Transferability of tag SNPs to capture common genetic variation in DNA repair genes across multiple populations.
Transferability of tag SNPs to capture common genetic variation in DNA repair genes across multiple populations.
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DOI：
10.1142/9789812701626_0044
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发表时间：
2006-01-01
影响因子：
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通讯作者：
Haiman, Christopher A
中科院分区：
文献类型：
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作者：
De Bakker, Paul I W;Graham, Robert R;Haiman, Christopher A
利用邻近单核苷酸多态性（SNPs）之间的连锁不平衡模式，可以使遗传关联研究更具成本效益。国际单体型图项目现在提供了一个密集的横跨四个种群样本的人类基因组SNP图谱。一个问题是，从像HapMap这样的资源中选择的标记snp能否很好地捕获独立疾病样本中的常见变异。为了解决标签SNP可转移性的问题，我们对来自多个群体的466个个体的DNA修复相关的61个基因（总跨度为6 Mb）中的2,783个SNP进行了基因分型。我们从人类多态性研究中心（Centre d’etude du Polymorphisme human）的欧洲血统样本中挑选标签snp，并评估其他样本中共同变异的覆盖率。我们的比较分析表明，非非洲样本的共同变异可以被稳健地捕获，而在最大r2方面只有边际损失。我们还评估了特定的多标记单倍型作为无型snp预测因子的可转移性，并证明与单标记测试（双标记）相比，它们提供了相同的覆盖范围，同时需要更少的snp进行基因分型。我们的实证结果强烈支持基于标记的方法在复杂性状中研究基因型-表型相关性的有效性。
Genetic association studies can be made more cost-effective by exploiting linkage disequilibrium patterns between nearby single-nucleotide polymorphisms (SNPs). The International HapMap Project now offers a dense SNP map across the human genome in four population samples. One question is how well tag SNPs chosen from a resource like HapMap can capture common variation in independent disease samples. To address the issue of tag SNP transferability, we genotyped 2,783 SNPs across 61 genes (with a total span of 6 Mb) involved in DNA repair in 466 individuals from multiple populations. We picked tag SNPs in samples with European ancestry from the Centre d'Etude du Polymorphisme Humain, and evaluated coverage of common variation in the other samples. Our comparative analysis shows that common variation in non-African samples can be captured robustly with only marginal loss in terms of the maximum r2. We also evaluated the transferability of specified multi-marker haplotypes as predictors for untyped SNPs, and demonstrate that they provide equivalent coverage compared to single-marker tests (pairwise tags) while requiring fewer SNPs for genotyping. The efficacy of a tagging-based approach in studying genotype-phenotype correlations in complex traits is strongly supported by our empirical results.