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

Estimating demographic parameters from large-scale population genomic data using Approximate Bayesian Computation

BACKGROUND

The Approximate Bayesian Computation (ABC) approach has been used to infer demographic parameters for numerous species, including humans. However, most applications of ABC still use limited amounts of data, from a small number of loci, compared to the large amount of genome-wide population-genetic data which have become available in the last few years.

RESULTS

We evaluated the performance of the ABC approach for three 'population divergence' models - similar to the 'isolation with migration' model - when the data consists of several hundred thousand SNPs typed for multiple individuals by simulating data from known demographic models. The ABC approach was used to infer demographic parameters of interest and we compared the inferred values to the true parameter values that was used to generate hypothetical "observed" data. For all three case models, the ABC approach inferred most demographic parameters quite well with narrow credible intervals, for example, population divergence times and past population sizes, but some parameters were more difficult to infer, such as population sizes at present and migration rates. We compared the ability of different summary statistics to infer demographic parameters, including haplotype and LD based statistics, and found that the accuracy of the parameter estimates can be improved by combining summary statistics that capture different parts of information in the data. Furthermore, our results suggest that poor choices of prior distributions can in some circumstances be detected using ABC. Finally, increasing the amount of data beyond some hundred loci will substantially improve the accuracy of many parameter estimates using ABC.

CONCLUSIONS

We conclude that the ABC approach can accommodate realistic genome-wide population genetic data, which may be difficult to analyze with full likelihood approaches, and that the ABC can provide accurate and precise inference of demographic parameters from these data, suggesting that the ABC approach will be a useful tool for analyzing large genome-wide datasets.

Heterogeneity in genetic diversity among non-coding loci fails to fit neutral coalescent models of population history

Inferring aspects of the population histories of species using coalescent analyses of non-coding nuclear DNA has grown in popularity. These inferences, such as divergence, gene flow, and changes in population size, assume that genetic data reflect simple population histories and neutral evolutionary processes. However, violating model assumptions can result in a poor fit between empirical data and the models. We sampled 22 nuclear intron sequences from at least 19 different chromosomes (a genomic transect) to test for deviations from selective neutrality in the gadwall (Anas strepera), a Holarctic duck. Nucleotide diversity among these loci varied by nearly two orders of magnitude (from 0.0004 to 0.029), and this heterogeneity could not be explained by differences in substitution rates alone. Using two different coalescent methods to infer models of population history and then simulating neutral genetic diversity under these models, we found that the observed among-locus heterogeneity in nucleotide diversity was significantly higher than expected for these simple models. Defining more complex models of population history demonstrated that a pre-divergence bottleneck was also unlikely to explain this heterogeneity. However, both selection and interspecific hybridization could account for the heterogeneity observed among loci. Regardless of the cause of the deviation, our results illustrate that violating key assumptions of coalescent models can mislead inferences of population history.

Female contributions to the peaceful nature of bonobo society

Although chimpanzees (Pan troglodytes) and bonobos (Pan paniscus) are closely related, females of the two species show surprisingly large differences in many behavioral aspects. While female chimpanzees tend to range alone or in small parties during non-estrous periods, female bonobos aggregate even more often than do males. Female chimpanzees do not have frequent social interactions with other females, whereas female bonobos maintain close social associations with one another. Although the ranging patterns of chimpanzee parties are generally led by males, female bonobos often take the initiative in ranging behavior. While female chimpanzees usually do not exhibit estrus during postpartum amenorrhea or pregnancy, female bonobos exhibit a prolonged pseudo-estrus during such non-conceptive periods. Studies of these two species have also shown great differences in agonistic behaviors performed by males. Male chimpanzees frequently fight with other males to compete for estrous females, but male bonobos seldom do so. While there are many records of infanticide by male chimpanzees, there is no confirmed record of such an event among bonobos. Several cases of within-group killing among adult male chimpanzees have been reported, but there is no such record for bonobos. While intergroup conflicts among chimpanzees sometimes involve killing members of the other group, intergroup conflicts among bonobos are considerably more moderate. In some cases, bonobos from two different groups may even range together for several days while engaging in various peaceful interactions. I will address two important questions that arise from these comparisons, exploring why females of such closely related species show such clear differences in behavior and whether or not the behavioral characteristics of female bonobos contribute to the peaceful nature of bonobo society.

Recent progress in polymorphism-based population genetic inference

The recent availability of whole-genome sequencing data affords tremendous power for statistical inference. With this, there has been great interest in the development of polymorphism-based approaches for the estimation of population genetic parameters. These approaches seek to estimate, for example, recently fixed or sweeping beneficial mutations, the rate of recurrent positive selection, the distribution of selection coefficients, and the demographic history of the population. Yet despite estimating similar parameters using similar data sets, results between methodologies are far from consistent. We here summarize the current state of the field, compare existing approaches, and attempt to reconcile emerging discrepancies. We also discuss the biases in selection estimators introduced by ignoring the demographic history of the population, discuss the biases in demographic estimators introduced by assuming neutrality, and highlight the important challenge to the field of achieving a true joint estimation procedure to circumvent these confounding effects.

