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Data from: Spatial patterns of neutral and functional genetic variation reveal patterns of local adaptation in raccoon (Procyon lotor) populations exposed to raccoon rabies

Cite this dataset

Castillo, Sarrah et al. (2014). Data from: Spatial patterns of neutral and functional genetic variation reveal patterns of local adaptation in raccoon (Procyon lotor) populations exposed to raccoon rabies [Dataset]. Dryad. https://doi.org/10.5061/dryad.d6p27

Abstract

Local adaptation is necessary for population survival and depends on the interplay between responses to selective forces and demographic processes that introduce or retain adaptive and maladaptive attributes. Host-parasite systems are dynamic, varying in space and time, where both host and parasites must adapt to their ever-changing environment in order to survive. We investigated patterns of local adaptation in raccoon populations with varying temporal exposure to the raccoon rabies virus (RRV). RRV infects approximately 85% of the population when epizootic and has been presumed to be completely lethal once contracted; however, disease challenge experiments and varying spatial patterns of RRV spread suggest some level of immunity may exist. We first assessed patterns of local adaptation in raccoon populations along the eastern seaboard of North America by contrasting spatial patterns of neutral (microsatellite loci) and functional, major histocompatibility complex (MHC) genetic diversity and structure. We explored variation of MHC allele frequencies in light of temporal population exposure to RRV (0-60 years) and specific RRV strains in infected raccoons. Our results revealed high levels of MHC variation (66 DRB exon 2 alleles) and pronounced genetic structure relative to neutral microsatellite loci, indicative of local adaptation. We found a positive association linking MHC genetic diversity and temporal RRV exposure, but no association with susceptibility and resistance to RRV strains. These results have implications for landscape epidemiology studies seeking to predict the spread of RRV and present an example of how population demographics influence the degree to which populations adapt to local selective pressures.

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Location

New York
Florida
Alabama
Ontario