Literature DB >> 16434598

How well do HapMap haplotypes identify common haplotypes of genes? A comparison with haplotypes of 334 genes resequenced in the environmental genome project.

Jack A Taylor1, Zong-Li Xu, Norman L Kaplan, Richard W Morris.   

Abstract

One of the goals of the International HapMap Project is the identification of common haplotypes in genes. However, HapMap uses an incomplete catalogue of single nucleotide polymorphisms (SNPs) and might miss some common haplotypes. We examined this issue using data from the Environmental Genome Project (EGP) which resequenced 335 genes in 90 people, and thus, has a nearly complete catalogue of gene SNPs. The EGP identified a total of 45,243 SNPs, of which 10,780 were common SNPs (minor allele frequency >or=0.1). Using EGP common SNP genotype data, we identified 1,459 haplotypes with frequency >or=0.05 and we use these as "benchmark" haplotypes. HapMap release 16 had genotype information for 1,573 of 10,780 (15%) EGP common SNPs. Using these SNPs, we identified common HapMap haplotypes (frequency >or=0.05) in each of the four HapMap ethnic groups. To compare common HapMap haplotypes to EGP benchmark haplotypes, we collapsed benchmark haplotypes to the set of 1,573 SNPs. Ninety-eight percent of the collapsed benchmark haplotypes could be found as common HapMap haplotypes in one or more of the four HapMap ethnic groups. However, collapsing benchmark haplotypes to the set of SNPs available in HapMap resulted in a loss of haplotype information: 545 of 1,459 (37%) benchmark haplotypes were uniquely identified, and only 25% of genes had all their benchmark haplotypes uniquely identified. We resampled the EGP data to examine the effect of increasing the number of HapMap SNPs to 5 million, and estimate that approximately 40% of common SNPs in genes will be sampled and that half of the genes will have sufficient SNPs to identify all common haplotypes. This inability to distinguish common haplotypes of genes may result in loss of power when examining haplotype-disease association. (Cancer Epidemiol Biomarkers Prev 2006;15(1):133-7).

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Year:  2006        PMID: 16434598     DOI: 10.1158/1055-9965.EPI-05-0641

Source DB:  PubMed          Journal:  Cancer Epidemiol Biomarkers Prev        ISSN: 1055-9965            Impact factor:   4.254


  7 in total

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Journal:  Genomics       Date:  2006-05-19       Impact factor: 5.736

Review 2.  Successful design and conduct of genome-wide association studies.

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3.  Shifting paradigm of association studies: value of rare single-nucleotide polymorphisms.

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4.  Beyond the HapMap Genotypic Data: Prospects of Deep Resequencing Projects.

Authors:  Wei Zhang; M Eileen Dolan
Journal:  Curr Bioinform       Date:  2008-09-01       Impact factor: 3.543

5.  Assessing human germ-cell mutagenesis in the Postgenome Era: a celebration of the legacy of William Lawson (Bill) Russell.

Authors:  Andrew J Wyrobek; John J Mulvihill; John S Wassom; Heinrich V Malling; Michael D Shelby; Susan E Lewis; Kristine L Witt; R Julian Preston; Sally D Perreault; James W Allen; David M Demarini; Richard P Woychik; Jack B Bishop
Journal:  Environ Mol Mutagen       Date:  2007-03       Impact factor: 3.216

6.  Comprehensive survey of SNPs in the Affymetrix exon array using the 1000 Genomes dataset.

Authors:  Eric R Gamazon; Wei Zhang; M Eileen Dolan; Nancy J Cox
Journal:  PLoS One       Date:  2010-02-23       Impact factor: 3.240

7.  The Environmental Polymorphisms Registry: a DNA resource to study genetic susceptibility loci.

Authors:  Patricia C Chulada; Heather L Vahdat; Richard R Sharp; Tracy C DeLozier; Paul B Watkins; Susan N Pusek; Perry J Blackshear
Journal:  Hum Genet       Date:  2008-01-10       Impact factor: 4.132

  7 in total

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