Modelling viral evolution and adaptation: challenges and rewards

Abstract

Viral populations are extremely plastic. They maintain and steadily generate high levels of genotypic and phenotypic diversity that may result in different adaptive strategies. A major unknown factor in constructing realistic models of viral evolution is how mutations affect fitness, which amounts to unveiling the nature of viral fitness landscapes. Our understanding of viral complexity is improving thanks to new techniques as deep sequencing or massive computation, and to systematic laboratory assays. In this way, we are clearing up the role played by neutral networks of genotypes, by defective and cooperative interactions among viral mutants, or by co-evolution with immune systems. Models of viral evolution are thus improving their accuracy and becoming more competent from a conceptual and a predictive viewpoint.