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Higher-order structure governs function for many RNAs. However, discerning this structure for large RNA molecules in solution is an unresolved challenge. Here, we present SHAPE-JuMP (selective 2'-hydroxyl acylation analyzed by primer extension and juxtaposed merged pairs) to interrogate through-space RNA tertiary interactions. A bifunctional small molecule is used to chemically link proximal nucleotides in an RNA structure. The RNA cross-link site is then encoded into complementary DNA (cDNA) in a single, direct step using an engineered reverse transcriptase that "jumps" across cross-linked nucleotides. The resulting cDNAs contain a deletion relative to the native RNA sequence, which can be detected by sequencing, that indicates the sites of cross-linked nucleotides. SHAPE-JuMP measures RNA tertiary structure proximity concisely across large RNA molecules at nanometer resolution. SHAPE-JuMP is especially effective at measuring interactions in multihelix junctions and loop-to-helix packing, enables modeling of the global fold for RNAs up to several hundred nucleotides in length, facilitates ranking of structural models by consistency with through-space restraints, and is poised to enable solution-phase structural interrogation and modeling of complex RNAs.

This protocol is an extension to: Nat. Protoc. 10, 1643-1669 (2015); doi:10.1038/nprot.2015.103; published online 01 October 2015RNAs play key roles in many cellular processes. The underlying structure of RNA is an important determinant of how transcripts function, are processed, and interact with RNA-binding proteins and ligands. RNA structure analysis by selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) takes advantage of the reactivity of small electrophilic chemical probes that react with the 2'-hydroxyl group to assess RNA structure at nucleotide resolution. When coupled with mutational profiling (MaP), in which modified nucleotides are detected as internal miscodings during reverse transcription and then read out by massively parallel sequencing, SHAPE yields quantitative per-nucleotide measurements of RNA structure. Here, we provide an extension to our previous in vitro SHAPE-MaP protocol with detailed guidance for undertaking and analyzing SHAPE-MaP probing experiments in live cells. The MaP strategy works for both abundant-transcriptome experiments and for cellular RNAs of low to moderate abundance, which are not well examined by whole-transcriptome methods. In-cell SHAPE-MaP, performed in roughly 3 d, can be applied in cell types ranging from bacteria to cultured mammalian cells and is compatible with a variety of structure-probing reagents. We detail several strategies by which in-cell SHAPE-MaP can inform new biological hypotheses and emphasize downstream analyses that reveal sequence or structure motifs important for RNA interactions in cells.

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.

Selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) chemistries exploit small electrophilic reagents that react with 2'-hydroxyl groups to interrogate RNA structure at single-nucleotide resolution. Mutational profiling (MaP) identifies modified residues by using reverse transcriptase to misread a SHAPE-modified nucleotide and then counting the resulting mutations by massively parallel sequencing. The SHAPE-MaP approach measures the structure of large and transcriptome-wide systems as accurately as can be done for simple model RNAs. This protocol describes the experimental steps, implemented over 3 d, that are required to perform SHAPE probing and to construct multiplexed SHAPE-MaP libraries suitable for deep sequencing. Automated processing of MaP sequencing data is accomplished using two software packages. ShapeMapper converts raw sequencing files into mutational profiles, creates SHAPE reactivity plots and provides useful troubleshooting information. SuperFold uses these data to model RNA secondary structures, identify regions with well-defined structures and visualize probable and alternative helices, often in under 1 d. SHAPE-MaP can be used to make nucleotide-resolution biophysical measurements of individual RNA motifs, rare components of complex RNA ensembles and entire transcriptomes.