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Empirical data relating body mass to immune defence against infections remain limited. Although the metabolic theory of ecology predicts that larger organisms would have weaker immune responses, recent studies have suggested that the opposite may be true. These discoveries have led to the safety factor hypothesis, which proposes that larger organisms have evolved stronger immune defences because they carry greater risks of exposure to pathogens and parasites. In this study, we simulated sepsis by exposing blood from nine primate species to a bacterial lipopolysaccharide (LPS), measured the relative expression of immune and other genes using RNAseq, and fitted phylogenetic models to determine how gene expression was related to body mass. In contrast to non-immune-annotated genes, we discovered hypermetric scaling in the LPS-induced expression of innate immune genes, such that large primates had a disproportionately greater increase in gene expression of immune genes compared to small primates. Hypermetric immune gene expression appears to support the safety factor hypothesis, though this pattern may represent a balanced evolutionary mechanism to compensate for lower per-transcript immunological effectiveness. This study contributes to the growing body of immune allometry research, highlighting its importance in understanding the complex interplay between body size and immunity over evolutionary timescales.

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., Competing Interests: Competing interests statement:The authors declare no competing interest.