Substantial Genetic Progress in the International Apis mellifera carnica Population Since the Implementation of Genetic Evaluation

Estimates of the vitality and performances of Apis mellifera mellifera and hybrid honey bee colonies in Siberia: a 13-year study

Honeybees display a great range of biological, behavioral, and economic traits, depending on their genetic origin and environmental factors. The high diversity of honeybees is the result of natural selection of specific phenotypes adapted to the local environment. Of particular interest is adaptation of local and non-local bee colonies to environmental conditions. To study the importance of genotype-environment interactions on the viability and productivity of local and non-local bee colonies, we analyzed the long-term dynamics of the main traits in dark forest bees (Apis mellifera mellifera) and hybrid colonies. From 2010 to 2022, a total of 64 colonies living in an apiary in Siberia, Russia, were monitored and tested to assess their biological, behavioral, and economic traits in a temperate continental climate. We detected significant correlations between the studied biological and behavioral indicators of the bee colony such as colony strength, overwintering ability, infection of colonies with diseases, hygienic behavior, and others. No relationships between the biological and economic (honey productivity) traits of bee colonies are shown. The overall result of our study is that local dark forest bee, A.m.mellifera, showed higher values for all analyzed traits than hybrid colonies. Compared to hybrids, dark forest bee colonies showed more gentleness, productivity, and survivorship. The results from our study indicate a specific local adaptation of the A.m.mellifera subspecies in a temperate continental climate. Siberia represents a unique region for the conservation of the dark forest bee. The creation of conservation areas is one way to protect local bee populations, well adapted to local environmental conditions, from uncontrolled importation of bee breeds from different regions.

Do Varroa destructor (Acari: Varroidae) mite flows between Apis mellifera (Hymenoptera: Apidae) colonies bias colony infestation evaluation for resistance selection?

Since the global invasion of the ectoparasitic mite Varroa destructor (Anderson and Trueman), selection of mite-resistant honey bee (Apis mellifera L.) colonies appears challenging and has to date not broadly reduced colony mortality. The low published estimated heritability values for mite infestation levels could explain the limited genetic progresses obtained so far. We hypothesize that intercolonial horizontal mite transmission could differentially affect the single colonies located in a given apiary and therefore invisibly bias colony infestation phenotypes. This bias may be lower in regions with lower colony density, providing suitable conditions to set up evaluation apiaries. To verify these hypotheses, we monitored mite infestation and reinvasion in experimental colonies, as well as infestation in neighboring colonies belonging to beekeepers in three areas with variable colony densities in the canton of Bern, Switzerland during three consecutive beekeeping seasons. Mite immigration fluctuated between apiaries and years and significantly contributed to colony infestation level. Depending on apiary and year, 17-48% of the mites present in the experimental colonies at the time of the summer oxalic acid final treatment potentially derived from mite immigration that had occurred since mid-spring. Mite immigration was not linked to local colony density or the infestation levels of beekeepers' colonies located within 2 km. Our results do not prove that apiaries for colony evaluation should necessarily be established in areas with low colony density. However, they highlight the high impact of beekeeping management practices on mite colony infestation levels.

Influence of honey bee (Apis mellifera) breeding on wing venation in Serbia and neighbouring countries

In order to improve the productivity of honey bees (Apis mellifera), some of their traits are selected by breeding. On one hand, breeding is mainly based on the natural geographical variation of this species; on the other hand, mass production and distribution of artificially selected queens can significantly affect the natural geographic variation of honey bees. In this study, we have compared honey bee wings originating from breeding and non-breeding populations in Serbia. In the comparison, we have also used data from a large area of south-eastern Europe. The wings were measured using the 19 landmarks indicated on the wing images. The coordinates were analysed using the methodology of geometric morphometrics. We found that honey bees obtained from honey bee queen breeder differed in wing venation from surrounding populations, which are under natural selection. Therefore, we argue against including populations under artificial selection in the analysis of the natural geographical variation of honey bees. In our analysis of non-breeding samples, we found that in south-eastern Europe there is continuous variation in wing venation and no clear boundaries between A. m. carnica, A. m. cecropia, and A. m. macedonica.

