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Metagenomic sequencing has expanded the ribonucleic acid (RNA) virosphere, but many identified viral genomes remain incomplete, especially for segmented viruses. Traditional methods relying on sequence homology struggle to identify highly divergent segments and group them confidently within a single virus species. To address this, we developed a new bioinformatic tool—SegFinder—that identifies virus genome segments based on their common co-occurrence at similar abundance within segmented viruses. SegFinder successfully re-discovered all segments from a test data set of individual mosquito transcriptomes, which was also used to establish parameter thresholds for reliable segment identification. Using these optimal parameters, we applied SegFinder to 858 libraries from eight metagenomic sequencing projects, including vertebrates, invertebrates, plants, and environmental samples. Excluding the RdRP segment, we identified 106 unique viral genome segments from these samples. Among them, 53 were novel, including 30 segments that showed no recognizable sequence homology to any known viruses. However, the viral origin of these highly divergent segment was supported by the presence of conserved terminal sequences. SegFinder identifies segmented genome structures in viruses previously considered to be predominantly unsegmented, and in doing so expanded the number of known families and orders of segmented RNA viruses, making it a valuable tool in an era of large-scale parallel sequencing.

SegFinder: an automated tool for identifying complete RNA virus genome segments through co-occurrence in multiple sequenced samples