Identification of RNA Virus-Derived RdRp Sequences in Publicly Available Transcriptomic Data Sets

Area of Science:

• Virology
• Bioinformatics
• Genomics

Background:

• RNA viruses are diverse and infect most eukaryotic organisms, but only a small fraction of their species have been catalogued.
• Discovering novel RNA virus sequences is crucial for understanding viral diversity and host interactions.
• Existing methods for virus discovery can be costly and limited in scope.

Purpose of the Study:

• To cost-effectively expand the catalogued diversity of RNA virus sequences.
• To develop a robust method for identifying RNA viruses in large-scale genomic datasets.
• To provide a valuable resource for the virus discovery community.

Main Methods:

• Mining publicly available transcriptomic datasets.
• Developing 77 family-level Hidden Markov Model (HMM) profiles for the viral RNA-dependent RNA polymerase (RdRp) gene.
• Searching the NCBI Transcriptome Shotgun Assembly (TSA) database using the developed RdRp HMM profiles.

Main Results:

• Identification of 5,867 contigs encoding RNA virus RdRps or fragments thereof.
• Analysis of the diversity, taxonomic classification, phylogeny, and host associations of the identified viral sequences.
• Successful expansion of the known RNA virus sequence diversity.

Conclusions:

• The study significantly expands the known diversity of RNA viruses.
• The 77 curated RdRp HMM profiles serve as a valuable resource for future virus discovery efforts.
• This approach offers a cost-effective strategy for cataloguing novel RNA virus sequences.