PopABC: a program to infer historical demographic parameters

Different molecular changes underlie the same phenotypic transition: Origins and consequences of independent shifts to homostyly within species

The repeated transition from outcrossing to selfing is a key topic in evolutionary biology. However, the molecular basis of such shifts has been rarely examined due to lack of knowledge of the genes controlling these transitions. A classic example of mating system transition is the repeated shift from heterostyly to homostyly. Occurring in 28 angiosperm families, heterostyly is characterized by the reciprocal position of male and female sexual organs in two (or three) distinct, usually self-incompatible floral morphs. Conversely, homostyly is characterized by a single, self-compatible floral morph with reduced separation of male and female organs, facilitating selfing. Here, we investigate the origins of homostyly in Primula vulgaris and its microevolutionary consequences by integrating surveys of the frequency of homostyles in natural populations, DNA sequence analyses of the gene controlling the position of female sexual organs (CYPᵀ), and microsatellite genotyping of both progeny arrays and natural populations characterized by varying frequencies of homostyles. As expected, we found that homostyles displace short-styled individuals, but long-style morphs are maintained at low frequencies within populations. We also demonstrated that homostyles repeatedly evolved from short-styled individuals in association with different types of loss-of-function mutations in CYPᵀ. Additionally, homostyly triggers a shift to selfing, promoting increased inbreeding within and genetic differentiation among populations. Our results elucidate the causes and consequences of repeated transitions to homostyly within species, and the putative mechanisms precluding its fixation in P. vulgaris. This study represents a benchmark for future analyses of losses of heterostyly in other angiosperms.

Efficient ancestry and mutation simulation with msprime 1.0

Stochastic simulation is a key tool in population genetics, since the models involved are often analytically intractable and simulation is usually the only way of obtaining ground-truth data to evaluate inferences. Because of this, a large number of specialized simulation programs have been developed, each filling a particular niche, but with largely overlapping functionality and a substantial duplication of effort. Here, we introduce msprime version 1.0, which efficiently implements ancestry and mutation simulations based on the succinct tree sequence data structure and the tskit library. We summarize msprime's many features, and show that its performance is excellent, often many times faster and more memory efficient than specialized alternatives. These high-performance features have been thoroughly tested and validated, and built using a collaborative, open source development model, which reduces duplication of effort and promotes software quality via community engagement.

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

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

Evolution and disappearance of sympatric Coregonus albula in a changing environment-A case study of the only remaining population pair in Sweden

During the past 50 years, Fennoscandian populations of spring-spawning Baltic cisco (Coregonus albula), sympatric to common autumn-spawners, have declined or disappeared; for example, three out of four known spring-spawning populations in Sweden are regarded as extinct. Over the same period, the climate has changed and populations have been subject to other anthropogenic stressors. We compared historic (1960s) and recent (1990-2000s) morphological data from the still-existent sympatric cisco populations in Lake Fegen, Sweden. Phenotypic changes were found for spring-spawners making them more similar to the sympatric autumn-spawners that had remained virtually unchanged. Based on results for other salmoniform fishes, a phenotypically plastic response to increased temperature during early development appears unlikely. The recent material was also analyzed with microsatellite markers; long-term effective population size in spring-spawners was estimated to be about 20 times lower than autumn-spawners, with signs of long-term gene flow in both directions and a recent genetic bottleneck in spring-spawners. We suggest the change toward a less distinct phenotype in spring-spawners to reflect a recent increase in gene flow from autumn-spawners. Time since divergence was estimated to only c. 1,900 years (95% CI: 400-5,900), but still the Fegen populations represent the most morphologically and genetically distinct sympatric populations studied. Consequently, we hypothesize that less distinct population pairs can be even younger and that spring-spawning may have repeatedly evolved and disappeared in several lakes since the end of the last glaciation, concurrent with changed environmental conditions.

