Language

    English

    Publication Date

    2-1-2026

    Journal

    Microbial Genomics

    DOI

    10.1099/mgen.0.001632

    PMID

    41642221

    PMCID

    PMC12877143

    PubMedCentral® Posted Date

    2-5-2026

    PubMedCentral® Full Text Version

    Post-print

    Abstract

    ssDNA viruses are important components of diverse ecosystems; however, it remains challenging to systematically identify and classify them. This is partly due to their broad host range and resulting genomic diversity, structure and rapid evolutionary rates. In addition, distinguishing genuine ssDNA genomes from contaminating sequences in metagenomic datasets (e.g. from commercial kits) has been an unresolved issue for years. Here, we present CRESSENT (CRESS-DNA Extended aNnotation Toolkit), a comprehensive and modular bioinformatic pipeline focused on ssDNA virus 'genome-to-analysis' and annotation. The pipeline integrates multiple functionalities organized into several modules: sequence dereplication, decontamination, phylogenetic analysis, motif discovery, stem-loop structure prediction and recombination detection. Each module can be used independently or in combination with others, allowing researchers to customize their analysis workflow. With this tool, researchers can comprehensively and systematically include ssDNA viruses in their viromics workflows and facilitate comparative genomic studies, which are often limited to dsDNA viruses, therefore leaving behind a crucial component of the microbiome community under study. Benchmarking analyses demonstrated that CRESSENT efficiently processes ssDNA virus datasets of varying scales, completing small family-level analyses within minutes and moderate comparative genomics studies within hours using standard computing resources. Its modular, parallelized design ensures scalability and low memory usage, making it accessible to research groups with diverse computational capacities.

    Keywords

    Computational Biology, DNA, Single-Stranded, DNA Viruses, annotation, genomics, metagenomics, phylogenetic analysis, ssDNA, ssDNA virus, Genome, Viral, Phylogeny, Molecular Sequence Annotation, Software, Metagenomics, DNA, Viral

    Published Open-Access

    yes

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