Joint Allele Frequency Spectrum Research Articles

Rapid vertebrate speciation via isolation, bottlenecks, and drift

Speciation is often driven by selective processes like those associated with viability, mate choice, or local adaptation, and "speciation genes" have been identified in many eukaryotic lineages. In contrast, neutral processes are rarely considered as the primary drivers of speciation, especially over short evolutionary timeframes. Here, we describe a rapid vertebrate speciation event driven primarily by genetic drift. The White Sands pupfish (Cyprinodon tularosa) is endemic to New Mexico's Tularosa Basin where the species is currently managed as two Evolutionarily significant units (ESUs) and is of international conservation concern (Endangered). Whole-genome resequencing data from each ESU showed remarkably high and uniform levels of differentiation across the entire genome (global FST ≈ 0.40). Despite inhabiting ecologically dissimilar springs and streams, our whole-genome analysis revealed no discrete islands of divergence indicative of strong selection, even when we focused on an array of candidate genes. Demographic modeling of the joint allele frequency spectrum indicates the two ESUs split only ~4 to 5 kya and that both ESUs have undergone major bottlenecks within the last 2.5 millennia. Our results indicate the genome-wide disparities between the two ESUs are not driven by divergent selection but by neutral drift due to small population sizes, geographic isolation, and repeated bottlenecks. While rapid speciation is often driven by natural or sexual selection, here we show that isolation and drift have led to speciation within a few thousand generations. We discuss these evolutionary insights in light of the conservation management challenges they pose.

Inferring Genome-Wide Correlations of Mutation Fitness Effects between Populations.

The effect of a mutation on fitness may differ between populations depending on environmental and genetic context, but little is known about the factors that underlie such differences. To quantify genome-wide correlations in mutation fitness effects, we developed a novel concept called a joint distribution of fitness effects (DFE) between populations. We then proposed a new statistic w to measure the DFE correlation between populations. Using simulation, we showed that inferring the DFE correlation from the joint allele frequency spectrum is statistically precise and robust. Using population genomic data, we inferred DFE correlations of populations in humans, Drosophila melanogaster, and wild tomatoes. In these species, we found that the overall correlation of the joint DFE was inversely related to genetic differentiation. In humans and D. melanogaster, deleterious mutations had a lower DFE correlation than tolerated mutations, indicating a complex joint DFE. Altogether, the DFE correlation can be reliably inferred, and it offers extensive insight into the genetics of population divergence.

Demographic Inference of Divergence and Gene Exchange Between Castanopsis fabri and Castanopsis lamontii.

The cytoplasmic genome of one species may be replaced by that of another species without leaving any trace of past hybridization in its nuclear genome, which can thus confuse the inference of genealogical relationship and evolutionary history of many congeneric species. In this study, we used sequence variations of chloroplast DNA and restriction site-associated DNA to investigate gene exchange between Castanopsis fabri and Castanopsis lamontii, and to infer the divergence history of the two species by comparing different divergence models based on the joint allele frequency spectrum. We evaluated climatic niche similarity of the two species using climatic variables across their entire distribution range in subtropical China. Clear genetic differentiation was revealed between C. fabri and C. lamontii, and gene exchange between the two species was discovered as a consequence of secondary contact. The gene exchange rates were variable across the genome. Gene exchange could allow C. fabri to widen its habitat through pollen swamping and broaden its climatic niche, and the chloroplast genome of C. lamontii is captured by C. fabri during this process. These results further our understanding of the timing and contribution of gene exchange to species divergence in forests.

Speciation history of European (Anguilla anguilla) and American eel (A.rostrata), analysed using genomic data.

Speciation in the ocean could differ from terrestrial environments due to fewer barriers to gene flow. Hence, sympatric speciation might be common, with American and European eel being candidates for exemplifying this. They show disjunct continental distributions on both sides of the Atlantic, but spawn in overlapping regions of the Sargasso Sea from where juveniles are advected to North American, European and North African coasts. Hybridization and introgression are known to occur, with hybrids almost exclusively observed in Iceland. Different speciation scenarios have been suggested, involving either vicariance or sympatric ecological speciation. Using RAD sequencing and whole-genome sequencing data from parental species and F1 hybrids, we analysed speciation history based on the joint allele frequency spectrum (JAFS) and pairwise sequentially Markovian coalescent (PSMC) plots. JAFS supported a model involving a split without gene flow 150,000-160,000 generations ago, followed by secondary contact 87,000-92,000 generations ago, with 64% of the genome experiencing restricted gene flow. This supports vicariance rather than sympatric speciation, likely associated with Pleistocene glaciation cycles and ocean current changes. Whole-genome PSMC analysis of F1 hybrids from Iceland suggested divergence 200,000 generations ago and indicated subsequent gene flow rather than strict isolation. Finally, simulations showed that results from both approaches (JAFS and PSMC) were congruent. Hence, there is strong evidence against sympatric speciation in North Atlantic eels. These results reiterate the need for careful consideration of cases of possible sympatric speciation, as even in seemingly barrier-free oceanic environments palaeoceanographic factors may have promoted vicariance and allopatric speciation.

