Abstract：
Age at first calving (AFC) is a measure of sexual maturity associated with the start of productive life of dairy animals. Additionally, a lower AFC reduces the generation interval and early culling of females. However, AFC has low heritability, making it a trait highly influenced by environmental factors. In this scenario, one way to improve the reproductive performance of buffalo cows is to select robust animals according to estimated breeding value (EBV) using models that include genotype-environment interaction (GEI) with the application of reaction norm models (RNMs). This can be achieved by understanding the genomic basis related to GEI of AFC. Thus, in this study, we aimed to predict EBV considering GEI via the RNM and identify candidate genes related to this component in dairy buffaloes through genome-wide association studies (GWAS). We used 1795 AFC records from three Murrah buffalo herds and formed environmental gradients (EGs) from contemporary group solutions obtained from genetic analysis of 270-day cumulative milk yield. Heritability estimates ranged from 0.15 to 0.39 along the EG. GWAS of the RNM slope parameter identified important genomic regions. The genomic window that explained the highest percentage of genetic variance of the slope (0.67%) was located on BBU1. After functional analysis, five candidate genes were detected, involved in two biological processes. The results suggested the existence of a GEI for AFC in Murrah buffaloes, with reclassification of animals when different environmental conditions were considered. The inclusion of genomic information increased the accuracy of breeding values for the intercept and slope of the reaction norm. GWAS analysis suggested that important genes associated with the AFC reaction norm slope were possibly also involved in biological processes related to lipid metabolism and immunity.
摘要：
初产牛年龄（AFC）是与产奶动物生产生活开始相关的性成熟的量度。此外,较低的AFC减少了雌性的世代间隔和早期剔除。然而,亚足联的遗传力低，使其成为受环境因素高度影响的特征。在这种情况下，提高水牛繁殖性能的一种方法是使用包括基因型-环境相互作用（GEI）和反应规范模型（RNM）的模型，根据估计的育种值（EBV）选择健壮的动物。这可以通过理解与AFC的GEI相关的基因组基础来实现。因此，在这项研究中，我们旨在通过RNM预测考虑GEI的EBV,并通过全基因组关联研究(GWAS)确定与该成分相关的候选基因.我们使用了来自三个Murrah水牛群的1795个AFC记录，并根据从270天累积产奶量的遗传分析获得的当代群体解决方案形成了环境梯度（EGs）。沿着EG的遗传力估计范围为0.15至0.39。RNM斜率参数的GWAS确定了重要的基因组区域。解释斜率遗传变异的最高百分比（0.67％）的基因组窗口位于BBU1上。功能分析后，检测到五个候选基因，参与两个生物过程。结果表明，在Murrah水牛中存在AFC的GEI，当考虑到不同的环境条件时，对动物进行重新分类。基因组信息的包含增加了反应范数的截距和斜率的育种值的准确性。GWAS分析表明，与AFC反应范数斜率相关的重要基因也可能参与与脂质代谢和免疫相关的生物过程。
