The Challenges of Analysing Highly Diverse Picobirnavirus Sequence Data

Area of Science:

• Virology
• Bioinformatics
• Genomics

Background:

• Accurate infectious disease identification is crucial for control and understanding viral biology.
• Vast undiscovered viral diversity exists, with classification relying on incomplete public databases.
• Picobirnaviridae, a dsRNA virus family, has limited sequence data, hindering its identification and study.

Purpose of the Study:

• To investigate the diversity within the Picobirnavirus genus and other dsRNA viruses.
• To assess the impact of common sequence analysis practices on phylogenetic classification.
• To explore the potential for undiscovered viral diversity within Picobirnaviridae.

Main Methods:

• Phylogenetic analysis of dsRNA virus sequences.
• Protein structure homology modeling for functional insights.
• Comparative analysis of Picobirnavirus diversity against other dsRNA genera.

Main Results:

• Picobirnavirus diversity surpasses that of many other dsRNA virus genera.
• Sequence fragment length and trimming significantly influence phylogenetic conclusions for Picobirnavirus.
• Significant phylogenetic and functional divergence indicates substantial undiscovered Picobirnavirus diversity.

Conclusions:

• The Picobirnavirus genus harbors immense undiscovered diversity, contributing to the
• viral dark matter
• observed in metagenomics.
• Current classification methods require re-evaluation to accurately represent Picobirnavirus diversity.
• Further research is needed to fully characterize the virosphere and its novel members.