The effect of undetected recombination on genealogy sampling and inference under an isolation-with-migration model

Many methods for fitting demographic models to data sets of aligned sequences rely upon an assumption that the data have a branching coalescent history without recombination within regions or loci. To mitigate the effects of the failure of this assumption, a common approach is to filter data and sample regions that pass the four-gamete criterion for recombination, an approach that allows data to run, but that is expected to detect only a minority of recombination events. A series of empirical tests of this approach were conducted using computer simulations with and without recombination for a variety of isolation-with-migration (IM) model for two and three populations. Only the IMa3 program was used, but the general results should apply to related genealogy-sampling-based methods for IM models or subsets of IM models. It was found that the details of sampling intervals that pass a four-gamete filter have a moderate effect, and that schemes that use the longest intervals, or that use overlapping intervals, gave poorer results. A simple approach of using a random nonoverlapping interval returned the smallest difference between results with and without recombination, with the mean difference between parameter estimates usually less than 20% of the true value (usually much less). However, the posterior probability distributions for migration rates were flatter with recombination, suggesting that filtering based on the four-gamete criterion, while necessary for methods like these, leads to reduced resolution on migration. A distinct, alternative approach, of using a finite sites mutation model and not filtering the data, performed quite poorly.

Using Genomic Data to Infer Historic Population Dynamics of Nonmodel Organisms

Genome sequence data are now being routinely obtained from many nonmodel organisms. These data contain a wealth of information about the demographic history of the populations from which they originate. Many sophisticated statistical inference procedures have been developed to infer the demographic history of populations from this type of genomic data. In this review, we discuss the different statistical methods available for inference of demography, providing an overview of the underlying theory and logic behind each approach. We also discuss the types of data required and the pros and cons of each method. We then discuss how these methods have been applied to a variety of nonmodel organisms. We conclude by presenting some recommendations for researchers looking to use genomic data to infer demographic history.

Phylogeny Estimation by Integration over Isolation with Migration Models

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

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

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

Voyage of discovery? A comment on Koch et al. "A voyage to Terra Australis: human-mediated dispersal of cats"

The origins of feral cats in Australia may be understood with the help of molecular studies, but it is important that hypotheses be tested with appropriate sampling and methodology. We point out several shortcomings in the analysis by Koch et al. (BMC Evol Biol 15:262, 2015; A voyage to Terra Australis: human-mediated dispersal of cats. Dryad Digital Repository, 2015), present a reanalysis of part of the study and discuss the challenges of elucidating the early history of feral cats.

Simulating and Summarizing Sources of Gene Tree Incongruence

We introduce a gene tree simulator that is designed for use in conjunction with approximate Bayesian computation approaches. We show that it can be used to determine the relative importance of hybrid speciation and introgression compared with incomplete lineage sorting (ILS) in producing patterns of incongruence across gene trees. Important features of the new simulator are (1) a choice of models to capture the decreasing probability of successful hybrid species formation or introgression as a function of genetic distance between potential parent species; (2) the ability for hybrid speciation to result in asymmetrical contributions of genetic material from each parent species; (3) the ability to vary the rates of hybrid speciation, introgression, and divergence speciation in different epochs; and (4) incorporation of the coalescent, so that patterns of incongruence due to ILS can be compared with those due to hybrid evolution. Given a set of gene trees generated by the simulator, we calculate a set of statistics, each measuring in a different way the discordance between the gene trees. We show that these statistics can be used to differentiate whether the gene tree discordance was largely due to hybridization, or only due to lineage sorting.

European wildcat populations are subdivided into five main biogeographic groups: consequences of Pleistocene climate changes or recent anthropogenic fragmentation?

