Joint Site Frequency Spectrum Research Articles

Fast and accurate estimation of multidimensional site frequency spectra from low-coverage high-throughput sequencing data.

BackgroundThe site frequency spectrum summarizes the distribution of allele frequencies throughout the genome, and it is widely used as a summary statistic to infer demographic parameters and to detect signals of natural selection. The use of high-throughput low-coverage DNA sequencing data can lead to biased estimates of the site frequency spectrum due to high levels of uncertainty in genotyping.ResultsHere we design and implement a method to efficiently and accurately estimate the multidimensional joint site frequency spectrum for large numbers of haploid or diploid individuals across an arbitrary number of populations, using low-coverage sequencing data. The method maximizes a likelihood function that represents the probability of the sequencing data observed given a multidimensional site frequency spectrum using genotype likelihoods. Notably, it uses an advanced binning heuristic paired with an accelerated expectation-maximization algorithm for a fast and memory-efficient computation, and can generate both unfolded and folded spectra and bootstrapped replicates for haploid and diploid genomes. On the basis of extensive simulations, we show that the new method requires remarkably less storage and is faster than previous implementations whilst retaining the same accuracy. When applied to low-coverage sequencing data from the fungal pathogen Neonectria neomacrospora, results recapitulate the patterns of population differentiation generated using the original high-coverage data.ConclusionThe new implementation allows for accurate estimation of population genetic parameters from arbitrarily large, low-coverage datasets, thus facilitating cost-effective sequencing experiments in model and non-model organisms.

A dynamic ancestral graph model and GPU-based simulation of a community based on metagenomic sampling.

In this paper, we present an ancestral graph model of the evolution of a guild in an ecological community. The model is based on a metagenomic sampling design in that a random sample is taken at the community, as opposed the taxon, level and species are discovered by genetic sequencing. The specific implementation of the model envisions an ecological guild that was founded by colonization at some point in the past that then potentially undergoes diversification by natural selection. Within the graph, species emerge and evolve through the diversification process and their densities in the graph are dynamic and governed by both ecological drift and random genetic drift, as well as differential viability. We employ the 3% sequence divergence rule at a marker locus to identify operational taxonomic units. We then explore approaches to see whether there are indirect signals of the diversification process, including population genetic and ecological approaches. In terms of population genetics, we study the joint site frequency spectrum of OTUs, as well its associated statistics. In terms of ecology, we study the species (or OTU) abundance distribution. For both, we observe deviations from neutrality, which indicates that there may be signals of diversifying selection in metagenomic studies under certain conditions. The model is available as a GPU-based computer program in C/C++ and using OpenCL, with the long-term goal of adding functionality iteratively to model large-scale eco-evolutionary processes for metagenomic data.

Evidence for the Pleistocene Arc Hypothesis from genome-wide SNPs in a Neotropical dry forest specialist, the Rufous-fronted Thornbird (Furnariidae: Phacellodomus rufifrons).

South American dry forests have a complex and poorly understood biogeographic history. Based on the fragmented distribution of many Neotropical dry forest species, it has been suggested that this biome was more widely distributed and contiguous under drier climate conditions in the Pleistocene. To test this scenario, known as the Pleistocene Arc Hypothesis, we studied the phylogeography of the Rufous-fronted Thornbird (Phacellodomus rufifrons), a widespread dry forest bird with a disjunct distribution closely matching that of the biome itself. We sequenced mtDNA and used ddRADseq to sample 7,167 genome-wide single-nucleotide polymorphisms from 74 P.rufifrons individuals across its range. We found low genetic differentiation over two prominent geographic breaks - particularly across a 1,000km gap between populations in Bolivia and Northern Peru. Using demographic analyses of the joint site frequency spectrum, we found evidence of recent divergence without subsequent gene flow across those breaks. By contrast, parapatric morphologically distinct populations in northeastern Brazil show high genetic divergence with evidence of recent gene flow. These results, in combination with our paleoclimate species distribution modelling, support the idea that currently disjunct patches of dry forest were more connected in the recent past, probably during the Middle and Late Pleistocene. This notion fits the major predictions of the Pleistocene Arc Hypothesis and illustrates the importance of comprehensive genomic and geographic sampling for examining biogeographic and evolutionary questions in complex ecosystems like Neotropical dry forests.

Comparative phylogeographic inference with genome‐wide data from aggregated population pairs

Comparing divergences across multiple sister population pairs has been a focus in phylogeography since its inception. Initial approaches used organelle genetic data and involved qualitative comparisons of phylogenetic patterns to evaluate hypotheses of shared and variable evolutionary responses. This endeavor has progressed with coalescent model-based statistical techniques and advances in next-generation sequencing, yet there remains a need for methods that can exploit aggregated genomic-scale data within a unified analytical framework. To this end, we introduce the aggregate joint site frequency spectrum (ajSFS) by validating its use within a hierarchical Bayesian framework through several in silico experiments. Subsequently, we applied our method against two published restriction site-associated DNA marker datasets consisting of eight local replicates of a lamprey species pair and six co-distributed passerine taxon pairs, respectively, with the aim of inferring variability in co-divergence and co-migration histories. We found that the lamprey population pairs exhibited temporal synchrony in both co-divergence and collective secondary contact times, yet an idiosyncratic pattern in secondary migration intensities. In contrast, the bird population pairs displayed thoroughly asynchronous co-divergence histories. Our results demonstrate that the ajSFS can be exploited for complex and flexible co-demographic inference, opening up new possibilities for comparative phylogeography and population genomic studies.

