A new approach to estimate parameters of speciation models with application to apes

Inference of Coalescence Times and Variant Ages Using Convolutional Neural Networks

Accurate inference of the time to the most recent common ancestor (TMRCA) between pairs of individuals and of the age of genomic variants is key in several population genetic analyses. We developed a likelihood-free approach, called CoalNN, which uses a convolutional neural network to predict pairwise TMRCAs and allele ages from sequencing or SNP array data. CoalNN is trained through simulation and can be adapted to varying parameters, such as demographic history, using transfer learning. Across several simulated scenarios, CoalNN matched or outperformed the accuracy of model-based approaches for pairwise TMRCA and allele age prediction. We applied CoalNN to settings for which model-based approaches are under-developed and performed analyses to gain insights into the set of features it uses to perform TMRCA prediction. We next used CoalNN to analyze 2,504 samples from 26 populations in the 1,000 Genome Project data set, inferring the age of ∼80 million variants. We observed substantial variation across populations and for variants predicted to be pathogenic, reflecting heterogeneous demographic histories and the action of negative selection. We used CoalNN's predicted allele ages to construct genome-wide annotations capturing the signature of past negative selection. We performed LD-score regression analysis of heritability using summary association statistics from 63 independent complex traits and diseases (average N=314k), observing increased annotation-specific effects on heritability compared to a previous allele age annotation. These results highlight the effectiveness of using likelihood-free, simulation-trained models to infer properties of gene genealogies in large genomic data sets.

Ghost admixture in eastern gorillas

Archaic admixture has had a substantial impact on human evolution with multiple events across different clades, including from extinct hominins such as Neanderthals and Denisovans into modern humans. In great apes, archaic admixture has been identified in chimpanzees and bonobos but the possibility of such events has not been explored in other species. Here, we address this question using high-coverage whole-genome sequences from all four extant gorilla subspecies, including six newly sequenced eastern gorillas from previously unsampled geographic regions. Using approximate Bayesian computation with neural networks to model the demographic history of gorillas, we find a signature of admixture from an archaic 'ghost' lineage into the common ancestor of eastern gorillas but not western gorillas. We infer that up to 3% of the genome of these individuals is introgressed from an archaic lineage that diverged more than 3 million years ago from the common ancestor of all extant gorillas. This introgression event took place before the split of mountain and eastern lowland gorillas, probably more than 40 thousand years ago and may have influenced perception of bitter taste in eastern gorillas. When comparing the introgression landscapes of gorillas, humans and bonobos, we find a consistent depletion of introgressed fragments on the X chromosome across these species. However, depletion in protein-coding content is not detectable in eastern gorillas, possibly as a consequence of stronger genetic drift in this species.

Morphological variation of the Pan talus relative to that of Gorilla

OBJECTIVES

Differences in talar articular morphology relative to locomotion have recently been found within Pan and Gorilla. Whole-bone talar morphology within, and shared variation among, Pan and Gorilla (sub)species, however, has yet to be investigated. Here we separately analyze talar external shape within Pan (P. t. troglodytes, P. t. schweinfurthii, P. t. verus, P. paniscus) and Gorilla (G. g. gorilla, G. b. beringei, G. b. graueri) relative to degree of arboreality and body size. Pan and Gorilla are additionally analyzed together to determine if consistent shape differences exist within the genera.

MATERIALS AND METHODS

Talar external shape was quantified using a weighted spherical harmonic analysis. Shape variation both within and among Pan and Gorilla was described using principal component analyses. Root mean square distances were calculated between taxon averages, and resampling statistics conducted to test for pairwise differences.

RESULTS

P. t. verus (most arboreal Pan) talar shape significantly differs from other Pan taxa (p < 0.05 for pairwise comparisons) driven by more asymmetrical trochlear rims and a medially-set talar head. P. t. troglodytes, P. t. schweinfurthii, and P. paniscus do not significantly differ (p > 0.05 for pairwise comparisons). All gorilla taxa exhibit significantly different talar morphologies (p < 0.007 for pairwise comparisons). The more terrestrial subspecies of G. beringei and P. troglodytes exhibit a superoinferiorly taller talar head/neck complex.

DISCUSSION

P. t. verus exhibits talar morphologies that have been previously related to more frequent arboreality. The adaptations in the more terrestrial G. beringei and P. troglodytes subspecies may serve to facilitate load transmission.

Graph-based algorithms for Laplace transformed coalescence time distributions

Extracting information on the selective and demographic past of populations that is contained in samples of genome sequences requires a description of the distribution of the underlying genealogies. Using the Laplace transform, this distribution can be generated with a simple recursive procedure, regardless of model complexity. Assuming an infinite-sites mutation model, the probability of observing specific configurations of linked variants within small haplotype blocks can be recovered from the Laplace transform of the joint distribution of branch lengths. However, the repeated differentiation required to compute these probabilities has proven to be a serious computational bottleneck in earlier implementations.

Here, I show that the state space diagram can be turned into a computational graph, allowing efficient evaluation of the Laplace transform by means of a graph traversal algorithm. This general algorithm can, for example, be applied to tabulate the likelihoods of mutational configurations in non-recombining blocks. This work provides a crucial speed up for existing composite likelihood approaches that rely on the joint distribution of branch lengths to fit isolation with migration models and estimate the parameters of selective sweeps. The associated software is available as an open-source Python library, agemo.

For simple models of idealised populations, the process that generates the observed sequences can be mathematically described. For a given number of samples, we can enumerate all possible genealogies. We can even incorporate the impact of past events like population size reductions on the observed sequence variation. However, the number of possible genealogies will become very large, very fast. So, to extract information from the observed mutations, we need mathematical tools and efficient algorithms to use the information contained within the large collection of possible genealogies.

The Laplace transform is one such mathematical tool that allows us to recursively generate the branch length distribution of all genealogies. Here I show how the transform can be represented as a graph. Using this nonlinear data structure, I define a general procedure to efficiently evaluate the associated mathematical expressions. And I further show how this can be used to speed up existing composite likelihood approaches to fit demographic models and estimate sweep parameters. The associated software, agemo, has a well-documented Python API and has been designed with extensibility in mind, making it an ideal back-end for many other inference approaches in population genetics.

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.

