Non-additive genetic effects are usually ignored in animal breeding programs due to data structure (e.g., incomplete pedigree), computational limitations and over-parameterization of the models. However, non-additive genetic effects may play an important role in the expression of complex traits in livestock species, such as fertility and reproduction traits. In this study, components of genetic variance for additive and non-additive genetic effects were estimated for a variety of fertility and reproduction traits in Holstein cattle using pedigree and genomic relationship matrices. Four linear models were used: (a) an additive genetic model; (b) a model including both additive and epistatic (additive by additive) genetic effects; (c) a model including both additive and dominance effects; and (d) a full model including additive, epistatic and dominance genetic effects. Nine fertility and reproduction traits were analysed, and models were run separately for heifers (N = 5,825) and cows (N = 6,090). For some traits, a larger proportion of phenotypic variance was explained by non-additive genetic effects compared with additive effects, indicating that epistasis, dominance or a combination thereof is of great importance. Epistatic genetic effects contributed more to the total phenotypic variance than dominance genetic effects. Although these models varied considerably in the partitioning of the components of genetic variance, the models including a non-additive genetic effect did not show a clear advantage over the additive model based on the Akaike information criterion. The partitioning of variance components resulted in a re-ranking of cows based solely on the cows' additive genetic effects between models, indicating that adjusting for non-additive genetic effects could affect selection decisions made in dairy cattle breeding programs. These results suggest that non-additive genetic effects play an important role in some fertility and reproduction traits in Holstein cattle.

中文翻译：

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使用基因组信息估计北美荷斯坦牛生育力和繁殖性状的加性和非加性遗传效应

由于数据结构（例如，不完整的谱系）、计算限制和模型的过度参数化，在动物育种程序中通常会忽略非加性遗传效应。然而，非加性遗传效应可能在牲畜物种复杂性状的表达中发挥重要作用，例如生育力和繁殖性状。在这项研究中，使用谱系和基因组关系矩阵估计了荷斯坦牛的各种生育力和繁殖性状的加性和非加性遗传效应的遗传方差分量。使用了四种线性模型： (a) 加性遗传模型；(b) 包括加性和上位性（加性加加性）遗传效应的模型；(c) 包括加性效应和支配效应的模型；(d) 包括加法在内的完整模型，上位性和显性遗传效应。分析了九个生育力和繁殖性状，并分别为小母牛（N = 5,825）和奶牛（N = 6,090）运行模型。对于某些性状，与加性效应相比，非加性遗传效应解释了更大比例的表型变异，表明上位性、显性或其组合非常重要。上位遗传效应对总表型变异的贡献大于显性遗传效应。尽管这些模型在遗传方差分量的划分上差异很大，但包含非加性遗传效应的模型并没有显示出优于基于 Akaike 信息准则的加性模型的明显优势。方差分量的划分导致仅基于奶牛的奶牛重新排名 模型之间的加性遗传效应，表明调整非加性遗传效应可能会影响奶牛育种计划中的选择决策。这些结果表明，非加性遗传效应在荷斯坦牛的某些生育力和繁殖性状中起着重要作用。