Next-generation sequencing for virus detection : covering all the bases

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visser_nextgeneration_2016.pdf(1.22 MB)
Date
2016-06
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Publisher
BioMed Central
Abstract
Background: The use of next-generation sequencing has become an established method for virus detection. Efficient study design for accurate detection relies on the optimal amount of data representing a significant portion of a virus genome. Findings: In this study, genome coverage at different sequencing depths was determined for a number of viruses, viroids, hosts and sequencing library types, using both read-mapping and de novo assembly-based approaches. The results highlighted the strength of ribo-depleted RNA and sRNA in obtaining saturated genome coverage with the least amount of data, while even though the poly(A)-selected RNA yielded virus-derived reads, it was insufficient to cover the complete genome of a non-polyadenylated virus. The ribo-depleted RNA data also outperformed the sRNA data in terms of the percentage of coverage that could be obtained particularly with the de novo assembled contigs. Conclusion: Our results suggest the use of ribo-depleted RNA in a de novo assembly-based approach for the detection of single-stranded RNA viruses. Furthermore, we suggest that sequencing one million reads will provide sufficient genome coverage specifically for closterovirus detection.
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CITATION: Visser, M., et al. 2016. Next-generation sequencing for virus detection : covering all the base. Virology Journal, 13(1): 85, doi: 10.1186/s12985-016-0539-x.
The original publication is available at http://bmcmusculoskeletdisord.biomedcentral.com
Publication of this article was funded by the Stellenbosch University Open Access Fund.
Keywords
Closterovirus, Genome coverage, GLRaV-3, Next-generation sequencing, Sequencing depth, Virus detection
Citation
Visser, M., et al. 2016. Next-generation sequencing for virus detection : covering all the base. Virology Journal, 13(1): 85, doi: 10.1186/s12985-016-0539-x
URI
http://hdl.handle.net/10019.1/99041
Collections
Research Articles (Genetics)