Extant populations of the European wildcat are fragmented across the continent, the likely consequence of recent extirpations due to habitat loss and over‐hunting. However, their underlying phylogeographic history has never been reconstructed. For testing the hypothesis that the European wildcat survived the Ice Age fragmented in Mediterranean refuges, we assayed the genetic variation at 31 microsatellites in 668 presumptive European wildcats sampled in 15 European countries. Moreover, to evaluate the extent of subspecies/population divergence and identify eventual wild × domestic cat hybrids, we genotyped 26 African wildcats from Sardinia and North Africa and 294 random‐bred domestic cats. Results of multivariate analyses and Bayesian clustering confirmed that the European wild and the domestic cats (plus the African wildcats) belong to two well‐differentiated clusters (average Ф_ST = 0.159, r_st = 0.392, P > 0.001; Analysis of molecular variance [AMOVA]). We identified from c. 5% to 10% cryptic hybrids in southern and central European populations. In contrast, wild‐living cats in Hungary and Scotland showed deep signatures of genetic admixture and introgression with domestic cats. The European wildcats are subdivided into five main genetic clusters (average Ф_ST = 0.103, r_st = 0.143, P > 0.001; AMOVA) corresponding to five biogeographic groups, respectively, distributed in the Iberian Peninsula, central Europe, central Germany, Italian Peninsula and the island of Sicily, and in north‐eastern Italy and northern Balkan regions (Dinaric Alps). Approximate Bayesian Computation simulations supported late Pleistocene–early Holocene population splittings (from c. 60 k to 10 k years ago), contemporary to the last Ice Age climatic changes. These results provide evidences for wildcat Mediterranean refuges in southwestern Europe, but the evolution history of eastern wildcat populations remains to be clarified. Historical genetic subdivisions suggest conservation strategies aimed at enhancing gene flow through the restoration of ecological corridors within each biogeographic units. Concomitantly, the risk of hybridization with free‐ranging domestic cats along corridor edges should be carefully monitored.

Genetic and Epigenetic Diversities Shed Light on Domestication of Cultivated Ginseng (Panax ginseng)

Chinese ginseng (Panax ginseng) is a medically important herb within Panax and has crucial cultural values in East Asia. As the symbol of traditional Chinese medicine, Chinese ginseng has been used as a herbal remedy to restore stamina and capacity in East Asia for thousands of years. To address the evolutionary origin and domestication history of cultivated ginseng, we employed multiple molecular approaches to investigate the genetic structures of cultivated and wild ginseng across their distribution ranges in northeastern Asia. Phylogenetic and population genetic analyses revealed that the four cultivated ginseng landraces, COMMON, BIANTIAO, SHIZHU, and GAOLI (also known as Korean ginseng), were not domesticated independently and Fusong Town is likely one of the primary domestication centers. In addition, our results from population genetic and epigenetic analyses demonstrated that cultivated ginseng maintained high levels of genetic and epigenetic diversity, but showed distinct cytosine methylation patterns compared with wild ginseng. The patterns of genetic and epigenetic variation revealed by this study have shed light on the domestication history of cultivated ginseng, which may serve as a framework for future genetic improvements.

Software solutions for the livestock genomics SNP array revolution

Since the beginning of the genomic era, the number of available single nucleotide polymorphism (SNP) arrays has grown considerably. In the bovine species alone, 11 SNP chips not completely covered by intellectual property are currently available, and the number is growing. Genomic/genotype data are not standardized, and this hampers its exchange and integration. In addition, software used for the analyses of these data usually requires not standard (i.e. case specific) input files which, considering the large amount of data to be handled, require at least some programming skills in their production. In this work, we describe a software toolkit for SNP array data management, imputation, genome-wide association studies, population genetics and genomic selection. However, this toolkit does not solve the critical need for standardization of the genotypic data and software input files. It only highlights the chaotic situation each researcher has to face on a daily basis and gives some helpful advice on the currently available tools in order to navigate the SNP array data complexity.

Challenges in analysis and interpretation of microsatellite data for population genetic studies

Advancing technologies have facilitated the ever-widening application of genetic markers such as microsatellites into new systems and research questions in biology. In light of the data and experience accumulated from several years of using microsatellites, we present here a literature review that synthesizes the limitations of microsatellites in population genetic studies. With a focus on population structure, we review the widely used fixation (F ST) statistics and Bayesian clustering algorithms and find that the former can be confusing and problematic for microsatellites and that the latter may be confounded by complex population models and lack power in certain cases. Clustering, multivariate analyses, and diversity-based statistics are increasingly being applied to infer population structure, but in some instances these methods lack formalization with microsatellites. Migration-specific methods perform well only under narrow constraints. We also examine the use of microsatellites for inferring effective population size, changes in population size, and deeper demographic history, and find that these methods are untested and/or highly context-dependent. Overall, each method possesses important weaknesses for use with microsatellites, and there are significant constraints on inferences commonly made using microsatellite markers in the areas of population structure, admixture, and effective population size. To ameliorate and better understand these constraints, researchers are encouraged to analyze simulated datasets both prior to and following data collection and analysis, the latter of which is formalized within the approximate Bayesian computation framework. We also examine trends in the literature and show that microsatellites continue to be widely used, especially in non-human subject areas. This review assists with study design and molecular marker selection, facilitates sound interpretation of microsatellite data while fostering respect for their practical limitations, and identifies lessons that could be applied toward emerging markers and high-throughput technologies in population genetics.

