Deep sequencing: becoming a critical tool in clinical virology

Abstract

Population (Sanger) sequencing has been the standard method in basic and clinical DNA sequencing for almost 40 years; however, next-generation (deep) sequencing methodologies are now revolutionizing the field of genomics, and clinical virology is no exception. Deep sequencing is highly efficient, producing an enormous amount of information at low cost in a relatively short period of time. High-throughput sequencing techniques have enabled significant contributions to multiples areas in virology, including virus discovery and metagenomics (viromes), molecular epidemiology, pathogenesis, and studies of how viruses to escape the host immune system and antiviral pressures. In addition, new and more affordable deep sequencing-based assays are now being implemented in clinical laboratories. Here, we review the use of the current deep sequencing platforms in virology, focusing on three of the most studied viruses: human immunodeficiency virus (HIV), hepatitis C virus (HCV), and influenza virus.

Keywords: Deep sequencing; Hepatitis C virus (HCV); Human immunodeficiency virus (HIV); Influenza virus; Next generation sequencing (NGS).

Figure 1

Principal characteristics of the four most used deep sequencing platforms to date: 454™ (GS Junior and GS FLX+ systems), Illumina® (MiSeq v2 and HiSeq 2500 systems), Ion Torrent™ (Ion Personal Genome Machine®, 318 v2 chip and Ion Proton™, I chip systems), and Pacific Biosciences® (PacBio RS II SMRT®). Information about virus-related publications was obtained from the respective companies (personal communications and/or websites) and PubMed (http://www.ncbi28nlm.nih.gov/pubmed/) search as of March 27^th, 2014.

Figure 2

Scientific publications based on deep sequencing. (A) Cumulative number of publications associated with HIV, HCV, or influenza virus and deep sequencing during the last 13 years. The size of the circles corresponds to the number of publications in each given year, e.g., 57 HIV studies using deep sequencing were published in 2013. The total number of publications per virus is indicated. (B) Percentage of scientific publications per research area. Search in PubMed (http://www.ncbi.nlm.nih.gov/pubmed/) as of March 27^th, 2014 using “HIV”, “HCV”, “influenza”, “deep sequencing”, “pyrosequencing”, “epidemiology”, “quasispecies”, “pathogenesis”, “transmission”, “drug resistance”, “tropism”, and/or “vaccine” as keywords.

Figure 3

Comparison of phylogenetic analyses based on Sanger or deep sequencing. Neighbor-joining phylogenetic trees were constructed using (A) Sanger sequencing of 105-bp fragments corresponding to the HIV-1 V3 region of gp120 (env gene) from 12 HIV-infected individuals or (B) deep sequencing reads with a frequency >1 corresponding to the same 105-bp fragments (Gibson and Quiñones-Mateu, unpublished results). Each color-coded dot represents a unique variant, frequency is not depicted. Bootstrap resampling (1,000 data sets) of the multiple alignments tested the statistical robustness of the trees, with percentage values above 75% indicated by an asterisk. s/nt, substitutions per nucleotide. Phylogenetic trees were constructed using MEGA 5.05 [261].