Genetic aspects of major blood metabolites in the Italian Simmental cattle population - S. Magro; A. Costa; A. Cesarani; L. Degano; M. De Marchi (Journal of Dairy Science)
ABSTRACT: The Simmental breed is widely known for its resilience, robustness, and resistance to disease, and the incidence of ketosis in this breed is therefore generally lower compared with Holsteins. Blood concentrations of nonesterified fatty acids (NEFA), BHB, and urea provide valuable information about the metabolic, health, and nutritional status of lactating animals. In the present study, we estimated h2 of BHB, NEFA, and urea in blood predicted from milk mid-infrared spectra and assessed their genetic correlation with milk yield and composition traits in the Italian Simmental cattle breed using phenotypes of 3,549 cows in 207 herds. Two sets were considered: early (1,920 records, 1 per cow, between 5 and 35 DIM) and whole (14,378 records, at least 3 per cow, between 5 and 305 DIM) lactation. In early lactation, h2 estimates were 0.06 for blood BHB as-is, 0.06 for log-transformed BHB, 0.18 for NEFA, 0.14 for log-transformed NEFA, and 0.05 for blood urea. In the whole lactation, the h2 were 0.09 for blood BHB as-is, 0.16 for log-transformed BHB, 0.03 for NEFA, 0.04 for log-transformed NEFA, and 0.04 for blood urea. As far as the genetic correlations were concerned, blood BHB was positively correlated with NEFA and blood urea. Blood BHB and NEFA were generally positively correlated with milk fat-to-protein ratio and milk, but only the first was negatively correlated with lactose content and positively with SCS. Sires' EBVs for BHB with accuracy ≥0.60 were extrapolated for a posteriori evaluation of the daughters' observed performance. The progeny of the top 5% of sires exhibited, on average, lower blood BHB, NEFA, and urea compared with the daughters of the bottom 5%. Overall, it is highly recommended to monitor the genetic variability of the metabolic traits in the dual-purpose Italian Simmental breed to monitor the incidence of metabolic diseases in future generations.