Uncertainty in the mating strategy of honeybees causes bias and unreliability in the estimates of genetic parameters

BACKGROUND

Breeding queens may be mated with drones that are produced by a single drone-producing queen (DPQ), or a group of sister-DPQs, but often only the dam of the DPQ(s) is reported in the pedigree. Furthermore, datasets may include colony phenotypes from DPQs that were open-mated at different locations, and thus to a heterogeneous drone population.

METHODS

Simulation was used to investigate the impact of the mating strategy and its modelling on the estimates of genetic parameters and genetic trends when the DPQs are treated in different ways in the statistical evaluation model. We quantified the bias and standard error of the estimates when breeding queens were mated to one DPQ or a group of DPQs, assuming that this information was known or not. We also investigated four alternative strategies to accommodate the phenotypes of open-mated DPQs in the genetic evaluation: excluding their phenotypes, adding a dummy pseudo-sire in the pedigree, or adding a non-genetic (fixed or random) effect to the statistical evaluation model to account for the origin of the mates.

RESULTS

The most precise estimates of genetic parameters and genetic trends were obtained when breeding queens were mated with drones of single DPQs that are correctly assigned in the pedigree. However, when they were mated with drones from one or a group of DPQs, and this information was not known, erroneous assumptions led to considerable bias in these estimates. Furthermore, genetic variances were considerably overestimated when phenotypes of colonies from open-mated DPQs were adjusted for their mates by adding a dummy pseudo-sire in the pedigree for each subpopulation of open-mating drones. On the contrary, correcting for the heterogeneous drone population by adding a non-genetic effect in the evaluation model produced unbiased estimates.

CONCLUSIONS

Knowing only the dam of the DPQ(s) used in each mating may lead to erroneous assumptions on how DPQs were used and severely bias the estimates of genetic parameters and trends. Thus, we recommend keeping track of DPQs in the pedigree, and not only of the dams of DPQ(s). Records from DPQ colonies with queens open-mated to a heterogeneous drone population can be integrated by adding non-genetic effects to the statistical evaluation model.

Comparison of pooled semen insemination and single colony insemination as sustainable honeybee breeding strategies

Instrumental insemination of honeybees allows for two opposing breeding strategies. In single colony insemination (SCI), all drones to inseminate a queen are taken from one colony. In pooled semen insemination (PSI), sperm of many genetically diverse drones is mixed and queens are fertilized from the resulting drone pool. While SCI allows for maximum pedigree control, proponents of PSI claim to reduce inbreeding and maintain genetic variance. Using stochastic simulation studies, we compared genetic progress and inbreeding rates in small honeybee populations under SCI and PSI. Four different selection criteria were covered: estimated breeding values (EBV), phenotypes, true breeding values (TBV) and random selection. Under EBV-based truncation selection, SCI yielded 9.0% to 44.4% higher genetic gain than PSI, but had vastly increased inbreeding rates. Under phenotypical or TBV selection, the gap between SCI and PSI in terms of genetic progress narrowed. Throughout, PSI yielded lower inbreeding rates than SCI, but the differences were only substantial under EBV truncation selection. As a result, PSI did not appear as a viable breeding strategy owing to its incompatibility with modern methods of genetic evaluation. Instead, SCI is to be preferred but instead of strict truncation selection, strategies to avoid inbreeding need to be installed.

Natural clines and human management impact the genetic structure of Algerian honey bee populations

BACKGROUND

The Algerian honey bee population is composed of two described subspecies A. m. intermissa and A. m. sahariensis, of which little is known regarding population genomics, both in terms of genetic differentiation and of possible contamination by exogenous stock. Moreover, the phenotypic differences between the two subspecies are expected to translate into genetic differences and possible adaptation to heat and drought in A. m. sahariensis. To shed light on the structure of this population and to integrate these two subspecies in the growing dataset of available haploid drone sequences, we performed whole-genome sequencing of 151 haploid drones.

RESULTS

Integrated analysis of our drone sequences with a similar dataset of European reference populations did not detect any significant admixture in the Algerian honey bees. Interestingly, most of the genetic variation was not found between the A. m. intermissa and A. m. sahariensis subspecies; instead, two main genetic clusters were found along an East-West axis. We found that the correlation between genetic and geographic distances was higher in the Western cluster and that close-family relationships were mostly detected in the Eastern cluster, sometimes at long distances. In addition, we selected a panel of 96 ancestry-informative markers to decide whether a sampled bee is Algerian or not, and tested this panel in simulated cases of admixture.