Distinct and diverse: range-wide phylogeography reveals ancient lineages and high genetic variation in the endangered okapi (Okapia johnstoni)

The okapi is an endangered, evolutionarily distinctive even-toed ungulate classified within the giraffidae family that is endemic to the Democratic Republic of Congo. The okapi is currently under major anthropogenic threat, yet to date nothing is known about its genetic structure and evolutionary history, information important for conservation management given the species' current plight. The distribution of the okapi, being confined to the Congo Basin and yet spanning the Congo River, also makes it an important species for testing general biogeographic hypotheses for Congo Basin fauna, a currently understudied area of research. Here we describe the evolutionary history and genetic structure of okapi, in the context of other African ungulates including the giraffe, and use this information to shed light on the biogeographic history of Congo Basin fauna in general. Using nuclear and mitochondrial DNA sequence analysis of mainly non-invasively collected samples, we show that the okapi is both highly genetically distinct and highly genetically diverse, an unusual combination of genetic traits for an endangered species, and feature a complex evolutionary history. Genetic data are consistent with repeated climatic cycles leading to multiple Plio-Pleistocene refugia in isolated forests in the Congo catchment but also imply historic gene flow across the Congo River.

Present-day genetic structure of Atlantic salmon (Salmo salar) in Icelandic rivers and ice-cap retreat models

Due to an improved understanding of past climatological conditions, it has now become possible to study the potential concordance between former climatological models and present-day genetic structure. Genetic variability was assessed in 26 samples from different rivers of Atlantic salmon in Iceland (total of 2,352 individuals), using 15 microsatellite loci. F-statistics revealed significant differences between the majority of the populations that were sampled. Bayesian cluster analyses using both prior information and no prior information on sampling location revealed the presence of two distinguishable genetic pools - namely, the Northern (Group 1) and Southern (Group 2) regions of Iceland. Furthermore, the random permutation of different allele sizes among allelic states revealed a significant mutational component to the genetic differentiation at four microsatellite loci (SsaD144, Ssa171, SSsp2201 and SsaF3), and supported the proposition of a historical origin behind the observed variation. The estimated time of divergence, using two different ABC methods, suggested that the observed genetic pattern originated from between the Last Glacial Maximum to the Younger Dryas, which serves as additional evidence of the relative immaturity of Icelandic fish populations, on account of the re-colonisation of this young environment following the Last Glacial Maximum. Additional analyses suggested the presence of several genetic entities which were likely to originate from the original groups detected.

Genome-scale analysis of demographic history and adaptive selection

One of the main topics in population genetics is identification of adaptive selection among populations. For this purpose, population history should be correctly inferred to evaluate the effect of random drift and exclude it in selection identification. With the rapid progress in genomics in the past decade, vast genome-scale variations are available for population genetic analysis, which however requires more sophisticated models to infer species' demographic history and robust methods to detect local adaptation. Here we aim to review what have been achieved in the fields of demographic modeling and selection detection. We summarize their rationales, implementations, and some classical applications. We also propose that some widely-used methods can be improved in both theoretical and practical aspects in near future.

