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Title: USE OF MICROSATELLITE DNA LOCI TO INFER GENETIC STRUCTURE IN THE HONEY BEE PARASITIC MITE VARROA DESTRUCTOR

Author
item Evans, Jay
item Pettis, Jeffery
item Sonstegard, Tad

Submitted to: Apidologie
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/7/2001
Publication Date: N/A
Citation: N/A

Interpretive Summary: While many parasites and pathogens impact honey bee health, mites in the genus Varroa are arguably the most serious honey bee pest worldwide. Our goal was to use newly developed genetic "DNA fingerprinting" markers to determine the genetic structure for populations of Varroa destructor. Knowing this structure allows estimates of mite migration rates and colonization dynamics at the level of apiaries and colonies. These estimates can aid attempts to regulate mite populations through changes in management practices, such as the spatial patterns of hives and the removal of heavily infested hives. The highly variable markers described here were used to predict mite movement within and between apiaries and regions of the United States. These estimates can be used by scientists and beekeeping professionals to minimize mite movement between hives.

Technical Abstract: To better estimate levels of migration by Varroa mites within and among colonies of their honey bee hosts, we used microsatellite DNA loci to genotype individual mites. We show levels of inbreeding that exceed those of most other organisms, but are in line with the mating structure of Varroa destructor. Cell-level relatedness estimates support the occurrence of multiple reproductive female mites in some cells. Colony-to-colony differences in allele frequencies were not significant by bootstrap analyses. At the apiary level, allele-frequency differences were significant among three apiaries surveyed, suggesting some limit of gene flow among these. Larger sample sizes, and perhaps a greater number of polymorphic loci, should resolve more directly the frequency of mite migration at different geographic scales. This information should aid the management of Varroa-infested hives and apiaries, by predicting the frequency of mite movement across hives, apiaries, and regions.