CONCLUSIONS

The differences between the two main genetic clusters suggest differential breeding management between eastern and western Algeria, with greater exchange of genetic material over long distances in the east. The lack of detected admixture events suggests that, unlike what is seen in many places worldwide, imports of queens from foreign countries do not seem to have occurred on a large scale in Algeria, a finding that is relevant for conservation purposes. In addition, the proposed panel of 96 markers was found effective to distinguish Algerian from European honey bees. Therefore, we conclude that applying this approach to other taxa is promising, in particular when genetic differentiation is difficult to capture.

Exploring a Potential Avenue for Beekeeping in Ireland: Safeguarding Locally Adapted Honeybees for Breeding Varroa-Resistant Lines

Beekeeping in Ireland has been strongly impacted by the parasitic mite Varroa destructor, whose introduction caused alarming honeybee colony losses. If unmitigated, these losses could lead to the disappearance of the native honeybee subspecies, Apis mellifera mellifera, with severe consequences for local biodiversity. Although beekeepers play a pivotal role in mitigating this crisis, beekeeping in Ireland is less intensive compared to other European regions, lacking significant infrastructure or support. These circumstances offer a unique opportunity for the development of national programmes that promote sustainable beekeeping practices for varroa control. Notably, local accounts highlight an increasing number of beekeepers successfully managing colonies in the absence of treatments, indicating a potential avenue for developing varroa-resistant stocks through selection of local colonies. Through a survey, we explored beekeeper's opinions and attitudes towards future national projects focused on the development of sustainable beekeeping practices and selection for varroa resistance. The findings confirm the hobbyist nature of Irish beekeepers and their preference for the native honey bee. Some beekeepers were reported to be effectively controlling varroa without treatment, yielding comparable survivals to those using treatments. The majority expressed preference towards a varroa-resistant line if it were of native origin; a few were open to importing non-Irish lines. Overall, a strong willingness to participate in a national breeding programme was expressed. These findings highlight a prime opportunity for Ireland to establish a community-driven strategy based on sustainable beekeeping practices for safeguarding native honeybees and local biodiversity.

The Potential of Instrumental Insemination for Sustainable Honeybee Breeding

Mating control is crucial in honeybee breeding and commonly guaranteed by bringing virgin queens to isolated mating stations (IMS) for their nuptial flights. However, most breeding programs struggle to provide sufficiently many IMS. Research institutions routinely perform instrumental insemination of honeybees, but its potential to substitute IMS in breeding programs has not been sufficiently studied. We performed stochastic simulations to compare instrumental insemination strategies and mating on IMS in terms of genetic progress and inbreeding development. We focused on the role of paternal generation intervals, which can be shortened to two years with instrumental insemination in comparison to three years when using IMS. After 70 years, instrumental insemination yielded up to 42% higher genetic gain than IMS strategies-particularly with few available mating sites. Inbreeding rates with instrumental insemination and IMS were comparable. When the paternal generation interval in instrumental insemination was stretched to three years, the number of drone producers required for sustainable breeding was reduced substantially. In contrast, when shortening the interval to two years, it yielded the highest generational inbreeding rates (up to 2.28%). Overall, instrumental insemination with drones from a single colony appears as a viable strategy for honeybee breeding and a promising alternative to IMS.

Observation of Genetic Gain with Instrumental Insemination of Honeybee Queens

Controlling mating in the honeybee (Apis mellifera) is part of one of the greatest challenges for the beekeeping industry's genetic selection programs due to specific characteristics of their reproduction. Several techniques for supervising honeybee mating with relative effective control have been developed over the years to allow honeybee selection. As part of this project, we compared the genetic gains for several colony performance traits, obtained using the BLUP-animal method, according to the selection pressure applied in controlled reproduction (directed fertilization versus instrumental insemination). Our results show similar genetic gains for hygienic behavior and honey production between colonies whether queens were fertilized naturally or via instrumental insemination, as well as similar or lower genetic gains for colonies with queens inseminated for spring development. In addition, we noticed greater fragility in queens following insemination. These findings show that instrumental insemination is an effective tool for reproductive control in genetic selection and for estimating breeding values more precisely. However, this technique does not result in queens of superior genetic quality for commercial purposes.

