Next-generation sequencing of HIV-1 RNA genomes: determination of error rates and minimizing artificial recombination.

Di Giallonardo, Francesca; Zagordi, Osvaldo; Duport, Yannick; Leemann, Christine; Joos, Beda; Künzli-Gontarczyk, Marzanna; Bruggmann, Rémy; Beerenwinkel, Niko; Günthard, Huldrych F.; Metzner, Karin J. (2013). Next-generation sequencing of HIV-1 RNA genomes: determination of error rates and minimizing artificial recombination. PLoS ONE, 8(9), e74249. Public Library of Science 10.1371/journal.pone.0074249

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Next-generation sequencing (NGS) is a valuable tool for the detection and quantification of HIV-1 variants in vivo. However, these technologies require detailed characterization and control of artificially induced errors to be applicable for accurate haplotype reconstruction. To investigate the occurrence of substitutions, insertions, and deletions at the individual steps of RT-PCR and NGS, 454 pyrosequencing was performed on amplified and non-amplified HIV-1 genomes. Artificial recombination was explored by mixing five different HIV-1 clonal strains (5-virus-mix) and applying different RT-PCR conditions followed by 454 pyrosequencing. Error rates ranged from 0.04-0.66% and were similar in amplified and non-amplified samples. Discrepancies were observed between forward and reverse reads, indicating that most errors were introduced during the pyrosequencing step. Using the 5-virus-mix, non-optimized, standard RT-PCR conditions introduced artificial recombinants in a fraction of at least 30% of the reads that subsequently led to an underestimation of true haplotype frequencies. We minimized the fraction of recombinants down to 0.9-2.6% by optimized, artifact-reducing RT-PCR conditions. This approach enabled correct haplotype reconstruction and frequency estimations consistent with reference data obtained by single genome amplification. RT-PCR conditions are crucial for correct frequency estimation and analysis of haplotypes in heterogeneous virus populations. We developed an RT-PCR procedure to generate NGS data useful for reliable haplotype reconstruction and quantification.

Item Type:

Journal Article (Original Article)

Division/Institute:

08 Faculty of Science > Department of Biology > Bioinformatics and Computational Biology > Bioinformatics
08 Faculty of Science > Department of Biology > Bioinformatics and Computational Biology > Computational Biology
08 Faculty of Science > Department of Biology > Bioinformatics and Computational Biology

UniBE Contributor:

Bruggmann, Rémy

ISSN:

1932-6203

Publisher:

Public Library of Science

Language:

English

Submitter:

Rémy Bruggmann

Date Deposited:

24 Jul 2014 14:44

Last Modified:

04 May 2023 13:56

Publisher DOI:

10.1371/journal.pone.0074249

PubMed ID:

24058534

BORIS DOI:

10.7892/boris.47850

URI:

https://boris.unibe.ch/id/eprint/47850

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