Encoding folding paths of RNA switches

RNA co-transcriptional folding has long been suspected to play an active role in helping proper native folding of ribozymes and structured regulatory motifs in mRNA untranslated regions. Yet, the underlying mechanisms and coding requirements for efficient co-transcriptional folding remain unclear. Traditional approaches have intrinsic limitations to dissect RNA folding paths, as they rely on sequence mutations or circular permutations that typically perturb both RNA folding paths and equilibrium structures. Here, we show that exploiting sequence symmetries instead of mutations can circumvent this problem by essentially decoupling folding paths from equilibrium structures of designed RNA sequences. Using bistable RNA switches with symmetrical helices conserved under sequence reversal, we demonstrate experimentally that native and transiently formed helices can guide efficient co-transcriptional folding into either long-lived structure of these RNA switches. Their folding path is controlled by the order of helix nucleations and subsequent exchanges during transcription, and may also be redirected by transient antisense interactions. Hence, transient intra- and intermolecular base pair interactions can effectively regulate the folding of nascent RNA molecules into different native structures, provided limited coding requirements, as discussed from an information theory perspective. This constitutive coupling between RNA synthesis and RNA folding regulation may have enabled the early emergence of autonomous RNA-based regulation networks.Comment: 9 pages, 6 figure

Kinefold web server for RNA/DNA folding path and structure prediction including pseudoknots and knots

The Kinefold web server provides a web interface for stochastic folding simulations of nucleic acids on second to minute molecular time scales. Renaturation or co-transcriptional folding paths are simulated at the level of helix formation and dissociation in agreement with the seminal experimental results. Pseudoknots and topologically ‘entangled’ helices (i.e. knots) are efficiently predicted taking into account simple geometrical and topological constraints. To encourage interactivity, simulations launched as immediate jobs are automatically stopped after a few seconds and return adapted recommendations. Users can then choose to continue incomplete simulations using the batch queuing system or go back and modify suggested options in their initial query. Detailed output provide (i) a series of low free energy structures, (ii) an online animated folding path and (iii) a programmable trajectory plot focusing on a few helices of interest to each user. The service can be accessed at

Probing complex RNA structures by mechanical force

RNA secondary structures of increasing complexity are probed combining single molecule stretching experiments and stochastic unfolding/refolding simulations. We find that force-induced unfolding pathways cannot usually be interpretated by solely invoking successive openings of native helices. Indeed, typical force-extension responses of complex RNA molecules are largely shaped by stretching-induced, long-lived intermediates including non-native helices. This is first shown for a set of generic structural motifs found in larger RNA structures, and then for Escherichia coli's 1540-base long 16S ribosomal RNA, which exhibits a surprisingly well-structured and reproducible unfolding pathway under mechanical stretching. Using out-of-equilibrium stochastic simulations, we demonstrate that these experimental results reflect the slow relaxation of RNA structural rearrangements. Hence, micromanipulations of single RNA molecules probe both their native structures and long-lived intermediates, so-called "kinetic traps", thereby capturing -at the single molecular level- the hallmark of RNA folding/unfolding dynamics.Comment: 9 pages, 9 figure

Prediction and statistics of pseudoknots in RNA structures using exactly clustered stochastic simulations

Ab initio RNA secondary structure predictions have long dismissed helices interior to loops, so-called pseudoknots, despite their structural importance. Here, we report that many pseudoknots can be predicted through long time scales RNA folding simulations, which follow the stochastic closing and opening of individual RNA helices. The numerical efficacy of these stochastic simulations relies on an O(n^2) clustering algorithm which computes time averages over a continously updated set of n reference structures. Applying this exact stochastic clustering approach, we typically obtain a 5- to 100-fold simulation speed-up for RNA sequences up to 400 bases, while the effective acceleration can be as high as 100,000-fold for short multistable molecules (<150 bases). We performed extensive folding statistics on random and natural RNA sequences, and found that pseudoknots are unevenly distributed amongst RNAstructures and account for up to 30% of base pairs in G+C rich RNA sequences (Online RNA folding kinetics server including pseudoknots : http://kinefold.u-strasbg.fr/ ).Comment: 6 pages, 5 figure

A complex adaptive systems approach to the kinetic folding of RNA

The kinetic folding of RNA sequences into secondary structures is modeled as a complex adaptive system, the components of which are possible RNA structural rearrangements (SRs) and their associated bases and base pairs. RNA bases and base pairs engage in local stacking interactions that determine the probabilities (or fitnesses) of possible SRs. Meanwhile, selection operates at the level of SRs; an autonomous stochastic process periodically (i.e., from one time step to another) selects a subset of possible SRs for realization based on the fitnesses of the SRs. Using examples based on selected natural and synthetic RNAs, the model is shown to qualitatively reproduce characteristic (nonlinear) RNA folding dynamics such as the attainment by RNAs of alternative stable states. Possible applications of the model to the analysis of properties of fitness landscapes, and of the RNA sequence to structure mapping are discussed.Comment: 23 pages, 4 figures, 2 tables, to be published in BioSystems (Note: updated 2 references

