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


BACKGROUND
the programs for the WGLRH algorithm are freely available and can be downloaded at http://www.affymetrix.com/support/supplement/WGLRH_program.zip.
Zhang
Chun
C
Affymetrix Inc, 3380 Central Expressway, Santa Clara, CA 95051, USA.
Bailey
Dione K
DK
Awad
Tarif
T
Liu
Guoying
G
Xing
Guoliang
G
Cao
Manqiu
M
Valmeekam
Venu
V
Retief
Jacques
J
Matsuzaki
Hajime
H
Taub
Margaret
M
Seielstad
Mark
M
Kennedy
Giulia C
GC
D000465:Algorithms; D000818:Animals; D005075:Biological Evolution; D002874:Chromosome Mapping / Q000379:methods*; D019143:Evolution, Molecular; D014644:Genetic Variation / Q000235:genetics*; D005828:Genetics, Population; D015894:Genome, Human / Q000235:genetics*; D018392:Genomic Imprinting / Q000235:genetics*; D006801:Humans; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D012641:Selection, Genetic; D017422:Sequence Analysis, DNA / Q000379:methods; D012984:Software