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A comprehensive analysis of primer IDs to study heterogeneous HIV-1 populations


Seifert, David; Di Giallonardo, Francesca; Töpfer, Armin; Singer, Jochen; Schmutz, Stefan; Günthard, Huldrych F; Beerenwinkel, Niko; Metzner, Karin J (2016). A comprehensive analysis of primer IDs to study heterogeneous HIV-1 populations. Journal of Molecular Biology, 428(1):238-250.

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.

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.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Infectious Diseases
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:16 January 2016
Deposited On:04 Aug 2016 10:40
Last Modified:04 Aug 2016 14:32
Publisher:Elsevier
ISSN:0022-2836
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1016/j.jmb.2015.12.012
PubMed ID:26711506

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