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Evaluation of Suppressed Mite Reproduction (SMR) Reveals Potential for Varroa Resistance in European Honey Bees (Apis mellifera L.)

Fanny Mondet, Melanie Parejo, Marina D. Meixner, Cecília Costa, Per Kryger, Sreten Andonov, Bertrand Servin, Benjamin Basso, Małgorzata Bieńkowska, Gianluigi Bigio, Eliza Căuia, Cebotari Valentina, Bjørn Dahle, Marica Maja Dražić, Fani Hatjina, Marin Kovačić, Justinas Kretavičius, A. Sofia Lima, Beata Panasiuk, M. Alice Pinto, Aleksandar Uzunov, J. Wilde, Ralph Büchler

2020Insects44 citationsDOIOpen Access PDF

Abstract

In the fight against the Varroa destructor mite, selective breeding of honey bee (Apis mellifera L.) populations that are resistant to the parasitic mite stands as a sustainable solution. Selection initiatives indicate that using the suppressed mite reproduction (SMR) trait as a selection criterion is a suitable tool to breed such resistant bee populations. We conducted a large European experiment to evaluate the SMR trait in different populations of honey bees spread over 13 different countries, and representing different honey bee genotypes with their local mite parasites. The first goal was to standardize and validate the SMR evaluation method, and then to compare the SMR trait between the different populations. Simulation results indicate that it is necessary to examine at least 35 single-infested cells to reliably estimate the SMR score of any given colony. Several colonies from our dataset display high SMR scores indicating that this trait is present within the European honey bee populations. The trait is highly variable between colonies and some countries, but no major differences could be identified between countries for a given genotype, or between genotypes in different countries. This study shows the potential to increase selective breeding efforts of V. destructor resistant populations.

Topics & Concepts

Varroa destructorBiologyVarroaHoney beeMiteDestructorVarroa sensitive hygieneTraitReproductionSelection (genetic algorithm)BreedResistance (ecology)ZoologyVeterinary medicineEcologyArtificial intelligenceProgramming languageMedicineComputer scienceInsect and Pesticide ResearchPlant and animal studiesInsect and Arachnid Ecology and Behavior
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