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Related Concept Videos

Viral Mutations00:36

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A mutation is a change in the sequence of bases of DNA or RNA in a genome. Some mutations occur during replication of the genome due to errors made by the polymerase enzymes that replicate DNA or RNA. Unlike DNA polymerase, RNA polymerase is prone to errors because it is not capable of “proofreading” its work. Viruses with RNA-based genomes, like HIV, therefore accrue mutations faster than viruses with DNA-based genomes. Because mutation and recombination provide the raw material...
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Cells are sometimes infected by more than one virus at once. When two viruses disassemble to expose their genomes for replication in the same cell, similar regions of their genomes can pair together and exchange sequences in a process called recombination. Alternatively, viruses with segmented genomes can swap segments in a process called reassortment.
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Related Experiment Video

Updated: Jun 3, 2025

Combining Analysis of DNA in a Crude Virion Extraction with the Analysis of RNA from Infected Leaves to Discover New Virus Genomes
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vClean: assessing virus sequence contamination in viral genomes.

Ryota Wagatsuma1,2, Yohei Nishikawa2,3, Masahito Hosokawa1,2,3,4

  • 1Department of Life Science and Medical Bioscience, Graduate School of Advanced Science and Engineering, Waseda University, 2-2 Wakamatsu-cho, Shinjuku-ku, Tokyo 162-8480, Japan.

NAR Genomics and Bioinformatics
|January 9, 2025
PubMed
Summary

A new tool, vClean, automatically detects sequence contamination in environmental viral genomes. This automated detection is crucial for accurate analysis of viral metagenomics and single-virus genomics data.

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Area of Science:

  • Environmental Virology
  • Bioinformatics
  • Genomics

Background:

  • Viral metagenomics and single-virus genomics enable environmental virus genome recovery.
  • Current methods risk introducing sequence contamination into assembled viral genomes.
  • Lack of practical tools hinders detection of these contaminations, impacting analysis accuracy.

Purpose of the Study:

  • To introduce vClean, a novel automated tool for detecting sequence contamination in viral genomes.
  • To establish a reliable method for quality control in environmental viral genome analysis.

Main Methods:

  • vClean utilizes machine learning based on nucleotide sequence features and gene patterns.
  • For tailed double-stranded DNA phages, predictions are refined by analyzing single-copy-like gene duplications.
  • Performance was validated using simulated datasets and real-world metagenomic data.

Main Results:

  • vClean achieved a binary accuracy of 0.932 on simulated datasets.
  • Analysis of 4693 public ocean metagenomic viral genomes revealed 1604 (34.2%) contaminated genomes.
  • Contamination was also detected in single-virus genome data from river water samples.

Conclusions:

  • vClean effectively identifies sequence contamination in environmental viral genomes.
  • The tool provides a new benchmark for viral genome quality control.
  • vClean is poised to become an essential tool for environmental viral genomics research.