Review toward all RNA structures, concisely

Structural analysis of MALAT1 long noncoding RNA in cells and in evolution

Although not canonically polyadenylated, the long noncoding RNA MALAT1 (metastasis-associated lung adenocarcinoma transcript 1) is stabilized by a highly conserved 76-nt triple helix structure on its 3' end. The entire MALAT1 transcript is over 8000 nt long in humans. The strongest structural conservation signal in MALAT1 (as measured by covariation of base pairs) is in the triple helix structure. Primary sequence analysis of covariation alone does not reveal the degree of structural conservation of the entire full-length transcript, however. Furthermore, RNA structure is often context dependent; RNA binding proteins that are differentially expressed in different cell types may alter structure. We investigate here the in-cell and cell-free structures of the full-length human and green monkey (Chlorocebus sabaeus) MALAT1 transcripts in multiple tissue-derived cell lines using SHAPE chemical probing. Our data reveal levels of uniform structural conservation in different cell lines, in cells and cell-free, and even between species, despite significant differences in primary sequence. The uniformity of the structural conservation across the entire transcript suggests that, despite seeing covariation signals only in the triple helix junction of the lncRNA, the rest of the transcript's structure is remarkably conserved, at least in primates and across multiple cell types and conditions.

Identifying proximal RNA interactions from cDNA-encoded crosslinks with ShapeJumper

SHAPE-JuMP is a concise strategy for identifying close-in-space interactions in RNA molecules. Nucleotides in close three-dimensional proximity are crosslinked with a bi-reactive reagent that covalently links the 2'-hydroxyl groups of the ribose moieties. The identities of crosslinked nucleotides are determined using an engineered reverse transcriptase that jumps across crosslinked sites, resulting in a deletion in the cDNA that is detected using massively parallel sequencing. Here we introduce ShapeJumper, a bioinformatics pipeline to process SHAPE-JuMP sequencing data and to accurately identify through-space interactions, as observed in complex JuMP datasets. ShapeJumper identifies proximal interactions with near-nucleotide resolution using an alignment strategy that is optimized to tolerate the unique non-templated reverse-transcription profile of the engineered crosslink-traversing reverse-transcriptase. JuMP-inspired strategies are now poised to replace adapter-ligation for detecting RNA-RNA interactions in most crosslinking experiments.

Direct Mapping of Higher-Order RNA Interactions by SHAPE-JuMP

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.

SHAPE Directed Discovery of New Functions in Large RNAs

RNA lies upstream of nearly all biology and functions as the central conduit of information exchange in all cells. RNA molecules encode information both in their primary sequences and in complex structures that form when an RNA folds back on itself. From the time of discovery of mRNA in the late 1950s until quite recently, we had only a rudimentary understanding of RNA structure across vast regions of most messenger and noncoding RNAs. This deficit is now rapidly being addressed, especially by selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) chemistry, mutational profiling (MaP), and closely related platform technologies that, collectively, create chemical microscopes for RNA. These technologies make it possible to interrogate RNA structure, quantitatively, at nucleotide resolution, and at large scales, for entire mRNAs, noncoding RNAs, and viral RNA genomes. By applying comprehensive structure probing to diverse problems, we and others are showing that control of biological function mediated by RNA structure is ubiquitous across prokaryotic and eukaryotic organisms.Work over the past decade using SHAPE-based analyses has clarified key principles. First, the method of RNA structure probing matters. SHAPE-MaP, with its direct and one-step readout that probes nearly every nucleotide by reaction at the 2'-hydroxyl, gives a more detailed and accurate readout than alternatives. Second, comprehensive chemical probing is essential. Focusing on fragments of large RNAs or using meta-gene or statistical analyses to compensate for sparse data sets misses critical features and often yields structure models with poor predictive power. Finally, every RNA has its own internal structural personality. There are myriad ways in which RNA structure modulates sequence accessibility, protein binding, translation, splice-site choice, phase separation, and other fundamental biological processes. In essentially every instance where we have applied rigorous and quantitative SHAPE technologies to study RNA structure-function interrelationships, new insights regarding biological regulatory mechanisms have emerged. RNA elements with more complex higher-order structures appear more likely to contain high-information-content clefts and pockets that bind small molecules, broadly informing a vigorous field of RNA-targeted drug discovery.The broad implications of this collective work are twofold. First, it is long past time to abandon depiction of large RNAs as simple noodle-like or gently flowing molecules. Instead, we need to emphasize that nearly all RNAs are punctuated with distinctive internal structures, a subset of which modulate function in profound ways. Second, structure probing should be an integral component of any effort that seeks to understand the functional nexuses and biological roles of large RNAs.

