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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.

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.

To survive stress, eukaryotes selectively translate stress-related transcripts while inhibiting growth-associated protein production. How this translational reprogramming occurs under biotic stress has not been systematically studied. To identify common features shared by transcripts with stress-upregulated translation efficiency (TE-up), we first performed high-resolution ribosome-sequencing inArabidopsisduring pattern-triggered immunity and found that TE-up transcripts are enriched with upstream open reading frames (uORFs). Under non-stress conditions, start codons of these uORFs (uAUGs) have higher-than-background ribosomal association. Upon immune induction, there is an overall downshift in ribosome occupancy at uAUGs, accompanied by enhanced translation of main ORFs (mORFs). Usingin plantanucleotide-resolution mRNA structurome probing, we discovered that this stress-induced switch in translation is mediated by highly structured regions detected downstream of uAUGs in TE-up transcripts. Without stress, these structures are responsible for uORF-mediated inhibition of mORF translation by slowing progression of the translation preinitiation complex to initiate translation from uAUGs, instead of mAUGs. In response to immune induction, uORF-inhibition is alleviated by three Ded1p/DDX3X-homologous RNA helicases which unwind the RNA structures, allowing ribosomes to bypass the inhibitory uORFs and upregulate defence protein production. Conservation of the RNA helicases suggests that mRNA structurome remodelling is a general mechanism for stress-induced translation across kingdoms.

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. These layers of RNA structural information are often most incisive for understanding RNA structure-function relationships when combined with each other and when evaluated under structure- and function-altering conditions. Analysis of these complex data has required, often time consuming and awkward, juggling of multiple intermediate data files and software to create visualizations that support RNA-centered hypotheses. Here, we present the RNA visualization and graphical analysis toolset RNAvigate, developed as an easy-to-use and flexible Python library. RNAvigate currently integrates seven chemical probing data formats, nine secondary and tertiary structure formats, and eleven plot types. These features enable efficient exploration of nuanced relationships between chemical probing data, RNA structures, and motif annotations across multiple experimental samples. Modularity supports integration of new data types and plotting features. Compatibility with Jupyter Notebooks facilitates reproducibility and organization of multistep analyses and makes RNAvigate an ideal, time-effective, and non-burdensome platform for sharing full analysis pipelines. RNAvigate streamlines implementation of chemical probing strategies and accelerates discovery and characterization of diverse RNA-centric functions in biology.

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.

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.

The genomes of RNA viruses encode the information required for replication in host cells in both their linear sequence and in complex higher-order structures. A subset of these complex functional RNA genome structures show clear sequence conservation. However, the extent to which viral RNA genomes contain conserved structural elements – that cannot be detected by sequence alone – that nonetheless are critical to viral fitness is largely unknown. Here, we take a structure-first approach to identify motifs conserved across the coding sequences of the RNA genomes for the four dengue virus (DENV) serotypes. We used SHAPE-MaP to identify 22 candidate motifs with conserved RNA structures, but no prior association with viral replication. At least ten of these motifs are important for viral fitness, revealing a significant unnoticed extent of RNA structure-mediated regulation within viral coding sequences. These conserved viral RNA structures promote a compact global genome architecture, interact with proteins, and regulate the viral replication cycle. These motifs are 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 is poised to guide efficient discovery of RNA-mediated regulation in viral genomes and other cellular RNAs.

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.

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.

7SK is a conserved non-coding 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-TEFb responsive 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.

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'

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.

Summary7SK is a highly conserved non-coding RNA that regulates eukaryotic transcription by sequestering positive transcription elongation factor b (P-TEFb). 7SK regulatory function likely entails changes in RNA structure, but characterizing dynamic RNA-protein complexes in cells has remained an unsolved challenge. We describe a new chemical probing strategy (DANCE-MaP) that uses maximum likelihood deconvolution and probabilistic read assignment to define simultaneously (i) per-nucleotide reactivity profiles, (ii) direct base pairing interactions, and (iii) tertiary and higher-order interactions for each conformation of multi-state RNA structural ensembles, all from a single experiment. We show that human 7SK RNA, despite significant heterogeneity, intrinsically codes for 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 is regulated by cell type, shifts dynamically in response to cell growth and stress, and can be exogenously targeted to modulate transcription in cells. Our data support that the 7SK structural ensemble functions as an integrator of diverse cellular signals to control transcription elongation in environment and cell specific ways, and establishes DANCE-MaP as a powerful strategy for comprehensively defining RNA structure and dynamics in cells.