Population dynamics and genetic connectivity in recent chimpanzee history

Knowledge on the population history of endangered species is critical for conservation, but whole-genome data on chimpanzees (Pan troglodytes) is geographically sparse. Here, we produced the first non-invasive geolocalized catalog of genomic diversity by capturing chromosome 21 from 828 non-invasive samples collected at 48 sampling sites across Africa. The four recognized subspecies show clear genetic differentiation correlating with known barriers, while previously undescribed genetic exchange suggests that these have been permeable on a local scale. We obtained a detailed reconstruction of population stratification and fine-scale patterns of isolation, migration, and connectivity, including a comprehensive picture of admixture with bonobos (Pan paniscus). Unlike humans, chimpanzees did not experience extended episodes of long-distance migrations, which might have limited cultural transmission. Finally, based on local rare variation, we implement a fine-grained geolocalization approach demonstrating improved precision in determining the origin of confiscated chimpanzees.

Estimating bonobo (Pan paniscus) and chimpanzee (Pan troglodytes) evolutionary history from nucleotide site patterns

There is genomic evidence of widespread admixture in deep time between many closely related species, including humans. Our closest living relatives, bonobos and chimpanzees, may also exhibit such patterns. However, assessing the exact degree of interbreeding remains challenging because previous studies have resulted in multiple inconsistent demographic models. We use an approach that addresses these gaps by analyzing all lineages, simultaneously estimating parameters, and comparing previously models. We find evidence of considerable introgression from western into eastern chimpanzees. We also show more breeding females than males and evidence of male-biased dispersal in western chimpanzees. These findings highlight the extent of admixture in bonobo and chimpanzee evolutionary history and are consistent with substantial differences between past and present chimpanzee biogeography.

Admixture appears increasingly ubiquitous in the evolutionary history of various taxa, including humans. Such gene flow likely also occurred among our closest living relatives: bonobos (Pan paniscus) and chimpanzees (Pan troglodytes). However, our understanding of their evolutionary history has been limited by studies that do not consider all Pan lineages or do not analyze all lineages simultaneously, resulting in conflicting demographic models. Here, we investigate this gap in knowledge using nucleotide site patterns calculated from whole-genome sequences from the autosomes of 71 bonobos and chimpanzees, representing all five extant Pan lineages. We estimated demographic parameters and compared all previously proposed demographic models for this clade. We further considered sex bias in Pan evolutionary history by analyzing the site patterns from the X chromosome. We show that 1) 21% of autosomal DNA in eastern chimpanzees derives from western chimpanzee introgression and that 2) all four chimpanzee lineages share a common ancestor about 987,000 y ago, much earlier than previous estimates. In addition, we suggest that 3) there was male reproductive skew throughout Pan evolutionary history and find evidence of 4) male-biased dispersal from western to eastern chimpanzees. Collectively, these results offer insight into bonobo and chimpanzee evolutionary history and suggest considerable differences between current and historic chimpanzee biogeography.

Evolutionary Genetic Signatures of Selection on Bone-Related Variation within Human and Chimpanzee Populations

Bone strength and the incidence and severity of skeletal disorders vary significantly among human populations, due in part to underlying genetic differentiation. While clinical models predict that this variation is largely deleterious, natural population variation unrelated to disease can go unnoticed, altering our perception of how natural selection has shaped bone morphologies over deep and recent time periods. Here, we conduct the first comparative population-based genetic analysis of the main bone structural protein gene, collagen type I α 1 (COL1A1), in clinical and 1000 Genomes Project datasets in humans, and in natural populations of chimpanzees. Contrary to predictions from clinical studies, we reveal abundant COL1A1 amino acid variation, predicted to have little association with disease in the natural population. We also find signatures of positive selection associated with intron haplotype structure, linkage disequilibrium, and population differentiation in regions of known gene expression regulation in humans and chimpanzees. These results recall how recent and deep evolutionary regimes can be linked, in that bone morphology differences that developed among vertebrates over 450 million years of evolution are the result of positive selection on subtle type I collagen functional variation segregating within populations over time.

The complex Y-chromosomal history of gorillas

Studies of the evolutionary relationships among gorilla populations using autosomal and mitochondrial sequences suggest that male-mediated gene flow may have been important in the past, but data on the Y-chromosomal relationships among the gorilla subspecies are limited. Here, we genotyped blood and noninvasively collected fecal samples from 12 captives and 257 wild male gorillas of known origin representing all four subspecies (Gorilla gorilla gorilla, G. g. diehli, G. beringei beringei, and G. b. graueri) at 10 Y-linked microsatellite loci resulting in 102 unique Y-haplotypes for 224 individuals. We found that western lowland gorilla (G. g. gorilla) haplotypes were consistently more diverse than any other subspecies for all measures of diversity and comprised several genetically distinct groups. However, these did not correspond to geographical proximity and some closely related haplotypes were found several hundred kilometers apart. Similarly, our broad sampling of eastern gorillas revealed that mountain (G. b. beringei) and Grauer's (G. b. graueri) gorilla Y-chromosomal haplotypes did not form distinct clusters. These observations suggest structure in the ancestral population with subsequent mixing of differentiated haplotypes by male dispersal for western lowland gorillas, and postisolation migration or incomplete lineage sorting due to short divergence times for eastern gorillas.

A brief history and popularity of methods and tools used to estimate micro-evolutionary forces

Population genetics is a field of research that predates the current generations of sequencing technology. Those approaches, that were established before massively parallel sequencing methods, have been adapted to these new marker systems (in some cases involving the development of new methods) that allow genome-wide estimates of the four major micro-evolutionary forces-mutation, gene flow, genetic drift, and selection. Nevertheless, classic population genetic markers are still commonly used and a plethora of analysis methods and programs is available for these and high-throughput sequencing (HTS) data. These methods employ various and diverse theoretical and statistical frameworks, to varying degrees of success, to estimate similar evolutionary parameters making it difficult to get a concise overview across the available approaches. Presently, reviews on this topic generally focus on a particular class of methods to estimate one or two evolutionary parameters. Here, we provide a brief history of methods and a comprehensive list of available programs for estimating micro-evolutionary forces. We furthermore analyzed their usage within the research community based on popularity (citation bias) and discuss the implications of this bias for the software community. We found that a few programs received the majority of citations, with program success being independent of both the parameters estimated and the computing platform. The only deviation from a model of exponential growth in the number of citations was found for the presence of a graphical user interface (GUI). Interestingly, no relationship was found for the impact factor of the journals, when the tools were published, suggesting accessibility might be more important than visibility.

