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

It's about time: divergence, demography, and the evolution of developmental modes in marine invertebrates

Differences in larval developmental mode are predicted to affect ecological and evolutionary processes ranging from gene flow and population bottlenecks to rates of population recovery from anthropogenic disturbance and capacity for local adaptation. The most powerful tests of these predictions use comparisons among species to ask how phylogeographic patterns are correlated with the evolution and loss of prolonged planktonic larval development. An important and largely untested assumption of these studies is that interspecific differences in population genetic structure are mainly caused by differences in dispersal and gene flow (rather than by differences in divergence times among populations or changes in effective population sizes), and that species with similar patterns of spatial genetic variation have similar underlying temporal demographic histories. Teasing apart these temporal and spatial patterns is important for understanding the causes and consequences of evolutionary changes in larval developmental mode. New analytical methods that use the coalescent history of allelic diversity can reveal these temporal patterns, test the strength of traditional population-genetic explanations for variation in spatial structure based on differences in dispersal, and identify strongly supported alternative explanations for spatial structure based on demographic history rather than on gene flow alone. We briefly review some of these recent analytical developments, and show their potential for refining ideas about the correspondence between the evolution of larval developmental mode, population demographic history, and spatial genetic variation.

Speciation genetics: current status and evolving approaches

The view of species as entities subjected to natural selection and amenable to change put forth by Charles Darwin and Alfred Wallace laid the conceptual foundation for understanding speciation. Initially marred by a rudimental understanding of hereditary principles, evolutionists gained appreciation of the mechanistic underpinnings of speciation following the merger of Mendelian genetic principles with Darwinian evolution. Only recently have we entered an era where deciphering the molecular basis of speciation is within reach. Much focus has been devoted to the genetic basis of intrinsic postzygotic isolation in model organisms and several hybrid incompatibility genes have been successfully identified. However, concomitant with the recent technological advancements in genome analysis and a newfound interest in the role of ecology in the differentiation process, speciation genetic research is becoming increasingly open to non-model organisms. This development will expand speciation research beyond the traditional boundaries and unveil the genetic basis of speciation from manifold perspectives and at various stages of the splitting process. This review aims at providing an extensive overview of speciation genetics. Starting from key historical developments and core concepts of speciation genetics, we focus much of our attention on evolving approaches and introduce promising methodological approaches for future research venues.

Approximate Bayesian Computation (ABC) in practice

Understanding the forces that influence natural variation within and among populations has been a major objective of evolutionary biologists for decades. Motivated by the growth in computational power and data complexity, modern approaches to this question make intensive use of simulation methods. Approximate Bayesian Computation (ABC) is one of these methods. Here we review the foundations of ABC, its recent algorithmic developments, and its applications in evolutionary biology and ecology. We argue that the use of ABC should incorporate all aspects of Bayesian data analysis: formulation, fitting, and improvement of a model. ABC can be a powerful tool to make inferences with complex models if these principles are carefully applied.

Likelihood-free inference of population structure and local adaptation in a Bayesian hierarchical model

We address the problem of finding evidence of natural selection from genetic data, accounting for the confounding effects of demographic history. In the absence of natural selection, gene genealogies should all be sampled from the same underlying distribution, often approximated by a coalescent model. Selection at a particular locus will lead to a modified genealogy, and this motivates a number of recent approaches for detecting the effects of natural selection in the genome as "outliers" under some models. The demographic history of a population affects the sampling distribution of genealogies, and therefore the observed genotypes and the classification of outliers. Since we cannot see genealogies directly, we have to infer them from the observed data under some model of mutation and demography. Thus the accuracy of an outlier-based approach depends to a greater or a lesser extent on the uncertainty about the demographic and mutational model. A natural modeling framework for this type of problem is provided by Bayesian hierarchical models, in which parameters, such as mutation rates and selection coefficients, are allowed to vary across loci. It has proved quite difficult computationally to implement fully probabilistic genealogical models with complex demographies, and this has motivated the development of approximations such as approximate Bayesian computation (ABC). In ABC the data are compressed into summary statistics, and computation of the likelihood function is replaced by simulation of data under the model. In a hierarchical setting one may be interested both in hyperparameters and parameters, and there may be very many of the latter--for example, in a genetic model, these may be parameters describing each of many loci or populations. This poses a problem for ABC in that one then requires summary statistics for each locus, which, if used naively, leads to a consequent difficulty in conditional density estimation. We develop a general method for applying ABC to Bayesian hierarchical models, and we apply it to detect microsatellite loci influenced by local selection. We demonstrate using receiver operating characteristic (ROC) analysis that this approach has comparable performance to a full-likelihood method and outperforms it when mutation rates are variable across loci.

New insights on the speciation history and nucleotide diversity of three boreal spruce species and a Tertiary relict

In all, 10 nuclear loci were re-sequenced in four spruce species. Three of the species are boreal species with very large natural ranges: Picea mariana and P. glauca are North American, and P. abies, is Eurasian. The fourth species, P. breweriana, is a Tertiary relict from Northern California, with a very small natural range. Although the boreal species population sizes have fluctuated through the Ice Ages, P. breweriana is believed to have had a rather stable population size through the Quaternary. Indeed, the average Tajima's D was close to zero in this species and negative in the three boreal ones. Reflecting differences in current population sizes, nucleotide diversity was an order of magnitude lower in P. breweriana than in the boreal species. This is in contrast to the similar and high levels of heterozygosity observed in previous studies at allozyme loci across species. As the species have very different histories and effective population sizes, selection at allozyme loci rather than demography appears to be a better explanation for this discrepancy. Parameters of Isolation-with-Migration (IM) models were also estimated for pairs of species. Shared polymorphisms were extensive and fixed polymorphisms few. Divergence times were much shorter than those previously reported. There was also evidence of historical gene flow between P. abies and P. glauca. The latter was more closely related to P. abies than to its sympatric relative P. mariana. This last result suggests that North American and Eurasian species might have been geographically much closer in the recent past than they are today.