Pleistocene speciation in the genus Populus (salicaceae)

The macroevolutionary consequences of recent climate change remain controversial, and there is little paleobotanical or morphological evidence that Pleistocene (1.8-0.12 Ma) glacial cycles acted as drivers of speciation, especially among lineages with long generation times, such as trees. We combined genetic and ecogeographic data from 2 closely related North American tree species, Populus balsamifera and P. trichocarpa (Salicacaeae), to determine if their divergence coincided with and was possibly caused by Pleistocene climatic events. We analyzed 32 nuclear loci from individuals of P. balsamifera and P. trichocarpa to produce coalescent-based estimates of the divergence time between the 2 species. We coupled the coalescent analyses with paleodistribution models to assess the influence of climate change on species' range. Furthermore, measures of niche overlap were used to investigate patterns of ecological differentiation between species. We estimated the divergence date of P. balsamifera and P. trichocarpa at approximately 75 Ka, which corresponds closely with the onset of Marine Isotope Stage 4 (∼76 Ka) and a rapid increase in global ice volume. Significance tests of niche overlap, in conjunction with genetic estimates of migration, suggested that speciation occurred in allopatry, possibly resulting from the environmental effects of Pleistocene glacial cycles. Our results indicate that the divergence of keystone tree species, which have shaped community diversity in northern North American ecosystems, was recent and may have been a consequence of Pleistocene-era glaciation and climate change.

Isolation and gene flow: inferring the speciation history of European house mice

Inferring the history of isolation and gene flow during species differentiation can inform us on the processes underlying their formation. Following their recent expansion in Europe, two subspecies of the house mouse (Mus musculus domesticus and Mus musculus musculus) have formed a hybrid zone maintained by hybrid incompatibilities and possibly behavioural reinforcement, offering a good model of incipient speciation. We reconstruct the history of their divergence using an approximate Bayesian computation framework and sequence variation at 57 autosomal loci. We find support for a long isolation period preceding the advent of gene flow around 200,000 generations ago, much before the formation of the European hybrid zone a few thousand years ago. The duration of the allopatric episode appears long enough (74% of divergence time) to explain the accumulation of many post-zygotic incompatibilities expressed in the present hybrid zone. The ancient contact inferred could have played a role in mating behaviour divergence and laid the ground for further reinforcement. We suggest that both subspecies originally colonized the Middle East from the northern Indian subcontinent, domesticus settling on the shores of the Persian Gulf and musculus on those of the Caspian Sea. Range expansions during interglacials would have induced secondary contacts, presumably in Iran, where they must have also interacted with Mus musculus castaneus. Future studies should incorporate this possibility, and we point to Iran and its surroundings as a hot spot for house mouse diversity and speciation studies.

Does speciation between Arabidopsis halleri and Arabidopsis lyrata coincide with major changes in a molecular target of adaptation?

Ever since Darwin proposed natural selection as the driving force for the origin of species, the role of adaptive processes in speciation has remained controversial. In particular, a largely unsolved issue is whether key divergent ecological adaptations are associated with speciation events or evolve secondarily within sister species after the split. The plant Arabidopsis halleri is one of the few species able to colonize soils highly enriched in zinc and cadmium. Recent advances in the molecular genetics of adaptation show that the physiology of this derived ecological trait involves copy number expansions of the AhHMA4 gene, for which orthologs are found in single copy in the closely related A. lyrata and the outgroup A. thaliana. To gain insight into the speciation process, we ask whether adaptive molecular changes at this candidate gene were contemporary with important stages of the speciation process. We first inferred the scenario and timescale of speciation by comparing patterns of variation across the genomic backgrounds of A. halleri and A. lyrata. Then, we estimated the timing of the first duplication of AhHMA4 in A. halleri. Our analysis suggests that the historical split between the two species closely coincides with major changes in this molecular target of adaptation in the A. halleri lineage. These results clearly indicate that these changes evolved in A. halleri well before industrial activities fostered the spread of Zn- and Cd-polluted areas, and suggest that adaptive processes related to heavy-metal homeostasis played a major role in the speciation process.

Perspectives on human population structure at the cusp of the sequencing era

Human groups show structured levels of genetic similarity as a consequence of factors such as geographical subdivision and genetic drift. Surveying this structure gives us a scientific perspective on human origins, sheds light on evolutionary processes that shape both human adaptation and disease, and is integral to effectively carrying out the mission of global medical genetics and personalized medicine. Surveys of population structure have been ongoing for decades, but in the past three years, single-nucleotide-polymorphism (SNP) array technology has provided unprecedented detail on human population structure at global and regional scales. These studies have confirmed well-known relationships between distantly related populations and uncovered previously unresolvable relationships among closely related human groups. SNPs represent the first dense genome-wide markers, and as such, their analysis has raised many challenges and insights relevant to the study of population genetics with whole-genome sequences. Here we draw on the lessons from these studies to anticipate the directions that will be most fruitful to pursue during the emerging whole-genome sequencing era.

Overestimation of nonsynonymous/synonymous rate ratio by reverse-translation of aligned amino acid sequences

In the analysis of protein-coding nucleotide sequences, the ratio of the number of nonsynonymous substitutions to that of synonymous substitutions (d(N)/d(S)) is used as an indicator for the direction and magnitude of natural selection operating at the amino acid sequence level. The d(S) and d(N) values are estimated based on the comparison of homologous codons, which are often identified by converting (reverse-translating) aligned amino acid sequences into codon sequences. In this method, however, homologous codons may be mis-identified when frame-shifts occurred or amino acid sequences were mis-aligned, which may lead to overestimation of the d(N)/d(S) ratio. Here the effect of reverse-translating aligned amino acid sequences on the estimation of d(N)/d(S) ratio was examined through a large-scale analysis of protein-coding nucleotide sequences from vertebrate species. Apparently, 1-9% of codon sites that were identified as homologous with reverse-translation contained non-homologous codons, where the d(N)/d(S) ratio was unduly high. By correcting the d(N)/d(S) ratio for these codon sites, it was inferred that the ratio was 5-43% overestimated with reverse-translation. These results suggest that caution should be exerted in the study of natural selection using the d(N)/d(S) ratio by reverse-translating aligned amino acid sequences.