First large-scale genomic prediction in the honey bee

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, 2970 queens were genotyped to gather a reference population. For the application of genomic selection in honey bees, this study analyzes the accuracy 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 accuracy of pedigree-based estimated breeding values was 0.12 for honey yield, and ranged from 0.42 to 0.61 for the workability traits. The inclusion of genomic marker data improved these accuracies to 0.23 for honey yield, and a range from 0.44 to 0.65 for the workability traits. The inclusion of genomic data did not improve the accuracy of the disease-related traits. Traits with high heritability for maternal effects compared to the heritability for direct effects showed the most promising results. For all traits except the Varroa resistance traits, the bias with genomic methods was on a similar level compared to the bias with pedigree-based BLUP. The results show that genomic selection can successfully be applied to honey bees.

Heritability of Apis mellifera recapping behavior and suppressed mite reproduction as resistance traits towards Varroa destructor

The selection of honeybee strains resistant to the ectoparasitic mite Varroa destructor is generally considered as one of the most sustainable ways of coping with this major bee parasite. Thus, breeding efforts increasingly focus on resistance parameters in addition to common beekeeping traits like honey yield and gentleness. In every breeding effort, the success strongly depends on the quantifiability and heritability of the traits accounted. To find the most suitable traits among the manifold variants to assess Varroa resistance, it is necessary to evaluate how easily a trait can be measured (i.e., testing effort) in relation to the underlying heritability (i.e., expected transfer to the following generation). Various possible selection traits are described as beneficial for colony survival in the presence of Varroa destructor and therefore are measured in breeding stocks around the globe. Two of them in particular, suppressed mite reproduction (SMR, sensu lato any reproductive failure of mother mites) and recapping of already sealed brood cells have recently gained increasing attention among the breeders because they closely resemble resistance mechanisms of some Varroa-surviving honeybee populations. However, it was still unknown whether the genetic background of the trait is sufficient for targeted selection. We therefore investigated the heritabilities and genetic correlations for SMR and REC, distinguishing between recapping of infested cells (RECinf) and all cells (RECall), on an extensive dataset of Buckfast and Carniolan stock in Germany. With an accessible h² of 0.18 and 0.44 for SMR and an accessible h² of 0.44 and 0.40 for RECinf, both traits turned out to be very promising for further selection in the Buckfast and Carnica breeding population, respectively.

Immunohistochemical Distribution of Serotonin Transporter (SERT) in the Optic Lobe of the Honeybee, Apis mellifera

Simple Summary

Serotonin is ubiquitously expressed in vertebrates and invertebrates, where it regulates specific behavioural patterns. Though the specific effects of serotonin release in the optic lobe are not entirely known, increasing evidence associates the serotonergic system with optic lobe-mediated behaviours. In this study, the localization of serotonin transporter (SERT) was immunohistochemically analysed in the optic lobes of moderate, docile and aggressive worker honeybees. SERT-immunoreactive fibres were stratified in the optic lobe and distributed in the three visual neuropils: lamina, medulla and lobula. Interestingly, SERT immunoreactivity was inversely related to aggressive behaviour. The present study indicates that low levels of serotonin in the optic lobe are associated with aggressive behaviour.

Abstract

Visual information is processed in the optic lobes, which consist of three retinotopic neuropils. These are the lamina, the medulla and the lobula. Biogenic amines play a crucial role in the control of insect responsiveness, and serotonin is clearly related to aggressiveness in invertebrates. Previous studies suggest that serotonin modulates aggression-related behaviours, possibly via alterations in optic lobe activity. The aim of this investigation was to immunohistochemically localize the distribution of serotonin transporter (SERT) in the optic lobe of moderate, docile and aggressive worker honeybees. SERT-immunoreactive fibres showed a wide distribution in the lamina, medulla and lobula; interestingly, the highest percentage of SERT immunoreactivity was observed across all the visual neuropils of the docile group. Although future research is needed to determine the relationship between the distribution of serotonin fibres in the honeybee brain and aggressive behaviours, our immunohistochemical study provides an anatomical basis supporting the role of serotonin in aggressive behaviour in the honeybee.

