In silico methods for co-transcriptional RNA secondary structure prediction and for investigating alternative RNA structure expression

ShapeSorter: a fully probabilistic method for detecting conserved RNA structure features supported by SHAPE evidence

There is an increased interest in the determination of RNA structures in vivo as it is now possible to probe them in a high-throughput manner, e.g. using SHAPE protocols. By now, there exist a range of computational methods that integrate experimental SHAPE-probing evidence into computational RNA secondary structure prediction. The state-of-the-art in this field is currently provided by computational methods that employ the minimum-free energy strategy for prediction RNA secondary structures with SHAPE-probing evidence. These methods, however, rely on the assumption that transcripts in vivo fold into the thermodynamically most stable configuration and ignore evolutionary evidence for conserved RNA structure features. We here present a new computational method, ShapeSorter, that predicts RNA structure features without employing the thermodynamic strategy. Instead, ShapeSorter employs a fully probabilistic framework to identify RNA structure features that are supported by evolutionary and SHAPE-probing evidence. Our method can capture RNA structure heterogeneity, pseudo-knotted RNA structures as well as transient and mutually exclusive RNA structure features. Moreover, it estimates P-values for the predicted RNA structure features which allows for easy filtering and ranking. We investigate the merits of our method in a comprehensive performance benchmarking and conclude that ShapeSorter has a significantly superior performance for predicting base-pairs than the existing state-of-the-art methods.

Transcription Regulation Through Nascent RNA Folding

Folding of RNA into secondary structures through intramolecular base pairing determines an RNA's three-dimensional architecture and associated function. Simple RNA structures like stem loops can provide specialized functions independent of coding capacity, such as protein binding, regulation of RNA processing and stability, stimulation or inhibition of translation. RNA catalysis is dependent on tertiary structures found in the ribosome, tRNAs and group I and II introns. While the extent to which non-coding RNAs contribute to cellular maintenance is generally appreciated, the fact that both non-coding and coding RNA can assume relevant structural states has only recently gained attention. In particular, the co-transcriptional folding of nascent RNA of all classes has the potential to regulate co-transcriptional processing, RNP (ribonucleoprotein particle) formation, and transcription itself. Riboswitches are established examples of co-transcriptionally folded coding RNAs that directly regulate transcription, mainly in prokaryotes. Here we discuss recent studies in both prokaryotes and eukaryotes showing that structure formation may carry a more widespread regulatory logic during RNA synthesis. Local structures forming close to the catalytic center of RNA polymerases have the potential to regulate transcription by reducing backtracking. In addition, stem loops or more complex structures may alter co-transcriptional RNA processing or its efficiency. Several examples of functional structures have been identified to date, and this review provides an overview of physiologically distinct processes where co-transcriptionally folded RNA plays a role. Experimental approaches such as single-molecule FRET and in vivo structural probing to further advance our insight into the significance of co-transcriptional structure formation are discussed.

The International Virus Bioinformatics Meeting 2020

The International Virus Bioinformatics Meeting 2020 was originally planned to take place in Bern, Switzerland, in March 2020. However, the COVID-19 pandemic put a spoke in the wheel of almost all conferences to be held in 2020. After moving the conference to 8-9 October 2020, we got hit by the second wave and finally decided at short notice to go fully online. On the other hand, the pandemic has made us even more aware of the importance of accelerating research in viral bioinformatics. Advances in bioinformatics have led to improved approaches to investigate viral infections and outbreaks. The International Virus Bioinformatics Meeting 2020 has attracted approximately 120 experts in virology and bioinformatics from all over the world to join the two-day virtual meeting. Despite concerns being raised that virtual meetings lack possibilities for face-to-face discussion, the participants from this small community created a highly interactive scientific environment, engaging in lively and inspiring discussions and suggesting new research directions and questions. The meeting featured five invited and twelve contributed talks, on the four main topics: (1) proteome and RNAome of RNA viruses, (2) viral metagenomics and ecology, (3) virus evolution and classification and (4) viral infections and immunology. Further, the meeting featured 20 oral poster presentations, all of which focused on specific areas of virus bioinformatics. This report summarizes the main research findings and highlights presented at the meeting.

