High-throughput determination of RNA structures

UFold: fast and accurate RNA secondary structure prediction with deep learning

For many RNA molecules, the secondary structure is essential for the correct function of the RNA. Predicting RNA secondary structure from nucleotide sequences is a long-standing problem in genomics, but the prediction performance has reached a plateau over time. Traditional RNA secondary structure prediction algorithms are primarily based on thermodynamic models through free energy minimization, which imposes strong prior assumptions and is slow to run. Here, we propose a deep learning-based method, called UFold, for RNA secondary structure prediction, trained directly on annotated data and base-pairing rules. UFold proposes a novel image-like representation of RNA sequences, which can be efficiently processed by Fully Convolutional Networks (FCNs). We benchmark the performance of UFold on both within- and cross-family RNA datasets. It significantly outperforms previous methods on within-family datasets, while achieving a similar performance as the traditional methods when trained and tested on distinct RNA families. UFold is also able to predict pseudoknots accurately. Its prediction is fast with an inference time of about 160 ms per sequence up to 1500 bp in length. An online web server running UFold is available at https://ufold.ics.uci.edu. Code is available at https://github.com/uci-cbcl/UFold.

Nuclear Magnetic Resonance Spectra and AMBER OL3 and ROC-RNA Simulations of UCUCGU Reveal Force Field Strengths and Weaknesses for Single-Stranded RNA

Single-stranded regions of RNA are important for folding of sequences into 3D structures and for design of therapeutics targeting RNA. Prediction of ensembles of 3D structures for single-stranded regions often involves classical mechanical approximations of interactions defined by quantum mechanical calculations on small model systems. Nuclear magnetic resonance (NMR) spectra and molecular dynamics (MD) simulations of short single strands provide tests for how well the approximations model many of the interactions. Here, the NMR spectra for UCUCGU at 2, 15, and 30 °C are compared to simulations with the AMBER force fields, OL3 and ROC-RNA. This is the first such comparison to an oligoribonucleotide containing an internal guanosine nucleotide (G). G is particularly interesting because of its many H-bonding groups, large dipole moment, and proclivity for both syn and anti conformations. Results reveal formation of a G amino to phosphate non-bridging oxygen H-bond. The results also demonstrate dramatic differences in details of the predicted structures. The variations emphasize the dependence of predictions on individual parameters and their balance with the rest of the force field. The NMR data can serve as a benchmark for future force fields.

Curcumin-embedded DBPC liposomes coated with chitosan layer as a fluorescence nanosensor for the selective detection of ribonucleic acid

One of the limitations of fluorescence probe molecules during biomedical estimation is their lack of ability to selectively determine the targeted species. To overcome this there have been various approaches that involve attaching a functional group or aptamers to the fluorescence probe. However, encapsulating probe molecules in a matrix using nanotechnology can be a viable and easier method. Curcumin (Cur) as a fluorescence marker cannot distinguish DNA and RNA. This research reports a novel selective approach involving the use of nanocapsules composed of liposomal curcumin coated with chitosan for the selective detection of RNA molecules using a fluorescence method. The increase in RNA concentration enhanced the electrostatic interaction between the negatively charge surface of RNA and the positively charged nanocapsule, which was further verified by zeta potential measurement. This method had a low limit of detection (36 ng/ml) and higher linear dynamic ranges compared with other studies found in the literature. Moreover, the method was not affected by DNA and was selective for the detection of RNA molecules for which the site of interaction was confined only to uracil. The selectivity for RNA molecules towards other analogues species was also examined and recovery range found was between 99 and 100.33%.

