论文标题
具有优势的无限模型
The infinitesimal model with dominance
论文作者
论文摘要
经典的无限模型是定量性状遗传的简单且可靠的模型。在该模型中,定量性状表示为遗传和非遗传(环境)成分的总和,以及一个家庭中后代性状的遗传成分遵循父母特征值平均值的正态分布,并且具有与父母特征值无关的方差。在先前的工作中,Barton等人(2017年),我们表明,当特征值由大量门德尔因素的总和确定时,每个效应都可以证明无穷小模型是孟德尔遗传的限制。 在本文中,我们表明,无限模型的鲁棒性扩展到包括优势。我们根据经典的定量遗传学来定义模型,然后将其视为孟德尔遗传的限制,因为它是基础基因座的数字m,倾向于无穷大。与加性情况一样,可以用祖先人群中的方差成分来表达性状值的多元正态分布,并通过谱系确定的下降来表达身份的概率。在这种情况下,分解性状值不仅是添加剂和优势组成部分,而且分解为家庭中所有个体和每个后代独立的“残留”组成部分,这是很自然的,该组件捕获了Mendelian遗传的随机性。我们表明,即使我们根据父母性状值进行条件,每个家族中共享的组件和残差都将在正态上正态分布,因为基因座的数量倾向于无穷大,并有1/\ sqrt {m}的误差。 我们用一些数值示例来说明结果。
The classical infinitesimal model is a simple and robust model for the inheritance of quantitative traits. In this model, a quantitative trait is expressed as the sum of a genetic and a non-genetic (environmental) component and the genetic component of offspring traits within a family follows a normal distribution around the average of the parents' trait values, and has a variance that is independent of the trait values of the parents. In previous work, Barton et al.(2017), we showed that when trait values are determined by the sum of a large number of Mendelian factors, each of small effect, one can justify the infinitesimal model as limit of Mendelian inheritance. In this paper, we show that the robustness of the infinitesimal model extends to include dominance. We define the model in terms of classical quantities of quantitative genetics, before justifying it as a limit of Mendelian inheritance as the number, M, of underlying loci tends to infinity. As in the additive case, the multivariate normal distribution of trait values across the pedigree can be expressed in terms of variance components in an ancestral population and probabilities of identity by descent determined by the pedigree. In this setting, it is natural to decompose trait values, not just into the additive and dominance components, but into a component that is shared by all individuals within the family and an independent `residual' for each offspring, which captures the randomness of Mendelian inheritance. We show that, even if we condition on parental trait values, both the shared component and the residuals within each family will be asymptotically normally distributed as the number of loci tends to infinity, with an error of order 1/\sqrt{M}. We illustrate our results with some numerical examples.