Nature Genetics 38, 86 - 92 (2006)
Published online: 4 December 2005; | doi:10.1038/ng1696
Common deletion polymorphisms in the human genomeSteven A McCarroll1, 2, 3, Tracy N Hadnott1, George H Perry4, Pardis C Sabeti3, Michael C Zody3, Jeffrey C Barrett3, Stephanie Dallaire4, Stacey B Gabriel3, Charles Lee4, 5, Mark J Daly2, 3, 5, 6, David M Altshuler1, 2, 3, 5, 6
& The International HapMap Consortium1
Department of Molecular Biology, Massachusetts General Hospital, 55 Fruit Street, Boston, Massachusetts 02114, USA. 2
Center for Human Genetic Research, Massachusetts General Hospital, 55 Fruit Street, Boston, Massachusetts 02114, USA. 3
Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02141, USA. 4
Department of Pathology, Brigham and Women's Hospital, 75 Francis Street, Boston, Massachusetts 02115, USA. 5
Harvard Medical School, Boston, Massachusetts 02115, USA. 6
Department of Medicine, Massachusetts General Hospital, Simches Research Center, 185 Cambridge St., Boston, Massachusetts 02114, USA.
Correspondence should be addressed to David M Altshuler altshuler@molbio.mgh.harvard.edu The locations and properties of common deletion variants in the human genome are largely unknown. We describe a systematic method for using dense SNP genotype data to discover deletions and its application to data from the International HapMap Consortium to characterize and catalogue segregating deletion variants across the human genome. We identified 541 deletion variants (94% novel) ranging from 1 kb to 745 kb in size; 278 of these variants were observed in multiple, unrelated individuals, 120 in the homozygous state. The coding exons of ten expressed genes were found to be commonly deleted, including multiple genes with roles in sex steroid metabolism, olfaction and drug response. These common deletion polymorphisms typically represent ancestral mutations that are in linkage disequilibrium with nearby SNPs, meaning that their association to disease can often be evaluated in the course of SNP-based whole-genome association studies.
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