Detection of RNA-Protein Interactions in Living Cells with SHAPE.

Abstract

SHAPE-MaP is unique among RNA structure probing strategies in that it both measures flexibility at single-nucleotide resolution and quantifies the uncertainties in these measurements. We report a straightforward analytical framework that incorporates these uncertainties to allow detection of RNA structural differences between any two states, and we use it here to detect RNA-protein interactions in healthy mouse trophoblast stem cells. We validate this approach by analysis of three model cytoplasmic and nuclear ribonucleoprotein complexes, in 2 min in-cell probing experiments. In contrast, data produced by alternative in-cell SHAPE probing methods correlate poorly (r = 0.2) with those generated by SHAPE-MaP and do not yield accurate signals for RNA-protein interactions. We then examine RNA-protein and RNA-substrate interactions in the RNase MRP complex and, by comparing in-cell interaction sites with disease-associated mutations, characterize these noncoding mutations in terms of molecular phenotype. Together, these results reveal that SHAPE-MaP can define true interaction sites and infer RNA functions under native cellular conditions with limited preexisting knowledge of the proteins or RNAs involved.