Inference of gene flow in the process of speciation: Efficient maximum-likelihood implementation of a generalised isolation-with-migration model

The 'isolation with migration' (IM) model has been extensively used in the literature to detect gene flow during the process of speciation. In this model, an ancestral population split into two or more descendant populations which subsequently exchanged migrants at a constant rate until the present. Of course, the assumption of constant gene flow until the present is often over-simplistic in the context of speciation. In this paper, we consider a 'generalised IM' (GIM) model: a two-population IM model in which migration rates and population sizes are allowed to change at some point in the past. By developing a maximum-likelihood implementation of this model, we enable inference on both historical and contemporary rates of gene flow between two closely related populations or species. The GIM model encompasses both the standard two-population IM model and the 'isolation with initial migration' (IIM) model as special cases, as well as a model of secondary contact. We examine for simulated data how our method can be used, by means of likelihood ratio tests or AIC scores, to distinguish between the following scenarios of population divergence: (a) divergence in complete isolation; (b) divergence with a period of gene flow followed by isolation; (c) divergence with a period of isolation followed by secondary contact; (d) divergence with ongoing gene flow. Our method is based on the coalescent and is suitable for data sets consisting of the number of nucleotide differences between one pair of DNA sequences at each of a large number of independent loci. As our method relies on an explicit expression for the likelihood, it is computationally very fast.

Similar patterns of genetic diversity and linkage disequilibrium in Western chimpanzees (Pan troglodytes verus) and humans indicate highly conserved mechanisms of MHC molecular evolution

BACKGROUND

Many species are threatened with extinction as their population sizes decrease with changing environments or face novel pathogenic threats. A reduction of genetic diversity at major histocompatibility complex (MHC) genes may have dramatic effects on populations' survival, as these genes play a key role in adaptive immunity. This might be the case for chimpanzees, the MHC genes of which reveal signatures of an ancient selective sweep likely due to a viral epidemic that reduced their population size a few million years ago. To better assess how this past event affected MHC variation in chimpanzees compared to humans, we analysed several indexes of genetic diversity and linkage disequilibrium across seven MHC genes on four cohorts of chimpanzees and we compared them to those estimated at orthologous HLA genes in a large set of human populations.

RESULTS

Interestingly, the analyses uncovered similar patterns of both molecular diversity and linkage disequilibrium across the seven MHC genes in chimpanzees and humans. Indeed, in both species the greatest allelic richness and heterozygosity were found at loci A, B, C and DRB1, the greatest nucleotide diversity at loci DRB1, DQA1 and DQB1, and both significant global linkage disequilibrium and the greatest proportions of haplotypes in linkage disequilibrium were observed at pairs DQA1 ~ DQB1, DQA1 ~ DRB1, DQB1 ~ DRB1 and B ~ C. Our results also showed that, despite some differences among loci, the levels of genetic diversity and linkage disequilibrium observed in contemporary chimpanzees were globally similar to those estimated in small isolated human populations, in contrast to significant differences compared to large populations.

CONCLUSIONS

We conclude, first, that highly conserved mechanisms shaped the diversity of orthologous MHC genes in chimpanzees and humans. Furthermore, our findings support the hypothesis that an ancient demographic decline affecting the chimpanzee populations - like that ascribed to a viral epidemic - exerted a substantial effect on the molecular diversity of their MHC genes, albeit not more pronounced than that experienced by HLA genes in human populations that underwent rapid genetic drift during humans' peopling history. We thus propose a model where chimpanzees' MHC genes regenerated molecular variation through recombination/gene conversion and/or balancing selection after the selective sweep.

Efficiently Summarizing Relationships in Large Samples: A General Duality Between Statistics of Genealogies and Genomes

As a genetic mutation is passed down across generations, it distinguishes those genomes that have inherited it from those that have not, providing a glimpse of the genealogical tree relating the genomes to each other at that site. Statistical summaries of genetic variation therefore also describe the underlying genealogies. We use this correspondence to define a general framework that efficiently computes single-site population genetic statistics using the succinct tree sequence encoding of genealogies and genome sequence. The general approach accumulates sample weights within the genealogical tree at each position on the genome, which are then combined using a summary function; different statistics result from different choices of weight and function. Results can be reported in three ways: by site, which corresponds to statistics calculated as usual from genome sequence; by branch, which gives the expected value of the dual site statistic under the infinite sites model of mutation, and by node, which summarizes the contribution of each ancestor to these statistics. We use the framework to implement many currently defined statistics of genome sequence (making the statistics' relationship to the underlying genealogical trees concrete and explicit), as well as the corresponding branch statistics of tree shape. We evaluate computational performance using simulated data, and show that calculating statistics from tree sequences using this general framework is several orders of magnitude more efficient than optimized matrix-based methods in terms of both run time and memory requirements. We also explore how well the duality between site and branch statistics holds in practice on trees inferred from the 1000 Genomes Project data set, and discuss ways in which deviations may encode interesting biological signals.

Adaptive divergence in shell morphology in an ongoing gastropod radiation from Lake Malawi

Background

Ecological speciation is a prominent mechanism of diversification but in many evolutionary radiations, particularly in invertebrates, it remains unclear whether supposedly critical ecological traits drove or facilitated diversification. As a result, we lack accurate knowledge on the drivers of diversification for most evolutionary radiations along the tree of life. Freshwater mollusks present an enigmatic example: Putatively adaptive radiations are being described in various families, typically from long-lived lakes, whereas other taxa represent celebrated model systems in the study of ecophenotypic plasticity. Here we examine determinants of shell-shape variation in three nominal species of an ongoing ampullariid radiation in the Malawi Basin (Lanistes nyassanus, L. solidus and Lanistes sp. (ovum-like)) with a common garden experiment and semi-landmark morphometrics.

Results

We found significant differences in survival and fecundity among these species in contrasting habitats. Morphological differences observed in the wild persisted in our experiments for L. nyassanus versus L. solidus and L. sp. (ovum-like), but differences between L. solidus and L. sp. (ovum-like) disappeared and re-emerged in the F₁ and F₂ generations, respectively. These results indicate that plasticity occurred, but that it is not solely responsible for the observed differences. Our experiments provide the first unambiguous evidence for genetic divergence in shell morphology in an ongoing freshwater gastropod radiation in association with marked fitness differences among species under controlled habitat conditions.

Conclusions

Our results indicate that differences in shell morphology among Lanistes species occupying different habitats have an adaptive value. These results also facilitate an accurate reinterpretation of morphological variation in fossil Lanistes radiations, and thus macroevolutionary dynamics. Finally, our work testifies that the shells of freshwater gastropods may retain signatures of adaptation at low taxonomic levels, beyond representing an evolutionary novelty responsible for much of the diversity and disparity in mollusks altogether.