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

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

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

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

Exact Calculation of the Joint Allele Frequency Spectrum for Isolation with Migration Models.

Population genomic datasets collected over the past decade have spurred interest in developing methods that can utilize massive numbers of loci for inference of demographic and selective histories of populations. The allele frequency spectrum (AFS) provides a convenient statistic for such analysis, and, accordingly, much attention has been paid to predicting theoretical expectations of the AFS under a number of different models. However, to date, exact solutions for the joint AFS of two or more populations under models of migration and divergence have not been found. Here, we present a novel Markov chain representation of the coalescent on the state space of the joint AFS that allows for rapid, exact calculation of the joint AFS under isolation with migration (IM) models. In turn, we show how our Markov chain method, in the context of composite likelihood estimation, can be used for accurate inference of parameters of the IM model using SNP data. Lastly, we apply our method to recent whole genome datasets from African Drosophila melanogaster.

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

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

Whole-genome sequence analyses of Western Central African Pygmy hunter-gatherers reveal a complex demographic history and identify candidate genes under positive natural selection.

African Pygmies practicing a mobile hunter-gatherer lifestyle are phenotypically and genetically diverged from other anatomically modern humans, and they likely experienced strong selective pressures due to their unique lifestyle in the Central African rainforest. To identify genomic targets of adaptation, we sequenced the genomes of four Biaka Pygmies from the Central African Republic and jointly analyzed these data with the genome sequences of three Baka Pygmies from Cameroon and nine Yoruba famers. To account for the complex demographic history of these populations that includes both isolation and gene flow, we fit models using the joint allele frequency spectrum and validated them using independent approaches. Our two best-fit models both suggest ancient divergence between the ancestors of the farmers and Pygmies, 90,000 or 150,000 yr ago. We also find that bidirectional asymmetric gene flow is statistically better supported than a single pulse of unidirectional gene flow from farmers to Pygmies, as previously suggested. We then applied complementary statistics to scan the genome for evidence of selective sweeps and polygenic selection. We found that conventional statistical outlier approaches were biased toward identifying candidates in regions of high mutation or low recombination rate. To avoid this bias, we assigned P-values for candidates using whole-genome simulations incorporating demography and variation in both recombination and mutation rates. We found that genes and gene sets involved in muscle development, bone synthesis, immunity, reproduction, cell signaling and development, and energy metabolism are likely to be targets of positive natural selection in Western African Pygmies or their recent ancestors.

Using Ancient Samples in Projection Analysis.

Projection analysis is a tool that extracts information from the joint allele frequency spectrum to better understand the relationship between two populations. In projection analysis, a test genome is compared to a set of genomes from a reference population. The projection’s shape depends on the historical relationship of the test genome’s population to the reference population. Here, we explore in greater depth the effects on the projection when ancient samples are included in the analysis. First, we conduct a series of simulations in which the ancient sample is directly ancestral to a present-day population (one-population model), or the ancient sample is ancestral to a sister population that diverged before the time of sampling (two-population model). We find that there are characteristic differences between the projections for the one-population and two-population models, which indicate that the projection can be used to determine whether a test genome is directly ancestral to a present-day population or not. Second, we compute projections for several published ancient genomes. We compare two Neanderthals and three ancient human genomes to European, Han Chinese and Yoruba reference panels. We use a previously constructed demographic model and insert these five ancient genomes to assess how well the observed projections are recovered.

Sampling strategies for frequency spectrum-based population genomic inference.

BackgroundThe allele frequency spectrum (AFS) consists of counts of the number of single nucleotide polymorphism (SNP) loci with derived variants present at each given frequency in a sample. Multiple approaches have recently been developed for parameter estimation and calculation of model likelihoods based on the joint AFS from two or more populations. We conducted a simulation study of one of these approaches, implemented in the Python module δaδi, to compare parameter estimation and model selection accuracy given different sample sizes under one- and two-population models.ResultsOur simulations included a variety of demographic models and two parameterizations that differed in the timing of events (divergence or size change). Using a number of SNPs reasonably obtained through next-generation sequencing approaches (10,000 - 50,000), accurate parameter estimates and model selection were possible for models with more ancient demographic events, even given relatively small numbers of sampled individuals. However, for recent events, larger numbers of individuals were required to achieve accuracy and precision in parameter estimates similar to that seen for models with older divergence or population size changes. We quantify i) the uncertainty in model selection, using tools from information theory, and ii) the accuracy and precision of parameter estimates, using the root mean squared error, as a function of the timing of demographic events, sample sizes used in the analysis, and complexity of the simulated models.ConclusionsHere, we illustrate the utility of the genome-wide AFS for estimating demographic history and provide recommendations to guide sampling in population genomics studies that seek to draw inference from the AFS. Our results indicate that larger samples of individuals (and thus larger AFS) provide greater power for model selection and parameter estimation for more recent demographic events.Electronic supplementary materialThe online version of this article (doi:10.1186/s12862-014-0254-4) contains supplementary material, which is available to authorized users.

