Bioinformatics of virus taxonomy: foundations and tools for developing sequence-based hierarchical classification.

Area of Science:

• Virology
• Bioinformatics
• Genomics

Background:

• Viral genome sequences are fundamental for systematic, evolution-aware classification (virus taxonomy).
• The International Committee on Taxonomy of Viruses (ICTV) oversees a hierarchical classification system with 15 ranks.
• Researchers outside ICTV use various computational metrics for classifying unassigned viruses into existing taxa.

Purpose of the Study:

• To highlight the critical role of comparative genomics in virus taxonomy.
• To review computational approaches used for virus clustering and classification.
• To emphasize the need for advancing computational tools for virosphere-wide taxa demarcation.

Main Methods:

• Analysis of virus genome sequences.
• Application of comparative genomics principles.
• Utilizing diverse computational clustering metrics (conserved domains, phylogenetic trees, distance spaces).

Main Results:

• Genome sequence is the primary data for virus classification.
• Multiple computational methods exist for virus clustering, with varying sensitivities and outputs.
• Advancements in computational tools are crucial for improving virus taxonomy.

Conclusions:

• Computational approaches are vital for organizing viral knowledge and refining virus taxonomy.
• Improved tools can enhance taxa demarcation across the entire virosphere.
• This research informs experimental virology by providing a systematic framework for viral classification.