Accounting for genetic differences among unknown parents in microevolutionary studies: how to include genetic groups in quantitative genetic animal models

Quantifying and predicting microevolutionary responses to environmental change requires unbiased estimation of quantitative genetic parameters in wild populations. ‘Animal models’, which utilize pedigree data to separate genetic and environmental effects on phenotypes, provide powerful means to estimate key parameters and have revolutionized quantitative genetic analyses of wild populations.
However, pedigrees collected in wild populations commonly contain many individuals with unknown parents. When unknown parents are non-randomly associated with genetic values for focal traits, animal model parameter estimates can be severely biased. Yet, such bias has not previously been highlighted and statistical methods designed to minimize such biases have not been implemented in evolutionary ecology.
We first illustrate how the occurrence of non-random unknown parents in population pedigrees can substantially bias animal model predictions of breeding values and estimates of additive genetic va...

量化并预测环境变化下的微进化响应，需对野生种群中的定量遗传参数开展无偏估计。借助系谱数据分离表型的遗传与环境效应的‘动物模型（Animal model）’，为关键参数的估算提供了强有力的手段，彻底革新了野生种群的定量遗传分析范式。
然而，野生种群中采集的系谱往往包含大量亲本信息未知的个体。若未知亲本与目标性状的遗传值存在非随机关联，则动物模型的参数估计结果会出现严重偏倚。但此前该类偏倚并未得到学界关注，且进化生态学领域尚未开发出旨在最小化此类偏倚的统计方法。
我们首先阐明了种群系谱中非随机未知亲本的出现，会如何显著偏倚动物模型对育种值的预测以及加性遗传方差的估计……