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Identification of the Genetic Basis for Complex Disorders by Use of Pooling-Based Genomewide Single-Nucleotide–Polymorphism Association Studies

机译:通过基于池的全基因组单核苷酸多态性关联研究确定复杂疾病的遗传基础

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摘要

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.
机译:我们报告了使用高通量单核苷酸多态性(SNP)基因分型微阵列的基于池的全基因组关联(GWA)研究的实验方法,研究设计和分析软件的开发和验证。我们首先描述一个理论框架,以建立合并基因组DNA的有效性,以此作为对高密度SNP微阵列上的数千个样本进行单独基因分型的低成本替代方案。接下来,我们介绍一种名为“ GenePool”的软件,该软件可以直接分析SNP微阵列探针强度数据,并通过与性状或疾病发生遗传关联的可能性增加来对SNP进行排名。最后,我们将这些方法应用于实验病例对照数据,并证明成功鉴定了罕见的单基因疾病(婴儿突然死亡,睾丸综合征的发育不全),罕见的复杂疾病(渐进性核上性麻痹)和跨多个SNP基因分型平台的常见复杂疾病(阿尔茨海默氏病)。根据这些理论计算和实验验证,我们的结果表明,基于合并的GWA研究是确定高遗传力疾病中是否存在主要遗传关联的逻辑第一步。

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