Genomic insights: Disentangling milk yield and reproduction performance in first-lactation German Holsteins

This study offers insight into the genetic complexity of the interaction between production and reproduction in German dairy cows. The phenotypes and genotypes of 32,352 primiparous German Holstein cows were available for investigation, and datasets (DS) of similar size were generated according to their milk yield. Five distinct DS, each including more than 6,400 animals, from lowest to highest milk yield (DS_Lowest, DS_Low, DS_Mean, DS_High, DS_Highest) were included for subsequent analysis. Heritabilities and genetic correlations (r_G) between traits were estimated, followed by GWAS. The overall heritability estimates were relatively low, with a maximum of h² = 0.127 for ovary cycle disturbances in DS_Highest and a minimum of h² = 0.026 for retained placenta (NGV) in the complete DS. The r_G between milk yield and reproduction traits exhibited a range from r_G = -0.436 between milk yield and metritis (MET) in DS_High to r_G = 0.435 between milk yield and NGV in DS_High. Genetic correlations between the various reproduction traits were moderate, as evidenced by the correlation between calving ease maternal (CEm) and MET in DS_High (r_G = 0.329). In contrast, a striking divergence within the specific traits was evident contingent on the performance subset. The range of r_G between CEm and NGV was covered from r_G = -0.146 in DS_Lowest up to r_G = 0.318 in DS_Highest. The heritabilities and r_G estimates did not demonstrate a straightforward linear relationship between milk yield and the analyzed reproduction parameters. Moreover, GWAS identified several significant SNPs across the various DS, with a total of 86 genome-wide and chromosome-wide signals. These findings led to the identification of previously described genes in the context of reproduction, as well as the postulation of additional potential candidate genes, including a high number of zinc finger proteins. Overall, this study provides important insights into the genetic background and interrelations of reproduction traits with special regards to the nonlinear relationship between milk yield and reproduction, and the findings may help to further improve selection decisions.