Genomic inference accurately predicts the timing and severity of a recent bottleneck in a nonmodel insect population

The analysis of molecular data from natural populations has allowed researchers to answer diverse ecological questions that were previously intractable. In particular, ecologists are often interested in the demographic history of populations, information that is rarely available from historical records. Methods have been developed to infer demographic parameters from genomic data, but it is not well understood how inferred parameters compare to true population history or depend on aspects of experimental design. Here, we present and evaluate a method of SNP discovery using RNA sequencing and demographic inference using the program δaδi, which uses a diffusion approximation to the allele frequency spectrum to fit demographic models. We test these methods in a population of the checkerspot butterfly Euphydryas gillettii. This population was intentionally introduced to Gothic, Colorado in 1977 and has as experienced extreme fluctuations including bottlenecks of fewer than 25 adults, as documented by nearly annual field surveys. Using RNA sequencing of eight individuals from Colorado and eight individuals from a native population in Wyoming, we generate the first genomic resources for this system. While demographic inference is commonly used to examine ancient demography, our study demonstrates that our inexpensive, all-in-one approach to marker discovery and genotyping provides sufficient data to accurately infer the timing of a recent bottleneck. This demographic scenario is relevant for many species of conservation concern, few of which have sequenced genomes. Our results are remarkably insensitive to sample size or number of genomic markers, which has important implications for applying this method to other nonmodel systems.

Genetic basis for spontaneous hybrid genome doubling during allopolyploid speciation of common wheat shown by natural variation analyses of the paternal species

The complex process of allopolyploid speciation includes various mechanisms ranging from species crosses and hybrid genome doubling to genome alterations and the establishment of new allopolyploids as persisting natural entities. Currently, little is known about the genetic mechanisms that underlie hybrid genome doubling, despite the fact that natural allopolyploid formation is highly dependent on this phenomenon. We examined the genetic basis for the spontaneous genome doubling of triploid F1 hybrids between the direct ancestors of allohexaploid common wheat (Triticum aestivum L., AABBDD genome), namely Triticumturgidum L. (AABB genome) and Aegilopstauschii Coss. (DD genome). An Ae. tauschii intraspecific lineage that is closely related to the D genome of common wheat was identified by population-based analysis. Two representative accessions, one that produces a high-genome-doubling-frequency hybrid when crossed with a T. turgidum cultivar and the other that produces a low-genome-doubling-frequency hybrid with the same cultivar, were chosen from that lineage for further analyses. A series of investigations including fertility analysis, immunostaining, and quantitative trait locus (QTL) analysis showed that (1) production of functional unreduced gametes through nonreductional meiosis is an early step key to successful hybrid genome doubling, (2) first division restitution is one of the cytological mechanisms that cause meiotic nonreduction during the production of functional male unreduced gametes, and (3) six QTLs in the Ae. tauschii genome, most of which likely regulate nonreductional meiosis and its subsequent gamete production processes, are involved in hybrid genome doubling. Interlineage comparisons of Ae. tauschii's ability to cause hybrid genome doubling suggested an evolutionary model for the natural variation pattern of the trait in which non-deleterious mutations in six QTLs may have important roles. The findings of this study demonstrated that the genetic mechanisms for hybrid genome doubling could be studied based on the intrinsic natural variation that exists in the parental species.

Continent-wide decoupling of Y-chromosomal genetic variation from language and geography in native South Americans

Numerous studies of human populations in Europe and Asia have revealed a concordance between their extant genetic structure and the prevailing regional pattern of geography and language. For native South Americans, however, such evidence has been lacking so far. Therefore, we examined the relationship between Y-chromosomal genotype on the one hand, and male geographic origin and linguistic affiliation on the other, in the largest study of South American natives to date in terms of sampled individuals and populations. A total of 1,011 individuals, representing 50 tribal populations from 81 settlements, were genotyped for up to 17 short tandem repeat (STR) markers and 16 single nucleotide polymorphisms (Y-SNPs), the latter resolving phylogenetic lineages Q and C. Virtually no structure became apparent for the extant Y-chromosomal genetic variation of South American males that could sensibly be related to their inter-tribal geographic and linguistic relationships. This continent-wide decoupling is consistent with a rapid peopling of the continent followed by long periods of isolation in small groups. Furthermore, for the first time, we identified a distinct geographical cluster of Y-SNP lineages C-M217 (C3*) in South America. Such haplotypes are virtually absent from North and Central America, but occur at high frequency in Asia. Together with the locally confined Y-STR autocorrelation observed in our study as a whole, the available data therefore suggest a late introduction of C3* into South America no more than 6,000 years ago, perhaps via coastal or trans-Pacific routes. Extensive simulations revealed that the observed lack of haplogroup C3* among extant North and Central American natives is only compatible with low levels of migration between the ancestor populations of C3* carriers and non-carriers. In summary, our data highlight the fact that a pronounced correlation between genetic and geographic/cultural structure can only be expected under very specific conditions, most of which are likely not to have been met by the ancestors of native South Americans.

