Broad Institute, 7 Cambridge Center, Cambridge, Massachusetts 02138, USA.
Nature. 2010 Sep 2;467(7311):52-8. doi: 10.1038/nature09298.
Despite great progress in identifying genetic variants that influence human disease, most inherited risk remains unexplained. A more complete understanding requires genome-wide studies that fully examine less common alleles in populations with a wide range of ancestry. To inform the design and interpretation of such studies, we genotyped 1.6 million common single nucleotide polymorphisms (SNPs) in 1,184 reference individuals from 11 global populations, and sequenced ten 100-kilobase regions in 692 of these individuals. This integrated data set of common and rare alleles, called 'HapMap 3', includes both SNPs and copy number polymorphisms (CNPs). We characterized population-specific differences among low-frequency variants, measured the improvement in imputation accuracy afforded by the larger reference panel, especially in imputing SNPs with a minor allele frequency of <or=5%, and demonstrated the feasibility of imputing newly discovered CNPs and SNPs. This expanded public resource of genome variants in global populations supports deeper interrogation of genomic variation and its role in human disease, and serves as a step towards a high-resolution map of the landscape of human genetic variation.
尽管在鉴定影响人类疾病的遗传变异方面取得了巨大进展，但大多数遗传风险仍然无法解释。更全面的理解需要进行全基因组研究，这些研究要充分检查具有广泛遗传背景的人群中不太常见的等位基因。为了为这些研究的设计和解释提供信息，我们对来自 11 个全球人群的 1184 名参考个体中的 160 万个常见单核苷酸多态性（SNP）进行了基因分型，并对其中 692 名个体的 10 个 100 千碱基区域进行了测序。这个称为“HapMap 3”的常见和稀有等位基因综合数据集包括 SNP 和拷贝数多态性（CNP）。我们描述了低频变异体在不同人群中的特异性差异，衡量了更大参考面板提供的更准确的基因分型准确性的提高，特别是在对频率低于 5%的次要等位基因进行基因分型时，并且证明了推断新发现的 CNP 和 SNP 的可行性。这个在全球人群中扩展的基因组变异公共资源支持对基因组变异及其在人类疾病中的作用进行更深入的研究，并为人类遗传变异景观的高分辨率图谱迈出了一步。
