ArticleMolecular biology and evolution2024
SegVir: Reconstruction of Complete Segmented RNA Viral Genomes from Metatranscriptomes.
Article in Molecular biology and evolution, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- RdRpCATCH: a unified resource for RNA virus discovery using viral RNA-dependent RNA polymerase profile Hidden Markov models.NAR genomics and bioinformatics · 2026Article
- Fast and accurate identification of emerging viral reassortment from genome sequences.Nucleic acids research · 2026Article
- SegFinder: an automated tool for identifying complete RNA virus genome segments through co-occurrence in multiple sequenced samples.Briefings in bioinformatics · 2025Article
- Discovery of additional genomic segments reveals the fluidity of jingmenvirus genomic organization.Virus evolution · 2025Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Segmented RNA viruses are a complex group of RNA viruses with multisegment genomes. Reconstructing complete segmented viruses is crucial for advancing our understanding of viral diversity, evolution, and public health impact. Using metatranscriptomic data to identify known and novel segmented viruses has sped up the survey of segmented viruses in various ecosystems. However, the high genetic diversity and the difficulty in binning complete segmented genomes present significant challenges in segmented virus reconstruction. Current virus detection tools are primarily used to identify nonsegmented viral genomes. This study presents SegVir, a novel tool designed to identify segmented RNA viruses and reconstruct their complete genomes from complex metatranscriptomes. SegVir leverages both close and remote homology searches to accurately detect conserved and divergent viral segments. Additionally, we introduce a new method that can evaluate the genome completeness and conservation based on gene content. Our evaluations on simulated datasets demonstrate SegVir's superior sensitivity and precision compared to existing tools. Moreover, in experiments using real data, we identified some virus segments missing in the NCBI database, underscoring SegVir's potential to enhance viral metagenome analysis. The source code and supporting data of SegVir are available via https://github.com/HubertTang/SegVir.
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Registered trials
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