SHAPE chemistries exploit small electrophilic reagents that react with the 2′-hydroxyl group to interrogate RNA structure at single-nucleotide resolution. Mutational profiling (MaP) identifies modified residues based on the ability of 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 for simple model RNAs. This protocol describes the experimental steps, implemented over three days, required to perform SHAPE probing and construct multiplexed SHAPE-MaP libraries suitable for deep sequencing. These steps include RNA folding and SHAPE structure probing, mutational profiling by reverse transcription, library construction, and 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, often within an hour. SuperFold uses these data to model RNA secondary structures, identify regions with well-defined structures, and visualize probable and alternative helices, often in under a day. We illustrate these algorithms with the E. coli thiamine pyrophosphate riboswitch, E. coli 16S rRNA, and HIV-1 genomic RNAs. SHAPE-MaP can be used to make nucleotide-resolution biophysical measurements of individual RNA motifs, rare components of complex RNA ensembles, and entire transcriptomes. The straightforward MaP strategy greatly expands the number, length, and complexity of analyzable RNA structures.

The 18-kb Xist long noncoding RNA (lncRNA) is essential for X-chromosome inactivation during female eutherian mammalian development. Global structural architecture, cell-induced conformational changes, and protein-RNA interactions within Xist are poorly understood. We used selective 2′-hydroxyl acylation analyzed by primer extension and mutational profiling (SHAPE-MaP) to examine these features of Xist at single-nucleotide resolution both in living cells and ex vivo. The Xist RNA forms complex welldefined secondary structure domains and the cellular environment strongly modulates the RNA structure, via motifs spanning onehalf of all Xist nucleotides. The Xist RNA structure modulates protein interactions in cells via multiple mechanisms. For example, repeatcontaining elements adopt accessible and dynamic structures that function as landing pads for protein cofactors. Structured RNA motifs create interaction domains for specific proteins and also sequester other motifs, such that only a subset of potential binding sites forms stable interactions. This work creates a broad quantitative framework for understanding structure-function interrelationships for Xist and other lncRNAs in cells.ong noncoding RNAs (lncRNAs) play central roles in the regulation of gene expression through interactions with numerous protein partners (1) and are necessary for normal health and development (2, 3). The 18-kb Xist lncRNA is essential for X-chromosome inactivation during female eutherian mammalian development and is an archetype of gene-silencing lncRNAs. During the early stages of X inactivation, Xist accumulates in cis around the future inactive X chromosome and recruits protein complexes that apply repressive chromatin modifications, leading to stable gene silencing (3,4).Genetic deletion studies have demarcated several broad regions of function within Xist. Several tandem repeat regions (labeled A-F in the mouse) show moderate conservation (5-7), and at least two of these, repeat A and the rodent-specific repeat C, are implicated in silencing and localization to the inactive X. Deletion of the final 7.5-kb exon of Xist causes a defect in its localization (8), and the 1.5-kb region encompassing repeats F and B is required for accumulation of heterochromatic marks over the inactive X (4); however, beyond these initial characterizations, the mechanisms by which gene silencing, heterochromatinization, and localization of Xist on the X chromosome occur are not well understood. In particular, the role of RNA structure in orchestrating these distinct functions remains unclear.Several previous studies have suggested the importance of RNA structures in specific regions of Xist (9-12), but overall, the locations and structures of functional domains within Xist are poorly defined. Detailed structural maps of other functional RNAs, such as ribosomal RNAs (13) and the HIV RNA genome (14-16), have been fundamental to understanding the mechanisms by which individual domains within large RNAs execute discrete cellular functions. A detailed an...

The emergence of catalysis in early genetic polymers like RNA is considered a key transition in the origin of life1, predating the appearance of protein enzymes. DNA also demonstrates the capacity to fold into three-dimensional structures and form catalysts in vitro2. However, to what degree these natural biopolymers comprise functionally privileged chemical scaffolds3 for folding or the evolution of catalysis is not known. The ability of synthetic genetic polymers (XNAs) with alternative backbone chemistries not found in nature to fold into defined structures and bind ligands4 raises the possibility that these too might be capable of forming catalysts (XNAzymes). Here we report the discovery of such XNAzymes, elaborated in four different chemistries (ANA (arabino nucleic acids)5, FANA (2′-fluoroarabino nucleic acids)6, HNA (hexitol nucleic acids) and CeNA (cyclohexene nucleic acids)7 directly from random XNA oligomer pools, exhibiting in trans RNA endonuclease and ligase activities. We also describe an XNA-XNA ligase metalloenzyme in the FANA framework, establishing catalysis in an entirely synthetic system and enabling the synthesis of FANA oligomers and an active RNA endonuclease FANAzyme from its constituent parts. These results extend catalysis beyond biopolymers and establish technologies for the discovery of catalysts in a wide range of polymer scaffolds not found in nature8. Evolution of catalysis independent of any natural polymer has implications for the definition of chemical boundary conditions for the emergence of life on earth and elsewhere in the universe9.

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 enable 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-minute 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 non-coding 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 pre-existing knowledge of the proteins or RNAs involved.

The functions of most long non-coding RNAs (lncRNAs) are unknown. In contrast to proteins, lncRNAs with similar functions often lack linear sequence homology; thus, the identification of function in one lncRNA rarely informs the identification of function in others. We developed a sequence comparison method to deconstruct linear sequence relationships in lncRNAs and evaluate similarity based on the abundance of short motifs called k-mers. We found that lncRNAs of related function often had similar k-mer profiles despite lacking linear homology, and that k-mer profiles correlated with protein binding to lncRNAs and with their subcellular localization. Using a novel assay to quantify Xist-like regulatory potential, we directly demonstrated that evolutionarily unrelated lncRNAs can encode similar function through different spatial arrangements of related sequence motifs. K-mer-based classification is a powerful approach to detect recurrent relationships between sequence and function in lncRNAs.