Recent advances in Bayesian inference of isolation-with-migration models

Isolation-with-migration (IM) models have become popular for explaining population divergence in the presence of migrations. Bayesian methods are commonly used to estimate IM models, but they are limited to small data analysis or simple model inference. Recently three methods, IMa3, MIST, and AIM, resolved these limitations. Here, we describe the major problems addressed by these three software and compare differences among their inference methods, despite their use of the same standard likelihood function.

Coalescent Simulation with msprime

Coalescent simulation is a fundamental tool in modern population genetics. The msprime library provides unprecedented scalability in terms of both the simulations that can be performed and the efficiency with which the results can be processed. We show how coalescent models for population structure and demography can be constructed using a simple Python API, as well as how we can process the results of such simulations to efficiently calculate statistics of interest. We illustrate msprime's flexibility by implementing a simple (but functional) approximate Bayesian computation inference method in just a few tens of lines of code.

Detection of Shared Balancing Selection in the Absence of Trans-Species Polymorphism

Trans-species polymorphism has been widely used as a key sign of long-term balancing selection across multiple species. However, such sites are often rare in the genome and could result from mutational processes or technical artifacts. Few methods are yet available to specifically detect footprints of trans-species balancing selection without using trans-species polymorphic sites. In this study, we develop summary- and model-based approaches that are each specifically tailored to uncover regions of long-term balancing selection shared by a set of species by using genomic patterns of intraspecific polymorphism and interspecific fixed differences. We demonstrate that our trans-species statistics have substantially higher power than single-species approaches to detect footprints of trans-species balancing selection, and are robust to those that do not affect all tested species. We further apply our model-based methods to human and chimpanzee whole-genome sequencing data. In addition to the previously established major histocompatibility complex and malaria resistance-associated FREM3/GYPE regions, we also find outstanding genomic regions involved in barrier integrity and innate immunity, such as the GRIK1/CLDN17 intergenic region, and the SLC35F1 and ABCA13 genes. Our findings not only echo the significance of pathogen defense but also reveal novel candidates in maintaining balanced polymorphisms across human and chimpanzee lineages. Finally, we show that these trans-species statistics can be applied to and work well for an arbitrary number of species, and integrate them into open-source software packages for ease of use by the scientific community.

Phylogeny Estimation by Integration over Isolation with Migration Models

Phylogeny estimation is difficult for closely related populations and species, especially if they have been exchanging genes. We present a hierarchical Bayesian, Markov-chain Monte Carlo method with a state space that includes all possible phylogenies in a full Isolation-with-Migration model framework. The method is based on a new type of genealogy augmentation called a "hidden genealogy" that enables efficient updating of the phylogeny. This is the first likelihood-based method to fully incorporate directional gene flow and genetic drift for estimation of a species or population phylogeny. Application to human hunter-gatherer populations from Africa revealed a clear phylogenetic history, with strong support for gene exchange with an unsampled ghost population, and relatively ancient divergence between a ghost population and modern human populations, consistent with human/archaic divergence. In contrast, a study of five chimpanzee populations reveals a clear phylogeny with several pairs of populations having exchanged DNA, but does not support a history with an unsampled ghost population.

ABLE: blockwise site frequency spectra for inferring complex population histories and recombination

We introduce ABLE (Approximate Blockwise Likelihood Estimation), a novel simulation-based composite likelihood method that uses the blockwise site frequency spectrum to jointly infer past demography and recombination. ABLE is explicitly designed for a wide variety of data from unphased diploid genomes to genome-wide multi-locus data (for example, RADSeq) and can also accommodate arbitrarily large samples. We use simulations to demonstrate the accuracy of this method to infer complex histories of divergence and gene flow and reanalyze whole genome data from two species of orangutan. ABLE is available for download at https://github.com/champost/ABLE.

The divergence history of European blue mussel species reconstructed from Approximate Bayesian Computation: the effects of sequencing techniques and sampling strategies

Genome-scale diversity data are increasingly available in a variety of biological systems, and can be used to reconstruct the past evolutionary history of species divergence. However, extracting the full demographic information from these data is not trivial, and requires inferential methods that account for the diversity of coalescent histories throughout the genome. Here, we evaluate the potential and limitations of one such approach. We reexamine a well-known system of mussel sister species, using the joint site frequency spectrum (jSFS) of synonymous mutations computed either from exome capture or RNA-seq, in an Approximate Bayesian Computation (ABC) framework. We first assess the best sampling strategy (number of: individuals, loci, and bins in the jSFS), and show that model selection is robust to variation in the number of individuals and loci. In contrast, different binning choices when summarizing the jSFS, strongly affect the results: including classes of low and high frequency shared polymorphisms can more effectively reveal recent migration events. We then take advantage of the flexibility of ABC to compare more realistic models of speciation, including variation in migration rates through time (i.e., periodic connectivity) and across genes (i.e., genome-wide heterogeneity in migration rates). We show that these models were consistently selected as the most probable, suggesting that mussels have experienced a complex history of gene flow during divergence and that the species boundary is semi-permeable. Our work provides a comprehensive evaluation of ABC demographic inference in mussels based on the coding jSFS, and supplies guidelines for employing different sequencing techniques and sampling strategies. We emphasize, perhaps surprisingly, that inferences are less limited by the volume of data, than by the way in which they are analyzed.

Ancestral polymorphisms explain the role of chromosomal inversions in speciation

Understanding the role of chromosomal inversions in speciation is a fundamental problem in evolutionary genetics. Here, we perform a comprehensive reconstruction of the evolutionary histories of the chromosomal inversions in Drosophila persimilis and D. pseudoobscura. We provide a solution to the puzzling origins of the selfish Sex-Ratio arrangement in D. persimilis and uncover surprising patterns of phylogenetic discordance on this chromosome. These patterns show that, contrary to widely held views, all fixed chromosomal inversions between D. persimilis and D. pseudoobscura were already present in their ancestral population long before the species split. Our results suggest that patterns of higher genomic divergence and an association of reproductive isolation genes with chromosomal inversions may be a direct consequence of incomplete lineage sorting of ancestral polymorphisms. These findings force a reconsideration of the role of chromosomal inversions in speciation, not as protectors of existing hybrid incompatibilities, but as fertile grounds for their formation.

