations from each species, assuming that the inferred population history represents the actual speciation history. However, this assumption may not be met when species diverge with gene flow, for example, when secondary contact may be confined to specific geographic regions. Here, we tested whether divergence histories inferred from heterospecific populations may vary depending on their geographic locations, using the two wood ant species Formica polyctena and F. aquilonia. We performed whole‐genome resequencing of 20 individuals sampled in multiple locations across the European ranges of both species. Then, we reconstructed the histories of distinct heterospecific population pairs using a coalescent‐based approach. Our analyses always supported a scenario of divergence with gene flow, suggesting that divergence started in the Pleistocene (c. 500 kya) and occurred with continuous asymmetrical gene flow from F. aquilonia to F. polyctena until a recent time, when migration became negligible (2–19 kya). However, we found support for contemporary gene flow in a sympatric pair from Finland, where the species hybridise, but no signature of recent bidirectional gene flow elsewhere. Overall, our results suggest that divergence histories reconstructed from a few individuals may be applicable at the species level. Nonetheless, the geographical context of populations chosen to represent their species should be taken into account, as it may affect estimates of migration rates between species when gene flow is spatially heterogeneous.

Strong and lasting impacts of past global warming on baleen whales and their prey

Global warming is affecting the population dynamics and trophic interactions across a wide range of ecosystems and habitats. Translating these real-time effects into their long-term consequences remains a challenge. The rapid and extreme warming period that occurred after the Last Glacial Maximum (LGM) during the Pleistocene-Holocene transition (7-12 thousand years ago) provides an opportunity to gain insights into the long-term responses of natural populations to periods with global warming. The effects of this post-LGM warming period have been assessed in many terrestrial taxa, whereas insights into the impacts of rapid global warming on marine taxa remain limited, especially for megafauna. In order to understand how large-scale climate fluctuations during the post-LGM affected baleen whales and their prey, we conducted an extensive, large-scale analysis of the long-term effects of the post-LGM warming on abundance and inter-ocean connectivity in eight baleen whale and seven prey (fish and invertebrates) species across the Southern and the North Atlantic Ocean; two ocean basins that differ in key oceanographic features. The analysis was based upon 7032 mitochondrial DNA sequences as well as genome-wide DNA sequence variation in 100 individuals. The estimated temporal changes in genetic diversity during the last 30,000 years indicated that most baleen whale populations underwent post-LGM expansions in both ocean basins. The increase in baleen whale abundance during the Holocene was associated with simultaneous changes in their prey and climate. Highly correlated, synchronized and exponential increases in abundance in both baleen whales and their prey in the Southern Ocean were indicative of a dramatic increase in ocean productivity. In contrast, the demographic fluctuations observed in baleen whales and their prey in the North Atlantic Ocean were subtle, varying across taxa and time. Perhaps most important was the observation that the ocean-wide expansions and decreases in abundance that were initiated by the post-LGM global warming, continued for millennia after global temperatures stabilized, reflecting persistent, long-lasting impacts of global warming on marine fauna.

Demographic Representation and Collective Storytelling in the Me Too Twitter Hashtag Activism Movement

The #MeToo movement on Twitter has drawn attention to the pervasive nature of sexual harassment and violence. While #MeToo has been praised for providing support for self-disclosures of harassment or violence and shifting societal response, it has also been criticized for exemplifying how women of color have been discounted for their historical contributions to and excluded from feminist movements. Through an analysis of over 600,000 tweets from over 256,000 unique users, we examine online #MeToo conversations across gender and racial/ethnic identities and the topics that each demographic emphasized. We found that tweets authored by white women were overrepresented in the movement compared to other demographics, aligning with criticism of unequal representation. We found that intersected identities contributed differing narratives to frame the movement, co-opted the movement to raise visibility in parallel ongoing movements, employed the same hashtags both critically and supportively, and revived and created new hashtags in response to pivotal moments. Notably, tweets authored by black women often expressed emotional support and were critical about differential treatment in the justice system and by police. In comparison, tweets authored by white women and men often highlighted sexual harassment and violence by public figures and weaved in more general political discussions. We discuss the implications of this work for digital activism research and design, including suggestions to raise visibility by those who were under-represented in this hashtag activism movement. Content warning: this article discusses issues of sexual harassment and violence.

Heterogeneity in effective size across the genome: effects on the inverse instantaneous coalescence rate (IICR) and implications for demographic inference under linked selection

The relative contribution of selection and neutrality in shaping species genetic diversity is one of the most central and controversial questions in evolutionary theory. Genomic data provide growing evidence that linked selection, i.e. the modification of genetic diversity at neutral sites through linkage with selected sites, might be pervasive over the genome. Several studies proposed that linked selection could be modeled as first approximation by a local reduction (e.g. purifying selection, selective sweeps) or increase (e.g. balancing selection) of effective population size (Ne). At the genome-wide scale, this leads to variations of Ne from one region to another, reflecting the heterogeneity of selective constraints and recombination rates between regions. We investigate here the consequences of such genomic variations of Ne on the genome-wide distribution of coalescence times. The underlying motivation concerns the impact of linked selection on demographic inference, because the distribution of coalescence times is at the heart of several important demographic inference approaches. Using the concept of inverse instantaneous coalescence rate, we demonstrate that in a panmictic population, linked selection always results in a spurious apparent decrease of Ne along time. Balancing selection has a particularly large effect, even when it concerns a very small part of the genome. We also study more general models including genuine population size changes, population structure or transient selection and find that the effect of linked selection can be significantly reduced by that of population structure. The models and conclusions presented here are also relevant to the study of other biological processes generating apparent variations of Ne along the genome.

