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PMID: 16845142 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't

A whole genome long-range haplotype (WGLRH) test for detecting imprints of positive selection in human populations.

Bioinformatics (Oxford, England) ·Vol. 22 ·No. 17 ·2006-09-01 ·Pages 2122-8

Zhang C, Bailey DK, Awad T, Liu G, Xing G, Cao M, Valmeekam V, Retief J, Matsuzaki H, Taub M, Seielstad M, Kennedy GC

Abstract

The identification of signatures of positive selection can provide important insights into recent evolutionary history in human populations. Current methods mostly rely on allele frequency determination or focus on one or a small number of candidate chromosomal regions per study. With the availability of large-scale genotype data, efficient approaches for an unbiased whole genome scan are becoming necessary. We have developed a new method, the whole genome long-range haplotype test (WGLRH), which uses genome-wide distributions to test for recent positive selection. Adapted from the long-range haplotype (LRH) test, the WGLRH test uses patterns of linkage disequilibrium (LD) to identify regions with extremely low historic recombination. Common haplotypes with significantly longer than expected ranges of LD given their frequencies are identified as putative signatures of recent positive selection. In addition, we have also determined the ancestral alleles of SNPs by genotyping chimpanzee and gorilla DNA, and have identified SNPs where the non-ancestral alleles have risen to extremely high frequencies in human populations, termed 'flipped SNPs'. Combining the haplotype test and the flipped SNPs determination, the WGLRH test serves as an unbiased genome-wide screen for regions under putative selection, and is potentially applicable to the study of other human populations. Using WGLRH and high-density oligonucleotide arrays interrogating 116 204 SNPs, we rapidly identified putative regions of positive selection in three populations (Asian, Caucasian, African-American), and extended these observations to a fourth population, Yoruba, with data obtained from the International HapMap consortium. We mapped significant regions to annotated genes. While some regions overlap with genes previously suggested to be under positive selection, many of the genes have not been previously implicated in natural selection and offer intriguing possibilities for further study. the programs for the WGLRH algorithm are freely available and can be downloaded at http://www.affymetrix.com/support/supplement/WGLRH_program.zip.

MeSH Terms
Algorithms Animals Biological Evolution Chromosome Mapping/methods Evolution, Molecular Genetic Variation/genetics Genetics, Population Genome, Human/genetics Genomic Imprinting/genetics Humans Polymorphism, Single Nucleotide/genetics Selection, Genetic Sequence Analysis, DNA/methods Software
Authors & Affiliations
12 authors, click to expand affiliations / ORCID
Zhang Chun
Affymetrix Inc, 3380 Central Expressway, Santa Clara, CA 95051, USA.
Bailey Dione K
Awad Tarif
Liu Guoying
Xing Guoliang
Cao Manqiu
Valmeekam Venu
Retief Jacques
Matsuzaki Hajime
Taub Margaret
Seielstad Mark
Kennedy Giulia C
Article Info
Journal
Bioinformatics (Oxford, England)
Abbr.
Bioinformatics
ISSN
1367-4811
Published
2006-09-01
Epub
2006-00-15
Pages
2122-8
Language
English
Region
England
NLM ID
9808944
Subset
IM
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