Intergenomic signatures of coevolution between Tasmanian devils and an infectious cancer

• 成果类型: Article
• 署名作者: Gallinson, Dylan G.; Kozakiewicz, Christopher P.; Rautsaw, Rhett M.; Beer, Marc A.; Ruiz-Aravena, Manuel; Comte, Sebastien; Hamilton, David G.; Kerlin, Douglas H.; Mccallum, Hamish I.; Hamede, Rodrigo; Jones, Menna E.; Storfer, Andrew; Mcminds, Ryan; Margres, Mark J.
• 署名单位: State University System of Florida; University of South Florida; State University System of Florida; University of South Florida; Washington State University; Michigan State University; University of Tasmania; Cornell University; Department of Primary Industries & Regional Development NSW; Griffith University
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-9139
• DOI: 10.1073/pnas.2307780121
• 发表日期: 2024-03-11
• 关键词: facial-tumor disease; genome-wide association; 2 transmissible cancers; population-structure; genetic diversity; MODEL; susceptibility; highlights; expression; DYNAMICS

摘要

Coevolution is common and frequently governs host-pathogen interaction outcomes. Phenotypes underlying these interactions often manifest as the combined products of the genomes of interacting species, yet traditional quantitative trait mapping approaches ignore these intergenomic interactions. Devil facial tumor disease (DFTD), an infectious cancer afflicting Tasmanian devils (Sarcophilus harrisii), has decimated devil populations due to universal host susceptibility and a fatality rate approaching 100%. Here, we used a recently developed joint genome- wide association study (i.e., co- GWAS) approach, 15 y of mark- recapture data, and 960 genomes to identify intergenomic signatures of coevolution between devils and DFTD. Using a traditional GWA approach, we found that both devil and DFTD genomes explained a substantial proportion of variance in how quickly susceptible devils became infected, although genomic architectures differed across devils and DFTD; the devil genome had fewer loci of large effect whereas the DFTD genome had a more polygenic architecture. Using a co- GWA approach, devil- DFTD intergenomic interactions explained -3x more variation in how quickly susceptible devils became infected than either genome alone, and the top genotype- by- genotype interactions were significantly enriched for cancer genes and signatures of selection. A devil regulatory mutation was associated with differential expression of a candidate cancer gene and showed putative allele matching effects with two DFTD coding sequence variants. Our results highlight the need to account for intergenomic interactions when investigating host-pathogen (co)evolution and emphasize the importance of such interactions when considering devil management strategies.