Likelihood-based inferences under isolation by distance: two-dimensional habitats and confidence intervals

Likelihood-based methods of inference of population parameters from genetic data in structured populations have been implemented but still little tested in large networks of populations. In this work, a previous software implementation of inference in linear habitats is extended to two-dimensional habitats, and the coverage properties of confidence intervals are analyzed in both cases. Both standard likelihood and an efficient approximation are considered. The effects of misspecification of mutation model and dispersal distribution, and of spatial binning of samples, are considered. In the absence of model misspecification, the estimators have low bias, low mean square error, and the coverage properties of confidence intervals are consistent with theoretical expectations. Inferences of dispersal parameters and of the mutation rate are sensitive to misspecification or to approximations inherent to the coalescent algorithms used. In particular, coalescent approximations are not appropriate to infer the shape of the dispersal distribution. However, inferences of the neighborhood parameter (or of the product of population density and mean square dispersal rate) are generally robust with respect to complicating factors, such as misspecification of the mutation process and of the shape of the dispersal distribution, and with respect to spatial binning of samples. Likelihood inferences appear feasible in moderately sized networks of populations (up to 400 populations in this work), and they are more efficient than previous moment-based spatial regression method in realistic conditions.

Higher differentiation among subspecies of the house mouse (Mus musculus) in genomic regions with low recombination

In the early stages of reproductive isolation, genomic regions of reduced recombination are expected to show greater levels of differentiation, either because gene flow between species is reduced in these regions or because the effects of selection at linked sites within species are enhanced in these regions. Here, we study the patterns of DNA sequence variation at 27 autosomal loci among populations of Mus musculus musculus, M. m. domesticus, and M. m. castaneus, three subspecies of house mice with collinear genomes. We found that some loci exhibit considerable shared variation among subspecies, while others exhibit fixed differences. We used an isolation-with-gene-flow model to estimate divergence times and effective population sizes (N(e) ) and to disentangle ancestral variation from gene flow. Estimates of divergence time indicate that all three subspecies diverged from one another within a very short period of time approximately 350,000 years ago. Overall, N(e) for each subspecies was associated with the degree of genetic differentiation: M. m. musculus had the smallest N(e) and the greatest proportion of monophyletic gene genealogies, while M. m. castaneus had the largest N(e) and the smallest proportion of monophyletic gene genealogies. M. m. domesticus and M. m. musculus were more differentiated from each other than either were from M. m. castaneus, consistent with greater reproductive isolation between M. m. domesticus and M. m. musculus. F(ST) was significantly greater at loci experiencing low recombination rates compared to loci experiencing high recombination rates in comparisons between M. m. castaneus and M. m. musculus or M. m. domesticus. These results provide evidence that genomic regions with less recombination show greater differentiation, even in the absence of chromosomal rearrangements.

Making inferences about speciation using sophisticated statistical genetics methods: look before you leap

Understanding speciation is a fundamental aim of evolutionary biology and a very challenging one. Speciation can be viewed as the dynamics of genetic differentiation between populations resulting in substantial reproductive isolation (Gavrilets 2003). It was generally accepted that very small levels of migration prevent genetic differentiation among populations and, therefore, speciation. However, recent theoretical work showed that sympatric speciation is possible (Gavrilets 2003). Nevertheless, providing empirical evidence that gene flow occurred during speciation is challenging because several gene flow scenarios can explain observed patterns of genetic differentiation. Positive migration rate estimates alone do not prove ongoing gene flow during divergence. We also need to know whether migration took place before, during or after speciation. There is no statistical method specifically aimed at estimating gene flow timing, but several studies used the isolation with migration model (Hey & Nielsen 2004, 2007; Hey 2010b) to estimate this parameter and make inferences about speciation scenarios. It is tempting to use statistical methods to estimate important evolutionary parameters even if they do not appear explicitly in the inference model. Nevertheless, before doing so, we need to determine whether they can provide reliable results. In this issue of Molecular Ecology, Strasburg and Rieseberg (2011) present a simulation study that examines the degree to which gene flow timing estimates obtained from IMa2 (Hey 2010b) can be used to make inferences about speciation mode. Their results are sobering; gene flow timing estimates obtained in this way are not reliable and cannot be used to unequivocally establish if gene flow was ongoing during speciation.

Demographic processes underlying subtle patterns of population structure in the scalloped hammerhead shark, Sphyrna lewini

Genetic diversity (θ), effective population size (N(e)), and contemporary levels of gene flow are important parameters to estimate for species of conservation concern, such as the globally endangered scalloped hammerhead shark, Sphyrna lewini. Therefore, we have reconstructed the demographic history of S. lewini across its Eastern Pacific (EP) range by applying classical and coalescent population genetic methods to a combination of 15 microsatellite loci and mtDNA control region sequences. In addition to significant population genetic structure and isolation-by-distance among seven coastal sites between central Mexico and Ecuador, the analyses revealed that all populations have experienced a bottleneck and that all current values of θ are at least an order of magnitude smaller than ancestral θ, indicating large decreases in N(e) (θ = 4N(e)μ), where μ is the mutation rate. Application of the isolation-with-migration (IM) model showed modest but significant genetic connectivity between most sampled sites (point estimates of Nm = 0.1-16.7), with divergence times (t) among all populations significantly greater than zero. Using a conservative (i.e., slow) fossil-based taxon-specific phylogenetic calibration for mtDNA mutation rates, posterior probability distributions (PPDs) for the onset of the decline in N(e) predate modern fishing in this region. The cause of decline over the last several thousand years is unknown but is highly atypical as a post-glacial demographic history. Regardless of the cause, our data and analyses suggest that S. lewini was far more abundant throughout the EP in the past than at present.

