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Understanding the dynamics of the SARS CoV-2 RNA genome and its dependence on temperature is necessary to fight the current COVID-19 crisis. Computationally, the handling of large data is a major challenge in the elucidation of the structures of RNA. This work presents network analysis as an important tool to see the conformational evolution and the most dominant structures of the RNA genome at six different temperatures. It effectively distinguished different communities of RNA having structural variation. It is found that at higher temperatures (348 K and above), 80% of the RNA structure is destroyed in both the SPC/E and mTIP3P water models. The thermal denaturation free energy change ΔΔG value calculated for the long-lived structure at higher temperatures of 348 and 363 K ranges from 2.58 to 2.78 kcal/mol for the SPC/E water model, which agrees well with the experimentally reported thermal denaturation free energy range of 2.874 kcal/mol of SARS CoV-NP at normal pH. At higher temperatures, the stability of RNA conformation is found to be due to the existence of non-native base pairs in the SPC/E water model.

Accurate prediction of RNA structure and folding stability has a far-reaching impact on our understanding of RNA functions. Here we develop Vfold2D-MC, a new physics-based model, to predict RNA structure and folding thermodynamics from the sequence. The model employs virtual bond-based coarse-graining of RNA backbone conformation and generates RNA conformations through Monte Carlo sampling of the bond angles and torsional angles of the virtual bonds. Using a coarse-grained statistical potential derived from the known structures, we assign each conformation with a statistical weight. The weighted average over the conformational ensemble gives the entropy and free energy parameters for the hairpin, bulge, and internal loops, and multi-way junctions. From the thermodynamic parameters, we predict RNA structures, melting curves, and structural changes from the sequence. Theory-experiment comparisons indicate that Vfold2D-MC not only gives improved structure predictions but also enables the interpretation of thermodynamic results for different RNA structures, including multibranched junctions. This new model sets a promising framework to treat more complicated RNA structures, such as pseudoknotted and intramolecular kissing loops, for which experimental thermodynamic parameters are often unavailable.

The ribonucleoprotein (RNP) form of archaeal RNase P comprises one catalytic RNA and five protein cofactors. To catalyze Mg2+-dependent cleavage of the 5′ leader from pre-tRNAs, the catalytic (C) and specificity (S) domains of the RNase P RNA (RPR) cooperate to recognize different parts of the pre-tRNA. While ∼250–500 mM Mg2+ renders the archaeal RPR active without RNase P proteins (RPPs), addition of all RPPs lowers the Mg2+ requirement to ∼10–20 mM and improves the rate and fidelity of cleavage. To understand the Mg2+- and RPP-dependent structural changes that increase activity, we used pre-tRNA cleavage and ensemble FRET assays to characterize inter-domain interactions in Pyrococcus furiosus (Pfu) RPR, either alone or with RPPs ± pre-tRNA. Following splint ligation to doubly label the RPR (Cy3-RPRC domain and Cy5-RPRS domain), we used native mass spectrometry to verify the final product. We found that FRET correlates closely with activity, the Pfu RPR and RNase P holoenzyme (RPR + 5 RPPs) traverse different Mg2+-dependent paths to converge on similar functional states, and binding of the pre-tRNA by the holoenzyme influences Mg2+ cooperativity. Our findings highlight how Mg2+ and proteins in multi-subunit RNPs together favor RNA conformations in a dynamic ensemble for functional gains.

N6-methyladenosine (m6A) is the most abundant inner RNA modification in eukaryotes. Due to the development of RNA sequencing technology, the distribution pattern of m6A in the transcriptome has been uncovered. Dynamically, the reversible N6-methylation is mediated by two types of proteins, which are classified as “writers” and “erasers”. Under the association of specific co-factors, writers show spatiotemporal N6-methyltransferase activity. Mechanically, m6A can be recognized by “reader” proteins or can directly modify RNA conformation, and it widely affects gene expression by mediating RNA stability, translation, splicing and export. m6A is involved in a series of physiology processes. Dysregulation of m6A is gradually defined as the pathogenesis of some diseases, e.g., cancer and cardiovascular disease. Therefore, a good understanding of m6A is essential for molecular biology and pathology research. In this article we systemically present an overview of the functions and mechanisms of identified m6A regulators. The discovered biological and pathological processes affected by m6A are also summarized. We hope that readers with related research interests benefit from our review.

Although conformational dynamics of RNA molecules are potentially important in microRNA (miRNA) processing, the role of the protein binding partners in facilitating the requisite structural changes is not well understood. In previous work, we and others have demonstrated that nonduplex structural elements and the conformational flexibility they support are necessary for efficient RNA binding and cleavage by the proteins associated with the two major stages of miRNA processing. However, recent studies showed that the protein DGCR8 binds primary miRNA and duplex RNA with similar affinities. Here, we study RNA binding by a small recombinant construct of the DGCR8 protein and the RNA conformation changes that result. This construct, the DGCR8 core, contains two double-stranded RNA-binding domains (dsRBDs) and a C-terminal tail. To assess conformational changes resulting from binding, we applied small-angle x-ray scattering with contrast variation to detect conformational changes of primary-miR-16-1 in complex with the DGCR8 core. This method reports only on the RNA conformation within the complex and suggests that the protein bends the RNA upon binding. Supporting work using smFRET to study the conformation of RNA duplexes bound to the core also shows bending. Together, these studies elucidate the role of DGCR8 in interacting with RNA during the early stages of miRNA processing.

