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bioRxiv · 10.1101/498436

Parallel genomic evolution of parasite tolerance in wild honey bee populations

Abstract

Sudden biotic pressures, such as those from novel diseases and pathogens, require populations to respond rapidly or face potential extinction. How this response process takes place remains poorly understood, particularly in natural environments. In this study we take advantage of unique decade-long data sets of two wild honey bee (Apis mellifera) populations in the United States to reconstruct the evolution of tolerance to a novel parasite, the ectoparasitic mite Varroa destructor. Upon the arrival of Varroa, the two geographically isolated populations simultaneously suffered massive Varroa-induced mortality, but stabilized within two years. Here we sequenced and phased genomes of 465 bees sampled from both populations annually over the decade that spanned Varroas arrival. Remarkably, we found that genetic changes were strongly correlated between the populations, suggesting parallel selective responses to Varroa parasitization. The arrival of Varroa was also correlated with an influx of genes of African origin into both populations, though surprisingly it did not substantially contribute to the overall similarity of the evolutionary response between them. Genes involved in metabolic, protein processing and developmental pathways were under particularly strong selection. It is possible that interactions among highly connected gene groups in these pathways may help channelize selective responses to novel parasites, causing completely unrelated populations to exhibit parallel evolutionary trajectories when faced with the same biotic pressure. Our analyses illustrate that ecologically relevant traits emerge from highly polygenic selection involving thousands of genes contributing to complex patterns of evolutionary change.

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BibTeXRIS

Bozek, K., Rangel, J., Arora, J., Tin, M., Crotteau, E., Loper, G., Fewell, J., Mikheyev, A.. 2018-12-19. Parallel genomic evolution of parasite tolerance in wild honey bee populations. https://doi.org/10.1101/498436

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