TFIIB aptamers inhibit transcription by perturbing PIC formation at distinct stages

Transcription in eukaryotes is a multistep process involving the assembly and disassembly of numerous inter- and intramolecular interactions between transcription factors and nucleic acids. The roles of each of these interactions and the regions responsible for them have been identified and studied primarily by the use of mutants, which destroy the inherent properties of the interacting surface. A less intrusive but potentially effective way to study the interactions as well as the surfaces responsible for them is the use of RNA aptamers that bind to the interacting factors. Here, we report the isolation and characterization of high-affinity RNA aptamers that bind to the yeast general transcription factor TFIIB. These aptamers fall into two classes that interfere with TFIIB's interactions with either TBP or RNA polymerase II, both of which are crucial for transcription in yeast. We demonstrate the high affinity and specificity of these reagents, their effect on transcription and preinitiation complex formation and discuss their potential use to address mechanistic questions in vitro as well as in vivo

Thermodynamics of RNA structures by Wang–Landau sampling

Motivation: Thermodynamics-based dynamic programming RNA secondary structure algorithms have been of immense importance in molecular biology, where applications range from the detection of novel selenoproteins using expressed sequence tag (EST) data, to the determination of microRNA genes and their targets. Dynamic programming algorithms have been developed to compute the minimum free energy secondary structure and partition function of a given RNA sequence, the minimum free-energy and partition function for the hybridization of two RNA molecules, etc. However, the applicability of dynamic programming methods depends on disallowing certain types of interactions (pseudoknots, zig-zags, etc.), as their inclusion renders structure prediction an nondeterministic polynomial time (NP)-complete problem. Nevertheless, such interactions have been observed in X-ray structures

The RNA Structure of cis-acting Translational Elements of the Chloroplast psbC mRNA in Chlamydomonas reinhardtii

Photosystem II is the first of two light-driven oxidoreductase complexes in oxygenic photosynthesis. The biogenesis of photosystem II requires the synthesis of polypeptide subunits encoded by the genomes in the chloroplast and the nucleus. In the chloroplast of the green alga Chlamydomonas reinhardtii, the synthesis of each subunit requires interactions between the 5′ UTR of the mRNA encoding it and gene-specific translation factors. Here, we analyze the sequences and structures in the 5′ UTR of the psbC mRNA, which are known to be required to promote translation and genetic interaction with TBC1, a nuclear gene required specifically for psbC translation. Results of enzymatic probing in vitro and chemical probing in vivo and in vitro support three secondary structures and reveal that one participates in a pseudoknot structure. Analyses of the effects of mutations affecting pseudoknot sequences, by structural mapping and thermal gradient gel electrophoresis, reveal that flexibility at the base of the major stem-loop is required for translation and higher order RNA conformation, and suggest that this conformation is stabilized by TBC1. This RNA pseudoknot tertiary structure is analogous to the internal ribosome entry sites that promote translation of certain viruses and cellular mRNAs in the nuclear-cytoplasmic systems of eukaryotes

Transat—A Method for Detecting the Conserved Helices of Functional RNA Structures, Including Transient, Pseudo-Knotted and Alternative Structures

The prediction of functional RNA structures has attracted increased interest, as it allows us to study the potential functional roles of many genes. RNA structure prediction methods, however, assume that there is a unique functional RNA structure and also do not predict functional features required for in vivo folding. In order to understand how functional RNA structures form in vivo, we require sophisticated experiments or reliable prediction methods. So far, there exist only a few, experimentally validated transient RNA structures. On the computational side, there exist several computer programs which aim to predict the co-transcriptional folding pathway in vivo, but these make a range of simplifying assumptions and do not capture all features known to influence RNA folding in vivo. We want to investigate if evolutionarily related RNA genes fold in a similar way in vivo. To this end, we have developed a new computational method, Transat, which detects conserved helices of high statistical significance. We introduce the method, present a comprehensive performance evaluation and show that Transat is able to predict the structural features of known reference structures including pseudo-knotted ones as well as those of known alternative structural configurations. Transat can also identify unstructured sub-sequences bound by other molecules and provides evidence for new helices which may define folding pathways, supporting the notion that homologous RNA sequence not only assume a similar reference RNA structure, but also fold similarly. Finally, we show that the structural features predicted by Transat differ from those assuming thermodynamic equilibrium. Unlike the existing methods for predicting folding pathways, our method works in a comparative way. This has the disadvantage of not being able to predict features as function of time, but has the considerable advantage of highlighting conserved features and of not requiring a detailed knowledge of the cellular environment