Host innate immune response profiling reveals hidden viral infections across diverse animal species

Virus discovery using RNA-seq data from wildlife and livestock offers a powerful strategy for identifying unknown pathogens with pandemic potential. However, conventional approaches rely on homology-based searches that have limited sensitivity for highly divergent viruses, are computationally intensive at scale, and cannot distinguish true infections from contamination. Viral infection induces interferon-stimulated genes (ISGs), key components of the frontline antiviral defense, and their expression serves as a robust indicator of viral infection. Here, we developed a host-response–based virus discovery framework that rapidly quantifies ISG expression and predicts viral infection status. Applying this framework to ~210,000 RNA-seq data sets from diverse mammalian and avian species, we identified hidden viral infections across diverse hosts, including those caused by highly divergent viruses missed by a conventional approach. Our framework complements existing virus discovery strategies by adding host innate immune response context and enabling computationally efficient prescreening for scalable viral surveillance. Data sets Data set 1: Metadata for the Shaw et al. RNA-seq data set.Data set 2: Metadata for the He et al. and Zhao et al. RNA-seq data sets.Data set 3: Metadata for the 170k RNA-seq data set.Data set 4: Metadata for the 40k RNA-seq data set.Data set 5: ISG Profiler output for the Shaw et al. RNA-seq data set.Data set 6: ISG Profiler output for the He et al. and Zhao et al. RNA-seq data sets.Data set 7: ISG Profiler output for the 170k RNA-seq data set.Data set 8: ISG Profiler output for the 40k RNA-seq data set.Data set 9: Metadata for sequences in the ortholog database.Data set 10: geNomad results for the 170k RNA-seq data set.Data set 11: geNomad results for the 40k RNA-seq data set.Data set 12: Viral-derived contigs identified by BLASTx.Data set 13: Metadata for viral sequences used in the phylogenetic analyses.