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Deep mutational scanning and mobility-based selection for 6 RNA targets

ABSTRACT: RNA mutations are known to change mobility in native gels. What is not known is if mobility can serve as an effective tool to separate structurally similar (structural homologs) from structurally destabilized variants in a deep-mutation library of an RNA. Here we defined the proportion of a mutant in the native band from native polyacrylamide gel electrophoresis (PAGE) as a native-mobility-fitness score. The fitness scores of single and double mutants allowed a unsupervised, RNA-specific analysis to detect key secondary and tertiary base pairs through covariational signals. Subsequent amplification of these signals and their use as restraints for folding led to not only high-accuracy secondary structures with the F1-score > 0.9, but also quality tertiary-structure models between 3.6 Å and 7.7 Å RMSD from their native structures for the best in top 5 models for 6 RNAs tested including two CASP 15 difficult targets. This MobiSeq method should provide a simple and effective method for inferring 2D and 3D structures and improving mechanistic understanding of all structured RNAs.

ORGANISM(S): Escherichia coli

PROVIDER: GSE276399 | GEO | 2024/09/10

REPOSITORIES: GEO

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