Islands of speciation or mirages in the desert? Examining the role of restricted recombination in maintaining species

Over the past decade, many studies documented high genetic divergence between closely related species in genomic regions experiencing restricted recombination in hybrids, such as within chromosomal rearrangements or areas adjacent to centromeres. Such regions have been called 'islands of speciation' because of their presumed role in maintaining the integrity of species despite gene flow elsewhere in the genome. Here, we review alternative explanations for such patterns. Segregation of ancestral variation or artifacts of nucleotide diversity within species can readily lead to higher F(ST) in regions of restricted recombination than other parts of the genome, even in the complete absence of interspecies gene flow, and thereby cause investigators to erroneously conclude that islands of speciation exist. We conclude by discussing strengths and weaknesses of various means for testing the role of restricted recombination in maintaining species.

Genetic variation at nuclear loci fails to distinguish two morphologically distinct species of Aquilegia

Aquilegia formosa and pubescens are two closely related species belonging to the columbine genus. Despite their morphological and ecological differences, previous studies have revealed a large degree of intercompatibility, as well as little sequence divergence between these two taxa. We compared the inter- and intraspecific patterns of variation for 9 nuclear loci, and found that the two species were practically indistinguishable at the level of DNA sequence polymorphism, indicating either very recent speciation or continued gene flow. As a comparison, we also analyzed variation at two loci across 30 other Aquilegia taxa; this revealed slightly more differentiation among taxa, which seemed best explained by geographic distance. By contrast, we found no evidence for isolation by distance on a more local geographic scale. We conclude that the extremely low levels of genetic differentiation between A. formosa and A. pubescens at neutral loci will facilitate future genome-wide scans for speciation genes.

Population genetic inference from genomic sequence variation

Population genetics has evolved from a theory-driven field with little empirical data into a data-driven discipline in which genome-scale data sets test the limits of available models and computational analysis methods. In humans and a few model organisms, analyses of whole-genome sequence polymorphism data are currently under way. And in light of the falling costs of next-generation sequencing technologies, such studies will soon become common in many other organisms as well. Here, we assess the challenges to analyzing whole-genome sequence polymorphism data, and we discuss the potential of these data to yield new insights concerning population history and the genomic prevalence of natural selection.

Rejecting strictly allopatric speciation on a continental island: prolonged postdivergence gene flow between Taiwan (Leucodioptron taewanus, Passeriformes Timaliidae) and Chinese (L. canorum canorum) hwameis

Allopatry is conventionally considered the geographical mode of speciation for continental island organisms. However, strictly allopatric speciation models that assume the lack of postdivergence gene flow seem oversimplified given the recurrence of land bridges during glacial periods since the late Pliocene. Here, to evaluate whether a continental island endemic, the Taiwan hwamei (Leucodioptron taewanus, Passeriformes Timaliidae) speciated in strict allopatry, we used weighted-regression-based approximate Bayesian computation (ABC) to analyse the genetic polymorphism of 18 neutral nuclear loci (total length: 8500 bp) in Taiwan hwamei and its continental sister species, the Chinese hwamei (L. canorum canorum). The nonallopatry model was found to fit better with observed genetic polymorphism of the two hwamei species (posterior possibility = 0.82). We also recovered unambiguous signals of nontrivial bidirectional postdivergence gene flow (N(e)m >> 1) between Chinese hwamei and Taiwan hwamei until 0.5 Ma. Divergence time was estimated to be 3.5 to 2 million years earlier than that estimated from mitochondrial cytochrome b sequences. Finally, using the inferred nonallopatry model to simulate genetic variation at 24 nuclear genes examined showed that the adiponectin receptor 1 gene may be under divergent adaptation. Our findings imply that the role of geographical barrier may be less prominent for the speciation of continental island endemics, and suggest a shift in speciation studies from simply correlating geographical barrier and genetic divergence to examining factors that facilitate and maintain divergence, e.g. differential selection and sexual selection, especially in the face of interpopulation gene flow.

Host-specific differentiation among populations of Venturia inaequalis causing scab on apple, pyracantha and loquat

Patterns of multilocus DNA sequence variation within and between closely related taxa can provide insights into the history of divergence. Here, we report on DNA polymorphism and divergence at six nuclear loci in globally distributed samples of the ascomycete Venturia inaequalis, responsible for scab on apple, loquat, and pyracantha. Isolates from different hosts were differentiated but did not form diagnosable distinct phylogenetic species. Parameters of an Isolation-with-Migration model estimated from the data suggested that the large amount of variation shared among groups more likely resulted from recent splitting than from extensive genetic exchanges. Inferred levels of gene flow among groups were low and more concentrated toward recent times, and we identified two potentially recent one-off shifters from apple and pyracantha to loquat. These findings support a scenario of recent divergence in allopatry followed by introgression through secondary contact, with groups from loquat and pyracantha being the most recently differentiated.

Bayesian computation and model selection without likelihoods

Until recently, the use of Bayesian inference was limited to a few cases because for many realistic probability models the likelihood function cannot be calculated analytically. The situation changed with the advent of likelihood-free inference algorithms, often subsumed under the term approximate Bayesian computation (ABC). A key innovation was the use of a postsampling regression adjustment, allowing larger tolerance values and as such shifting computation time to realistic orders of magnitude. Here we propose a reformulation of the regression adjustment in terms of a general linear model (GLM). This allows the integration into the sound theoretical framework of Bayesian statistics and the use of its methods, including model selection via Bayes factors. We then apply the proposed methodology to the question of population subdivision among western chimpanzees, Pan troglodytes verus.

