RNAvigate: efficient exploration of RNA chemical probing datasets.

Chemical probing technologies enable high-throughput examination of diverse structural features of RNA, including local nucleotide flexibility, RNA secondary structure, protein and ligand binding, through-space interaction networks, and multistate structural ensembles. Deep understanding of RNA structure-function relationships typically requires evaluating a system under structure- and function-altering conditions, linking these data with additional information, and visualizing multilayered relationships. Current platforms lack the broad accessibility, flexibility and efficiency needed to iterate on integrative analyses of these diverse, complex data. Here, we share the RNA visualization and graphical analysis toolset RNAvigate, a straightforward and flexible Python library that automatically parses 21 standard file formats (primary sequence annotations, per- and internucleotide data, and secondary and tertiary structures) and outputs 18 plot types. RNAvigate enables efficient exploration of nuanced relationships between multiple layers of RNA structure information and across multiple experimental conditions. Compatibility with Jupyter notebooks enables nonburdensome, reproducible, transparent and organized sharing of multistep analyses and data visualization strategies. RNAvigate simplifies and accelerates discovery and characterization of RNA-centric functions in biology.

Voices: Challenges and opportunities in RNA biology.

In the first of many thematic issues marking the 30th anniversary of Cell Chemical Biology, we highlight the contribution of chemical biology to RNA biology in a special issue on RNA modulation. We asked several leaders in the field to share their opinions on the current challenges and opportunities in RNA biology.

Pervasive downstream RNA hairpins dynamically dictate start-codon selection.

Translational reprogramming allows organisms to adapt to changing conditions. Upstream start codons (uAUGs), which are prevalently present in mRNAs, have crucial roles in regulating translation by providing alternative translation start sites1-4. However, what determines this selective initiation of translation between conditions remains unclear. Here, by integrating transcriptome-wide translational and structural analyses during pattern-triggered immunity in Arabidopsis, we found that transcripts with immune-induced translation are enriched with upstream open reading frames (uORFs). Without infection, these uORFs are selectively translated owing to hairpins immediately downstream of uAUGs, presumably by slowing and engaging the scanning preinitiation complex. Modelling using deep learning provides unbiased support for these recognizable double-stranded RNA structures downstream of uAUGs (which we term uAUG-ds) being responsible for the selective translation of uAUGs, and allows the prediction and rational design of translating uAUG-ds. We found that uAUG-ds-mediated regulation can be generalized to human cells. Moreover, uAUG-ds-mediated start-codon selection is dynamically regulated. After immune challenge in plants, induced RNA helicases that are homologous to Ded1p in yeast and DDX3X in humans resolve these structures, allowing ribosomes to bypass uAUGs to translate downstream defence proteins. This study shows that mRNA structures dynamically regulate start-codon selection. The prevalence of this RNA structural feature and the conservation of RNA helicases across kingdoms suggest that mRNA structural remodelling is a general feature of translational reprogramming.

RNAvigate: Efficient exploration of RNA chemical probing datasets.

Chemical probing technologies enable high-throughput examination of diverse structural features of RNA including local nucleotide flexibility, RNA secondary structure, protein- and ligand-binding, through-space interaction networks, and multi-state structural ensembles. Performing these experiments, by themselves, does not directly lead to biological insight. Instead, deep understanding of RNA structure-function relationships typically requires evaluating a system under structure- and function-altering conditions, linking these data with additional information, and visualizing multi-layered relationships. Current platforms lack the broad accessibility, flexibility, and efficiency needed to iterate on integrative analyses of these diverse, complex data. Here, we share the RNA visualization and graphical analysis toolset RNAvigate, a straightforward and flexible Python library. RNAvigate currently automatically parses twenty-one standard file formats (primary sequence annotations, per- and internucleotide data, and secondary and tertiary structures) and outputs eighteen plot types. These features enable efficient exploration of nuanced relationships between chemical probing data, RNA structure, and motif annotations across multiple experimental samples. Compatibility with Jupyter Notebooks enables non-burdensome, reproducible, transparent and organized sharing of multi-step analyses and data visualization strategies. RNAvigate simplifies examination of multi-layered RNA structure information and accelerates discovery and characterization of RNA-centric functions in biology.

Structure-first identification of RNA elements that regulate dengue virus genome architecture and replication.

