Sirlene F Lázaro, Humberto Tonhati, Hinayah R Oliveira, Alessandra A Silva, Daiane C B Scalez, André V Nascimento, Daniel J A Santos, Gabriela Stefani, Isabella S Carvalho, Amanda F Sandoval, Luiz F Brito
Genetic and genomic analyses of longitudinal traits related to milk production efficiency are paramount for optimizing water buffaloes breeding schemes. Therefore, this study aimed to: 1) compare single-trait random regression models under a Single-step Genomic Best Linear Unbiased Prediction (ssGBLUP) setting based on alternative covariance functions (i.e., Wood - WD, Wilmink - WL, and Ali-and-Schaeffer - AS) to describe milk (MY), fat (FY), protein (PY), and mozzarella (MZY) yields, fat-to-protein ratio (FPR), somatic cell score (SCS), lactation length (LL), and lactation persistency (LP) in Murrah dairy buffaloes (Bubalus bubalis); 2) combine the best functions for each trait under a multiple-trait framework; 3) estimate time-dependent SNP effects for all the studied longitudinal traits; and, 5) identify the most likely candidate genes associated with the traits...
September 18, 2023: Journal of Dairy Science