首页> 美国卫生研究院文献>American Journal of Human Genetics >Large-Scale Single-Nucleotide Polymorphism (SNP) and Haplotype Analyses Using Dense SNP Maps of 199 Drug-Related Genes in 752 Subjects: the Analysis of the Association between Uncommon SNPs within Haplotype Blocks and the Haplotypes Constructed with Haplotype-Tagging SNPs
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Large-Scale Single-Nucleotide Polymorphism (SNP) and Haplotype Analyses Using Dense SNP Maps of 199 Drug-Related Genes in 752 Subjects: the Analysis of the Association between Uncommon SNPs within Haplotype Blocks and the Haplotypes Constructed with Haplotype-Tagging SNPs

机译:大规模单核苷酸多态性(SNP)和单倍型分析使用密集SNP图谱对752名受试者中199个与药物相关的基因进行了分析:单倍型模块内罕见的SNP与单倍型标签SNP构成的单倍型之间的关联性分析

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摘要

To optimize the strategies for population-based pharmacogenetic studies, we extensively analyzed single-nucleotide polymorphisms (SNPs) and haplotypes in 199 drug-related genes, through use of 4,190 SNPs in 752 control subjects. Drug-related genes, like other genes, have a haplotype-block structure, and a few haplotype-tagging SNPs (htSNPs) could represent most of the major haplotypes constructed with common SNPs in a block. Because our data included 860 uncommon (frequency <0.1) SNPs with frequencies that were accurately estimated, we analyzed the relationship between haplotypes and uncommon SNPs within the blocks (549 SNPs). We inferred haplotype frequencies through use of the data from all htSNPs and one of the uncommon SNPs within a block and calculated four joint probabilities for the haplotypes. We show that, irrespective of the minor-allele frequency of an uncommon SNP, the majority (mean ± SD frequency 0.943±0.117) of the minor alleles were assigned to a single haplotype tagged by htSNPs if the uncommon SNP was within the block. These results support the hypothesis that recombinations occur only infrequently within blocks. The proportion of a single haplotype tagged by htSNPs to which the minor alleles of an uncommon SNP were assigned was positively correlated with the minor-allele frequency when the frequency was <0.03 (P<.000001; n=233 [Spearman’s rank correlation coefficient]). The results of simulation studies suggested that haplotype analysis using htSNPs may be useful in the detection of uncommon SNPs associated with phenotypes if the frequencies of the SNPs are higher in affected than in control populations, the SNPs are within the blocks, and the frequencies of the SNPs are >0.03.
机译:为了优化基于人群的药物遗传学研究的策略,我们通过在752个对照受试者中使用4190个SNP,广泛分析了199个与药物相关的基因中的单核苷酸多态性(SNP)和单倍型。与其他基因一样,与药物相关的基因也具有单倍型嵌段结构,并且一些带有单倍型标签的SNP(htSNPs)可以代表一个区块中由常见SNP构成的大多数主要单倍型。由于我们的数据包括860个不常见(频率<0.1)的SNP,其频率已被准确估算,因此我们分析了单倍型与模块内的不常见SNP(549个SNP)之间的关系。我们通过使用来自一个块内所有htSNP和一个罕见SNP的数据推断出单倍型频率,并计算了该单倍型的四个联合概率。我们显示,不管罕见SNP的次要等位基因频率如何,如果罕见SNP在该区域内,则大多数次要等位基因(平均值±SD频率0.943±0.117)被分配给htSNPs标记的单倍型。这些结果支持这样的假设,即重组仅在块内很少发生。当频率<0.03时,由htSNPs标记的单个单倍型的比例(不常见的SNP的次要等位基因)与次要等位基因频率呈正相关(P <.000001; n = 233 [Spearman秩相关系数] )。模拟研究的结果表明,如果受影响人群中单核苷酸多态性的频率高于对照人群,且单核苷酸多态性处于受阻区域内,并且使用单核苷酸多态性的频率,则使用htSNP进行单倍型分析可能有助于检测与表型相关的罕见SNP。 SNP> 0.03。

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