Cotranscriptional RNA Chemical Probing

Cotranscriptional folding is a fundamental step in RNA biogenesis and the basis for many RNA-mediated gene regulation systems. Understanding how RNA folds as it is synthesized requires experimental methods that can systematically identify intermediate RNA structures that form during transcription. Cotranscriptional RNA chemical probing experiments achieve this by applying high-throughput RNA structure probing to an in vitro transcribed array of cotranscriptionally folded intermediate transcripts. In this chapter, we present guidelines and procedures for integrating single-round in vitro transcription using E. coli RNA polymerase with high-throughput RNA chemical probing workflows. We provide an overview of key concepts including DNA template design, transcription roadblocking strategies, single-round in vitro transcription with E. coli RNA polymerase, and RNA chemical probing and describe procedures for DNA template preparation, cotranscriptional RNA chemical probing, RNA purification, and 3' adapter ligation. The end result of these procedures is a purified RNA library that can be prepared for Illumina sequencing using established high-throughput RNA structure probing library construction strategies.

RNA Structure Prediction, Analysis, and Design: An Introduction to Web-Based Tools

Understanding RNA structure has become critical in the study of RNA in their roles as mediators of biological processes. To aid in these studies, computational algorithms that utilize thermodynamics have been developed to predict RNA secondary structure. Due to the importance of intermolecular interactions, the algorithms have been expanded to determine and predict RNA-RNA hybridization. This chapter discusses popular webservers with the tools for RNA secondary structure prediction, RNA-RNA hybridization, and design. We address key features that distinguish common-functioning programs and their purposes for the interests of the user. Ultimately, we hope this review elucidates web-based tools researchers may take advantage of in their investigations of RNA structure and function.

An ultra low-input method for global RNA structure probing uncovers Regnase-1-mediated regulation in macrophages

To enable diverse functions and precise regulation, an RNA sequence often folds into complex yet distinct structures in different cellular states. Probing RNA in its native environment is essential to uncovering RNA structures of biological contexts. However, current methods generally require large amounts of input RNA and are challenging for physiologically relevant use. Here, we report smartSHAPE, a new RNA structure probing method that requires very low amounts of RNA input due to the largely reduced artefact of probing signals and increased efficiency of library construction. Using smartSHAPE, we showcased the profiling of the RNA structure landscape of mouse intestinal macrophages upon inflammation, and provided evidence that RNA conformational changes regulate immune responses. These results demonstrate that smartSHAPE can greatly expand the scope of RNA structure-based investigations in practical biological systems, and also provide a research paradigm for the study of post-transcriptional regulation.

Characterizing hydrogen bonds in intact RNA from MS2 bacteriophage using magic angle spinning NMR

RNA is a polymer with pivotal functions in many biological processes. RNA structure determination is thus a vital step toward understanding its function. The secondary structure of RNA is stabilized by hydrogen bonds formed between nucleotide basepairs, and it defines the positions and shapes of functional stem-loops, internal loops, bulges, and other functional and structural elements. In this work, we present a methodology for studying large intact RNA biomolecules using homonuclear ¹⁵N solid-state NMR spectroscopy. We show that proton-driven spin-diffusion experiments with long mixing times, up to 16 s, improved by the incorporation of multiple rotor-synchronous ¹H inversion pulses (termed radio-frequency dipolar recoupling pulses), reveal key hydrogen-bond contacts. In the full-length RNA isolated from MS2 phage, we observed strong and dominant contributions of guanine-cytosine Watson-Crick basepairs, and beyond these common interactions, we observe a significant contribution of the guanine-uracil wobble basepairs. Moreover, we can differentiate basepaired and non-basepaired nitrogen atoms. Using the improved technique facilitates characterization of hydrogen-bond types in intact large-scale RNA using solid-state NMR. It can be highly useful to guide secondary structure prediction techniques and possibly structure determination methods.

