Quantification of inbreeding due to distant ancestors and its detection using dense single nucleotide polymorphism data.
Quantification of inbreeding due to distant ancestors and its detection using dense single nucleotide polymorphism data.
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DOI：
10.1534/genetics.111.130922
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发表时间：
2011-09
期刊：
影响因子：
3.3
通讯作者：
Goddard ME
中科院分区：
文献类型：
--
作者：
Keller MC;Visscher PM;Goddard ME
近亲繁殖抑郁症，指的是亲缘关系亲缘关系的后代之间的适应性降低，传统上是用谱系来研究的。在实践中，谱系信息很难获得，可能不可靠，并且很少评估来自生活在几代以前的共同祖先的近亲繁殖。最近，人们对使用SNP数据来估计在明显的“近亲繁殖”种群中由遥远的共同祖先产生的近亲繁殖(F)感到兴奋。使用SNP数据检测近交抑制的统计能力取决于种群中近交的实际变化、使用标记数据检测近交抑制的准确性、效应大小和样本量。目前还没有人研究过SNP数据中F的变化作为种群大小的函数，也不清楚哪种F的估计对于检测近亲繁殖抑制是最佳的。在本研究中，我们使用理论、模拟遗传数据和实际遗传数据来寻找F的最佳估计值，量化不同大小群体中F的可能变化，并估计检测近交抑制的能力。我们发现，从纯合性（Froh）中估计的F，反映了遗传单倍型的共同祖先，即使在大群体中也能保持变异（例如，当Ne = 10,000时，SD = 0.5%），并且可能是从几个F的替代估计中检测近交效应的最有效方法。然而，为了可能的效应大小，检测近交抑制将需要大样本（例如，12,000-65,000）。所以迄今为止使用Froh的研究可能不够有力。
Inbreeding depression, which refers to reduced fitness among offspring of related parents, has traditionally been studied using pedigrees. In practice, pedigree information is difficult to obtain, potentially unreliable, and rarely assessed for inbreeding arising from common ancestors who lived more than a few generations ago. Recently, there has been excitement about using SNP data to estimate inbreeding (F) arising from distant common ancestors in apparently “outbred” populations. Statistical power to detect inbreeding depression using SNP data depends on the actual variation in inbreeding in a population, the accuracy of detecting that with marker data, the effect size, and the sample size. No one has yet investigated what variation in F is expected in SNP data as a function of population size, and it is unclear which estimate of F is optimal for detecting inbreeding depression. In the present study, we use theory, simulated genetic data, and real genetic data to find the optimal estimate of F, to quantify the likely variation in F in populations of various sizes, and to estimate the power to detect inbreeding depression. We find that F estimated from runs of homozygosity (Froh), which reflects shared ancestry of genetic haplotypes, retains variation in even large populations (e.g., SD = 0.5% when Ne = 10,000) and is likely to be the most powerful method of detecting inbreeding effects from among several alternative estimates of F. However, large samples (e.g., 12,000–65,000) will be required to detect inbreeding depression for likely effect sizes, and so studies using Froh to date have probably been underpowered.