Genomic consequences of colonisation, migration and genetic drift in barn owl insular populations of the eastern Mediterranean

The study of insular populations was key in the development of evolutionary theory. The successful colonisation of an island depends on the geographic context, and specific characteristics of the organism and the island, but also on stochastic processes. As a result, apparently identical islands may harbour populations with contrasting histories. Here, we use whole genome sequences of 65 barn owls to investigate the patterns of inbreeding and genetic diversity of insular populations in the eastern Mediterranean Sea. We focus on Crete and Cyprus, islands with similar size, climate and distance to mainland, that provide natural replicates for a comparative analysis of the impacts of microevolutionary processes on isolated populations. We show that barn owl populations from each island have a separate origin, Crete being genetically more similar to other Greek islands and mainland Greece, and Cyprus more similar to the Levant. Further, our data show that their respective demographic histories following colonisation were also distinct. On the one hand, Crete harbours a small population and maintains very low levels of gene flow with neighbouring populations. This has resulted in low genetic diversity, strong genetic drift, increased relatedness in the population and remote inbreeding. Cyprus, on the other hand, appears to maintain enough gene flow with the mainland to avoid such an outcome. Our study provides a comparative population genomic analysis of the effects of neutral processes on a classical island‐mainland model system. It provides empirical evidence for the role of stochastic processes in determining the fate of diverging isolated populations.

Demographic history and genetic diversity of wild African harlequin quail (Coturnix delegorguei delegorguei) populations of Kenya

Hunting wild African harlequin quails (Coturnix delegorguei delegorguei) using traditional methods in Western Kenya has been ongoing for generations, yet their genetic diversity and evolutionary history are largely unknown. In this study, the genetic variation and demographic history of wild African harlequin quails were assessed using a 347bp mitochondrial DNA (mtDNA) control region fragment and 119,339 single nucleotide polymorphisms (SNPs) from genotyping-by-sequencing (GBS) data. Genetic diversity analyses revealed that the genetic variation in wild African harlequin quails was predominantly among individuals than populations. Demographic analyses indicated a signal of rapid demographic expansion, and the estimated time since population expansion was found to be 150,000-350,000 years ago, corresponding to around the Pliocene-Pleistocene boundary. A gradual decline in their effective population size was also observed, which raised concerns about their conservation status. These results provide the first account of the genetic diversity of wild African harlequin quails of Siaya, thereby creating a helpful foundation in their biodiversity conservation.

Unexpected post-glacial colonisation route explains the white colour of barn owls (Tyto alba) from the British Isles

The climate fluctuations of the Quaternary shaped the movement of species in and out of glacial refugia. In Europe, the majority of species followed one of the described traditional postglacial recolonization routes from the southern peninsulas towards the north. Like most organisms, barn owls are assumed to have colonized the British Isles by crossing over Doggerland, a land bridge that connected Britain to northern Europe. However, while they are dark rufous in northern Europe, barn owls in the British Isles are conspicuously white, a contrast that could suggest selective forces are at play on the islands. Yet, our analysis of known candidate genes involved in coloration found no signature of selection. Instead, using whole genome sequences and species distribution modelling, we found that owls colonised the British Isles soon after the last glaciation, directly from a white coloured refugium in the Iberian Peninsula, before colonising northern Europe. They would have followed a hitherto unknown post‐glacial colonization route to the Isles over a westwards path of suitable habitat in now submerged land in the Bay of Biscay, thus not crossing Doggerland. As such, they inherited the white colour of their Iberian founders and maintained it through low gene flow with the mainland that prevents the import of rufous alleles. Thus, we contend that neutral processes probably explain this contrasting white colour compared to continental owls. With the barn owl being a top predator, we expect future research will show this unanticipated route was used by other species from its paleo community.

The demographic history of Madagascan micro-endemics: have rare species always been rare?

Extinction has increased as human activities impact ecosystems, yet relatively few species have conservation assessments. Novel approaches are needed to highlight threatened species that are currently data-deficient. Many Madagascan plant species have extremely narrow ranges, but this may not have always been the case-it is unclear how the island's diverse flora evolved. To assess this, we generated restriction-site associated DNA sequence data for 10 Madagascan plant species, estimated effective population size (Ne) for each species and compared this to census (Nc) sizes. In each case, Ne was an order of magnitude larger than Nc-signifying rapid, recent population decline. We then estimated species' demographic history, tracking changes in Ne over time. We show that it is possible to predict extinction risk, particularly in the most threatened species. Furthermore, simulations showed that our approach has the power to detect population decline during the Anthropocene. Our analyses reveal that Madagascar's micro-endemics were not always rare, having experienced a rapid decline in their recent history. This casts further uncertainty over the processes that generated Madagascar's exceptional biodiversity. Our approach targets data-deficient species in need of conservation assessment, particularly in regions where human modification of the environment has been rapid.

Multiple Merger Genealogies in Outbreaks of Mycobacterium tuberculosis

The Kingman coalescent and its developments are often considered among the most important advances in population genetics of the last decades. Demographic inference based on coalescent theory has been used to reconstruct the population dynamics and evolutionary history of several species, including Mycobacterium tuberculosis (MTB), an important human pathogen causing tuberculosis. One key assumption of the Kingman coalescent is that the number of descendants of different individuals does not vary strongly, and violating this assumption could lead to severe biases caused by model misspecification. Individual lineages of MTB are expected to vary strongly in reproductive success because 1) MTB is potentially under constant selection due to the pressure of the host immune system and of antibiotic treatment, 2) MTB undergoes repeated population bottlenecks when it transmits from one host to the next, and 3) some hosts show much higher transmission rates compared with the average (superspreaders).