In the largest population genetic study of South Americans to date, we analyzed the Y-chromosomal makeup of more than 1,000 male natives. We found that the male-specific genetic variation of Native Americans lacks any clear structure that could sensibly be related to their geographic and/or linguistic relationships. This finding is consistent with a rapid initial peopling of South America, followed by long periods of isolation in small tribal groups. The observed continent-wide decoupling of geography, spoken language, and genetics contrasts strikingly with previous reports of such correlation from many parts of Europe and Asia. Moreover, we identified a cluster of Native American founding lineages of Y chromosomes, called C-M217 (C3*), within a restricted area of Ecuador in North-Western South America. The same haplogroup occurs at high frequency in Central, East, and North East Asia, but is virtually absent from North (except Alaska) and Central America. Possible scenarios for the introduction of C-M217 (C3*) into Ecuador may thus include a coastal or trans-Pacific route, an idea also supported by occasional archeological evidence and the recent coalescence of the C3* haplotypes, estimated from our data to have occurred some 6,000 years ago.

Approximate Bayesian computation

Approximate Bayesian computation (ABC) constitutes a class of computational methods rooted in Bayesian statistics. In all model-based statistical inference, the likelihood function is of central importance, since it expresses the probability of the observed data under a particular statistical model, and thus quantifies the support data lend to particular values of parameters and to choices among different models. For simple models, an analytical formula for the likelihood function can typically be derived. However, for more complex models, an analytical formula might be elusive or the likelihood function might be computationally very costly to evaluate. ABC methods bypass the evaluation of the likelihood function. In this way, ABC methods widen the realm of models for which statistical inference can be considered. ABC methods are mathematically well-founded, but they inevitably make assumptions and approximations whose impact needs to be carefully assessed. Furthermore, the wider application domain of ABC exacerbates the challenges of parameter estimation and model selection. ABC has rapidly gained popularity over the last years and in particular for the analysis of complex problems arising in biological sciences (e.g., in population genetics, ecology, epidemiology, and systems biology).

The influence of the arid Andean high plateau on the phylogeography and population genetics of guanaco (Lama guanicoe) in South America

A comprehensive study of the phylogeography and population genetics of the largest wild artiodactyl in the arid and cold-temperate South American environments, the guanaco (Lama guanicoe) was conducted. Patterns of molecular genetic structure were described using 514 bp of mtDNA sequence and 14 biparentally inherited microsatellite markers from 314 samples. These individuals originated from 17 localities throughout the current distribution across Peru, Bolivia, Argentina and Chile. This confirmed well-defined genetic differentiation and subspecies designation of populations geographically separated to the northwest (L. g. cacsilensis) and southeast (L. g. guanicoe) of the central Andes plateau. However, these populations are not completely isolated, as shown by admixture prevalent throughout a limited contact zone, and a strong signal of expansion from north to south in the beginning of the Holocene. Microsatellite analyses differentiated three northwestern and 4-5 southeastern populations, suggesting patterns of genetic contact among these populations. Possible genetic refuges were identified, as were source-sink patterns of gene flow at historical and recent time scales. Conservation and management of guanaco should be implemented with an understanding of these local population dynamics while also considering the preservation of broader adaptive variation and evolutionary processes.

Signature of a pre-human population decline in the critically endangered Reunion Island endemic forest bird Coracina newtoni