Bonobos fall within the genomic variation of chimpanzees

To gain insight into the patterns of genetic variation and evolutionary relationships within and between bonobos and chimpanzees, we sequenced 150,000 base pairs of nuclear DNA divided among 15 autosomal regions as well as the complete mitochondrial genomes from 20 bonobos and 58 chimpanzees. Except for western chimpanzees, we found poor genetic separation of chimpanzees based on sample locality. In contrast, bonobos consistently cluster together but fall as a group within the variation of chimpanzees for many of the regions. Thus, while chimpanzees retain genomic variation that predates bonobo-chimpanzee speciation, extensive lineage sorting has occurred within bonobos such that much of their genome traces its ancestry back to a single common ancestor that postdates their origin as a group separate from chimpanzees.

The complex analytical landscape of gene flow inference

Gene flow estimation is essential for characterizing local adaptation, speciation potential and connectivity among threatened populations. New model-based population genetic methods can resolve complex demographic histories, but many studies in fields such as landscape genetics continue to rely on simple rules of thumb focused on gene flow to explain patterns of spatial differentiation. Here, we show how methods that use gene genealogies can reveal cryptic demographic histories and provide better estimates of gene flow with other parameters that contribute to genetic variation across landscapes and seascapes. We advocate for the expanded use and development of methods that consider spatial differentiation as the product of multiple forces interacting over time, and caution against a routine reliance on post-hoc gene flow interpretations.

Jaatha: a fast composite-likelihood approach to estimate demographic parameters

While information about a species' demography is interesting in its own right, it is an absolute necessity for certain types of population genetic analyses. The most widely used methods to infer a species' demographic history do not take intralocus recombination or recent divergence into account, and some methods take several weeks to converge. Here, we present Jaatha, a new composite-likelihood method that does incorporate recent divergence and is also applicable when intralocus recombination rates are high. This new method estimates four demographic parameters. The accuracy of Jaatha is comparable to that of other currently available methods, although it is superior under certain conditions, especially when divergence is very recent. As a proof of concept, we apply this new method to estimate demographic parameters for two closely related wild tomato species, Solanum chilense and S. peruvianum. Our results indicate that these species likely diverged 1.44·N generations ago, where N is the effective population size of S. chilense, and that some introgression between these species continued after the divergence process initiated. Furthermore, S. peruvianum likely experienced a population expansion following speciation.

Estimating parameters of speciation models based on refined summaries of the joint site-frequency spectrum

Understanding the processes and conditions under which populations diverge to give rise to distinct species is a central question in evolutionary biology. Since recently diverged populations have high levels of shared polymorphisms, it is challenging to distinguish between recent divergence with no (or very low) inter-population gene flow and older splitting events with subsequent gene flow. Recently published methods to infer speciation parameters under the isolation-migration framework are based on summarizing polymorphism data at multiple loci in two species using the joint site-frequency spectrum (JSFS). We have developed two improvements of these methods based on a more extensive use of the JSFS classes of polymorphisms for species with high intra-locus recombination rates. First, using a likelihood based method, we demonstrate that taking into account low-frequency polymorphisms shared between species significantly improves the joint estimation of the divergence time and gene flow between species. Second, we introduce a local linear regression algorithm that considerably reduces the computational time and allows for the estimation of unequal rates of gene flow between species. We also investigate which summary statistics from the JSFS allow the greatest estimation accuracy for divergence time and migration rates for low (around 10) and high (around 100) numbers of loci. Focusing on cases with low numbers of loci and high intra-locus recombination rates we show that our methods for the estimation of divergence time and migration rates are more precise than existing approaches.

Controlling for non-independence in comparative analysis of patterns across populations within species

How do we quantify patterns (such as responses to local selection) sampled across multiple populations within a single species? Key to this question is the extent to which populations within species represent statistically independent data points in our analysis. Comparative analyses across species and higher taxa have long recognized the need to control for the non-independence of species data that arises through patterns of shared common ancestry among them (phylogenetic non-independence), as have quantitative genetic studies of individuals linked by a pedigree. Analyses across populations lacking pedigree information fall in the middle, and not only have to deal with shared common ancestry, but also the impact of exchange of migrants between populations (gene flow). As a result, phenotypes measured in one population are influenced by processes acting on others, and may not be a good guide to either the strength or direction of local selection. Although many studies examine patterns across populations within species, few consider such non-independence. Here, we discuss the sources of non-independence in comparative analysis, and show why the phylogeny-based approaches widely used in cross-species analyses are unlikely to be useful in analyses across populations within species. We outline the approaches (intraspecific contrasts, generalized least squares, generalized linear mixed models and autoregression) that have been used in this context, and explain their specific assumptions. We highlight the power of 'mixed models' in many contexts where problems of non-independence arise, and show that these allow incorporation of both shared common ancestry and gene flow. We suggest what can be done when ideal solutions are inaccessible, highlight the need for incorporation of a wider range of population models in intraspecific comparative methods and call for simulation studies of the error rates associated with alternative approaches.

"Patchy-tachy" leads to false positives for recombination

Indirect tests have detected recombination in mitochondrial DNA (mtDNA) from many animal lineages, including mammals. However, it is possible that features of the molecular evolutionary process without recombination could be incorrectly inferred by indirect tests as being due to recombination. We have identified one such example, which we call "patchy-tachy" (PT), where different partitions of sequences evolve at different rates, that leads to an excess of false positives for recombination inferred by indirect tests. To explore this phenomena, we characterized the false positive rates of six widely used indirect tests for recombination using simulations of general models for mtDNA evolution with PT but without recombination. All tests produced 30-99% false positives for recombination, although the conditions that produced the maximal level of false positives differed between the tests. To evaluate the degree to which conditions that exacerbate false positives are found in published sequence data, we turned to 20 animal mtDNA data sets in which recombination is suggested by indirect tests. Using a model where different regions of the sequences were free to evolve at different rates in different lineages, we demonstrated that PT is prevalent in many data sets in which recombination was previously inferred using indirect tests. Taken together, our results argue that PT without recombination is a viable alternative explanation for detection of widespread recombination in animal mtDNA using indirect tests.

