The Population Reference Sample, POPRES: a resource for population, disease, and pharmacological genetics research |
| |
Authors: | Nelson Matthew R Bryc Katarzyna King Karen S Indap Amit Boyko Adam R Novembre John Briley Linda P Maruyama Yuka Waterworth Dawn M Waeber Gérard Vollenweider Peter Oksenberg Jorge R Hauser Stephen L Stirnadel Heide A Kooner Jaspal S Chambers John C Jones Brendan Mooser Vincent Bustamante Carlos D Roses Allen D Burns Daniel K Ehm Margaret G Lai Eric H |
| |
Affiliation: | Matthew R. Nelson, Katarzyna Bryc, Karen S. King, Amit Indap, Adam R. Boyko, John Novembre, Linda P. Briley, Yuka Maruyama, Dawn M. Waterworth, Gérard Waeber, Peter Vollenweider, Jorge R. Oksenberg, Stephen L. Hauser, Heide A. Stirnadel, Jaspal S. Kooner, John C. Chambers, Brendan Jones, Vincent Mooser, Carlos D. Bustamante, Allen D. Roses, Daniel K. Burns, Margaret G. Ehm, and Eric H. Lai |
| |
Abstract: | Technological and scientific advances, stemming in large part from the Human Genome and HapMap projects, have made large-scale, genome-wide investigations feasible and cost effective. These advances have the potential to dramatically impact drug discovery and development by identifying genetic factors that contribute to variation in disease risk as well as drug pharmacokinetics, treatment efficacy, and adverse drug reactions. In spite of the technological advancements, successful application in biomedical research would be limited without access to suitable sample collections. To facilitate exploratory genetics research, we have assembled a DNA resource from a large number of subjects participating in multiple studies throughout the world. This growing resource was initially genotyped with a commercially available genome-wide 500,000 single-nucleotide polymorphism panel. This project includes nearly 6,000 subjects of African-American, East Asian, South Asian, Mexican, and European origin. Seven informative axes of variation identified via principal-component analysis (PCA) of these data confirm the overall integrity of the data and highlight important features of the genetic structure of diverse populations. The potential value of such extensively genotyped collections is illustrated by selection of genetically matched population controls in a genome-wide analysis of abacavir-associated hypersensitivity reaction. We find that matching based on country of origin, identity-by-state distance, and multidimensional PCA do similarly well to control the type I error rate. The genotype and demographic data from this reference sample are freely available through the NCBI database of Genotypes and Phenotypes (dbGaP). |
| |
Keywords: | |
本文献已被 ScienceDirect PubMed 等数据库收录! |
|