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Tracking human population structure through time from whole genome sequences

The genetic diversity of humans, like many species, has been shaped by a complex pattern of population separations followed by isolation and subsequent admixture. This pattern, reaching at least as far back as the appearance of our species in the paleontological record, has left its traces in our ge...

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Detalles Bibliográficos
Autores principales: Wang, Ke, Mathieson, Iain, O’Connell, Jared, Schiffels, Stephan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7082067/
https://www.ncbi.nlm.nih.gov/pubmed/32150539
http://dx.doi.org/10.1371/journal.pgen.1008552
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author Wang, Ke
Mathieson, Iain
O’Connell, Jared
Schiffels, Stephan
author_facet Wang, Ke
Mathieson, Iain
O’Connell, Jared
Schiffels, Stephan
author_sort Wang, Ke
collection PubMed
description The genetic diversity of humans, like many species, has been shaped by a complex pattern of population separations followed by isolation and subsequent admixture. This pattern, reaching at least as far back as the appearance of our species in the paleontological record, has left its traces in our genomes. Reconstructing a population’s history from these traces is a challenging problem. Here we present a novel approach based on the Multiple Sequentially Markovian Coalescent (MSMC) to analyze the separation history between populations. Our approach, called MSMC-IM, uses an improved implementation of the MSMC (MSMC2) to estimate coalescence rates within and across pairs of populations, and then fits a continuous Isolation-Migration model to these rates to obtain a time-dependent estimate of gene flow. We show, using simulations, that our method can identify complex demographic scenarios involving post-split admixture or archaic introgression. We apply MSMC-IM to whole genome sequences from 15 worldwide populations, tracking the process of human genetic diversification. We detect traces of extremely deep ancestry between some African populations, with around 1% of ancestry dating to divergences older than a million years ago.
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spelling pubmed-70820672020-03-24 Tracking human population structure through time from whole genome sequences Wang, Ke Mathieson, Iain O’Connell, Jared Schiffels, Stephan PLoS Genet Research Article The genetic diversity of humans, like many species, has been shaped by a complex pattern of population separations followed by isolation and subsequent admixture. This pattern, reaching at least as far back as the appearance of our species in the paleontological record, has left its traces in our genomes. Reconstructing a population’s history from these traces is a challenging problem. Here we present a novel approach based on the Multiple Sequentially Markovian Coalescent (MSMC) to analyze the separation history between populations. Our approach, called MSMC-IM, uses an improved implementation of the MSMC (MSMC2) to estimate coalescence rates within and across pairs of populations, and then fits a continuous Isolation-Migration model to these rates to obtain a time-dependent estimate of gene flow. We show, using simulations, that our method can identify complex demographic scenarios involving post-split admixture or archaic introgression. We apply MSMC-IM to whole genome sequences from 15 worldwide populations, tracking the process of human genetic diversification. We detect traces of extremely deep ancestry between some African populations, with around 1% of ancestry dating to divergences older than a million years ago. Public Library of Science 2020-03-09 /pmc/articles/PMC7082067/ /pubmed/32150539 http://dx.doi.org/10.1371/journal.pgen.1008552 Text en © 2020 Wang et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Wang, Ke
Mathieson, Iain
O’Connell, Jared
Schiffels, Stephan
Tracking human population structure through time from whole genome sequences
title Tracking human population structure through time from whole genome sequences
title_full Tracking human population structure through time from whole genome sequences
title_fullStr Tracking human population structure through time from whole genome sequences
title_full_unstemmed Tracking human population structure through time from whole genome sequences
title_short Tracking human population structure through time from whole genome sequences
title_sort tracking human population structure through time from whole genome sequences
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7082067/
https://www.ncbi.nlm.nih.gov/pubmed/32150539
http://dx.doi.org/10.1371/journal.pgen.1008552
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