TYR, Storhamargata 44, 2317, Hamar, Norway.
Center for Quantitative Genetics and Genomics, Aarhus University, 8830 Tjele, Denmark.
J Anim Sci. 2021 Sep 1;99(9). doi: 10.1093/jas/skab231.
Rates of gain and feed efficiency are important traits in most breeding programs for growing farm animals. The rate of gain (GAIN) is usually expressed over a certain age period and feed efficiency is often expressed as residual feed intake (RFI), defined as observed feed intake (FI) minus expected feed intake based on live weight (WGT) and GAIN. However, the basic traits recorded are always WGT and FI and other traits are derived from these basic records. The aim of this study was to develop a procedure for simultaneous analysis of the basic records and then derive linear traits related to feed efficiency without retorting to any approximation. A bivariate longitudinal random regression model was employed on 13,791 individual longitudinal records of WGT and FI from 2,827 bulls of six different beef breeds tested for their own performance in the period from 7 to 13 mo of age. Genetic and permanent environmental covariance functions for curves of WGT and FI were estimated using Gibbs sampling. Genetic and permanent covariance functions for curves of GAIN were estimated from the first derivative of the function for WGT and finally the covariance functions were extended to curves for RFI, based on the conditional distribution of FI given WGT and GAIN. Furthermore, the covariance functions were extended to include GAIN and RFI defined over different periods of the performance test. These periods included the whole test period as normally used when predicting breeding values for GAIN and RFI for beef bulls. Based on the presented method, breeding values and genetic parameters for derived traits such as GAIN and RFI defined longitudinally or integrated over (parts of) of the test period can be obtained from a joint analysis of the basic records. The resulting covariance functions for WGT, FI, GAIN, and RFI are usually singular but the method presented here does not suffer from the estimation problems associated with defining these traits individually before the genetic analysis. All the results are thus estimated simultaneously, and the set of parameters is consistent.
在大多数生长家畜的育种计划中,增长率和饲料效率都是重要的特征。增长率(GAIN)通常在一定的年龄期内表示,而饲料效率通常表示为剩余饲料摄入量(RFI),定义为观察到的饲料摄入量(FI)减去基于活重(WGT)和 GAIN 的预期饲料摄入量。然而,记录的基本特征始终是 WGT 和 FI,其他特征是从这些基本记录中得出的。本研究的目的是开发一种同时分析基本记录的程序,然后在不进行任何近似的情况下推导出与饲料效率相关的线性特征。采用双变量纵向随机回归模型,对 6 个不同肉牛品种的 2827 头公牛在 7 至 13 月龄期间进行自身性能测试的 13791 个个体纵向 WGT 和 FI 记录进行了分析。使用 Gibbs 抽样估计 WGT 和 FI 曲线的遗传和永久环境协方差函数。基于 WGT 和 GAIN 函数的一阶导数,估计 GAIN 曲线的遗传和永久协方差函数,最后基于 FI 给 WGT 和 GAIN 的条件分布,将协方差函数扩展到 RFI 曲线。此外,将协方差函数扩展到包括在性能测试的不同时期定义的 GAIN 和 RFI。这些时期包括通常用于预测肉牛 GAIN 和 RFI 育种值的整个测试期。基于所提出的方法,可以从基本记录的联合分析中获得纵向定义或在(部分)测试期内综合定义的衍生特征(如 GAIN 和 RFI)的育种值和遗传参数。WGT、FI、GAIN 和 RFI 的协方差函数通常是奇异的,但这里提出的方法不会受到在遗传分析之前单独定义这些特征所带来的估计问题的影响。因此,所有结果都是同时估计的,参数集是一致的。