The 3-dimensional fold of an RNA molecule is largely determined by patterns of intramolecular hydrogen bonds between bases. Predicting the base pairing network from the sequence, also referred to as RNA secondary structure prediction or RNA folding, is a nondeterministic polynomial-time (NP)-complete computational problem. The structure of the molecule is strongly predictive of its functions and biochemical properties, and therefore the ability to accurately predict the structure is a crucial tool for biochemists. Many methods have been proposed to efficiently sample possible secondary structure patterns. Classic approaches employ dynamic programming, and recent studies have explored approaches inspired by evolutionary and machine learning algorithms. This work demonstrates leveraging quantum computing hardware to predict the secondary structure of RNA. A Hamiltonian written in the form of a Binary Quadratic Model (BQM) is derived to drive the system toward maximizing the number of consecutive base pairs while jointly maximizing the average length of the stems. A Quantum Annealer (QA) is compared to a Replica Exchange Monte Carlo (REMC) algorithm programmed with the same objective function, with the QA being shown to be highly competitive at rapidly identifying low energy solutions. The method proposed in this study was compared to three algorithms from literature and, despite its simplicity, was found to be competitive on a test set containing known structures with pseudoknots.

RNA begins to fold as it is transcribed by an RNA polymerase. Consequently, RNA folding is constrained by the direction and rate of transcription. Understanding how RNA folds into secondary and tertiary structures therefore requires methods for determining the structure of cotranscriptional folding intermediates. Cotranscriptional RNA chemical probing methods accomplish this by systematically probing the structure of nascent RNA that is displayed from RNA polymerase. Here, we have developed a concise, high-resolution cotranscriptional RNA chemical probing procedure called T ranscription E longation C omplex RNA structure prob ing- M ultilength (TECprobe-ML). We validated TECprobe-ML by replicating and extending previous analyses of ZTP and fluoride riboswitch folding, and mapped the folding pathway of a ppGpp-sensing riboswitch. In each system, TECprobe-ML identified coordinated cotranscriptional folding events that mediate transcription antitermination. Our findings establish TECprobe-ML as an accessible method for mapping cotranscriptional RNA folding pathways.

Transcription is mutagenic, in part because the R-loop formed by the binding of the nascent RNA with its DNA template exposes the nontemplate DNA strand to mutagens and primes unscheduled error-prone DNA synthesis. We hypothesize that strong folding of nascent RNA weakens R-loops and hence decreases mutagenesis. By a yeast forward mutation assay, we show that strengthening RNA folding and reducing R-loop formation by synonymous changes in a reporter gene can lower mutation rate by >80%. This effect is diminished after the overexpression of the gene encoding RNase H1 that degrades the RNA in a DNA-RNA hybrid, indicating that the effect is R-loop-dependent. Analysis of genomic data of yeast mutation accumulation lines and human neutral polymorphisms confirms the generality of these findings. This mechanism for local protection of genome integrity is of special importance to highly expressed genes because of their frequent transcription and strong RNA folding, the latter also improves translational fidelity. As a result, strengthening RNA folding simultaneously curtails genotypic and phenotypic mutations.

Structures that recur across multiple different transcripts, called structure motifs, often perform a similar function-for example, recruiting a specific RNA-binding protein that then regulates translation, splicing, or subcellular localization. Identifying common motifs between coregulated transcripts may therefore yield significant insight into their binding partners and mechanism of regulation. However, as most methods for clustering structures are based on folding individual sequences or doing many pairwise alignments, this results in a tradeoff between speed and accuracy that can be problematic for large-scale data sets. Here we describe a novel method for comparing and characterizing RNA secondary structures that does not require folding or pairwise alignment of the input sequences. Our method uses the idea of constructing a distance function between two objects by their respective distances to a collection of empirical examples or models, which in our case consists of 1973 Rfam family covariance models. Using this as a basis for measuring structural similarity, we developed a clustering pipeline called NoFold to automatically identify and annotate structure motifs within large sequence data sets. We demonstrate that NoFold can simultaneously identify multiple structure motifs with an average sensitivity of 0.80 and precision of 0.98 and generally exceeds the performance of existing methods. We also perform a cross-validation analysis of the entire set of Rfam families, achieving an average sensitivity of 0.57. We apply NoFold to identify motifs enriched in dendritically localized transcripts and report 213 enriched motifs, including both known and novel structures.

