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Genome-wide insights into the patterns and determinants of fine-scale population structure in humans.

Abstract：

:Studying genomic patterns of human population structure provides important insights into human evolutionary history and the relationship among populations, and it has significant practical implications for disease-gene mapping. Here we describe a principal component (PC)-based approach to studying intracontinental population structure in humans, identify the underlying markers mediating the observed patterns of fine-scale population structure, and infer the predominating evolutionary forces shaping local population structure. We applied this methodology to a data set of 650K SNPs genotyped in 944 unrelated individuals from 52 populations and demonstrate that, although typical PC analyses focus on the top axes of variation, substantial information about population structure is contained in lower-ranked PCs. We identified 18 significant PCs, some of which distinguish individual populations. In addition to visually representing sample clusters in PC biplots, we estimated the set of all SNPs significantly correlated with each of the most informative axes of variation. These polymorphisms, unlike ancestry-informative markers (AIMs), constitute a much larger set of loci that drive genomic signatures of population structure. The genome-wide distribution of these significantly correlated markers can largely be accounted for by the stochastic effects of genetic drift, although significant clustering does occur in genomic regions that have been previously implicated as targets of recent adaptive evolution.

journal_name

Am J Hum Genet

journal_title

American journal of human genetics

authors

Biswas S,Scheinfeldt LB,Akey JM

doi

10.1016/j.ajhg.2009.04.015

subject

Has Abstract

pub_date

2009-05-01 00:00:00

pages

641-50

issue

5

eissn

0002-9297

issn

1537-6605

pii

S0002-9297(09)00157-8

journal_volume

84

pub_type

杂志文章

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