Recent advances in pseudouridine detection reveal a complex pseudouridine landscape that includes messenger RNA and diverse classes of noncoding RNA in human cells. The known molecular functions of pseudouridine, which include stabilizing RNA conformations and destabilizing interactions with varied RNA-binding proteins, suggest that RNA pseudouridylation could have widespread effects on RNA metabolism and gene expression. Here, we emphasize how much remains to be learned about the RNA targets of human pseudouridine synthases, their basis for recognizing distinct RNA sequences, and the mechanisms responsible for regulated RNA pseudouridylation. We also examine the roles of noncoding RNA pseudouridylation in splicing and translation and point out the potential effects of mRNA pseudouridylation on protein production, including in the context of therapeutic mRNAs.

The ability to accurately predict the binding site, binding pose, and binding affinity for ligand-RNA binding is important for RNA-targeted drug design. Here, we describe a new computational method, RLDOCK, for predicting the binding site and binding pose for ligand-RNA binding. By developing an energy-based scoring function, we sample exhaustively all of the possible binding sites with flexible ligand conformations for a ligand-RNA pair based on the geometric and energetic scores. The model distinguishes from other approaches in three notable features. First, the model enables exhaustive scanning of all of the possible binding sites, including multiple alternative or coexisting binding sites, for a given ligand-RNA pair. Second, the model is based on a new energy-based scoring function developed here. Third, the model employs a novel multistep screening algorithm to improve computational efficiency. Specifically, first, for each binding site, we use a gird-based energy map to rank the binding sites according to the minimum Lennard-Jones potential energy for the different ligand poses. Second, for a given selected binding site, we predict the ligand pose using a two-step algorithm. In the first step, we quickly identify the probable ligand poses using a coarse-grained simplified energy function. In the second step, for each of the probable ligand poses, we predict the ligand poses using a refined energy function. Tests of the RLDOCK for a set of 230 RNA-ligand-bound structures indicate that RLDOCK can successfully predict ligand poses for 27.8, 58.3, and 69.6% of all of the test cases with the root-mean-square deviation within 1.0, 2.0, and 3.0 Å, respectively, for the top three predicted docking poses. The computational method presented here may enable the development of a new, more comprehensive framework for the prediction of ligand-RNA binding with an ensemble of RNA conformations and the metal-ion effects.

Human immunodeficiency virus 1 (HIV-1) is a retrovirus with a ten-kilobase single-stranded RNA genome. HIV-1 must express all of its gene products from a single primary transcript, which undergoes alternative splicing to produce diverse protein products that include structural proteins and regulatory factors1,2. Despite the critical role of alternative splicing, the mechanisms that drive the choice of splice site are poorly understood. Synonymous RNA mutations that lead to severe defects in splicing and viral replication indicate the presence of unknown cis-regulatory elements3. Here we use dimethyl sulfate mutational profiling with sequencing (DMS-MaPseq) to investigate the structure of HIV-1 RNA in cells, and develop an algorithm that we name 'detection of RNA folding ensembles using expectation-maximization' (DREEM), which reveals the alternative conformations that are assumed by the same RNA sequence. Contrary to previous models that have analysed population averages4, our results reveal heterogeneous regions of RNA structure across the entire HIV-1 genome. In addition to confirming that in vitro characterized5 alternative structures for the HIV-1 Rev responsive element also exist in cells, we discover alternative conformations at critical splice sites that influence the ratio of transcript isoforms. Our simultaneous measurement of splicing and intracellular RNA structure provides evidence for the long-standing hypothesis6-8 that heterogeneity in RNA conformation regulates splice-site use and viral gene expression.

The realization that noncoding RNA is implicated in numerous cellular processes, makes it imperative to understand and predict RNA-folding. RNA secondary structure prediction is more tractable than tertiary structure or protein structure. Yet insights into RNA structure-function relationships are complicated by coupling between RNA-folding and ligand-binding. Here, perturbations to equilibrium secondary structure conformational distributions for two riboswitches are calculated in the presence of bound cognate ligands. This work incorporates a key factor coupling ligand binding to RNA conformation but not considered in most previous calculations: the differential affinity of the ligand for a range of RNA-folding intermediates. Significant shifts in the free energy landscape (FEL) due to the ligand occur for transcripts of lengths corresponding to the "decision window," following transcription of the so-called anti-terminator helix. The results suggest how ligand perturbation can stabilize the formation of an intermediate conformation, readily facilitating terminator hairpin formation in the full-length riboswitch.

