Signatures of positive selection apparent in a small sample of human exomes
Signatures of positive selection apparent in a small sample of human exomes
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DOI：
10.1101/gr.106161.110
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发表时间：
2010-10-01
期刊：
影响因子：
7
通讯作者：
Akey, Joshua M.
中科院分区：
文献类型：
--
作者：
Tennessen, Jacob A.;Madeoy, Jennifer;Akey, Joshua M.
外显子组序列包含所有蛋白质编码区，是用于自然选择研究的有希望的数据集，因为它们提供了对多态性的无偏基因组范围的估计，同时关注基因组中最有可能具有重要功能的部分。我们检查了欧洲和非洲血统的 10 个二倍体常染色体外显子组内的多态性基因组模式。通过聚结模拟，我们展示了这些样本中的多态性、位点频谱和洲际分歧将如何受到不同正选择模式的影响。我们检查了之前四次 SNP 基因型全基因组扫描中推定选定的位点，并证明这些区域确实在外显子组数据中显示出不寻常的群体遗传模式。使用一系列基于外显子组多态性的保守标准，我们能够精细绘制选择特征图谱，在许多情况下精确定位单个候选 SNP。我们还识别和评估显示不寻常多态性模式的新候选选择基因。我们对来自多个大陆的 74 名个体的一个新候选基因座 IVL 的一部分进行了测序，并检查了全球遗传多样性。因此，我们确认、缩小和补充了现有的假定选择目标目录，并表明可能很快就会变得普遍的外显子组数据集将成为识别适应性遗传变异的强大工具。
Exome sequences, which comprise all protein-coding regions, are promising data sets for studies of natural selection because they offer unbiased genome-wide estimates of polymorphism while focusing on the portions of the genome that are most likely to be functionally important. We examine genomic patterns of polymorphism within 10 diploid autosomal exomes of European and African descent. Using coalescent simulations, we show how polymorphism, site frequency spectra, and intercontinental divergence in these samples would be influenced by different modes of positive selection. We examine putatively selected loci from four previous genome-wide scans of SNP genotypes and demonstrate that these regions indeed show unusual population genetic patterns in the exome data. Using a series of conservative criteria based on exome polymorphism, we are able to fine-scale map signatures of selection, in many cases pinpointing a single candidate SNP. We also identify and evaluate novel candidate selection genes that show unusual patterns of polymorphism. We sequence a portion of one novel candidate locus, IVL, in 74 individuals from multiple continents and examine global genetic diversity. Thus, we confirm, narrow, and supplement existing catalogs of putative targets of selection, and show that exome data sets, which are likely to soon become common, will be powerful tools for identifying adaptive genetic variation.