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Population genomic analysis of 962 whole genome sequences of humans reveals natural selection in non-coding regions.

Authors :
Fuli Yu
Jian Lu
Xiaoming Liu
Elodie Gazave
Diana Chang
Srilakshmi Raj
Haley Hunter-Zinck
Ran Blekhman
Leonardo Arbiza
Cris Van Hout
Alanna Morrison
Andrew D Johnson
Joshua Bis
L Adrienne Cupples
Bruce M Psaty
Donna Muzny
Jin Yu
Richard A Gibbs
Alon Keinan
Andrew G Clark
Eric Boerwinkle
Source :
PLoS ONE, Vol 10, Iss 3, p e0121644 (2015)
Publication Year :
2015
Publisher :
Public Library of Science (PLoS), 2015.

Abstract

Whole genome analysis in large samples from a single population is needed to provide adequate power to assess relative strengths of natural selection across different functional components of the genome. In this study, we analyzed next-generation sequencing data from 962 European Americans, and found that as expected approximately 60% of the top 1% of positive selection signals lie in intergenic regions, 33% in intronic regions, and slightly over 1% in coding regions. Several detailed functional annotation categories in intergenic regions showed statistically significant enrichment in positively selected loci when compared to the null distribution of the genomic span of ENCODE categories. There was a significant enrichment of purifying selection signals detected in enhancers, transcription factor binding sites, microRNAs and target sites, but not on lincRNA or piRNAs, suggesting different evolutionary constraints for these domains. Loci in "repressed or low activity regions" and loci near or overlapping the transcription start site were the most significantly over-represented annotations among the top 1% of signals for positive selection.

Subjects

Subjects :
Medicine
Science

Details

Language :
English
ISSN :
19326203
Volume :
10
Issue :
3
Database :
Directory of Open Access Journals
Journal :
PLoS ONE
Publication Type :
Academic Journal
Accession number :
edsdoj.82d23a2115ca48b08e1cafeb0077e3eb
Document Type :
article
Full Text :
https://doi.org/10.1371/journal.pone.0121644