One of the many challenges faced by RNA viruses is the maintenance of their genomes during infections of host cells. Members of the family Tombusviridae are plus-strand RNA viruses with unmodified triphosphorylated genomic 5′ termini. The tombusvirus Carnation Italian ringspot virus was used to investigate how it protects its RNA genome from attack by 5′-end-targeting degradation enzymes. In vivo and in vitro assays were employed to determine the role of genomic RNA structure in conferring protection from the 5′-to-3′ exoribonuclease Xrn. The results revealed that (i) the CIRV RNA genome is more resistant to Xrn than its sg mRNAs, (ii) the genomic 5′-untranslated region (UTR) folds into a compact RNA structure that effectively and independently prevents Xrn access, (iii) the RNA structure limiting 5′ access is formed by secondary and tertiary interactions that function cooperatively, (iv) the structure is also able to block access of RNA pyrophosphohydrolase to the genomic 5′ terminus, and (v) the RNA structure does not stall an actively digesting Xrn. Based on its proficiency at impeding Xrn 5′ access, we have termed this 5′-terminal structure an Xrn-evading RNA, or xeRNA. These and other findings demonstrate that the 5′UTR of the CIRV RNA genome folds into a complex structural conformation that helps to protect its unmodified 5′ terminus from enzymatic decay during infections. IMPORTANCE The plus-strand RNA genomes of plant viruses in the large family Tombusviridae are not 5′ capped. Here, we explored how a species in the type genus Tombusvirus protects its genomic 5′ end from cellular nuclease attack. Our results revealed that the 5′-terminal sequence of the CIRV genome folds into a complex RNA structure that limits access of the 5′-to-3′ exoribonuclease Xrn, thereby protecting it from processive degradation. The RNA conformation also impeded access of RNA pyrophosphohydrolase, which converts 5′-triphosphorylated RNA termini into 5′-monophosphorylated forms, the preferred substrate for Xrn. This study represents the first report of a higher-order RNA structure in an RNA plant virus genome independently conferring resistance to 5′-end-attacking cellular enzymes.

Transposable elements make up half of the mammalian genome. One of the most abundant is the short interspersed nuclear element (SINE). Among their million copies, B2 accounts for ∼350,000 in the mouse genome and has garnered special interest because of emerging roles in epigenetic regulation. Our recent work demonstrated that B2 RNA binds stress genes to retard transcription elongation. Although epigenetically silenced, B2s become massively up-regulated during thermal and other types of stress. Specifically, an interaction between B2 RNA and the Polycomb protein, EZH2, results in cleavage of B2 RNA, release of B2 RNA from chromatin, and activation of thermal stress genes. Although an established RNA-binding protein and histone methyltransferase, EZH2 is not known to be a nuclease. Here, we provide evidence for the surprising conclusion that B2 is a self-cleaving ribozyme. Ribozyme activity depends on Mg +2 and monovalent cations but is resistant to protease treatment. However, contact with EZH2 accelerates cleavage rate by >100-fold, suggesting that EZH2 promotes a cleavage-competent RNA conformation. B2 modification-interference analysis demonstrates that phosphorothioate changes at A and C nucleotides can substitute for EZH2. B2 nucleotides 45 to 55 and 100 to 101 are essential for activity. Finally, another family of SINEs, the human ALU element, also produces a self-cleaving RNA and is cleaved during T-cell activation as well as thermal and endoplasmic reticulum (ER) stress. Thus, B2/ALU SINEs may be classified as “epigenetic ribozymes” that function as transcriptional switches during stress. Given their high copy numbers, B2 and ALU may represent the predominant ribozyme activity in mammalian cells.

RNA recognition frequently results in conformational changes that optimize intermolecular binding. As a consequence, the overall binding affinity of RNA to its binding partners depends not only on the intermolecular interactions formed in the bound state but also on the energy cost associated with changing the RNA conformational distribution. Measuring these “conformational penalties” is, however, challenging because bound RNA conformations tend to have equilibrium populations in the absence of the binding partner that fall outside detection by conventional biophysical methods. In this study we employ as a model system HIV-1 TAR RNA and its interaction with the ligand argininamide (ARG), a mimic of TAR’s cognate protein binding partner, the transactivator Tat. We use NMR chemical shift perturbations and relaxation dispersion in combination with Bayesian inference to develop a detailed thermodynamic model of coupled conformational change and ligand binding. Starting from a comprehensive 12-state model of the equilibrium, we estimate the energies of six distinct detectable thermodynamic states that are not accessible by currently available methods. Our approach identifies a minimum of four RNA intermediates that differ in terms of the TAR conformation and ARG occupancy. The dominant bound TAR conformation features two bound ARG ligands and has an equilibrium population in the absence of ARG that is below detection limit. Consequently, even though ARG binds to TAR with an apparent overall weak affinity [Formula: see text] , it binds the prefolded conformation with a K(d) in the nM range. Our results show that conformational penalties can be major determinants of RNA-ligand binding affinity as well as a source of binding cooperativity, with important implications for a predictive understanding of how RNA is recognized and for RNA-targeted drug discovery.

Published by Oxford University Press on behalf of Nucleic Acids Research. Interbase FRET can reveal highly detailed information about distance, orientation and dynamics in nucleic acids, complementing the existing structure and dynamics techniques. We here report the first RNA base analogue FRET pair, consisting of the donor tCO and the non-emissive acceptor tCnitro. The acceptor ribonucleoside is here synthesised and incorporated into RNA for the first time. This FRET pair accurately reports the average structure of A-form RNA, and its utility for probing RNA structural changes is demonstrated by monitoring the transition from A- to Z-form RNA. Finally, the measured FRET data were compared with theoretical FRET patterns obtained from two previously reported Z-RNA PDB structures, to shed new light on this elusive RNA conformation.

