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显性在理解数量遗传变异中的作用。

The contribution of dominance to the understanding of quantitative genetic variation.

作者信息

Wellmann Robin, Bennewitz Jörn

机构信息

Department of Animal Husbandry and Animal Breeding, University of Hohenheim, D-70599 Stuttgart, Germany.

出版信息

Genet Res (Camb). 2011 Apr;93(2):139-54. doi: 10.1017/S0016672310000649. Epub 2011 Apr 12.

Abstract

Knowledge of the genetic architecture of a quantitative trait is useful to adjust methods for the prediction of genomic breeding values and to discover the extent to which common assumptions in quantitative trait locus (QTL) mapping experiments and breeding value estimation are violated. It also affects our ability to predict the long-term response of selection. In this paper, we focus on additive and dominance effects of QTL. We derive formulae that can be used to estimate the number of QTLs that affect a quantitative trait and parameters of the distribution of their additive and dominance effects from variance components, inbreeding depression and results from QTL mapping experiments. It is shown that a lower bound for the number of QTLs depends on the ratio of squared inbreeding depression to dominance variance. That is, high inbreeding depression must be due to a sufficient number of QTLs because otherwise the dominance variance would exceed the true value. Moreover, the second moment of the dominance coefficient depends only on the ratio of dominance variance to additive variance and on the dependency between additive effects and dominance coefficients. This has implications on the relative frequency of overdominant alleles. It is also demonstrated how the expected number of large QTLs determines the shape of the distribution of additive effects. The formulae are applied to milk yield and productive life in Holstein cattle. Possible sources for a potential bias of the results are discussed.

摘要

了解数量性状的遗传结构,有助于调整基因组育种值预测方法,揭示数量性状基因座(QTL)定位实验和育种值估计中常见假设被违背的程度。它还会影响我们预测选择长期反应的能力。在本文中,我们聚焦于QTL的加性效应和显性效应。我们推导了一些公式,可用于从方差分量、近交衰退以及QTL定位实验结果中,估计影响数量性状的QTL数量及其加性效应和显性效应分布的参数。结果表明,QTL数量的下限取决于近交衰退平方与显性方差的比值。也就是说,高近交衰退必定源于足够数量的QTL,否则显性方差会超过真实值。此外,显性系数的二阶矩仅取决于显性方差与加性方差的比值以及加性效应和显性系数之间的相关性。这对超显性等位基因的相对频率有影响。还证明了大QTL的预期数量如何决定加性效应分布的形状。这些公式应用于荷斯坦奶牛的产奶量和生产寿命,并讨论了结果可能存在偏差的潜在来源。

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