Insights into human genetic variation and population history from 929 diverse genomes

Anders Bergström(The Francis Crick Institute), Shane McCarthy(University of Cambridge), Ruoyun Hui(University of Cambridge), Mohamed A. Almarri(Wellcome Sanger Institute), Qasim Ayub(Monash University Malaysia), Petr Danecek(Wellcome Sanger Institute), Yuan Chen(Wellcome Sanger Institute), Sabine Felkel(University of Veterinary Medicine Vienna), Pille Hallast(Wellcome Sanger Institute), Jack Kamm(University of Cambridge), Hélène Blanché(Fondation Jean Dausset-CEPH), Jean‐François Deleuze(Fondation Jean Dausset-CEPH), Howard M. Cann(Fondation Jean Dausset-CEPH), Swapan Mallick(Broad Institute), David Reich(Broad Institute), Manjinder S. Sandhu(University of Cambridge), Pontus Skoglund(The Francis Crick Institute), Aylwyn Scally(University of Cambridge), Yali Xue(Wellcome Sanger Institute), Richard Durbin(University of Cambridge), Chris Tyler‐Smith(Wellcome Sanger Institute)
bioRxiv (Cold Spring Harbor Laboratory)
June 27, 2019
Cited by 156Open Access
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Abstract

Abstract Genome sequences from diverse human groups are needed to understand the structure of genetic variation in our species and the history of, and relationships between, different populations. We present 929 high-coverage genome sequences from 54 diverse human populations, 26 of which are physically phased using linked-read sequencing. Analyses of these genomes reveal an excess of previously undocumented private genetic variation in southern and central Africa and in Oceania and the Americas, but an absence of fixed, private variants between major geographical regions. We also find deep and gradual population separations within Africa, contrasting population size histories between hunter-gatherer and agriculturalist groups in the last 10,000 years, a potentially major population growth episode after the peopling of the Americas, and a contrast between single Neanderthal but multiple Denisovan source populations contributing to present-day human populations. We also demonstrate benefits to the study of population relationships of genome sequences over ascertained array genotypes. These genome sequences are freely available as a resource with no access or analysis restrictions.


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