The exceptional biodiversity of Reunion Island is threatened by anthropogenic landscape changes that took place during the 350 years of human colonization. During this period the human population size increased dramatically from 250 to 800,000. The arrival of humans together with the development of agriculture, invasive species such as rats and cats, and deforestation has lead to the extinction of more than half of the original vertebrate species of the island. For the remaining species, significant work is being carried out to identify threats and conservation status, but little genetic work has been carried on some of the most endangered species. In the last decade theoretical studies have shown the ability of neutral genetic markers to infer the demographic history of endangered species and identify and date past population size changes (expansions or bottlenecks). In this study we provide the first genetic data on the critically endangered species the Reunion cuckoo-shrike Coracina newtoni. The Reunion cuckoo-shrike is a rare endemic forest bird surviving in a restricted 12-km(2) area of forested uplands and mountains. The total known population consists of less than one hundred individuals out of which 45 were genotyped using seventeen polymorphic microsatellite loci. We found a limited level of genetic variability and weak population structure, probably due to the limited geographic distribution. Using Bayesian methods, we identified a strong decline in population size during the Holocene, most likely caused by an ancient climatic or volcanic event around 5000 years ago. This result was surprising as it appeared in apparent contradiction with the accepted theory of recent population collapse due to deforestation and predator introduction. These results suggest that new methods allowing for more complex demographic models are necessary to reconstruct the demographic history of populations.

The impact of recent events on human genetic diversity

The historical record tells us stories of migrations, population expansions and colonization events in the last few thousand years, but what was their demographic impact? Genetics can throw light on this issue, and has mostly done so through the maternally inherited mitochondrial DNA (mtDNA) and the male-specific Y chromosome. However, there are a number of problems, including marker ascertainment bias, possible influences of natural selection, and the obscuring layers of the palimpsest of historical and prehistorical events. Y-chromosomal lineages are particularly affected by genetic drift, which can be accentuated by recent social selection. A diversity of approaches to expansions in Europe is yielding insights into the histories of Phoenicians, Roma, Anglo-Saxons and Vikings, and new methods for producing and analysing genome-wide data hold much promise. The field would benefit from more consensus on appropriate methods, and better communication between geneticists and experts in other disciplines, such as history, archaeology and linguistics.

Recombination rate variation and speciation: theoretical predictions and empirical results from rabbits and mice

Recently diverged taxa may continue to exchange genes. A number of models of speciation with gene flow propose that the frequency of gene exchange will be lower in genomic regions of low recombination and that these regions will therefore be more differentiated. However, several population-genetic models that focus on selection at linked sites also predict greater differentiation in regions of low recombination simply as a result of faster sorting of ancestral alleles even in the absence of gene flow. Moreover, identifying the actual amount of gene flow from patterns of genetic variation is tricky, because both ancestral polymorphism and migration lead to shared variation between recently diverged taxa. New analytic methods have been developed to help distinguish ancestral polymorphism from migration. Along with a growing number of datasets of multi-locus DNA sequence variation, these methods have spawned a renewed interest in speciation models with gene flow. Here, we review both speciation and population-genetic models that make explicit predictions about how the rate of recombination influences patterns of genetic variation within and between species. We then compare those predictions with empirical data of DNA sequence variation in rabbits and mice. We find strong support for the prediction that genomic regions experiencing low levels of recombination are more differentiated. In most cases, reduced gene flow appears to contribute to the pattern, although disentangling the relative contribution of reduced gene flow and selection at linked sites remains a challenge. We suggest fruitful areas of research that might help distinguish between different models.

Population genetics and objectivity in species diagnosis

Species as evolutionary lineages are expected to show greater evolutionary independence from one another than are populations within species. Two measures of evolutionary independence that stem from the study of isolation-with-migration models, one reflecting the amount of gene exchange and one reflecting the time of separation, were drawn from the literature for a large number of pairs of closely related species and pairs of populations within species. Both measures, for gene flow and time, showed broadly overlapping distributions for pairs of species and for pairs of populations within species. Species on average show more time and less gene flow than populations, but the similarity of the distributions argues against there being a qualitative difference associated with species status, as compared to populations. The two measures of evolutionary independence were similarly correlated with F(ST) estimates, which in turn also showed similar distributions for species comparisons relative to population comparisons. The measures of gene flow and separation time were examined for the capacity to discriminate intraspecific differences from interspecific differences. If used together, the two measures could be used to develop an objective (in the sense of being repeatable) measure for species diagnosis.

