Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE), University of Padova, Legnaro, Padova, Italy.
Department of Animal Science, Food and Nutrition (DIANA), Università Cattolica del Sacro Cuore, Piacenza, Italy.
J Anim Sci. 2024 Jan 3;102. doi: 10.1093/jas/skae271.
During lactation, high-yielding cows experience metabolic disturbances due to milk production. Metabolic monitoring offers valuable insights into how cows manage these challenges throughout the lactation period, making it a topic of considerable interest to breeders. In this study, we used Bayesian networks to uncover potential dependencies among various energy-related blood metabolites, i.e., glucose, urea, beta-hydroxybutyrate (BHB), non-esterified fatty acids (NEFA), cholesterol (CHOL), and daily milk energy output (dMEO) in 1,254 Holstein cows. The inferred causal structure was then incorporated into structural equation models (SEM) to estimate heritabilities and additive genetic correlations among these phenotypes using both pedigree and genotypes from a 100k chip. Dependencies among traits were determined using the Hill-Climbing algorithm, implemented with the posterior distribution of the residuals obtained from the standard multiple-trait model. These identified relationships were then used to construct the SEM, considering both direct and indirect relationships. The relevant dependencies and path coefficients obtained, expressed in units of measurement variation of 1σ, were as follows: dMEO → CHOL (0.181), dMEO → BHB (-0.149), dMEO → urea (0.038), glucose → BHB (-0.55), glucose → urea (-0.194), CHOL → urea (0.175), BHB → urea (-0.049), and NEFA → urea (-0.097). Heritabilities for traits of concern obtained with SEM ranged from 0.09 to 0.2. Genetic correlations with a minimum 95% probability (P) of the posterior mean being >0 for positive means or <0 for negative means include those between dMEO and glucose (-0.583, P = 100), dMEO and BHB (0.349, P = 99), glucose and CHOL (0.325, P = 100), glucose and NEFA (-0.388, P = 100), and NEFA and BHB (0.759, P = 100). The results of this analysis revealed the existence of recursive relationships among the energy-related blood metabolites and dMEO. Understanding these connections is paramount for establishing effective genetic selection strategies, enhancing production and animal welfare.
在哺乳期，高产奶牛会因产奶而出现代谢紊乱。代谢监测可以深入了解奶牛在整个哺乳期如何应对这些挑战，因此成为了养殖者非常关注的话题。在这项研究中，我们使用贝叶斯网络揭示了 1254 头荷斯坦奶牛中各种与能量相关的血液代谢物（葡萄糖、尿素、β-羟丁酸（BHB）、非酯化脂肪酸（NEFA）、胆固醇（CHOL）和每日奶能量输出（dMEO）之间的潜在依赖关系。然后，将推断出的因果结构纳入结构方程模型（SEM）中，使用来自 100k 芯片的系谱和基因型来估计这些表型的遗传力和加性遗传相关。使用 Hill-Climbing 算法确定性状之间的依赖关系，该算法使用从标准多性状模型获得的残差的后验分布来实现。然后，使用这些确定的关系构建 SEM，同时考虑直接和间接关系。以测量变异 1σ 的单位表示，获得的相关依赖关系和路径系数如下：dMEO→CHOL（0.181），dMEO→BHB（-0.149），dMEO→urea（0.038），glucose→BHB（-0.55），glucose→urea（-0.194），CHOL→urea（0.175），BHB→urea（-0.049），和 NEFA→urea（-0.097）。使用 SEM 获得的关注性状的遗传力范围为 0.09 到 0.2。具有正均值的后验均值概率（P）大于 95%或具有负均值的后验均值概率（P）小于 95%的遗传相关包括 dMEO 和葡萄糖之间的遗传相关（-0.583，P=100），dMEO 和 BHB 之间的遗传相关（0.349，P=99），葡萄糖和 CHOL 之间的遗传相关（0.325，P=100），葡萄糖和 NEFA 之间的遗传相关（-0.388，P=100），以及 NEFA 和 BHB 之间的遗传相关（0.759，P=100）。这项分析的结果揭示了与能量相关的血液代谢物和 dMEO 之间存在递归关系。了解这些联系对于建立有效的遗传选择策略、提高生产效率和动物福利至关重要。