U2 snRNP is an essential component of the spliceosome. It is responsible for branch point recognition in the spliceosome A-complex via base-pairing of U2 snRNA with an intron to form the branch helix. Small molecule inhibitors target the SF3B component of the U2 snRNP and interfere with A-complex formation during spliceosome assembly. We previously found that the first SF3B inhibited-complex is less stable than A-complex and hypothesized that SF3B inhibitors interfere with U2 snRNA secondary structure changes required to form the branch helix. Using RNA chemical modifiers, we probed U2 snRNA structure in A-complex and SF3B inhibited splicing complexes. The reactivity pattern for U2 snRNA in the SF3B inhibited-complex is indistinguishable from that of A-complex, suggesting that they have the same secondary structure conformation, including the branch helix. This observation suggests SF3B inhibited-complex instability does not stem from an alternate RNA conformation and instead points to the inhibitors interfering with protein component interactions that normally stabilize U2 snRNP’s association with an intron. In addition, we probed U2 snRNA in the free U2 snRNP in the presence of SF3B inhibitor and again saw no differences. However, increased protection of nucleotides upstream of Stem I in the absence of SF3A and SF3B proteins suggests a change of secondary structure at the very 5′ end of U2 snRNA. Chemical probing of synthetic U2 snRNA in the absence of proteins results in similar protections and predicts a previously uncharacterized extension of Stem I. Because this stem must be disrupted for SF3A and SF3B proteins to stably join the snRNP, the structure has the potential to influence snRNP assembly and recycling after spliceosome disassembly.

Predicting the secondary, i.e. base-pairing structure of a folded RNA strand is an important problem in synthetic and computational biology. First-principle algorithmic approaches to this task are challenging because existing models of the folding process are inaccurate, and even if a perfect model existed, finding an optimal solution would be in general NP-complete. In this paper, we propose a simple, yet extremely effective data-driven approach. We represent RNA sequences in the form of three-dimensional tensors in which we encode possible relations between all pairs of bases in a given sequence. We then use a convolutional neural network to predict a two-dimensional map which represents the correct pairings between the bases. Our model achieves significant accuracy improvements over existing methods on two standard datasets. Our experiments show excellent performance of the model across a wide range of sequence lengths and RNA families. We also observe considerable improvements in predicting complex pseudoknotted RNA structures, as compared to previous approaches.Author summaryStructure prediction for RNA sequences is a computationally difficult task that is of increasing importance in applications such as medical diagnostics and drug design; this is because the structure of a folded RNA strand to a large extent defines its function. An open RNA strand can fold to many different structures of varying thermal stability, and the goal of structure prediction is to determine a most stable one among these. There are two main difficulties to this task. Firstly, a given RNA sequence can fold into an enormous number of alternative structures, and a computational search for a most stable one in this huge space can be very demanding. The search can however be facilitated by using heuristics that take into account some underlying principles of the folding process. Here is where machine learning methods come into play: they are suitable for discovering patterns in data, and can thus predict features of the desired structure based on previously learned patterns. Secondly, there do not yet exist fully satisfactory coarse-grained models for the most popular metric for stability, the free energy of the folded structure. Although in principle a minimum free energy (MFE) structure should be a good candidate for a most stable one, MFE structures determined according to current energy models do not match experimental data on native RNA conformations very well. We show how to use an artificial neural network design to predict the structure for a given RNA sequence with high accuracy only by learning from samples whose native structures have been experimentally characterized, independent of any stability metric or energy model.

SummarySARS-CoV-2 is a betacoronavirus with a single-stranded, positive-sense, 30-kilobase RNA genome responsible for the ongoing COVID-19 pandemic. Currently, there are no antiviral drugs with proven efficacy, and development of these treatments are hampered by our limited understanding of the molecular and structural biology of the virus. Like many other RNA viruses, RNA structures in coronaviruses regulate gene expression and are crucial for viral replication. Although genome and transcriptome data were recently reported, there is to date little experimental data on native RNA structures in SARS-CoV-2 and most putative regulatory sequences are functionally uncharacterized. Here we report secondary structure ensembles of the entire SARS-CoV-2 genome in infected cells at single nucleotide resolution using dimethyl sulfate mutational profiling with sequencing (DMS-MaPseq) and the algorithm ‘detection of RNA folding ensembles using expectation–maximization’ clustering (DREEM). Our results reveal previously undescribed alternative RNA conformations across the genome, including structures of the frameshift stimulating element (FSE), a major drug target, that are drastically different from prevailing in vitro population average models. Importantly, we find that this structural ensemble promotes frameshifting rates (~40%) similar to in vivo ribosome profiling studies and much higher than the canonical minimal FSE (~20%). Overall, our result highlight the value of studying RNA folding in its native, dynamic and cellular context. The genomic structures detailed here lays the groundwork for coronavirus RNA biology and will guide the design of SARS-CoV-2 RNA-based therapeutics.

RNA structure heterogeneity is a major challenge when querying RNA structures with chemical probing. We introduce DRACO, an algorithm for the deconvolution of coexisting RNA conformations from mutational profiling experiments. Analysis of the SARS-CoV-2 genome using dimethyl sulfate mutational profiling with sequencing (DMS-MaPseq) and DRACO, identifies multiple regions that fold into two mutually exclusive conformations, including a conserved structural switch in the 3' untranslated region. This work may open the way to dissecting the heterogeneity of the RNA structurome.

