Describing adaptation to heat stress through untargeted metabolomics in pig genetic resources

Climate change is significantly affecting pig production systems worldwide, pushing breeders to face a new challenge: pigs have to respond well to heat-derived stresses while maintaining good productivity. Local pig breeds are genetically and physiologically adapted to their native environments, making them valuable resources for the identification of novel biomarkers. In this study, we used untargeted metabolomics to explore the relationship between the metabolomes of four Italian breeds (Cinta Senese, Mora Romagnola, Italian Large and Italian Duroc) and two Polish breeds or populations (Złotnicka White and Złotnicka White x Złotnicka Spotted) and their response to high temperatures and related stress through the evaluation of the metabolomic profiles over the circadian rhythm of the animals. The study took place in summer, sampling 12 animals per breed at two time points: 1) in the late afternoon (the hottest part of the day) and 2) early in the morning (the coolest part of the day). For each breed, metabolomic profiles of about 700 molecules were compared through a machine learning approach (Random Forest). From each breed, about 30-50 heat-stress-related metabolites were identified and their discriminative power was confirmed with unsupervised analyses. What emerged was a heterogeneous composition of the heat-stress-related metabolome, with few molecules shared between two or more breeds. Nevertheless, this pilot study provided new insights into the biological processes involved in adaptation to heat stress conditions, deepening our understanding of the mechanisms underlying the circadian rhythm physiological processes in these pig breeds. Acknowledgments: This study has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No. 01059609 (Re-Livestock project).