A Comprehensive Analysis of Primer IDs to Study Heterogeneous HIV-1 Populations. Issue 1 (16th January 2016)

• Record Type: Journal Article
• Authors: Seifert, David; Di Giallonardo, Francesca; Töpfer, Armin; Singer, Jochen; Schmutz, Stefan; Günthard, Huldrych F.; Beerenwinkel, Niko; Metzner, Karin J.
• Is Part Of: Journal of molecular biology. Volume 428:Issue 1(2016:Jan. 01)
• Page Start: 238
• Page End: 250
• Publication Date: 2016-01-16
• Subjects: pID primer ID -- RT reverse transcription -- NGS next-generation sequencing -- CI confidence interval -- qPCR quantitative PCR; HIV-1 -- next-generation sequencing -- primer ID -- PCR -- RT; Molecular biology -- Periodicals; Biology -- Periodicals; Biochemistry -- Periodicals; Bacteriology -- Periodicals; Molecular Biology -- Periodicals; Biochemistry -- Periodicals; Biologie moléculaire -- Périodiques; Biologie -- Périodiques; Biochimie -- Périodiques; Moleculaire biologie; Biochemistry; Biology; Molecular biology; Periodicals; 572.805
• DOI: 10.1016/j.jmb.2015.12.012
• Languages: English
• ISSNs: 0022-2836

Abstract

Abstract: Determining the composition of viral populations is becoming increasingly important in the field of medical virology. While recently developed computational tools for viral haplotype analysis allow for correcting sequencing errors, they do not always allow for the removal of errors occurring in the upstream experimental protocol, such as PCR errors. Primer IDs (pIDs) are one method to address this problem by harnessing redundant template resampling for error correction. By using a reference mixture of five HIV-1 strains, we show how pIDs can be useful for estimating key experimental parameters, such as the substitution rate of the PCR process and the reverse transcription (RT) error rate. In addition, we introduce a hidden Markov model for determining the recombination rate of the RT PCR process. We found no strong sequence-specific bias in pID abundances (the same RT efficiencies as compared to commonly used short, specific RT primers) and no effects of pIDs on the estimated distribution of the references viruses. Graphical Abstract: Highlights: pIDs are unique tags that track a single cDNA molecule through to sequencing. pIDs allow for inferring enzymatic error rates. pIDs show no strong bias effects within their ID region. pIDs do not improve population frequency estimators over standard approaches. Public healthcare economics unclear required redundancy incompatible with pooling.