Here, we used an approximate Bayesian computation approach to test whether multiple-merger coalescents (MMC), a class of models that allow for large variation in reproductive success among lineages, are more appropriate models to study MTB populations. We considered 11 publicly available whole-genome sequence data sets sampled from local MTB populations and outbreaks and found that MMC had a better fit compared with the Kingman coalescent for 10 of the 11 data sets. These results indicate that the null model for analyzing MTB outbreaks should be reassessed and that past findings based on the Kingman coalescent need to be revisited.

Nonparametric coalescent inference of mutation spectrum history and demography

As populations boom and bust, the accumulation of genetic diversity is modulated, encoding histories of living populations in present-day variation. Many methods exist to decode these histories, and all must make strong model assumptions. It is typical to assume that mutations accumulate uniformly across the genome at a constant rate that does not vary between closely related populations. However, recent work shows that mutational processes in human and great ape populations vary across genomic regions and evolve over time. This perturbs the mutation spectrum (relative mutation rates in different local nucleotide contexts). Here, we develop theoretical tools in the framework of Kingman's coalescent to accommodate mutation spectrum dynamics. We present mutation spectrum history inference (mushi), a method to perform nonparametric inference of demographic and mutation spectrum histories from allele frequency data. We use mushi to reconstruct trajectories of effective population size and mutation spectrum divergence between human populations, identify mutation signatures and their dynamics in different human populations, and calibrate the timing of a previously reported mutational pulse in the ancestors of Europeans. We show that mutation spectrum histories can be placed in a well-studied theoretical setting and rigorously inferred from genomic variation data, like other features of evolutionary history.

Contrasting demographic histories revealed in two invasive populations of the dry rot fungus Serpula lacrymans

Globalization and international trade have impacted organisms around the world leading to a considerable number of species establishing in new geographic areas. Many organisms have taken advantage of human-made environments, including buildings. One such species is the dry rot fungus Serpula lacrymans, which is the most aggressive wood-decay fungus in indoor environments in temperate regions. Using population genomic analyses of 36 full genome sequenced isolates, we demonstrated that European and Japanese isolates are highly divergent and the populations split 3000-19,000 generations ago, probably predating human influence. Approximately 250 generations ago, the European population went through a tight bottleneck, probably corresponding to the fungus colonization of the built environment in Europe. The demographic history of these populations, probably lead to low adaptive potential. Only two loci under selection were identified using a F_st outlier approach, and selective sweep analyses identified three loci with extended haplotype homozygosity. The selective sweep analyses found signals in genes possibly related to decay of various substrates in Japan and in genes involved DNA replication and protein modification in Europe. Our results suggest that the dry rot fungus independently established in indoor environments in Europe and Japan and that invasive species can potentially establish large populations in new habitats based on a few colonizing individuals.

Whole-genome analysis of giraffe supports four distinct species

Species is the fundamental taxonomic unit in biology and its delimitation has implications for conservation. In giraffe (Giraffa spp.), multiple taxonomic classifications have been proposed since the early 1900s.¹ However, one species with nine subspecies has been generally accepted,² likely due to limited in-depth assessments, subspecies hybridizing in captivity,^3,4 and anecdotal reports of hybrids in the wild.⁵ Giraffe taxonomy received new attention after population genetic studies using traditional genetic markers suggested at least four species.^6,7 This view has been met with controversy,⁸ setting the stage for debate.^9,10 Genomics is significantly enhancing our understanding of biodiversity and speciation relative to traditional genetic approaches and thus has important implications for species delineation and conservation.¹¹ We present a high-quality de novo genome assembly of the critically endangered Kordofan giraffe (G. camelopardalis antiquorum)¹² and a comprehensive whole-genome analysis of 50 giraffe representing all traditionally recognized subspecies. Population structure and phylogenomic analyses support four separately evolving giraffe lineages, which diverged 230-370 ka ago. These lineages underwent distinct demographic histories and show different levels of heterozygosity and inbreeding. Our results strengthen previous findings of limited gene flow and admixture among putative giraffe species^6,7,9 and establish a genomic foundation for recognizing four species and seven subspecies, the latter of which should be considered as evolutionary significant units. Achieving a consensus over the number of species and subspecies in giraffe is essential for adequately assessing their threat level and will improve conservation efforts for these iconic taxa.

Automatic inference of demographic parameters using generative adversarial networks

Population genetics relies heavily on simulated data for validation, inference and intuition. In particular, since the evolutionary ‘ground truth’ for real data is always limited, simulated data are crucial for training supervised machine learning methods. Simulation software can accurately model evolutionary processes but requires many hand‐selected input parameters. As a result, simulated data often fail to mirror the properties of real genetic data, which limits the scope of methods that rely on it. Here, we develop a novel approach to estimating parameters in population genetic models that automatically adapts to data from any population. Our method, pg‐gan, is based on a generative adversarial network that gradually learns to generate realistic synthetic data. We demonstrate that our method is able to recover input parameters in a simulated isolation‐with‐migration model. We then apply our method to human data from the 1000 Genomes Project and show that we can accurately recapitulate the features of real data.

