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Bioinformatics Advance Access published online on July 15, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl365
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© 2006 The Author(s)
Received December 2, 2005
Revised June 28, 2006
Accepted June 29, 2006

Article

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

Chun Zhang 1, Dione K. Bailey 2, Tarif Awad 2, Guoying Liu 3, Guoliang Xing 2, Manqiu Cao 4, Venu Valmeekam 3, Jacques Retief 5, Hajime Matsuzaki 2, Margaret Taub 6, Mark Seielstad 7, and Giulia C. Kennedy 2 *

1 Affymetrix Inc., 3380 Central Expressway, Santa Clara CA 95051; Current address: Roche Palo Alto LLC, 3431 Hillview Avenue, Palo Alto, CA 94304
2 Affymetrix Inc., 3380 Central Expressway, Santa Clara CA 95051
3 Affymetrix Inc., 6550 Vallejo Street, Emeryville, CA 94608
4 Affymetrix Inc., 3380 Central Expressway, Santa Clara CA 95051; Current address: Intel Corporation, 3065 Bower Avenue, Santa Clara, CA 95054
5 Affymetrix Inc., 3380 Central Expressway, Santa Clara CA 95051; Current address: Iconix Pharmaceuticals Inc., 325 E. Middlefield Rd., Mountain View, CA 94043
6 Department of Statistics, University of California, Berkeley, CA
7 Department of Population Genetics and Genetic Epidemiology, Genome Institute of Singapore, Singapore 138672

* To whom correspondence should be addressed.
Giulia C. Kennedy, E-mail: Giulia_Kennedy{at}affymetrix.com


  Abstract

Motivation: 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.

Methods: 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 (Sabeti et al., 2001), 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.

Results: 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.

Availability: the programs for the WGLRH algorithm are freely available and can be downloaded at http://www.affymetrix.com/support/supplement/WGLRH_program.zip.

Supplementary Material: 3 Supplementary Tables.

Associate Editor: Charlie Hodgman
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