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      Inferring the Joint Demographic History of Multiple Populations from Multidimensional SNP Frequency Data

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          Abstract

          Demographic models built from genetic data play important roles in illuminating prehistorical events and serving as null models in genome scans for selection. We introduce an inference method based on the joint frequency spectrum of genetic variants within and between populations. For candidate models we numerically compute the expected spectrum using a diffusion approximation to the one-locus, two-allele Wright-Fisher process, involving up to three simultaneous populations. Our approach is a composite likelihood scheme, since linkage between neutral loci alters the variance but not the expectation of the frequency spectrum. We thus use bootstraps incorporating linkage to estimate uncertainties for parameters and significance values for hypothesis tests. Our method can also incorporate selection on single sites, predicting the joint distribution of selected alleles among populations experiencing a bevy of evolutionary forces, including expansions, contractions, migrations, and admixture. We model human expansion out of Africa and the settlement of the New World, using 5 Mb of noncoding DNA resequenced in 68 individuals from 4 populations (YRI, CHB, CEU, and MXL) by the Environmental Genome Project. We infer divergence between West African and Eurasian populations 140 thousand years ago (95% confidence interval: 40–270 kya). This is earlier than other genetic studies, in part because we incorporate migration. We estimate the European (CEU) and East Asian (CHB) divergence time to be 23 kya (95% c.i.: 17–43 kya), long after archeological evidence places modern humans in Europe. Finally, we estimate divergence between East Asians (CHB) and Mexican-Americans (MXL) of 22 kya (95% c.i.: 16.3–26.9 kya), and our analysis yields no evidence for subsequent migration. Furthermore, combining our demographic model with a previously estimated distribution of selective effects among newly arising amino acid mutations accurately predicts the frequency spectrum of nonsynonymous variants across three continental populations (YRI, CHB, CEU).

          Author Summary

          The demographic history of our species is reflected in patterns of genetic variation within and among populations. We developed an efficient method for calculating the expected distribution of genetic variation, given a demographic model including such events as population size changes, population splits and joins, and migration. We applied our approach to publicly available human sequencing data, searching for models that best reproduce the observed patterns. Our joint analysis of data from African, European, and Asian populations yielded new dates for when these populations diverged. In particular, we found that African and Eurasian populations diverged around 100,000 years ago. This is earlier than other genetic studies suggest, because our model includes the effects of migration, which we found to be important for reproducing observed patterns of variation in the data. We also analyzed data from European, Asian, and Mexican populations to model the peopling of the Americas. Here, we find no evidence for recurrent migration after East Asian and Native American populations diverged. Our methods are not limited to studying humans, and we hope that future sequencing projects will offer more insights into the history of both our own species and others.

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          Most cited references38

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          Genotype, haplotype and copy-number variation in worldwide human populations.

          Genome-wide patterns of variation across individuals provide a powerful source of data for uncovering the history of migration, range expansion, and adaptation of the human species. However, high-resolution surveys of variation in genotype, haplotype and copy number have generally focused on a small number of population groups. Here we report the analysis of high-quality genotypes at 525,910 single-nucleotide polymorphisms (SNPs) and 396 copy-number-variable loci in a worldwide sample of 29 populations. Analysis of SNP genotypes yields strongly supported fine-scale inferences about population structure. Increasing linkage disequilibrium is observed with increasing geographic distance from Africa, as expected under a serial founder effect for the out-of-Africa spread of human populations. New approaches for haplotype analysis produce inferences about population structure that complement results based on unphased SNPs. Despite a difference from SNPs in the frequency spectrum of the copy-number variants (CNVs) detected--including a comparatively large number of CNVs in previously unexamined populations from Oceania and the Americas--the global distribution of CNVs largely accords with population structure analyses for SNP data sets of similar size. Our results produce new inferences about inter-population variation, support the utility of CNVs in human population-genetic research, and serve as a genomic resource for human-genetic studies in diverse worldwide populations.
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            The late Pleistocene dispersal of modern humans in the Americas.

            When did humans colonize the Americas? From where did they come and what routes did they take? These questions have gripped scientists for decades, but until recently answers have proven difficult to find. Current genetic evidence implies dispersal from a single Siberian population toward the Bering Land Bridge no earlier than about 30,000 years ago (and possibly after 22,000 years ago), then migration from Beringia to the Americas sometime after 16,500 years ago. The archaeological records of Siberia and Beringia generally support these findings, as do archaeological sites in North and South America dating to as early as 15,000 years ago. If this is the time of colonization, geological data from western Canada suggest that humans dispersed along the recently deglaciated Pacific coastline.
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              Calibrating a coalescent simulation of human genome sequence variation.

              Population genetic models play an important role in human genetic research, connecting empirical observations about sequence variation with hypotheses about underlying historical and biological causes. More specifically, models are used to compare empirical measures of sequence variation, linkage disequilibrium (LD), and selection to expectations under a "null" distribution. In the absence of detailed information about human demographic history, and about variation in mutation and recombination rates, simulations have of necessity used arbitrary models, usually simple ones. With the advent of large empirical data sets, it is now possible to calibrate population genetic models with genome-wide data, permitting for the first time the generation of data that are consistent with empirical data across a wide range of characteristics. We present here the first such calibrated model and show that, while still arbitrary, it successfully generates simulated data (for three populations) that closely resemble empirical data in allele frequency, linkage disequilibrium, and population differentiation. No assertion is made about the accuracy of the proposed historical and recombination model, but its ability to generate realistic data meets a long-standing need among geneticists. We anticipate that this model, for which software is publicly available, and others like it will have numerous applications in empirical studies of human genetics.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Genet
                plos
                plosgen
                PLoS Genetics
                Public Library of Science (San Francisco, USA )
                1553-7390
                1553-7404
                October 2009
                October 2009
                23 October 2009
                : 5
                : 10
                : e1000695
                Affiliations
                [1 ]Theoretical Biology and Biophysics and Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America
                [2 ]Human Genetics, University of Chicago, Chicago, Illinois, United States of America
                [3 ]Biological Statistics and Computational Biology, Cornell University, Ithaca, New York, United States of America
                University of Oxford, United Kingdom
                Author notes

                Conceived and designed the experiments: RNG SHW CDB. Performed the experiments: RNG. Analyzed the data: RNG. Contributed reagents/materials/analysis tools: RNG RDH. Wrote the paper: RNG CDB.

                Article
                09-PLGE-RA-0228R3
                10.1371/journal.pgen.1000695
                2760211
                19851460
                d08bd5b8-fbab-4311-b103-0b09e46a9b47
                This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
                History
                : 12 February 2009
                : 23 September 2009
                Page count
                Pages: 11
                Categories
                Research Article
                Computational Biology/Genomics
                Genetics and Genomics/Population Genetics

                Genetics
                Genetics

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