A community-maintained standard library of population genetic models

The explosion in population genomic data demands ever more complex modes of analysis, and increasingly, these analyses depend on sophisticated simulations. Recent advances in population genetic simulation have made it possible to simulate large and complex models, but specifying such models for a particular simulation engine remains a difficult and error-prone task. Computational genetics researchers currently re-implement simulation models independently, leading to inconsistency and duplication of effort. This situation presents a major barrier to empirical researchers seeking to use simulations for power analyses of upcoming studies or sanity checks on existing genomic data. Population genetics, as a field, also lacks standard benchmarks by which new tools for inference might be measured. Here, we describe a new resource, stdpopsim, that attempts to rectify this situation. Stdpopsim is a community-driven open source project, which provides easy access to a growing catalog of published simulation models from a range of organisms and supports multiple simulation engine backends. This resource is available as a well-documented python library with a simple command-line interface. We share some examples demonstrating how stdpopsim can be used to systematically compare demographic inference methods, and we encourage a broader community of developers to contribute to this growing resource.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Genome sequencing highlights the dynamic early history of dogs

To identify genetic changes underlying dog domestication and reconstruct their early evolutionary history, we generated high-quality genome sequences from three gray wolves, one from each of the three putative centers of dog domestication, two basal dog lineages (Basenji and Dingo) and a golden jackal as an outgroup. Analysis of these sequences supports a demographic model in which dogs and wolves diverged through a dynamic process involving population bottlenecks in both lineages and post-divergence gene flow. In dogs, the domestication bottleneck involved at least a 16-fold reduction in population size, a much more severe bottleneck than estimated previously. A sharp bottleneck in wolves occurred soon after their divergence from dogs, implying that the pool of diversity from which dogs arose was substantially larger than represented by modern wolf populations. We narrow the plausible range for the date of initial dog domestication to an interval spanning 11-16 thousand years ago, predating the rise of agriculture. In light of this finding, we expand upon previous work regarding the increase in copy number of the amylase gene (AMY2B) in dogs, which is believed to have aided digestion of starch in agricultural refuse. We find standing variation for amylase copy number variation in wolves and little or no copy number increase in the Dingo and Husky lineages. In conjunction with the estimated timing of dog origins, these results provide additional support to archaeological finds, suggesting the earliest dogs arose alongside hunter-gathers rather than agriculturists. Regarding the geographic origin of dogs, we find that, surprisingly, none of the extant wolf lineages from putative domestication centers is more closely related to dogs, and, instead, the sampled wolves form a sister monophyletic clade. This result, in combination with dog-wolf admixture during the process of domestication, suggests that a re-evaluation of past hypotheses regarding dog origins is necessary

Genome Sequencing Highlights Genes Under Selection and the Dynamic Early History of Dogs

Abstract To identify genetic changes underlying dog domestication and reconstruct their early evolutionary history, we analyzed novel high-quality genome sequences of three gray wolves, one from each of three putative centers of dog domestication, two ancient dog lineages (Basenji and Dingo) and a golden jackal as an outgroup. We find dogs and wolves diverged through a dynamic process involving population bottlenecks in both lineages and post-divergence gene flow, which confounds previous inferences of dog origins. In dogs, the domestication bottleneck was severe involving a 17 to 49-fold reduction in population size, a much stronger bottleneck than estimated previously from less intensive sequencing efforts. A sharp bottleneck in wolves occurred soon after their divergence from dogs, implying that the pool of diversity from which dogs arose was far larger than represented by modern wolf populations. Conditional on mutation rate, we narrow the plausible range for the date of initial dog domestication to an interval from 11 to 16 thousand years ago. This period predates the rise of agriculture and, along with new evidence from variation in amylase copy number, implies that the earliest dogs arose alongside hunter-gathers rather than agriculturists. Regarding the geographic origin of dogs, we find that surprisingly, none of the extant wolf lineages from putative domestication centers are more closely related to dogs, and the sampled wolves instead form a sister monophyletic clade. This result, in combination with our finding of dogwolf admixture during the process of domestication, suggests a re-evaluation of past hypotheses of dog origin is necessary. Finally, we also detect signatures of selection, including evidence for selection on genes implicated in morphology, metabolism, and neural development. Uniquely, we find support for selective sweeps at regulatory sites suggesting gene regulatory changes played a critical role in dog domestication