Acta crystallographica / Section D 77(4), 496-509 (2021). doi:10.1107/S2059798321001194, Noncoding intron sequences present in precursor mRNAs need to be removed prior to translation, and they are excised via the spliceosome, a multimegadalton molecular machine composed of numerous protein and RNA components. The DEAH-box ATPase Prp2 plays a crucial role during pre-mRNA splicing as it ensures the catalytic activation of the spliceosome. Despite high structural similarity to other spliceosomal DEAH-box helicases, Prp2 does not seem to function as an RNA helicase, but rather as an RNA-dependent ribonucleo��protein particle-modifying ATPase. Recent crystal structures of the spliceosomal DEAH-box ATPases Prp43 and Prp22, as well as of the related RNA helicase MLE, in complex with RNA have contributed to a better understanding of how RNA binding and processivity might be achieved in this helicase family. In order to shed light onto the divergent manner of function of Prp2, an N-terminally truncated construct of Chaetomium thermophilum Prp2 was crystallized in the presence of ADP-BeF$_3$$^���$ and a poly-U$_{12}$ RNA. The refined structure revealed a virtually identical conformation of the helicase core compared with the ADP-BeF$_3$$^���$- and RNA-bound structure of Prp43, and only a minor shift of the C-terminal domains. However, Prp2 and Prp43 differ in the hook-loop and a loop of the helix-bundle domain, which interacts with the hook-loop and evokes a different RNA conformation immediately after the 3��� stack. On replacing these loop residues in Prp43 by the Prp2 sequence, the unwinding activity of Prp43 was abolished. Furthermore, a putative exit tunnel for the $��$-phosphate after ATP hydrolysis could be identified in one of the Prp2 structures., Published by Wiley, Bognor Regis

We report the asymmetric reconstruction of the single-stranded RNA (ssRNA) content in one of the three otherwise identical virions of a multipartite RNA virus, brome mosaic virus (BMV). We exploit a sample consisting exclusively of particles with the same RNA content—specifically, RNAs 3 and 4—assembled in planta by agrobacterium-mediated transient expression. We find that the interior of the particle is nearly empty, with most of the RNA genome situated at the capsid shell. However, this density is disordered in the sense that the RNA is not associated with any particular structure but rather, with an ensemble of secondary/tertiary structures that interact with the capsid protein. Our results illustrate a fundamental difference between the ssRNA organization in the multipartite BMV viral capsid and the monopartite bacteriophages MS2 and Qβ for which a dominant RNA conformation is found inside the assembled viral capsids, with RNA density conserved even at the center of the particle. This can be understood in the context of the differing demands on their respective lifecycles: BMV must package separately each of several different RNA molecules and has been shown to replicate and package them in isolated, membrane-bound, cytoplasmic complexes, whereas the bacteriophages exploit sequence-specific “packaging signals” throughout the viral RNA to package their monopartite genomes.

Pentatricopeptide repeat (PPR) proteins, a helical repeat family of organellar RNA binding proteins, play essential roles in post-transcriptional RNA processing. In Trypanosoma brucei, an expanded family of PPR proteins localize to the parasite’s single mitochondrion, where they are believed to perform important roles in both RNA processing and translation. We studied the RNA binding specificity of the simplest T. brucei PPR protein (KRIPP11) using electrophoretic mobility shift assays, fluorescence anisotropy, circular dichroism spectroscopy, and in vitro selection. We found KRIPP11 to be an RNA binding protein with specificity for sequences of four or more consecutive guanosine residues (G-tracts). Such G-tracts are dramatically enriched in T. brucei mitochondrial transcripts that are destined for extensive uridine insertion/deletion editing but are not present in mRNAs following editing. We further found that the quadruplex oligoguanosine RNA conformation is preferentially recognized by KRIPP11 over other conformational forms, and is bound without disruption of the quadruplex structure. In combination with prior data demonstrating association of KRIPP11 with the small ribosomal subunit, these results suggest possible roles for KRIPP11 in bridging mRNA maturation and translation or in facilitating translation of unusual dual-coded open reading frames.

© The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research. Telomerase adds telomeric repeats to chromosome ends by processive copying of a template within the telomerase RNA bound to telomerase reverse transcriptase. Telomerase RNAs have single-stranded regions that separate the template from a 5 stem and 3 pseudoknot, and mammals gained additional stem P2a.1 separating the template from the pseudoknot. Using human telomerase, we show that the length of template 3-flanking single-stranded RNA is a determinant of repeat addition processivity whereas template 5-flanking single-stranded RNA and P2a.1 are critical for activity but not processivity. In comparison, requirements for the template sequence itself are confounding: different substitutions of the same position have strikingly different consequences, from improved processivity and activity to complete inactivation. We discovered that some altered-template sequences stabilize an alternative RNA conformation that precludes the pseudoknot by base-pairing of one pseudoknot strand to the template 3 end. Using mutations to reduce over-stability of the alternative conformation, we restore high activity and processivity to otherwise inactive altered-template telomerase ribonucleoproteins. In cells, over-stabilization or destabilization of the alternative state severely inhibited biogenesis of active telomerase. Our findings delineate roles for human telomerase RNA template-flanking regions, establish a biologically relevant pseudoknot-alternative RNA conformation, and expand the repertoire of human telomerase repeat synthesis.

