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The Variance of Identity-by-Descent Sharing in the Wright–Fisher Model

机译:Wright-Fisher模型中的后裔身份认同差异

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摘要

Widespread sharing of long, identical-by-descent (IBD) genetic segments is a hallmark of populations that have experienced recent genetic drift. Detection of these IBD segments has recently become feasible, enabling a wide range of applications from phasing and imputation to demographic inference. Here, we study the distribution of IBD sharing in the Wright–Fisher model. Specifically, using coalescent theory, we calculate the variance of the total sharing between random pairs of individuals. We then investigate the cohort-averaged sharing: the average total sharing between one individual and the rest of the cohort. We find that for large cohorts, the cohort-averaged sharing is distributed approximately normally. Surprisingly, the variance of this distribution does not vanish even for large cohorts, implying the existence of “hypersharing” individuals. The presence of such individuals has consequences for the design of sequencing studies, since, if they are selected for whole-genome sequencing, a larger fraction of the cohort can be subsequently imputed. We calculate the expected gain in power of imputation by IBD and subsequently in power to detect an association, when individuals are either randomly selected or specifically chosen to be the hypersharing individuals. Using our framework, we also compute the variance of an estimator of the population size that is based on the mean IBD sharing and the variance in the sharing between inbred siblings. Finally, we study IBD sharing in an admixture pulse model and show that in the Ashkenazi Jewish population the admixture fraction is correlated with the cohort-averaged sharing.
机译:长期相同的后代(IBD)遗传片段的广泛共享是最近经历过遗传漂移的人群的标志。这些IBD段的检测最近变得可行,从而使从定相和归类到人口统计学推断的广泛应用成为可能。在这里,我们研究了Wright-Fisher模型中IBD共享的分布。具体而言,使用合并理论,我们计算了个体随机对之间的总份额方差。然后,我们调查了同类群组平均共享:一个人与其他同类群组之间的平均总体共享。我们发现,对于大型同类群组,同类群组平均共享大致呈正态分布。出人意料的是,即使对于大型队列,该分布的方差也不会消失,这意味着存在“超共享”个体。此类个体的存在对测序研究的设计具有影响,因为如果将其选择用于全基因组测序,则随后可以推算出较大部分的同类人群。当个体被随机选择或被特别选择为超共享个体时,我们将计算IBD的归因能力的预期增益,并随后检测关联的能力。使用我们的框架,我们还基于平均IBD共享和近交同胞之间共享的方差来计算人口规模估计量的方差。最后,我们在混合脉冲模型中研究了IBD共享,并表明在Ashkenazi犹太人口中,混合分数与队列平均共享相关。

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