The genomes of RNA viruses encode the information required for replication in host cells both in their linear sequence and in complex higher-order structures. A subset of these RNA genome structures show clear sequence conservation, and have been extensively described for well-characterized viruses. However, the extent to which viral RNA genomes contain functional structural elements-unable to be detected by sequence alone-that nonetheless are critical to viral fitness is largely unknown. Here, we devise a structure-first experimental strategy and use it to identify 22 structure-similar motifs across the coding sequences of the RNA genomes for the four dengue virus serotypes. At least 10 of these motifs modulate viral fitness, revealing a significant unnoticed extent of RNA structure-mediated regulation within viral coding sequences. These viral RNA structures promote a compact global genome architecture, interact with proteins, and regulate the viral replication cycle. These motifs are also thus constrained at the levels of both RNA structure and protein sequence and are potential resistance-refractory targets for antivirals and live-attenuated vaccines. Structure-first identification of conserved RNA structure enables efficient discovery of pervasive RNA-mediated regulation in viral genomes and, likely, other cellular RNAs.

Innovations in targeting RNA by fragment-based ligand discovery.

A subset of functional regions within large RNAs fold into complex structures able to bind small-molecule ligands with high affinity and specificity. Fragment-based ligand discovery (FBLD) offers notable opportunities for discovery and design of potent small molecules that bind pockets in RNA. Here we share an integrated analysis of recent innovations in FBLD, emphasizing opportunities resulting from fragment elaboration via both linking and growing. Analysis of elaborated fragments emphasizes that high-quality interactions form with complex tertiary structures in RNA. FBLD-inspired small molecules have been shown to modulate RNA functions by competitively inhibiting protein binding and by selectively stabilizing dynamic RNA states. FBLD is creating a foundation to interrogate the relatively unknown structural space for RNA ligands and for discovery of RNA-targeted therapeutics.

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.

Double-stranded RNA drives SARS-CoV-2 nucleocapsid protein to undergo phase separation at specific temperatures.

Nucleocapsid protein (N-protein) is required for multiple steps in betacoronaviruses replication. SARS-CoV-2-N-protein condenses with specific viral RNAs at particular temperatures making it a powerful model for deciphering RNA sequence specificity in condensates. We identify two separate and distinct double-stranded, RNA motifs (dsRNA stickers) that promote N-protein condensation. These dsRNA stickers are separately recognized by N-protein's two RNA binding domains (RBDs). RBD1 prefers structured RNA with sequences like the transcription-regulatory sequence (TRS). RBD2 prefers long stretches of dsRNA, independent of sequence. Thus, the two N-protein RBDs interact with distinct dsRNA stickers, and these interactions impart specific droplet physical properties that could support varied viral functions. Specifically, we find that addition of dsRNA lowers the condensation temperature dependent on RBD2 interactions and tunes translational repression. In contrast RBD1 sites are sequences critical for sub-genomic (sg) RNA generation and promote gRNA compression. The density of RBD1 binding motifs in proximity to TRS-L/B sequences is associated with levels of sub-genomic RNA generation. The switch to packaging is likely mediated by RBD1 interactions which generate particles that recapitulate the packaging unit of the virion. Thus, SARS-CoV-2 can achieve biochemical complexity, performing multiple functions in the same cytoplasm, with minimal protein components based on utilizing multiple distinct RNA motifs that control N-protein interactions.

RNA-Ligand Interactions Quantified by Surface Plasmon Resonance with Reference Subtraction.

Structured RNAs bind ligands and are attractive targets for small-molecule drugs. A wide variety of analytical methods have been used to characterize RNA-ligand interactions, but our experience is that most have significant limitations in terms of material requirements and applicability to complex RNAs. Surface plasmon resonance (SPR) potentially overcomes these limitations, but we find that the standard experimental framework measures notable nonspecific electrostatic-mediated interactions, frustrating analysis of weak RNA binders. SPR measurements are typically quantified relative to a non-target reference channel. Here, we show that referencing to a channel containing a non-binding control RNA enables subtraction of nonspecific binding contributions, allowing measurements of accurate and specific binding affinities. We validated this approach for small-molecule binders of two riboswitch RNAs with affinities ranging from nanomolar to millimolar, including low-molecular-mass fragment ligands. SPR implemented with reference subtraction reliably discriminates specific from nonspecific binding, uses RNA and ligand material efficiently, and enables rapid exploration of the ligand-binding landscape for RNA targets.

