GxE

Exploring farm-environment descriptors to assess their potential for GxE interactions on milk production in Holstein dairy cattle

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Abstract

Current genetic evaluations estimate genetic merit independent from the animals' rearing environment. These animals are, however, raised in a variety of environments, characterized by their geographical region or farming systems, potentially interacting with the individuals' genetic merit, expressed in the form of genotype-by-environment (GxE) interactions. For selection purposes, GxE interactions are very relevant in the current context of climate change, as animals are expected to face greater environmental variability. GxE interactions are therefore an important information to be considered in genetic evaluations for livestock breeding programs. Implementing GxE interactions in genetic evaluations relies on having a detailed description of the farming environment, comprising not only meteorological variables, but also farm management descriptors. Our study focus on the description of the farming environment, aiming to identify variables that can provide an effective description, more specifically of the sanitary environment. Three approaches were considered to characterize the herd sanitary environment, and then used to estimate their effects on milk production of French Holstein dairy cows, to validate these variables' relevance. The first two approaches consisted of environmental gradients created from the herds' cell effects, derived from the official French genetic evaluations of the somatic cell score (SCS).To overcome difficulties linked to differences in mean and variability in herd-year effects between years, we assigned a year-to-year comparable value to the herd-year effects either as (1) the value of the quantile to which it belongs (Qt_eft), or as (2) the reduced centred value (RC_eft). The third approach consisted in creating a synthetic variable (Var_synth_sanit) using 77 variables describing the global farming management environment beyond sanitary indicators, from the genetic information system. A principal component analysis (PCA) was performed to identify the relevance and potential clusters of the 77 variables, which identified a cluster of six variables related with the sanitary environment. Var_synth_sanit was finally defined as the weighted sum of these six sanitary variables, with the weights being the PCA-based variance explained by each of these six variables, considering the first two components. Finally, GxE interactions studies were performed for 305-day milk yield (MY_305d) using a sire random regression model, with the sanitary environment gradient described by these variables obtained from each of the three approaches. Genetic standard deviations and heritabilities followed the same trend regardless of the gradient, with higher values for favourable and unfavourable environments compared to average environments. The genetic correlations (rg) of MY_305d measured in the different types of sanitary environments were estimated for the three gradients, being all rg ≥0.9. Thus, these results indicate that, in our data, there were no significant GxE interactions for MY_305d with respect to the sanitary herd environment.

Keywords: 2026

How to Cite:

Beerling, S., Vinet, A., Cuyabano, B., Plantard, Y., Dominique, S., Mattalia, S., Croiseau, P. & Aguerre, S., (2026) “Exploring farm-environment descriptors to assess their potential for GxE interactions on milk production in Holstein dairy cattle”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2286488. doi: https://doi.org/10.31274/wcgalp.24026

Rights: 1