Historical sampling reveals dramatic demographic changes in western gorilla populations

BACKGROUND

Today many large mammals live in small, fragmented populations, but it is often unclear whether this subdivision is the result of long-term or recent events. Demographic modeling using genetic data can estimate changes in long-term population sizes while temporal sampling provides a way to compare genetic variation present today with that sampled in the past. In order to better understand the dynamics associated with the divergences of great ape populations, these analytical approaches were applied to western gorillas (Gorilla gorilla) and in particular to the isolated and Critically Endangered Cross River gorilla subspecies (G. g. diehli).

RESULTS

We used microsatellite genotypes from museum specimens and contemporary samples of Cross River gorillas to infer both the long-term and recent population history. We find that Cross River gorillas diverged from the ancestral western gorilla population ~17,800 years ago (95% HDI: 760, 63,245 years). However, gene flow ceased only ~420 years ago (95% HDI: 200, 16,256 years), followed by a bottleneck beginning ~320 years ago (95% HDI: 200, 2,825 years) that caused a 60-fold decrease in the effective population size of Cross River gorillas. Direct comparison of heterozygosity estimates from museum and contemporary samples suggests a loss of genetic variation over the last 100 years.

CONCLUSIONS

The composite history of western gorillas could plausibly be explained by climatic oscillations inducing environmental changes in western equatorial Africa that would have allowed gorilla populations to expand over time but ultimately isolate the Cross River gorillas, which thereafter exhibited a dramatic population size reduction. The recent decrease in the Cross River population is accordingly most likely attributable to increasing anthropogenic pressure over the last several hundred years. Isolation of diverging populations with prolonged concomitant gene flow, but not secondary admixture, appears to be a typical characteristic of the population histories of African great apes, including gorillas, chimpanzees and bonobos.

Speciation history of three closely related pines Pinus mugo (T.), P. uliginosa (N.) and P. sylvestris (L.)

Nucleotide polymorphisms at genomic regions including 17 nuclear loci, two chloroplast and one mitochondrial DNA fragments were used to study the speciation history of three pine species: dwarf mountain pine (Pinus mugo), peat-bog pine (P. uliginosa) and Scots pine (P. sylvestris). We set out to investigate three specific speciation scenarios: (I) P. uliginosa is a homoploid hybrid between the other two, (II) the species have evolved without gene flow after divergence and (III) there has been substantial gene flow between the species since their divergence. Overall, the genetic data suggest that P. mugo and P. uliginosa share the same gene pool (average net divergence of 0.0001) and that the phenotypic differences (e.g. growth form) are most likely due to very limited areas of the genome. P. mugo and P. uliginosa are more diverged from P. sylvestris than from each other (average net divergence of 0.0027 and 0.0026, respectively). The nucleotide patterns can best be explained by the divergence with migration speciation scenario, although the hybrid speciation scenario with small genomic contribution from P. sylvestris cannot be completely ruled out. We suggest that the large amount of shared polymorphisms between the pine taxa and the lack of monophyly at all loci studied between P. sylvestris and P. mugo-P. uliginosa can largely be explained by relatively recent speciation history and large effective population sizes but also by interspecific gene flow. These closely related pine taxa form an excellent system for searching for loci involved in adaptive variation as they are differentiated in phenotype and ecology but have very similar genetic background.

Estimating divergence time and ancestral effective population size of Bornean and Sumatran orangutan subspecies using a coalescent hidden Markov model

Due to genetic variation in the ancestor of two populations or two species, the divergence time for DNA sequences from two populations is variable along the genome. Within genomic segments all bases will share the same divergence—because they share a most recent common ancestor—when no recombination event has occurred to split them apart. The size of these segments of constant divergence depends on the recombination rate, but also on the speciation time, the effective population size of the ancestral population, as well as demographic effects and selection. Thus, inference of these parameters may be possible if we can decode the divergence times along a genomic alignment. Here, we present a new hidden Markov model that infers the changing divergence (coalescence) times along the genome alignment using a coalescent framework, in order to estimate the speciation time, the recombination rate, and the ancestral effective population size. The model is efficient enough to allow inference on whole-genome data sets. We first investigate the power and consistency of the model with coalescent simulations and then apply it to the whole-genome sequences of the two orangutan sub-species, Bornean (P. p. pygmaeus) and Sumatran (P. p. abelii) orangutans from the Orangutan Genome Project. We estimate the speciation time between the two sub-species to be thousand years ago and the effective population size of the ancestral orangutan species to be , consistent with recent results based on smaller data sets. We also report a negative correlation between chromosome size and ancestral effective population size, which we interpret as a signature of recombination increasing the efficacy of selection.

We present a hidden Markov model that uses variation in coalescence times between two distantly related populations, or closely related species, to infer population genetics parameters in ancestral population or species. The model infers the divergence times in segments along the alignment. Using coalescent simulations, we show that the model accurately estimates the divergence time between the two populations and the effective population size of the ancestral population. We apply the model to the recently sequenced orangutan sub-species and estimate their divergence time and the effective population size of their ancestor population.

