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Estimating dominance genetic variances for growth traits in American Angus males using genomic models

机译:使用基因组模型估算美国安格斯男性生长特性的优势遗传方差

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摘要

Estimates of dominance variance for growth traits in beef cattle based on pedigree data vary considerably across studies, and the proportion of genetic variance explained by dominance deviations remains largely unknown. The potential benefits of including nonadditive genetic effects in the genomic model combined with the increasing availability of large genomic data sets have recently renewed the interest in including nonadditive genetic effects in genomic evaluation models. The availability of genomic information enables the computation of covariance matrices of dominant genomic relationships among animals, similar to matrices of additive genomic relationships, and in a more straightforward manner than the pedigree-based dominance relationship matrix. Data from 19,357 genotyped American Angus males were used to estimate additive and dominant variance components for 3 growth traits: birth weight, weaning weight, and postweaning gain, and to evaluate the benefit of including dominance effects in beef cattle genomic evaluations. Variance components were estimated using 2 models: the first one included only additive effects ( ) and the second one included both additive and dominance effects ( ). The dominance deviation variance ranged from 3% to 8% of the additive variance for all 3 traits. Gibbs sampling and REML estimates showed good concordance. Goodness of fit of the models was assessed by a likelihood ratio test. For all traits, MG fitted the data as well as MGD as assessed either by the likelihood ratio test or by the Akaike information criterion. Predictive ability of both models was assessed by cross-validation and did not improve when including dominance effects in the model. There was little evidence of nonadditive genetic variation for growth traits in the American Angus male population as only a small proportion of genetic variation was explained by nonadditive effects. A genomic model including the dominance effect did not improve the model fit. Consequently, including nonadditive effects in the genomic evaluation model is not beneficial for growth traits in the American Angus male population.
机译:在不同的研究中,基于系谱数据对肉牛生长性状的优势变异估计值有很大差异,并且由遗传优势变异解释的遗传变异比例仍然未知。近来,在基因组模型中包含非加性遗传效应的潜在好处,以及大型基因组数据集的可用性日益提高,重新引起了人们的兴趣,将非累加性遗传效应纳入基因组评估模型。基因组信息的可用性使得能够计算动物之间主要基因组关系的协方差矩阵,类似于加性基因组关系矩阵,并且比基于谱系的优势关系矩阵更直接。来自19,357个基因型美国安格斯(Angus)雄性的数据用于估算3个生长性状的加性和显性方差成分:出生体重,断奶体重和断奶后增重,并评估在肉牛基因组评估中包括优势效应的益处。方差分量使用​​2个模型进行估算:第一个模型仅包含加性效应(),第二个模型既包含加性效应也包括优势效应()。对于所有3个性状,优势偏差方差为加性方差的3%至8%。 Gibbs抽样和REML估计显示出良好的一致性。通过似然比检验评估模型的拟合优度。对于所有性状,MG拟合数据以及通过似然比检验或Akaike信息标准评估的MGD。两种模型的预测能力均通过交叉验证进行了评估,当在模型中包含优势效应时并没有提高。几乎没有证据表明美国安格斯男性人口的生长性状具有非加性遗传变异,因为只有一小部分遗传变异是由非加性效应解释的。包括优势效应的基因组模型并不能改善模型拟合。因此,在基因组评估模型中包括非累加效应对美国安格斯男性种群的生长特性无益。

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