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

Genetic and residual variances of traits are important input parameters for best linear unbiased prediction (BLUP) breeding value estimation. In honeybees, estimates of these variances are often associated with large standard errors, entailing a risk to perform genetic evaluations under wrong premises. The consequences hereof have not been sufficiently studied. In particular, there are no adequate investigations on this topic accounting for multi-trait selection or genetic peculiarities of the honeybee. We performed simulation studies and explored the consequences of selection for honeybee populations with a broad range of true and assumed genetic parameters. We found that in single-trait evaluations, the response to selection was barely compromised by assuming erroneous parameters, so that reductions in genetic progress after 20 years never exceeded 21%. Phenotypic selection appeared inferior to BLUP selection, particularly under low heritabilities. Parameter choices for genetic evaluation had great effects on inbreeding development. By wrongly assuming high heritabilities, inbreeding rates were reduced by up to 74%. When parallel selection was performed for two traits, the right choice of genetic parameters appeared considerably more crucial as several incorrect premises yielded inadvertent negative selection for one of the traits. This phenomenon occurred in multiple constellations in which the selection traits expressed a negative genetic correlation. It was not reflected in the estimated breeding values. Our results indicate that breeding efforts heavily rely on detailed knowledge on genetic parameters, particularly when multi-trait selection is performed. Thus, considerable effort should be invested into precise parameter estimations.

Long-Term Artificial Selection for Increased Larval Body Weight of Hermetia illucens in Industrial Settings

Black soldier fly (Hermetia illucens) farming has exponentially increased in recent years due to the ability of its larvae to efficiently convert low-grade organic materials into high-value food, feed, and technical products. There is a need to further improve the efficiency of production, to meet the rising demands for proteins in the feed and food industries under limited resources. One means of improvement is artificial selection, which has been widely applied in plants and in other livestock species. In 2019, a genetic improvement program was started with the aim to increase larval body weight in black soldier fly larvae. In this paper, we present the outcomes of this breeding program after 10, 13, and 16 generations of selection. The performance of the selected body weight line was compared to the base population line over six experimental rounds under different environmental conditions. Under automated production settings, an average increase of +39% in larval weight, +34% in wet crate yield, +26% in dry matter crate yield, +32% in crude protein per crate, and +21% crude fat per crate was achieved in the selected line compared to the base population line. This research demonstrates the potential contribution of artificial selection to improve efficiency when farming black soldier flies in industrial settings. Further research is needed to fully unlock that potential.

Decreased Mite Reproduction to Select Varroa destructor (Acari: Varroidae) Resistant Honey Bees (Hymenoptera: Apidae): Limitations and Potential Methodological Improvements

The invasive parasitic mite, Varroa destructor (Anderson and Trueman), is the major biotic threat to the survival of European honey bees, Apis mellifera L. To improve colony survival against V. destructor, the selection of resistant lineages against this parasite is considered a sustainable solution. Among selected traits, mite fertility and fecundity, often referred to as suppressed mite reproduction are increasingly used in breeding programmes. However, the current literature leaves some gaps in the assessment of the effectiveness of selecting these traits toward achieving resistance. In the population studied here, we show a low repeatability and reproducibility of mite fertility and fecundity phenotypes, as well as a low correlation of these traits with infestation rates of colonies. Phenotyping reliability could neither be improved by increasing the number of worker brood cells screened, nor by screening drone brood, which is highly attractive for the parasite and available early in the season, theoretically allowing a reduction of generation time and thus an acceleration of genetic progress in selected lineages. Our results provide an evaluation of the potential and limitations of selecting on decreased mite reproduction traits to obtain V. destructor-resistant honeybee colonies. To allow for a more precise implementation of such selection and output reporting, we propose a refined nomenclature by introducing the terms of decreased mite reproduction and reduced mite reproduction, depending on the extent of mite reproduction targeted. We also highlight the importance of ensuring accurate phenotyping ahead of initiating long-lasting selection programmes.

