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      Bayesian inference of ancient human demography from individual genome sequences

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          Abstract

          Besides their value for biomedicine, individual genome sequences are a rich source of information about human evolution. Here we describe an effort to estimate key evolutionary parameters from sequences for six individuals from diverse human populations. We use a Bayesian, coalescent-based approach to extract information about ancestral population sizes, divergence times, and migration rates from inferred genealogies at many neutrally evolving loci from across the genome. We introduce new methods for accommodating gene flow between populations and integrating over possible phasings of diploid genotypes. We also describe a custom pipeline for genotype inference to mitigate biases from heterogeneous sequencing technologies and coverage levels. Our analysis indicates that the San of Southern Africa diverged from other human populations 108–157 thousand years ago (kya), that Eurasians diverged from an ancestral African population 38–64 kya, and that the effective population size of the ancestors of all modern humans was ~9,000.

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          Most cited references 18

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          The genetic structure and history of Africans and African Americans.

          Africa is the source of all modern humans, but characterization of genetic variation and of relationships among populations across the continent has been enigmatic. We studied 121 African populations, four African American populations, and 60 non-African populations for patterns of variation at 1327 nuclear microsatellite and insertion/deletion markers. We identified 14 ancestral population clusters in Africa that correlate with self-described ethnicity and shared cultural and/or linguistic properties. We observed high levels of mixed ancestry in most populations, reflecting historical migration events across the continent. Our data also provide evidence for shared ancestry among geographically diverse hunter-gatherer populations (Khoesan speakers and Pygmies). The ancestry of African Americans is predominantly from Niger-Kordofanian (approximately 71%), European (approximately 13%), and other African (approximately 8%) populations, although admixture levels varied considerably among individuals. This study helps tease apart the complex evolutionary history of Africans and African Americans, aiding both anthropological and genetic epidemiologic studies.
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            The Apportionment of Human Diversity

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              Distinguishing migration from isolation: a Markov chain Monte Carlo approach.

              A Markov chain Monte Carlo method for estimating the relative effects of migration and isolation on genetic diversity in a pair of populations from DNA sequence data is developed and tested using simulations. The two populations are assumed to be descended from a panmictic ancestral population at some time in the past and may (or may not) after that be connected by migration. The use of a Markov chain Monte Carlo method allows the joint estimation of multiple demographic parameters in either a Bayesian or a likelihood framework. The parameters estimated include the migration rate for each population, the time since the two populations diverged from a common ancestral population, and the relative size of each of the two current populations and of the common ancestral population. The results show that even a single nonrecombining genetic locus can provide substantial power to test the hypothesis of no ongoing migration and/or to test models of symmetric migration between the two populations. The use of the method is illustrated in an application to mitochondrial DNA sequence data from a fish species: the threespine stickleback (Gasterosteus aculeatus).
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                Author and article information

                Journal
                9216904
                2419
                Nat Genet
                Nature Genetics
                1061-4036
                1546-1718
                10 November 2011
                18 September 2011
                1 April 2012
                : 43
                : 10
                : 1031-1034
                Affiliations
                [1 ]Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14853, USA
                [2 ]Graduate Field of Computer Science, Cornell University, Ithaca, NY 14853, USA
                Author notes
                [3 ]Correspondence should be addressed to A.S. ( acs4@ 123456cornell.edu )
                Article
                nihpa335191
                10.1038/ng.937
                3245873
                21926973

                Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

                Funding
                Funded by: National Institute of Child Health & Human Development : NICHD
                Award ID: T32 HD052471-01A1 || HD
                Categories
                Article

                Genetics

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