Pseudoknot length modulates the folding, conformational dynamics, and robustness of Xrn1 resistance of flaviviral xrRNAs.

To understand how RNA dynamics is regulated and connected to its function, we investigate the folding, conformational dynamics and robustness of Xrn1 resistance of a set of flaviviral xrRNAs using SAXS, smFRET and in vitro enzymatic assays. Flaviviral xrRNAs form discrete ring-like 3D structures, in which the length of a conserved long-range pseudoknot (PK2) ranges from 2 bp to 7 bp. We find that xrRNAs' folding, conformational dynamics and Xrn1 resistance are strongly correlated and highly Mg2+-dependent, furthermore, the Mg2+-dependence is modulated by PK2 length variations. xrRNAs with long PK2 require less Mg2+ to stabilize their folding, exhibit reduced conformational dynamics and strong Xrn1 resistance even at low Mg2+, and tolerate mutations at key tertiary motifs at high Mg2+, which generally are destructive to xrRNAs with short PK2. These results demonstrate an unusual regulatory mechanism of RNA dynamics providing insights into the functions and future biomedical applications of xrRNAs.

Complex Conformational Dynamics of the Heart Failure-Associated Pre-miRNA-377 Hairpin Revealed by Single-Molecule Optical Tweezers.

Pre-miRNA-377 is a hairpin-shaped regulatory RNA associated with heart failure. Here, we use single-molecule optical tweezers to unzip pre-miRNA-377 and study its stability and dynamics. We show that magnesium ions have a strong stabilizing effect, and that sodium ions stabilize the hairpin more than potassium ions. The hairpin unfolds in a single step, regardless of buffer composition. Interestingly, hairpin folding occurs either in a single step (type 1) or through the formation of intermediates, in multiple steps (type 2) or gradually (type 3). Type 3 occurs only in the presence of both sodium and magnesium, while type 1 and 2 take place in all buffers, with type 1 being the most prevalent. By reducing the size of the native hairpin loop from fourteen to four nucleotides, we demonstrate that the folding heterogeneity originates from the large size of the hairpin loop. Further, while efficient pre-miRNA-377 binders are lacking, we demonstrate that the recently developed C2 ligand displays bimodal activity: it enhances the mechanical stability of the pre-miRNA-377 hairpin and perturbs its folding. The knowledge regarding pre-miRNA stability and dynamics that we provide is important in understanding its regulatory function and how it can be modulated to achieve a therapeutic effect, e.g., in heart failure treatment.

Conserved long-range base pairings are associated with pre-mRNA processing of human genes.

The ability of nucleic acids to form double-stranded structures is essential for all living systems on Earth. Current knowledge on functional RNA structures is focused on locally-occurring base pairs. However, crosslinking and proximity ligation experiments demonstrated that long-range RNA structures are highly abundant. Here, we present the most complete to-date catalog of conserved complementary regions (PCCRs) in human protein-coding genes. PCCRs tend to occur within introns, suppress intervening exons, and obstruct cryptic and inactive splice sites. Double-stranded structure of PCCRs is supported by decreased icSHAPE nucleotide accessibility, high abundance of RNA editing sites, and frequent occurrence of forked eCLIP peaks. Introns with PCCRs show a distinct splicing pattern in response to RNAPII slowdown suggesting that splicing is widely affected by co-transcriptional RNA folding. The enrichment of 3'-ends within PCCRs raises the intriguing hypothesis that coupling between RNA folding and splicing could mediate co-transcriptional suppression of premature pre-mRNA cleavage and polyadenylation.

Information Encoded by the Flavivirus Genomes beyond the Nucleotide Sequence.

The genus Flavivirus comprises numerous, small, single positive-stranded RNA viruses, many of which are important human pathogens. To store all the information required for their successful propagation, flaviviruses use discrete structural genomic RNA elements to code for functional information by the establishment of dynamic networks of long-range RNA-RNA interactions that promote specific folding. These structural elements behave as true cis-acting, non-coding RNAs (ncRNAs) and have essential regulatory roles in the viral cycle. These include the control of the formation of subgenomic RNAs, known as sfRNAs, via the prevention of the complete degradation of the RNA genome. These sfRNAs are important in ensuring viral fitness. This work summarizes our current knowledge of the functions performed by the genome conformations and the role of RNA-RNA interactions in these functions. It also reviews the role of RNA structure in the production of sfRNAs across the genus Flavivirus, and their existence in related viruses.