Modeling the Multiple Facets of Speciation-with-Gene-Flow toward Inferring the Divergence History of Lake Whitefish Species Pairs (Coregonus clupeaformis)

Parallel divergence across replicated species pairs occurring in similar environmental contrasts may arise through distinct evolutionary scenarios. Deciphering whether such parallelism actually reflects repeated parallel divergence driven by divergent selection or a single divergence event with subsequent gene flow needs to be ascertained. Reconstructing historical gene flow is therefore of fundamental interest to understand how demography and selection jointly shaped genomic divergence during speciation. Here, we use an extended modeling framework to explore the multiple facets of speciation-with-gene-flow with demo-genetic divergence models that capture both temporal and genomic variation in effective population size and migration rate. We investigate the divergence history of replicate sympatric species pairs of Lake Whitefish (normal benthic and dwarf limnetic) characterized by variable degrees of ecological divergence and reproductive isolation. Genome-wide SNPs were used to document the extent of genetic differentiation in each species pair, and 26 divergence models were fitted and compared with the unfolded joint allele frequency spectrum of each pair. We found evidence that a recent (circa 3,000–4,000 generations) asymmetrical secondary contact between expanding postglacial populations has accompanied Whitefish diversification. Our results suggest that heterogeneous genomic differentiation has emerged through the combined effects of linked selection generating variable rates of lineage sorting across the genome during geographical isolation, and heterogeneous introgression eroding divergence at different rates across the genome upon secondary contact. This study thus provides a new retrospective insight into the historical demographic and selective processes that shaped a continuum of divergence associated with ecological speciation.

Reticulation, divergence, and the phylogeography-phylogenetics continuum

Phylogeography, and its extensions into comparative phylogeography, have their roots in the layering of gene trees across geography, a paradigm that was greatly facilitated by the nonrecombining, fast evolution provided by animal mtDNA. As phylogeography moves into the era of next-generation sequencing, the specter of reticulation at several levels-within loci and genomes in the form of recombination and across populations and species in the form of introgression-has raised its head with a prominence even greater than glimpsed during the nuclear gene PCR era. Here we explore the theme of reticulation in comparative phylogeography, speciation analysis, and phylogenomics, and ask how the centrality of gene trees has fared in the next-generation era. To frame these issues, we first provide a snapshot of multilocus phylogeographic studies across the Carpentarian Barrier, a prominent biogeographic barrier dividing faunas spanning the monsoon tropics in northern Australia. We find that divergence across this barrier is evident in most species, but is heterogeneous in time and demographic history, often reflecting the taxonomic distinctness of lineages spanning it. We then discuss a variety of forces generating reticulate patterns in phylogeography, including introgression, contact zones, and the potential selection-driven outliers on next-generation molecular markers. We emphasize the continued need for demographic models incorporating reticulation at the level of genomes and populations, and conclude that gene trees, whether explicit or implicit, should continue to play a role in the future of phylogeography.

Bayesian Analysis of Evolutionary Divergence with Genomic Data under Diverse Demographic Models

We present a new Bayesian method for estimating demographic and phylogenetic history using population genomic data. Several key innovations are introduced that allow the study of diverse models within an Isolation-with-Migration framework. The new method implements a 2-step analysis, with an initial Markov chain Monte Carlo (MCMC) phase that samples simple coalescent trees, followed by the calculation of the joint posterior density for the parameters of a demographic model. In step 1, the MCMC sampling phase, the method uses a reduced state space, consisting of coalescent trees without migration paths, and a simple importance sampling distribution without the demography of interest. Once obtained, a single sample of trees can be used in step 2 to calculate the joint posterior density for model parameters under multiple diverse demographic models, without having to repeat MCMC runs. Because migration paths are not included in the state space of the MCMC phase, but rather are handled by analytic integration in step 2 of the analysis, the method is scalable to a large number of loci with excellent MCMC mixing properties. With an implementation of the new method in the computer program MIST, we demonstrate the method's accuracy, scalability, and other advantages using simulated data and DNA sequences of two common chimpanzee subspecies: Pan troglodytes (P. t.) troglodytes and P. t. verus.

On the independent gene trees assumption in phylogenomic studies

Multilocus coalescent methods for inferring species trees or historical demographic parameters typically require the assumption that gene trees for sampled SNPs or DNA sequence loci are conditionally independent given their species tree. In practice, researchers have used different criteria to delimit "independent loci." One criterion identifies sampled loci as being independent of each other if they undergo Mendelian independent assortment (IA criterion). O'Neill et al. (2013, Molecular Ecology, 22, 111-129) used this approach in their phylogeographic study of North American tiger salamander species complex. In two other studies, researchers developed a pair of related methods that employ an independent genealogies criterion (IG criterion), which considers the effects of population-level recombination on correlations between the gene trees of intrachromosomal loci. Here, I explain these three methods, illustrate their use with example data, and evaluate their efficacies. I show that the IA approach is more conservative, is simpler to use and requires fewer assumptions than the IG approaches. However, IG approaches can identify much larger numbers of independent loci than the IA method, which, in turn, allows researchers to obtain more precise and accurate estimates of species trees and historical demographic parameters. A disadvantage of the IG methods is that they require an estimate of the population recombination rate. Despite their drawbacks, IA and IG approaches provide molecular ecologists with promising a priori methods for selecting SNPs or DNA sequence loci that likely meet the independence assumption in coalescent-based phylogenomic studies.

Limited genomic consequences of hybridization between two African clawed frogs, Xenopus gilli and X. laevis (Anura: Pipidae)

The Cape platanna, Xenopus gilli, an endangered frog, hybridizes with the African clawed frog, X. laevis, in South Africa. Estimates of the extent of gene flow between these species range from pervasive to rare. Efforts have been made in the last 30 years to minimize hybridization between these two species in the west population of X. gilli, but not the east populations. To further explore the impact of hybridization and the efforts to minimize it, we examined molecular variation in one mitochondrial and 13 nuclear genes in genetic samples collected recently (2013) and also over two decades ago (1994). Despite the presence of F₁ hybrids, none of the genomic regions we surveyed had evidence of gene flow between these species, indicating a lack of extensive introgression. Additionally we found no significant effect of sampling time on genetic diversity of populations of each species. Thus, we speculate that F₁ hybrids have low fitness and are not backcrossing with the parental species to an appreciable degree. Within X. gilli, evidence for gene flow was recovered between eastern and western populations, a finding that has implications for conservation management of this species and its threatened habitat.