Demographic histories of four spruce (Picea) species of the Qinghai-Tibetan Plateau and neighboring areas inferred from multiple nuclear loci

Nucleotide variation at 12-16 nuclear loci was studied in three spruce species from the Qinghai-Tibetan Plateau (QTP), Picea likiangensis, P. wilsonii, and P. purpurea, and one species from the Tian Shan mountain range, P. schrenkiana. Silent nucleotide diversity was limited in P. schrenkiana and high in the three species from the QTP, with values higher than in boreal spruce species, despite their much more restricted distributions compared with that of the boreal species. In contrast to European boreal species that have experienced severe bottlenecks in the past, coalescent-based analysis suggests that DNA polymorphism in the species from the QTP and adjacent areas is compatible with the standard neutral model (P. likiangensis, P. wilsonii, and P. schrenkiana) or with population growth (P. purpurea). In order to test if P. purpurea is a diploid hybrid of P. likiangensis and P. wilsonii, we used a combination of approaches, including model-based inference of population structure, isolation-with-migration models, and recent theoretical results on the effect of introgression on the geographic distribution of diversity. In contrast to the three other species, each of which was predominantly assigned to a single cluster in the Structure analysis, P. purpurea individuals were scattered over the three main clusters and not, as we had expected, confined to the P. likiangensis and P. wilsonii clusters. Furthermore, the contribution of P. schrenkiana was by far the largest one. In agreement with this, the divergence between P. purpurea and P. schrenkiana was lower than the divergence of either P. likiangensis or P. wilsonii from P. schrenkiana. These results, together with previous ones showing that P. purpurea and P. wilsonii share the same haplotypes at both chloroplast and mitochondrial markers, suggest that P. purpurea has a complex origin, possibly involving additional species.

Elucidating population histories using genomic DNA sequences

In 1993, Cliff Jolly suggested that rather than debating species definitions and classifications, energy would be better spent investigating multidimensional patterns of variation and gene flow among populations. Until now, however, genetic studies of wild primate populations have been limited to very small portions of the genome. Access to complete genome sequences of humans, chimpanzees, macaques, and other primates makes it possible to design studies surveying substantial amounts of DNA sequence variation at multiple genetic loci in representatives of closely related but distinct wild primate populations. Such data can be analyzed with new approaches that estimate not only when populations diverged but also the relative amounts and directions of subsequent gene flow. These analyses will reemphasize the difficulty of achieving consistent species and subspecies definitions by revealing the extent of variation in the amount and duration of gene flow accompanying population divergences.

The divergence of chimpanzee species and subspecies as revealed in multipopulation isolation-with-migration analyses

The divergence of bonobos and three subspecies of the common chimpanzee was examined under a multipopulation isolation-with-migration (IM) model with data from 73 loci drawn from the literature. A benefit of having a full multipopulation model, relative to conducting multiple pairwise analyses between sampled populations, is that a full model can reveal historical gene flow involving ancestral populations. An example of this was found in which gene flow is indicated between the western common chimpanzee subspecies and the ancestor of the central and the eastern common chimpanzee subspecies. The results of a full analysis on all four populations are strongly consistent with analyses on pairs of populations and generally similar to results from previous studies. The basal split between bonobos and common chimpanzees was estimated at 0.93 Ma (0.68-1.54 Ma, 95% highest posterior density interval), with the split among the ancestor of three common chimpanzee populations at 0.46 Ma (0.35-0.65), and the most recent split between central and eastern common chimpanzee populations at 0.093 Ma (0.041-0.157). Population size estimates mostly fell in the range from 5,000 to 10,000 individuals. The exceptions are the size of the ancestor of the common chimpanzee and the bonobo, at 17,000 (8,000-28,000) individuals, and the central common chimpanzee and its immediate ancestor with the eastern common chimpanzee, which have effective size estimates at 27,000 (16,000-44,000) and 32,000 (19,000-54,000) individuals, respectively.

Isolation with migration models for more than two populations

A method for studying the divergence of multiple closely related populations is described and assessed. The approach of Hey and Nielsen (2007, Integration within the Felsenstein equation for improved Markov chain Monte Carlo methods in population genetics. Proc Natl Acad Sci USA. 104:2785-2790) for fitting an isolation-with-migration model was extended to the case of multiple populations with a known phylogeny. Analysis of simulated data sets reveals the kinds of history that are accessible with a multipopulation analysis. Necessarily, processes associated with older time periods in a phylogeny are more difficult to estimate; and histories with high levels of gene flow are particularly difficult with more than two populations. However, for histories with modest levels of gene flow, or for very large data sets, it is possible to study large complex divergence problems that involve multiple closely related populations or species.

Estimating divergence parameters with small samples from a large number of loci

Most methods for studying divergence with gene flow rely upon data from many individuals at few loci. Such data can be useful for inferring recent population history but they are unlikely to contain sufficient information about older events. However, the growing availability of genome sequences suggests a different kind of sampling scheme, one that may be more suited to studying relatively ancient divergence. Data sets extracted from whole-genome alignments may represent very few individuals but contain a very large number of loci. To take advantage of such data we developed a new maximum-likelihood method for genomic data under the isolation-with-migration model. Unlike many coalescent-based likelihood methods, our method does not rely on Monte Carlo sampling of genealogies, but rather provides a precise calculation of the likelihood by numerical integration over all genealogies. We demonstrate that the method works well on simulated data sets. We also consider two models for accommodating mutation rate variation among loci and find that the model that treats mutation rates as random variables leads to better estimates. We applied the method to the divergence of Drosophila melanogaster and D. simulans and detected a low, but statistically significant, signal of gene flow from D. simulans to D. melanogaster.

