Virus classification based on in-depth sequence analyses and development of demarcation criteria using the Betaflexiviridae as a case study. (18th November 2022)

• Record Type: Journal Article
• Authors: Silva, João Marcos Fagundes; Melo, Fernando Lucas; Elena, Santiago F.; Candresse, Thierry; Sabanadzovic, Sead; Tzanetakis, Ioannis E.; Blouin, Arnaud G.; Villamor, Dan Edward Veloso; Mollov, Dimitre; Constable, Fiona; Cao, Mengji; Saldarelli, Pasquale; Cho, Won Kyong; Nagata, Tatsuya
• Is Part Of: Journal of general virology. Volume 103:Number 11(2022)
• Publication Date: 2022-11-18
• Subjects: betaflexivirus -- demarcation criteria -- phylogenetics -- virus taxonomy; Virology -- Periodicals; Viruses; Microbiology; Virology; Virologie -- Périodiques; Microbiologie -- Périodiques; Virology; Virologie; Virologie; Electronic journals; Periodical; Periodicals; 579.2
• DOI: 10.1099/jgv.0.001806
• Languages: English
• ISSNs: 0022-1317

Abstract

Abstract : Currently, many viruses are classified based on their genome organization and nucleotide/amino acid sequence identities of their capsid and replication-associated proteins. Although biological traits such as vector specificities and host range are also considered, this later information is scarce for the majority of recently identified viruses, characterized only from genomic sequences. Accordingly, genomic sequences and derived information are being frequently used as the major, if not only, criteria for virus classification and this calls for a full review of the process. Herein, we critically addressed current issues concerning classification of viruses in the family Betaflexiviridae in the era of high-throughput sequencing and propose an updated set of demarcation criteria based on a process involving pairwise identity analyses and phylogenetics. The proposed framework has been designed to solve the majority of current conundrums in taxonomy and to facilitate future virus classification. Finally, the analyses performed herein, alongside the proposed approaches, could be used as a blueprint for virus classification at-large.