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

RNA molecules adopt three-dimensional structures that are critical to their function and of interest in drug discovery. Few RNA structures are known, however, and predicting them computationally has proven challenging. We introduce a machine learning approach that enables identification of accurate structural models without assumptions about their defining characteristics, despite being trained with only 18 known RNA structures. The resulting scoring function, the Atomic Rotationally Equivariant Scorer (ARES), substantially outperforms previous methods and consistently produces the best results in community-wide blind RNA structure prediction challenges. By learning effectively even from a small amount of data, our approach overcomes a major limitation of standard deep neural networks. Because it uses only atomic coordinates as inputs and incorporates no RNA-specific information, this approach is applicable to diverse problems in structural biology, chemistry, materials science, and beyond.

SummaryMany lncRNAs have been discovered using transcriptomic data, however, it is broadly unclear what fraction of lncRNAs are functional and what structural properties affect their phenotype. MUNC lncRNA, also known as DRReRNA, stimulates skeletal muscle differentiation. The prevailing hypothesis is that MUNC stimulates the Myod1 gene in cis as an enhancer RNA and stimulates expression of several other promyogenic genes in trans by recruiting the cohesin complex to their promoters. Experimental probing of the RNA structure revealed that MUNC contains multiple structural domains not detected by RNA structure prediction algorithms in the absence of experimental information. We discovered that these specific and structurally distinct domains are required for induction of different promyogenic genes, for binding at different genomic sites to regulate the expression of adjacent genes, and for binding the cohesin complex. Moreover, we found that induction of Myod1 or interaction with cohesin comprise only a subset of the broad regulatory impact of this lncRNA. Our study thus 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.

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

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.

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., Author summary In principle, crosslinking represents a simple and elegant way to measure important features of RNA structure. Crosslinking-derived, close-in-space structural information can be highly useful for modeling complex higher-order RNA structure and for generating hypotheses regarding how an RNA functions. In practice, extracting the information from an RNA crosslinking experiment, rigorously and at nucleotide resolution, has been difficult and imprecise. This work outlines the development and optimization of an analysis pipeline, called ShapeJumper, that substantially facilitates analysis of RNA crosslinking experiments, based on easily implemented JuMP technology. Both the crosslinking experiment and the analysis software described here are readily implemented by non-expert users.

Chemical probing experiments, coupled with empirically determined free energy change relationships, can enable accurate modeling of the secondary structures of diverse and complex RNAs. A current frontier lies in modeling large and structurally heterogeneous transcripts, including complex eukaryotic RNAs. To validate and improve on experimentally driven approaches for modeling large transcripts, we obtained high-quality SHAPE data for the protein-free human 18S and 28S ribosomal RNAs (rRNAs). To our surprise, SHAPE-directed structure models for the human rRNAs poorly matched accepted structures. Analysis of predicted rRNA structures based on low-SHAPE and low-entropy (lowSS) metrics revealed that, whereas ∼75% of Escherichia coli rRNA sequences form well-determined lowSS secondary structure, only ∼40% of the human rRNAs do. Critically, regions of the human rRNAs that specifically fold into well-determined lowSS structures were modeled to high accuracy using SHAPE data. This work reveals that eukaryotic rRNAs are more unfolded than are those of prokaryotic rRNAs and indeed are largely unfolded overall, likely reflecting increased protein dependence for eukaryotic ribosome structure. In addition, those regions and substructures that are well-determined can be identified de novo and successfully modeled by SHAPE-directed folding.

Chemical probing is an important tool for characterizing the complex folded structures of RNA molecules, many of which play key cellular roles. Electrophilic SHAPE reagents create adducts at the 2'-hydroxyl position on the RNA backbone of flexible ribonucleotides with relatively little dependence on nucleotide identity. Strategies for adduct detection such as mutational profiling (MaP) allow accurate, automated calculation of relative adduct frequencies for each nucleotide in a given RNA or group of RNAs. A number of alternative reagents and adduct detection strategies have been proposed, especially for use in living cells. Here we evaluate five SHAPE reagents: three previously well-validated reagents 1M7 (1-methyl-7-nitroisatoic anhydride), 1M6 (1-methyl-6-nitroisatoic anhydride), and NMIA ( N-methylisatoic anhydride), one more recently proposed NAI (2-methylnicotinic acid imidazolide), and one novel reagent 5NIA (5-nitroisatoic anhydride). We clarify the importance of carefully designed software in reading out SHAPE experiments using massively parallel sequencing approaches. We examine SHAPE modification in living cells in diverse cell lines, compare MaP and reverse transcription-truncation as SHAPE adduct detection strategies, make recommendations for SHAPE reagent choice, and outline areas for future development.