Profiling of RNA Structure at Single-Nucleotide Resolution Using nextPARS.

RNA molecules play important roles in almost every cellular process, and their functions are mediated by their sequence and structure. Determining the secondary structure of RNAs is central to understanding RNA function and evolution. RNA structure probing techniques coupled to high-throughput sequencing allow determining structural features of RNA molecules at transcriptome-wide scales. Our group recently developed a novel Illumina-based implementation of in vitro parallel probing of RNA structures called nextPARS.Here, we describe a protocol for the computation of the nextPARS scores and their use to obtain the structural profile (single- or double-stranded state) of an RNA sequence at single-nucleotide resolution.

Perspectives on Viral RNA Genomes and the RNA Folding Problem.

Viral RNA genomes change shape as virus particles disassemble, form replication complexes, attach to ribosomes for translation, evade host defense mechanisms, and assemble new virus particles. These structurally dynamic RNA shapeshifters present a challenging RNA folding problem, because the RNA sequence adopts multiple structures and may sometimes contain regions of partial disorder. Recent advances in high resolution asymmetric cryoelectron microscopy and chemical probing provide new ways to probe the degree of structure and disorder, and have identified more than one conformation in dynamic equilibrium in viral RNA. Chemical probing and the Detection of RNA Folding Ensembles using Expectation Maximization (DREEM) algorithm has been applied to studies of the dynamic equilibrium conformations in HIV RNA in vitro, in virio, and in vivo. This new type of data provides insight into important questions about virus assembly mechanisms and the fundamental physical forces driving virus particle assembly.

Light-controlled twister ribozyme with single-molecule detection resolves RNA function in time and space.

Small ribozymes such as Oryza sativa twister spontaneously cleave their own RNA when the ribozyme folds into its active conformation. The coupling between twister folding and self-cleavage has been difficult to study, however, because the active ribozyme rapidly converts to product. Here, we describe the synthesis of a photocaged nucleotide that releases guanosine within microseconds upon photosolvolysis with blue light. Application of this tool to O. sativa twister achieved the spatial (75 µm) and temporal (≤30 ms) control required to resolve folding and self-cleavage events when combined with single-molecule fluorescence detection of the ribozyme folding pathway. Real-time observation of single ribozymes after photo-deprotection showed that the precleaved folded state is unstable and quickly unfolds if the RNA does not react. Kinetic analysis showed that Mg2+ and Mn2+ ions increase ribozyme efficiency by making transitions to the high energy active conformation more probable, rather than by stabilizing the folded ground state or the cleaved product. This tool for light-controlled single RNA folding should offer precise and rapid control of other nucleic acid systems.

Refolding through a Linear Transition State Enables Fast Temperature Adaptation of a Translational Riboswitch.

The adenine-sensing riboswitch from the Gram-negative bacterium Vibrio vulnificus is an RNA-based gene regulatory element that acts in response to both its cognate low-molecular weight ligand and temperature. The combined sensitivity to environmental temperature and ligand concentration is maintained by an equilibrium of three distinct conformations involving two ligand-free states and one ligand-bound state. The key structural element that undergoes refolding in the ligand-free states comprises a 35-nucleotide temperature response module. Here, we present the structural characterization of this temperature response module. We employ high-resolution NMR spectroscopy and photocaged RNAs as molecular probes to decipher the kinetic and thermodynamic framework of the secondary structure transition in the apo state of the riboswitch. We propose a model for the transition state adopted during the thermal refolding of the temperature response module that connects two mutually exclusive long-lived and stable conformational states. This transition state is characterized by a comparatively low free activation enthalpy. A pseudoknot conformation in the transition state, as commonly seen in RNA refolding, is therefore unlikely. More likely, the transition state of the adenine-sensing riboswitch temperature response module features a linear conformation.

Theory and simulations for RNA folding in mixtures of monovalent and divalent cations.

