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

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

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DOI
10.7892/boris.47850
Publisher DOI
10.1371/journal.pone.0074249
PubMed ID
24058534
Abstract
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.
Date Issued
2013-09-18
Publication Type
Article
Language(s)
en
Author(s)
Di Giallonardo, Francesca
Zagordi, Osvaldo
Duport, Yannick
Leemann, Christine
Joos, Beda
Künzli-Gontarczyk, Marzanna
Bruggmann, Rémy  
Bioinformatik und computerbasierte Biologie  
Beerenwinkel, Niko
Günthard, Huldrych F.
Metzner, Karin J.
Additional Credits
Bioinformatik und computerbasierte Biologie  
Journal
PLoS ONE
Publisher
Public Library of Science
ISSN
1932-6203
Access(Rights)
open.access
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