Every class of RNA forms base-paired structures that impact biological functions. Chemical probing of RNA structure, especially with the advent of strategies such as SHAPE-MaP, vastly expands the scale and quantitative accuracy over which RNA structure can be examined. These methods have enabled large-scale structural studies of mRNAs and lncRNAs, but the length and complexity of these RNAs makes interpretation of the data challenging. We have created modules available through the open-source Integrative Genomics Viewer (IGV) for straightforward visualization of RNA structures and associated and complementary experimental data. Here we present detailed and stepwise strategies for exploring and visualizing complex RNA structures in IGV. Individuals can use these instructions and supplied sample data to become adept at using IGV to visualize RNA structure models in conjunction with useful allied information.

We report that the SARS-CoV-2 nucleocapsid protein (N-protein) undergoes liquid-liquid phase separation (LLPS) with viral RNA. N-protein condenses with specific RNA genomic elements under physiological buffer conditions and condensation is enhanced at human body temperatures (33°C and 37°C) and reduced at room temperature (22°C). RNA sequence and structure in specific genomic regions regulate N-protein condensation while other genomic regions promote condensate dissolution, potentially preventing aggregation of the large genome. At low concentrations, N-protein preferentially crosslinks to specific regions with single-stranded RNA flanked by structure and these features specify the location, number, and strength of N-protein binding sites (valency). Liquid-like N-protein condensates form in mammalian cells in a concentration-dependent manner and can be altered by small molecules. Condensation of N-protein is RNA sequence and structure specific, sensitive to human body temperature, and manipulatable with small molecules, and presents a screenable process for identifying antiviral compounds effective against SARS-CoV-2., Graphical Abstract, Highlights Phase separation occurs with the viral genome (gRNA) and at human body temperature. Phase separation is driven by specific elements in gRNA. RBD mutant N-protein fails to undergo LLPS; exhibits altered RNA crosslinking. N-protein forms liquid-like droplets in cells., Iserman and Roden et al. demonstrate phase separation (LLPS) of SARS-CoV-2 nucleocapsid (N-protein) with viral RNA. Viral RNA sequences promote or oppose phase separation depending on binding patterns of N-protein and genomic RNA. LLPS-promoting sequences occur at 5′ and 3′-Ends of the genome, suggestive of a genome packaging role.

A mechanistic understanding of the SARS-CoV-2 viral replication cycle is essential to develop new therapies for the COVID-19 global health crisis. In this study, we show that the SARS-CoV-2 nucleocapsid protein (N-protein) undergoes liquid-liquid phase separation (LLPS) with the viral genome, and propose a model of viral packaging through LLPS. N-protein condenses with specific RNA sequences in the first 1000 nts (5’-End) under physiological conditions and is enhanced at human upper airway temperatures. N-protein condensates exclude non-packaged RNA sequences. We comprehensively map sites bound by N-protein in the 5’-End and find preferences for single-stranded RNA flanked by stable structured elements. Liquid-like N-protein condensates form in mammalian cells in a concentration-dependent manner and can be altered by small molecules. Condensation of N-protein is sequence and structure specific, sensitive to human body temperature, and manipulatable with small molecules thus presenting screenable processes for identifying antiviral compounds effective against SARS-CoV-2.

Many methods exist to detect RNA modifications by short-read sequencing, relying on either antibody enrichment of transcripts bearing modified bases or mutational profiling approaches which require conversion to cDNA. Endogenous modifications are present on several major classes of RNA including tRNA, rRNA and mRNA and can modulate diverse biological processes such as genetic recoding, mRNA export and RNA folding. In addition, exogenous modifications can be introduced to RNA molecules to reveal RNA structure and dynamics. Limitations on read length and library size inherent in short-read-based methods dissociate modifications from their native context, preventing single molecule analysis and modification phasing. Here we demonstrate direct RNA nanopore sequencing to detect endogenous and exogenous RNA modifications over long sequence distance at the single molecule level. We demonstrate comprehensive detection of endogenous modifications in E. coli and S. cerevisiae ribosomal RNA (rRNA) using current signal deviations. Notably 2’-O-methyl (Nm) modifications generated a discernible shift in current signal and event level dwell times. We show that dwell times are mediated by the RNA motor protein which sits atop the nanopore. Further, we characterize a recently described small adduct-generating 2’-O-acylation reagent, acetylimidazole (AcIm) for exogenously labeling flexible nucleotides in RNA. Finally, we demonstrate the utility of AcIm for single molecule RNA structural probing using nanopore sequencing.Graphical abstract

