Department of Animal Sciences, Purdue University, West Lafayette, IN 47907; Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, Sichuan, 611130, China.
Department of Animal Sciences, Purdue University, West Lafayette, IN 47907.
J Dairy Sci. 2024 Feb;107(2):1035-1053. doi: 10.3168/jds.2023-23650. Epub 2023 Sep 29.
Breeding more resilient animals will benefit the dairy cattle industry in the long term, especially as global climate changes become more severe. Previous studies have reported genetic parameters for various milk yield-based resilience indicators, but the underlying genomic background of these traits remain unknown. In this study, we conducted GWAS of 62,029 SNPs with 4 milk yield-based resilience indicators, including the weighted occurrence frequency (wfPert) and accumulated milk losses (dPert) of milk yield perturbations, and log-transformed variance (LnVar) and lag-1 autocorrelation (r) of daily yield residuals. These variables were previously derived from 5.6 million daily milk yield records from 21,350 lactations (parities 1-3) of 11,787 North American Holstein cows. The average daily milk yield (ADMY) throughout lactation was also included to compare the shared genetic background of resilience indicators with milk yield. The differential genetic background of these indicators was first revealed by the significant genomic regions identified and significantly enriched biological pathways of positional candidate genes, which confirmed the genetic difference among resilience indicators. Interestingly, the functional analyses of candidate genes suggested that the regulation of intestinal homeostasis is most likely affecting resilience derived based on variability in milk yield. Based on Mendelian randomization analyses of multiple instrumental SNPs, we further found an unfavorable causal association of ADMY with LnVar. In conclusion, the resilience indicators evaluated are genetically different traits, and there are causal associations of milk yield with some of the resilience indicators evaluated. In addition to providing biological insights into the molecular regulation mechanisms of resilience derived based on variability in milk yield, this study also indicates the need for developing selection indexes combining multiple indicator traits and taking into account their genetic relationship for breeding more resilient dairy cattle.
培育更具弹性的动物将从长远来看有利于奶牛养殖业，尤其是随着全球气候变化变得更加严重。先前的研究已经报道了各种基于产奶量的弹性指标的遗传参数，但这些性状的潜在基因组背景仍不清楚。在这项研究中，我们对 62029 个 SNP 进行了基于产奶量的 4 个弹性指标的 GWAS，包括产奶量波动的加权发生频率（wfPert）和累积产奶量损失（dPert），以及对数变换方差（LnVar）和日产量残差的滞后 1 自相关（r）。这些变量是从前 21350 个泌乳期（胎次 1-3）的 11787 头北美荷斯坦奶牛的 560 万条日产奶量记录中得出的，包括整个泌乳期的平均日产奶量（ADMY），以比较弹性指标与产奶量的共同遗传背景。通过确定的显著基因组区域和显著富集的位置候选基因的生物学途径，首次揭示了这些指标的差异遗传背景，证实了弹性指标之间的遗传差异。有趣的是，候选基因的功能分析表明，肠道稳态的调节最有可能影响基于产奶量变化的弹性。基于对多个工具 SNP 的孟德尔随机化分析，我们进一步发现 ADMY 与 LnVar 之间存在不利的因果关联。总之，评估的弹性指标是具有遗传差异的性状，并且产奶量与评估的某些弹性指标之间存在因果关联。除了为基于产奶量变化的弹性的分子调控机制提供生物学见解外，本研究还表明需要开发结合多个指标性状的选择指数，并考虑它们的遗传关系，以培育更具弹性的奶牛。
