Genetic analysis of milk cheese-making traits predicted from mid-infrared spectra in Montbéliarde cows

Abstract

The cheese-making properties are closely linked to milk composition. These traits, which are difficult to measure directly, were predicted from milk mid-infrared (MIR) spectra in the Montbéliarde breed within the From’MIR project. We summarize here the analysis of the genetic determinism of milk cheese-making properties (CMP) and composition traits, predicted from six million MIR spectra of 400,000 cows. These traits are moderately to highly heritable and genetic correlations between CMP (cheese yields and coagulation) and with milk composition (proteins, fatty acids, and minerals) are high and favorable. Genome-wide association (GWAS) and gene network analyses, carried out on imputed whole-genome sequences of 20,000 cows, enabled the identification of candidate genes and variants as well as a network of 736 genes with metabolic pathways and regulatory genes functionally linked to milk composition traits. Finally, estimation of genomic prediction accuracies reveals that a test-day model, including variants detected by GWAS, gives the most accurate genomic evaluations. In addition, simulation of a selection including CMP shows that they could be efficiently selected with a limited impact on the genetic gain for the currently selected traits. As a result, a pilot genomic evaluation in Montbéliarde cows of the Comté PDO area is going to be implemented in 2019.