Comparison of Multi-Breed and Within-Breed Genomic Evaluation in French Dairy Goat

In French dairy goats, 825 bucks were genotyped with the Illumina goat SNP50 Bead-Chip. The objective of this study was to compare in a genomic best linear unbiased prediction (GBLUP) single step approach three models: 1) a multi-breed model with Saanen and Alpine considered as the same breed, 2) a within-breed model analysed separately for each breed, and 3) a multiple trait one with genetic correlation between Alpine and Saanen. Quality of predictions was evaluated using Pearson correlations between genomic estimated breeding values (GEBV) and daughter yield deviations (DYD) for 252 validation males. Accuracies of GEBV were estimated from prediction error variances and derived for the 148 candidates (genotyped but no phenotyped).

Using the single step approach instead of the two-step one increased the Pearson correlations for all traits by 10% for milk yield to 60% for udder floor position. The prediction accuracies achieved with the multiple trait models were similar to the ones obtained with multi-breed or multiple trait models whatever the genetic covariance levels considered.  They were higher in Saanen breed than in Alpine breed due to higher relationship level between training and testing sets in Saanen breed. The three different models led to no differences in average GEBV accuracies for candidates. These accuracies were higher than the accuracy of candidates’ parent average breeding values for all traits. Using single step approaches instead of two-step ones increased model accuracy from 28% for udder type traits and SCS to 37% for milk and fat yields.