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Description: Honey bees are exposed to a number of damaging pathogens and parasites. The most destructive among them, affecting mainly the brood, is Varroa destructor. A promising approach to prevent its spread is to breed for Varroa‐tolerant honey bees. A trait that has been shown to provide significant resistance against the Varroa mite is hygienic behaviour, a behavioural response of honey bee workers to brood diseases in general. This study reports the development of a 44K SNP assay, specifically designed for the analysis of hygienic behaviour of individual worker bees (Apis mellifera carnica) directed against V. destructor. Initially, 70 000 SNPs chosen from a large set of SNPs published by the Honey Bee Genome Project were validated for their suitability in the analysis of the Varroa resistance trait ‘uncapping of Varroa‐infested brood’. This was achieved by genotyping of pooled DNA samples of trait bearers and two trait‐negative controls using next‐generation sequencing. Approximately 36 000 of these validated SNPs and another 8000 SNPs not validated in this study were selected for the construction of a SNP assay. This assay will be employed in following experiments to analyse individualized DNA samples in order to identify quantitative trait loci (QTL) involved in the control of the investigated trait and to evaluate and possibly confirm QTL found in other studies. However, this assay is not just suitable to study Varroa tolerance, it is as well applicable to analyse any other trait in honey bees. In addition, because of its high density, this assay provides access into genomic selection with respect to several traits considered in honey bee breeding. It will become publicly available via AROS Applied Biotechnology AS, Aarhus, Denmark, before the end of the year 2011.

Description: Over the past years, reports have indicated that honey bee populations are declining and that infestation by an ecto-parasitic mite (Varroa destructor) is one of the main causes. Selective breeding of resistant bees can help to prevent losses due to the parasite, but it requires that a robust breeding program and genetic evaluation are implemented. Genomic selection has emerged as an important tool in animal breeding programs and simulation studies have shown that it yields more accurate breeding values estimates, higher genetic gain and low rates of inbreeding. Since genomic selection relies on marker data, simulations conducted on a genomic dataset are a pre-requisite before selection can be implemented. Although genomic datasets have been simulated in other species undergoing genetic evaluation, simulation of a genomic dataset specific to the honey bee is required since this species has distinct genetic and reproductive biology characteristics. Our software program was aimed at constructing a base population by simulating a random mating honey bee population. A forward-time population simulation approach was applied since it allows modeling of genetic characteristics and reproductive behavior specific to the honey bee.  Results: Our software program yielded a genomic dataset for a base population in linkage disequilibrium. In addition, information was obtained on (1) the position of markers on each chromosome, (2) allele frequency, (3) ?2 statistics for Hardy- Weinberg equilibrium, (4) a sorted list of markers with a minor allele frequency less than or equal to the input value, (5) average r2 values of linkage disequilibrium between all simulated marker loci pair for all generations and (6) average r2 value of linkage disequilibrium in the last generation for selected markers with the highest minor allele frequency. Conclusion: We developed a software program that takes into account the genetic and reproductive biology characteristics specific to the honey bee and that can be used to constitute a genomic dataset compatible with the simulation studies necessary to optimize breeding programs. The source code together with an instruction file is freely accessible at http://msproteomics.org/Research/Misc/honeybeepopulationsimulator.html