Genomic Selection for Milk Production Traits in Xinjiang Brown Cattle.
Genomic Selection for Milk Production Traits in Xinjiang Brown Cattle.
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新疆褐牛产奶性状的基因组选择
DOI：
10.3390/ani12020136
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发表时间：
2022-01-07
期刊：
影响因子：
--
通讯作者：
Wang Y
中科院分区：
文献类型：
--
作者：
Zhang M;Luo H;Xu L;Shi Y;Zhou J;Wang D;Zhang X;Huang X;Wang Y
产奶量是新疆褐牛育种和遗传改良的重要性状。为了获得提高每个性状育种值估计可靠性的最佳策略，我们使用基于A-阵列谱系最佳线性无偏预测（PBLUP）和H-阵列单步基因组最佳线性无偏预测（ssGBLUP）的单性状和多性状模型，使用限制最大似然（REML）和贝叶斯方法对不同策略进行遗传评估。经比较，使用REML和贝叶斯方法获得的多性状模型的ssGBLUP计算结果优于其他策略。考虑到计算时间，建议采用多性状模型REML方法进行ssGBLUP计算，以准确预测幼龄动物的育种值，该策略可用于新疆褐牛的早期育种选择。一步基因组选择是一种提高育种值估计可靠性的方法。本研究旨在比较基于家系的最佳线性无偏预测（PBLUP）和单步基因组最佳线性无偏预测（ssGBLUP）、单性状和多性状模型以及限制最大似然法（REML）和贝叶斯方法的可靠性。数据来源于1983 - 2018年新疆2207头新疆褐牛的生产性能记录。采用正交试验设计，计算新疆褐牛305 dMY、MFY、MPY、SCS的遗传参数和育种值的可靠性。使用REML和贝叶斯多性状模型估计的305 dMY、MFY、MPY和SCS的遗传力分别约为0.39（0.02）、0.40（0.03）、0.49（0.02）和0.07（0.02）。采用多性状模型REML和贝叶斯方法，基于PBLUP和ssGBLUP计算的奶牛产奶性状的遗传力、估计育种值（EBV）和可靠性均高于单性状模型REML方法; ssGBLUP方法显著优于PBLUP方法。遗传育种值的可靠性从0.9%提高到3.6%，基因组遗传育种值（GEBV）的可靠性可达83%。因此，多性状模型的遗传评价优于单性状模型。因此，基因组选择可应用于新疆褐牛等小群体品种，在提高基因组估计育种值的可靠性方面具有一定的应用价值。
Milk production is an important trait in the breeding and genetic improvement of Xinjiang Brown cattle. To obtain the best strategy for improving the reliability of the breeding value estimation for each trait, we used single-trait and multitrait models based on the A-array pedigree-based best linear unbiased prediction (PBLUP) and H-array single-step genomic best linear unbiased prediction (ssGBLUP) to perform the genetic evaluation of different strategies using the restricted maximum likelihood (REML) and Bayesian methods. Upon comparison, the ssGBLUP calculation results of the multitrait models obtained using the REML and Bayesian methods were better than those of other strategies. Considering the calculation time, the multitrait model REML method is recommended for ssGBLUP calculation to accurately predict the breeding value of young animals; thus, this strategy should be used for the early breeding selection of Xinjiang Brown cattle. One-step genomic selection is a method for improving the reliability of the breeding value estimation. This study aimed to compare the reliability of pedigree-based best linear unbiased prediction (PBLUP) and single-step genomic best linear unbiased prediction (ssGBLUP), single-trait and multitrait models, and the restricted maximum likelihood (REML) and Bayesian methods. Data were collected from the production performance records of 2207 Xinjiang Brown cattle in Xinjiang from 1983 to 2018. A cross test was designed to calculate the genetic parameters and reliability of the breeding value of 305 daily milk yield (305 dMY), milk fat yield (MFY), milk protein yield (MPY), and somatic cell score (SCS) of Xinjiang Brown cattle. The heritability of 305 dMY, MFY, MPY, and SCS estimated using the REML and Bayesian multitrait models was approximately 0.39 (0.02), 0.40 (0.03), 0.49 (0.02), and 0.07 (0.02), respectively. The heritability and estimated breeding value (EBV) and the reliability of milk production traits of these cattle calculated based on PBLUP and ssGBLUP using the multitrait model REML and Bayesian methods were higher than those of the single-trait model REML method; the ssGBLUP method was significantly better than the PBLUP method. The reliability of the estimated breeding value can be improved from 0.9% to 3.6%, and the reliability of the genomic estimated breeding value (GEBV) for the genotyped population can reach 83%. Therefore, the genetic evaluation of the multitrait model is better than that of the single-trait model. Thus, genomic selection can be applied to small population varieties such as Xinjiang Brown cattle, in improving the reliability of the genomic estimated breeding value.
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影响因子：
3.3
作者：
Habier, D.;Fernando, R. L.;Dekkers, J. C. M.
通讯作者：
Dekkers, J. C. M.
影响因子：
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3.5
作者：
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影响因子：
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作者：
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通讯作者：
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