Development of a user-friendly pipeline for mutational analyses of hiv using ultra-accurate maximum-depth sequencing

Morgan E. Meissner, Emily J. Julik, Jonathan P. Badalamenti, William G. Arndt, Lauren J. Mills, Louis M. Mansky

Research output: Contribution to journalArticlepeer-review


Human immunodeficiency virus type 2 (HIV-2) accumulates fewer mutations during replication than HIV type 1 (HIV-1). Advanced studies of HIV-2 mutagenesis, however, have histor-ically been confounded by high background error rates in traditional next-generation sequencing techniques. In this study, we describe the adaptation of the previously described maximum-depth sequencing (MDS) technique to studies of both HIV-1 and HIV-2 for the ultra-accurate characterization of viral mutagenesis. We also present the development of a user-friendly Galaxy workflow for the bioinformatic analyses of sequencing data generated using the MDS technique, designed to improve replicability and accessibility to molecular virologists. This adapted MDS technique and analysis pipeline were validated by comparisons with previously published analyses of the frequency and spectra of mutations in HIV-1 and HIV-2 and is readily expandable to studies of viral mutation across the genomes of both viruses. Using this novel sequencing pipeline, we observed that the background error rate was reduced 100-fold over standard Illumina error rates, and 10-fold over traditional unique molecular identifier (UMI)-based sequencing. This technical advancement will allow for the exploration of novel and previously unrecognized sources of viral mutagenesis in both HIV-1 and HIV-2, which will expand our understanding of retroviral diversity and evolution.

Original languageEnglish (US)
Article number1338
Issue number7
StatePublished - Jul 2021

Bibliographical note

Funding Information:
Funding: This research was funded by National Institutes of Health, grant number R01 AI150468 (L.M.M.), the University of Minnesota Masonic Cancer Center (L.M.M.), and the University of Minnesota Informatics Institute Updraft Awards Program (L.M.M and M.E.M). M.E.M. was supported by NIH grants T32 AI083196 and F31 AI 50487; E.J.J. was supported by NIH grant T32 HL007741.

Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.


  • HIV-1
  • HIV-2
  • Human immunodeficiency virus
  • Mutation
  • Sequence analysis
  • Sequencing


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