First large-scale genomic prediction in the honey bee

Area of Science:

• Animal Breeding and Genetics
• Apiculture
• Genomics

Background:

• Genomic selection (GS) has advanced livestock breeding but its application in honey bees (Apis mellifera) is limited by complex genetics.
• A reference population of 2970 genotyped queens was established to facilitate GS in honey bees.

Purpose of the Study:

• To evaluate the accuracy and bias of pedigree-based and genomic breeding values for key honey bee traits.
• To assess the potential of genomic selection for improving honey yield, workability, and resistance to Varroa destructor.

Main Methods:

• A honey bee-specific model incorporating maternal and direct genetic effects was used for breeding value estimation.
• Validation was performed using both last-generation validation and five-fold cross-validation.

Main Results:

• Genomic selection improved accuracy for honey yield (from 0.12 to 0.23) and workability traits (from 0.42-0.61 to 0.44-0.65).
• Accuracy for Varroa destructor resistance traits did not significantly improve with genomic data.
• Bias was comparable between genomic and pedigree-based methods for most traits.

Conclusions:

• Genomic selection is a viable tool for enhancing honey bee breeding programs, particularly for traits with significant maternal effects.
• Further research may be needed to optimize genomic selection for disease resistance traits in honey bees.