Inference of Gene Flow in the Process of Speciation: An Efficient Maximum-Likelihood Method for the Isolation-with-Initial-Migration Model

The isolation-with-migration (IM) model is commonly used to make inferences about gene flow during speciation, using polymorphism data. However, it has been reported that the parameter estimates obtained by fitting the IM model are very sensitive to the model's assumptions-including the assumption of constant gene flow until the present. This article is concerned with the isolation-with-initial-migration (IIM) model, which drops precisely this assumption. In the IIM model, one ancestral population divides into two descendant subpopulations, between which there is an initial period of gene flow and a subsequent period of isolation. We derive a very fast method of fitting an extended version of the IIM model, which also allows for asymmetric gene flow and unequal population sizes. This is a maximum-likelihood method, applicable to data on the number of segregating sites between pairs of DNA sequences from a large number of independent loci. In addition to obtaining parameter estimates, our method can also be used, by means of likelihood-ratio tests, to distinguish between alternative models representing the following divergence scenarios: (a) divergence with potentially asymmetric gene flow until the present, (b) divergence with potentially asymmetric gene flow until some point in the past and in isolation since then, and (c) divergence in complete isolation. We illustrate the procedure on pairs of Drosophila sequences from ∼30,000 loci. The computing time needed to fit the most complex version of the model to this data set is only a couple of minutes. The R code to fit the IIM model can be found in the supplementary files of this article.

Shedding Light on the Grey Zone of Speciation along a Continuum of Genomic Divergence

Speciation results from the progressive accumulation of mutations that decrease the probability of mating between parental populations or reduce the fitness of hybrids—the so-called species barriers. The speciation genomic literature, however, is mainly a collection of case studies, each with its own approach and specificities, such that a global view of the gradual process of evolution from one to two species is currently lacking. Of primary importance is the prevalence of gene flow between diverging entities, which is central in most species concepts and has been widely discussed in recent years. Here, we explore the continuum of speciation thanks to a comparative analysis of genomic data from 61 pairs of populations/species of animals with variable levels of divergence. Gene flow between diverging gene pools is assessed under an approximate Bayesian computation (ABC) framework. We show that the intermediate "grey zone" of speciation, in which taxonomy is often controversial, spans from 0.5% to 2% of net synonymous divergence, irrespective of species life history traits or ecology. Thanks to appropriate modeling of among-locus variation in genetic drift and introgression rate, we clarify the status of the majority of ambiguous cases and uncover a number of cryptic species. Our analysis also reveals the high incidence in animals of semi-isolated species (when some but not all loci are affected by barriers to gene flow) and highlights the intrinsic difficulty, both statistical and conceptual, of delineating species in the grey zone of speciation.

Isolated populations accumulate genetic differences across their genomes as they diverge, whereas gene flow between populations counteracts divergence and tends to restore genetic homogeneity. Speciation proceeds by the accumulation at specific loci of mutations that reduce the fitness of hybrids, therefore preventing gene flow—the so-called species barriers. Importantly, species barriers are expected to act locally within the genome, leading to the prediction of a mosaic pattern of genetic differentiation between populations at intermediate levels of divergence—the genic view of speciation. At the same time, linked selection also contributes to speed up differentiation in low-recombining and gene-dense regions. We used a modelling approach that accounts for both sources of genomic heterogeneity and explored a wide continuum of genomic divergence made by 61 pairs of species/populations in animals. Our analysis provides a unifying picture of the relationship between molecular divergence and ability to exchange genes. We show that the "grey zone" of speciation—the intermediate state in which species definition is controversial—spans from 0.5% to 2% of molecular divergence, with these thresholds being independent of species life history traits and ecology. Semi-isolated species, between which alleles can be exchanged at some but not all loci, are numerous, with the earliest species barriers being detected at divergences as low as 0.075%. These results have important implications regarding taxonomy, conservation biology, and the management of biodiversity.

Chimpanzee genomic diversity reveals ancient admixture with bonobos

Our closest living relatives, chimpanzees and bonobos, have a complex demographic history. We analyzed the high-coverage whole genomes of 75 wild-born chimpanzees and bonobos from 10 countries in Africa. We found that chimpanzee population substructure makes genetic information a good predictor of geographic origin at country and regional scales. Multiple lines of evidence suggest that gene flow occurred from bonobos into the ancestors of central and eastern chimpanzees between 200,000 and 550,000 years ago, probably with subsequent spread into Nigeria-Cameroon chimpanzees. Together with another, possibly more recent contact (after 200,000 years ago), bonobos contributed less than 1% to the central chimpanzee genomes. Admixture thus appears to have been widespread during hominid evolution.

Evolution and demography of the great apes

The great apes are the closest living relatives of humans. Chimpanzees and bonobos group together with humans, while gorillas and orangutans are more divergent from humans. Here, we review insights into their evolution pertaining to the topology of species and subspecies and the reconstruction of their demography based on genome-wide variation. These advances have only become possible recently through next-generation sequencing technologies. Given the close relationship to humans, they provide an important evolutionary context for human genetics.

Epidemiological Surveillance of Lymphocryptovirus Infection in Wild Bonobos

Lymphocryptovirus (LCV) is one of the major gena in the herpesvirus family and is widely disseminated among primates. LCVs of human and rhesus macaques are shown to be causative agents of a number of malignant diseases including lymphoma and carcinoma. Bonobos (Pan paniscus) are highly endangered and the least studied species of the great apes. Considering the potential pathogenicity of the LCV that might threaten the fate of wild bonobos, population-based epidemiological information in terms of LCV prevalence in different location of Bonobo’s habitats will help propose improved conservation strategies for the bonobos. However, such data are not available yet because it is very difficult to collect blood samples in the wild and thus virtually impossible to conduct sero-epidemiological study on the wild ape. In order to overcome this issue, we focused on evaluating anti-LCV IgA in the feces of bonobos, which are available in a non-invasive manner. Preliminary study showed that anti-LCV IgA but not IgG was efficiently and reproducibly detected in the feces of captive chimpanzees. It is noteworthy that the fecal IgA-positive individuals were seropositive for both anti-LCV IgG and IgA and that the IgA antibodies in both sera and feces were also detectable by Western blotting assay. These results indicate that the detection of fecal anti-LCV IgA is likely a reliable and feasible for epidemiological surveillance of LCV prevalence in the great apes. We then applied this method and found that 31% of wild bonobos tested were positive for anti-LCV IgA antibody in the feces. Notably, the positivity rates varied extensively among their sampled populations. In conclusion, our results in this study demonstrate that LCV is highly disseminated among wild bonobos while the prevalence is remarkably diverse in their population-dependent manner.