RNA molecules cannot fold in the absence of counterions. Experiments are typically performed in the presence of monovalent and divalent cations. How to treat the impact of a solution containing a mixture of both ion types on RNA folding has remained a challenging problem for decades. By exploiting the large concentration difference between divalent and monovalent ions used in experiments, we develop a theory based on the reference interaction site model (RISM), which allows us to treat divalent cations explicitly while keeping the implicit screening effect due to monovalent ions. Our theory captures both the inner shell and outer shell coordination of divalent cations to phosphate groups, which we demonstrate is crucial for an accurate calculation of RNA folding thermodynamics. The RISM theory for ion-phosphate interactions when combined with simulations based on a transferable coarse-grained model allows us to predict accurately the folding of several RNA molecules in a mixture containing monovalent and divalent ions. The calculated folding free energies and ion-preferential coefficients for RNA molecules (pseudoknots, a fragment of the rRNA, and the aptamer domain of the adenine riboswitch) are in excellent agreement with experiments over a wide range of monovalent and divalent ion concentrations. Because the theory is general, it can be readily used to investigate ion and sequence effects on DNA properties.

Complex dynamics under tension in a high-efficiency frameshift stimulatory structure.

Specific structures in mRNA can stimulate programmed ribosomal frameshifting (PRF). PRF efficiency can vary enormously between different stimulatory structures, but the features that lead to efficient PRF stimulation remain uncertain. To address this question, we studied the structural dynamics of the frameshift signal from West Nile virus (WNV), which stimulates -1 PRF at very high levels and has been proposed to form several different structures, including mutually incompatible pseudoknots and a double hairpin. Using optical tweezers to apply tension to single mRNA molecules, mimicking the tension applied by the ribosome during PRF, we found that the WNV frameshift signal formed an unusually large number of different metastable structures, including all of those previously proposed. From force-extension curve measurements, we mapped 2 mutually exclusive pathways for the folding, each encompassing multiple intermediates. We identified the intermediates in each pathway from length changes and the effects of antisense oligomers blocking formation of specific contacts. Intriguingly, the number of transitions between the different conformers of the WNV frameshift signal was maximal in the range of forces applied by the ribosome during -1 PRF. Furthermore, the occupancy of the pseudoknotted conformations was far too low for static pseudoknots to account for the high levels of -1 PRF. These results support the hypothesis that conformational heterogeneity plays a key role in frameshifting and suggest that transitions between different conformers under tension are linked to efficient PRF stimulation.

The roles of structural dynamics in the cellular functions of RNAs.

RNAs fold into 3D structures that range from simple helical elements to complex tertiary structures and quaternary ribonucleoprotein assemblies. The functions of many regulatory RNAs depend on how their 3D structure changes in response to a diverse array of cellular conditions. In this Review, we examine how the structural characterization of RNA as dynamic ensembles of conformations, which form with different probabilities and at different timescales, is improving our understanding of RNA function in cells. We discuss the mechanisms of gene regulation by microRNAs, riboswitches, ribozymes, post-transcriptional RNA modifications and RNA-binding proteins, and how the cellular environment and processes such as liquid-liquid phase separation may affect RNA folding and activity. The emerging RNA-ensemble-function paradigm is changing our perspective and understanding of RNA regulation, from in vitro to in vivo and from descriptive to predictive.

Folding, Assembly, and Persistence: The Essential Nature and Origins of Biopolymers.

Life as we know it requires three basic types of polymers: polypeptide, polynucleotide, and polysaccharide. Here we evaluate both universal and idiosyncratic characteristics of these biopolymers. We incorporate this information into a model that explains much about their origins, selection, and early evolution. We observe that all three biopolymer types are pre-organized, conditionally self-complementary, chemically unstable in aqueous media yet persistent because of kinetic trapping, with chiral monomers and directional chains. All three biopolymers are synthesized by dehydration reactions that are catalyzed by molecular motors driven by hydrolysis of phosphorylated nucleosides. All three biopolymers can access specific states that protect against hydrolysis. These protected states are folded, using self-complementary interactions among recurrent folding elements within a given biopolymer, or assembled, in associations between the same or different biopolymer types. Self-association in a hydrolytic environment achieves self-preservation. Heterogeneous association achieves partner-preservation. These universal properties support a model in which life's polymers emerged simultaneously and co-evolved in a common hydrolytic milieu where molecular persistence depended on folding and assembly. We believe that an understanding of the structure, function, and origins of any given type of biopolymer requires the context of other biopolymers.

Effects of Preferential Counterion Interactions on the Specificity of RNA Folding.

