Evolutionary Applications (Feb 2021)

Sarcoptic mange severity is associated with reduced genomic variation and evidence of selection in Yellowstone National Park wolves (Canis lupus)

  • Alexandra L. DeCandia,
  • Edward C. Schrom,
  • Ellen E. Brandell,
  • Daniel R. Stahler,
  • Bridgett M. vonHoldt

DOI
https://doi.org/10.1111/eva.13127
Journal volume & issue
Vol. 14, no. 2
pp. 429 – 445

Abstract

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Abstract Population genetic theory posits that molecular variation buffers against disease risk. Although this “monoculture effect” is well supported in agricultural settings, its applicability to wildlife populations remains in question. In the present study, we examined the genomics underlying individual‐level disease severity and population‐level consequences of sarcoptic mange infection in a wild population of canids. Using gray wolves (Canis lupus) reintroduced to Yellowstone National Park (YNP) as our focal system, we leveraged 25 years of observational data and biobanked blood and tissue to genotype 76,859 loci in over 400 wolves. At the individual level, we reported an inverse relationship between host genomic variation and infection severity. We additionally identified 410 loci significantly associated with mange severity, with annotations related to inflammation, immunity, and skin barrier integrity and disorders. We contextualized results within environmental, demographic, and behavioral variables, and confirmed that genetic variation was predictive of infection severity. At the population level, we reported decreased genome‐wide variation since the initial gray wolf reintroduction event and identified evidence of selection acting against alleles associated with mange infection severity. We concluded that genomic variation plays an important role in disease severity in YNP wolves. This role scales from individual to population levels, and includes patterns of genome‐wide variation in support of the monoculture effect and specific loci associated with the complex mange phenotype. Results yielded system‐specific insights, while also highlighting the relevance of genomic analyses to wildlife disease ecology, evolution, and conservation.

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