In Vitro Methods to Decipher the Structure of Viral RNA Genomes

RNA viruses encode essential information in their genomes as conserved structural elements that are involved in efficient viral protein synthesis, replication, and encapsidation. These elements can also establish complex networks of RNA-RNA interactions, the so-called RNA interactome, to shape the viral genome and control different events during intracellular infection. In recent years, targeting these conserved structural elements has become a promising strategy for the development of new antiviral tools due to their sequence and structural conservation. In this context, RNA-based specific therapeutic strategies, such as the use of siRNAs have been extensively pursued to target the genome of different viruses. Importantly, siRNA-mediated targeting is not a straightforward approach and its efficiency is highly dependent on the structure of the target region. Therefore, the knowledge of the viral structure is critical for the identification of potentially good target sites. Here, we describe detailed protocols used in our laboratory for the in vitro study of the structure of viral RNA genomes. These protocols include DMS (dimethylsulfate) probing, SHAPE (selective 2'-hydroxyl acylation analyzed by primer extension) analysis, and HMX (2'-hydroxyl molecular interference). These methodologies involve the use of high-throughput analysis techniques that provide extensive information about the 3D folding of the RNA under study and the structural tuning derived from the interactome activity. They are therefore a good tool for the development of new RNA-based antiviral compounds.

Diverse functional elements in RNA predicted transcriptome-wide by orthogonal RNA structure probing

RNA molecules can fold into complex structures and interact with trans-acting factors to control their biology. Recent methods have been focused on developing novel tools to measure RNA structure transcriptome-wide, but their utility to study and predict RNA-protein interactions or RNA processing has been limited thus far. Here, we extend these studies with the first transcriptome-wide mapping method for cataloging RNA solvent accessibility, icLASER. By combining solvent accessibility (icLASER) with RNA flexibility (icSHAPE) data, we efficiently predict RNA-protein interactions transcriptome-wide and catalog RNA polyadenylation sites by RNA structure alone. These studies showcase the power of designing novel chemical approaches to studying RNA biology. Further, our study exemplifies merging complementary methods to measure RNA structure inside cells and its utility for predicting transcriptome-wide interactions that are critical for control of and regulation by RNA structure. We envision such approaches can be applied to studying different cell types or cells under varying conditions, using RNA structure and footprinting to characterize cellular interactions and processing involving RNA.

Piercing the fog of the RNA structure-ome

Machine learning is poised to transform RNA structure and function discovery

Predicting RNA Scaffolds with a Hybrid Method of Vfold3D and VfoldLA

The ever-increasing discoveries of noncoding RNA functions draw a strong demand for RNA structure determination from the sequence. In recently years, computational studies for RNA structures, at both the two-dimensional and the three-dimensional levels, led to several highly promising new developments. In this chapter, we describe a hybrid method, which combines the motif template-based Vfold3D model and the loop template-based VfoldLA model, to predict RNA 3D structures. The main emphasis is placed on the definition of motifs and loops, the treatment of no-template motifs, and the 3D structure assembly from templates of motifs and loops. For illustration, we use the ZIKV xrRNA1 as an example to show the template-based prediction of RNA 3D structures from the 2D structure. The web server for the hybrid model is freely accessible at http://rna.physics.missouri.edu/vfold3D2 .

RNA structure probing uncovers RNA structure-dependent biological functions

RNA molecules fold into complex structures that enable their diverse functions in cells. Recent revolutionary innovations in transcriptome-wide RNA structural probing of living cells have ushered in a new era in understanding RNA functions. Here, we summarize the latest technological advances for probing RNA secondary structures and discuss striking discoveries that have linked RNA regulation and biological processes through interrogation of RNA structures. In particular, we highlight how different long noncoding RNAs form into distinct secondary structures that determine their modes of interactions with protein partners to realize their unique functions. These dynamic structures mediate RNA regulatory functions through altering interactions with proteins and other RNAs. We also outline current methodological hurdles and speculate about future directions for development of the next generation of RNA structure-probing technologies of higher sensitivity and resolution, which could then be applied in increasingly physiologically relevant studies.

