Shaffer William R, Hidalgo Jorge, Bello Nora M, Noland Rylie S, Bormann Jennifer M, Weaber Robert L, Ahlberg Cashley M, Bruno Kelsey, Krehbiel Clint R, Calvo-Lorenzo Michelle S, Richards Chris J, Place Sara, DeSilva Udaya, Kuehn Larry A, Rolf Megan M
Department of Animal Sciences and Industry, Kansas State University, Manhattan, KS 66506, USA.
Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USA.
J Anim Sci. 2025 Jan 4;103. doi: 10.1093/jas/skaf115.
Expected changes in climate warrant research on selection for a phenotypically stable cattle population that can perform consistently across diverse environmental conditions. In this study, we utilize a heteroscedastic random regression model to 1) characterize the additive genetic and other phenotypic components of dry matter intake (DMI) and respiration rate (RR) concerning the temperature humidity index (THI), 2) assess the presence of genotype-by-environment interactions (G × E) by determining whether the additive genetic reaction norm changes along the observed THI range and by evaluating the additive genetic correlations between DMI or RR at different THI values, and 3) evaluate model-derived accuracy of estimated breeding values (EBV) along a range of THI. Data consisted of repeated observations of DMI and RR on 788 and 569 steers, respectively, over a period of 70 d. A hierarchical model with subject-specific additive genetic and permanent environment effects was fitted to each trait using Bayesian inference. Estimated population slopes, expressed as posterior median and 95% highest posterior density (HPD) interval, were -0.046 (-0.053, -0.039) kg DMI per unit increase in THI per day and 0.027 (0.026, 0.029) breaths per 30s (BP30S) RR for each unit increase in THI on the logarithmic scale, thereby suggesting environmental sensitivity for both traits. Estimated correlations between the additive genetic intercept and slope were -0.78 (-0.86, -0.69) and -0.66 (-1.0, -0.20) for DMI and RR, respectively, indicating that selection for increased DMI and decreased RR at the onset of heat stress can be expected to associate positively with mean population environmental sensitivity to THI. Heritability estimates for DMI at the onset of heat stress (i.e., THI of 70) ranged from 0.30 (0.17, 0.44) to 0.37 (0.20, 0.48) across cohorts but decreased as THI increased. Heritability estimates for RR were low, with 95% HPD upper boundaries ranging from 0.03 to 0.08 across the range of THI evaluated. For DMI, the median additive genetic correlation between 70 and 85 THI and the Spearman correlations between EBV at 70 and 85 THI levels were 0.42 (0.26, 0.57) and 0.39 (0.26, 0.52), respectively, indicating substantial G × E. The median DMI EBV model-derived accuracy at a specific THI value increased from 70 THI to 0.65 at 82 THI, at which point it stabilized. This was likely because more data points were gathered at greater THI.
预期的气候变化使得有必要开展相关研究，以选育出在不同环境条件下均能保持稳定表现的表型牛群。在本研究中，我们使用异方差随机回归模型来：1）描述干物质摄入量（DMI）和呼吸频率（RR）与温度湿度指数（THI）相关的加性遗传及其他表型成分；2）通过确定加性遗传反应规范是否沿观察到的THI范围变化，以及评估不同THI值下DMI或RR之间的加性遗传相关性，来评估基因型与环境互作（G×E）的存在情况；3）评估在一系列THI范围内模型推导的估计育种值（EBV）的准确性。数据包括分别对788头和569头公牛在70天内对DMI和RR的重复观测。使用贝叶斯推断对每个性状拟合了具有个体特异性加性遗传和永久环境效应的层次模型。以每日每单位THI增加量的后验中位数和95%最高后验密度（HPD）区间表示的估计群体斜率为，DMI为-0.046（-0.053，-0.039）kg/单位THI增加量，RR为对数尺度上每单位THI增加量0.027（0.026，0.029）次呼吸/30秒（BP30S），这表明两个性状均对环境敏感。DMI和RR的加性遗传截距与斜率之间的估计相关性分别为-0.78（-0.86，-0.69）和-0.66（-1.0，-0.20），这表明在热应激开始时选择增加DMI和降低RR有望与群体对THI的平均环境敏感性呈正相关。热应激开始时（即THI为70时）DMI的遗传力估计值在不同队列中范围为0.30（0.17，0.44）至0.37（0.20，0.48），但随THI增加而降低。RR的遗传力估计值较低，在评估的THI范围内95% HPD上限范围为0.03至0.08。对于DMI，70和85 THI之间的加性遗传相关性中位数以及70和85 THI水平下EBV之间的斯皮尔曼相关性分别为0.42（0.26，0.57）和0.39（0.26，0.52），表明存在显著的G×E。在特定THI值下，DMI EBV模型推导的准确性中位数从70 THI时的增加到82 THI时的0.65，此后趋于稳定。这可能是因为在更高的THI下收集了更多数据点。
