Genotype-by-environment interaction for yearling weight of Nellore cattle in pasture and feedlot conditions using a "double" genomic reaction norm model.

In many tropical climate countries, beef cattle are typically raised in extensive pasture-based systems and exposed to harsh environmental conditions. A portion of these animals is then confined for 3 to 4 mo prior to slaughter. Thus, the main objectives of this study were to estimate variance components and genetic parameters to assess the level of genotype-by-environment interactions (G×E) in Nellore cattle raised on pasture until weaning and finished in feedlot conditions, evaluate genetic trends, and perform a genome-wide association study to identify genomic regions associated with the animals' responses to different production environments. We analyzed the body weight measured at approximately 378 d of age (W378) of 5,070 Nellore males from an experimental herd. The heritability estimates for W378 varied considerably between pasture and feedlot environments (0.33 ± 0.05 to 0.62 ± 0.05), indicating potential differential responses to selection across environments. Overall, the genetic correlation estimates for W378 across environments were high (>0.80) but reached values around 0.60 between certain levels of pasture and feedlot environments (e.g., "good" pasture vs. "poor" feedlot and vice versa). Reaction norms for sires and single nucleotide polymorphism highlighted the existence of G×E, showing divergent genetic responses to pasture and feedlot conditions. Genetic trends revealed a gradual improvement in feedlot environments at the cost of reduced performance in optimal pasture conditions, indicating a moderate genetic antagonism. Genomic regions explaining significant percentage (1% to 11%) of the total additive genetic variance for responses to pasture and feedlot were identified, with distinct loci contributing to the genetic architecture of W378 in each environment. Therefore, G×E between pasture and feedlot environments should be considered in breeding programs. The genomic regions identified provide potential targets for further exploration to enhance beef cattle performance across production system conditions.