title: Understanding the complex evolution of rapidly mutating viruses with deep sequencing: Beyond the analysis of viral diversity.
abstract: With the advent of affordable deep sequencing technologies, detection of low frequency variants within genetically diverse viral populations can now be achieved with unprecedented depth and efficiency. The high-resolution data provided by next generation sequencing technologies is currently recognised as the gold standard in estimation of viral diversity. In the analysis of rapidly mutating viruses, longitudinal deep sequencing datasets from viral genomes during individual infection episodes, as well as at the epidemiological level during outbreaks, now allow for more sophisticated analyses such as statistical estimates of the impact of complex mutation patterns on the evolution of the viral populations both within and between hosts. These analyses are revealing more accurate descriptions of the evolutionary dynamics that underpin the rapid adaptation of these viruses to the host response, and to drug therapies. This review assesses recent developments in methods and provide informative research examples using deep sequencing data generated from rapidly mutating viruses infecting humans, particularly hepatitis C virus (HCV), human immunodeficiency virus (HIV), Ebola virus and influenza virus, to understand the evolution of viral genomes and to explore the relationship between viral mutations and the host adaptive immune response. Finally, we discuss limitations in current technologies, and future directions that take advantage of publically available large deep sequencing datasets.
authors.affiliation: School of Medical Sciences, Faculty of Medicine, UNSW Australia, Sydney, NSW 2052, Australia; The Kirby Institute, UNSW Australia, Sydney, NSW 2052, Australia.
authors.forename: Preston
authors.initials: P
authors.lastname: Leung
authors.affiliation: School of Medical Sciences, Faculty of Medicine, UNSW Australia, Sydney, NSW 2052, Australia; The Kirby Institute, UNSW Australia, Sydney, NSW 2052, Australia.
authors.forename: Auda A
authors.initials: AA
authors.lastname: Eltahla
authors.affiliation: The Kirby Institute, UNSW Australia, Sydney, NSW 2052, Australia.
authors.forename: Andrew R
authors.initials: AR
authors.lastname: Lloyd
authors.affiliation: School of Medical Sciences, Faculty of Medicine, UNSW Australia, Sydney, NSW 2052, Australia; The Kirby Institute, UNSW Australia, Sydney, NSW 2052, Australia.
authors.forename: Rowena A
authors.initials: RA
authors.lastname: Bull
authors.affiliation: School of Medical Sciences, Faculty of Medicine, UNSW Australia, Sydney, NSW 2052, Australia; The Kirby Institute, UNSW Australia, Sydney, NSW 2052, Australia. Electronic address: luciani@unsw.edu.au.
authors.forename: Fabio
authors.initials: F
authors.lastname: Luciani
mesh_terms: D000818:Animals; D024882:Drug Resistance, Viral; D019143:Evolution, Molecular; D016679:Genome, Viral; D059014:High-Throughput Nucleotide Sequencing; D054884:Host-Pathogen Interactions; D006801:Humans; D009154:Mutation; D010802:Phylogeny; D058974:Phylogeography; D014777:Virus Diseases / Q000453:epidemiology / Q000635:transmission / Q000821:virology; D014780:Viruses / Q000145:classification / Q000187:drug effects / Q000235:genetics*
keywords: Co-occurring mutation; Deep sequencing; Immune escape; Phylogenetics; Rapidly mutating viruses; Transmission clusters