Comparing estimates of genetic variance across different relationship models
Comparing estimates of genetic variance across different relationship models
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DOI：
10.1016/j.tpb.2015.08.005
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发表时间：
2016-02-01
影响因子：
1.4
通讯作者：
Legarra, Andres
中科院分区：
文献类型：
--
作者：
Legarra, Andres
使用个体之间的关系通过混合模型来估计遗传方差和遗传力是人类、植物和牲畜遗传学的标准实践。不同的关系模型或信息可能会给出不同的遗传方差估计。然而，在不同的关系模型之间比较这些估计值并不简单，因为关系模型之间隐含的基础人群不同。在这项工作中，我提出了一种方法来比较不同的关系模型的方差分量的估计。我建议将使用不同关系模型获得的遗传方差引用到同一参考群体，通常是群体中的一组个体。该群体的预期遗传方差是来自混合模型的估计方差分量乘以统计量D-k，D-k是平均自身关系减去平均（自身和交叉）关系。对于大多数典型的关系模型，D-k接近于1。然而，这是不正确的非常深的系谱，身份的状态关系，或非参数内核，往往高估的遗传方差和遗传力。使用小鼠的数据，我表明，从身份的状态和内核为基础的关系的遗传力被高估。通过D-k对这些估计值进行加权，将它们缩放到与基因组或谱系关系相当的基础上，避免错误的比较，例如“缺失遗传力”。(C)2015 Elsevier Inc. All rights reserved.
Use of relationships between individuals to estimate genetic variances and heritabilities via mixed models is standard practice in human, plant and livestock genetics. Different models or information for relationships may give different estimates of genetic variances. However, comparing these estimates across different relationship models is not straightforward as the implied base populations differ between relationship models. In this work, I present a method to compare estimates of variance components across different relationship models. I suggest referring genetic variances obtained using different relationship models to the same reference population, usually a set of individuals in the population. Expected genetic variance of this population is the estimated variance component from the mixed model times a statistic, D-k, which is the average self-relationship minus the average (self- and across-) relationship. For most typical models of relationships, D-k is close to 1. However, this is not true for very deep pedigrees, for identity-by-state relationships, or for non-parametric kernels, which tend to overestimate the genetic variance and the heritability. Using mice data, I show that heritabilities from identity-by-state and kernel-based relationships are overestimated. Weighting these estimates by D-k scales them to a base comparable to genomic or pedigree relationships, avoiding wrong comparisons, for instance, "missing heritabilities". (C) 2015 Elsevier Inc. All rights reserved.