Mating-system variation, demographic history and patterns of nucleotide diversity in the Tristylous plant Eichhornia paniculata

Inbreeding in highly selfing populations reduces effective size and, combined with demographic conditions associated with selfing, this can erode genetic diversity and increase population differentiation. Here we investigate the role that variation in mating patterns and demographic history play in shaping the distribution of nucleotide variation within and among populations of the annual neotropical colonizing plant Eichhornia paniculata, a species with wide variation in selfing rates. We sequenced 10 EST-derived nuclear loci in 225 individuals from 25 populations sampled from much of the geographic range and used coalescent simulations to investigate demographic history. Highly selfing populations exhibited moderate reductions in diversity but there was no significant difference in variation between outcrossing and mixed mating populations. Population size interacted strongly with mating system and explained more of the variation in diversity within populations. Bayesian structure analysis revealed strong regional clustering and selfing populations were highly differentiated on the basis of an analysis of F(st). There was no evidence for a significant loss of within-locus linkage disequilibrium within populations, but regional samples revealed greater breakdown in Brazil than in selfing populations from the Caribbean. Coalescent simulations indicate a moderate bottleneck associated with colonization of the Caribbean from Brazil approximately 125,000 years before the present. Our results suggest that the recent multiple origins of selfing in E. paniculata from diverse outcrossing populations result in higher diversity than expected under long-term equilibrium.

Inferring the joint demographic history of multiple populations from multidimensional SNP frequency data

Demographic models built from genetic data play important roles in illuminating prehistorical events and serving as null models in genome scans for selection. We introduce an inference method based on the joint frequency spectrum of genetic variants within and between populations. For candidate models we numerically compute the expected spectrum using a diffusion approximation to the one-locus, two-allele Wright-Fisher process, involving up to three simultaneous populations. Our approach is a composite likelihood scheme, since linkage between neutral loci alters the variance but not the expectation of the frequency spectrum. We thus use bootstraps incorporating linkage to estimate uncertainties for parameters and significance values for hypothesis tests. Our method can also incorporate selection on single sites, predicting the joint distribution of selected alleles among populations experiencing a bevy of evolutionary forces, including expansions, contractions, migrations, and admixture. We model human expansion out of Africa and the settlement of the New World, using 5 Mb of noncoding DNA resequenced in 68 individuals from 4 populations (YRI, CHB, CEU, and MXL) by the Environmental Genome Project. We infer divergence between West African and Eurasian populations 140 thousand years ago (95% confidence interval: 40–270 kya). This is earlier than other genetic studies, in part because we incorporate migration. We estimate the European (CEU) and East Asian (CHB) divergence time to be 23 kya (95% c.i.: 17–43 kya), long after archeological evidence places modern humans in Europe. Finally, we estimate divergence between East Asians (CHB) and Mexican-Americans (MXL) of 22 kya (95% c.i.: 16.3–26.9 kya), and our analysis yields no evidence for subsequent migration. Furthermore, combining our demographic model with a previously estimated distribution of selective effects among newly arising amino acid mutations accurately predicts the frequency spectrum of nonsynonymous variants across three continental populations (YRI, CHB, CEU).

The demographic history of our species is reflected in patterns of genetic variation within and among populations. We developed an efficient method for calculating the expected distribution of genetic variation, given a demographic model including such events as population size changes, population splits and joins, and migration. We applied our approach to publicly available human sequencing data, searching for models that best reproduce the observed patterns. Our joint analysis of data from African, European, and Asian populations yielded new dates for when these populations diverged. In particular, we found that African and Eurasian populations diverged around 100,000 years ago. This is earlier than other genetic studies suggest, because our model includes the effects of migration, which we found to be important for reproducing observed patterns of variation in the data. We also analyzed data from European, Asian, and Mexican populations to model the peopling of the Americas. Here, we find no evidence for recurrent migration after East Asian and Native American populations diverged. Our methods are not limited to studying humans, and we hope that future sequencing projects will offer more insights into the history of both our own species and others.

Sequencing primate genomes: what have we learned?

We summarize the progress in whole-genome sequencing and analyses of primate genomes. These emerging genome datasets have broadened our understanding of primate genome evolution revealing unexpected and complex patterns of evolutionary change. This includes the characterization of genome structural variation, episodic changes in the repeat landscape, differences in gene expression, new models regarding speciation, and the ephemeral nature of the recombination landscape. The functional characterization of genomic differences important in primate speciation and adaptation remains a significant challenge. Limited access to biological materials, the lack of detailed phenotypic data and the endangered status of many critical primate species have significantly attenuated research into the genetic basis of primate evolution. Next-generation sequencing technologies promise to greatly expand the number of available primate genome sequences; however, such draft genome sequences will likely miss critical genetic differences within complex genomic regions unless dedicated efforts are put forward to understand the full spectrum of genetic variation.

How robust are "isolation with migration" analyses to violations of the im model? A simulation study

Methods developed over the past decade have made it possible to estimate molecular demographic parameters such as effective population size, divergence time, and gene flow with unprecedented accuracy and precision. However, they make simplifying assumptions about certain aspects of the species' histories and the nature of the genetic data, and it is not clear how robust they are to violations of these assumptions. Here, we use simulated data sets to examine the effects of a number of violations of the "Isolation with Migration" (IM) model, including intralocus recombination, population structure, gene flow from an unsampled species, linkage among loci, and divergent selection, on demographic parameter estimates made using the program IMA. We also examine the effect of having data that fit a nucleotide substitution model other than the two relatively simple models available in IMA. We find that IMA estimates are generally quite robust to small to moderate violations of the IM model assumptions, comparable with what is often encountered in real-world scenarios. In particular, population structure within species, a condition encountered to some degree in virtually all species, has little effect on parameter estimates even for fairly high levels of structure. Likewise, most parameter estimates are robust to significant levels of recombination when data sets are pared down to apparently nonrecombining blocks, although substantial bias is introduced to several estimates when the entire data set with recombination is included. In contrast, a poor fit to the nucleotide substitution model can result in an increased error rate, in some cases due to a predictable bias and in other cases due to an increase in variance in parameter estimates among data sets simulated under the same conditions.

