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Estimates of genetic parameters for growth traits in Brahman cattle using random regression and multitrait models

机译:用随机回归和多焦点模型估计婆罗门牛生长性状的遗传参数

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Random regression models (RRM) and multitrait models (MTM) were used to estimate genetic parameters for growth traits in Brazilian Brahman cattle and to compare the estimated breeding values obtained by these 2 methodologies. For RRM, 78,641 weight records taken between 60 and 550 d of age from 16,204 cattle were analyzed, and for MTM, the analysis consisted of 17,385 weight records taken at the same ages from 12,925 cattle. All models included the fixed effects of contemporary group and the additive genetic, maternal genetic, and animal permanent environmental effects and the quadratic effect of age at calving (AAC) as covariate. For RRM, the AAC was nested in the animal's age class. The best RRM considered cubic polynomials and the residual variance heterogeneity (5 levels). For MTM, the weights were adjusted for standard ages. For RRM, additive heritability estimates ranged from 0.42 to 0.75, and for MTM, the estimates ranged from 0.44 to 0.72 for both models at 60, 120, 205, 365, and 550 d of age. The maximum maternal heritability estimate (0.08) was at 140 d for RRM, but for MTM, it was highest at weaning (0.09). The magnitude of the genetic correlations was generally from moderate to high. The RRM adequately modeled changes in variance or covariance with age, and provided there was sufficient number of samples, increased accuracy in the estimation of the genetic parameters can be expected. Correlation of bull classifications were different in both methods and at all the ages evaluated, especially at high selection intensities, which could affect the response to selection.
机译:随机回归模型(RRM)和多型模型(MTM)用于估算巴西Brahman牛生长性状的遗传参数,并比较这两种方法获得的估计育种值。对于RRM,分析了78,641次以上,从16,204次养牛的60%和550 d之间的重量记录,并且用于MTM,分析由12,925次牛的同一年龄段采用17,385次重量。所有模型包括当代组和添加剂遗传,母体遗传,动物永久性环境影响的固定效果以及在Calcing(AAC)中的年龄的二次效果。对于RRM,AAC嵌套在动物的年龄阶级。最佳RRM认为立方多项式和残留方差异质性(5级)。对于MTM,调整重量以进行标准年龄。对于RRM,附加遗传性估计范围为0.42至0.75,对于MTM,估计值为0.44至0.72,适用于60,120,205,365和550 d时的模型。最大母体遗传性估计(0.08)为RRM的140 d,但对于MTM,在断奶中最高(0.09)。遗传相关的幅度通常是中等至高的。 RRM与年龄的差异或协方差的变化进行了充分建模的,并且提供了足够数量的样品,可以预期估计遗传参数的提高精度。两种方法和在评估的所有年龄的情况下,公牛分类的相关性不同,特别是在高选择强度,这可能影响对选择的响应。

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