Causes, functions, and therapeutic possibilities of RNA secondary structure ensembles and alternative states.

RNA secondary structure plays essential roles in encoding RNA regulatory fate and function. Most RNAs populate ensembles of alternatively paired states and are continually unfolded and refolded by cellular processes. Measuring these structural ensembles and their contributions to cellular function has traditionally posed major challenges, but new methods and conceptual frameworks are beginning to fill this void. In this review, we provide a mechanism- and function-centric compendium of the roles of RNA secondary structural ensembles and minority states in regulating the RNA life cycle, from transcription to degradation. We further explore how dysregulation of RNA structural ensembles contributes to human disease and discuss the potential of drugging alternative RNA states to therapeutically modulate RNA activity. The emerging paradigm of RNA structural ensembles as central to RNA function provides a foundation for a deeper understanding of RNA biology and new therapeutic possibilities.

Mutation signature filtering enables high-fidelity RNA structure probing at all four nucleobases with DMS.

Chemical probing experiments have transformed RNA structure analysis, enabling high-throughput measurement of base-pairing in living cells. Dimethyl sulfate (DMS) is one of the most widely used structure probing reagents and has played a pivotal role in enabling next-generation single-molecule probing analyses. However, DMS has traditionally only been able to probe adenine and cytosine nucleobases. We previously showed that, using appropriate conditions, DMS can also be used to interrogate base-pairing of uracil and guanines in vitro at reduced accuracy. However, DMS remained unable to informatively probe guanines in cells. Here, we develop an improved DMS mutational profiling (MaP) strategy that leverages the unique mutational signature of N1-methylguanine DMS modifications to enable high-fidelity structure probing at all four nucleotides, including in cells. Using information theory, we show that four-base DMS reactivities convey greater structural information than current two-base DMS and SHAPE probing strategies. Four-base DMS experiments further enable improved direct base-pair detection by single-molecule PAIR analysis, and ultimately support RNA structure modeling at superior accuracy. Four-base DMS probing experiments are straightforward to perform and will broadly facilitate improved RNA structural analysis in living cells.

Mutation signature filtering enables high-fidelity RNA structure probing at all four nucleobases with DMS.

Chemical probing experiments have transformed RNA structure analysis, enabling high-throughput measurement of base-pairing in living cells. Dimethyl sulfate (DMS) is one of the most widely used structure probing reagents and has played a prominent role in enabling next-generation single-molecule probing analyses. However, DMS has traditionally only been able to probe adenine and cytosine nucleobases. We previously showed that, using appropriate conditions, DMS can also be used to interrogate base-pairing of uracil and guanines in vitro at reduced accuracy. However, DMS remained unable to informatively probe guanines in cells. Here, we develop an improved DMS mutational profiling (MaP) strategy that leverages the unique mutational signature of N 1 -methylguanine DMS modifications to enable robust, high-fidelity structure probing at all four nucleotides, including in cells. Using information theory, we show that four-base DMS reactivities convey greater structural information than comparable two-base DMS and SHAPE probing strategies. Four-base DMS experiments further enable improved direct base-pair detection by single-molecule PAIR analysis, and ultimately support RNA structure modeling at superior accuracy. Four-base DMS probing experiments are easily performed and will broadly facilitate improved RNA structural analysis in living cells.

Single-Molecule Correlated Chemical Probing: A Revolution in RNA Structure Analysis.

RNA molecules convey biological information both in their linear sequence and in their base-paired secondary and tertiary structures. Chemical probing experiments, which involve treating an RNA with a reagent that modifies conformationally dynamic nucleotides, have broadly enabled examination of short- and long-range RNA structure in diverse contexts, including in living cells. For decades, chemical probing experiments have been interpreted in a per-nucleotide way, such that the reactivity measured at each nucleotide reports the average structure at a position over all RNA molecules within a sample. However, there are numerous important cases where per-nucleotide chemical probing falls short, including for RNAs that are bound by proteins, RNAs that form complex higher order structures, and RNAs that sample multiple conformations.Recent experimental and computational innovations have started a revolution in RNA structure analysis by transforming chemical probing into a massively parallel, single-molecule experiment. Enabled by a specialized reverse transcription strategy called mutational profiling (MaP), multiple chemical modification events can be measured within individual RNA molecules. Nucleotides that communicate structurally through direct base pairing or large-scale folding-unfolding transitions will react with chemical probes in a correlated manner, thereby revealing structural complexity hidden to conventional approaches. These single-molecule correlated chemical probing (smCCP) experiments can be interpreted to directly identify nucleotides that base pair (the PAIR-MaP strategy) and to reveal long-range, through-space structural communication (RING-MaP). Correlated probing can also define the thermodynamic populations of complex RNA ensembles (DANCE-MaP). Complex RNA-protein networks can be interrogated by cross-linking proteins to RNA and measuring correlations between cross-linked positions (RNP-MaP).smCCP thus visualizes RNA secondary and higher-order structure with unprecedented accuracy, defining novel structures, RNA-protein interaction networks, time-resolved dynamics, and allosteric structural switches. These strategies are not mutually exclusive; in favorable cases, multiple levels of RNA structure ─ base pairing, through-space structural communication, and equilibrium ensembles ─ can be resolved concurrently. The physical experimentation required for smCCP is profoundly simple, and experiments are readily performed in cells on RNAs of any size, including large noncoding RNAs and mRNAs. Single-molecule correlated chemical probing is paving the way for a new generation of biophysical studies on RNA in living systems.

