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The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
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PuMA: A papillomavirus genome annotation tool.

Josh Pace1, Ken Youens-Clark2, Cordell Freeman1

  • 1School of Animal and Comparative Biomedical Sciences, University of Arizona, 1200 E. University Blvd. Tucson, AZ 85721-0073, USA.

Virus Evolution
|December 31, 2020
PubMed
Summary

Researchers can now easily identify and report novel papillomaviruses using PuMA, a new bioinformatics tool. This viral metagenomics software accurately annotates viral genes, enhancing the discovery of new viruses.

Keywords:
annotationhigh-throughput sequencingmetagenomicspapillomaviruspolyomavirusvirome

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Area of Science:

  • Virology
  • Bioinformatics
  • Computational Biology

Background:

  • High-throughput sequencing and viral metagenomics have greatly expanded knowledge of viral diversity.
  • Identifying novel viruses often involves researchers unfamiliar with specific viral families.
  • A need exists for user-friendly tools to annotate and report newly discovered viruses.

Purpose of the Study:

  • To develop a convenient and reproducible method for annotating novel papillomaviruses.
  • To provide a tool that assists researchers in reporting newly identified viral genomes.
  • To enhance the process of viral discovery in metagenomic studies.

Main Methods:

  • Development of the papillomavirus annotation tool (PuMA).
  • Benchmarking PuMA against 655 reference papillomavirus genomes.
  • Comparison of PuMA's performance with existing viral annotation pipelines.
  • Development of a preliminary version of PuMA for polyomavirus annotation.

Main Results:

  • PuMA accurately annotates 99% of papillomavirus genes.
  • PuMA demonstrates higher accuracy and annotates more viral features than a comparative pipeline.
  • A preliminary version of PuMA successfully annotates polyomaviruses, showing broader applicability.

Conclusions:

  • PuMA offers a reliable and efficient solution for annotating novel papillomaviruses.
  • The tool facilitates the reporting and characterization of newly discovered viruses.
  • PuMA's adaptability suggests potential for annotating other viral families, aiding broader viral metagenomics research.