Implementation of marker-assisted selection (MAS) in modern beekeeping would improve sustainability, especially in breeding programs aiming for resilience against the parasitic mite Varroa destructor. Selecting honey bee colonies for natural resistance traits, such as brood-intrinsic suppression of varroa mite reproduction, reduces the use of chemical acaricides while respecting local adaptation. In 2019, eight genomic variants associated with varroa non-reproduction in drone brood were discovered in a single colony from the Amsterdam Water Dune population in the Netherlands. Recently, a new study tested the applicability of these eight genetic variants for the same phenotype on a population-wide scale in Flanders, Belgium. As the properties of some variants varied between the two studies, one hypothesized that the difference in genetic ancestry of the sampled colonies may underly these contribution shifts. In order to frame this, we determined the allele frequencies of the eight genetic variants in more than 360 Apis mellifera colonies across the European continent and found that variant type allele frequencies of these variants are primarily related to the A. mellifera subspecies or phylogenetic honey bee lineage. Our results confirm that population-specific genetic markers should always be evaluated in a new population prior to using them in MAS programs.

The mechanisms of action behind decreased mite reproduction (DMR) are still unknown, but current hypotheses state that DMR is the result of brood-intrinsic and/or external disturbances in the V. destructor—honey bee pupa signal interactions. For accurate and precise DMR phenotyping, sufficient single infested honey bee brood cells are required (e.g., 35), which requires extensive labor and time and may exclude many samples not reaching the threshold. We defined a new comprehensive trait called the ‘mean V. destructor reproduction rate’ (mVR), which describes the mean number of offspring mites per infested cell in the sample while compensating for the reduced number of offspring with increasing multiple infested cells. We found a significant correlation between mVR and DMR, allowing for an estimation of DMR based on the mVR only. When the mVR was calculated with 10 infested cells, we found an average variation in mVR of 16.8%. For the same variation in DMR determination, 40 single infested cells are required. This broader look at V. destructor resistance phenotyping can improve the applicability and effectiveness of traits related to V. destructor reproduction in honey bee breeding programs.

Viral infections pose a major threat to honey bee health. While viruses are typically controlled indirectly through efforts of attaining Varroa resistance, the heritable trait suppressed in ovo virus infection (SOV) provides a direct avenue for selecting virus resistance. This study evaluated the potential of this trait using data collected within an established mass breeding selection program. Drone egg samples collected from honey bee colonies in Flanders (2015–2024) were screened for four viruses to determine the queen’s SOV status. Queens are classified as SOV-positive if no viral particles are detected in their sample, and as SOV-negative if genomic material from at least one of these viruses is present. The proportion of SOV-positive queens significantly increased over time, regardless of maternal background, and targeted breeding from SOV-positive maternal lines enhanced the likelihood of producing SOV-positive offspring. Simultaneously, the prevalence and viral load values of several viruses decreased over time. These findings demonstrate that selective breeding for SOV-positivity can improve virus resistance in managed honey bee populations. There is even a potential to raise the SOV trait occurrence by incorporating targeted mating within selection programs. Therefore, future research should focus on the combined selection for SOV through targeted breeding and mating, alongside Varroa-resistant traits.

Selective breeding is widely used to improve honey bee health and colony performance, commonly applying selection based on colony traits. Since 2017, a mass selection program in Flanders, Belgium, has ranked queens according to resilience, productivity and behavior traits. Using longitudinal data (2017–2024), we evaluated the effectiveness of this strategy by assessing colony performance across years and generations. Behavioral traits showed the clearest improvement over time, whereas progress in productivity and especially resilience-related traits remained limited. Offspring of top-ranking queens frequently failed to achieve overall ranking values comparable to those of their mothers; rather, they scored lower. For the traits Varroa index and spring development, offspring from lower-scoring queens often performed better, while offspring from higher-scoring queens tended to perform worse. These findings indicate that the current mass selection approach did not consistently result in cumulative genetic improvement. Factors such as open participation, limited breeding standardization, and insufficient paternal genetic control may have reduced selection efficiency. These results highlight the opportunities and challenges of implementing an accessible honey bee breeding program. Refinement of the current selection framework and evaluation of alternative strategies, such as selection by exclusion, may therefore be necessary to achieve more robust and resilient honey bee populations.

Selective breeding for Varroa resistance is an important strategy to improve honey bee colony survival against Varroa destructor, which remains a major threat to their health. However, phenotyping resistance traits is often labor-intensive. Marker-assisted selection (MAS) offers an alternative by selecting colonies based on molecular markers associated with resistance traits. This study evaluated the implementation of MAS for drone brood resistance (DBR, i.e., mite non-reproduction in drone brood), using a three-SNP model within the ongoing Flemish honey bee breeding program. From 2022 to 2025, predominantly Apis mellifera carnica workers and drones were genotyped. Through targeted breeding and mating via instrumental insemination, we aimed to reconstruct the genetic profile with all three SNPs’ protective alleles. Over sampling years, SNP2 and SNP6 increased in frequency in both workers and drones, whereas SNP4 did not. The cumulative three-SNP score also increased over years and generations, with the greatest genetic gain achieved by combining targeted breeding and targeted mating. The ideal genetic profile was obtained in three queens. However, genetic progress was not reflected in the DBR phenotype. These findings provide insights into the potential and limitations of MAS, suggesting future efforts in breeding programs towards genomic selection.