Author response: Pausing guides RNA folding to populate transiently stable RNA structures for riboswitch-based transcription regulation

AbstractThe 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.

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The global and local distribution of RNA structure throughout the SARS-CoV-2 genome

Journal of Virology ◽

10.1128/jvi.02190-20 ◽

2020 ◽

Cited By ~ 2

Author(s):

Rafael de Cesaris Araujo Tavares ◽

Gandhar Mahadeshwar ◽

Han Wan ◽

Nicholas C. Huston ◽

Anna Marie Pyle

Keyword(s):

In Silico ◽

Rna Structure ◽

Drug Targets ◽

Rna Folding ◽

Rna Viruses ◽

Viral Agent ◽

Rna Structures ◽

Viral Rnas ◽

Viral Genomes ◽

Rna Genome

SARS-CoV-2 is the causative viral agent of COVID-19, the disease at the center of the current global pandemic. While knowledge of highly structured regions is integral for mechanistic insights into the viral infection cycle, very little is known about the location and folding stability of functional elements within the massive, ∼30kb SARS-CoV-2 RNA genome. In this study, we analyze the folding stability of this RNA genome relative to the structural landscape of other well-known viral RNAs. We present an in-silico pipeline to predict regions of high base pair content across long genomes and to pinpoint hotspots of well-defined RNA structures, a method that allows for direct comparisons of RNA structural complexity within the several domains in SARS-CoV-2 genome. We report that the SARS-CoV-2 genomic propensity for stable RNA folding is exceptional among RNA viruses, superseding even that of HCV, one of the most structured viral RNAs in nature. Furthermore, our analysis suggests varying levels of RNA structure across genomic functional regions, with accessory and structural ORFs containing the highest structural density in the viral genome. Finally, we take a step further to examine how individual RNA structures formed by these ORFs are affected by the differences in genomic and subgenomic contexts, which given the technical difficulty of experimentally separating cellular mixtures of sgRNA from gRNA, is a unique advantage of our in-silico pipeline. The resulting findings provide a useful roadmap for planning focused empirical studies of SARS-CoV-2 RNA biology, and a preliminary guide for exploring potential SARS-CoV-2 RNA drug targets. Importance The RNA genome of SARS-CoV-2 is among the largest and most complex viral genomes, and yet its RNA structural features remain relatively unexplored. Since RNA elements guide function in most RNA viruses, and they represent potential drug targets, it is essential to chart the architectural features of SARS-CoV-2 and pinpoint regions that merit focused study. Here we show that RNA folding stability of SARS-CoV-2 genome is exceptional among viral genomes and we develop a method to directly compare levels of predicted secondary structure across SARS-CoV-2 domains. Remarkably, we find that coding regions display the highest structural propensity in the genome, forming motifs that differ between the genomic and subgenomic contexts. Our approach provides an attractive strategy to rapidly screen for candidate structured regions based on base pairing potential and provides a readily interpretable roadmap to guide functional studies of RNA viruses and other pharmacologically relevant RNA transcripts.

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Cotranscriptional kinetic folding of RNA secondary structures

10.1101/2020.07.10.196972 ◽

2020 ◽

Author(s):

Vo Hong Thanh ◽

Pekka Orponen

Keyword(s):

Structure Formation ◽

Rna Structure ◽

Rna Folding ◽

Computational Prediction ◽

Simulation Method ◽

Rna Structures ◽

Rna Molecules ◽

Primitive Operation ◽

Nucleotide Resolution ◽

Kinetics Of

Computational prediction of RNA structures is an important problem in computational structural biology. Studies of RNA structure formation often assume that the process starts from a fully synthesized sequence. Experimental evidence, however, has shown that RNA folds concurrently with its elongation. We investigate RNA structure formation, taking into account also the cotranscriptional effects. We propose a single-nucleotide resolution kinetic model of the folding process of RNA molecules, where the polymerase-driven elongation of an RNA strand by a new nucleotide is included as a primitive operation, together with a stochastic simulation method that implements this folding concurrently with the transcriptional synthesis. Numerical case studies show that our cotranscriptional RNA folding model can predict the formation of metastable conformations that are favored in actual biological systems. Our new computational tool can thus provide quantitative predictions and offer useful insights into the kinetics of RNA folding.

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Distributed Biotin-Streptavidin Transcription Roadblocks for Mapping Cotranscriptional RNA Folding

10.1101/100073 ◽

2017 ◽

Author(s):

Eric J. Strobel ◽

Kyle E. Watters ◽

Julius B. Lucks

Keyword(s):

Experimental Study ◽

Rna Structure ◽

Rna Folding ◽

Folding Pathway ◽

Decision Making Process ◽

Important Process ◽

Rna Structures ◽

Rna Molecules ◽

Fundamental Properties ◽

Nucleotide Resolution

AbstractRNA molecules fold cotranscriptionally as they emerge from RNA polymerase. Cotranscriptional folding is an important process for proper RNA structure formation as the order of folding can determine an RNA molecule’s structure, and thus its functional properties. Despite its fundamental importance, the experimental study of RNA cotranscriptional folding has been limited by the lack of easily approachable methods that can interrogate nascent RNA structures at nucleotide resolution during transcription. We previously developed cotranscriptional selective 2’-hydroxyl acylation analyzed by primer extension sequencing (SHAPE-seq) to simultaneously probe all of the intermediate structures an RNA molecule transitions through during transcription elongation. Here, we improve the broad applicability of cotranscriptional SHAPE-Seq by developing a sequence-independent streptavidin roadblocking strategy to simplify the preparation of roadblocking transcription templates. We determine the fundamental properties of streptavidin roadblocks and show that randomly distributed streptavidin roadblocks can be used in cotranscriptional SHAPE-Seq experiments to measure the Bacillus cereus crcB fluoride riboswitch folding pathway. Comparison of EcoRIE111Q and streptavidin roadblocks in cotranscriptional SHAPE-Seq data shows that both strategies identify the same RNA structural transitions related to the riboswitch decision-making process. Finally, we propose guidelines to leverage the complementary strengths of each transcription roadblock for use in studying cotranscriptional folding.

