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Inferring human colonization history using a copying model.


ABSTRACT: Genome-wide scans of genetic variation can potentially provide detailed information on how modern humans colonized the world but require new methods of analysis. We introduce a statistical approach that uses Single Nucleotide Polymorphism (SNP) data to identify sharing of chromosomal segments between populations and uses the pattern of sharing to reconstruct a detailed colonization scenario. We apply our model to the SNP data for the 53 populations of the Human Genome Diversity Project described in Conrad et al. (Nature Genetics 38,1251-60, 2006). Our results are consistent with the consensus view of a single "Out-of-Africa" bottleneck and serial dilution of diversity during global colonization, including a prominent East Asian bottleneck. They also suggest novel details including: (1) the most northerly East Asian population in the sample (Yakut) has received a significant genetic contribution from the ancestors of the most northerly European one (Orcadian). (2) Native North [corrected] Americans have received ancestry from a source closely related to modern North-East Asians (Mongolians and Oroquen) that is distinct from the sources for native South [corrected] Americans, implying multiple waves of migration into the Americas. A detailed depiction of the peopling of the world is available in animated form.

SUBMITTER: Hellenthal G 

PROVIDER: S-EPMC2367454 | biostudies-literature | 2008 May

REPOSITORIES: biostudies-literature

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Inferring human colonization history using a copying model.

Hellenthal Garrett G   Auton Adam A   Falush Daniel D  

PLoS genetics 20080523 5


Genome-wide scans of genetic variation can potentially provide detailed information on how modern humans colonized the world but require new methods of analysis. We introduce a statistical approach that uses Single Nucleotide Polymorphism (SNP) data to identify sharing of chromosomal segments between populations and uses the pattern of sharing to reconstruct a detailed colonization scenario. We apply our model to the SNP data for the 53 populations of the Human Genome Diversity Project described  ...[more]

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