In Vivo RNA Chemical Footprinting Analysis in Archaea

RNA structural conformation and dynamics govern the functional properties of all RNA/RNP. Accordingly, defining changes of RNA structure and dynamics in various conditions may provide detailed insight into how RNA structural properties regulate the function of RNA/RNP. Traditional chemical footprinting analysis using chemical modifiers allows to sample the dynamics and conformation landscape of diverse RNA/RNP. However, many chemical modifiers are limited in their capacity to provide unbiased information reflecting the in vivo RNA/RNP structural landscape. In the recent years, the development of selective-2'-hydroxyl acylation analyzed by primer extension (SHAPE) methodology that uses powerful new chemical modifiers has significantly improved in vitro and in vivo structural probing of secondary and tertiary interactions of diverse RNA species at the single nucleotide level.Although the original discovery of Archaea as an independent domain of life is intimately linked to the technological development of RNA analysis, our understanding of in vivo RNA structural conformation and dynamics in this domain of life remains scarce.This protocol describes the in vivo use of SHAPE chemistry in two evolutionary divergent model Archaea, Sulfolobus acidocaldarius and Haloferax volcanii.

Alignments of biomolecular contact maps

Alignments of discrete objects can be constructed in a very general setting as super-objects from which the constituent objects are recovered by means of projections. Here, we focus on contact maps, i.e. undirected graphs with an ordered set of vertices. These serve as natural discretizations of RNA and protein structures. In the general case, the alignment problem for vertex-ordered graphs is NP-complete. In the special case of RNA secondary structures, i.e. crossing-free matchings, however, the alignments have a recursive structure. The alignment problem then can be solved by a variant of the Sankoff algorithm in polynomial time. Moreover, the tree or forest alignments of RNA secondary structure can be understood as the alignments of ordered edge sets.

Decoding LncRNAs

Non-coding RNAs (ncRNAs) have been considered as unimportant additions to the transcriptome. Yet, in light of numerous studies, it has become clear that ncRNAs play important roles in development, health and disease. Long-ignored, long non-coding RNAs (lncRNAs), ncRNAs made of more than 200 nucleotides have gained attention due to their involvement as drivers or suppressors of a myriad of tumours. The detailed understanding of some of their functions, structures and interactomes has been the result of interdisciplinary efforts, as in many cases, new methods need to be created or adapted to characterise these molecules. Unlike most reviews on lncRNAs, we summarize the achievements on lncRNA studies by taking into consideration the approaches for identification of lncRNA functions, interactomes, and structural arrangements. We also provide information about the recent data on the involvement of lncRNAs in diseases and present applications of these molecules, especially in medicine.

SHAPE Directed Discovery of New Functions in Large RNAs

RNA lies upstream of nearly all biology and functions as the central conduit of information exchange in all cells. RNA molecules encode information both in their primary sequences and in complex structures that form when an RNA folds back on itself. From the time of discovery of mRNA in the late 1950s until quite recently, we had only a rudimentary understanding of RNA structure across vast regions of most messenger and noncoding RNAs. This deficit is now rapidly being addressed, especially by selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) chemistry, mutational profiling (MaP), and closely related platform technologies that, collectively, create chemical microscopes for RNA. These technologies make it possible to interrogate RNA structure, quantitatively, at nucleotide resolution, and at large scales, for entire mRNAs, noncoding RNAs, and viral RNA genomes. By applying comprehensive structure probing to diverse problems, we and others are showing that control of biological function mediated by RNA structure is ubiquitous across prokaryotic and eukaryotic organisms.Work over the past decade using SHAPE-based analyses has clarified key principles. First, the method of RNA structure probing matters. SHAPE-MaP, with its direct and one-step readout that probes nearly every nucleotide by reaction at the 2'-hydroxyl, gives a more detailed and accurate readout than alternatives. Second, comprehensive chemical probing is essential. Focusing on fragments of large RNAs or using meta-gene or statistical analyses to compensate for sparse data sets misses critical features and often yields structure models with poor predictive power. Finally, every RNA has its own internal structural personality. There are myriad ways in which RNA structure modulates sequence accessibility, protein binding, translation, splice-site choice, phase separation, and other fundamental biological processes. In essentially every instance where we have applied rigorous and quantitative SHAPE technologies to study RNA structure-function interrelationships, new insights regarding biological regulatory mechanisms have emerged. RNA elements with more complex higher-order structures appear more likely to contain high-information-content clefts and pockets that bind small molecules, broadly informing a vigorous field of RNA-targeted drug discovery.The broad implications of this collective work are twofold. First, it is long past time to abandon depiction of large RNAs as simple noodle-like or gently flowing molecules. Instead, we need to emphasize that nearly all RNAs are punctuated with distinctive internal structures, a subset of which modulate function in profound ways. Second, structure probing should be an integral component of any effort that seeks to understand the functional nexuses and biological roles of large RNAs.