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. Networks of proteins bound to single RNAs are identified by correlated chemical crosslinking.

We report that the SARS-CoV-2 nucleocapsid protein (N-protein) undergoes liquid-liquid phase separation (LLPS) with the viral genome and propose a model of viral packaging through LLPS. N-protein condenses with specific RNA sequences in the first 1000 nts (5'-End) under physiological conditions and condensation is enhanced at human body temperatures. Other regions of gRNA promote dissolution, counteracting aggregation of the large genome. This combination of elements ensures condensates of both specific molecular and physical identity, leading to exclusion of non-packaged RNA sequences. N-protein binds single-stranded RNA flanked by stable structured elements and these features specify the number and location of N-protein binding sites (valency). Liquid-like N-protein condensates form in mammalian cells in a concentration-dependent manner and can be altered by small molecules. Condensation of N-protein is sequence and structure specific, sensitive to human body temperature, and manipulatable with small molecules thus presenting screenable processes for identifying antiviral compounds effective against SARS-CoV-2.

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.

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.

The HIV-1 RNA genome contains complex structures with many structural elements playing regulatory roles during viral replication. A recent study has identified multiple RNA structures with unknown functions that are conserved among HIV-1 and two simian immunodeficiency viruses. To explore the roles of these conserved RNA structures, we introduced synonymous mutations into the HIV-1 genome to disrupt each structure. These mutants exhibited similar particle production, viral infectivity, and replication kinetics relative to the parent NL4-3 virus. However, when replicating in direct competition with the wild-type NL4-3 virus, mutations of RNA structures at inter-protein domain junctions can cause fitness defects. These findings reveal the ability of HIV-1 to tolerate changes in its sequences, even in apparently highly conserved structures, which permits high genetic diversity in HIV-1 population. Our results also suggest that some conserved RNA structures may function to fine-tune viral replication.

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.

The RNA genomes of viruses likely undergo multiple functionally important conformational changes during their replication cycles, changes that are poorly understood at present. We used two complementary in-solution RNA structure probing strategies (SHAPE-MaP and RING-MaP) to examine the structure of the RNA genome of satellite tobacco mosaic virus inside authentic virions and in a capsid-free state. Both RNA states feature similar three-domain architectures in which each major replicative function-translation, capsid coding, and genome synthesis-fall into distinct domains. There are, however, large conformational differences between the in-virion and capsid-free states, primarily in one arm of the central T domain. These data support a model in which the packaged capsid-bound RNA is constrained in a local high-energy conformation by the native capsid shell. The removal of the viral capsid then allows the RNA genome to relax into a more thermodynamically stable conformation. The RNA architecture of the central T domain thus likely changes during capsid assembly and disassembly and may play a role in genome packaging.

RNA viruses encode the information required to usurp cellular metabolism and gene regulation and to enable their own replication in two ways: in the linear sequence of their RNA genomes and in higher-order structures that form when the genomic RNA strand folds back on itself. Application of high-resolution SHAPE (selective 2′-hydroxyl acylation analyzed by primer extension) structure probing to viral RNA genomes has identified numerous new regulatory elements, defined new principles by which viral RNAs interact with the cellular host and evade host immune responses, and revealed relationships between virus evolution and RNA structure. This review summarizes our current understanding of genome structure-function interrelationships for RNA viruses, as informed by SHAPE structure probing, and outlines opportunities for future studies.

