A1 Refereed original research article in a scientific journal
Comprehensive hallmark gene sequence, genomic and structural analysis clarifies new and established taxa within the Picornavirales; 
Authors: Mayne, Richard; Smith, Donald B.; Brown, Katherine; Chen, Yan Ping; Firth, Andrew E.; Katayama, Kazuhiko; Knowles, Nick J.; Simmonds, Peter
Publisher: Oxford University Press
Publication year: 2026
Journal: Virus evolution
Article number: veag023
Volume: 12
Issue: 1
eISSN: 2057-1577
DOI: https://doi.org/10.1093/ve/veag023
Publication's open availability at the time of reporting: Open Access
Publication channel's open availability : Open Access publication channel
Web address : https://academic.oup.com/ve/article/12/1/veag023/8659228
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/526511350
Self-archived copy's licence: CC BY
Self-archived copy's version: Publisher`s PDF
The order Picornavirales is a group of highly diverse RNA viruses that includes many pathogens of significance to human and veterinary health, agriculture, and the wider environment. However, the wide range of viruses assigned to the order, together with their genomic variability, and the recent description of numerous ‘picorna-like’ viruses derived from metagenomic analyses of environmental samples, challenge the established taxonomic classification of members of the order and the criteria for their classification. Here, we combine the existing gold standard, hallmark RNA-directed RNA-polymerase (RdRP) gene sequence-based analysis with helicase sequence-based phylogeny, RdRP structural prediction through the use of ColabFold and Fold Tree, and analysis of coding-complete genomes using GRAViTy-V2, to genetically classify 525 picornaviral genomes and recently described ‘picorna-like’ viruses. All analyses were conducted with a bespoke, fully automated pipeline for retrieval of genome sequences, domain prediction and extraction, phylogenetic analysis, and output conditioning, which is available as open-source software. Our results reveal broad support for established families as well as for 6 novel families, and 32 new genera. In instances where inconsistencies were found between classification methods, we demonstrate how examination of the pipeline’s output may be used to reconcile differences with respect to the genomic features quantified by the analysis. Automated multimodal taxonomic analysis may save significant resources over manual methods and better define demarcation criteria for families and genera.
Keywords:
ICTV
Downloadable publication This is an electronic reprint of the original article. |
Funding information in the publication:
The Pirbright Institute receives grant-aided support from the Biotechnology and Biological Sciences Research Council (BBSRC) of the United Kingdom (projects BBS/E/I/00007037, BBS/E/PI/230001 A, BBS/E/PI/230002 C, and BBS/E/PI/23NB0004).