Abstract
BackgroundThe duration of treatment for HCV infection is partly indicated by the genotype of the virus. For studies of disease transmission, vaccine design, and surveillance for novel variants, subtype-level classification is also needed. This study used the Shimodaira-Hasegawa test and related statistical techniques to compare phylogenetic trees obtained from coding and non-coding regions of a whole-genome alignment for the reliability of subtyping in different regions.ResultsDifferent regions of the HCV genome yield inconsistent phylogenies, which can lead to erroneous conclusions about classification of a given infection. In particular, the highly conserved 5' untranslated region (UTR) yields phylogenetic trees with topologies that differ from the HCV polyprotein and complete genome phylogenies. Phylogenetic trees from the NS5B gene reliably cluster related subtypes, and yield topologies consistent with those of the whole genome and polyprotein.ConclusionThese results extend those from previous studies and indicate that, unlike the NS5B gene, the 5' UTR contains insufficient variation to resolve HCV classifications to the level of viral subtype, and fails to distinguish genotypes reliably. Use of the 5' UTR for clinical tests to characterize HCV infection should be replaced by a subtype-informative test.
Highlights
The duration of treatment for HCV infection is partly indicated by the genotype of the virus
This study evaluates phylogenies derived from coding (NS5B) and non-coding (5' untranslated region (UTR)) regions of wholegenome HCV sequences for consistent classification of viral subtypes into distinct genetic groups, or clades, with the aim of evaluating their suitability for genotype and subtype classification
To compensate for this, we considered a smaller, oft-studied portion of NS5B that we call the "Okamoto region" for its ability to represent the phylogeny of NS5B and the entire HCV genome
Summary
The duration of treatment for HCV infection is partly indicated by the genotype of the virus. For studies of disease transmission, vaccine design, and surveillance for novel variants, subtype-level classification is needed. In treating infection with hepatitis C virus, knowledge of a patient's viral genotype informs the choice of appropriate therapy [1,2,3]. The HCV subtype afflicting a patient is not currently used to make clinical treatment decisions, knowing the viral subtype is important for studies of its origin, transmission, and evolution [1,2,3,4]. New emerging variants can be characterized better when they can be assigned an unequivocal subtype classification [5]. Effective methods for both genotype and subtype classification are important tools to manage HCV infections
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