Massively parallel characterization of RNA G-quadruplex stability and molecular recognition

Abstract

RNA G-quadruplexes (rG4s) have been implicated as important regulators of RNA metabolism and are promising targets for RNA-targeted therapeutics. rG4s typically require a canonical (G[≥]2N1-7)4 motif, but the sequence features that affect rG4 stability and recognition by RNA-binding proteins (RBPs) and rG4-binding ligands are not fully understood. To interrogate sequence-level drivers of rG4 folding, we applied a reverse-transcriptase stop sequencing strategy to a library of [~]3,000 synthetic rG4s with varied G-tract lengths, loop lengths, and loop compositions, permitting massively parallel quantification of rG4 stability. Our data confirm known sequence-level features and characterize novel combinatorial impacts of these features. We also assessed systematically mutagenized natural rG4s, revealing unexpected mutations that significantly affect rG4 stability, including contributions from flanking sequences outside of the rG4. We further used our strategy to assess rG4 recognition preferences of the model rG4- ligand pyridostatin, revealing a preferential stabilization of rG4s containing mixed-length G-tracts. We further demonstrated the potential for large-scale protein binding assays with our library to reveal rG4 features recognized by RBPs, specifically G3BP1 and FMRP. Our approach and data provide a generalizable framework to study sequence-level drivers of rG4 stability, binding by RBPs, and ligand interactions, defining basic principles of rG4 formation and downstream biology.