Oliveira Hinayah R, Brito Luiz F, Miller Stephen P, Schenkel Flavio S
Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada.
Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA.
Animals (Basel). 2020 Dec 16;10(12):2410. doi: 10.3390/ani10122410.
This study aimed to propose novel longevity indicators by comparing genetic parameters for traditional (TL; i.e., the cow's lifespan after the first calving) and functional (FL; i.e., how long the cow stayed in the herd while also calving; assuming no missing (FLa) or missing (FLb) records for unknown calving) longevity, considering different culling reasons (natural death, structural problems, disease, fertility, performance, and miscellaneous). Longevity definitions were evaluated from 2 to 15 years of age, using single- and multiple-trait Bayesian random regression models (RRM). The RRM fitting heterogenous residual variance and fourth order Legendre polynomials were considered as the optimal models for the majority of longevity indicators. The average heritability estimates over ages for FLb (from 0.08 to 0.25) were always higher than those for FLa (from 0.07 to 0.19), and higher or equal to the ones estimated for TL (from 0.07 to 0.23), considering the different culling reasons. The average genetic correlations estimated between ages were low to moderate (~0.40), for all longevity definitions and culling reasons. However, removing the extreme ages (i.e., 2 and >12 years) increased the average correlation between ages (from ~0.40 to >0.70). The genetic correlations estimated between culling reasons were low (0.12 and 0.20 on average, considering all ages and ages between 3 and 12 years old, respectively), indicating that longevity based on different culling reasons should be considered as different traits in the genetic evaluations. Higher average genetic correlations (estimated from 3 to 12 years old) were observed between TL and FLb (0.73) in comparison to TL and FLa (0.64), or FLa and FLb (0.65). Consequently, a higher average proportion of commonly-selected sires, for the top 1% sires, was also observed between TL and FLb (91.74%), compared to TL and FLa (59.68%), or FLa and FLb (61.01%). Higher prediction accuracies for the expected daughter performances (calculated based on the pedigree information) were obtained for FLb in comparison to TL and FLa. Our findings indicate that FLb is preferred for the genetic evaluation of longevity. In addition, it is recommended including multiple longevity traits based on different groups of culling reasons in a selection sub-index, as they are genetically-different traits. Genetic selection based on breeding values at the age of four years is expected to result in greater selection responses for increased longevity in North American Angus cattle.
本研究旨在通过比较传统寿命（TL，即首次产犊后奶牛的寿命）和功能寿命（FL，即奶牛在产犊的同时留在牛群中的时间；假设未知产犊记录无缺失（FLa）或有缺失（FLb））的遗传参数，考虑不同的淘汰原因（自然死亡、结构问题、疾病、繁殖力、性能和其他），提出新的长寿指标。使用单性状和多性状贝叶斯随机回归模型（RRM），对2至15岁的牛进行寿命定义评估。拟合异质残差方差和四阶勒让德多项式的RRM被认为是大多数长寿指标的最优模型。考虑到不同的淘汰原因，FLb各年龄的平均遗传力估计值（从0.08到0.25）始终高于FLa（从0.07到0.19），且高于或等于TL的估计值（从0.07到0.23）。对于所有寿命定义和淘汰原因，各年龄之间估计的平均遗传相关性较低至中等（约为0.40）。然而，去除极端年龄（即2岁和大于12岁）后，各年龄之间的平均相关性增加（从约0.40增至大于0.70）。淘汰原因之间估计的遗传相关性较低（分别考虑所有年龄和3至12岁年龄时，平均为0.12和0.20），这表明基于不同淘汰原因的寿命应在遗传评估中视为不同的性状。与TL和FLa（0.64）或FLa和FLb（0.65）相比，TL和FLb之间（0.73）在3至12岁之间观察到更高的平均遗传相关性。因此，对于排名前1%的公牛，TL和FLb之间（91.74%）共同选择的公牛平均比例也高于TL和FLa（59.68%）或FLa和FLb（61.01%）。与TL和FLa相比，FLb在预期女儿性能（基于系谱信息计算）方面获得了更高的预测准确性。我们 的研究结果表明，在长寿的遗传评估中FLb更受青睐。此外，建议在选择子指数中纳入基于不同淘汰原因组的多个长寿性状，因为它们是遗传上不同的性状。预计基于四岁时育种值的遗传选择将在北美安格斯牛中对延长寿命产生更大的选择反应。