The real-time search for native RNA structure is essential for the operation of regulatory RNAs. We previously reported that a fraction of the Azoarcus ribozyme achieves a compact structure in less than a millisecond. To scrutinize the forces that drive initial folding steps, we used time-resolved SAXS to compare the folding dynamics of this ribozyme in thermodynamically isostable concentrations of different counterions. The results show that the size of the fast-folding population increases with the number of available counterions and correlates with the flexibility of initial RNA structures. Within 1 ms of folding, Mg2+ exhibits a smaller preferential interaction coefficient per charge, ΔΓ+/ Z, than Na+ or [Co(NH3)6]3+. The lower ΔΓ+/ Z corresponds to a smaller yield of folded RNA, although Mg2+ stabilizes native RNA more efficiently than other ions at equilibrium. These results suggest that strong Mg2+-RNA interactions impede the search for globally native structure during early folding stages.

Interactive implementations of thermodynamics-based RNA structure and RNA-RNA interaction prediction approaches for example-driven teaching.

The investigation of RNA-based regulation of cellular processes is becoming an increasingly important part of biological or medical research. For the analysis of this type of data, RNA-related prediction tools are integrated into many pipelines and workflows. In order to correctly apply and tune these programs, the user has to have a precise understanding of their limitations and concepts. Within this manuscript, we provide the mathematical foundations and extract the algorithmic ideas that are core to state-of-the-art RNA structure and RNA-RNA interaction prediction algorithms. To allow the reader to change and adapt the algorithms or to play with different inputs, we provide an open-source web interface to JavaScript implementations and visualizations of each algorithm. The conceptual, teaching-focused presentation enables a high-level survey of the approaches, while providing sufficient details for understanding important concepts. This is boosted by the simple generation and study of examples using the web interface available at http://rna.informatik.uni-freiburg.de/Teaching/. In combination, we provide a valuable resource for teaching, learning, and understanding the discussed prediction tools and thus enable a more informed analysis of RNA-related effects.

Solving the RNA design problem with reinforcement learning.

We use reinforcement learning to train an agent for computational RNA design: given a target secondary structure, design a sequence that folds to that structure in silico. Our agent uses a novel graph convolutional architecture allowing a single model to be applied to arbitrary target structures of any length. After training it on randomly generated targets, we test it on the Eterna100 benchmark and find it outperforms all previous algorithms. Analysis of its solutions shows it has successfully learned some advanced strategies identified by players of the game Eterna, allowing it to solve some very difficult structures. On the other hand, it has failed to learn other strategies, possibly because they were not required for the targets in the training set. This suggests the possibility that future improvements to the training protocol may yield further gains in performance.

Predicting 3D structure and stability of RNA pseudoknots in monovalent and divalent ion solutions.

RNA pseudoknots are a kind of minimal RNA tertiary structural motifs, and their three-dimensional (3D) structures and stability play essential roles in a variety of biological functions. Therefore, to predict 3D structures and stability of RNA pseudoknots is essential for understanding their functions. In the work, we employed our previously developed coarse-grained model with implicit salt to make extensive predictions and comprehensive analyses on the 3D structures and stability for RNA pseudoknots in monovalent/divalent ion solutions. The comparisons with available experimental data show that our model can successfully predict the 3D structures of RNA pseudoknots from their sequences, and can also make reliable predictions for the stability of RNA pseudoknots with different lengths and sequences over a wide range of monovalent/divalent ion concentrations. Furthermore, we made comprehensive analyses on the unfolding pathway for various RNA pseudoknots in ion solutions. Our analyses for extensive pseudokonts and the wide range of monovalent/divalent ion concentrations verify that the unfolding pathway of RNA pseudoknots is mainly dependent on the relative stability of unfolded intermediate states, and show that the unfolding pathway of RNA pseudoknots can be significantly modulated by their sequences and solution ion conditions.

Allele-specific SHAPE-MaP assessment of the effects of somatic variation and protein binding on mRNA structure.