Genetic demographic networks: Mathematical model and applications

Recent improvement in the quality of genetic data obtained from extinct human populations and their ancestors encourages searching for answers to basic questions regarding human population history. The most common and successful are model-based approaches, in which genetic data are compared to the data obtained from the assumed demography model. Using such approach, it is possible to either validate or adjust assumed demography. Model fit to data can be obtained based on reverse-time coalescent simulations or forward-time simulations. In this paper we introduce a computational method based on mathematical equation that allows obtaining joint distributions of pairs of individuals under a specified demography model, each of them characterized by a genetic variant at a chosen locus. The two individuals are randomly sampled from either the same or two different populations. The model assumes three types of demographic events (split, merge and migration). Populations evolve according to the time-continuous Moran model with drift and Markov-process mutation. This latter process is described by the Lyapunov-type equation introduced by O'Brien and generalized in our previous works. Application of this equation constitutes an original contribution. In the result section of the paper we present sample applications of our model to both simulated and literature-based demographies. Among other we include a study of the Slavs-Balts-Finns genetic relationship, in which we model split and migrations between the Balts and Slavs. We also include another example that involves the migration rates between farmers and hunters-gatherers, based on modern and ancient DNA samples. This latter process was previously studied using coalescent simulations. Our results are in general agreement with the previous method, which provides validation of our approach. Although our model is not an alternative to simulation methods in the practical sense, it provides an algorithm to compute pairwise distributions of alleles, in the case of haploid non-recombining loci such as mitochondrial and Y-chromosome loci in humans.

Parallel genetic divergence among coastal-marine ecotype pairs of European anchovy explained by differential introgression after secondary contact

Ecophenotypic differentiation among replicate ecotype pairs within a species complex is often attributed to independent outcomes of parallel divergence driven by adaptation to similar environmental contrasts. However, the extent to which parallel phenotypic and genetic divergence patterns have emerged independently is increasingly questioned by population genomic studies. Here, we document the extent of genetic differentiation within and among two geographic replicates of the coastal and marine ecotypes of the European anchovy (Engraulis encrasicolus) gathered from Atlantic and Mediterranean locations. Using a genome-wide data set of RAD-derived SNPs, we show that habitat type (marine vs. coastal) is the most important component of genetic differentiation among populations of anchovy. By analysing the joint allele frequency spectrum of each coastal-marine ecotype pair, we show that genomic divergence patterns between ecotypes can be explained by a postglacial secondary contact following a long period of allopatric isolation (c. 300 kyrs). We found strong support for a model including heterogeneous migration among loci, suggesting that secondary gene flow has eroded past differentiation at different rates across the genome. Markers experiencing reduced introgression exhibited strongly correlated differentiation levels among Atlantic and Mediterranean regions. These results support that partial reproductive isolation and parallel genetic differentiation among replicate pairs of anchovy ecotypes are largely due to a common divergence history prior to secondary contact. They moreover provide comprehensive insights into the origin of a surprisingly strong fine-scale genetic structuring in a high gene flow marine fish, which should improve stock management and conservation actions.

A genomic perspective on hybridization and speciation

Hybridization among diverging lineages is common in nature. Genomic data provide a special opportunity to characterize the history of hybridization and the genetic basis of speciation. We review existing methods and empirical studies to identify recent advances in the genomics of hybridization, as well as issues that need to be addressed. Notable progress has been made in the development of methods for detecting hybridization and inferring individual ancestries. However, few approaches reconstruct the magnitude and timing of gene flow, estimate the fitness of hybrids or incorporate knowledge of recombination rate. Empirical studies indicate that the genomic consequences of hybridization are complex, including a highly heterogeneous landscape of differentiation. Inferred characteristics of hybridization differ substantially among species groups. Loci showing unusual patterns - which may contribute to reproductive barriers - are usually scattered throughout the genome, with potential enrichment in sex chromosomes and regions of reduced recombination. We caution against the growing trend of interpreting genomic variation in summary statistics across genomes as evidence of differential gene flow. We argue that converting genomic patterns into useful inferences about hybridization will ultimately require models and methods that directly incorporate key ingredients of speciation, including the dynamic nature of gene flow, selection acting in hybrid populations and recombination rate variation.

How did bonobos come to range south of the congo river? Reconsideration of the divergence of Pan paniscus from other Pan populations

While investigating the genetic structure in wild bonobos,(1) we realized that the widely accepted scenario positing that the Pleistocene appearance of the Congo River separated the common ancestor of chimpanzees (Pan troglodytes) and bonobos (P. paniscus) into two species is not supported by recent geographical knowledge about the formation of the Congo River. We explored the origin of bonobos using a broader biogeographical perspective by examining local faunas in the central African region. The submarine Congo River sediments and paleotopography of central Africa show that the Congo River has functioned as a geographical barrier for the last 34 million years. This evidence allows us to hypothesize that when the river was first formed, the ancestor of bonobos did not inhabit the current range of the species on the left bank of the Congo River but that, during rare times when the Congo River discharge decreased during the Pleistocene, one or more founder populations of ancestral Pan paniscus crossed the river to its left bank. The proposed scenario for formation of the Congo River and the corridor hypothesis for an ancestral bonobo population is key to understanding the distribution of great apes and their evolution.

Model-based analysis supports interglacial refugia over long-dispersal events in the diversification of two South American cactus species

Pilosocereus machrisii and P. aurisetus are cactus species within the P. aurisetus complex, a group of eight cacti that are restricted to rocky habitats within the Neotropical savannas of eastern South America. Previous studies have suggested that diversification within this complex was driven by distributional fragmentation, isolation leading to allopatric differentiation, and secondary contact among divergent lineages. These events have been associated with Quaternary climatic cycles, leading to the hypothesis that the xerophytic vegetation patches which presently harbor these populations operate as refugia during the current interglacial. However, owing to limitations of the standard phylogeographic approaches used in these studies, this hypothesis was not explicitly tested. Here we use Approximate Bayesian Computation to refine the previous inferences and test the role of different events in the diversification of two species within P. aurisetus group. We used molecular data from chloroplast DNA and simple sequence repeats loci of P. machrisii and P. aurisetus, the two species with broadest distribution in the complex, in order to test if the diversification in each species was driven mostly by vicariance or by long-dispersal events. We found that both species were affected primarily by vicariance, with a refuge model as the most likely scenario for P. aurisetus and a soft vicariance scenario most probable for P. machrisii. These results emphasize the importance of distributional fragmentation in these species, and add support to the hypothesis of long-term isolation in interglacial refugia previously proposed for the P. aurisetus species complex diversification.

