Viral RNAs as Dual Graphs: Extending the Motif Universe of RNAs

Abstract

In the evolving landscape of RNA research, the classification and analysis of RNA motifs is necessary to uncover the intricate mechanisms governing cellular and viral processes. Here we apply the coarse-grained RAG (RNA-As-Graphs) framework to advance the classification and understanding of RNA motifs, with a focus on expanding the RNA Motif Atlas through the inclusion of novel viral RNA structures. By analyzing 273 experimentally resolved viral RNA structures from the Protein Data Bank (PDB) using RAG dual-graph representations, we identify 14 previously uncatalogued viral RNA motifs. These motifs, which include tRNA mimicking domains, exoribonuclease-resistant domains, and internal ribosome entry sites, expand the diversity of RNA to a total number of 197 dual graph motifs. We applied k-means, PAM, and Ward clustering and observed substantial overlap between viral and general RNAs. The expanded library of RNA motifs and submotifs provides a resource for motif discovery and RNA design.