The impact of inherited and somatic mutations on messenger RNA (mRNA) structure remains poorly understood. Recent technological advances that leverage next-generation sequencing to obtain experimental structure data, such as SHAPE-MaP, can reveal structural effects of mutations, especially when these data are incorporated into structure modeling. Here, we analyze the ability of SHAPE-MaP to detect the relatively subtle structural changes caused by single-nucleotide mutations. We find that allele-specific sorting greatly improved our detection ability. Thus, we used SHAPE-MaP with a novel combination of clone-free robotic mutagenesis and allele-specific sorting to perform a rapid, comprehensive survey of noncoding somatic and inherited riboSNitches in two cancer-associated mRNAs, TPT1 and LCP1 Using rigorous thermodynamic modeling of the Boltzmann suboptimal ensemble, we identified a subset of mutations that change TPT1 and LCP1 RNA structure, with approximately 14% of all variants identified as riboSNitches. To confirm that these in vitro structures were biologically relevant, we tested how dependent TPT1 and LCP1 mRNA structures were on their environments. We performed SHAPE-MaP on TPT1 and LCP1 mRNAs in the presence or absence of cellular proteins and found that both mRNAs have similar overall folds in all conditions. RiboSNitches identified within these mRNAs in vitro likely exist under biological conditions. Overall, these data reveal a robust mRNA structural landscape where differences in environmental conditions and most sequence variants do not significantly alter RNA structural ensembles. Finally, predicting riboSNitches in mRNAs from sequence alone remains particularly challenging; these data will provide the community with benchmarks for further algorithmic development.

RNA design using simulated SHAPE data.

It has long been established that in addition to being involved in protein translation, RNA plays essential roles in numerous other cellular processes, including gene regulation and DNA replication. Such roles are known to be dictated by higher-order structures of RNA molecules. It is therefore of prime importance to find an RNA sequence that can fold to acquire a particular function that is desirable for use in pharmaceuticals and basic research. The challenge of finding an RNA sequence for a given structure is known as the RNA design problem. Although there are several algorithms to solve this problem, they mainly consider hard constraints, such as minimum free energy, to evaluate the predicted sequences. Recently, SHAPE data has emerged as a new soft constraint for RNA secondary structure prediction. To take advantage of this new experimental constraint, we report here a new method for accurate design of RNA sequences based on their secondary structures using SHAPE data as pseudo-free energy. We then compare our algorithm with four others: INFO-RNA, ERD, MODENA and RNAifold 2.0. Our algorithm precisely predicts 26 out of 29 new sequences for the structures extracted from the Rfam dataset, while the other four algorithms predict no more than 22 out of 29. The proposed algorithm is comparable to the above algorithms on RNA-SSD datasets, where they can predict up to 33 appropriate sequences for RNA secondary structures out of 34.

Effect of Population Size and Mutation Rate on the Evolution of RNA Sequences on an Adaptive Landscape Determined by RNA Folding.

The dynamics of populations evolving on an adaptive landscape depends on multiple factors, including the structure of the landscape, the rate of mutations, and effective population size. Existing theoretical work often makes ad hoc and simplifying assumptions about landscape structure, whereas experimental work can vary important parameters only to a limited extent. We here overcome some of these limitations by simulating the adaptive evolution of RNA molecules, whose fitness is determined by the thermodynamics of RNA secondary structure folding. We study the influence of mutation rates and population sizes on final mean population fitness, on the substitution rates of mutations, and on population diversity. We show that evolutionary dynamics cannot be understood as a function of mutation rate µ, population size N, or population mutation rate Nµ alone. For example, at a given mutation rate, clonal interference prevents the fixation of beneficial mutations as population size increases, but larger populations still arrive at a higher mean fitness. In addition, at the highest population mutation rates we study, mean final fitness increases with population size, because small populations are driven to low fitness by the relatively higher incidence of mutations they experience. Our observations show that mutation rate and population size can interact in complex ways to influence the adaptive dynamics of a population on a biophysically motivated fitness landscape.

LRPPRC-mediated folding of the mitochondrial transcriptome.

The expression of the compact mammalian mitochondrial genome requires transcription, RNA processing, translation and RNA decay, much like the more complex chromosomal systems, and here we use it as a model system to understand the fundamental aspects of gene expression. Here we combine RNase footprinting with PAR-CLIP at unprecedented depth to reveal the importance of RNA-protein interactions in dictating RNA folding within the mitochondrial transcriptome. We show that LRPPRC, in complex with its protein partner SLIRP, binds throughout the mitochondrial transcriptome, with a preference for mRNAs, and its loss affects the entire secondary structure and stability of the transcriptome. We demonstrate that the LRPPRC-SLIRP complex is a global RNA chaperone that stabilizes RNA structures to expose the required sites for translation, stabilization, and polyadenylation. Our findings reveal a general mechanism where extensive RNA-protein interactions ensure that RNA is accessible for its biological functions.