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Characteristics and Prediction of RNA Structure

BioMed Research International ◽

10.1155/2014/690340 ◽

2014 ◽

Vol 2014 ◽

pp. 1-10

Author(s):

Hengwu Li ◽

Daming Zhu ◽

Caiming Zhang ◽

Huijian Han ◽

Keith A. Crandall

Keyword(s):

Rna Structure ◽

Structure Prediction ◽

Rna Folding ◽

Golden Section ◽

Hierarchical Structures ◽

Secondary Structures ◽

Sequence Length ◽

Rna Structures ◽

Rna Secondary Structures ◽

Hierarchical Folding

RNA secondary structures with pseudoknots are often predicted by minimizing free energy, which is NP-hard. Most RNAs fold during transcription from DNA into RNA through a hierarchical pathway wherein secondary structures form prior to tertiary structures. Real RNA secondary structures often have local instead of global optimization because of kinetic reasons. The performance of RNA structure prediction may be improved by considering dynamic and hierarchical folding mechanisms. This study is a novel report on RNA folding that accords with the golden mean characteristic based on the statistical analysis of the real RNA secondary structures of all 480 sequences from RNA STRAND, which are validated by NMR or X-ray. The length ratios of domains in these sequences are approximately 0.382L, 0.5L, 0.618L, andL, whereLis the sequence length. These points are just the important golden sections of sequence. With this characteristic, an algorithm is designed to predict RNA hierarchical structures and simulate RNA folding by dynamically folding RNA structures according to the above golden section points. The sensitivity and number of predicted pseudoknots of our algorithm are better than those of the Mfold, HotKnots, McQfold, ProbKnot, and Lhw-Zhu algorithms. Experimental results reflect the folding rules of RNA from a new angle that is close to natural folding.

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Author response: RNA structures that resist degradation by Xrn1 produce a pathogenic Dengue virus RNA

10.7554/elife.01892.021 ◽

2014 ◽

Author(s):

Erich G Chapman ◽

Stephanie L Moon ◽

Jeffrey Wilusz ◽

Jeffrey S Kieft

Keyword(s):

Dengue Virus ◽

Author Response ◽

Rna Structures ◽

Virus Rna

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Building the library of RNA 3D nucleotide conformations using the clustering approach

International Journal of Applied Mathematics and Computer Science ◽

10.1515/amcs-2015-0050 ◽

2015 ◽

Vol 25 (3) ◽

pp. 689-700 ◽

Cited By ~ 2

Author(s):

Tomasz Zok ◽

Maciej Antczak ◽

Martin Riedel ◽

David Nebel ◽

Thomas Villmann ◽

...

Keyword(s):

Structure Prediction ◽

Rna Folding ◽

Three Dimensional ◽

Rna Structures ◽

Neural Gas ◽

Levels Of Detail ◽

Data Points ◽

Clustering Approach ◽

Automated Methods ◽

Different Levels

Abstract An increasing number of known RNA 3D structures contributes to the recognition of various RNA families and identification of their features. These tasks are based on an analysis of RNA conformations conducted at different levels of detail. On the other hand, the knowledge of native nucleotide conformations is crucial for structure prediction and understanding of RNA folding. However, this knowledge is stored in structural databases in a rather distributed form. Therefore, only automated methods for sampling the space of RNA structures can reveal plausible conformational representatives useful for further analysis. Here, we present a machine learning-based approach to inspect the dataset of RNA three-dimensional structures and to create a library of nucleotide conformers. A median neural gas algorithm is applied to cluster nucleotide structures upon their trigonometric description. The clustering procedure is two-stage: (i) backbone- and (ii) ribose-driven. We show the resulting library that contains RNA nucleotide representatives over the entire data, and we evaluate its quality by computing normal distribution measures and average RMSD between data points as well as the prototype within each cluster.

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RNA structures that resist degradation by Xrn1 produce a pathogenic Dengue virus RNA

eLife ◽

10.7554/elife.01892 ◽

2014 ◽

Vol 3 ◽

Cited By ~ 122

Author(s):

Erich G Chapman ◽

Stephanie L Moon ◽

Jeffrey Wilusz ◽

Jeffrey S Kieft

Keyword(s):

Dengue Virus ◽

Rna Structure ◽

Noncoding Rna ◽

Rna Folding ◽

Rna Degradation ◽

Rna Structures ◽

Genomic Rna ◽

Virus Rna ◽

Folded Rna ◽

Viral Genomic Rna

Dengue virus is a growing global health threat. Dengue and other flaviviruses commandeer the host cell’s RNA degradation machinery to generate the small flaviviral RNA (sfRNA), a noncoding RNA that induces cytopathicity and pathogenesis. Host cell exonuclease Xrn1 likely loads on the 5′ end of viral genomic RNA and degrades processively through ∼10 kB of RNA, halting near the 3′ end of the viral RNA. The surviving RNA is the sfRNA. We interrogated the architecture of the complete Dengue 2 sfRNA, identifying five independently-folded RNA structures, two of which quantitatively confer Xrn1 resistance. We developed an assay for real-time monitoring of Xrn1 resistance that we used with mutagenesis and RNA folding experiments to show that Xrn1-resistant RNAs adopt a specific fold organized around a three-way junction. Disrupting the junction’s fold eliminates the buildup of disease-related sfRNAs in human cells infected with a flavivirus, directly linking RNA structure to sfRNA production.

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