GRAViTy-V2: A grounded viral taxonomy application

Mayne, Richard; Aiewsakun, Pakorn; Turner, Dann; Adriaenssens, Evelien M; Simmonds, Peter

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.

• Journal Article Type: Article
• Acceptance Date: Dec 3, 2024
• Online Publication Date: Dec 18, 2024
• Publication Date: Dec 31, 2024
• Deposit Date: Jan 14, 2025
• Publicly Available Date: Jan 14, 2025
• Journal: NAR Genomics and Bioinformatics
• Electronic ISSN: 2631-9268
• Publisher: Oxford University Press
• Peer Reviewed: Peer Reviewed
• Volume: 6
• Issue: 4
• Article Number: lqae183
• DOI: https://doi.org/10.1093/nargab/lqae183
• Keywords: Bioinformatics, Virus classification
• Public URL: https://uwe-repository.worktribe.com/output/13540494