title: Inferring the Clonal Structure of Viral Populations from Time Series Sequencing.
abstract: RNA virus populations will undergo processes of mutation and selection resulting in a mixed population of viral particles. High throughput sequencing of a viral population subsequently contains a mixed signal of the underlying clones. We would like to identify the underlying evolutionary structures. We utilize two sources of information to attempt this; within segment linkage information, and mutation prevalence. We demonstrate that clone haplotypes, their prevalence, and maximum parsimony reticulate evolutionary structures can be identified, although the solutions may not be unique, even for complete sets of information. This is applied to a chain of influenza infection, where we infer evolutionary structures, including reassortment, and demonstrate some of the difficulties of interpretation that arise from deep sequencing due to artifacts such as template switching during PCR amplification.
authors.affiliation: The Genome Analysis Centre, Norwich Research Park, Norwich, United Kingdom.
authors.forename: Donatien F
authors.initials: DF
authors.lastname: Chedom
authors.affiliation: MRC-University of Glasgow Centre for Virus Research, United Kingdom.
authors.forename: Pablo R
authors.initials: PR
authors.lastname: Murcia
authors.affiliation: The Genome Analysis Centre, Norwich Research Park, Norwich, United Kingdom.|School of Computing Sciences, University of East Anglia, Norwich, United Kingdom.
authors.forename: Chris D
authors.initials: CD
authors.lastname: Greenman
mesh_terms: D000465:Algorithms; D019295:Computational Biology; D019143:Evolution, Molecular; D059014:High-Throughput Nucleotide Sequencing; D008957:Models, Genetic; D009154:Mutation / Q000235:genetics; D010802:Phylogeny; D016133:Polymerase Chain Reaction; D012328:RNA Viruses / Q000145:classification* / Q000235:genetics*; D012367:RNA, Viral / Q000235:genetics*; D017423:Sequence Analysis, RNA / Q000379:methods*
chemical_list: D012367:RNA, Viral