Population History and Gene Divergence in Native Mexicans Inferred from 76 Human Exomes

Native American genetic variation remains underrepresented in most catalogs of human genome sequencing data. Previous genotyping efforts have revealed that Mexico’s Indigenous population is highly differentiated and substructured, thus potentially harboring higher proportions of private genetic variants of functional and biomedical relevance. Here we have targeted the coding fraction of the genome and characterized its full site frequency spectrum by sequencing 76 exomes from five Indigenous populations across Mexico. Using diffusion approximations, we modeled the demographic history of Indigenous populations from Mexico with northern and southern ethnic groups splitting 7.2 KYA and subsequently diverging locally 6.5 and 5.7 KYA, respectively. Selection scans for positive selection revealed BCL2L13 and KBTBD8 genes as potential candidates for adaptive evolution in Rarámuris and Triquis, respectively. BCL2L13 is highly expressed in skeletal muscle and could be related to physical endurance, a well-known phenotype of the northern Mexico Rarámuri. The KBTBD8 gene has been associated with idiopathic short stature and we found it to be highly differentiated in Triqui, a southern Indigenous group from Oaxaca whose height is extremely low compared to other Native populations.

The Impact of Purifying and Background Selection on the Inference of Population History: Problems and Prospects

Current procedures for inferring population history generally assume complete neutrality—that is, they neglect both direct selection and the effects of selection on linked sites. We here examine how the presence of direct purifying selection and background selection may bias demographic inference by evaluating two commonly-used methods (MSMC and fastsimcoal2), specifically studying how the underlying shape of the distribution of fitness effects and the fraction of directly selected sites interact with demographic parameter estimation. The results show that, even after masking functional genomic regions, background selection may cause the mis-inference of population growth under models of both constant population size and decline. This effect is amplified as the strength of purifying selection and the density of directly selected sites increases, as indicated by the distortion of the site frequency spectrum and levels of nucleotide diversity at linked neutral sites. We also show how simulated changes in background selection effects caused by population size changes can be predicted analytically. We propose a potential method for correcting for the mis-inference of population growth caused by selection. By treating the distribution of fitness effect as a nuisance parameter and averaging across all potential realizations, we demonstrate that even directly selected sites can be used to infer demographic histories with reasonable accuracy.

Population Genomics Insights into the First Wave of COVID-19

Full-genome-sequence computational analyses of the SARS-coronavirus (CoV)-2 genomes allow us to understand the evolutionary events and adaptability mechanisms. We used population genetics analyses on human SARS-CoV-2 genomes available on 2 April 2020 to infer the mutation rate and plausible recombination events between the Betacoronavirus genomes in nonhuman hosts that may have contributed to the evolution of SARS-CoV-2. Furthermore, we localized the targets of recent and strong, positive selection during the first pandemic wave. The genomic regions that appear to be under positive selection are largely co-localized with regions in which recombination from nonhuman hosts took place. Our results suggest that the pangolin coronavirus genome may have contributed to the SARS-CoV-2 genome by recombination with the bat coronavirus genome. However, we find evidence for additional recombination events that involve coronavirus genomes from other hosts, i.e., hedgehogs and sparrows. We further infer that recombination may have recently occurred within human hosts. Finally, we estimate the parameters of a demographic scenario involving an exponential growth of the size of the SARS-CoV-2 populations that have infected European, Asian, and Northern American cohorts, and we demonstrate that a rapid exponential growth in population size from the first wave can support the observed polymorphism patterns in SARS-CoV-2 genomes.

Global drivers of recent diversification in a marine species complex

Investigating historical gene flow in species complexes can indicate how environmental and reproductive barriers shape genome divergence during speciation. The processes influencing species diversification under environmental change remain one of the central focal points of evolutionary biology, particularly for marine organisms with high dispersal potential. We investigated genome-wide divergence, introgression patterns and inferred demographic history between species pairs of all six extant rock lobster species (Jasus spp.), which have a long larval duration of up to two years and have populated continental shelf and seamount habitats around the globe at approximately 40^o S. Genetic differentiation patterns reflected geographic isolation and the environment (i.e. habitat structure). Eastern Pacific species (J. caveorum and J. frontalis) were geographically more distant and genetically more differentiated from the remaining four species. Species associated with continental shelf habitats shared a common ancestry, but are geographically distant from one another. Similarly, species associated with island/seamount habitats in the Atlantic and Indian Oceans shared a common ancestry, but are also geographically distant. Benthic temperature was the environmental variable that explained most of the genetic differentiation (F_ST ), while controlling for the effects of geographic distance. Eastern Pacific species retained a signal of strict isolation following ancient migration, whereas species pairs from Australia and Africa, and seamounts in the Indian and Atlantic oceans, included events of introgression after secondary contact. Our results reveal important effects of habitat and demographic processes on the recent divergence of species within the genus Jasus, providing one of the first empirical studies of genome-wide drivers of diversification that incorporates all extant species in a marine genus with long pelagic larval duration.

Unbiased Estimation of Linkage Disequilibrium from Unphased Data

Linkage disequilibrium (LD) is used to infer evolutionary history, to identify genomic regions under selection, and to dissect the relationship between genotype and phenotype. In each case, we require accurate estimates of LD statistics from sequencing data. Unphased data present a challenge because multilocus haplotypes cannot be inferred exactly. Widely used estimators for the common statistics r2 and D2 exhibit large and variable upward biases that complicate interpretation and comparison across cohorts. Here, we show how to find unbiased estimators for a wide range of two-locus statistics, including D2, for both single and multiple randomly mating populations. These unbiased statistics are particularly well suited to estimate effective population sizes from unlinked loci in small populations. We develop a simple inference pipeline and use it to refine estimates of recent effective population sizes of the threatened Channel Island Fox populations.