McSwan: A joint site frequency spectrum method to detect and date selective sweeps across multiple population genomes.

Inferring the mode and tempo of natural selection helps further our understanding of adaptation to past environmental changes. Here, we introduce McSwan, a method to detect and date past and recent natural selection events in the case of a hard sweep. The method is based on the comparison of site frequency spectra obtained under various demographic models that include selection. McSwan demonstrated high power (high sensitivity and specificity) in capturing hard selective sweep events without requiring haplotype phasing. It performed slightly better than SweeD when the recent effective population size was low and the genomic region was small. We then applied our method to a European (CEU) and an African (LWK) human re-sequencing data set. Most hard sweeps were detected in the CEU population (96%). Moreover, hard sweeps in the African population were estimated to have occurred further back in time (mode: 43,625years BP) compared to those of Europeans (mode: 24,850years BP). Most of the estimated ages of hard sweeps in Europeans were associated with the Last Glacial Maximum and were enriched in immunity-associated genes.

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

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

Evolutionary processes and cellular functions underlying divergence in Alexandrium minutum.

Understanding divergence in the highly dispersive and seemingly homogeneous pelagic environment for organisms living as free drifters in the water column remains a challenge. Here, we analysed the transcriptome-wide mRNA sequences, as well as the morphology of 18 strains of Alexandrium minutum, a dinoflagellate responsible for harmful algal blooms worldwide, to investigate the functional bases of a divergence event. Analysis of the joint site frequency spectrum (JSFS) pointed towards an ancestral divergence in complete isolations followed by a secondary contact resulting in gene flow between the two diverging groups, but heterogeneous across sites. The sites displaying fixed SNPs were associated with a highly restricted gene flow and a strong overrepresentation of nonsynonymous polymorphism, suggesting the importance of selective pressures as drivers of the divergence. The most divergent transcripts were homologs to genes involved in calcium/potassium fluxes across the membrane, calcium transduction signal and saxitoxin production. The implication of these results in terms of ecological divergence and build-up of reproductive isolation is discussed. Dinoflagellates are especially difficult to study in the field at the ecological level due to their small size and the dynamic nature of their natural environment, but also at the genomic level due to their huge and complex genome and the absence of closely related model organism. This study illustrates the possibility to identify the traits of primary importance in ecology and evolution starting from high-throughput sequencing data, even for such organisms.

Genetic variability, local selection and demographic history: genomic evidence of evolving towards allopatric speciation in Asian seabass.

Genomewide analysis of genetic divergence is critically important in understanding the genetic processes of allopatric speciation. We sequenced RAD tags of 131 Asian seabass individuals of six populations from South-East Asia and Australia/Papua New Guinea. Using 32433 SNPs, we examined the genetic diversity and patterns of population differentiation across all the populations. We found significant evidence of genetic heterogeneity between South-East Asian and Australian/Papua New Guinean populations. The Australian/Papua New Guinean populations showed a rather lower level of genetic diversity. FST and principal components analysis revealed striking divergence between South-East Asian and Australian/Papua New Guinean populations. Interestingly, no evidence of contemporary gene flow was observed. The demographic history was further tested based on the folded joint site frequency spectrum. The scenario of ancient migration with historical population size changes was suggested to be the best fit model to explain the genetic divergence of Asian seabass between South-East Asia and Australia/Papua New Guinea. This scenario also revealed that Australian/Papua New Guinean populations were founded by ancestors from South-East Asia during mid-Pleistocene and were completely isolated from the ancestral population after the last glacial retreat. We also detected footprints of local selection, which might be related to differential ecological adaptation. The ancient gene flow was examined and deemed likely insufficient to counteract the genetic differentiation caused by genetic drift. The observed genomic pattern of divergence conflicted with the 'genomic islands' scenario. Altogether, Asian seabass have likely been evolving towards allopatric speciation since the split from the ancestral population during mid-Pleistocene.