Model criticism based on likelihood-free inference, with an application to protein network evolution

Mathematical models are an important tool to explain and comprehend complex phenomena, and unparalleled computational advances enable us to easily explore them without any or little understanding of their global properties. In fact, the likelihood of the data under complex stochastic models is often analytically or numerically intractable in many areas of sciences. This makes it even more important to simultaneously investigate the adequacy of these models-in absolute terms, against the data, rather than relative to the performance of other models-but no such procedure has been formally discussed when the likelihood is intractable. We provide a statistical interpretation to current developments in likelihood-free Bayesian inference that explicitly accounts for discrepancies between the model and the data, termed Approximate Bayesian Computation under model uncertainty (ABCmicro). We augment the likelihood of the data with unknown error terms that correspond to freely chosen checking functions, and provide Monte Carlo strategies for sampling from the associated joint posterior distribution without the need of evaluating the likelihood. We discuss the benefit of incorporating model diagnostics within an ABC framework, and demonstrate how this method diagnoses model mismatch and guides model refinement by contrasting three qualitative models of protein network evolution to the protein interaction datasets of Helicobacter pylori and Treponema pallidum. Our results make a number of model deficiencies explicit, and suggest that the T. pallidum network topology is inconsistent with evolution dominated by link turnover or lateral gene transfer alone.

Efficient approximate Bayesian computation coupled with Markov chain Monte Carlo without likelihood

Approximate Bayesian computation (ABC) techniques permit inferences in complex demographic models, but are computationally inefficient. A Markov chain Monte Carlo (MCMC) approach has been proposed (Marjoram et al. 2003), but it suffers from computational problems and poor mixing. We propose several methodological developments to overcome the shortcomings of this MCMC approach and hence realize substantial computational advances over standard ABC. The principal idea is to relax the tolerance within MCMC to permit good mixing, but retain a good approximation to the posterior by a combination of subsampling the output and regression adjustment. We also propose to use a partial least-squares (PLS) transformation to choose informative statistics. The accuracy of our approach is examined in the case of the divergence of two populations with and without migration. In that case, our ABC-MCMC approach needs considerably lower computation time to reach the same accuracy than conventional ABC. We then apply our method to a more complex case with the estimation of divergence times and migration rates between three African populations.

Inferring the demographic history of African farmers and pygmy hunter-gatherers using a multilocus resequencing data set

The transition from hunting and gathering to farming involved a major cultural innovation that has spread rapidly over most of the globe in the last ten millennia. In sub-Saharan Africa, hunter–gatherers have begun to shift toward an agriculture-based lifestyle over the last 5,000 years. Only a few populations still base their mode of subsistence on hunting and gathering. The Pygmies are considered to be the largest group of mobile hunter–gatherers of Africa. They dwell in equatorial rainforests and are characterized by their short mean stature. However, little is known about the chronology of the demographic events—size changes, population splits, and gene flow—ultimately giving rise to contemporary Pygmy (Western and Eastern) groups and neighboring agricultural populations. We studied the branching history of Pygmy hunter–gatherers and agricultural populations from Africa and estimated separation times and gene flow between these populations. We resequenced 24 independent noncoding regions across the genome, corresponding to a total of ∼33 kb per individual, in 236 samples from seven Pygmy and five agricultural populations dispersed over the African continent. We used simulation-based inference to identify the historical model best fitting our data. The model identified included the early divergence of the ancestors of Pygmy hunter–gatherers and farming populations ∼60,000 years ago, followed by a split of the Pygmies' ancestors into the Western and Eastern Pygmy groups ∼20,000 years ago. Our findings increase knowledge of the history of the peopling of the African continent in a region lacking archaeological data. An appreciation of the demographic and adaptive history of African populations with different modes of subsistence should improve our understanding of the influence of human lifestyles on genome diversity.

The central African belt represents a key region for understanding recent changes in human history and modes of subsistence because the largest group of hunter–gatherers of Africa, the Pygmies, still inhabits this region and coexists with neighboring agricultural populations. However, the understanding of the peopling history of equatorial Africa is hampered by the rapid disintegration of fossil remains in the rainforest's acidic soils. When archaeology fails, population genetics can reconstruct the history of populations from their present-day genetic variation. We generated a large resequencing dataset in different farming, Western Pygmy, and Eastern Pygmy populations dispersed over the African continent. By means of simulation-based inferences, we show that the ancestors of Pygmy hunter–gatherers and farming populations started to diverge ∼60,000 years ago. This indicates that the transition to agriculture—occurring in Africa ∼5,000 years ago—was not responsible for the separation of the ancestors of modern-day Pygmies and farmers. We also show that Western and Eastern Pygmy groups separated roughly 20,000 years ago from a common ancestral population. This finding suggests that the shared physical and cultural features of Pygmies were inherited from a common ancestor, rather than reflecting convergent adaptation to the rainforest.