Genomic inference of complex domestication histories in three Solanaceae species

Domestication is a human-induced selection process that imprints the genomes of domesticated populations over a short evolutionary time scale and that occurs in a given demographic context. Reconstructing historical gene flow, effective population size changes and their timing is therefore of fundamental interest to understand how plant demography and human selection jointly shape genomic divergence during domestication. Yet, the comparison under a single statistical framework of independent domestication histories across different crop species has been little evaluated so far. Thus, it is unclear whether domestication leads to convergent demographic changes that similarly affect crop genomes. To address this question, we used existing and new transcriptome data on three crop species of Solanaceae (eggplant, pepper and tomato), together with their close wild relatives. We fitted twelve demographic models of increasing complexity on the unfolded joint allele frequency spectrum for each wild/crop pair, and we found evidence for both shared and species-specific demographic processes between species. A convergent history of domestication with gene flow was inferred for all three species, along with evidence of strong reduction in the effective population size during the cultivation stage of tomato and pepper. The absence of any reduction in size of the crop in eggplant stands out from the classical view of the domestication process; as does the existence of a "protracted period" of management before cultivation. Our results also suggest divergent management strategies of modern cultivars among species as their current demography substantially differs. Finally, the timing of domestication is species-specific and supported by the few historical records available.

Jointly Inferring the Dynamics of Population Size and Sampling Intensity from Molecular Sequences

Estimating past population dynamics from molecular sequences that have been sampled longitudinally through time is an important problem in infectious disease epidemiology, molecular ecology, and macroevolution. Popular solutions, such as the skyline and skygrid methods, infer past effective population sizes from the coalescent event times of phylogenies reconstructed from sampled sequences but assume that sequence sampling times are uninformative about population size changes. Recent work has started to question this assumption by exploring how sampling time information can aid coalescent inference. Here, we develop, investigate, and implement a new skyline method, termed the epoch sampling skyline plot (ESP), to jointly estimate the dynamics of population size and sampling rate through time. The ESP is inspired by real-world data collection practices and comprises a flexible model in which the sequence sampling rate is proportional to the population size within an epoch but can change discontinuously between epochs. We show that the ESP is accurate under several realistic sampling protocols and we prove analytically that it can at least double the best precision achievable by standard approaches. We generalize the ESP to incorporate phylogenetic uncertainty in a new Bayesian package (BESP) in BEAST2. We re-examine two well-studied empirical data sets from virus epidemiology and molecular evolution and find that the BESP improves upon previous coalescent estimators and generates new, biologically useful insights into the sampling protocols underpinning these data sets. Sequence sampling times provide a rich source of information for coalescent inference that will become increasingly important as sequence collection intensifies and becomes more formalized.

The evolution of strong reproductive isolation between sympatric intertidal snails

The evolution of strong reproductive isolation (RI) is fundamental to the origins and maintenance of biological diversity, especially in situations where geographical distributions of taxa broadly overlap. But what is the history behind strong barriers currently acting in sympatry? Using whole-genome sequencing and single nucleotide polymorphism genotyping, we inferred (i) the evolutionary relationships, (ii) the strength of RI, and (iii) the demographic history of divergence between two broadly sympatric taxa of intertidal snail. Despite being cryptic, based on external morphology, Littorina arcana and Littorina saxatilis differ in their mode of female reproduction (egg-laying versus brooding), which may generate a strong post-zygotic barrier. We show that egg-laying and brooding snails are closely related, but genetically distinct. Genotyping of 3092 snails from three locations failed to recover any recent hybrid or backcrossed individuals, confirming that RI is strong. There was, however, evidence for a very low level of asymmetrical introgression, suggesting that isolation remains incomplete. The presence of strong, asymmetrical RI was further supported by demographic analysis of these populations. Although the taxa are currently broadly sympatric, demographic modelling suggests that they initially diverged during a short period of geographical separation involving very low gene flow. Our study suggests that some geographical separation may kick-start the evolution of strong RI, facilitating subsequent coexistence of taxa in sympatry. The strength of RI needed to achieve sympatry and the subsequent effect of sympatry on RI remain open questions. This article is part of the theme issue 'Towards the completion of speciation: the evolution of reproductive isolation beyond the first barriers'.

Insights into the neutral and adaptive processes shaping the spatial distribution of genomic variation in the economically important Moroccan locust (Dociostaurus maroccanus)

Understanding the processes that shape neutral and adaptive genomic variation is a fundamental step to determine the demographic and evolutionary dynamics of pest species. Here, we use genomic data obtained via restriction site-associated DNA sequencing to investigate the genetic structure of Moroccan locust (Dociostaurus maroccanus) populations from the westernmost portion of the species distribution (Iberian Peninsula and Canary Islands), infer demographic trends, and determine the role of neutral versus selective processes in shaping spatial patterns of genomic variation in this pest species of great economic importance. Our analyses showed that Iberian populations are characterized by high gene flow, whereas the highly isolated Canarian populations have experienced strong genetic drift and loss of genetic diversity. Historical demographic reconstructions revealed that all populations have passed through a substantial genetic bottleneck around the last glacial maximum (~21 ka BP) followed by a sharp demographic expansion at the onset of the Holocene, indicating increased effective population sizes during warm periods as expected from the thermophilic nature of the species. Genome scans and environmental association analyses identified several loci putatively under selection, suggesting that local adaptation processes in certain populations might not be impeded by widespread gene flow. Finally, all analyses showed few differences between outbreak and nonoutbreak populations. Integrated pest management practices should consider high population connectivity and the potential importance of local adaptation processes on population persistence.

