Abstract

Taxonomic classification of viruses is essential for understanding their evolution. Genomic classification of viruses at higher taxonomic ranks, such as order or phylum, is typically based on alignment and comparison of amino acid sequence motifs in conserved genes. Classification at lower taxonomic ranks, such as genus or species, is usually based on nucleotide sequence identities between genomic sequences. Building on our whole-genome analytical classification framework, we here describe Genome Relationships Applied to Viral Taxonomy Version 2 (GRAViTy-V2), which encompasses a greatly expanded range of features and numerous optimisations, packaged as an application that may be used as a general-purpose virus classification tool. Using 28 datasets derived from the ICTV 2022 taxonomy proposals, GRAViTy-V2 output was compared against human expert-curated classifications used for assignments in the 2023 round of ICTV taxonomy changes. GRAViTy-V2 produced taxonomies equivalent to manually-curated versions down to the family level and in almost all cases, to genus and species levels. The majority of discrepant results arose from errors in coding sequence annotations in INDSC records, or from inclusion of incomplete genome sequences in the analysis. Analysis times ranged from 1-506 min (median 3.59) on datasets with 17-1004 genomes and mean genome length of 3000–1 000 000 bases.

Details

Title
GRAViTy-V2: a grounded viral taxonomy application
Author
Mayne, Richard 1   VIAFID ORCID Logo  ; Aiewsakun, Pakorn 2   VIAFID ORCID Logo  ; Turner, Dann 3   VIAFID ORCID Logo  ; Adriaenssens, Evelien M 4   VIAFID ORCID Logo  ; Simmonds, Peter 1   VIAFID ORCID Logo 

 Peter Medawar Building for Pathogen Research, Nuffield Department of Medicine, University of Oxford , 3 South Parks Road, OX1 3SY Oxfordshire , UK 
 Department of Microbiology, Faculty of Science, Mahidol University , 272 Rama VI Road, Thung Phaya Thai, Ratchathewi, Bangkok 10400 , Thailand 
 School of Applied Sciences, University of the West of England , Frenchay Campus, BS16 1QY Bristol , UK 
 Quadram Institute Bioscience , Rosalind Franklin Rd, NR4 7UQ Norwich , UK 
Publication year
2024
Publication date
Dec 2024
Publisher
Oxford University Press
e-ISSN
26319268
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3168786546
Copyright
© The Author(s) 2024. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics. This work is published under https://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.