bioRxivMicrobiology
Taxonomic classification methods reveal a new subgenus in the paramyxovirus subfamily Orthoparamyxovirinae
H. L. Wells, E. Loh, A. Nava, M. H. Lee, J. Lee, J. R. A. Sukor, I. Navarrete-Macias, E. Liang, C. Firth, J. Epstein, M. Rostal, C. Zambrana-Torrelio, K. A. Murray, P. Daszak, T. Goldstein, J. A. K. Mazet, B. Lee, T. Hughes, E. L. Durigon, S. J. Anthony
Abstract
As part of a broad One Health surveillance effort to detect novel viruses in wildlife and people, we report several paramyxoviruses sequenced primarily from bats during 2013 and 2014 in Brazil and Malaysia, including seven from which we recovered full-length genomes. Of these, six represent the first full-length paramyxovirus genomes sequenced from the Americas, including two sequences which are the first full-length bat morbillivirus genomes published to date. Our findings add to the vast number of viral sequences in public repositories that have been increasing considerably in recent years due to the rising accessibility of metagenomics. Taxonomic classification of these sequences in the absence of phenotypic data has been a significant challenge, particularly in the paramyxovirus subfamily Orthoparamyxovirinae, where the rate of discovery of novel sequences has been substantial. Using pairwise amino acid sequence classification (PASC), we describe a novel genus within this subfamily tentatively named Jeishaanvirus, which we propose should include as subgenera Jeilongvirus, Shaanvirus, and a novel South American subgenus Cadivirus. We also highlight inconsistencies in the classification of Tupaia virus and Mojiang virus using the same demarcation criteria and show that members of the proposed subgenus Shaanvirus are paraphyletic. Importantly, this study underscores the critical importance of sequence length in PASC analysis as well as the importance of biological characteristics such as genome organization in the taxonomic classification of viral sequences.
- assay: whole-genome sequencing
- research focus: chromatin & epigenetic regulation
- research focus: cell type annotation
- research focus: clustering
- research focus: gene regulatory network inference
- approach: deep learning
- approach: statistical model
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