In Vivo and In Vitro Genome-Wide Profiling of RNA Secondary Structures Reveals Key Regulatory Features in Plasmodium falciparum

It is widely accepted that the structure of RNA plays important roles in a number of biological processes, such as polyadenylation, splicing, and catalytic functions. Dynamic changes in RNA structure are able to regulate the gene expression programme and can be used as a highly specific and subtle mechanism for governing cellular processes. However, the nature of most RNA secondary structures in Plasmodium falciparum has not been determined. To investigate the genome-wide RNA secondary structural features at single-nucleotide resolution in P. falciparum, we applied a novel high-throughput method utilizing the chemical modification of RNA structures to characterize these structures. Structural data from parasites are in close agreement with the known 18S ribosomal RNA secondary structures of P. falciparum and can help to predict the in vivo RNA secondary structure of a total of 3,396 transcripts in the ring-stage and trophozoite-stage developmental cycles. By parallel analysis of RNA structures in vivo and in vitro during the Plasmodium parasite ring-stage and trophozoite-stage intraerythrocytic developmental cycles, we identified some key regulatory features. Recent studies have established that the RNA structure is a ubiquitous and fundamental regulator of gene expression. Our study indicate that there is a critical connection between RNA secondary structure and mRNA abundance during the complex biological programme of P. falciparum. This work presents a useful framework and important results, which may facilitate further research investigating the interactions between RNA secondary structure and the complex biological programme in P. falciparum. The RNA secondary structure characterized in this study has potential applications and important implications regarding the identification of RNA structural elements, which are important for parasite infection and elucidating host-parasite interactions and parasites in the environment.

An mRNA-mRNA Interaction Couples Expression of a Virulence Factor and Its Chaperone in Listeria monocytogenes

Bacterial pathogens often employ RNA regulatory elements located in the 5' untranslated regions (UTRs) to control gene expression. Using a comparative structural analysis, we examine the structure of 5' UTRs at a global scale in the pathogenic bacterium Listeria monocytogenes under different conditions. In addition to discovering an RNA thermoswitch and detecting simultaneous interaction of ribosomes and small RNAs with mRNA, we identify structural changes in the 5' UTR of an mRNA encoding the post-translocation chaperone PrsA2 during infection conditions. We demonstrate that the 5' UTR of the prsA2 mRNA base pairs with the 3' UTR of the full-length hly mRNA encoding listeriolysin O, thus preventing RNase J1-mediated degradation of the prsA2 transcript. Mutants lacking the hly-prsA2 interaction exhibit reduced virulence properties. This work highlights an additional level of RNA regulation, where the mRNA encoding a chaperone is stabilized by the mRNA encoding its substrate.

Chemical Approaches To Analyzing RNA Structure Transcriptome-Wide

RNA molecules can fold into complex two- and three-dimensional shapes that are critical for their function. Chemical probes have long been utilized to interrogate RNA structure and are now considered invaluable resources in the goal of relating structure to function. Recently, the power of deep sequencing and careful chemical probe design have merged, permitting researchers to obtain a holistic understanding of how RNA structure can be utilized to control RNA biology transcriptome-wide. Within this review, we outline the recent advancements in chemical probe design for interrogating RNA structures inside cells and discuss the recent advances in our understanding of RNA biology through the lens of chemical probing.

