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The contribution of dominance to the understanding of quantitative genetic variation

机译：优势对定量遗传变异的理解的贡献

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摘要

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.
机译：数量性状遗传结构的知识对于调整预测基因组育种值的方法以及发现定量性状基因座（QTL）作图实验和育种价值估算中常见假设遭到违反的程度非常有用。它还会影响我们预测选择的长期响应的能力。在本文中，我们关注QTL的加性和优势效应。我们推导了可用于估算影响数量特征的QTL数量的公式，这些参数来自方差分量，近交衰退和QTL映射实验的结果，其加性和优势效应的分布参数。结果表明，QTL数量的下限取决于近交抑制度平方与优势方差之比。就是说，高度近亲抑郁症必须归因于足够数量的QTL，因为否则，优势差异将超过真实值。此外，优势系数的第二矩仅取决于优势方差与加性方差之比，以及加性效应与优势系数之间的依存关系。这对占主导地位的等位基因的相对频率有影响。还证明了预期的大QTL数量如何确定加性效应分布的形状。该公式适用于荷斯坦奶牛的产奶量和生产寿命。讨论了可能导致结果偏差的来源。

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