An approximate likelihood for genetic data under a model with recombination and population splitting

We describe a new approximate likelihood for population genetic data under a model in which a single ancestral population has split into two daughter populations. The approximate likelihood is based on the 'Product of Approximate Conditionals' likelihood and 'copying model' of Li and Stephens [Li, N., Stephens, M., 2003. Modeling linkage disequilibrium and identifying recombination hotspots using single-nucleotide polymorphism data. Genetics 165 (4), 2213-2233]. The approach developed here may be used for efficient approximate likelihood-based analyses of unlinked data. However our copying model also considers the effects of recombination. Hence, a more important application is to loosely-linked haplotype data, for which efficient statistical models explicitly featuring non-equilibrium population structure have so far been unavailable. Thus, in addition to the information in allele frequency differences about the timing of the population split, the method can also extract information from the lengths of haplotypes shared between the populations. There are a number of challenges posed by extracting such information, which makes parameter estimation difficult. We discuss how the approach could be extended to identify haplotypes introduced by migrants.

Using genetics to understand the dynamics of wild primate populations

While much can be learned about primates by means of observation, the slow life history of many primates means that even decades of dedicated effort cannot illuminate long-term evolutionary processes. For example, while the size of a contemporary population can be estimated from field censuses, it is often desirable to know whether a population has been constant or changing in size over a time frame of hundreds or thousands of years. Even the nature of "a population" is open to question, and the extent to which individuals successfully disperse among defined populations is also difficult to estimate by using observational methods alone. Researchers have thus turned to genetic methods to examine the size, structure, and evolutionary histories of primate populations. Many results have been gained by study of sequence variation of maternally inherited mitochondrial DNA, but in recent years researchers have been increasingly focusing on analysis of short, highly variable microsatellite segments in the autosomal genome for a high-resolution view of evolutionary processes involving both sexes. In this review we describe some of the insights thus gained, and discuss the likely impact on this field of new technologies such as high-throughput DNA sequencing.

Recent speciation associated with the evolution of selfing in Capsella

The evolution from outcrossing to predominant self-fertilization represents one of the most common transitions in flowering plant evolution. This shift in mating system is almost universally associated with the "selfing syndrome," characterized by marked reduction in flower size and a breakdown of the morphological and genetic mechanisms that prevent self-fertilization. In general, the timescale in which these transitions occur, and the evolutionary dynamics associated with the evolution of the selfing syndrome are poorly known. We investigated the origin and evolution of selfing in the annual plant Capsella rubella from its self-incompatible, outcrossing progenitor Capsella grandiflora by characterizing multilocus patterns of DNA sequence variation at nuclear genes. We estimate that the transition to selfing and subsequent geographic expansion have taken place during the past 20,000 years. This transition was probably associated with a shift from stable equilibrium toward a near-complete population bottleneck causing a major reduction in effective population size. The timing and severe founder event support the hypothesis that selfing was favored during colonization as new habitats emerged after the last glaciation and the expansion of agriculture. These results suggest that natural selection for reproductive assurance can lead to major morphological evolution and speciation on relatively short evolutionary timescales.

Learning about modes of speciation by computational approaches

How often do the early stages of speciation occur in the presence of gene flow? To address this enduring question, a number of recent papers have used computational approaches, estimating parameters of simple divergence models from multilocus polymorphism data collected in closely related species. Applications to a variety of species have yielded extensive evidence for migration, with the results interpreted as supporting the widespread occurrence of parapatric speciation. Here, we conduct a simulation study to assess the reliability of such inferences, using a program that we recently developed MCMC estimation of the isolation-migration model allowing for recombination (MIMAR) as well as the program isolation-migration (IM) of Hey and Nielsen (2004). We find that when one of many assumptions of the isolation-migration model is violated, the methods tend to yield biased estimates of the parameters, potentially lending spurious support for allopatric or parapatric divergence. More generally, our results highlight the difficulty in drawing inferences about modes of speciation from the existing computational approaches alone.

Approximate bayesian computation without summary statistics: the case of admixture

In recent years approximate Bayesian computation (ABC) methods have become popular in population genetics as an alternative to full-likelihood methods to make inferences under complex demographic models. Most ABC methods rely on the choice of a set of summary statistics to extract information from the data. In this article we tested the use of the full allelic distribution directly in an ABC framework. Although the ABC techniques are becoming more widely used, there is still uncertainty over how they perform in comparison with full-likelihood methods. We thus conducted a simulation study and provide a detailed examination of ABC in comparison with full likelihood in the case of a model of admixture. This model assumes that two parental populations mixed at a certain time in the past, creating a hybrid population, and that the three populations then evolve under pure drift. Several aspects of ABC methodology were investigated, such as the effect of the distance metric chosen to measure the similarity between simulated and observed data sets. Results show that in general ABC provides good approximations to the posterior distributions obtained with the full-likelihood method. This suggests that it is possible to apply ABC using allele frequencies to make inferences in cases where it is difficult to select a set of suitable summary statistics and when the complexity of the model or the size of the data set makes it computationally prohibitive to use full-likelihood methods.

Historical divergence and gene flow in the genus Zea

Gene flow plays a fundamental role in plant evolutionary history, yet its role in population divergence--and ultimately speciation--remains poorly understood. We investigated gene flow and the modalities of divergence in the domesticated Zea mays ssp. mays and three wild Zea taxa using sequence polymorphism data from 26 nuclear loci. We described diversity across loci and assessed evidence for adaptive and purifying selection at nonsynonymous sites. For each of three divergence events in the history of these taxa, we used approximate Bayesian simulation to estimate population sizes and divergence times and explicitly compare among alternative models of divergence. Our estimates of divergence times are surprisingly consistent with previous data from other markers and suggest rapid diversification of lineages within Zea in the last approximately 150,000 years. We found widespread evidence of historical gene flow, including evidence for divergence in the face of gene flow. We speculate that cultivated maize may serve as a bridge for gene flow among otherwise allopatric wild taxa.