Assembly of the major viral pathogens of the Picornaviridae family is poorly understood. Human parechovirus 1 is an example of such viruses that contains 60 short regions of ordered RNA density making identical contacts with the protein shell. We show here via a combination of RNA-based systematic evolution of ligands by exponential enrichment, bioinformatics analysis and reverse genetics that these RNA segments are bound to the coat proteins in a sequence-specific manner. Disruption of either the RNA coat protein recognition motif or its contact amino acid residues is deleterious for viral assembly. The data are consistent with RNA packaging signals playing essential roles in virion assembly. Their binding sites on the coat proteins are evolutionarily conserved across the Parechovirus genus, suggesting that they represent potential broad-spectrum anti-viral targets.The mechanism underlying packaging of genomic RNA into viral particles is not well understood for human parechoviruses. Here the authors identify short RNA motifs in the parechovirus genome that bind capsid proteins, providing approximately 60 specific interactions for virion assembly.

Mg²⁺ shares a distinctive relationship with RNA, playing important and specific roles in the folding and function of essentially all large RNAs. Here we use theory and experiment to evaluate Fe²⁺ in the absence of free oxygen as a replacement for Mg²⁺ in RNA folding and catalysis. We describe both quantum mechanical calculations and experiments that suggest that the roles of Mg²⁺ in RNA folding and function can indeed be served by Fe²⁺. The results of quantum mechanical calculations show that the geometry of coordination of Fe²⁺ by RNA phosphates is similar to that of Mg²⁺. Chemical footprinting experiments suggest that the conformation of the Tetrahymena thermophila Group I intron P4-P6 domain RNA is conserved between complexes with Fe²⁺ or Mg²⁺. The catalytic activities of both the L1 ribozyme ligase, obtained previously by in vitro selection in the presence of Mg²⁺, and the hammerhead ribozyme are enhanced in the presence of Fe²⁺ compared to Mg²⁺. All chemical footprinting and ribozyme assays in the presence of Fe²⁺ were performed under anaerobic conditions. The primary motivation of this work is to understand RNA in plausible early earth conditions. Life originated during the early Archean Eon, characterized by a non-oxidative atmosphere and abundant soluble Fe²⁺. The combined biochemical and paleogeological data are consistent with a role for Fe²⁺ in an RNA World. RNA and Fe²⁺ could, in principle, support an array of RNA structures and catalytic functions more diverse than RNA with Mg²⁺ alone.

RNA begins to fold as it is transcribed by an RNA polymerase. Consequently, RNA folding is constrained by the direction and rate of transcription. Understanding how RNA folds into secondary and tertiary structures therefore requires methods for determining the structure of cotranscriptional folding intermediates. Cotranscriptional RNA chemical probing methods accomplish this by systematically probing the structure of nascent RNA that is displayed from an RNA polymerase. Here, we describe a concise, high-resolution cotranscriptional RNA chemical probing procedure called variable length Transcription Elongation Complex RNA structure probing (TECprobe-VL). We demonstrate the accuracy and resolution of TECprobe-VL by replicating and extending previous analyses of ZTP and fluoride riboswitch folding and mapping the folding pathway of a ppGpp-sensing riboswitch. In each system, we show that TECprobe-VL identifies coordinated cotranscriptional folding events that mediate transcription antitermination. Our findings establish TECprobe-VL as an accessible method for mapping cotranscriptional RNA folding pathways.

