Human genomic regions with exceptionally high levels of population differentiation identified from 911 whole-genome sequences.

Published

Journal Article

BACKGROUND:Population differentiation has proved to be effective for identifying loci under geographically localized positive selection, and has the potential to identify loci subject to balancing selection. We have previously investigated the pattern of genetic differentiation among human populations at 36.8 million genomic variants to identify sites in the genome showing high frequency differences. Here, we extend this dataset to include additional variants, survey sites with low levels of differentiation, and evaluate the extent to which highly differentiated sites are likely to result from selective or other processes. RESULTS:We demonstrate that while sites with low differentiation represent sampling effects rather than balancing selection, sites showing extremely high population differentiation are enriched for positive selection events and that one half may be the result of classic selective sweeps. Among these, we rediscover known examples, where we actually identify the established functional SNP, and discover novel examples including the genes ABCA12, CALD1 and ZNF804, which we speculate may be linked to adaptations in skin, calcium metabolism and defense, respectively. CONCLUSIONS:We identify known and many novel candidate regions for geographically restricted positive selection, and suggest several directions for further research.

Full Text

Duke Authors

Cited Authors

  • Colonna, V; Ayub, Q; Chen, Y; Pagani, L; Luisi, P; Pybus, M; Garrison, E; Xue, Y; Tyler-Smith, C; 1000 Genomes Project Consortium, ; Abecasis, GR; Auton, A; Brooks, LD; DePristo, MA; Durbin, RM; Handsaker, RE; Kang, HM; Marth, GT; McVean, GA

Published Date

  • June 30, 2014

Published In

Volume / Issue

  • 15 / 6

Start / End Page

  • R88 -

PubMed ID

  • 24980144

Pubmed Central ID

  • 24980144

Electronic International Standard Serial Number (EISSN)

  • 1474-760X

International Standard Serial Number (ISSN)

  • 1474-7596

Digital Object Identifier (DOI)

  • 10.1186/gb-2014-15-6-r88

Language

  • eng