Divergence in the face of gene flow: the case of two newts (amphibia: salamandridae)

Understanding the process of divergence requires the quantitative characterization of patterns of gene flow between diverging taxa. New and powerful coalescent-based methods give insight into these processes in unprecedented details by enabling the reconstruction of the temporal distribution of past gene flow. Here, we use sequence variation at eight nuclear markers and mitochondrial DNA (mtDNA) in multiple populations to study diversity, divergence, and gene flow between two subspecies of a salamander, the smooth newt (Lissotriton vulgaris kosswigi and Lissotriton vulgaris vulgaris) in Turkey. The ranges of both subspecies encompass mainly the areas of this important glacial refugial area. Populations in refugia where species have been present for a long time and differentiated in situ should better preserve the record of past gene flow than young populations in postglacial expansion areas. Sequence diversity in both subspecies was substantial (nuclear pi(sil) = 0.69% and 1.31%). We detected long-term demographic stability in these refugial populations with large effective population sizes (N(e)) of the order of 1.5-3 x 10(5) individuals. Gene trees and the isolation with migration (IM) analysis complemented by tests of nested IM models showed that despite deep, pre-Pleistocene divergence of the studied newts, asymmetric introgression from vulgaris to kosswigi has occurred, with signatures of recent gene flow in mtDNA and an anonymous nuclear marker, and evidence for more ancient introgression in nuclear introns. The distribution of migration times raises the intriguing possibility that even the initial divergence may have occurred in the face of gene flow.

Inference of historical changes in migration rate from the lengths of migrant tracts

After migrant chromosomes enter a population, they are progressively sliced into smaller pieces by recombination. Therefore, the length distribution of "migrant tracts" (chromosome segments with recent migrant ancestry) contains information about historical patterns of migration. Here we introduce a theoretical framework describing the migrant tract length distribution and propose a likelihood inference method to test demographic hypotheses and estimate parameters related to a historical change in migration rate. Applying this method to data from the hybridizing subspecies Mus musculus domesticus and M. m. musculus, we find evidence for an increase in the rate of hybridization. Our findings could indicate an evolutionary trajectory toward fusion rather than speciation in these taxa.

Divergence between human populations estimated from linkage disequilibrium

Observed linkage disequilibrium (LD) between genetic markers in different populations descended independently from a common ancestral population can be used to estimate their absolute time of divergence, because the correlation of LD between populations will be reduced each generation by an amount that, approximately, depends only on the recombination rate between markers. Although drift leads to divergence in allele frequencies, it has less effect on divergence in LD values. We derived the relationship between LD and time of divergence and verified it with coalescent simulations. We then used HapMap Phase II data to estimate time of divergence between human populations. Summed over large numbers of pairs of loci, we find a positive correlation of LD between African and non-African populations at levels of up to approximately 0.3 cM. We estimate that the observed correlation of LD is consistent with an effective separation time of approximately 1,000 generations or approximately 25,000 years before present. The most likely explanation for such relatively low separation times is the existence of substantial levels of migration between populations after the initial separation. Theory and results from coalescent simulations confirm that low levels of migration can lead to a downward bias in the estimate of separation time.

Nucleotide variation, linkage disequilibrium and founder-facilitated speciation in wild populations of the zebra finch (Taeniopygia guttata)

The zebra finch has long been an important model system for the study of vocal learning, vocal production, and behavior. With the imminent sequencing of its genome, the zebra finch is now poised to become a model system for population genetics. Using a panel of 30 noncoding loci, we characterized patterns of polymorphism and divergence among wild zebra finch populations. Continental Australian populations displayed little population structure, exceptionally high levels of nucleotide diversity (pi = 0.010), a rapid decay of linkage disequilibrium (LD), and a high population recombination rate (rho approximately 0.05), all of which suggest an open and fluid genomic background that could facilitate adaptive variation. By contrast, substantial divergence between the Australian and Lesser Sunda Island populations (K(ST) = 0.193), reduced genetic diversity (pi = 0.002), and higher levels of LD in the island population suggest a strong but relatively recent founder event, which may have contributed to speciation between these populations as envisioned under founder-effect speciation models. Consistent with this hypothesis, we find that under a simple quantitative genetic model both drift and selection could have contributed to the observed divergence in six quantitative traits. In both Australian and Lesser Sundas populations, diversity in Z-linked loci was significantly lower than in autosomal loci. Our analysis provides a quantitative framework for studying the role of selection and drift in shaping patterns of molecular evolution in the zebra finch genome.

Assessing natural introgression in 2 biomedical model species, the rhesus macaque (Macaca mulatta) and the long-tailed macaque (Macaca fascicularis)

Rhesus macaque (Macaca mulatta) and long-tailed macaque (Macaca fascicularis) are the 2 most commonly used primate model species in biomedical sciences. Although morphological studies have revealed a weak hybridization at the interspecific contact zone, in the north of Indochina, a molecular study has suggested an ancient introgression from rhesus to long-tailed macaque into the Indo-Chinese peninsula. However, the gene flow between these 2 taxa has never been quantified using genetic data and theoretical models. In this study, we have examined genetic variation within and between the parapatric Chinese rhesus macaque and Indo-Chinese long-tailed macaque populations, using 13 autosomal, 5 sex-linked microsatellite loci and mitochondrial DNA sequence data. From these data, we assessed genetic structure and estimated gene flow using a Bayesian clustering approach and the "Isolation with Migration" model. Our results reveal a weak interspecific genetic differentiation at both autosomal and sex-linked loci, suggesting large population sizes and/or gene flow between populations. According to the Bayesian clustering, Chinese rhesus macaque is a highly homogeneous gene pool that contributes strongly to the current Indo-Chinese long-tailed macaque genetic makeup, whether or not current admixture is assumed. Coalescent simulations, which integrated the characteristics of the loci, pointed out 1) a higher effective population size in rhesus macaque, 2) no mitochondrial gene flow, and 3) unilateral and male-mediated nuclear gene flow of approximately 10 migrants per generation from rhesus to long-tailed macaque. These patterns of genetic structure and gene flow suggest extensive ancient introgression from Chinese rhesus macaque into the Indo-Chinese long-tailed macaque population.