G-quadruplexes (G4s) are non-canonical structures involved in many important cellular processes. To date, the prediction of potential G-quadruplex structures (PG4s) has been based almost exclusively on the sequence of interest agreeing with the algorithm Gx-N-1-7-Gx-N1-7-Gx-N1-7-Gx (where x ≥ 3 and N = A, U, G or C). However, many sequences agreeing with this algorithm do not form G4s and are considered false-positive predictions. Here we show the RNA PG4 candidate in the 3'-untranslated region (UTR) of the TTYH1 gene to be one such false positive. Specifically, G4 folding was observed to be inhibited by the presence of multiple-cytosine tracks, located in the candidate's genomic context, that adopted a Watson-Crick base-paired structure. Clearly, the neighbouring sequences of a PG4 may influence its folding. The secondary structure of 12 PG4 motifs along with either 15 or 50 nucleotides of their upstream and downstream genomic contexts were evaluated by in-line probing. Data permitted the development of a scoring system for the prediction of PG4s taking into account the effect of the neighbouring sequences. The accuracy of this scoring system was assessed by probing 14 other novel PG4 candidates retrieved in human 5'-UTRs. This new scoring system can be used, in combination with the standard algorithm, to better predict the folding of RNA G4s.

A synthetic biology approach toward constructing an RNA-based genome expands our understanding of living things and opens avenues for technological advancement. For the precise design of an artificial RNA replicon either from scratch or based on a natural RNA replicon, understanding structure-function relationships of RNA sequences is critical. However, our knowledge remains limited to a few particular structural elements intensively studied so far. Here, we conducted a series of site-directed mutagenesis studies of yeast narnaviruses ScNV20S and ScNV23S, perhaps the simplest natural autonomous RNA replicons, to identify RNA elements required for maintenance and replication. RNA structure disruption corresponding to various portions of the entire narnavirus genome suggests that pervasive RNA folding, in addition to the precise secondary structure of genome termini, is essential for maintenance of the RNA replicon in vivo. Computational RNA structure analyses suggest that this scenario likely applies to other "narna-like" viruses. This finding implies selective pressure on these simplest autonomous natural RNA replicons to fold into a unique structure that acquires both thermodynamic and biological stability. We propose the importance of pervasive RNA folding for the design of RNA replicons that could serve as a platform for in vivo continuous evolution as well as an interesting model to study the origin of life.

DCL1 is the ribonuclease that carries out miRNA biogenesis in plants. The enzyme has two tandem double stranded RNA binding domains (dsRBDs) in its C-terminus. Here we show that the first of these domains binds precursor RNA fragments when isolated and cooperates with the second domain in the recognition of substrate RNA. Remarkably, despite showing RNA binding activity, this domain is intrinsically disordered. We found that it acquires a folded conformation when bound to its substrate, being the first report of a complete dsRBD folding upon binding. The free unfolded form shows tendency to adopt folded conformations, and goes through an unfolded bound state prior to the folding event. The significance of these results is discussed by comparison with the behavior of other dsRBDs.

Telomerase maintains telomere length at the ends of linear chromosomes using an integral telomerase RNA (TER) and telomerase reverse transcriptase (TERT). An essential part of TER is the template/pseudoknot domain (t/PK) which includes the template, for adding telomeric repeats, template boundary element (TBE), and pseudoknot, enclosed in a circle by stem 1. The Tetrahymena telomerase holoenzyme catalytic core (p65-TER-TERT) was recently modeled in our 9 Å resolution cryo-electron microscopy map by fitting protein and TER domains, including a solution NMR structure of the Tetrahymena pseudoknot. Here, we describe in detail the structure and folding of the isolated pseudoknot, which forms a compact structure with major groove U•A-U and novel C•G-A+ base triples. Base substitutions that disrupt the base triples reduce telomerase activity in vitro NMR studies also reveal that the pseudoknot does not form in the context of full-length TER in the absence of TERT, due to formation of a competing structure that sequesters pseudoknot residues. The residues around the TBE remain unpaired, potentially providing access by TERT to this high affinity binding site during an early step in TERT-TER assembly. A model for the assembly pathway of the catalytic core is proposed.

Large-scale, cooperative rearrangements underlie the functions of RNA in RNA-protein machines and gene regulation. To understand how such rearrangements are orchestrated, we used high-throughput chemical footprinting to dissect a seemingly concerted rearrangement in P5abc RNA, a paradigm of RNA folding studies. With mutations that systematically disrupt or restore putative structural elements, we found that this transition reflects local folding of structural modules, with modest and incremental cooperativity that results in concerted behavior. First, two distant secondary structure changes are coupled through a bridging three-way junction and Mg2+-dependent tertiary structure. Second, long-range contacts are formed between modules, resulting in additional cooperativity. Given the sparseness of RNA tertiary contacts after secondary structure formation, we expect that modular folding and incremental cooperativity are generally important for specifying functional structures while also providing productive kinetic paths to these structures. Additionally, we expect our approach to be useful for uncovering modularity in other complex RNAs.