HIV-1 packages two copies of its gRNA into virions via an interaction with the viral structural protein Gag. Both copies and their native RNA structure are essential for virion infectivity. The precise stepwise nature of the packaging process has not been resolved. This is largely due to a prior lack of structural techniques that follow RNA structural changes within an RNA���protein complex. Here, we apply the in-gel SHAPE (selective 2���OH acylation analysed by primer extension) technique to study the initiation of HIV-1 packaging, examining the interaction between the packaging signal RNA and the Gag polyprotein, and compare it with that of the NC domain of Gag alone. Our results imply interactions between Gag and monomeric packaging signal RNA in switching the RNA conformation into a dimerisation-competent structure, and show that the Gag���dimer complex then continues to stabilise. These data provide a novel insight into how HIV-1 regulates the translation and packaging of its genome., This work was funded by an Eric Reid fund for Methodology grant from the Biochemical Society (to JCK), UK Medical Research Council, Grant/Award Number: MR/N022939/1 (to AML and JCK). AMLL is supported by the Clinical Academic Reserve and his laboratory by the NIHR Cambridge BRC (Grant RCAG/18). Research in the Kappei laboratory was supported by the National Research Foundation Singapore and the Singapore Ministry of Education under its Re-search Centres of Excellence initiative.

The current RNA structure prediction methods cannot keep up the pace of the rapidly increasing number of sequences and the emerging new functions of RNAs. Template-based RNA three-dimensional structure prediction methods are restricted by the limited number of known RNA structures, and traditional motif-based search for the templates does not always lead to successful results. Here we report a new template search and assembly algorithm, the hierarchical loop template-assembly method (VfoldLA). The method searches for templates for single strand loop/junctions instead of the whole motifs, which often renders no available templates, or short fragments (several nucleotides), which requires a long computational time to assemble and refine. The VfoldLA method has the advantage of accounting for local and nonlocal interloop interactions. Benchmark tests indicate that this new method can provide low-resolution predictions for RNA conformations at different levels of structural complexities. Furthermore, the VfoldLA-predicted conformations may also serve as reliable putative models for further structure prediction and refinements. VfoldLA is accessible at http://rna.physics.missouri.edu/vfoldLA .

Chemical probing has the power to provide insight into RNA conformation in vivo and in vitro, but interpreting the results depends on methods to detect the chemically modified nucleotides. Traditionally, the presence of modified bases was inferred from their ability to halt reverse transcriptase during primer extension and the locations of termination sites observed by electrophoresis or sequencing. More recently, modification-induced mutations have been used as a readout for chemical probing data. Given the variable propensity for mismatch incorporation and read-through with different reverse transcriptases, we examined how termination and mutation events compare to each other in the same chemical probing experiments. We found that mutations and terminations induced by dimethyl sulfate probing are both specific for methylated bases, but these two measures have surprisingly little correlation and represent largely nonoverlapping indicators of chemical modification data. We also show that specific biases for modified bases depend partly on local sequence context and that different reverse transcriptases show different biases toward reading a modification as a stop or a mutation. These results support approaches that incorporate analysis of both termination and mutation events into RNA probing experiments.

The spliceosome is an extraordinarily dynamic molecular machine in which significant changes in composition as well as protein and RNA conformation are required for carrying out pre-mRNA splicing. Single-molecule fluorescence resonance energy transfer (smFRET) can be used to elucidate these dynamics both in well-characterized model systems and in entire spliceosomes. These types of single-molecule data provide novel information about spliceosome components and can be used to identify sub-populations of molecules with unique behaviors. When smFRET is combined with single-molecule fluorescence colocalization, conformational dynamics can be further linked to the presence or absence of a given spliceosome component. Here, we provide a description of experimental considerations, approaches, and workflows for smFRET with an emphasis on applications for the splicing machinery.

Motivation Kinetics is key to understand many phenomena involving RNAs, such as co-transcriptional folding and riboswitches. Exact out-of-equilibrium studies induce extreme computational demands, leading state-of-the-art methods to rely on approximated kinetics landscapes, obtained using sampling strategies that strive to generate the key landmarks of the landscape topology. However, such methods are impeded by a large level of redundancy within sampled sets. Such a redundancy is uninformative, and obfuscates important intermediate states, leading to an incomplete vision of RNA dynamics. Results We introduce RNANR, a new set of algorithms for the exploration of RNA kinetics landscapes at the secondary structure level. RNANR considers locally optimal structures, a reduced set of RNA conformations, in order to focus its sampling on basins in the kinetic landscape. Along with an exhaustive enumeration, RNANR implements a novel non-redundant stochastic sampling, and offers a rich array of structural parameters. Our tests on both real and random RNAs reveal that RNANR allows to generate more unique structures in a given time than its competitors, and allows a deeper exploration of kinetics landscapes. Availability and implementation RNANR is freely available at https://project.inria.fr/rnalands/rnanr.

Chemical modifications of 2'-O-methyl (2'-OMe) and locked nucleic acid (LNA) of the nucleotides in the seed region (positions 2-8) of the small interfering RNA (siRNA) guide strand significantly reduced seed-matched (SM) off-target effects. The siRNA with 2'-OMe modifications inhibited the expression of a completely-matched (CM) target gene, whereas that with LNA modifications did not inhibit the expression of the CM target. By computational predictions of conformational changes of siRNA by these modifications, we revealed that both modifications in the siRNA seed region reduce SM off-target effects by steric hindrance to base-pairing with target transcripts but LNA modifications also disturb the association of the siRNA guide strand with the Argonaute (AGO) protein by altering RNA conformation. Thus, chemical modifications of the siRNA guide strand, which alter steric conformation to disturb base-pairing with target transcripts but do not disturb the association with the AGO protein, may successfully suppress off-target effects without substantial loss of RNA silencing activity.