Patterns of polymorphism and demographic history in natural populations of Arabidopsis lyrata

BACKGROUND

Many of the processes affecting genetic diversity act on local populations. However, studies of plant nucleotide diversity have largely ignored local sampling, making it difficult to infer the demographic history of populations and to assess the importance of local adaptation. Arabidopsis lyrata, a self-incompatible, perennial species with a circumpolar distribution, is an excellent model system in which to study the roles of demographic history and local adaptation in patterning genetic variation.

PRINCIPAL FINDINGS

We studied nucleotide diversity in six natural populations of Arabidopsis lyrata, using 77 loci sampled from 140 chromosomes. The six populations were highly differentiated, with a median FST of 0.52, and structure analysis revealed no evidence of admixed individuals. Average within-population diversity varied among populations, with the highest diversity found in a German population; this population harbors 3-fold higher levels of silent diversity than worldwide samples of A. thaliana. All A. lyrata populations also yielded positive values of Tajima's D. We estimated a demographic model for these populations, finding evidence of population divergence over the past 19,000 to 47,000 years involving non-equilibrium demographic events that reduced the effective size of most populations. Finally, we used the inferred demographic model to perform an initial test for local adaptation and identified several genes, including the flowering time gene FCA and a disease resistance locus, as candidates for local adaptation events.

CONCLUSIONS

Our results underscore the importance of population-specific, non-equilibrium demographic processes in patterning diversity within A. lyrata. Moreover, our extensive dataset provides an important resource for future molecular population genetic studies of local adaptation in A. lyrata.

Molecular demographic history of the annual sunflowers Helianthus annuus and H. petiolaris--large effective population sizes and rates of long-term gene flow

Hybridization between distinct species may lead to introgression of genes across species boundaries, and this pattern can potentially persist for extended periods as long as selection at some loci or genomic regions prevents thorough mixing of gene pools. However, very few reliable estimates of long-term levels of effective migration are available between hybridizing species throughout their history. Accurate estimates of divergence dates and levels of gene flow require data from multiple unlinked loci as well as an analytical framework that can distinguish between lineage sorting and gene flow and incorporate the effects of demographic changes within each species. Here we use sequence data from 18 anonymous nuclear loci in two broadly sympatric sunflower species, Helianthus annuus and H. petiolaris, analyzed within an "isolation with migration" framework to make genome-wide estimates of the ages of these two species, long-term rates of gene flow between them, and effective population sizes and historical patterns of population growth. Our results indicate that H. annuus and H. petiolaris are approximately one million years old and have exchanged genes at a surprisingly high rate (long-term N(ef)m estimates of approximately 0.5 in each direction), with somewhat higher rates of introgression from H. annuus into H. petiolaris than vice versa. In addition, each species has undergone dramatic population expansion since divergence, and both species have among the highest levels of genetic diversity reported for flowering plants. Our results provide the most comprehensive estimate to date of long-term patterns of gene flow and historical demography in a nonmodel plant system, and they indicate that species integrity can be maintained even in the face of extensive gene flow over a prolonged period.

Analysis of chimpanzee history based on genome sequence alignments

Population geneticists often study small numbers of carefully chosen loci, but it has become possible to obtain orders of magnitude for more data from overlaps of genome sequences. Here, we generate tens of millions of base pairs of multiple sequence alignments from combinations of three western chimpanzees, three central chimpanzees, an eastern chimpanzee, a bonobo, a human, an orangutan, and a macaque. Analysis provides a more precise understanding of demographic history than was previously available. We show that bonobos and common chimpanzees were separated ∼1,290,000 years ago, western and other common chimpanzees ∼510,000 years ago, and eastern and central chimpanzees at least 50,000 years ago. We infer that the central chimpanzee population size increased by at least a factor of 4 since its separation from western chimpanzees, while the western chimpanzee effective population size decreased. Surprisingly, in about one percent of the genome, the genetic relationships between humans, chimpanzees, and bonobos appear to be different from the species relationships. We used PCR-based resequencing to confirm 11 regions where chimpanzees and bonobos are not most closely related. Study of such loci should provide information about the period of time 5–7 million years ago when the ancestors of humans separated from those of the chimpanzees.

Studies of population history traditionally examine a small number of genetic regions in many individuals; however, with genome sequencing technologies it is possible to assemble data sets with thousands more aligned sequences albeit in fewer individuals. To explore whether such data can provide useful insights about population history, we assembled large-scale data sets consisting of overlaps of random genome sequencing reads from chimpanzees and bonobos. Analysis of these data finds that bonobos and chimpanzees split from each other about 1.29 million years ago, western and central chimpanzees about 0.51 million years ago, and eastern and central chimpanzees at least 50,000 years ago. We find that the chimpanzee population has fluctuated significantly in size over the past half million years, with the central chimpanzee population size expanding dramatically, and the western chimpanzee population size contracting. Surprisingly, we also find that there are widespread regions of the genome where chimpanzees and bonobos are less closely related to each other than any of them are to humans. In these regions, chimpanzees and bonobos share a common genetic ancestor dating back to speciation from humans, providing a new source of information about that evolutionary event.