Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, Blichers Allé 20, Postboks 50, Tjele, DK, 8830, Denmark.
Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, 200240, Shanghai, China.
Heredity (Edinb). 2019 Aug;123(2):202-214. doi: 10.1038/s41437-019-0192-4. Epub 2019 Feb 13.
Genotype-by-environment (G × E) interactions could play an important role in cattle populations, and it should be considered in breeding programmes to select the best sires for different environments. The objectives of this study were to study G × E interactions for female fertility traits in the Danish Holstein dairy cattle population using a reaction norm model (RNM), and to detect the particular genomic regions contributing to the performance of these traits and the G × E interactions. In total 4534 bulls were genotyped by an Illumina BovineSNP50 BeadChip. An RNM with a pedigree-based relationship matrix and a pedigree-genomic combined relationship matrix was used to explore the existence of G × E interactions. In the RNM, the environmental gradient (EG) was defined as herd effect. Further, the genomic regions affecting interval from calving to first insemination (ICF) and interval from first to last insemination (IFL) were detected using single-step genome-wide association study (ssGWAS). The genetic correlations between extreme EGs indicated that G × E interactions were sizable for ICF and IFL. The genomic RNM (pedigree-genomic combined relationship matrix) had higher prediction accuracy than the conventional RNM (pedigree-based relationship matrix). The top genomic regions affecting the slope of the reaction norm included immunity-related genes (IL17, IL17F and LIF), and growth-related genes (MC4R and LEP), while the top regions influencing the intercept of the reaction norm included fertility-related genes such as EREG, AREG and SMAD4. In conclusion, our findings validated the G × E interactions for fertility traits across different herds and were helpful in understanding the genetic background of G × E interactions for these traits.
基因型与环境互作（G × E）在牛群中可能起着重要作用，因此在选育计划中应考虑到这一点，以便为不同的环境选择最佳的公牛。本研究的目的是使用反应规范模型（RNM）研究丹麦荷斯坦奶牛群体中雌性生育力性状的 G × E 互作，并检测对这些性状和 G × E 互作表现有贡献的特定基因组区域。总共有 4534 头公牛通过伊利诺伊州牛 SNP50 珠芯芯片进行了基因分型。使用基于系谱的关系矩阵和系谱-基因组组合关系矩阵的 RNM 来探索 G × E 互作的存在。在 RNM 中，环境梯度（EG）定义为牛群效应。此外，还使用一步全基因组关联研究（ssGWAS）检测了影响产犊至首次配种间隔（ICF）和首次至末次配种间隔（IFL）的基因组区域。极端 EG 之间的遗传相关性表明，ICF 和 IFL 的 G × E 互作很大。基因组 RNM（系谱-基因组组合关系矩阵）的预测准确性高于传统 RNM（系谱基于关系矩阵）。影响反应规范斜率的最重要基因组区域包括与免疫相关的基因（IL17、IL17F 和 LIF）和与生长相关的基因（MC4R 和 LEP），而影响反应规范截距的最重要区域包括与生育力相关的基因，如 EREG、AREG 和 SMAD4。总之，本研究结果验证了不同牛群中生育力性状的 G × E 互作，并有助于了解这些性状的 G × E 互作的遗传背景。
