  Genomic selection has increased genetic gain in several livestock species,
but due to the complicated genetics and reproduction biology not yet in honey
bees. Recently, 2 970 queens were genotyped to gather a reference population.
For the application of genomic selection in honey bees, this study analyses the
predictive ability and bias of pedigree-based and genomic breeding values for
honey yield, three workability traits and two traits for resistance against the
parasite Varroa destructor. For breeding value estimation, we use a honey
bee-specific model with maternal and direct effects, to account for the
contributions of the workers and the queen of a colony to the phenotypes. We
conducted a validation for the last generation and a five-fold
cross-validation. In the validation for the last generation, the predictive
ability of pedigree-based estimated breeding values was 0.06 for honey yield,
and ranged from 0.2 to 0.41 for the workability traits. The inclusion of
genomic marker data improved these predictive abilities to 0.11 for honey
yield, and a range from 0.22 to 0.44 for the workability traits. The inclusion
of genomic data did not improve the predictive ability for the disease related
traits. Traits with high heritability for maternal effects compared to the
heritability for direct effects showed the most promising results. Across all
traits, the bias with genomic methods was close to the bias with pedigree-based
BLUP. The results show that genomic selection can successfully be applied to
honey bees.
