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Abstract Emerging infectious diseases (EIDs) not only cause catastrophic declines in wildlife populations but also generate selective pressures that may result in rapid evolutionary responses. One such EID is devil facial tumour disease (DFTD) in the Tasmanian devil. DFTD is almost always fatal and has reduced the average lifespan of individuals by around 2 years, likely causing strong selection for traits that reduce susceptibility to the disease, but population decline has also left Tasmanian devils vulnerable to inbreeding depression. We analysed 22 years of data from an ongoing study of a population of Tasmanian devils on Freycinet Peninsula, Tasmania, to (1) identify whether DFTD may be causing selection on body size, by estimating phenotypic and genetic correlations between DFTD and size traits, (2) estimate the additive genetic variance of susceptibility to DFTD, and (3) investigate whether size traits or susceptibility to DFTD were under inbreeding depression. We found a positive phenotypic relationship between head width and susceptibility to DFTD, but this was not underpinned by a genetic correlation. Conversely, we found a negative phenotypic relationship between body weight and susceptibility to DFTD, and there was evidence for a negative genetic correlation between susceptibility to DFTD and body weight. There was additive genetic variance in susceptibility to DFTD, head width and body weight, but there was no evidence for inbreeding depression in any of these traits. These results suggest that Tasmanian devils have the potential to respond adaptively to DFTD, although the realised evolutionary response will critically further depend on the evolution of DFTD itself. 

Abstract Understanding age structure in populations is foundational for ecological study, yet ascertaining the age of individuals in the wild can be problematic. Methods typically rely on the prior determination of a relationship between age and some morphological measurement specific to the species or animal group under investigation.We present a novel method to incorporate multiple measures of animal size and development to estimate age, using Bayesian parallel regression to integrate multiple regression relationships into predictions.We apply the method to Tasmanian devils, a carnivorous marsupial that is threatened by a transmissible cancer. We estimate devil age based on measures of mass, head width, canine over‐eruption and molar characteristics.Practical implication. The method provides a flexible framework with potential application to a range of species; however, the method is best suited to capture–mark–recapture style studies where repeated measures data have been collected for individuals across multiple points in time. 

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 ~3× 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.