The antiviral state has shaped the CpG composition of the vertebrate interferome to avoid self-targeting

How do vertebrates stop their sequence-specific antiviral defences from accidentally targeting their own gene transcripts? We show that self-targeting by antiviral effectors - and ZAP in particular - has shaped the composition of host transcripts in the vertebrate interferome. These unique compositional signatures give us a better picture of what viral genomes capable of evading sequence-specific host defences might look like, an observation we are exploiting in our work to develop genome-based zoonotic risk prediction methods.

Identifying and prioritizing potential human-infecting viruses from their genome sequences

We describe machine learning algorithms that identify candidate zoonoses using evolutionary signals of host range encoded in viral genomes. This allows identification of high-risk viruses immediately upon discovery, increasing both the feasibility and likelihood of downstream virological and ecological characterization and allowing for evidence-driven virus surveillance.