Computational and Structural Biotechnology Journal (Jan 2021)

AutoVEM2: A flexible automated tool to analyze candidate key mutations and epidemic trends for virus

  • Binbin Xi,
  • Zixi Chen,
  • Shuhua Li,
  • Wei Liu,
  • Dawei Jiang,
  • Yunmeng Bai,
  • Yimo Qu,
  • Jerome Rumdon Lon,
  • Lizhen Huang,
  • Hongli Du

Journal volume & issue
Vol. 19
pp. 5029 – 5038

Abstract

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In our previous work, we developed an automated tool, AutoVEM, for real-time monitoring the candidate key mutations and epidemic trends of SARS-CoV-2. In this research, we further developed AutoVEM into AutoVEM2. AutoVEM2 is composed of three modules, including call module, analysis module, and plot module, which can be used modularly or as a whole for any virus, as long as the corresponding reference genome is provided. Therefore, it’s much more flexible than AutoVEM. Here, we analyzed three existing viruses by AutoVEM2, including SARS-CoV-2, HBV and HPV-16, to show the functions, effectiveness and flexibility of AutoVEM2. We found that the N501Y locus was almost completely linked to the other 16 loci in SARS-CoV-2 genomes from the UK and Europe. Among the 17 loci, 5 loci were on the S protein and all of the five mutations cause amino acid changes, which may influence the epidemic traits of SARS-CoV-2. And some candidate key mutations of HBV and HPV-16, including T350G of HPV-16 and C659T of HBV, were detected. In brief, we developed a flexible automated tool to analyze candidate key mutations and epidemic trends for any virus, which would become a standard process for virus analysis based on genome sequences in the future.

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