Patterns of genetic variation within and between Gibbon species

Gibbons are small, arboreal, highly endangered apes that are understudied compared with other hominoids. At present, there are four recognized genera and approximately 17 species, all likely to have diverged from each other within the last 5-6 My. Although the gibbon phylogeny has been investigated using various approaches (i.e., vocalization, morphology, mitochondrial DNA, karyotype, etc.), the precise taxonomic relationships are still highly debated. Here, we present the first survey of nuclear sequence variation within and between gibbon species with the goal of estimating basic population genetic parameters. We gathered ~60 kb of sequence data from a panel of 19 gibbons representing nine species and all four genera. We observe high levels of nucleotide diversity within species, indicative of large historical population sizes. In addition, we find low levels of genetic differentiation between species within a genus comparable to what has been estimated for human populations. This is likely due to ongoing or episodic gene flow between species, and we estimate a migration rate between Nomascus leucogenys and N. gabriellae of roughly one migrant every two generations. Together, our findings suggest that gibbons have had a complex demographic history involving hybridization or mixing between diverged populations.

Evidence from Cameroon reveals differences in the genetic structure and histories of chimpanzee populations

The history of the genus Pan is a topic of enduring interest. Chimpanzees (Pan troglodytes) are often divided into subspecies, but the population structure and genetic history of chimpanzees across Africa remain unclear. Some population genetics studies have led to speculation that, until recently, this species constituted a single population with ongoing gene flow across its range, which resulted in a continuous gradient of allele frequencies. Chimpanzees, designated here as P. t. ellioti, occupy the Gulf of Guinea region that spans southern Nigeria and western Cameroon at the center of the distribution of this species. Remarkably, few studies have included individuals from this region, hindering the examination of chimpanzee population structure across Africa. Here, we analyzed microsatellite genotypes of 94 chimpanzees, including 32 designated as P. t. ellioti. We find that chimpanzees fall into three major populations: (i) Upper Guinea in western Africa (P. t. verus); (ii) the Gulf of Guinea region (P. t. ellioti); and (iii) equatorial Africa (P. t. troglodytes and P. t. schweinfurthii). Importantly, the Gulf of Guinea population is significantly different genetically from the others, sharing a last common ancestor with the populations in Upper Guinea ~0.46 million years ago (mya) and equatorial Africa ~0.32 mya. Equatorial chimpanzees are subdivided into up to three populations occupying southern Cameroon, central Africa, and eastern Africa, which may have constituted a single population until ~0.10-0.11 mya. Finally, occasional hybridization may be occurring between the Gulf of Guinea and southern Cameroon populations.

More reliable estimates of divergence times in Pan using complete mtDNA sequences and accounting for population structure

Here, we report the sequencing and analysis of eight complete mitochondrial genomes of chimpanzees (Pan troglodytes) from each of the three established subspecies (P. t. troglodytes, P. t. schweinfurthii and P. t. verus) and the proposed fourth subspecies (P. t. ellioti). Our population genetic analyses are consistent with neutral patterns of evolution that have been shaped by demography. The high levels of mtDNA diversity in western chimpanzees are unlike those seen at nuclear loci, which may reflect a demographic history of greater female to male effective population sizes possibly owing to the characteristics of the founding population. By using relaxed-clock methods, we have inferred a timetree of chimpanzee species and subspecies. The absolute divergence times vary based on the methods and calibration used, but relative divergence times show extensive uniformity. Overall, mtDNA produces consistently older times than those known from nuclear markers, a discrepancy that is reduced significantly by explicitly accounting for chimpanzee population structures in time estimation. Assuming the human-chimpanzee split to be between 7 and 5 Ma, chimpanzee time estimates are 2.1-1.5, 1.1-0.76 and 0.25-0.18 Ma for the chimpanzee/bonobo, western/(eastern + central) and eastern/central chimpanzee divergences, respectively.

Demographic signatures accompanying the evolution of selfing in Leavenworthia alabamica

The evolution of selfing from outcrossing is a common transition, yet little is known about the mutations and selective factors that promote this shift. In the mustard family, single-locus self-incompatibility (SI) enforces outcrossing. In this study, we test whether mutations causing self-compatibility (SC) are linked to the self-incompatibility locus (S-locus) in Leavenworthia alabamica, a species where two selfing races (a2 and a4) co-occur with outcrossing populations. We also infer the ecological circumstances associated with origins of selfing using molecular sequence data. Genealogical reconstruction of the Lal2 locus, the putative ortholog of the SRK locus, showed that both selfing races are fixed for one of two different S-linked Lal2 sequences, whereas outcrossing populations harbor many S-alleles. Hybrid crosses demonstrated that S-linked mutations cause SC in each selfing race. These results strongly suggest two origins of selfing in this species, a result supported by population admixture analysis of 16 microsatellite loci and by a population tree built from eight nuclear loci. One selfing race (a4) shows signs of a severe population bottleneck, suggesting that reproductive assurance might have caused the evolution of selfing in this case. In contrast, the population size of race a2 cannot be distinguished from that of outcrossing populations after correcting for differences in selfing rates. Coalescent-based analyses suggest a relatively old origin of selfing in the a4 race (∼150 ka ago), whereas selfing evolved recently in the a2 race (∼12-48 ka ago). These results imply that S-locus mutations have triggered two recent shifts to selfing in L. alabamica, but that these transitions are not always associated with a severe population bottleneck, suggesting that factors other than reproductive assurance may play a role in its evolution.

Recovering population parameters from a single gene genealogy: an unbiased estimator of the growth rate

We show that the number of lineages ancestral to a sample, as a function of time back into the past, which we call the number of lineages as a function of time (NLFT), is a nearly deterministic property of large-sample gene genealogies. We obtain analytic expressions for the NLFT for both constant-sized and exponentially growing populations. The low level of stochastic variation associated with the NLFT of a large sample suggests using the NLFT to make estimates of population parameters. Based on this, we develop a new computational method of inferring the size and growth rate of a population from a large sample of DNA sequences at a single locus. We apply our method first to a sample of 1,212 mitochondrial DNA (mtDNA) sequences from China, confirming a pattern of recent population growth previously identified using other techniques, but with much smaller confidence intervals for past population sizes due to the low variation of the NLFT. We further analyze a set of 63 mtDNA sequences from blue whales (BWs), concluding that the population grew in the past. This calls for reevaluation of previous studies that were based on the assumption that the BW population was fixed.

