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Elucidating the adaptive genetic potential of wildlife populations to environmental selective pressures is fundamental for species conservation. Genes of the major histocompatibility complex (MHC) are highly polymorphic, and play a key role in the adaptive immune response against pathogens. MHC polymorphism has been linked to balancing selection or heterogeneous selection promoting local adaptation. However, spatial patterns of MHC polymorphism are also influenced by gene flow and drift. Wolverines are highly vagile, inhabiting varied ecoregions that include boreal forest, taiga, tundra, and high alpine ecosystems. Here, we investigated the immunogenetic variation of wolverines in Canada as a surrogate for identifying local adaptation by contrasting the genetic structure at MHC relative to the structure at 11 neutral microsatellites to account for gene flow and drift. Evidence of historical positive selection was detected at MHC using maximum likelihood codon-based methods. Bayesian and multivariate cluster analyses revealed weaker population genetic differentiation at MHC relative to the increasing microsatellite genetic structure towards the eastern wolverine distribution. Mantel correlations of MHC against geographical distances showed no pattern of isolation by distance (IBD: r = -0.03,  p  = 0.9), whereas for microsatellites we found a relatively strong and significant IBD (r = 0.54,  p  = 0.01). Moreover, we found a significant correlation between microsatellite allelic richness and the mean number of MHC alleles, but we did not observe low MHC diversity in small populations. Overall these results suggest that MHC polymorphism has been influenced primarily by balancing selection and to a lesser extent by neutral processes such as genetic drift, with no clear evidence for local adaptation. This study contributes to our understanding of how vulnerable populations of wolverines may respond to selective pressures across their range.

Lack of Spatial Immunogenetic Structure among Wolverine (Gulo gulo) Populations Suggestive of Broad Scale Balancing Selection