Transposon clusters as substrates for aberrant splice-site activation

Transposed elements (TEs) have dramatically shaped evolution of the exon-intron structure and significantly contributed to morbidity, but how recent TE invasions into older TEs cooperate in generating new coding sequences is poorly understood. Employing an updated repository of new exon-intron boundaries induced by pathogenic mutations, termed DBASS, here we identify novel TE clusters that facilitated exon selection. To explore the extent to which such TE exons maintain RNA secondary structure of their progenitors, we carried out structural studies with a composite exon that was derived from a long terminal repeat (LTR78) and AluJ and was activated by a C > T mutation optimizing the 5ʹ splice site. Using a combination of SHAPE, DMS and enzymatic probing, we show that the disease-causing mutation disrupted a conserved AluJ stem that evolved from helix 3.3 (or 5b) of 7SL RNA, liberating a primordial GC 5ʹ splice site from the paired conformation for interactions with the spliceosome. The mutation also reduced flexibility of conserved residues in adjacent exon-derived loops of the central Alu hairpin, revealing a cross-talk between traditional and auxilliary splicing motifs that evolved from opposite termini of 7SL RNA and were approximated by Watson-Crick base-pairing already in organisms without spliceosomal introns. We also identify existing Alu exons activated by the same RNA rearrangement. Collectively, these results provide valuable TE exon models for studying formation and kinetics of pre-mRNA building blocks required for splice-site selection and will be useful for fine-tuning auxilliary splicing motifs and exon and intron size constraints that govern aberrant splice-site activation.

On the Way to Understanding the Interplay between the RNA Structure and Functions in Cells: A Genome-Wide Perspective

RNAs adopt specific structures in order to perform their biological activities. The structure of RNA is an important layer of gene expression regulation, and can impact a plethora of cellular processes, starting with transcription, RNA processing, and translation, and ending with RNA turnover. The development of high-throughput technologies has enabled a deeper insight into the sophisticated interplay between the structure of the cellular transcriptome and the living cells environment. In this review, we present the current view on the RNA structure in vivo resulting from the most recent transcriptome-wide studies in different organisms, including mammalians, yeast, plants, and bacteria. We focus on the relationship between the mRNA structure and translation, mRNA stability and degradation, protein binding, and RNA posttranscriptional modifications.

On an enhancement of RNA probing data using information theory

Identifying the secondary structure of an RNA is crucial for understanding its diverse regulatory functions. This paper focuses on how to enhance target identification in a Boltzmann ensemble of structures via chemical probing data. We employ an information-theoretic approach to solve the problem, via considering a variant of the Rényi-Ulam game. Our framework is centered around the ensemble tree, a hierarchical bi-partition of the input ensemble, that is constructed by recursively querying about whether or not a base pair of maximum information entropy is contained in the target. These queries are answered via relating local with global probing data, employing the modularity in RNA secondary structures. We present that leaves of the tree are comprised of sub-samples exhibiting a distinguished structure with high probability. In particular, for a Boltzmann ensemble incorporating probing data, which is well established in the literature, the probability of our framework correctly identifying the target in the leaf is greater than \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$90\%$$\end{document}90%.

