Identification of the Genetic Basis for Complex Disorders by Use of Pooling-Based Genomewide Single-Nucleotide–Polymorphism Association Studies
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- 作者：John V. Pearson ; Matthew J. Huentelman ; Rebecca F. Halperin ; Waibhav D. Tembe ; Stacey Melquist ; Nils Homer ; Marcel Brun ; Szabolcs Szelinger ; Keith D. Coon ; Victoria L. Zismann ; Jennifer A. Webster ; Thomas Beach ; Sigrid B. S ; o ; Jan O. Aasly ; Reinhard Heun ; Frank Jessen ; Heike Kö ; lsch ; Magdalini T
- 刊名：The American Journal of Human Genetics
- 出版年：2007
- 出版时间：January 2007
- 年：2007
- 卷：80
- 期：1
- 页码：126-139
- 全文大小：3681 K
文摘
We report the development and validation of experimental methods, study designs, and analysis software for pooling-based genomewide association (GWA) studies that use high-throughput single-nucleotide–polymorphism (SNP) genotyping microarrays. We first describe a theoretical framework for establishing the effectiveness of pooling genomic DNA as a low-cost alternative to individually genotyping thousands of samples on high-density SNP microarrays. Next, we describe software called “GenePool,” which directly analyzes SNP microarray probe intensity data and ranks SNPs by increased likelihood of being genetically associated with a trait or disorder. Finally, we apply these methods to experimental case-control data and demonstrate successful identification of published genetic susceptibility loci for a rare monogenic disease (sudden infant death with dysgenesis of the testes syndrome), a rare complex disease (progressive supranuclear palsy), and a common complex disease (Alzheimer disease) across multiple SNP genotyping platforms. On the basis of these theoretical calculations and their experimental validation, our results suggest that pooling-based GWA studies are a logical first step for determining whether major genetic associations exist in diseases with high heritability.