Diet Supplementation Helps Honey Bee Colonies in Combat Infections by Enhancing their Hygienic Behaviour

The hygienic behavior in honey bees is a complex polygenic trait that serves as a natural defense mechanism against bacterial and fungal brood diseases and Varroa destructor mites infesting brood cells. The aim of this study was to evaluate the effect of a dietary amino acids and vitamins supplement “BEEWELL AminoPlus” on hygienic behavior of Apis mellifera colonies combating microsporidial and viral infections. The experiment was performed during a one-year period on 40 colonies alloted to five groups: one supplemented and infected with Nosema ceranae and four viruses (Deformed wing virus - DWV, Acute bee paralysis virus - ABPV, Chronic bee paralysis virus - CBPV and Sacbrood virus – SBV), three not supplemented, but infected with N. ceranae and/ or viruses, and one negative control group. Beside the l isted pathogens, honey bee trypanosomatids were also monitored in all groups.

The supplement “BEEWELL AminoPlus” induced a significant and consistent increase of the hygienic behavior in spite of the negative effects of N. ceranae and viral infections. N. ceranae and viruses significantly and consistently decreased hygienic behavior, but also threatened the survival of bee colonies. The tested supplement showed anti-Nosema effect, since the N. ceranae infection level significantly and consistently declined only in the supplemented group. Among infected groups, only the supplemented one remained Lotmaria passim-free throughout the study. In conclusion, diet supplementation enhances hygienic behavior of honey bee colonies and helps them fight the most common infections of honey bees.

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

Estimating genetic parameters of quantitative traits is a prerequisite for animal breeding. In honeybees, the genetic variance separates into queen and worker effects. However, under data paucity, parameter estimations that account for this peculiarity often yield implausible results. Consequently, simplified models that attribute all genetic contributions to either the queen (queen model) or the workers (worker model) are often used to estimate variance components in honeybees. However, the causes for estimations with the complete model (colony model) to fail and the consequences of simplified models for variance estimates are little understood. We newly developed the necessary theory to compare parameter estimates that were achieved by the colony model with those of the queen and worker models. Furthermore, we performed computer simulations to quantify the influence of model choice, estimation algorithm, true genetic parameters, rates of controlled mating, apiary sizes, and phenotype data completeness on the success of genetic parameter estimations. We found that successful estimations with the colony model were only possible if at least some of the queens mated controlled on mating stations. In that case, estimates were largely unbiased if more than 20% of the colonies had phenotype records. The simplified queen and worker models proved more stable and yielded plausible parameter estimates for almost all settings. Results obtained from these models were unbiased when mating was uncontrolled, but with controlled mating, the simplified models consistently overestimated heritabilities. This study elucidates the requirements for variance component estimation in honeybees and provides the theoretical groundwork for simplified honeybee models.

Simulation studies to optimize genomic selection in honey bees

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00654-x.

A theoretical derivation of response to selection with and without controlled mating in honeybees

BACKGROUND

In recent years, the breeding of honeybees has gained significant scientific interest, and numerous theoretical and practical improvements have been made regarding the collection and processing of their performance data. It is now known that the selection of high-quality drone material is crucial for mid to long-term breeding success. However, there has been no conclusive mathematical theory to explain these findings.

METHODS

We derived mathematical formulas to describe the response to selection of a breeding population and an unselected passive population of honeybees that benefits indirectly from genetic improvement in the breeding population via migration. This was done under the assumption of either controlled or uncontrolled mating of queens in the breeding population.

RESULTS

Our model equations confirm what has been observed in simulation studies. In particular, we have proven that the breeding population and the passive population will show parallel genetic gain after some years and we were able to assess the responses to selection for different breeding strategies. Thus, we confirmed the crucial importance of controlled mating for successful honeybee breeding. When compared with data from simulation studies, the derived formulas showed high coefficients of determination [Formula: see text] in cases where many passive queens had dams from the breeding population. For self-sufficient passive populations, the coefficients of determination were lower ([Formula: see text]) if the breeding population was under controlled mating. This can be explained by the limited simulated time-frame and lower convergence rates.

CONCLUSION

The presented theoretical derivations allow extrapolation of honeybee-specific simulation results for breeding programs to a wide range of population parameters. Furthermore, they provide general insights into the genetic dynamics of interdependent populations, not only for honeybees but also in a broader context.