Abstract
Pathogenic viruses represent a small fraction of viral diversity, and emerging diseases are frequently the result of cross-species transmissions. Therefore, we need to develop high-throughput techniques to investigate a broader range of viral biodiversity across a greater number of species. This is especially important in the context of new practices in agriculture that have arisen to tackle the challenges of global food security, including the rising number of marine and freshwater species that are used in aquaculture. In this study, we demonstrate the utility of combining evolutionary approaches with bioinformatics to mine non-viral genome data for viruses, by adapting methods from paleovirology. We report the discovery of a new lineage of dsDNA viruses that are associated with at least fifteen different species of fish. This approach also enabled us to simultaneously identify sequences that likely represent endogenous viral elements, which we experimentally confirmed in commercial salmon samples. Moreover, genomic analysis revealed that the endogenous sequences have co-opted PiggyBac-like transposable elements, possibly as a mechanism of intragenomic proliferation. The identification of novel viruses from genome data shows that our approach has applications in genomics, virology, and the development of best practices for aquaculture and farming.