While synonymous single-nucleotide variants (sSNVs) have largely been unstudied, since they do not alter protein sequence, mounting evidence suggests that they may affect RNA conformation, splicing, and the stability of nascent-mRNAs to promote various diseases. Accurately prioritizing deleterious sSNVs from a pool of neutral ones can significantly improve our ability of selecting functional genetic variants identified from various genome-sequencing projects, and, therefore, advance our understanding of disease etiology. In this study, we develop a computational algorithm to prioritize sSNVs based on their impact on mRNA splicing and protein function. In addition to genomic features that potentially affect splicing regulation, our proposed algorithm also includes dozens structural features that characterize the functions of alternatively spliced exons on protein function. Our systematical evaluation on thousands of sSNVs suggests that several structural features, including intrinsic disorder protein scores, solvent accessible surface areas, protein secondary structures, and known and predicted protein family domains, show significant differences between disease-causing and neutral sSNVs. Our result suggests that the protein structure features offer an added dimension of information while distinguishing disease-causing and neutral synonymous variants. The inclusion of structural features increases the predictive accuracy for functional sSNV prioritization. Electronic supplementary material The online version of this article (doi:10.1007/s00439-017-1783-x) contains supplementary material, which is available to authorized users.

Atomic force and transmission electron microscopies (AFM/TEM) are powerful tools to analyze RNA-based nanostructures. While cryo-TEM analysis allows the determination of near-atomic resolution structures of large RNA complexes, this chapter intends to present how RNA nanostructures can be analyzed at room temperature on surfaces. Indeed, TEM and AFM analyses permit the conformation of a large population of individual molecular structures to be observed, providing a statistical basis for the variability of these nanostructures within the population. Nevertheless, if double-stranded DNA molecular imaging has been described extensively, only a few investigations of single-stranded DNA and RNA filaments have been conducted so far. Indeed, technique for spreading and adsorption of ss-molecules on AFM surfaces or TEM grids is a crucial step to avoid disturbing RNA conformation on the surface. In this chapter, we present a specific method to analyze RNA assemblies and RNA-protein complexes for molecular microscopies.

Long non-coding RNAs (lncRNAs) constitute a significant fraction of the transcriptome, playing important roles in development and disease. However, our understanding of structure-function relationships for this emerging class of RNAs has been limited to secondary structures. Here, we report the 3-D atomistic structural study of epigenetic lncRNA, Braveheart (Bvht), and its complex with CNBP (Cellular Nucleic acid Binding Protein). Using small angle X-ray scattering (SAXS), we elucidate the ensemble of Bvht RNA conformations in solution, revealing that Bvht lncRNA has a well-defined, albeit flexible 3-D structure that is remodeled upon CNBP binding. Our study suggests that CNBP binding requires multiple domains of Bvht and the RHT/AGIL RNA motif. We show that RHT/AGIL, previously shown to interact with CNBP, contains a highly flexible loop surrounded by more ordered helices. As one of the largest RNA-only 3-D studies, the work lays the foundation for future structural studies of lncRNA-protein complexes., Many RNA systems possess highly ordered 3-D structures that are essential to their function. Here the authors demonstrate that the long non-coding RNA Braveheart possesses a flexible but defined 3-D structure which is remodeled upon binding the protein CNBP.

Structured RNA elements within the internal ribosome entry site (IRES) of hepatitis C virus (HCV) genome hijack host cell machinery for translation initiation through a cap-independent mechanism. Here, using a phage display selection, we obtained two antibody fragments (Fabs), HCV2 and HCV3, against HCV IRES that bind the RNA with dissociation constants of 32 ± 7 nM and 37 ± 8 nM respectively, specifically recognizing the so-called junction IIIabc (JIIIabc). We used these Fabs as crystallization chaperones and determined the high-resolution crystal structures of JIIIabc – HCV2 and – HCV3 complexes at 1.81-Å and 2.75-Å resolution respectively, revealing an anti-parallel four-way junction with the so-called IIIa and IIIc sub-domains brought together through tertiary interactions. The RNA conformation observed in the structures supports the structural model for this region derived from cryo-EM data for the HCV IRES – 40S ribosome complex, suggesting that the tertiary fold of the RNA pre-organizes the domain for interactions with the 40S ribosome. Strikingly, both Fabs and the ribosomal protein eS27 not only interact with a common subset of nucleotides within the JIIIabc but also use physio-chemically similar sets of protein residues to do so, suggesting that the RNA surface is well-suited for interactions with proteins, perhaps analogous to the ‘hot spot’ concept elaborated for protein-protein interactions. Using a rabbit reticulocyte lysate-based translation assay with a bicistronic reporter construct, we further demonstrated that Fabs HCV2 and HCV3 specifically inhibit the HCV IRES-directed translation, implicating disruption of the JIIIabc – ribosome interaction as a potential therapeutic strategy against HCV.

