A total of 4,218 animals genotyped for 50 K SNPs were used to evaluate accuracy of molecular breeding values (MBVs) of Canadian crossbred beef cattle traits. A cross-validation approach that involves random sampling of all animals to form 5-groups was applied. One group was dedicated as a validation set and the remaining four groups were combined to form a reference set. Genomic best linear unbiased prediction method was applied for training and prediction of MBVs in the validation set. Estimated breeding values (EBV) were used as the phenotype and a bivariate animal model was applied to each trait to estimate the genetic correlation between MBV and EBV. Accuracy of MBVs ranged from 0.05 to 0.68 for the studied traits. The results suggest that genomic predictions can be produced for crossbred beef cattle with greater efficiency for selection and management especially in younger animals.

Everestus C Akanno, Graham Plastow, Changxi Li, Stephen P Miller, John A Basarab

Proceedings of the World Congress on Genetics Applied to Livestock Production, Volume Genetic Improvement Programs: Selection using molecular information (Posters), , 513, 2014
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