Global 5'-UTR RNA structure regulates translation of a SERPINA1 mRNA.

SERPINA1 mRNAs encode the protease inhibitor α-1-antitrypsin and are regulated through post-transcriptional mechanisms. α-1-antitrypsin deficiency leads to chronic obstructive pulmonary disease (COPD) and liver cirrhosis, and specific variants in the 5'-untranslated region (5'-UTR) are associated with COPD. The NM_000295.4 transcript is well expressed and translated in lung and blood and features an extended 5'-UTR that does not contain a competing upstream open reading frame (uORF). We show that the 5'-UTR of NM_000295.4 folds into a well-defined multi-helix structural domain. We systematically destabilized mRNA structure across the NM_000295.4 5'-UTR, and measured changes in (SHAPE quantified) RNA structure and cap-dependent translation relative to a native-sequence reporter. Surprisingly, despite destabilizing local RNA structure, most mutations either had no effect on or decreased translation. Most structure-destabilizing mutations retained native, global 5'-UTR structure. However, those mutations that disrupted the helix that anchors the 5'-UTR domain yielded three groups of non-native structures. Two of these non-native structure groups refolded to create a stable helix near the translation initiation site that decreases translation. Thus, in contrast to the conventional model that RNA structure in 5'-UTRs primarily inhibits translation, complex folding of the NM_000295.4 5'-UTR creates a translation-optimized message by promoting accessibility at the translation initiation site.

Quantitative prediction of variant effects on alternative splicing in MAPT using endogenous pre-messenger RNA structure probing.

Splicing is highly regulated and is modulated by numerous factors. Quantitative predictions for how a mutation will affect precursor mRNA (pre-mRNA) structure and downstream function are particularly challenging. Here, we use a novel chemical probing strategy to visualize endogenous precursor and mature MAPT mRNA structures in cells. We used these data to estimate Boltzmann suboptimal structural ensembles, which were then analyzed to predict consequences of mutations on pre-mRNA structure. Further analysis of recent cryo-EM structures of the spliceosome at different stages of the splicing cycle revealed that the footprint of the Bact complex with pre-mRNA best predicted alternative splicing outcomes for exon 10 inclusion of the alternatively spliced MAPT gene, achieving 74% accuracy. We further developed a ß-regression weighting framework that incorporates splice site strength, RNA structure, and exonic/intronic splicing regulatory elements capable of predicting, with 90% accuracy, the effects of 47 known and 6 newly discovered mutations on inclusion of exon 10 of MAPT. This combined experimental and computational framework represents a path forward for accurate prediction of splicing-related disease-causing variants.

Discovery of a large-scale, cell-state-responsive allosteric switch in the 7SK RNA using DANCE-MaP.

7SK is a conserved noncoding RNA that regulates transcription by sequestering the transcription factor P-TEFb. 7SK function entails complex changes in RNA structure, but characterizing RNA dynamics in cells remains an unsolved challenge. We developed a single-molecule chemical probing strategy, DANCE-MaP (deconvolution and annotation of ribonucleic conformational ensembles), that defines per-nucleotide reactivity, direct base pairing interactions, tertiary interactions, and thermodynamic populations for each state in RNA structural ensembles from a single experiment. DANCE-MaP reveals that 7SK RNA encodes a large-scale structural switch that couples dissolution of the P-TEFb binding site to structural remodeling at distal release factor binding sites. The 7SK structural equilibrium shifts in response to cell growth and stress and can be targeted to modulate expression of P-TEFbresponsive genes. Our study reveals that RNA structural dynamics underlie 7SK function as an integrator of diverse cellular signals to control transcription and establishes the power of DANCE-MaP to define RNA dynamics in cells.

