Title : A population genomics approach to inferring local movement of plant pathogen vectors (Bactericera cockerelli, Hemiptera: Triozidae) among solanaceous hosts
Abstract:
Herbivores often move among spatially interspersed host plants, tracking high-quality resources through space and time. This dispersal is of particular interest for vectors of plant pathogens. Existing molecular tools to track such movement have yielded important insights, but often provide insufficient genetic resolution to infer spread at finer spatiotemporal scales. Here, we explore the use of Nextera-tagmented reductively-amplified DNA (NextRAD) sequencing to infer movement of a highly-mobile winged insect, the potato psyllid (Bactericera cockerelli), among host plants. The psyllid vectors the pathogen that causes zebra chip disease in potato (Solanum tuberosum), but understanding and managing the spread of this pathogen is limited by uncertainty about the insect’s host plant(s) outside of the growing season. We identified 8,443 polymorphic loci among psyllids separated spatiotemporally on potato or in patches of bittersweet nightshade (S. dulcumara), a weedy plant proposed to be the source of potatocolonizing psyllids. A subset of the psyllids on potato exhibited close genetic similarity to insects on nightshade, consistent with regular movement between these two host plants. However, a second subset of potato-collected psyllids was genetically distinct from those collected on bittersweet nightshade; this suggests that a currently unrecognized host-plant species could be contributing to psyllid populations in potato. Oftentimes, dispersal of vectors of plant or animal pathogens must be tracked at a relatively fine scale in order to understand, predict, and manage disease spread. With this research we demonstrate that emerging sequencing technologies that detect SNPs across a vector’s entire genome can be used to infer such localized movement.