SHAPE probing pictures Mg2+-dependent folding of small self-cleaving ribozymes

Self-cleaving ribozymes are biologically relevant RNA molecules which catalyze site-specific cleavage of the phosphodiester backbone. Gathering knowledge of their three-dimensional structures is critical toward an in-depth understanding of their function and chemical mechanism. Equally important is collecting information on the folding process and the inherent dynamics of a ribozyme fold. Over the past years, Selective-2′-Hydroxyl Acylation analyzed by Primer Extension (SHAPE) turned out to be a significant tool to probe secondary and tertiary interactions of diverse RNA species at the single nucleotide level under varying environmental conditions. Small self-cleaving ribozymes, however, have not been investigated by this method so far. Here, we describe SHAPE probing of pre-catalytic folds of the recently discovered ribozyme classes twister, twister-sister (TS), pistol and hatchet. The study has implications on Mg²⁺-dependent folding and reveals potentially dynamic residues of these ribozymes that are otherwise difficult to identify. For twister, TS and pistol ribozymes the new findings are discussed in the light of their crystal structures, and in case of twister also with respect to a smFRET folding analysis. For the hatchet ribozyme where an atomic resolution structure is not yet available, the SHAPE data challenge the proposed secondary structure model and point at selected residues and putative long-distance interactions that appear crucial for structure formation and cleavage activity.

Exploration of Catalytic Nucleic Acids on Porphyrin Metalation and Peroxidase Activity by in Vitro Selection of Aptamers for N-Methyl Mesoporphyrin IX

To develop a novel light-up probe and DNAzyme, we selected aptamers for N-methyl mesoporphyrin IX (NMM), a common fluorogenic analogue of coenzyme hemin, by a modified affinity chromatography-based systematic evolution of ligands by exponential enrichment (SELEX). Two truncated aptamers Nm1 and Nm2 with low micromolar dissociation constants (0.75 and 13.27 μM) were obtained after 11 rounds of selection and the final minimized 39-mer aptamer Nm2.1 showed 24-fold fluorescence enhancement for NMM at saturated concentration. Study of the interactions between aptamers and other porphyrin compounds by circular dichroism (CD) and absorption spectroscopy showed that Nm1 mainly assembled as a stem-loop structure, which exhibited a catalytic activity for the metal insertion reaction of mesoporphyrin IX with 3.3-fold rate enhancement. In contrast, the G-rich Nm2 and Nm2.1 were likely to form G-quadruplexes in the presence of alkali metal cations (K⁺ and Na⁺), which displayed excellent peroxidase activity exhibiting 19-fold higher catalytic efficiency than hemin alone. The selected aptamers could therefore be used as novel light-up fluorescent probes and DNAzymes by pairing with porphyrin compounds that have potential to construct sensors for various applications.

RNA Structural Differentiation: Opportunities with Pattern Recognition

Our awareness and appreciation of the many regulatory roles of RNA have dramatically increased in the past decade. This understanding, in addition to the impact of RNA in many disease states, has renewed interest in developing selective RNA-targeted small molecule probes. However, the fundamental guiding principles in RNA molecular recognition that could accelerate these efforts remain elusive. While high-resolution structural characterization can provide invaluable insight, examples of well-characterized RNA structures, not to mention small molecule:RNA complexes, remain limited. This Perspective provides an overview of the current techniques used to understand RNA molecular recognition when high-resolution structural information is unavailable. We will place particular emphasis on a new method, pattern recognition of RNA with small molecules (PRRSM), that provides rapid insight into critical components of RNA recognition and differentiation by small molecules as well as into RNA structural features.

A guide to large-scale RNA sample preparation

RNA is becoming more important as an increasing number of functions, both regulatory and enzymatic, are being discovered on a daily basis. As the RNA boom has just begun, most techniques are still in development and changes occur frequently. To understand RNA functions, revealing the structure of RNA is of utmost importance, which requires sample preparation. We review the latest methods to produce and purify a variation of RNA molecules for different purposes with the main focus on structural biology and biophysics. We present a guide aimed at identifying the most suitable method for your RNA and your biological question and highlighting the advantages of different methods. Graphical abstract In this review we present different methods for large-scale production and purification of RNAs for structural and biophysical studies.