The ubiquitous influence of double stranded RNAs in biological events makes them imperative to gather data based on specific binding procedure of small molecules to various RNA conformations. Particular interest may be attributed to situations wherein small molecules target RNAs altering their structures and causing functional modifications. The main focus of this study is to delve into the interactive pattern of two small molecule phenothiazinium dyes, methylene blue and new methylene blue, with three duplex RNA polynucleotides-poly(A).poly(U), poly(C).poly(G) and poly(I).poly(C) by spectroscopic and molecular modeling techniques. Analysis of data as per Scatchard and Benesi-Hildebrand methodologies revealed highest affinity of these dyes to poly(A).poly(U) and least to poly(I).poly(C). In addition to fluorescence quenching, viscometric studies also substantiated that the dyes follow different modes of binding to different RNA polynucleotides. Distortion in the RNA structures with induced optical activity in the otherwise optically inactive dye molecules was evidenced from circular dichroism results. Dye-induced RNA structural modification occurred from extended conformation to compact particles visualized by atomic force microscopy. Molecular docking results revealed different binding patterns of the dye molecules within the RNA duplexes. The novelty of the present work lies towards a new contribution of the phenothiazinium dyes in dysfunctioning double stranded RNAs, advancing our knowledge to their potential use as RNA targeted small molecules.

Influenza A viruses (IAVs) constitute a major threat to human health. The IAV genome consists of eight single-stranded viral RNA (vRNA) segments contained in separate viral ribonucleoprotein complexes (vRNPs) that are packaged together into a single virus particle. The structure of the vRNA is believed to play a role in assembling the different vRNPs into budding virions(1–8) and in directing reassortment between IAVs(9). Reassortment between established human IAVs and IAVs harboured in the animal reservoir can lead to the emergence of pandemic influenza strains to which there is little pre existing immunity in the human population(10,11). While previous studies have revealed the overall organisation of the proteins within vRNPs, characterisation of vRNA structure using conventional structural methods is hampered by limited resolution and an inability to resolve dynamic components(12,13). Here, we employ multiple high-throughput sequencing approaches to generate the first global high-resolution structure of the IAV genome. We show that different IAV genome segments acquire distinct RNA conformations and form both intra- and inter-segment RNA interactions inside influenza virions. We use our detailed map of IAV genome structure to provide the first direct evidence for how inter-segment RNA interactions drive vRNP co-segregation during reassortment between different IAV strains. The work presented here is a roadmap both for the development of improved vaccine strains and for the creation of a framework to ‘risk assess’ reassortment potential to better predict the emergence of new pandemic influenza strains.

Background Predicted RNA secondary structures are typically visualized using dot-plots for base pair binding probabilities and planar graphs for unique structures, such as the minimum free energy structure. These are however difficult to analyze simultaneously. Results This work introduces a compact unified view of the most stable conformation of an RNA secondary structure and its base pair probabilities, which is called the Circular Secondary Structure Base Pairs Probabilities Plot (CS 2 BP 2 -Plot). Along with our design we provide access to a web server implementation of our solution that facilitates pairwise comparison of short RNA (and DNA) sequences up to 200 base pairs. The web server first calculates the minimum free energy secondary structure and the base pair probabilities for up to 10 RNA or DNA sequences using RNAfold and then provides a two panel comparative view that includes CS2BP2-Plots along with the traditional graph, planar and circular diagrams obtained with VARNA. The CS2BP2-Plots include highlighting of the nucleotide differences between two selected sequences using ClustalW local alignments. We also provide descriptive statistics, dot-bracket secondary structure representations and ClustalW local alignments for compared sequences. Conclusions Using circular diagrams and colour and weight-coded arcs, we demonstrate how a single image can replace the state-of-the-art dual representations (dot-plots and minimum free energy structures) for base-pair probabilities of RNA secondary structures while allowing efficient exploration and comparison of different RNA conformations via a web server front end. With that, we provide the community, especially the biologically oriented, with an intuitive tool for ncRNA visualization. Web-server: https://nrcmonsrv01.nrc.ca/cs2bp2plot

The viral RNA (vRNA) genome of influenza viruses is replicated by the RNA-dependent RNA polymerase (RNAP) via a complementary RNA (cRNA) intermediate. The vRNA promoter can adopt multiple conformations when bound by the RNAP. However, the dynamics, determinants, and biological role of these conformations are unknown; further, little is known about cRNA promoter conformations. To probe the RNA conformations adopted during initial replication, we monitored single, surface-immobilised vRNA and cRNA initiation complexes in real-time. Our results show that, while the 3’ terminus of the vRNA promoter exists in dynamic equilibrium between pre-initiation and initiation conformations, the cRNA promoter exhibited very limited dynamics. Two residues in the proximal 3’ region of the cRNA promoter (residues absent in the vRNA promoter) allowed the cRNA template strand to reach further into the active site, limiting promoter dynamics. Our results highlight promoter-dependent differences in influenza initiation mechanisms, and advance our understanding of virus replication.

Summary The majority of the mammalian genome is transcribed into non-coding RNAs, many of which co-evolve with RNA-binding proteins (RBPs) to function as biochemically defined and tractable ribonucleoproteins (RNPs). Here, we applied icSHAPE- a robust and versatile RNA structural probing pipeline- to endogenous RNPs purified from nuclei, providing base-resolution structural rationale for RNP activity and subcellular localization. Combining with genetic and biochemical reconstitutions, structural and functional alternations can be directly attributed to a given RBP without ambiguity. For complete details on the use and execution of this protocol, please refer to Chen et al. (2018) .