Understanding RNA-mediated functions requires a detailed characterization of the underlying RNA structure. In many cases, structure probing experiments are performed on RNA that has been "refolded" in some way, which may cause the conformation to differ from that of the native RNA. We used SHAPE-MaP (selective 2'-hydroxyl acylation analyzed by primer extension, read out by mutational profiling), to probe the structure of the Dengue virus (DENV) RNA genome after gentle extraction of the native RNA from intact virions (ex virion) and after heat denaturation and refolding. Comparison of mutiple SHAPE-informed structural features revealed that refolded RNA is more highly structured and samples fewer conformations than the ex virion RNA. Regions with similar structural features are generally those with low SHAPE reactivity and low Shannon entropy (lowSS regions), which correspond to elements with high levels of well-determined structure. This high-structure and low-entropy analysis framework, previously shown to make possible discovery of functional RNA structures, is thus now shown to allow de novo identification of structural elements in a refolded RNA that are likely to recapitulate RNA structures in the ex virion RNA state. Regions with less well-defined structures, which occurred more frequently in the more native-like ex virion RNA and may contain RNA switches, are challenging to recapitulate using refolded RNA.

Summary: Long non-coding RNAs (lncRNAs) are critical regulators of numerous physiological processes and diseases, especially cancers. However, development of lncRNA-based therapies is limited because the mechanisms of many lncRNAs are obscure, and interactions with functional partners, including proteins, remain uncharacterized. The lncRNA SLNCR1 binds to and regulates the androgen receptor (AR) to mediate melanoma invasion and proliferation in an androgen-independent manner. Here, we use biochemical analyses coupled with selective 2′-hydroxyl acylation analyzed by primer extension (SHAPE) RNA structure probing to show that the N-terminal domain of AR binds a pyrimidine-rich motif in an unstructured region of SLNCR1. This motif is predictive of AR binding, as we identify an AR-binding motif in lncRNA HOXA11-AS-203. Oligonucleotides that bind either the AR N-terminal domain or the AR RNA motif block the SLNCR1-AR interaction and reduce SLNCR1-mediated melanoma invasion. Delivery of oligos that block SLNCR1-AR interaction thus represent a plausible therapeutic strategy. : Androgen receptor (AR)-RNA complexes have been implicated in cancer, including melanoma. Schmidt et al. demonstrate that AR binds a single strand sequence in the long non-coding RNA (lncRNA) SLNCR. Point mutations or oligonucleotides that abrogate AR binding to SLNCR block melanoma invasion, suggesting that targeting lncRNA-protein complexes holds therapeutic promise. Keywords: long non-coding RNA, hormone receptor, androgen receptor, HOXA11AS, LINC00673, antisense oligos, melanoma, invasion, RNA scaffold, SHAPE

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RNA virus genomes are efficient and compact carriers of biological information, encoding information required for replication both in their primary sequences and in higher-order RNA structures. However, the ubiquity of RNA elements with higher-order folds—in which helices pack together to form complex 3D structures—and the extent to which these elements affect viral fitness are largely unknown. Here we used single-molecule correlated chemical probing to define secondary and tertiary structures across the RNA genome of dengue virus serotype 2 (DENV2). Higher-order RNA structures are pervasive and involve more than one-third of nucleotides in the DENV2 genomic RNA. These 3D structures promote a compact overall architecture and contribute to viral fitness. Disrupting RNA regions with higher-order structures leads to stable, nonreverting mutants and could guide the development of vaccines based on attenuated RNA viruses. The existence of extensive regions of functional RNA elements with tertiary folds in viral RNAs, and likely many other messenger and noncoding RNAs, means that there are significant regions with pocket-containing surfaces that may serve as novel RNA-directed drug targets.

RNA molecules are essential for cellular information transfer and gene regulation, and RNAs have been implicated in many human diseases. Messenger and non-coding RNAs contain highly structured elements, and evidence suggests that many of these structures are important for function. Targeting these RNAs with small molecules offers opportunities to therapeutically modulate numerous cellular processes, including those linked to 'undruggable' protein targets. Despite this promise, there is currently only a single class of human-designed small molecules that target RNA used clinically - the linezolid antibiotics. However, a growing number of small-molecule RNA ligands are being identified, leading to burgeoning interest in the field. Here, we discuss principles for discovering small-molecule drugs that target RNA and argue that the overarching challenge is to identify appropriate target structures - namely, in disease-causing RNAs that have high information content and, consequently, appropriate ligand-binding pockets. If focus is placed on such druggable binding sites in RNA, extensive knowledge of the typical physicochemical properties of drug-like small molecules could then enable small-molecule drug discovery for RNA targets to become (only) roughly as difficult as for protein targets.