Improved RNA Secondary Structure and Tertiary Base-pairing Prediction Using Evolutionary Profile, Mutational Coupling and Two-dimensional Transfer Learning

MOTIVATION

The recent discovery of numerous non-coding RNAs (long non-coding RNAs, in particular) has transformed our perception about the roles of RNAs in living organisms. Our ability to understand them, however, is hampered by our inability to solve their secondary and tertiary structures in high resolution efficiently by existing experimental techniques. Computational prediction of RNA secondary structure, on the other hand, has received much-needed improvement, recently, through deep learning of a large approximate data, followed by transfer learning with gold-standard base-pairing structures from high-resolution 3-D structures. Here, we expand this single-sequence-based learning to the use of evolutionary profiles and mutational coupling.

RESULTS

The new method allows large improvement not only in canonical base-pairs (RNA secondary structures) but more so in base-pairing associated with tertiary interactions such as pseudoknots, noncanonical and lone base-pairs. In particular, it is highly accurate for those RNAs of more than 1000 homologous sequences by achieving >0.8 F1-score (harmonic mean of sensitivity and precision) for 14/16 RNAs tested. The method can also significantly improve base-pairing prediction by incorporating artificial but functional homologous sequences generated from deep mutational scanning without any modification. The fully automatic method (publicly available as server and standalone software) should provide the scientific community a new powerful tool to capture not only the secondary structure but also tertiary base-pairing information for building three-dimensional models. It also highlights the future of accurately solving the base-pairing structure by using a large number of natural and/or artificial homologous sequences.

AVAILABILITY

Standalone-version of SPOT-RNA2 is available at https://github.com/jaswindersingh2/SPOT-RNA2. Direct prediction can also be made at https://sparks-lab.org/server/spot-rna2/. The datasets used in this research can also be downloaded from the GITHUB and the webserver mentioned above.

Genome-scale deconvolution of RNA structure ensembles

RNA structure heterogeneity is a major challenge when querying RNA structures with chemical probing. We introduce DRACO, an algorithm for the deconvolution of coexisting RNA conformations from mutational profiling experiments. Analysis of the SARS-CoV-2 genome using dimethyl sulfate mutational profiling with sequencing (DMS-MaPseq) and DRACO, identifies multiple regions that fold into two mutually exclusive conformations, including a conserved structural switch in the 3' untranslated region. This work may open the way to dissecting the heterogeneity of the RNA structurome.

RASP: an atlas of transcriptome-wide RNA secondary structure probing data

RNA molecules fold into complex structures that are important across many biological processes. Recent technological developments have enabled transcriptome-wide probing of RNA secondary structure using nucleases and chemical modifiers. These approaches have been widely applied to capture RNA secondary structure in many studies, but gathering and presenting such data from very different technologies in a comprehensive and accessible way has been challenging. Existing RNA structure probing databases usually focus on low-throughput or very specific datasets. Here, we present a comprehensive RNA structure probing database called RASP (RNA Atlas of Structure Probing) by collecting 161 deduplicated transcriptome-wide RNA secondary structure probing datasets from 38 papers. RASP covers 18 species across animals, plants, bacteria, fungi, and also viruses, and categorizes 18 experimental methods including DMS-seq, SHAPE-Seq, SHAPE-MaP, and icSHAPE, etc. Specially, RASP curates the up-to-date datasets of several RNA secondary structure probing studies for the RNA genome of SARS-CoV-2, the RNA virus that caused the on-going COVID-19 pandemic. RASP also provides a user-friendly interface to query, browse, and visualize RNA structure profiles, offering a shortcut to accessing RNA secondary structures grounded in experimental data. The database is freely available at http://rasp.zhanglab.net.

Characterizing Genetic Parts and Devices Using RNA Sequencing

Synthetic genetic circuits are composed of many parts that must interact and function together to produce a desired pattern of gene expression. A challenge when assembling circuits is that genetic parts often behave differently within a circuit, potentially impacting the desired functionality. Existing debugging methods based on fluorescent reporter proteins allow for only a few internal states to be monitored simultaneously, making diagnosis of the root cause impossible for large systems. Here, we present a tool called the Genetic Analyzer which uses RNA sequencing data to simultaneously characterize all transcriptional parts (e.g., promoters and terminators) and devices (e.g., sensors and logic gates) in complex genetic circuits. This provides a complete picture of the inner workings of a genetic circuit enabling faults to be easily identified and fixed. We construct a complete workflow to coordinate the execution of the various data processing and analysis steps and explain the options available when adapting these for the characterization of new systems.

