Abstract :
[en] Breeding for resilience to heat stress (HS) is a topic where associating multiple omics data has the potential to get a better view of the issues and to allow significant advances to overcome undesirable consequences of future extreme weather scenarios. An example of omics is here epigenomics (e.g. early programming due to heat-stress) allowing new insights to explain biological mechanisms of resilience to HS and G×E interactions. Even if biological mechanisms are complex and still elusive, this study tried to use a holistic approach integrating milk-based biomarkers, climate conditions, and genomics. Data used included 65,907 third-lactation test-day records for production traits (milk, fat and protein yields), specific fatty acids (FA) and metabolites predicted from mid-infrared spectra (C4:0, C18:1cis9, long chain ‘LCFA’, mono- and unsaturated FA ‘MUFA and UFA’, acetone and BHB) of 9,327 Holstein cows. Phenotypes were merged with a temperature humidity index (THI) from public weather stations. For each trait, the response to THI was estimated via days in milk (DIM) × THI combination, and for each cow by using a random regression model with a common threshold of THI=62. The slope (heat tolerance)-to-intercept (general) genetic variance ratios increased as THI increased. They were higher during mid-lactation (140-245 DIM) for C18:1 cis9, acetone, BHB and for production traits, whereas higher in early lactation (≤125 DIM) for C4:0, LCFA, MUFA, and UFA. At extreme high THI scale, slope-to-intercept ratios for C18:1 cis9, MUFA, UFA, and LCFA were 3.8, 3.4, 3.1, 2.8 fold higher than milk yield. These findings indicate that tolerance to HS and traditional production trait responses to THI are marginally related, and changes in milk-based biomarkers under high THI better elucidate physiological and metabolic pathways in HS dairy cows. Ongoing genomic wide association studies will better explain genetic markers unravelling the biological background of resilience to HS.
