Copyright © 2007 The American Society of Human Genetics. All rights reserved.
The American Journal of Human Genetics, Volume 81, Issue 6, 1221-1231, 1 December 2007
doi:10.1086/522239
Article
The Structure of Common Genetic Variation in United States Populations
Stephen L. Gutherya, Benjamin A. Salisburyb, Manish S. Pungliyab, J. Claiborne Stephensc and Michael Bamshadd, e, 
, 
a Department of Pediatrics, University of Utah, Salt Lake City
b Genaissance Pharmaceuticals, New Haven, CT
c Departments of Pediatrics and Genome Sciences, University of Washington, Motif BioSciences, New York
d Departments of Pediatrics and Genome Sciences, University of Washington, Seattle
e Children’s Hospital and Regional Medical Center, Seattle
Address for correspondence and reprints: Dr. Michael Bamshad, Department of Pediatrics, Division of Genetics and Developmental Medicine, University of Washington School of Medicine, 1959 NE Pacific Street, HSB RR349, Seattle, WA 98195Abstract
The common-variant/common-disease model predicts that most risk alleles underlying complex health-related traits are common and, therefore, old and found in multiple populations, rather than being rare or population specific. Accordingly, there is widespread interest in assessing the population structure of common alleles. However, such assessments have been confounded by analysis of data sets with bias toward ascertainment of common alleles (e.g., HapMap and Perlegen) or in which a relatively small number of genes and/or populations were sampled. The aim of this study was to examine the structure of common variation ascertained in major U.S. populations, by resequencing the exons and flanking regions of 3,873 genes in 154 chromosomes from European, Latino/Hispanic, Asian, and African Americans generated by the Genaissance Resequencing Project. The frequency distributions of private and common single-nucleotide polymorphisms (SNPs) were measured, and the extent to which common SNPs were shared across populations was analyzed using several different estimators of population structure. Most SNPs that were common in one population were present in multiple populations, but SNPs common in one population were frequently not common in other populations. Moreover, SNPs that were common in two or more populations often differed significantly in frequency from one population to another, particularly in comparisons of African Americans versus other U.S. populations. These findings indicate that, even if the bulk of alleles underlying complex health-related traits are common SNPs, geographic ancestry might well be an important predictor of whether a person carries a risk allele.
Article Information
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