Literature DB >> 32445281

Disease swamps molecular signatures of genetic-environmental associations to abiotic factors in Tasmanian devil (Sarcophilus harrisii) populations.

Alexandra K Fraik1, Mark J Margres1, Brendan Epstein1,2, Soraia Barbosa3, Menna Jones4, Sarah Hendricks3, Barbara Schönfeld4, Amanda R Stahlke3, Anne Veillet3, Rodrigo Hamede4, Hamish McCallum5, Elisa Lopez-Contreras1, Samantha J Kallinen1, Paul A Hohenlohe3, Joanna L Kelley1, Andrew Storfer1.   

Abstract

Landscape genomics studies focus on identifying candidate genes under selection via spatial variation in abiotic environmental variables, but rarely by biotic factors (i.e., disease). The Tasmanian devil (Sarcophilus harrisii) is found only on the environmentally heterogeneous island of Tasmania and is threatened with extinction by a transmissible cancer, devil facial tumor disease (DFTD). Devils persist in regions of long-term infection despite epidemiological model predictions of species' extinction, suggesting possible adaptation to DFTD. Here, we test the extent to which spatial variation and genetic diversity are associated with the abiotic environment (i.e., climatic variables, elevation, vegetation cover) and/or DFTD. We employ genetic-environment association analyses using 6886 SNPs from 3287 individuals sampled pre- and post-disease arrival across the devil's geographic range. Pre-disease, we find significant correlations of allele frequencies with environmental variables, including 365 unique loci linked to 71 genes, suggesting local adaptation to abiotic environment. The majority of candidate loci detected pre-DFTD are not detected post-DFTD arrival. Several post-DFTD candidate loci are associated with disease prevalence and were in linkage disequilibrium with genes involved in tumor suppression and immune response. Loss of apparent signal of abiotic local adaptation post-disease suggests swamping by strong selection resulting from the rapid onset of DFTD.
© 2020 The Authors. Evolution © 2020 The Society for the Study of Evolution.

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Year:  2020        PMID: 32445281      PMCID: PMC7384379          DOI: 10.1111/evo.14023

Source DB:  PubMed          Journal:  Evolution        ISSN: 0014-3820            Impact factor:   3.694


  104 in total

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