Deep Learning for Population Genetic Inference

Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. Deep learning makes use of multilayer neural networks to learn a feature-based function from the input (e.g., hundreds of correlated summary statistics of data) to the output (e.g., population genetic parameters of interest). We demonstrate that deep learning can be effectively employed for population genetic inference and learning informative features of data. As a concrete application, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history). Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep) or balancing selection. Interestingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme.

Visualizing spatial population structure with estimated effective migration surfaces

Genetic data often exhibit patterns broadly consistent with 'isolation by distance'-a phenomenon where genetic similarity decays with geographic distance. In a heterogeneous habitat, this may occur more quickly in some regions than in others: for example, barriers to gene flow can accelerate differentiation between neighboring groups. We use the concept of 'effective migration' to model the relationship between genetics and geography. In this paradigm, effective migration is low in regions where genetic similarity decays quickly. We present a method to visualize variation in effective migration across a habitat from geographically indexed genetic data. Our approach uses a population genetic model to relate effective migration rates to expected genetic dissimilarities. We illustrate its potential and limitations using simulations and data from elephant, human and Arabidopsis thaliana populations. The resulting visualizations highlight important spatial features of population structure that are difficult to discern using existing methods for summarizing genetic variation.

Estimating time to the most recent common ancestor (TMRCA): comparison and application of eight methods

Investigating how an ancestral population diverges to give rise to distinct subpopulations remains a fundamental pursuit in population genetics. There is broad consensus for the 'Out-of-Africa' hypothesis that states that modern humans arose ∼200 000 years ago in Africa and spread throughout the continent ∼100 000 years ago. This was followed by several waves of major population dispersals across the globe, although the exact nature of the population divergence remains debatable. Existing methods to estimate population divergence time differ in their methodological frameworks and demographic assumptions, and require different types of genetic data as input. These fundamental differences often result in the methods producing inconsistent estimates of the population divergence time, further confounding attempts to robustly uncover the history of human migration, especially when most population genetic studies do not employ multiple methods to estimate the time to the most recent common ancestor (TMRCA). Here, we chose eight popular methods for estimating TMRCA and evaluated their robustness and accuracy in correctly identifying the true TMRCA through a series of simulations that mimicked different evolutionary scenarios. We subsequently applied all eight methods to estimate the population divergence time between Southeast Asian Malays and South Asian Indians using deep whole-genome sequencing data.

Long-Distance Dispersal Shaped Patterns of Human Genetic Diversity in Eurasia

Most previous attempts at reconstructing the past history of human populations did not explicitly take geography into account or considered very simple scenarios of migration and ignored environmental information. However, it is likely that the last glacial maximum (LGM) affected the demography and the range of many species, including our own. Moreover, long-distance dispersal (LDD) may have been an important component of human migrations, allowing fast colonization of new territories and preserving high levels of genetic diversity. Here, we use a high-quality microsatellite data set genotyped in 22 populations to estimate the posterior probabilities of several scenarios for the settlement of the Old World by modern humans. We considered models ranging from a simple spatial expansion to others including LDD and a LGM-induced range contraction, as well as Neolithic demographic expansions. We find that scenarios with LDD are much better supported by data than models without LDD. Nevertheless, we show evidence that LDD events to empty habitats were strongly prevented during the settlement of Eurasia. This unexpected absence of LDD ahead of the colonization wave front could have been caused by an Allee effect, either due to intrinsic causes such as an inbreeding depression built during the expansion or due to extrinsic causes such as direct competition with archaic humans. Overall, our results suggest only a relatively limited effect of the LGM contraction on current patterns of human diversity. This is in clear contrast with the major role of LDD migrations, which have potentially contributed to the intermingled genetic structure of Eurasian populations.

Evolutionary history inferred from the de novo assembly of a nonmodel organism, the blue-eyed black lemur

Lemurs, the living primates most distantly related to humans, demonstrate incredible diversity in behaviour, life history patterns and adaptive traits. Although many lemur species are endangered within their native Madagascar, there is no high-quality genome assembly from this taxon, limiting population and conservation genetic studies. One critically endangered lemur is the blue-eyed black lemur Eulemur flavifrons. This species is fixed for blue irises, a convergent trait that evolved at least four times in primates and was subject to positive selection in humans, where 5′ regulatory variation of OCA2 explains most of the brown/blue eye colour differences. We built a de novo genome assembly for E. flavifrons, providing the most complete lemur genome to date, and a high confidence consensus sequence for close sister species E. macaco, the (brown-eyed) black lemur. From diversity and divergence patterns across the genomes, we estimated a recent split time of the two species (160 Kya) and temporal fluctuations in effective population sizes that accord with known environmental changes. By looking for regions of unusually low diversity, we identified potential signals of directional selection in E. flavifrons at MITF, a melanocyte development gene that regulates OCA2 and has previously been associated with variation in human iris colour, as well as at several other genes involved in melanin biosynthesis in mammals. Our study thus illustrates how whole-genome sequencing of a few individuals can illuminate the demographic and selection history of nonmodel species.

Gene flow between Drosophila yakuba and Drosophila santomea in subunit V of cytochrome c oxidase: A potential case of cytonuclear cointrogression

Introgression is the effective exchange of genetic information between species through natural hybridization. Previous genetic analyses of the Drosophila yakuba—D. santomea hybrid zone showed that the mitochondrial genome of D. yakuba had introgressed into D. santomea and completely replaced its native form. Since mitochondrial proteins work intimately with nuclear‐encoded proteins in the oxidative phosphorylation (OXPHOS) pathway, we hypothesized that some nuclear genes in OXPHOS cointrogressed along with the mitochondrial genome. We analyzed nucleotide variation in the 12 nuclear genes that form cytochrome c oxidase (COX) in 33 Drosophila lines. COX is an OXPHOS enzyme composed of both nuclear‐ and mitochondrial‐encoded proteins and shows evidence of cytonuclear coadaptation in some species. Using maximum‐likelihood methods, we detected significant gene flow from D. yakuba to D. santomea for the entire COX complex. Interestingly, the signal of introgression is concentrated in the three nuclear genes composing subunit V, which shows population migration rates significantly greater than the background level of introgression in these species. The detection of introgression in three proteins that work together, interact directly with the mitochondrial‐encoded core, and are critical for early COX assembly suggests this could be a case of cytonuclear cointrogression.