Eco‐morphological differentiation in Lake Magadi tilapia, an extremophile cichlid fish living in hot, alkaline and hypersaline lakes in East Africa

Ecological diversification through divergent selection is thought to be a major force during the process of adaptive radiations. However, the large sizes and complexity of most radiations such as those of the cichlids in the African Great Lakes make it impossible to infer the exact evolutionary history of any population divergence event. The genus Alcolapia, a small cichlid lineage endemic to Lakes Magadi and Natron in East Africa, exhibits phenotypes similar to some of those found in cichlids of the radiations of the African Great Lakes. The simplicity within Alcolapia makes it an excellent model system to investigate ecological diversification and speciation. We used an integrated approach including population genomics based on RAD-seq data, geometric morphometrics and stable isotope analyses to investigate the eco-morphological diversification of tilapia in Lake Magadi and its satellite lake Little Magadi. Additionally, we reconstructed the demographic history of the species using coalescent simulations based on the joint site frequency spectrum. The population in Little Magadi has a characteristically upturned mouth--possibly an adaptation to feeding on prey from the water surface. Eco-morphological differences between populations within Lake Magadi are more subtle, but are consistent with known ecological differences between its lagoons such as high concentrations of nitrogen attributable to extensive guano deposits in Rest of Magadi relative to Fish Springs Lagoon. All populations diverged simultaneously only about 1100 generations ago. Differences in levels of gene flow between populations and the effective population sizes have likely resulted in the inferred heterogeneous patterns of genome-wide differentiation.

Evaluating the ability of the pairwise joint site frequency spectrum to co-estimate selection and demography.

The ability to infer the parameters of positive selection from genomic data has many important implications, from identifying drug-resistance mutations in viruses to increasing crop yield by genetically integrating favorable alleles. Although it has been well-described that selection and demography may result in similar patterns of diversity, the ability to jointly estimate these two processes has remained elusive. Here, we use simulation to explore the utility of the joint site frequency spectrum to estimate selection and demography simultaneously, including developing an extension of the previously proposed Jaatha program (Mathew et al., 2013). We evaluate both complete and incomplete selective sweeps under an isolation-with-migration model with and without population size change (both population growth and bottlenecks). Results suggest that while it may not be possible to precisely estimate the strength of selection, it is possible to infer the presence of selection while estimating accurate demographic parameters. We further demonstrate that the common assumption of selective neutrality when estimating demographic models may lead to severe biases. Finally, we apply the approach we have developed to better characterize the within-host demographic and selective history of human cytomegalovirus (HCMV) infection using published next generation sequencing data.

The site frequency spectrum of dispensable genes

The differences between DNA-sequences within a population are the basis to infer the ancestral relationship of the individuals. Within the classical infinitely many sites model, it is possible to estimate the mutation rate based on the site frequency spectrum, which is comprised by the numbers C1,…,Cn−1 where n is the sample size and Cs is the number of site mutations (Single Nucleotide Polymorphisms, SNPs) which are seen in s genomes. Classical results can be used to compare the observed site frequency spectrum with its neutral expectation, E[Cs]=θ2/s, where θ2 is the scaled site mutation rate. In this paper, we will relax the assumption of the infinitely many sites model that all individuals only carry homologous genetic material. Especially, it is today well-known that bacterial genomes have the ability to gain and lose genes, such that every single genome is a mosaic of genes, and genes are present and absent in a random fashion, giving rise to the dispensable genome. While this presence and absence has been modeled under neutral evolution within the infinitely many genes model in Baumdicker et al. (2010), we link presence and absence of genes with the numbers of site mutations seen within each gene. In this work we derive a formula for the expectation of the joint gene and site frequency spectrum, denoted by Gk,s, the number of mutated sites occurring in exactly s gene sequences, while the corresponding gene is present in exactly k individuals. We show that standard estimators of θ2 for dispensable genes are biased and that the site frequency spectrum for dispensable genes differs from the classical result.

Unlocking the vault: next‐generation museum population genomics

Natural history museum collections provide unique resources for understanding how species respond to environmental change, including the abrupt, anthropogenic climate change of the past century. Ideally, researchers would conduct genome-scale screening of museum specimens to explore the evolutionary consequences of environmental changes, but to date such analyses have been severely limited by the numerous challenges of working with the highly degraded DNA typical of historic samples. Here, we circumvent these challenges by using custom, multiplexed, exon capture to enrich and sequence ~11,000 exons (~4 Mb) from early 20th-century museum skins. We used this approach to test for changes in genomic diversity accompanying a climate-related range retraction in the alpine chipmunks (Tamias alpinus) in the high Sierra Nevada area of California, USA. We developed robust bioinformatic pipelines that rigorously detect and filter out base misincorporations in DNA derived from skins, most of which likely resulted from postmortem damage. Furthermore, to accommodate genotyping uncertainties associated with low-medium coverage data, we applied a recently developed probabilistic method to call single-nucleotide polymorphisms and estimate allele frequencies and the joint site frequency spectrum. Our results show increased genetic subdivision following range retraction, but no change in overall genetic diversity at either nonsynonymous or synonymous sites. This case study showcases the advantages of integrating emerging genomic and statistical tools in museum collection-based population genomic applications. Such technical advances greatly enhance the value of museum collections, even where a pre-existing reference is lacking and points to a broad range of potential applications in evolutionary and conservation biology.

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.