利用共享基因组片段分析鉴定正选择区域。
Identification of regions of positive selection using Shared Genomic Segment analysis.
机构信息
Department of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, UT 84108, USA.
出版信息
Eur J Hum Genet. 2011 Jun;19(6):667-71. doi: 10.1038/ejhg.2010.257. Epub 2011 Feb 9.
Abstract
We applied a shared genomic segment (SGS) analysis, incorporating an error model, to identify complete, or near complete, selective sweeps in the HapMap phase II data sets. This method is based on detecting heterozygous sharing across all individuals within a population, to identify regions of sharing with at least one allele in common. We identified multiple interesting regions, many of which are concordant with positive selection regions detected by previous population genetic tests. Others are suggested to be novel regions. Our finding illustrates the utility of SGS as a method for identifying regions of selection, and some of these regions have been proposed to be candidate regions for harboring disease genes.
摘要
我们应用了一种包含误差模型的共享基因组片段（SGS）分析方法，以识别 HapMap 二期数据集中完整或近乎完整的选择清除。这种方法基于在一个种群中的所有个体之间检测杂合性共享，以识别具有至少一个共同等位基因的共享区域。我们确定了多个有趣的区域，其中许多与之前的群体遗传测试检测到的正选择区域一致。其他区域被认为是新的区域。我们的发现说明了 SGS 作为一种识别选择区域的方法的有效性，其中一些区域已被提议为携带疾病基因的候选区域。
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