title: Using nearly full-genome HIV sequence data improves phylogeny reconstruction in a simulated epidemic.
abstract: HIV molecular epidemiology studies analyse viral pol gene sequences due to their availability, but whole genome sequencing allows to use other genes. We aimed to determine what gene(s) provide(s) the best approximation to the real phylogeny by analysing a simulated epidemic (created as part of the PANGEA_HIV project) with a known transmission tree. We sub-sampled a simulated dataset of 4662 sequences into different combinations of genes (gag-pol-env, gag-pol, gag, pol, env and partial pol) and sampling depths (100%, 60%, 20% and 5%), generating 100 replicates for each case. We built maximum-likelihood trees for each combination using RAxML (GTR + Γ), and compared their topologies to the corresponding true tree's using CompareTree. The accuracy of the trees was significantly proportional to the length of the sequences used, with the gag-pol-env datasets showing the best performance and gag and partial pol sequences showing the worst. The lowest sampling depths (20% and 5%) greatly reduced the accuracy of tree reconstruction and showed high variability among replicates, especially when using the shortest gene datasets. In conclusion, using longer sequences derived from nearly whole genomes will improve the reliability of phylogenetic reconstruction. With low sample coverage, results can be highly variable, particularly when based on short sequences.
authors.affiliation: Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK.
authors.forename: Gonzalo
authors.initials: G
authors.lastname: Yebra
authors.affiliation: Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK.
authors.forename: Emma B
authors.initials: EB
authors.lastname: Hodcroft
authors.affiliation: Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK.
authors.forename: Manon L
authors.initials: ML
authors.lastname: Ragonnet-Cronin
authors.affiliation: Wellcome Trust-Africa Centre for Health and Population Studies, University of KwaZulu-Natal, Durban, South Africa.
authors.forename: Deenan
authors.initials: D
authors.lastname: Pillay
authors.affiliation: Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK.
authors.forename: Andrew J Leigh
authors.initials: AJ
authors.lastname: Brown
mesh_terms: D015331:Cohort Studies; D058872:Epidemics; D015752:Genes, env; D015750:Genes, gag; D015751:Genes, pol; D016679:Genome, Viral; D006678:HIV / Q000235:genetics*; D015658:HIV Infections / Q000453:epidemiology* / Q000821:virology*; D006801:Humans; D016013:Likelihood Functions; D017720:Molecular Epidemiology; D010802:Phylogeny; D012044:Regression Analysis; D015203:Reproducibility of Results; D013019:South Africa; D006113:United Kingdom