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;




AuthorsMayne, Richard; Smith, Donald B.; Brown, Katherine; Chen, Yan Ping; Firth, Andrew E.; Katayama, Kazuhiko; Knowles, Nick J.; Simmonds, Peter

PublisherOxford University Press

Publication year2026

Journal: Virus evolution

Article numberveag023

Volume12

Issue1

eISSN2057-1577

DOIhttps://doi.org/10.1093/ve/veag023

Publication's open availability at the time of reportingOpen 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 addresshttps://research.utu.fi/converis/portal/detail/Publication/526511350

Self-archived copy's licenceCC BY

Self-archived copy's versionPublisher`s PDF


Abstract

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.
This reprint may differ from the original in pagination and typographic detail. Please cite the original version.




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).


Last updated on 15/06/2026 12:47:58 PM