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Viruses 2016, 8(1), 12; doi:10.3390/v8010012

Quantifying Next Generation Sequencing Sample Pre-Processing Bias in HIV-1 Complete Genome Sequencing

1
Rega Institute for Medical Research, Clinical and Epidemiological Virology, Department of Microbiology and Immunology, KU Leuven—University of Leuven, 3000 Leuven, Belgium
2
University Hospitals Leuven, 3000 Leuven, Belgium
3
Center for Global Health and Tropical Medicine, Unidade de Microbiologia, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, 1349-008 Lisbon, Portugal
*
Author to whom correspondence should be addressed.
Academic Editors: Johnson Mak, Peter Walker and Marcus Thomas Gilbert
Received: 28 September 2015 / Revised: 8 December 2015 / Accepted: 15 December 2015 / Published: 7 January 2016
View Full-Text   |   Download PDF [223 KB, uploaded 7 January 2016]

Abstract

Genetic analyses play a central role in infectious disease research. Massively parallelized “mechanical cloning” and sequencing technologies were quickly adopted by HIV researchers in order to broaden the understanding of the clinical importance of minor drug-resistant variants. These efforts have, however, remained largely limited to small genomic regions. The growing need to monitor multiple genome regions for drug resistance testing, as well as the obvious benefit for studying evolutionary and epidemic processes makes complete genome sequencing an important goal in viral research. In addition, a major drawback for NGS applications to RNA viruses is the need for large quantities of input DNA. Here, we use a generic overlapping amplicon-based near full-genome amplification protocol to compare low-input enzymatic fragmentation (Nextera™) with conventional mechanical shearing for Roche 454 sequencing. We find that the fragmentation method has only a modest impact on the characterization of the population composition and that for reliable results, the variation introduced at all steps of the procedure—from nucleic acid extraction to sequencing—should be taken into account, a finding that is also relevant for NGS technologies that are now more commonly used. Furthermore, by applying our protocol to deep sequence a number of pre-therapy plasma and PBMC samples, we illustrate the potential benefits of a near complete genome sequencing approach in routine genotyping. View Full-Text
Keywords: HIV; full genome sequencing; NGS HIV; full genome sequencing; NGS
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Vrancken, B.; Trovão, N.S.; Baele, G.; van Wijngaerden, E.; Vandamme, A.-M.; van Laethem, K.; Lemey, P. Quantifying Next Generation Sequencing Sample Pre-Processing Bias in HIV-1 Complete Genome Sequencing. Viruses 2016, 8, 12.

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