Lack of confidence in approximate Bayesian computation model choice

Approximate Bayesian computation (ABC) have become an essential tool for the analysis of complex stochastic models. Grelaud et al. [(2009) Bayesian Anal 3:427-442] advocated the use of ABC for model choice in the specific case of Gibbs random fields, relying on an intermodel sufficiency property to show that the approximation was legitimate. We implemented ABC model choice in a wide range of phylogenetic models in the Do It Yourself-ABC (DIY-ABC) software [Cornuet et al. (2008) Bioinformatics 24:2713-2719]. We now present arguments as to why the theoretical arguments for ABC model choice are missing, because the algorithm involves an unknown loss of information induced by the use of insufficient summary statistics. The approximation error of the posterior probabilities of the models under comparison may thus be unrelated with the computational effort spent in running an ABC algorithm. We then conclude that additional empirical verifications of the performances of the ABC procedure as those available in DIY-ABC are necessary to conduct model choice.

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.

MTML-msBayes: approximate Bayesian comparative phylogeographic inference from multiple taxa and multiple loci with rate heterogeneity

Background

MTML-msBayes uses hierarchical approximate Bayesian computation (HABC) under a coalescent model to infer temporal patterns of divergence and gene flow across codistributed taxon-pairs. Under a model of multiple codistributed taxa that diverge into taxon-pairs with subsequent gene flow or isolation, one can estimate hyper-parameters that quantify the mean and variability in divergence times or test models of migration and isolation. The software uses multi-locus DNA sequence data collected from multiple taxon-pairs and allows variation across taxa in demographic parameters as well as heterogeneity in DNA mutation rates across loci. The method also allows a flexible sampling scheme: different numbers of loci of varying length can be sampled from different taxon-pairs.

Results

Simulation tests reveal increasing power with increasing numbers of loci when attempting to distinguish temporal congruence from incongruence in divergence times across taxon-pairs. These results are robust to DNA mutation rate heterogeneity. Estimating mean divergence times and testing simultaneous divergence was less accurate with migration, but improved if one specified the correct migration model. Simulation validation tests demonstrated that one can detect the correct migration or isolation model with high probability, and that this HABC model testing procedure was greatly improved by incorporating a summary statistic originally developed for this task (Wakeley's Ψ_W). The method is applied to an empirical data set of three Australian avian taxon-pairs and a result of simultaneous divergence with some subsequent gene flow is inferred.

Conclusions

To retain flexibility and compatibility with existing bioinformatics tools, MTML-msBayes is a pipeline software package consisting of Perl, C and R programs that are executed via the command line. Source code and binaries are available for download at http://msbayes.sourceforge.net/ under an open source license (GNU Public License).

Insights into the demographic history of African Pygmies from complete mitochondrial genomes

Pygmy populations are among the few hunter-gatherers currently living in sub-Saharan Africa and are mainly represented by two groups, Eastern and Western, according to their current geographical distribution. They are scattered across the Central African belt and surrounded by Bantu-speaking farmers, with whom they have complex social and economic interactions. To investigate the demographic history of Pygmy groups, a population approach was applied to the analysis of 205 complete mitochondrial DNA (mtDNA) sequences from ten central African populations. No sharing of maternal lineages was observed between the two Pygmy groups, with haplogroup L1c being characteristic of the Western group but most of Eastern Pygmy lineages falling into subclades of L0a, L2a, and L5. Demographic inferences based on Bayesian coalescent simulations point to an early split among the maternal ancestors of Pygmies and those of Bantu-speaking farmers (∼ 70,000 years ago [ya]). Evidence for population growth in the ancestors of Bantu-speaking farmers has been observed, starting ∼ 65,000 ya, well before the diffusion of Bantu languages. Subsequently, the effective population size of the ancestors of Pygmies remained constant over time and ∼ 27,000 ya, coincident with the Last Glacial Maximum, Eastern and Western Pygmies diverged, with evidence of subsequent migration only among the Western group and the Bantu-speaking farmers. Western Pygmies show signs of a recent bottleneck 4,000-650 ya, coincident with the diffusion of Bantu languages, whereas Eastern Pygmies seem to have experienced a more ancient decrease in population size (20,000-4,000 ya). In conclusion, the results of this first attempt at analyzing complete mtDNA sequences at the population level in sub-Saharan Africa not only support previous findings but also offer new insights into the demographic history of Pygmy populations, shedding new light on the ancient peopling of the African continent.