Characterization of emerging swine viral diseases through oxford nanopore sequencing using senecavirus a as a model

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Emerging viral infectious diseases present a major threat to the global swine industry. Since 2015, Senecavirus A (SVA) has been identified as a cause of vesicular disease in different countries and is considered an emerging disease. Despite the growing concern about SVA, there is a lack of preventive and diagnostic strategies, which is also a problem for all emerging infectious diseases. Using SVA as a model, we demonstrated that Oxford Nanopore MinION sequencing could be used as a robust tool for the investigation and surveillance of emerging viral diseases. Our results identified that MinION sequencing allowed for rapid, unbiased pathogen detection at the species and strain level for clinical cases. SVA whole genome sequences were generated using both direct RNA sequencing and PCR-cDNA sequencing methods, with an optimized consensus accuracy of 94% and 99%, respectively. The advantages of direct RNA sequencing lie in its shorter turnaround time, higher analytical sensitivity and its quantitative relationship between input RNA and output sequencing reads, while PCR-cDNA sequencing excelled at creating highly accurate sequences. This study developed whole genome sequencing methods to facilitate the control of SVA and provide a reference for the timely detection and prevention of other emerging infectious diseases.

Original languageEnglish (US)
Article number1136
Issue number10
StatePublished - Oct 2020

Bibliographical note

Funding Information:
Funding: This research was funded by National Pork Board Grant, grant number #18-040.

Publisher Copyright:
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (


  • Bioinformatics
  • Emerging infectious diseases
  • Molecular diagnostic techniques
  • Oxford Nanopore sequencing
  • Senecavirus A
  • Swine viral diseases

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't


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