Simulation studies to optimize genomic selection in honey bees

Abstract

Background With the completion of a single nucleotide polymorphism (SNP) chip for honey bees, the technical basis of genomic selection is laid. However, for its application in practice, methods to estimate genomic breeding values need to be adapted to the specificities of the genetics and breeding infrastructure of this species. Drone-producing queens (DPQ) are used for mating control, and usually, they head non-phenotyped colonies that will be placed on mating stations. Breeding queens (BQ) head colonies that are intended to be phenotyped and used to produce new queens. Our aim was to evaluate different breeding program designs for the initiation of genomic selection in honey bees. Methods Stochastic simulations were conducted to evaluate the quality of the estimated breeding values. We developed a variation of the genomic relationship matrix to include genotypes of DPQ and tested different sizes of the reference population. The results were used to estimate genetic gain in the initial selection cycle of a genomic breeding program. This program was run over six years, and different numbers of genotyped queens per year were considered. Resources could be allocated to increase the reference population, or to perform genomic preselection of BQ and/or DPQ. Results Including the genotypes of 5000 phenotyped BQ increased the accuracy of predictions of breeding values by up to 173%, depending on the size of the reference population and the trait considered. To initiate a breeding program, genotyping a minimum number of 1000 queens per year is required. In this case, genetic gain was highest when genomic preselection of DPQ was coupled with the genotyping of 10–20% of the phenotyped BQ. For maximum genetic gain per used genotype, more than 2500 genotyped queens per year and preselection of all BQ and DPQ are required. Conclusions This study shows that the first priority in a breeding program is to genotype phenotyped BQ to obtain a sufficiently large reference population, which allows successful genomic preselection of queens. To maximize genetic gain, DPQ should be preselected, and their genotypes included in the genomic relationship matrix. We suggest, that the developed methods for genomic prediction are suitable for implementation in genomic honey bee breeding programs.

Evaluating the Potential of Brood Recapping to Select Varroa destructor (Acari: Varroidae) Resistant Honey Bees (Hymenoptera: Apidae)

“…A previous attempt to propose an easier method to evaluate recapping ended with unconvincing results, such as low heritabilities and low correlations with mite infestation ( Guichard et al 2021 ). The development of genome-based methods, however, appears promising to gain knowledge on the genetic background of recapping and to enable the emergence of genomic marker-assisted selection ( Brascamp et al 2018 , Bernstein et al 2021 , Guichard et al 2022 ), which might help increase the speed of genetic progress. Our results confirm the difficulty of identifying suitable traits for successful resistance selection programs but suggest that recapping is one of the promising candidate traits that may lead to colonies with an elevated resistance against Varroa destructor , or at least a significant reduction in the need for miticide treatments.…”

Influence of model selection and data structure on the estimation of genetic parameters in honeybee populations

“…The phenotypic variance for honeybee colonies equals [ Brascamp and Bijma 2019 ; Bernstein et al 2021 , Equation (2)]. …”

Consequences of incorrect genetic parameter estimates for single‐trait and multi‐trait genetic evaluations in honeybees

“…Instead, both phenomena were consequences of incomplete phenotype records due to preselection strategies. Thus, in comparison with other factors that influence breeding success in honeybees, such as mating control (Du et al, 2021a; Plate et al, 2019b) or the inclusion of genomic data in the relationship matrix (Bernstein et al, 2021; Brascamp et al, 2018; Gupta et al, 2013), the use of correct genetic parameters in single‐trait selection appears secondary. The results clearly suggest that BLUP selection is a viable option in honeybee breeding, also for incipient breeding programmes where genetic parameters cannot yet be estimated with high accuracy.…”

“…In contrast, earlier studies have shown that this ratio can be heavily influenced by the mating strategy of the breeding programme (Du et al, 2021a; Kistler et al, 2021; Plate et al, 2019b). Furthermore, Bernstein et al (2021) showed that the inclusion of genomic queen data into the BLUP evaluations shifts the breeding focus towards the maternal effects.…”