CRESSENT: a bioinformatics toolkit to explore and improve ssDNA virus annotation

Area of Science:

• Virology
• Bioinformatics
• Genomics

Background:

• Single-stranded DNA (ssDNA) viruses are ecologically significant but difficult to identify and classify due to genomic diversity and rapid evolution.
• Distinguishing true ssDNA viral sequences from contaminants in metagenomic data is a persistent challenge.

Purpose of the Study:

• To introduce CRESSENT (CRESS-DNA Extended aNnotation TToolkit), a comprehensive bioinformatic pipeline for ssDNA virus genome analysis and annotation.
• To enable systematic inclusion of ssDNA viruses in viromics workflows and facilitate comparative genomic studies.

Main Methods:

• CRESSENT is a modular pipeline integrating sequence dereplication, decontamination, phylogenetic analysis, motif discovery, stem-loop structure prediction, and recombination detection.
• Modules can be used independently or combined for customized analysis workflows.
• The pipeline is designed for scalability, low memory usage, and parallel processing.

Main Results:

• CRESSENT efficiently processes ssDNA virus datasets of various sizes.
• Small family-level analyses are completed in minutes, and moderate comparative genomics studies in hours on standard computing resources.
• Benchmarking confirms the tool's effectiveness and accessibility for diverse research groups.

Conclusions:

• CRESSENT provides a robust solution for the systematic identification, classification, and analysis of ssDNA viruses.
• The tool enhances the study of microbial communities by enabling comprehensive viromic analyses previously limited for ssDNA viruses.
• CRESSENT facilitates comparative genomics of ssDNA viruses, crucial for understanding their role in ecosystems.