Pervasive Regulatory Functions of mRNA Structure Revealed by High-Resolution SHAPE Probing

mRNAs can fold into complex structures that regulate gene expression. Resolving such structures de novo has remained challenging and has limited our understanding of the prevalence and functions of mRNA structure. We use SHAPE-MaP experiments in living E. coli cells to derive quantitative, nucleotide-resolution structure models for 194 endogenous transcripts encompassing approximately 400 genes. Individual mRNAs have exceptionally diverse architectures, and most contain well-defined structures. Active translation destabilizes mRNA structure in cells. Nevertheless, mRNA structure remains similar between in-cell and cell-free environments, indicating broad potential for structure-mediated gene regulation. We find that the translation efficiency of endogenous genes is regulated by unfolding kinetics of structures overlapping the ribosome binding site. We discover conserved structured elements in 35% of UTRs, several of which we validate as novel protein binding motifs. RNA structure regulates every gene studied here in a meaningful way, implying that most functional structures remain to be discovered.

Accurate detection of chemical modifications in RNA by mutational profiling (MaP) with ShapeMapper 2

Mutational profiling (MaP) enables detection of sites of chemical modification in RNA as sequence changes during reverse transcription (RT), subsequently read out by massively parallel sequencing. We introduce ShapeMapper 2, which integrates careful handling of all classes of adduct-induced sequence changes, sequence variant correction, basecall quality filters, and quality-control warnings to now identify RNA adduct sites as accurately as achieved by careful manual analysis of electrophoresis data, the prior highest-accuracy standard. MaP and ShapeMapper 2 provide a robust, experimentally concise, and accurate approach for reading out nucleic acid chemical probing experiments.

Know Your Enemy: Successful Bioinformatic Approaches to Predict Functional RNA Structures in Viral RNAs

Structured RNA elements may control virus replication, transcription and translation, and their distinct features are being exploited by novel antiviral strategies. Viral RNA elements continue to be discovered using combinations of experimental and computational analyses. However, the wealth of sequence data, notably from deep viral RNA sequencing, viromes, and metagenomes, necessitates computational approaches being used as an essential discovery tool. In this review, we describe practical approaches being used to discover functional RNA elements in viral genomes. In addition to success stories in new and emerging viruses, these approaches have revealed some surprising new features of well-studied viruses e.g., human immunodeficiency virus, hepatitis C virus, influenza, and dengue viruses. Some notable discoveries were facilitated by new comparative analyses of diverse viral genome alignments. Importantly, comparative approaches for finding RNA elements embedded in coding and non-coding regions differ. With the exponential growth of computer power we have progressed from stem-loop prediction on single sequences to cutting edge 3D prediction, and from command line to user friendly web interfaces. Despite these advances, many powerful, user friendly prediction tools and resources are underutilized by the virology community.

Coiled coil protein origami: from modular design principles towards biotechnological applications

This review illustrates the current state in designing coiled-coil-based proteins with an emphasis on coiled coil protein origami structures and their potential.