Population genetics of foxtail millet and its wild ancestor

Background

Foxtail millet (Setaria italica (L.) P. Beauv.), one of the most ancient domesticated crops, is becoming a model system for studying biofuel crops and comparative genomics in the grasses. However, knowledge on the level of genetic diversity and linkage disequilibrium (LD) is very limited in this crop and its wild ancestor, green foxtail (Setaria viridis (L.) P. Beauv.). Such information would help us to understand the domestication process of cultivated species and will allow further research in these species, including association mapping and identification of agricultural significant genes involved in domestication.

Results

In this study, we surveyed DNA sequence for nine loci across 50 accessions of cultivated foxtail millet and 34 of its wild progenitor. We found a low level of genetic diversity in wild green foxtail (θ = 0.0059), θ means Watterson's estimator of θ. Despite of a 55% loss of its wild diversity, foxtail millet still harbored a considerable level of diversity (θ = 0.0027) when compared to rice and sorghum (θ = 0.0024 and 0.0034, respectively). The level of LD in the domesticated foxtail millet extends to 1 kb, while it decayed rapidly to a negligible level within 150 bp in wild green foxtail. Using coalescent simulation, we estimated the bottleneck severity at k = 0.6095 when ρ/θ = 1. These results indicated that the domestication bottleneck of foxtail millet was more severe than that of maize but slightly less pronounced than that of rice.

Conclusions

The results in this study establish a general framework for the domestication history of foxtail millet. The low level of genetic diversity and the increased level of LD in foxtail millet are mainly caused by a population bottleneck, although gene flow from foxtail millet to green foxtail is another factor that may have shaped the pattern of genetic diversity of these two related gene pools. The knowledge provided in this study will benefit future population based studies in foxtail millet.

The population genomics of plant adaptation

There has been an enormous increase in the amount of data on DNA sequence polymorphism available for many organisms in the last decade. New sequencing technologies provide great potential for investigating natural selection in plants using population genomic approaches. However, plant populations frequently show significant departures from the assumptions of standard models used to detect selection and many forms of directional selection do not fit with classical population genetics theory. Here, we explore the extent to which plant populations show departures from standard model assumptions, and the implications this has for detecting selection on molecular variation. A growing number of multilocus studies of nucleotide variation suggest that changes in population size, particularly bottlenecks, and strong subdivision may be common in plants. This demographic variation presents important challenges for models used to infer selection. In addition, selection from standing genetic variation and multiple independent adaptive substitutions can further complicate efforts to understand the nature of selection. We discuss emerging patterns from plant studies and propose that, rather than treating population history as a nuisance variable when testing for selection, the interaction between demography and selection is of fundamental importance for evolutionary studies of plant populations using molecular data.

Nucleotide diversity patterns of local adaptation at drought-related candidate genes in wild tomatoes

We surveyed nucleotide diversity at two candidate genes LeNCED1 and pLC30-15, involved in an ABA (abscisic acid) signalling pathway, in two closely related tomato species Solanum peruvianum and Solanum chilense. Our six population samples (three for each species) cover a range of mesic to very dry habitats. The ABA pathway plays an important role in the plants' response to drought stress. LeNCED1 is an upstream gene involved in ABA biosynthesis, and pLC30-15 is a dehydrin gene positioned downstream in the pathway. The two genes show very different patterns of nucleotide variation. LeNCED1 exhibits very low nucleotide diversity relative to the eight neutral reference loci that were previously surveyed in these populations. This suggests that strong purifying selection has been acting on this gene. In contrast, pLC30-15 exhibits higher levels of nucleotide diversity and, in particular in S. chilense, higher genetic differentiation between populations than the reference loci, which is indicative of local adaptation. In the more drought-tolerant species S. chilense, one population (from Quicacha) shows a significant haplotype structure, which appears to be the result of positive (diversifying) selection.

The confounding effects of population structure, genetic diversity and the sampling scheme on the detection and quantification of population size changes

The idea that molecular data should contain information on the recent evolutionary history of populations is rather old. However, much of the work carried out today owes to the work of the statisticians and theoreticians who demonstrated that it was possible to detect departures from equilibrium conditions (e.g., panmictic population/mutation-drift equilibrium) and interpret them in terms of deviations from neutrality or stationarity. During the last 20 years the detection of population size changes has usually been carried out under the assumption that samples were obtained from populations that can be approximated by a Wright-Fisher model (i.e., assuming panmixia, demographic stationarity, etc.). However, natural populations are usually part of spatial networks and are interconnected through gene flow. Here we simulated genetic data at mutation and migration-drift equilibrium under an n-island and a stepping-stone model. The simulated populations were thus stationary and not subject to any population size change. We varied the level of gene flow between populations and the scaled mutation rate. We also used several sampling schemes. We then analyzed the simulated samples using the Bayesian method implemented in MSVAR, the Markov Chain Monte Carlo simulation program, to detect and quantify putative population size changes using microsatellite data. Our results show that all three factors (genetic differentiation/gene flow, genetic diversity, and the sampling scheme) play a role in generating false bottleneck signals. We also suggest an ad hoc method to counter this effect. The confounding effect of population structure and of the sampling scheme has practical implications for many conservation studies. Indeed, if population structure is creating "spurious" bottleneck signals, the interpretation of bottleneck signals from genetic data might be less straightforward than it would seem, and several studies may have overestimated or incorrectly detected bottlenecks in endangered species.