Analysis of RNA-protein networks with RNP-MaP defines functional hubs on RNA.

RNA-protein interaction networks govern many biological processes but are difficult to examine comprehensively. We devised ribonucleoprotein networks analyzed by mutational profiling (RNP-MaP), a live-cell chemical probing strategy that maps cooperative interactions among multiple proteins bound to single RNA molecules at nucleotide resolution. RNP-MaP uses a hetero-bifunctional crosslinker to freeze interacting proteins in place on RNA and then maps multiple bound proteins on single RNA strands by read-through reverse transcription and DNA sequencing. RNP-MaP revealed that RNase P and RMRP, two sequence-divergent but structurally related non-coding RNAs, share RNP networks and that network hubs define functional sites in these RNAs. RNP-MaP also identified protein interaction networks conserved between mouse and human XIST long non-coding RNAs and defined protein communities whose binding sites colocalize and form networks in functional regions of XIST. RNP-MaP enables discovery and efficient validation of functional protein interaction networks on long RNAs in living cells.

Natural Selection Shapes Codon Usage in the Human Genome.

Synonymous codon usage has been identified as a determinant of translational efficiency and mRNA stability in model organisms and human cell lines. However, whether natural selection shapes human codon content to optimize translation efficiency is unclear. Furthermore, aside from those that affect splicing, synonymous mutations are typically ignored as potential contributors to disease. Using genetic sequencing data from nearly 200,000 individuals, we uncover clear evidence that natural selection optimizes codon content in the human genome. In deriving intolerance metrics to quantify gene-level constraint on synonymous variation, we discover that dosage-sensitive genes, DNA-damage-response genes, and cell-cycle-regulated genes are particularly intolerant to synonymous variation. Notably, we illustrate that reductions in codon optimality in BRCA1 can attenuate its function. Our results reveal that synonymous mutations most likely play an underappreciated role in human variation.

RNA base-pairing complexity in living cells visualized by correlated chemical probing.

RNA structure and dynamics are critical to biological function. However, strategies for determining RNA structure in vivo are limited, with established chemical probing and newer duplex detection methods each having deficiencies. Here we convert the common reagent dimethyl sulfate into a useful probe of all 4 RNA nucleotides. Building on this advance, we introduce PAIR-MaP, which uses single-molecule correlated chemical probing to directly detect base-pairing interactions in cells. PAIR-MaP has superior resolution compared to alternative experiments, can resolve multiple sets of pairing interactions for structurally dynamic RNAs, and enables highly accurate structure modeling, including of RNAs containing multiple pseudoknots and extensively bound by proteins. Application of PAIR-MaP to human RNase MRP and 2 bacterial messenger RNA 5' untranslated regions reveals functionally important and complex structures undetected by prior analyses. PAIR-MaP is a powerful, experimentally concise, and broadly applicable strategy for directly visualizing RNA base pairs and dynamics in cells.

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.

An RNA structure-mediated, posttranscriptional model of human α-1-antitrypsin expression.

Chronic obstructive pulmonary disease (COPD) affects over 65 million individuals worldwide, where α-1-antitrypsin deficiency is a major genetic cause of the disease. The α-1-antitrypsin gene, SERPINA1, expresses an exceptional number of mRNA isoforms generated entirely by alternative splicing in the 5'-untranslated region (5'-UTR). Although all SERPINA1 mRNAs encode exactly the same protein, expression levels of the individual mRNAs vary substantially in different human tissues. We hypothesize that these transcripts behave unequally due to a posttranscriptional regulatory program governed by their distinct 5'-UTRs and that this regulation ultimately determines α-1-antitrypsin expression. Using whole-transcript selective 2'-hydroxyl acylation by primer extension (SHAPE) chemical probing, we show that splicing yields distinct local 5'-UTR secondary structures in SERPINA1 transcripts. Splicing in the 5'-UTR also changes the inclusion of long upstream ORFs (uORFs). We demonstrate that disrupting the uORFs results in markedly increased translation efficiencies in luciferase reporter assays. These uORF-dependent changes suggest that α-1-antitrypsin protein expression levels are controlled at the posttranscriptional level. A leaky-scanning model of translation based on Kozak translation initiation sequences alone does not adequately explain our quantitative expression data. However, when we incorporate the experimentally derived RNA structure data, the model accurately predicts translation efficiencies in reporter assays and improves α-1-antitrypsin expression prediction in primary human tissues. Our results reveal that RNA structure governs a complex posttranscriptional regulatory program of α-1-antitrypsin expression. Crucially, these findings describe a mechanism by which genetic alterations in noncoding gene regions may result in α-1-antitrypsin deficiency.

