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Challenges and opportunities in estimating viral genetic diversity from next-generation sequencing data

Beerenwinkel, Niko and Günthard, Huldrych F. and Roth, Volker and Metzner, Karin J.. (2012) Challenges and opportunities in estimating viral genetic diversity from next-generation sequencing data. Frontiers in microbiology, Vol. 3, H. 329.

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Official URL: http://edoc.unibas.ch/dok/A6018453

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Abstract

Many viruses, including the clinically relevant RNA viruses HIV (human immunodeficiency virus) and HCV (hepatitis C virus), exist in large populations and display high genetic heterogeneity within and between infected hosts. Assessing intra-patient viral genetic diversity is essential for understanding the evolutionary dynamics of viruses, for designing effective vaccines, and for the success of antiviral therapy. Next-generation sequencing (NGS) technologies allow the rapid and cost-effective acquisition of thousands to millions of short DNA sequences from a single sample. However, this approach entails several challenges in experimental design and computational data analysis. Here, we review the entire process of inferring viral diversity from sample collection to computing measures of genetic diversity. We discuss sample preparation, including reverse transcription and amplification, and the effect of experimental conditions on diversity estimates due to in vitro base substitutions, insertions, deletions, and recombination. The use of different NGS platforms and their sequencing error profiles are compared in the context of various applications of diversity estimation, ranging from the detection of single nucleotide variants (SNVs) to the reconstruction of whole-genome haplotypes. We describe the statistical and computational challenges arising from these technical artifacts, and we review existing approaches, including available software, for their solution. Finally, we discuss open problems, and highlight successful biomedical applications and potential future clinical use of NGS to estimate viral diversity.
Faculties and Departments:05 Faculty of Science > Departement Mathematik und Informatik > Informatik > Datenanalyse (Roth)
UniBasel Contributors:Roth, Volker
Item Type:Article, refereed
Article Subtype:Research Article
Bibsysno:Link to catalogue
Publisher:CRC Press
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:04 Sep 2015 14:31
Deposited On:08 Nov 2012 16:15

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