Toward an Evolutionarily Appropriate Null Model: Jointly Inferring Demography and Purifying Selection

The question of the relative evolutionary roles of adaptive and nonadaptive processes has been a central debate in population genetics for nearly a century. While advances have been made in the theoretical development of the underlying models, and statistical methods for estimating their parameters from large-scale genomic data, a framework for an appropriate null model remains elusive. A model incorporating evolutionary processes known to be in constant operation, genetic drift (as modulated by the demographic history of the population) and purifying selection, is lacking. Without such a null model, the role of adaptive processes in shaping within- and between-population variation may not be accurately assessed. Here, we investigate how population size changes and the strength of purifying selection affect patterns of variation at "neutral" sites near functional genomic components. We propose a novel statistical framework for jointly inferring the contribution of the relevant selective and demographic parameters. By means of extensive performance analyses, we quantify the utility of the approach, identify the most important statistics for parameter estimation, and compare the results with existing methods. Finally, we reanalyze genome-wide population-level data from a Zambian population of Drosophila melanogaster, and find that it has experienced a much slower rate of population growth than was inferred when the effects of purifying selection were neglected. Our approach represents an appropriate null model, against which the effects of positive selection can be assessed.

GADMA: Genetic algorithm for inferring demographic history of multiple populations from allele frequency spectrum data

BACKGROUND

The demographic history of any population is imprinted in the genomes of the individuals that make up the population. One of the most popular and convenient representations of genetic information is the allele frequency spectrum (AFS), the distribution of allele frequencies in populations. The joint AFS is commonly used to reconstruct the demographic history of multiple populations, and several methods based on diffusion approximation (e.g., ∂a∂i) and ordinary differential equations (e.g., moments) have been developed and applied for demographic inference. These methods provide an opportunity to simulate AFS under a variety of researcher-specified demographic models and to estimate the best model and associated parameters using likelihood-based local optimizations. However, there are no known algorithms to perform global searches of demographic models with a given AFS.

RESULTS

Here, we introduce a new method that implements a global search using a genetic algorithm for the automatic and unsupervised inference of demographic history from joint AFS data. Our method is implemented in the software GADMA (Genetic Algorithm for Demographic Model Analysis, https://github.com/ctlab/GADMA).

CONCLUSIONS

We demonstrate the performance of GADMA by applying it to sequence data from humans and non-model organisms and show that it is able to automatically infer a demographic model close to or even better than the one that was previously obtained manually. Moreover, GADMA is able to infer multiple demographic models at different local optima close to the global one, providing a larger set of possible scenarios to further explore demographic history.

An ABC Method for Whole-Genome Sequence Data: Inferring Paleolithic and Neolithic Human Expansions

Species generally undergo a complex demographic history consisting, in particular, of multiple changes in population size. Genome-wide sequencing data are potentially highly informative for reconstructing this demographic history. A crucial point is to extract the relevant information from these very large data sets. Here, we design an approach for inferring past demographic events from a moderate number of fully sequenced genomes. Our new approach uses Approximate Bayesian Computation, a simulation-based statistical framework that allows 1) identifying the best demographic scenario among several competing scenarios and 2) estimating the best-fitting parameters under the chosen scenario. Approximate Bayesian Computation relies on the computation of summary statistics. Using a cross-validation approach, we show that statistics such as the lengths of haplotypes shared between individuals, or the decay of linkage disequilibrium with distance, can be combined with classical statistics (e.g., heterozygosity and Tajima's D) to accurately infer complex demographic scenarios including bottlenecks and expansion periods. We also demonstrate the importance of simultaneously estimating the genotyping error rate. Applying our method on genome-wide human-sequence databases, we finally show that a model consisting in a bottleneck followed by a Paleolithic and a Neolithic expansion is the most relevant for Eurasian populations.

The Demographic History of African Drosophila melanogaster

As one of the most commonly utilized organisms in the study of local adaptation, an accurate characterization of the demographic history of Drosophila melanogaster remains as an important research question. This owes both to the inherent interest in characterizing the population history of this model organism, as well as to the well-established importance of an accurate null demographic model for increasing power and decreasing false positive rates in genomic scans for positive selection. Although considerable attention has been afforded to this issue in non-African populations, less is known about the demographic history of African populations, including from the ancestral range of the species. While qualitative predictions and hypotheses have previously been forwarded, we here present a quantitative model fitting of the population history characterizing both the ancestral Zambian population range as well as the subsequently colonized west African populations, which themselves served as the source of multiple non-African colonization events. We here report the split time of the West African population at 72 kya, a date corresponding to human migration into this region as well as a period of climatic changes in the African continent. Furthermore, we have estimated population sizes at this split time. These parameter estimates thus represent an important null model for future investigations in to African and non-African D. melanogaster populations alike.

