Interpreting viral deep sequencing data with glue

Joshua B. Singer*, Emma C. Thomson, Joseph Hughes, Elihu Aranday-Cortes, John McLauchlan, Ana Da Silva Filipe, Lily Tong, Carmen F. Manso, Robert J. Gifford, David L. Robertson, Eleanor Barnes, M. Azim Ansari, Jean Mbisa, David F. Bibby, Daniel Bradshaw, David Smith

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

Using deep sequencing technologies such as Illumina’s platform, it is possible to obtain reads from the viral RNA population revealing the viral genome diversity within a single host. A range of software tools and pipelines can transform raw deep sequencing reads into Sequence Alignment Mapping (SAM) files. We propose that interpretation tools should process these SAM files, directly translating individual reads to amino acids in order to extract statistics of interest such as the proportion of different amino acid residues at specific sites. This preserves per-read linkage between nucleotide variants at different positions within a codon location. The samReporter is a subsystem of the GLUE software toolkit which follows this direct read translation approach in its processing of SAM files. We test samReporter on a deep sequencing dataset obtained from a cohort of 241 UK HCV patients for whom prior treatment with direct-acting antivirals has failed; deep sequencing and resistance testing have been suggested to be of clinical use in this context. We compared the polymorphism interpretation results of the samReporter against an approach that does not preserve per-read linkage. We found that the samReporter was able to properly interpret the sequence data at resistance-associated locations in nine patients where the alternative approach was equivocal. In three cases, the samReporter confirmed that resistance or an atypical substitution was present at NS5A position 30. In three further cases, it confirmed that the sofosbuvir-resistant NS5B substitution S282T was absent. This suggests the direct read translation approach implemented is of value for interpreting viral deep sequencing data.

Original languageEnglish
Article number323
JournalViruses
Volume11
Issue number4
DOIs
Publication statusPublished - Apr 2019

Bibliographical note

Funding Information:
Funding: This work was funded by the Medical Research Council (MRC) of the United Kingdom, award number MC_UU_12014/12. JBS was also part funded by a MRC Confidence in Concept award to the University of Glasgow, MC_PC_16045. ECT was funded by the Wellcome Trust (102789/Z/13/Z). EB is funded by the MRC, the Oxford National Institute for Health Research (NIHR) Biomedical Research Centre and is an NIHR Senior Investigator. The views expressed in this article are those of the authors and not necessarily those of the National Health Service (NHS), the NIHR, or the Department of Health.

Publisher Copyright:
© 2019 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

  • Bioinformatics
  • Deep sequencing
  • Drug resistance
  • Hepatitis C virus
  • Sequence interpretation
  • Variant calling
  • Virus genomics

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