Modelling the Evolutionary Dynamics of Cheating in Natural Viral Infections

Viral replication requires shared gene products that can be used by multiple viral genomes within the same cell. This gives rise to viral ‘cheats’, a type of mutant genome formed by large deletions, that spread by parasitizing full-length viruses. Cheats emerge spontaneously in laboratory infections of almost all known viruses, driving drastic reductions in viral population sizes, and reflecting a fundamental manifestation of conflict in virus evolution. However, our knowledge of viral cheating is limited almost entirely to laboratory studies conducted in tissue culture conditions. Understanding the evolution of viral cheats in natural infections would pave the way for transformative new ways to predict and control viral infections.

In this working group, we will provide the first quantitative insights into the evolution of cheats during natural viral infections. We will use modelling approaches drawn from population genetics to capture the emergence and subsequent selection of viral cheats, and then parameterise our results using a dataset of 198 natural influenza infections. This approach will allow us to quantify the strength of selection acting on the genome length of viral cheats within influenza, while developing a flexible framework for modelling cheat genetics and dynamics across viruses.