Tuning RNA folding and function through rational design of junction topology.

Structured RNAs such as ribozymes must fold into specific 3D structures to carry out their biological functions. While it is well-known that architectural features such as flexible junctions between helices help guide RNA tertiary folding, the mechanisms through which junctions influence folding remain poorly understood. We combine computational modeling with single molecule Förster resonance energy transfer (smFRET) and catalytic activity measurements to investigate the influence of junction design on the folding and function of the hairpin ribozyme. Coarse-grained simulations of a wide range of junction topologies indicate that differences in sterics and connectivity, independent of stacking, significantly affect tertiary folding and appear to largely explain previously observed variations in hairpin ribozyme stability. We further use our simulations to identify stabilizing modifications of non-optimal junction topologies, and experimentally validate that a three-way junction variant of the hairpin ribozyme can be stabilized by specific insertion of a short single-stranded linker. Combined, our multi-disciplinary study further reinforces that junction sterics and connectivity are important determinants of RNA folding, and demonstrates the potential of coarse-grained simulations as a tool for rationally tuning and optimizing RNA folding and function.

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.

Direct Duplex Detection: An Emerging Tool in the RNA Structure Analysis Toolbox.

While a variety of powerful tools exists for analyzing RNA structure, identifying long-range and intermolecular base-pairing interactions has remained challenging. Recently, three groups introduced a high-throughput strategy that uses psoralen-mediated crosslinking to directly identify RNA-RNA duplexes in cells. Initial application of these methods highlights the preponderance of long-range structures within and between RNA molecules and their widespread structural dynamics.

Secondary structure encodes a cooperative tertiary folding funnel in the Azoarcus ribozyme.

A requirement for specific RNA folding is that the free-energy landscape discriminate against non-native folds. While tertiary interactions are critical for stabilizing the native fold, they are relatively non-specific, suggesting additional mechanisms contribute to tertiary folding specificity. In this study, we use coarse-grained molecular dynamics simulations to explore how secondary structure shapes the tertiary free-energy landscape of the Azoarcus ribozyme. We show that steric and connectivity constraints posed by secondary structure strongly limit the accessible conformational space of the ribozyme, and that these so-called topological constraints in turn pose strong free-energy penalties on forming different tertiary contacts. Notably, native A-minor and base-triple interactions form with low conformational free energy, while non-native tetraloop/tetraloop-receptor interactions are penalized by high conformational free energies. Topological constraints also give rise to strong cooperativity between distal tertiary interactions, quantitatively matching prior experimental measurements. The specificity of the folding landscape is further enhanced as tertiary contacts place additional constraints on the conformational space, progressively funneling the molecule to the native state. These results indicate that secondary structure assists the ribozyme in navigating the otherwise rugged tertiary folding landscape, and further emphasize topological constraints as a key force in RNA folding.

Noncanonical secondary structure stabilizes mitochondrial tRNA(Ser(UCN)) by reducing the entropic cost of tertiary folding.

Mammalian mitochondrial tRNA(Ser(UCN)) (mt-tRNA(Ser)) and pyrrolysine tRNA (tRNA(Pyl)) fold to near-canonical three-dimensional structures despite having noncanonical secondary structures with shortened interhelical loops that disrupt the conserved tRNA tertiary interaction network. How these noncanonical tRNAs compensate for their loss of tertiary interactions remains unclear. Furthermore, in human mt-tRNA(Ser), lengthening the variable loop by the 7472insC mutation reduces mt-tRNA(Ser) concentration in vivo through poorly understood mechanisms and is strongly associated with diseases such as deafness and epilepsy. Using simulations of the TOPRNA coarse-grained model, we show that increased topological constraints encoded by the unique secondary structure of wild-type mt-tRNA(Ser) decrease the entropic cost of folding by ∼2.5 kcal/mol compared to canonical tRNA, offsetting its loss of tertiary interactions. Further simulations show that the pathogenic 7472insC mutation disrupts topological constraints and hence destabilizes the mutant mt-tRNA(Ser) by ∼0.6 kcal/mol relative to wild-type. UV melting experiments confirm that insertion mutations lower mt-tRNA(Ser) melting temperature by 6-9 °C and increase the folding free energy by 0.8-1.7 kcal/mol in a largely sequence- and salt-independent manner, in quantitative agreement with our simulation predictions. Our results show that topological constraints provide a quantitative framework for describing key aspects of RNA folding behavior and also provide the first evidence of a pathogenic mutation that is due to disruption of topological constraints.