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:
10.1371/journal.pone.0074249
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发表时间:
2013
期刊:
影响因子:
3.7
通讯作者:
Metzner KJ
中科院分区:
文献类型:
--
作者:
Di Giallonardo F;Zagordi O;Duport Y;Leemann C;Joos B;Künzli-Gontarczyk M;Bruggmann R;Beerenwinkel N;Günthard HF;Metzner KJ
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.
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影响因子:
12.3
作者:
Huse SM;Huber JA;Morrison HG;Sogin ML;Welch DM
通讯作者:
Welch DM
DOI:
10.1093/cid/ciq164
发表时间:
2011-02-15
期刊:
Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
影响因子:
--
作者:
Kouyos RD;von Wyl V;Yerly S;Böni J;Rieder P;Joos B;Taffé P;Shah C;Bürgisser P;Klimkait T;Weber R;Hirschel B;Cavassini M;Rauch A;Battegay M;Vernazza PL;Bernasconi E;Ledergerber B;Bonhoeffer S;Günthard HF;Swiss HIV Cohort Study
通讯作者:
Swiss HIV Cohort Study
影响因子:
6.4
作者:
Metzner, Karin J.;Rauch, Pia;Guenthard, Huldrych F.
通讯作者:
Guenthard, Huldrych F.
DOI:
10.1093/bioinformatics/btq365
发表时间:
2010-09-15
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
作者:
Balzer S;Malde K;Lanzén A;Sharma A;Jonassen I
通讯作者:
Jonassen I
影响因子:
5.8
作者:
Maydt, J;Lengauer, T
通讯作者:
Lengauer, T