Demography-aware inference of the strength of natural selection

Levels of genetic and possibly phenotypic variation are influenced by how natural selection acts to change the frequency of deleterious and advantageous mutations. However, the demographic history of a population influences the efficacy of natural selection to keep deleterious variants at low frequencies and to raise the frequency of advantageous mutations. I present three projects where I study how natural selection works in the context of different demographic histories. On the first project, I study the early demographic history of dogs and wolves since their divergence using genomic data. I inferred population bottlenecks in dogs and wolves and I found evidence for gene flow between dogs and wolves after their divergence. I develop a summary statistic to find the most plausible demographic model for dogs and wolves, where I found evidence for a demographic model stating that dogs evolved from one single location. This project laid the foundation to study how advantageous and deleterious variants behave in the context of the bottlenecks found in dogs and wolves. On the second chapter, I leverage the demographic models I inferred to study how demographic processes have influenced levels of deleterious genetic variation in dogs using 90 whole-genome sequences from breed dogs, village dogs and gray wolves. I used the ratio of heterozygosity at amino-acid changing variants over silent variants to show how bottlenecks associated with domestication and breed formation in dogs have affected the efficacy of negative selection. I show multiple lines of evidence indicating that bottlenecks, and not inbreeding, are driving the patterns of deleterious genetic variation we observed in dogs. In the third project, I develop a novel likelihood-based method that uses the lengths of pairwise haplotype identity by state among haplotypes carrying rare variants. The method conditions on the present-day frequency of the allele and is based on theory predicting that, under constant population sizes, the alleles under negative selection are on average younger than neutral alleles and should have higher average levels of haplotype identity among variant carriers. I developed a computational framework to obtain the probability distribution of the lengths of pairwise haplotype identity given a certain selection coefficient, demographic scenario and present-day allele frequency. Simulations indicate that our method provides unbiased estimates of selection under constant population sizes and realistic demographic scenarios. I show how the method can also be used to estimate the parameters that define the distribution of selective coefficients of a set of rare variants. I provide an example of how to apply this method to estimate the distribution of selective coefficients of a set of amino-acid changing variants in the UK10K, a large genomic dataset of British individuals

FST between archaic and present-day samples

The increasing abundance of DNA sequences obtained from fossils calls for new population genetics theory that takes account of both the temporal and spatial separation of samples. Here, we exploit the relationship between Wright's FST and average coalescence times to develop an analytic theory describing how FST depends on both the distance and time separating pairs of sampled genomes. We apply this theory to several simple models of population history. If there is a time series of samples, partial population replacement creates a discontinuity in pairwise FST values. The magnitude of the discontinuity depends on the extent of replacement. In stepping-stone models, pairwise FST values between archaic and present-day samples reflect both the spatial and temporal separation. At long distances, an isolation by distance pattern dominates. At short distances, the time separation dominates. Analytic predictions fit patterns generated by simulations. We illustrate our results with applications to archaic samples from European human populations. We compare present-day samples with a pair of archaic samples taken before and after a replacement event

PReFerSim: fast simulation of demography and selection under the Poisson Random Field model.

The Poisson Random Field (PRF) model has become an important tool in population genetics to study weakly deleterious genetic variation under complicated demographic scenarios. Currently, there are no freely available software applications that allow simulation of genetic variation data under this model. Here we present PReFerSim, an ANSI C program that performs forward simulations under the PRF model. PReFerSim models changes in population size, arbitrary amounts of inbreeding, dominance and distributions of selective effects. Users can track summaries of genetic variation over time and output trajectories of selected alleles.Availability and implementationPReFerSim is freely available at: https://github.com/LohmuellerLab/PReFerSim CONTACT: [email protected] information: Supplementary data are available at Bioinformatics online

HomoplasyMetrics

A set of instructions to reproduce all the Figures from our Homoplasy Metrics paper: Appropriate homoplasy metrics in linked SSRs to predict an underestimation of demographic expansion times