Testing founder effect speciation: divergence population genetics of the spoonbills Platalea regia and Pl. minor (Threskiornithidae, Aves)

Although founder effect speciation has been a popular theoretical model for the speciation of geographically isolated taxa, its empirical importance has remained difficult to evaluate due to the intractability of past demography, which in a founder effect speciation scenario would involve a speciational bottleneck in the emergent species and the complete cessation of gene flow following divergence. Using regression-weighted approximate Bayesian computation, we tested the validity of these two fundamental conditions of founder effect speciation in a pair of sister species with disjunct distributions: the royal spoonbill Platalea regia in Australasia and the black-faced spoonbill Pl. minor in eastern Asia. When compared with genetic polymorphism observed at 20 nuclear loci in the two species, simulations showed that the founder effect speciation model had an extremely low posterior probability (1.55 × 10(-8)) of producing the extant genetic pattern. In contrast, speciation models that allowed for postdivergence gene flow were much more probable (posterior probabilities were 0.37 and 0.50 for the bottleneck with gene flow and the gene flow models, respectively) and postdivergence gene flow persisted for a considerable period of time (more than 80% of the divergence history in both models) following initial divergence (median = 197,000 generations, 95% credible interval [CI]: 50,000-478,000, for the bottleneck with gene flow model; and 186,000 generations, 95% CI: 45,000-477,000, for the gene flow model). Furthermore, the estimated population size reduction in Pl. regia to 7,000 individuals (median, 95% CI: 487-12,000, according to the bottleneck with gene flow model) was unlikely to have been severe enough to be considered a bottleneck. Therefore, these results do not support founder effect speciation in Pl. regia but indicate instead that the divergence between Pl. regia and Pl. minor was probably driven by selection despite continuous gene flow. In this light, we discuss the potential importance of evolutionarily labile traits with significant fitness consequences, such as migratory behavior and habitat preference, in facilitating divergence of the spoonbills.

Evolutionary genetics in wild primates: combining genetic approaches with field studies of natural populations

Ecological and evolutionary studies of wild primates hold important keys to understanding both the shared characteristics of primate biology and the genetic and phenotypic differences that make specific lineages, including our own, unique. Although complementary genetic research on nonhuman primates has long been of interest, recent technological and methodological advances now enable functional and population genetic studies in an unprecedented manner. In the past several years, novel genetic data sets have revealed new information about the demographic history of primate populations and the genetics of adaptively important traits. In combination with the rich history of behavioral, ecological, and physiological work on natural primate populations, genetic approaches promise to provide a compelling picture of primate evolution in the past and in the present day.

A likelihood ratio test of speciation with gene flow using genomic sequence data

Genomic sequence data may be used to test hypotheses about the process of species formation. In this paper, I implement a likelihood ratio test of variable species divergence times over the genome, which may be considered a test of the null model of allopatric speciation without gene flow against the alternative model of parapatric speciation with gene flow. Two models are implemented in the likelihood framework, which accommodate coalescent events in the ancestral populations in a phylogeny of three species. One model assumes a constant species divergence time over the genome, whereas another allows it to vary. Computer simulation shows that the test has acceptable false positive rate but to achieve reasonable power, hundreds or even thousands of genomic loci may be necessary. The test is applied to genomic data from the human, chimpanzee, and gorilla.

Sex-linked inheritance in macaque monkeys: implications for effective population size and dispersal to Sulawesi

Sex-specific differences in dispersal, survival, reproductive success, and natural selection differentially affect the effective population size (N(e)) of genomic regions with different modes of inheritance such as sex chromosomes and mitochondrial DNA. In papionin monkeys (macaques, baboons, geladas, mandrills, drills, and mangabeys), for example, these factors are expected to reduce N(e) of paternally inherited portions of the genome compared to maternally inherited portions. To explore this further, we quantified relative N(e) of autosomal DNA, X and Y chromosomes, and mitochondrial DNA using molecular polymorphism and divergence information from pigtail macaque monkeys (Macaca nemestrina). Consistent with demographic expectations, we found that N(e) of the Y is lower than expected from a Wright-Fisher idealized population with an equal proportion of males and females, whereas N(e) of mitochondrial DNA is higher. However, N(e) of 11 loci on the X chromosome was lower than expected, a finding that could be explained by pervasive hitchhiking effects on this chromosome. We evaluated the fit of these data to various models involving natural selection or sex-biased demography. Significant support was recovered for natural selection acting on the Y chromosome. A demographic model with a skewed sex ratio was more likely than one with sex-biased migration and explained the data about as well as an ideal model without sex-biased demography. We then incorporated these results into an evaluation of macaque divergence and migration on Borneo and Sulawesi islands. One X-linked locus was not monophyletic on Sulawesi, but multilocus data analyzed in a coalescent framework failed to reject a model without migration between these islands after both were colonized.

ABC as a flexible framework to estimate demography over space and time: some cons, many pros

The analysis of genetic variation to estimate demographic and historical parameters and to quantitatively compare alternative scenarios recently gained a powerful and flexible approach: the Approximate Bayesian Computation (ABC). The likelihood functions does not need to be theoretically specified, but posterior distributions can be approximated by simulation even assuming very complex population models including both natural and human-induced processes. Prior information can be easily incorporated and the quality of the results can be analysed with rather limited additional effort. ABC is not a statistical analysis per se, but rather a statistical framework and any specific application is a sort of hybrid between a simulation and a data-analysis study. Complete software packages performing the necessary steps under a set of models and for specific genetic markers are already available, but the flexibility of the method is better exploited combining different programs. Many questions relevant in ecology can be addressed using ABC, but adequate amount of time should be dedicated to decide among alternative options and to evaluate the results. In this paper we will describe and critically comment on the different steps of an ABC analysis, analyse some of the published applications of ABC and provide user guidelines.