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Deep mutational scanning and mobility-based selection for structured RNAs

ABSTRACT: Deciphering RNA three-dimensional structures remains a central challenge in molecular biology. Deep mutational profiling has captured evolutionary constraints. However, its current application has been limited to a few RNA functions that are compatible with high-throughput selection. Here, we introduce RNA-MobiSeq, where deep-mutational variants with similar structures to the wild type were enriched by mobility-selected native gel bands and analyzed for covariation by an unsupervised, RNA-specific method and thermodynamic modeling. This de novo folding platform enabled accurate prediction of base-pairing (F1-score ≥ 90%) and improved performance on tertiary structure prediction over existing template-free modeling techniques for nine RNAs in diverse structures and functions. Validated for robustness by replicate experiments, the integrated platform provides a probe-free and broadly applicable framework for elucidating structural landscapes for RNAs that can be synthesized and assayed under in vitro native gel electrophoresis conditions, thereby bridging sequence information and functional understanding.

ORGANISM(S): Escherichia coli

PROVIDER: GSE276399 | GEO | 2024/09/10

REPOSITORIES: GEO

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