Integrating population genetics to define conservation units from the core to the edge of Rhinolophus ferrumequinum western range

The greater horseshoe bat (Rhinolophus ferrumequinum) is among the most widespread bat species in Europe but it has experienced severe declines, especially in Northern Europe. This species is listed Near Threatened in the European IUCN Red List of Threatened Animals, and it is considered to be highly sensitive to human activities and particularly to habitat fragmentation. Therefore, understanding the population boundaries and demographic history of populations of this species is of primary importance to assess relevant conservation strategies. In this study, we used 17 microsatellite markers to assess the genetic diversity, the genetic structure, and the demographic history of R. ferrumequinum colonies in the western part of its distribution. We identified one large population showing high levels of genetic diversity and large population size. Lower estimates were found in England and northern France. Analyses of clustering and isolation by distance suggested that the Channel and the Mediterranean seas could impede R. ferrumequinum gene flow. These results provide important information to improve the delineation of R. ferrumequinum management units. We suggest that a large management unit corresponding to the population ranging from Spanish Basque Country to northern France must be considered. Particular attention should be given to mating territories as they seem to play a key role in maintaining high levels of genetic mixing between colonies. Smaller management units corresponding to English and northern France colonies must also be implemented. These insular or peripheral colonies could be at higher risk of extinction in the near future.

Efficiently inferring the demographic history of many populations with allele count data

The sample frequency spectrum (SFS), or histogram of allele counts, is an important summary statistic in evolutionary biology, and is often used to infer the history of population size changes, migrations, and other demographic events affecting a set of populations. The expected multipopulation SFS under a given demographic model can be efficiently computed when the populations in the model are related by a tree, scaling to hundreds of populations. Admixture, back-migration, and introgression are common natural processes that violate the assumption of a tree-like population history, however, and until now the expected SFS could be computed for only a handful of populations when the demographic history is not a tree. In this article, we present a new method for efficiently computing the expected SFS and linear functionals of it, for demographies described by general directed acyclic graphs. This method can scale to more populations than p reviously possible for complex demographic histories including admixture. We apply our method to an 8-population SFS to estimate the timing and strength of a proposed "basal Eurasian" admixture event in human history. We implement and release our method in a new open-source software package momi2.

Geography best explains global patterns of genetic diversity and postglacial co-expansion in marine turtles

For many species, climate oscillations drove cycles of population contraction during cool glacial periods followed by expansion during interglacials. Some groups, however, show evidence of uniform and synchronous expansion, while others display differences in the timing and extent of demographic change. We compared demographic histories inferred from genetic data across marine turtle species to identify responses to postglacial warming shared across taxa and to examine drivers of past demographic change at the global scale. Using coalescent simulations and approximate Bayesian computation (ABC), we estimated demographic parameters, including the likelihood of past population expansion, from a mitochondrial data set encompassing 23 previously identified lineages from all seven marine turtle species. For lineages with a high posterior probability of expansion, we conducted a hierarchical ABC analysis to estimate the proportion of lineages expanding synchronously and the timing of synchronous expansion. We used Bayesian model averaging to identify variables associated with expansion and genetic diversity. Approximately 60% of extant marine turtle lineages showed evidence of expansion, with the rest mainly exhibiting patterns of genetic diversity most consistent with population stability. For lineages showing expansion, there was a strong signal of synchronous expansion after the Last Glacial Maximum. Expansion and genetic diversity were best explained by ocean basin and the degree of endemism for a given lineage. Geographic differences in sensitivity to climate change have implications for prioritizing conservation actions in marine turtles as well as for identifying areas of past demographic stability and potential resilience to future climate change for broadly distributed taxa.

The evolution of microendemism in a reef fish (Hypoplectrus maya)

Marine species tend to have extensive distributions, which are commonly attributed to the dispersal potential provided by planktonic larvae and the rarity of absolute barriers to dispersal in the ocean. Under this paradigm, the occurrence of marine microendemism without geographic isolation in species with planktonic larvae poses a dilemma. The recently described Maya hamlet (Hypoplectrus maya, Serranidae) is exactly such a case, being endemic to a 50-km segment of the Mesoamerican Barrier Reef System (MBRS). We use whole-genome analysis to infer the demographic history of the Maya hamlet and contrast it with the sympatric and pan-Caribbean black (H. nigricans), barred (H. puella) and butter (H. unicolor) hamlets, as well as the allopatric but phenotypically similar blue hamlet (H. gemma). We show that H. maya is indeed a distinct evolutionary lineage, with genomic signatures of inbreeding and a unique demographic history of continuous decrease in effective population size since it diverged from congeners just ~3,000 generations ago. We suggest that this case of microendemism may be driven by the combination of a narrow ecological niche and restrictive oceanographic conditions in the southern MBRS, which is consistent with the occurrence of an unusually high number of marine microendemics in this region. The restricted distribution of the Maya hamlet, its decline in both census and effective population sizes, and the degradation of its habitat place it at risk of extinction. We conclude that the evolution of marine microendemism can be a fast and dynamic process, with extinction possibly occurring before speciation is complete.

The Quetzal Coalescence template library: A C++ programmers resource for integrating distributional, demographic and coalescent models

Genetic samples can be used to understand and predict the behaviour of species living in a fragmented and temporally changing environment. In this regard, models of coalescence conditioned to an environment through an explicit modelling of population growth and migration have been developed in recent years, and simulators implementing these models have been developed, enabling biologists to estimate parameters of interest with Approximate Bayesian Computation techniques. However, model choice remains limited, and developing new coalescence simulators is extremely time consuming because code re-use is limited. We present Quetzal, a C++ library composed of re-usable components, which is sufficiently general to efficiently implement a wide range of spatially explicit coalescence-based environmental models of population genetics and to embed the simulation in an Approximate Bayesian Computation framework. Quetzal is not a simulation program, but a toolbox for programming simulators aimed at the community of scientific coders and research software engineers in molecular ecology and phylogeography. This new code resource is open-source and available at https://becheler.github.io/pages/quetzal.html along with other documentation resources.