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.

SHAPE-enabled fragment-based ligand discovery for RNA.

The transcriptome represents an attractive but underused set of targets for small-molecule ligands. Here, we devise a technology that leverages fragment-based screening and SHAPE-MaP RNA structure probing to discover small-molecule fragments that bind an RNA structure of interest. We identified fragments and cooperatively binding fragment pairs that bind to the thiamine pyrophosphate (TPP) riboswitch with millimolar to micromolar affinities. We then used structure-activity relationship information to efficiently design a linked-fragment ligand, with no resemblance to the native ligand, with high ligand efficiency and druglikeness, that binds to the TPP thiM riboswitch with high nanomolar affinity and that modulates RNA conformation during cotranscriptional folding. Principles from this work are broadly applicable, leveraging cooperativity and multisite binding, for developing high-quality ligands for diverse RNA targets.

Direct detection of RNA modifications and structure using single-molecule nanopore sequencing.

Modifications are present on many classes of RNA, including tRNA, rRNA, and mRNA. These modifications modulate diverse biological processes such as genetic recoding and mRNA export and folding. In addition, modifications can be introduced to RNA molecules using chemical probing strategies that reveal RNA structure and dynamics. Many methods exist to detect RNA modifications by short-read sequencing; however, limitations on read length inherent to short-read-based methods dissociate modifications from their native context, preventing single-molecule modification analysis. Here, we demonstrate direct RNA nanopore sequencing to detect endogenous and exogenous RNA modifications on long RNAs at the single-molecule level. We detect endogenous 2'-O-methyl and base modifications across E. coli and S. cerevisiae ribosomal RNAs as shifts in current signal and dwell times distally through interactions with the helicase motor protein. We further use the 2'-hydroxyl reactive SHAPE reagent acetylimidazole to probe RNA structure at the single-molecule level with readout by direct nanopore sequencing.

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.

Distinct MUNC lncRNA structural domains regulate transcription of different promyogenic factors.

Many lncRNAs have been discovered using transcriptomic data; however, it is unclear what fraction of lncRNAs is functional and what structural properties affect their phenotype. MUNC lncRNA (also known as DRReRNA) acts as an enhancer RNA for the Myod1 gene in cis and stimulates the expression of other promyogenic genes in trans by recruiting the cohesin complex. Here, experimental probing of the RNA structure revealed that MUNC contains multiple structural domains not detected by prediction algorithms in the absence of experimental information. We show that these specific and structurally distinct domains are required for induction of promyogenic genes, for binding genomic sites and gene expression regulation, and for binding the cohesin complex. Myod1 induction and cohesin interaction comprise only a subset of MUNC phenotype. Our study reveals unexpectedly complex, structure-driven functions for the MUNC lncRNA and emphasizes the importance of experimentally determined structures for understanding structure-function relationships in lncRNAs.

Subsite Ligand Recognition and Cooperativity in the TPP Riboswitch: Implications for Fragment-Linking in RNA Ligand Discovery.

RNA molecules can show high levels of cooperativity in their global folding and interactions with divalent ions. However, cooperativity at individual ligand-RNA interaction sites remains poorly understood. Here, we investigated the binding of thiamine and methylene diphosphonic acid (MDP, a soluble structural analogue of pyrophosphate) to the thiamine pyrophosphate riboswitch. These ligands each bind weakly at proximal subsites, with 10 µM and 1 mM affinities, respectively. The affinity of MDP moderately improves when thiamine or thiamine-like fragments are pre-bound to the RNA. Covalent linking of thiamine and MDP substantially increases riboswitch binding to a notable high affinity of 20 nM. Crystal structures and single-molecule correlated chemical probing revealed favorable induced fit effects upon binding of individual ligands and, unexpectedly, a substantial thermodynamically unfavorable RNA structural rearrangement upon binding of the linked thiamine-MDP ligand. Thus, linking of two ligands of modest affinity, accompanied by an unfavorable structural rearrangement, still yields a potent linked RNA-binding compound. Since complex ligands often bind riboswitches and other RNAs at proximal subsites, principles derived from this work inform and support fragment-linking strategies for identifying small molecules that interact with RNA specifically and with high affinity.

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.