Genotype by environment interactions (GxE) may occur when individuals show different adaptation to local environment. Due to their typically great adeptness to environment local breeds may be reared in a variety of geographical areas and farming conditions, suggesting to investigate the occurrence of GxE for genetic improvement. Considering the local cattle breed Rendena, this study aimed to investigate GxE for traits of interest in a number of environmental conditions including the geographical area (plain, hill or mountain), the type of housing (tie-stall or loose housing), the feeding system (traditional or total mixed ration) and the occurrence of summer pasture. Following the reaction norm model approach, milk yield, fat and protein yield and percentage, and SCS were analysed via Bayesian inference. The solutions for the herd-test day (HTD) effect firstly obtained via animal model as estimates of environmental effect, were then used in a random regression model as environmental covariate for sire effect to obtain the intercept and the slope for target traits across different HTD levels. As result, GxE interactions explained a certain quote of phenotypic variance (about the 20% on average), even greater than G in milk, protein yield and SCS. Some differences in genetic variances were observed between estimates for HTD ascribable to different environmental conditions. A greater genetic component was observed for milk, fat and protein yield in plain farms, without summer pasture, under loose housing, and with a total mixed ration as feed. This may be explained by the fact that better conditions for individuals or for production could enhance the expression of individual performance. This study confirms the importance to detect GxE in local breeds reared in various environments. Keywords: GxE, genotype by environment, Reaction norm model, milk, cattle

Cristina Sartori, Francesco Tiezzi, Mara Battagin, Nadia Guzzo, Roberto Mantovani

Proceedings of the World Congress on Genetics Applied to Livestock Production, Volume Electronic Poster Session - Challenges - Genotype by Environment Interactions, , 918, 2018
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