Electronegative clusters (ENCs) made up of acidic residues and/or phosphorylation sites are the most abundant repetitive sequences in RNA-binding proteins. Previous studies have indicated that ENCs inhibit RNA binding for structured RNA-binding domains (RBDs). However, this is not the case for the unstructured RBD in histone pre-mRNA stem-loop binding protein (SLBP). The SLBP RBD contains 70 amino acids and is followed by a phosphorylatable ENC. ENC phosphorylation increases RNA-binding affinity of SLBP to the sub-picomolar range. In this study, we use NMR and molecular dynamics simulations to elucidate the mechanism for this tight binding. Our NMR data demonstrate that the ENC transiently folds apo SLBP into an RNA-bound resembling state. We find that in the RNA-bound state, the phosphorylated ENC interacts with the loop region opposite to the RNA-binding site. This allosteric interaction stabilizes the complex and therefore enhances RNA binding. To evaluate the generality of our findings, we graft an ENC onto endoribonuclease homolog 1's first double-stranded RNA-binding motif (DRBM1), an unstructured RBD that shares no homology with SLBP. We find that the engineered ENC increases the folded species of DRBM1 and inhibits RNA binding. On the contrary, introducing basic residues to DRBM1 makes the domain more unfolded, enhances RNA binding, and mitigates the inhibitory effect of the engineered ENC. In summary, our study suggests that ENCs promote folding of unstructured RNA-binding domains, and their effects on RNA binding depend on the electropositive charges on the RBD surface.

Guanine (G)-rich nucleic acids can fold into G-quadruplex (G4) structures under permissive conditions. Although many RNAs contain sequences that fold into RNA G4s (rG4s) in vitro, their folding and functions in vivo are not well understood. In this report, we showed that the folding of putative rG4s in human cells into rG4 structures is dynamically regulated under stress. By using high-throughput dimethylsulfate (DMS) probing, we identified hundreds of endogenous stress-induced rG4s, and validated them by using an rG4 pull-down approach. Our results demonstrate that stress-induced rG4s are enriched in mRNA 3'-untranslated regions and enhance mRNA stability. Furthermore, stress-induced rG4 folding is readily reversible upon stress removal. In summary, our study revealed the dynamic regulation of rG4 folding in human cells and suggested that widespread rG4 motifs may have a global regulatory impact on mRNA stability and cellular stress response.

Antitermination is a regulatory process based on the competitive folding of terminator-antiterminator structures that can form in the leader region of nascent transcripts. In the case of the Bacillus subtilis licS gene involved in β-glucosides utilization, the binding of the antitermination protein LicT to a short RNA hairpin (RAT) prevents the formation of an overlapping terminator and thereby allows transcription to proceed. Here, we monitored in vitro the competition between termination and antitermination by combining bulk and single-molecule fluorescence-based assays using labeled RNA oligonucleotide constructs of increasing length that mimic the progressive transcription of the terminator invading the antiterminator hairpin. Although high affinity binding is abolished as soon as the antiterminator basal stem is disrupted by the invading terminator, LicT can still bind and promote closing of the partially unfolded RAT hairpin. However, binding no longer occurs once the antiterminator structure has been disrupted by the full-length terminator. Based on these findings, we propose a kinetic competition model for the sequential events taking place at the termination-antitermination site, where LicT needs to capture its RAT target before completion of the terminator to remain tightly bound during RNAP pausing, before finally dissociating irreversibly from the elongated licS transcript.

