Newly identified genomic sequences establish benchmarks for proposed taxonomic classification of jingmenviruses

Abstract

Jingmenviruses are a group of viruses related to orthoflaviviruses characterized by a segmented genome and multipartite organisation that have been detected worldwide in a wide range of hosts. As next-generation sequencing has become more affordable, increasing numbers of large-scale metagenomics studies have been published, alongside raw sequencing data. With the growing number of new jingmenvirus sequences identified in metagenomics data, it can be difficult to assess whether a new sequence is associated to a new virus species or to a strain of an existing species. In order to propose clear classification criteria for this group, we assembled a large jingmenvirus sequence database, from published and newly assembled sequences. Indeed, we screened data from studies that did not search for or report jingmenvirus sequences, looking for new strains of known jingmenvirus species. We then performed multiple sequence alignments and used the inferred percentage identity values to determine demarcation criteria based on the distribution of evolutionary distances upon pairwise comparisons. We report the identification of almost 60 libraries containing jingmenvirus sequences, in a wide range of sample types and geographical locations. Using these data and published jingmenvirus sequences, we have determined that to classify jingmenvirus sequences into virus species, at least four segments are required, on which eight cut-off values in percentage identity (nucleotide and amino acid) are used for demarcation. The ratification of this proposal would enhance consistency in virus taxonomy and provide a standardized framework for comparative genomics studies of jingmenviruses, a group that is yet under-characterised. ImportanceThere are currently no guidelines to classify jingmenvirus sequences which means sequences are associated to species with no ratified rationale, which can result in missed opportunities at better describing jingmenvirus genomics. In this study we propose criteria to provide a parsimonious framework for classifying jingmenvirus species based on current knowledge, and allow us to propose re-classification of some sequences and to identify outlier sequences which we recommend should be further characterised in vitro.