A map of recent positive selection in the human genome.
A map of recent positive selection in the human genome.
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在人类基因组中近期阳性选择的地图。
DOI：
10.1371/journal.pbio.0040072
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发表时间：
2006-03
期刊：
影响因子：
9.8
通讯作者：
Pritchard JK
中科院分区：
文献类型：
--
作者：
Voight BF;Kudaravalli S;Wen X;Pritchard JK
对近期正选择信号的识别为现代人类对当地环境的适应提供了信息。我们在此报告一项在全基因组范围内对尚未达到固定的有利变异的近期正选择信号的扫描。我们描述了一种用于扫描单核苷酸多态性（SNP）数据以寻找近期选择信号的新分析方法，并将其应用于国际人类基因组单体型图计划的数据。在所有三个大陆群体中，我们都发现了近期正选择的广泛信号。大多数信号是特定区域的，尽管有相当多的信号在不同群体间是共有的。与一些早期低分辨率研究表明撒哈拉以南非洲人近期选择较少相反，我们发现从某些测量标准来看，我们最强的选择信号来自约鲁巴族人群。最后，由于这些信号表明存在适应性有显著差异的基因变异，它们必定指向是显著表型变异来源的基因座。尽管相关表型通常不为人知，但在复杂性状的定位研究中，这类基因座应该特别令人感兴趣。为此，我们开发了一组SNP，可用于标记每个群体中最强的约250个近期选择信号。
作者应用他们新开发的方法，在代表三个人群的国际人类基因组单体型图计划数据中搜索人类基因组上的近期选择信号。
The identification of signals of very recent positive selection provides information about the adaptation of modern humans to local conditions. We report here on a genome-wide scan for signals of very recent positive selection in favor of variants that have not yet reached fixation. We describe a new analytical method for scanning single nucleotide polymorphism (SNP) data for signals of recent selection, and apply this to data from the International HapMap Project. In all three continental groups we find widespread signals of recent positive selection. Most signals are region-specific, though a significant excess are shared across groups. Contrary to some earlier low resolution studies that suggested a paucity of recent selection in sub-Saharan Africans, we find that by some measures our strongest signals of selection are from the Yoruba population. Finally, since these signals indicate the existence of genetic variants that have substantially different fitnesses, they must indicate loci that are the source of significant phenotypic variation. Though the relevant phenotypes are generally not known, such loci should be of particular interest in mapping studies of complex traits. For this purpose we have developed a set of SNPs that can be used to tag the strongest ∼250 signals of recent selection in each population. Applying their newly developed method, the authors search International HapMap Project data representing three populations for signals of recent selection across the human genome.