RNA secondary structure prediction is widely used for developing hypotheses about the structures of RNA sequences, and structure can provide insight about RNA function. The accuracy of structure prediction is known to be improved using experimental mapping data that provide information about the pairing status of single nucleotides, and these data can now be acquired for whole transcriptomes using high-throughput sequencing. Prior methods for using these experimental data focused on predicting structures for sequences assuming that they populate a single structure. Most RNAs populate multiple structures, however, where the ensemble of strands populates structures with different sets of canonical base pairs. The focus on modeling single structures has been a bottleneck for accurately modeling RNA structure. In this work, we introduce Rsample, an algorithm for using experimental data to predict more than one RNA structure for sequences that populate multiple structures at equilibrium. We demonstrate, using SHAPE mapping data, that we can accurately model RNA sequences that populate multiple structures, including the relative probabilities of those structures. This program is freely available as part of the RNAstructure software package.

RNA folding during transcription directs an order of folding that can determine RNA structure and function. However, the experimental study of cotranscriptional RNA folding has been limited by the lack of easily approachable methods that can interrogate nascent RNA structure at nucleotide resolution. To address this, we previously developed cotranscriptional selective 2΄-hydroxyl acylation analyzed by primer extension sequencing (SHAPE-Seq) to simultaneously probe all intermediate RNA transcripts during transcription by stalling elongation complexes at catalytically dead EcoRIE111Q roadblocks. While effective, the distribution of elongation complexes using EcoRIE111Q requires laborious PCR using many different oligonucleotides for each sequence analyzed. Here, we improve the broad applicability of cotranscriptional SHAPE-Seq by developing a sequence-independent biotin-streptavidin (SAv) roadblocking strategy that simplifies the preparation of roadblocking DNA templates. We first determine the properties of biotin-SAv roadblocks. We then show that randomly distributed biotin-SAv roadblocks can be used in cotranscriptional SHAPE-Seq experiments to identify the same RNA structural transitions related to a riboswitch decision-making process that we previously identified using EcoRIE111Q. Lastly, we find that EcoRIE111Q maps nascent RNA structure to specific transcript lengths more precisely than biotin-SAv and propose guidelines to leverage the complementary strengths of each transcription roadblock in cotranscriptional SHAPE-Seq.

Ribonucleic acid (RNA) secondary structure prediction continues to be a significant challenge, in particular when attempting to model sequences with less rigidly defined structures, such as messenger and non-coding RNAs. Crucial to interpreting RNA structures as they pertain to individual phenotypes is the ability to detect RNAs with large structural disparities caused by a single nucleotide variant (SNV) or riboSNitches. A recently published human genome-wide parallel analysis of RNA structure (PARS) study identified a large number of riboSNitches as well as non-riboSNitches, providing an unprecedented set of RNA sequences against which to benchmark structure prediction algorithms. Here we evaluate 11 different RNA folding algorithms' riboSNitch prediction performance on these data. We find that recent algorithms designed specifically to predict the effects of SNVs on RNA structure, in particular remuRNA, RNAsnp and SNPfold, perform best on the most rigorously validated subsets of the benchmark data. In addition, our benchmark indicates that general structure prediction algorithms (e.g. RNAfold and RNAstructure) have overall better performance if base pairing probabilities are considered rather than minimum free energy calculations. Although overall aggregate algorithmic performance on the full set of riboSNitches is relatively low, significant improvement is possible if the highest confidence predictions are evaluated independently.

Segmented RNA viruses are ubiquitous pathogens, which include influenza viruses and rotaviruses. A major challenge in understanding their assembly is the combinatorial problem of a non-random selection of a full genomic set of distinct RNAs. This process involves complex RNA-RNA and protein-RNA interactions, which are often obscured by non-specific binding at concentrations approaching in vivo assembly conditions. Here, we present direct experimental evidence of sequence-specific inter-segment interactions between rotavirus RNAs, taking place in a complex RNA- and protein-rich milieu. We show that binding of the rotavirus-encoded non-structural protein NSP2 to viral ssRNAs results in the remodeling of RNA, which is conducive to formation of stable inter-segment contacts. To identify the sites of these interactions, we have developed an RNA-RNA SELEX approach for mapping the sequences involved in inter-segment base-pairing. Our findings elucidate the molecular basis underlying inter-segment interactions in rotaviruses, paving the way for delineating similar RNA-RNA interactions that govern assembly of other segmented RNA viruses.

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