Identification of the genetic basis for complex disorders by use of pooling-based genomewide single-nucleotide-polymorphism association studies |
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| Authors: | Pearson John V Huentelman Matthew J Halperin Rebecca F Tembe Waibhav D Melquist Stacey Homer Nils Brun Marcel Szelinger Szabolcs Coon Keith D Zismann Victoria L Webster Jennifer A Beach Thomas Sando Sigrid B Aasly Jan O Heun Reinhard Jessen Frank Kolsch Heike Tsolaki Magdalini Daniilidou Makrina Reiman Eric M Papassotiropoulos Andreas Hutton Michael L Stephan Dietrich A Craig David W |
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| Affiliation: | Translational Genomics Research Institute, Phoenix, AZ, 85004, USA. |
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| Abstract: | 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. |
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