Sequencing an Ashkenazi reference panel supports population-targeted personal genomics and illuminates Jewish and European origins.

The Ashkenazi Jewish (AJ) population is a genetic isolate close to European and Middle Eastern groups, with genetic diversity patterns conducive to disease mapping. Here we report high-depth sequencing of 128 complete genomes of AJ controls. Compared with European samples, our AJ panel has 47% more novel variants per genome and is eightfold more effective at filtering benign variants out of AJ clinical genomes. Our panel improves imputation accuracy for AJ SNP arrays by 28%, and covers at least one haplotype in ≈67% of any AJ genome with long, identical-by-descent segments. Reconstruction of recent AJ history from such segments confirms a recent bottleneck of merely ≈350 individuals. Modelling of ancient histories for AJ and European populations using their joint allele frequency spectrum determines AJ to be an even admixture of European and likely Middle Eastern origins. We date the split between the two ancestral populations to ≈12–25 Kyr, suggesting a predominantly Near Eastern source for the repopulation of Europe after the Last Glacial Maximum.

Intercoalescence Time Distribution of Incomplete Gene Genealogies in Temporally Varying Populations, and Applications in Population Genetic Inference

Tracing back to a specific time T in the past, the genealogy of a sample of haplotypes may not have reached their common ancestor and may leave m lineages extant. For such an incomplete genealogy truncated at a specific time T in the past, the distribution and expectation of the intercoalescence times conditional on T are derived in an exact form in this paper for populations of deterministically time-varying sizes, specifically, for populations growing exponentially. The derived intercoalescence time distribution can be integrated to the coalescent-based joint allele frequency spectrum (JAFS) theory, and is useful for population genetic inference from large-scale genomic data, without relying on computationally intensive approaches, such as importance sampling and Markov Chain Monte Carlo (MCMC) methods. The inference of several important parameters relying on this derived conditional distribution is demonstrated: quantifying population growth rate and onset time, and estimating the number of ancestral lineages at a specific ancient time. Simulation studies confirm validity of the derivation and statistical efficiency of the methods using the derived intercoalescence time distribution. Two examples of real data are given to show the inference of the population growth rate of a European sample from the NIEHS Environmental Genome Project, and the number of ancient lineages of 31 mitochondrial genomes from Tibetan populations.

The joint allele frequency spectrum of multiple populations: A coalescent theory approach

The allele frequency spectrum is a series of statistics that describe genetic polymorphism, and is commonly used for inferring population genetic parameters and detecting natural selection. Population genetic theory on the allele frequency spectrum for a single population has been well studied using both coalescent theory and diffusion equations. Recently, the theory was extended to the joint allele frequency spectrum (JAFS) for three populations using diffusion equations and was shown to be very useful in inferring human demographic history. In this paper, I show that the JAFS can be analytically derived with coalescent theory for a basic model of two isolated populations and then extended to multiple populations and various complex scenarios, such as those involving population growth and bottleneck, migration, and positive selection. Simulation study is used to demonstrate the accuracy and applicability of the theoretical model. The coalescent theory-based approach for the JAFS can characterize the demographic history with comprehensive statistical models as the diffusion approach does, and in addition gains several novel advantages: the computational complexity of calculating the JAFS with coalescent theory is reduced, and thus it is feasible to analytically obtain the JAFS for multiple populations; the hitchhiking effect can be efficiently modeled in coalescent theory, enabling the development of methodologies for detecting selection via multi-population polymorphism data. As an alternative to the diffusion approximation approach, the coalescent theory for the JAFS also provides a foundation for population genetic inference with the advent of large-scale genomic polymorphism data.

The Joint Allele-Frequency Spectrum in Closely Related Species

We develop the theory for computing the joint frequency spectra of alleles in two closely related species. We allow for arbitrary population growth in both species after they had a common ancestor. We focus on the case in which a single chromosome is sequenced from one of the species. We use classical diffusion theory to show that, if the ancestral species was at equilibrium under mutation and drift and a chromosome from one of the descendant species carries the derived allele, the frequency spectrum in the other species is uniform, independently of the demographic history of both species. We also predict the expected densities of segregating and fixed sites when the chromosome from the other species carries the ancestral allele. We compare the predictions of our model with the site-frequency spectra of SNPs in the four HapMap populations of humans when the nucleotide present in the Neanderthal DNA sequence is ancestral or derived, using the chimp genome as the outgroup.