%0 Journal Article
%T Joint genomic evaluation of French dairy cattle breeds using multiple-trait models
%A Sofiene Karoui
%A Mar¨ªa Jes¨²s Caraba£¿o
%A Clara D¨ªaz
%A Andr¨¦s Legarra
%J Genetics Selection Evolution
%D 2012
%I BioMed Central
%R 10.1186/1297-9686-44-39
%X Three traits (milk production, fat content and female fertility) were analyzed by genomic mixed linear models and Bayesian methodology. Three breeds of French dairy cattle were used: Holstein, Montb¨¦liarde and Normande with 2976, 950 and 970 bulls in the training population, respectively and 964, 222 and 248 bulls in the validation population, respectively. All animals were genotyped with the Illumina Bovine SNP50 array. Accuracy of genomic breeding values was evaluated under three scenarios for the correlation of genomic breeding values between breeds (rg): uncorrelated (1), rg = 0; estimated rg (2); high, rg = 0.95 (3). Accuracy and bias of predictions obtained in the validation population with the multi-breed training set were assessed by the coefficient of determination (R2) and by the regression coefficient of daughter yield deviations of validation bulls on their predicted genomic breeding values, respectively.The genetic variation captured by the markers for each trait was similar to that estimated for routine pedigree-based genetic evaluation. Posterior means for rg ranged from £¿0.01 for fertility between Montb¨¦liarde and Normande to 0.79 for milk yield between Montb¨¦liarde and Holstein. Differences in R2 between the three scenarios were notable only for fat content in the Montb¨¦liarde breed: from 0.27 in scenario (1) to 0.33 in scenarios (2) and (3). Accuracies for fertility were lower than for other traits.Using a multi-breed reference population resulted in small or no increases in accuracy. Only the breed with a small data set and large genetic correlation with the breed with a large data set showed increased accuracy for the traits with moderate (milk) to high (fat content) heritability. No benefit was observed for fertility, a lowly heritable trait.Increasing the accuracy of the prediction of breeding values has become a major objective in genomic selection (GS). The success of GS depends on many factors [1,2], some of which cannot be easily controlled
%U http://www.gsejournal.org/content/44/1/39