Conservative taxonomy and quality assessment of giant virus genomes with GVClass

Large double-stranded DNA viruses of the phylum Nucleocytoviricota (Giant Viruses; GVs) are the largest known viruses, infecting various eukaryotic hosts, particularly protists and algae. These viruses impact biogeochemical cycles and host genome evolution but are challenging to identify and classify due to their complex genomes. We present GVClass, a tool for identifying giant viruses in sequence data, providing taxonomic assignments, and estimating genome completeness and contamination. GVClass employs optimized gene calling and a conservative approach using consensus single-protein phylogenies for robust taxonomic classification, relying on highly conserved orthologous groups. Benchmarking demonstrates over 90% accuracy at the genus-level and >99% at higher taxonomic ranks. GVClass addresses classification challenges and is available as a standalone tool and integrated into the Integrated Microbial Genomes/Virus database (IMG/VR).

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Publication Details

Journal
npj Viruses
Published
2024-11-25
DOI
https://doi.org/10.1038/s44298-024-00069-7
Citations
10
Primary Topic
Bacteriophages and microbial interactions
Type
article
Field-Weighted Citation Impact
4.59

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article

Conservative taxonomy and quality assessment of giant virus genomes with GVClass

Thomas M. Pitot, Frederik Schulz, Tomáš Brůna
10 citations
npj Viruses
Bacteriophages and microbial interactions
4.59
article

Conservative taxonomy and quality assessment of giant virus genomes with GVClass

Thomas M. Pitot, Frederik Schulz, Tomáš Brůna
article en
10 citations

Abstract

Large double-stranded DNA viruses of the phylum Nucleocytoviricota (Giant Viruses; GVs) are the largest known viruses, infecting various eukaryotic hosts, particularly protists and algae. These viruses impact biogeochemical cycles and host genome evolution but are challenging to identify and classify due to their complex genomes. We present GVClass, a tool for identifying giant viruses in sequence data, providing taxonomic assignments, and estimating genome completeness and contamination. GVClass employs optimized gene calling and a conservative approach using consensus single-protein phylogenies for robust taxonomic classification, relying on highly conserved orthologous groups. Benchmarking demonstrates over 90% accuracy at the genus-level and >99% at higher taxonomic ranks. GVClass addresses classification challenges and is available as a standalone tool and integrated into the Integrated Microbial Genomes/Virus database (IMG/VR).

npj VirusesVol. 2(1)
Lawrence Berkeley National Laboratory (US), Joint Genome Institute (US), Université Laval (CA)
U.S. Department of Energy, Joint Genome Institute, Office of Science
Openalex Percentile: Top 5%
Bacteriophages and microbial interactions
4.59
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