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Table 1 Representative examples of deep sequencing applied to viral populations

From: Deep sequencing of evolving pathogen populations: applications, errors, and bioinformatic solutions

Pathogen

Design

Technology

Ref seq

Filter

Align

SNV

Hap

Application

Reference

HIV

RT-PCR, nested PCR of pol fragment

Roche-454 GS-FLX amplicon sequencing

Sanger sequenced pol gene

In-house software: removes reads with ambiguous bases, < 80% similarity to reference, or outside region of interest

GS amplicon software (Roche, Penzberg, Germany), Needleman-Wunsch

In house scripts, manual inspection: remove gaps, remove reads with frameshift indels or stop codons, remove variants only contained in reads in one direction, positional variant cut-off values based on control sequences

Individual reads (40 bp region of interest)

Longitudinal emergence of drug resistance during treatment failure

[10]

HIV

RT, PCR amplificatin of 4 fragments (3.5 kb each). Full genome analysis

Roche-454 GS-FLX Titanium

De novo assembled reference using AssembleViral454 v1.0

NS

Mosaik

RC454 / V-Phaser

V-Phaser (one read length only)

Longitudinal emergence of CD8+ T cell escape variants, viral adaptation

[11]

HCV

RT, PCR amplification of HVR-1, nested PCR using sequencing adapters

Roche-454 GS-FLX Titanium amplicon sequencing

358 HCV HVR-1 representative sequences from Los Alamos National Laboratory HCV

Flow clustering as implemented in QIIME, only reads covering entire region of interest

MAFFT (multiple sequence alignment)

NA

Individual reads

Identification of a transmission event

[12]

HCV

Whole-genome library prep direct from RNA isolated from human serum, using mRNA-seq sample prep kit (Illumina, San Diego, CA)

Illumina GA IIx 76 bp single end reads

970 reference HCV sequences registered at the Hepatitis Virus Database server

Primer stripping using CLC Genomics Workbench (4.6), remove reads aligning to human genome, removal of duplicate reads

BWA 0.5.9-r16

Samtools (0.1.16)

NA

PCR-free whole genome HCV sequencing from human serum; variant comparison between treatment naïve and treatment experienced patients

[13]

HCV

RT-PCR using genotype specific primers, nested PCR of full genome, followed by random shearing and library preparation

Roche-454 GS-FLX Titanium

Sanger-sequenced consensus

In house software (discard reads with Phred quality scores below 20 or length < 55nt)

Mosaik

ShoRAH, manual cleaning

ShoRAH (up to 1600 bp reconstructions)

Within-host evolution/genetic bottleneck

[14]

HRV

Duplicate whole-genome RT-PCR of overlapping primer pairs, nebulisation of pooled fragments and library prep

Illumina GA IIx

Sanger-sequenced consensus

Illumina software: RTA SCS.2.6 and CASAVA 1.6

MAQ v0.7.1

In house scripts; cut-off based on statistical analyses of base frequencies along reference. Comparison between replicates.

NA

Within-host evolution during immunosuppression

[15]

76 bp single end reads

Dengue

RT, PCR amplification of four different fragments, random shearing and adapter ligation

Roche-454 GS-FLX Titanium

De novo assembled using AV454 with manual finishing

NS

Mosaik

RC454/ V-Phaser. Manual removal of variants in primer binding sites or only in ends of reads

NA

Intra-host viral diversity

[16]

Poliovirus

RT-PCR and nested PCR of target amplicon, followed by random shearing and library preparation

Roche-454 FLX Titanium and Illumina GA IIx 76 bp single end reads

Known amplicon sequences

Proprietary Roche/Illumina software. In house software (discard reads with Phred quality scores below 20).

NS

Custom made scripts – disregard variants with strand bias, as well as insertions and deletions adjacent to homopolymers for Roche-454 data.

NA

Detection of emerging resistant variants in a vaccine stock

[17]

  1. Details of the experimental design and analysis pipeline for various applications of deep sequencing to different viruses are given. ‘Design’ describes the types of samples used and any sample processing up to library preparation. ‘Technology’ indicates the type of sequencing employed. ‘Filter’ details any pre-alignment read processing steps. ‘Ref. Seq.’ describes what kinds of reference sequences were used for read alignment, while ‘Align’ gives the actual alignment software used. ‘SNV’ and ‘Hap.’ indicate software used for SNV detection and haplotype reconstruction respectively. ‘Application’ describes the biological motivation for the study. ‘NS’ indicates the method was not specified in the cited publication, while ‘NA’ means not attempted.