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Detection and Classification of Hard and Soft Sweeps from Unphased Genotypes by Multilocus Genotype Identity

机译:通过多基因座基因型识别对未分期基因型的硬性和软性扫描进行分类和检测

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摘要

Positive natural selection can lead to a decrease in genomic diversity at the selected site and at linked sites, producing a characteristic signature of elevated expected haplotype homozygosity. These selective sweeps can be hard or soft. In the case of a hard selective sweep, a single adaptive haplotype rises to high population frequency, whereas multiple adaptive haplotypes sweep through the population simultaneously in a soft sweep, producing distinct patterns of genetic variation in the vicinity of the selected site. Measures of expected haplotype homozygosity have previously been used to detect sweeps in multiple study systems. However, these methods are formulated for phased haplotype data, typically unavailable for nonmodel organisms, and some may have reduced power to detect soft sweeps due to their increased genetic diversity relative to hard sweeps. To address these limitations, we applied the H12 and H2/H1 statistics proposed in 2015 by Garud , which have power to detect both hard and soft sweeps, to unphased multilocus genotypes, denoting them as G12 and G2/G1. G12 (and the more direct expected homozygosity analog to H12, denoted G123) has comparable power to H12 for detecting both hard and soft sweeps. G2/G1 can be used to classify hard and soft sweeps analogously to H2/H1, conditional on a genomic region having high G12 or G123 values. The reason for this power is that, under random mating, the most frequent haplotypes will yield the most frequent multilocus genotypes. Simulations based on parameters compatible with our recent understanding of human demographic history suggest that expected homozygosity methods are best suited for detecting recent sweeps, and increase in power under recent population expansions. Finally, we find candidates for selective sweeps within the 1000 Genomes CEU, YRI, GIH, and CHB populations, which corroborate and complement existing studies.
机译:阳性自然选择会导致所选位点和链接位点的基因组多样性降低,从而产生预期单倍型纯合性提高的特征。这些选择性扫描可以是硬的也可以是软的。在硬选择扫描的情况下,单个自适应单倍型会上升到较高的种群频率,而多个自适应单倍型会在软扫描中同时扫描整个种群,从而在所选位点附近产生不同的遗传变异模式。预期的单倍型纯合性的检测方法先前已用于检测多个研究系统中的扫描。但是,这些方法针对分阶段的单倍型数据而制定,通常不适用于非模型生物,由于相对于硬扫描,遗传多样性增加,某些方法检测软扫描的能力可能降低。为了解决这些局限性,我们将Garud在2015年提出的H12和H2 / H1统计数据应用到了无阶段多基因座基因型中,这些统计数据可以检测硬扫描和软扫描,将它们表示为G12和G2 / G1。 G12(以及与H12类似的更直接的预期纯合子,表示为G123)具有与H12相当的功能,可检测硬扫和软扫。 G2 / G1可以类似于H2 / H1来对硬扫描和软扫描进行分类,条件是具有高G12或G123值的基因组区域。这种能力的原因是,在随机交配下,最常见的单倍型将产生最常见的多基因座基因型。基于与我们最近对人类人口历史的了解相兼容的参数进行的模拟表明,预期的纯合性方法最适合于检测最近的扫描,以及在最近的人口扩展下功率的增加。最后,我们在1000个基因组CEU,YRI,GIH和CHB人群中找到了选择性扫描的候选者,这些佐证了现有研究并对其进行了补充。

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