Model-based demographic inference of introgression history in European whitefish species pairs'

Parallel phenotypic differentiation is generally attributed to parallel adaptive divergence as an evolutionary response to similar environmental contrasts. Such parallelism may actually originate from several evolutionary scenarios ranging from repeated parallel divergence caused by divergent selection to a unique divergence event followed by gene flow. Reconstructing the evolutionary history underlying parallel phenotypic differentiation is thus fundamental to understand the relative contribution of demography and selection on genomic divergence during speciation. In this study, we investigate the divergence history of replicate European whitefish (Coregonus lavaretus), limnetic and benthic species pairs from two lakes in Norway and two lakes in Switzerland. Demographic models accounting for semi-permeability and linked selection were fitted to the unfolded joint allele frequency spectrum built from genome-wide SNPs and compared to each other in each species pair. We found strong support for a model of asymmetrical post-glacial secondary contact between glacial lineages in all four lakes. Moreover, our results suggest that heterogeneous genomic differentiation has been shaped by the joint action of linked selection accelerating lineage sorting during allopatry, and heterogeneous migration eroding divergence at different rates along the genome following secondary contact. Our analyses reveal how the interplay between demography, selection and historical contingency has influenced the levels of diversity observed in previous whitefish phylogeographic studies. This study thus provides new insights into the historical demographic and selective processes that shaped the divergence associated with ecological speciation in European whitefish.

Unravelling the invasion history of the Asian tiger mosquito in Europe

Multiple introductions are key features for the establishment and persistence of introduced species. However, little is known about the contribution of genetic admixture to the invasive potential of populations. To address this issue, we studied the recent invasion of the Asian tiger mosquito (Aedes albopictus) in Europe. Combining genome-wide single nucleotide polymorphisms and historical knowledge using an approximate Bayesian computation framework, we reconstruct the colonization routes and establish the demographic dynamics of invasion. The colonization of Europe involved at least three independent introductions in Albania, North Italy and Central Italy that subsequently acted as dispersal centres throughout Europe. We show that the topology of human transportation networks shaped demographic histories with North Italy and Central Italy being the main dispersal centres in Europe. Introduction modalities conditioned the levels of genetic diversity in invading populations, and genetically diverse and admixed populations promoted more secondary introductions and have spread farther than single-source invasions. This genomic study provides further crucial insights into a general understanding of the role of genetic diversity promoted by modern trade in driving biological invasions.

The Unreasonable Effectiveness of Convolutional Neural Networks in Population Genetic Inference

Population-scale genomic data sets have given researchers incredible amounts of information from which to infer evolutionary histories. Concomitant with this flood of data, theoretical and methodological advances have sought to extract information from genomic sequences to infer demographic events such as population size changes and gene flow among closely related populations/species, construct recombination maps, and uncover loci underlying recent adaptation. To date, most methods make use of only one or a few summaries of the input sequences and therefore ignore potentially useful information encoded in the data. The most sophisticated of these approaches involve likelihood calculations, which require theoretical advances for each new problem, and often focus on a single aspect of the data (e.g., only allele frequency information) in the interest of mathematical and computational tractability. Directly interrogating the entirety of the input sequence data in a likelihood-free manner would thus offer a fruitful alternative. Here, we accomplish this by representing DNA sequence alignments as images and using a class of deep learning methods called convolutional neural networks (CNNs) to make population genetic inferences from these images. We apply CNNs to a number of evolutionary questions and find that they frequently match or exceed the accuracy of current methods. Importantly, we show that CNNs perform accurate evolutionary model selection and parameter estimation, even on problems that have not received detailed theoretical treatments. Thus, when applied to population genetic alignments, CNNs are capable of outperforming expert-derived statistical methods and offer a new path forward in cases where no likelihood approach exists.

Genetic legacy of state centralization in the Kuba Kingdom of the Democratic Republic of the Congo

Few phenomena have had as profound or long-lasting consequences in human history as the emergence of large-scale centralized states in the place of smaller scale and more local societies. This study examines a fundamental, and yet unexplored, consequence of state formation: its genetic legacy. We studied the genetic impact of state centralization during the formation of the eminent precolonial Kuba Kingdom of the Democratic Republic of the Congo (DRC) in the 17th century. We analyzed genome-wide data from over 690 individuals sampled from 27 different ethnic groups from the Kasai Central Province of the DRC. By comparing genetic patterns in the present-day Kuba, whose ancestors were part of the Kuba Kingdom, with those in neighboring non-Kuba groups, we show that the Kuba today are more genetically diverse and more similar to other groups in the region than expected, consistent with the historical unification of distinct subgroups during state centralization. We also found evidence of genetic mixing dating to the time of the Kingdom at its most prominent. Using this unique dataset, we characterize the genetic history of the Kasai Central Province and describe the historic late wave of migrations into the region that contributed to a Bantu-like ancestry component found across large parts of Africa today. Taken together, we show the power of genetics to evidence events of sociopolitical importance and highlight how DNA can be used to better understand the behaviors of both people and institutions in the past.