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. 2013 Jul 4:14:444.
doi: 10.1186/1471-2164-14-444.

Next generation sequencing of viral RNA genomes

Denise A Marston, Lorraine M McElhinney, Richard J Ellis, Daniel L Horton, Emma L Wise, Stacey L Leech, Dan David, Xavier de Lamballerie, Anthony R Fooks

Next generation sequencing of viral RNA genomes

Denise A Marston et al. BMC Genomics. .

Abstract

Background: With the advent of Next Generation Sequencing (NGS) technologies, the ability to generate large amounts of sequence data has revolutionized the genomics field. Most RNA viruses have relatively small genomes in comparison to other organisms and as such, would appear to be an obvious success story for the use of NGS technologies. However, due to the relatively low abundance of viral RNA in relation to host RNA, RNA viruses have proved relatively difficult to sequence using NGS technologies. Here we detail a simple, robust methodology, without the use of ultra-centrifugation, filtration or viral enrichment protocols, to prepare RNA from diagnostic clinical tissue samples, cell monolayers and tissue culture supernatant, for subsequent sequencing on the Roche 454 platform.

Results: As representative RNA viruses, full genome sequence was successfully obtained from known lyssaviruses belonging to recognized species and a novel lyssavirus species using these protocols and assembling the reads using de novo algorithms. Furthermore, genome sequences were generated from considerably less than 200 ng RNA, indicating that manufacturers' minimum template guidance is conservative. In addition to obtaining genome consensus sequence, a high proportion of SNPs (Single Nucleotide Polymorphisms) were identified in the majority of samples analyzed.

Conclusions: The approaches reported clearly facilitate successful full genome lyssavirus sequencing and can be universally applied to discovering and obtaining consensus genome sequences of RNA viruses from a variety of sources.

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Figures

Figure 1
Figure 1
Depth of sequence obtained from (a) infected brain samples and (b) from cultured samples.
Figure 2
Figure 2
Alignment of 454 reads for (a) RV20 consensus sequence and the reads with variations, (b) RV61 consensus sequence and published RV61 glycoprotein gene sequences and (c) RV50 published genome sequence; * indicating single nucleotide polymorphisms which are detailed at the top of each figure.
Figure 3
Figure 3
Typical variation of the reads over a homopolymeric repeat at the termination signal of the M-gene displayed as (a) an alignment of individual 454 reads with the consensus sequence (contig00001) and a reference sequence (RV437) and (b) a flowgram with reference sequence (RV437, top panel), read G3FY5P04JF0R0 (middle panel) and the difference between the reference sequence and read (bottom panel).
See this image and copyright information in PMC

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