Small Molecule-Based Pattern Recognition To Classify RNA Structure

Three-dimensional RNA structures are notoriously difficult to determine, and the link between secondary structure and RNA conformation is only beginning to be understood. These challenges have hindered the identification of guiding principles for small molecule:RNA recognition. We herein demonstrate that the strong and differential binding ability of aminoglycosides to RNA structures can be used to classify five canonical RNA secondary structure motifs through principal component analysis (PCA). In these analyses, the aminoglycosides act as receptors, while RNA structures labeled with a benzofuranyluridine fluorophore act as analytes. Complete (100%) predictive ability for this RNA training set was achieved by incorporating two exhaustively guanidinylated aminoglycosides into the receptor library. The PCA was then externally validated using biologically relevant RNA constructs. In bulge-stem-loop constructs of HIV-1 transactivation response element (TAR) RNA, we achieved nucleotide-specific classification of two independent secondary structure motifs. Furthermore, examination of cheminformatic parameters and PCA loading factors revealed trends in aminoglycoside:RNA recognition, including the importance of shape-based discrimination, and suggested the potential for size and sequence discrimination within RNA structural motifs. These studies present a new approach to classifying RNA structure and provide direct evidence that RNA topology, in addition to sequence, is critical for the molecular recognition of RNA.

Direct identification of base-paired RNA nucleotides by correlated chemical probing

Many RNA molecules fold into complex secondary and tertiary structures that play critical roles in biological function. Among the best-established methods for examining RNA structure are chemical probing experiments, which can report on local nucleotide structure in a concise and extensible manner. While probing data are highly useful for inferring overall RNA secondary structure, these data do not directly measure through-space base-pairing interactions. We recently introduced an approach for single-molecule correlated chemical probing with dimethyl sulfate (DMS) that measures RNA interaction groups by mutational profiling (RING-MaP). RING-MaP experiments reveal diverse through-space interactions corresponding to both secondary and tertiary structure. Here we develop a framework for using RING-MaP data to directly and robustly identify canonical base pairs in RNA. When applied to three representative RNAs, this framework identified 20%-50% of accepted base pairs with a <10% false discovery rate, allowing detection of 88% of duplexes containing four or more base pairs, including pseudoknotted pairs. We further show that base pairs determined from RING-MaP analysis significantly improve secondary structure modeling. RING-MaP-based correlated chemical probing represents a direct, experimentally concise, and accurate approach for detection of individual base pairs and helices and should greatly facilitate structure modeling for complex RNAs.

Mechanisms of long noncoding RNA function in development and disease

Since decades it has been known that non-protein-coding RNAs have important cellular functions. Deep sequencing recently facilitated the discovery of thousands of novel transcripts, now classified as long noncoding RNAs (lncRNAs), in many vertebrate and invertebrate species. LncRNAs are involved in a wide range of cellular mechanisms, from almost all aspects of gene expression to protein translation and stability. Recent findings implicate lncRNAs as key players of cellular differentiation, cell lineage choice, organogenesis and tissue homeostasis. Moreover, lncRNAs are involved in pathological conditions such as cancer and cardiovascular disease, and therefore provide novel biomarkers and pharmaceutical targets. Here we discuss examples illustrating the versatility of lncRNAs in gene control, development and differentiation, as well as in human disease.

The RNA chaperone activity of the Trypanosoma brucei editosome raises the dynamic of bound pre-mRNAs

Mitochondrial transcript maturation in African trypanosomes requires an RNA editing reaction that is characterized by the insertion and deletion of U-nucleotides into otherwise non-functional mRNAs. The reaction is catalyzed by editosomes and requires guide (g)RNAs as templates. Recent data demonstrate that the binding of pre-edited mRNAs to editosomes is followed by a chaperone-type RNA remodeling reaction. Here we map the changes in RNA folding using selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE). We demonstrate that pre-mRNAs in their free state adopt intricately folded, highly stable 2D-structures. Editosome binding renders the pre-mRNAs to adopt 2D-conformations of reduced stabilities. On average about 30% of the nucleotides in every pre-mRNA are affected with a prevalence for U-nucleotides. The data demonstrate that the chaperone activity acts by increasing the flexibility of U-residues to lower their base-pairing probability. This results in a simplified RNA folding landscape with a reduced energy barrier to facilitate the binding of gRNAs. The data provide a first rational for the enigmatic U-specificity of the editing reaction.

Detection of RNA-Protein Interactions in Living Cells with SHAPE

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 and mutational profiling (SHAPE-MaP) for direct, versatile and accurate RNA structure analysis

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.