A genetic selection reveals functional metastable structures embedded in a toxin-encoding mRNA

Post-transcriptional regulation plays important roles to fine-tune gene expression in bacteria. In particular, regulation of type I toxin-antitoxin (TA) systems is achieved through sophisticated mechanisms involving toxin mRNA folding. Here, we set up a genetic approach to decipher the molecular underpinnings behind the regulation of a type I TA in Helicobacter pylori. We used the lethality induced by chromosomal inactivation of the antitoxin to select mutations that suppress toxicity. We found that single point mutations are sufficient to allow cell survival. Mutations located either in the 5’ untranslated region or within the open reading frame of the toxin hamper its translation by stabilizing stem-loop structures that sequester the Shine-Dalgarno sequence. We propose that these short hairpins correspond to metastable structures that are transiently formed during transcription to avoid premature toxin expression. This work uncovers the co-transcriptional inhibition of translation as an additional layer of TA regulation in bacteria.

Viroid research and its significance for RNA technology and basic biochemistry

Viroids were described 47 years ago as the smallest RNA molecules capable of infecting plants and autonomously self-replicating without an encoded protein. Work on viroids initiated the development of a number of innovative methods. Novel chromatographic and gelelectrophoretic methods were developed for the purification and characterization of viroids; these methods were later used in molecular biology, gene technology and in prion research. Theoretical and experimental studies of RNA folding demonstrated the general biological importance of metastable structures, and nuclear magnetic resonance spectroscopy of viroid RNA showed the partially covalent nature of hydrogen bonds in biological macromolecules. RNA biochemistry and molecular biology profited from viroid research, such as in the detection of RNA as template of DNA-dependent polymerases and in mechanisms of gene silencing. Viroids, the first circular RNA detected in nature, are important for studies on the much wider spectrum of circular RNAs and other non-coding RNAs.

Prediction of DNA and RNA structure with the NARES-2P force field and conformational space annealing

A physics-based method for the prediction of the structures of nucleic acids, which is based on the physics-based 2-bead NARES-2P model of polynucleotides and global-optimization Conformational Space Annealing (CSA) algorithm has been proposed. The target structure is sought as the global-energy-minimum structure, which ignores the entropy component of the free energy but spares expensive multicanonical simulations necessary to find the conformational ensemble with the lowest free energy. The CSA algorithm has been modified to optimize its performance when treating both single and multi-chain nucleic acids. It was shown that the method finds the native fold for simple RNA molecules and DNA duplexes and with limited distance restraints, which can easily be obtained from the secondary-structure-prediction servers, complex RNA folds can be treated with using moderate computer resources.

Know Your Enemy: Successful Bioinformatic Approaches to Predict Functional RNA Structures in Viral RNAs

Structured RNA elements may control virus replication, transcription and translation, and their distinct features are being exploited by novel antiviral strategies. Viral RNA elements continue to be discovered using combinations of experimental and computational analyses. However, the wealth of sequence data, notably from deep viral RNA sequencing, viromes, and metagenomes, necessitates computational approaches being used as an essential discovery tool. In this review, we describe practical approaches being used to discover functional RNA elements in viral genomes. In addition to success stories in new and emerging viruses, these approaches have revealed some surprising new features of well-studied viruses e.g., human immunodeficiency virus, hepatitis C virus, influenza, and dengue viruses. Some notable discoveries were facilitated by new comparative analyses of diverse viral genome alignments. Importantly, comparative approaches for finding RNA elements embedded in coding and non-coding regions differ. With the exponential growth of computer power we have progressed from stem-loop prediction on single sequences to cutting edge 3D prediction, and from command line to user friendly web interfaces. Despite these advances, many powerful, user friendly prediction tools and resources are underutilized by the virology community.