RNA structure probing to characterize RNA-protein interactions on a low abundance pre-mRNA in living cells

In vivo RNA structure analysis has become a powerful tool in molecular biology, largely due to the coupling of an increasingly diverse set of chemical approaches with high-throughput sequencing. This has resulted in a transition from single target to transcriptome-wide approaches. However, these methods require sequencing depths that preclude studying low abundance targets, which are not sufficiently captured in transcriptome-wide approaches. Here we present a ligation-free method to enrich for low abundance RNA sequences, which improves the diversity of molecules analyzed and results in improved analysis. In addition, this method is compatible with any choice of chemical adduct or read-out approach. We utilized this approach to study an autoregulated event in the pre-mRNA of the splicing factor, muscleblind-like splicing regulator 1 (MBNL1).

Small molecule-RNA targeting: starting with the fundamentals

The structural and regulatory elements in therapeutically relevant RNAs offer many opportunities for targeting by small molecules, yet fundamental understanding of what drives selectivity in small molecule:RNA recognition has been a recurrent challenge. In particular, RNAs tend to be more dynamic and offer less chemical functionality than proteins, and biologically active ligands must compete with the highly abundant and highly structured RNA of the ribosome. Indeed, the only small molecule drug targeting RNA other than the ribosome was just approved in August 2020, and our recent survey of the literature revealed fewer than 150 reported chemical probes that target non-ribosomal RNA in biological systems. This Feature outlines our efforts to improve small molecule targeting strategies and gain fundamental insights into small molecule:RNA recognition by analyzing patterns in both RNA-biased small molecule chemical space and RNA topological space privileged for differentiation. First, we synthesized libraries based on RNA binding scaffolds that allowed us to reveal general principles in small molecule:recognition and to ask precise chemical questions about drivers of affinity and selectivity. Elaboration of these scaffolds has led to recognition of medicinally relevant RNA targets, including viral and long noncoding RNA structures. More globally, we identified physicochemical, structural, and spatial properties of biologically active RNA ligands that are distinct from those of protein-targeted ligands, and we have provided the dataset and associated analytical tools as part of a publicly available online platform to facilitate RNA ligand discovery. At the same time, we used pattern recognition protocols to identify RNA topologies that can be differentially recognized by small molecules and have elaborated this technique to visualize conformational changes in RNA secondary structure. These fundamental insights into the drivers of RNA recognition in vitro have led to functional targeting of RNA structures in biological systems. We hope that these initial guiding principles, as well as the approaches and assays developed in their pursuit, will enable rapid progress toward the development of RNA-targeted chemical probes and ultimately new therapeutic approaches to a wide range of deadly human diseases.

Integrated approaches to reveal mechanisms by which RNA viruses reprogram the cellular environment

RNA viruses are major threats to global society and mass outbreaks can cause long-lasting damage to international economies. RNA and related retro viruses represent a large and diverse family that contribute to the onset of human diseases such as AIDS; certain cancers like T cell lymphoma; severe acute respiratory illnesses as seen with COVID-19; and others. The hallmark of this viral family is the storage of genetic material in the form of RNA, and upon infecting host cells, their RNA genomes reprogram the cellular environment to favor productive viral replication. RNA is a multifunctional biomolecule that not only stores and transmits heritable information, but it also has the capacity to catalyze complex biochemical reactions. It is therefore no surprise that RNA viruses use this functional diversity to their advantage to sustain chronic or lifelong infections. Efforts to subvert RNA viruses therefore requires a deep understanding of the mechanisms by which these pathogens usurp cellular machinery. Here, we briefly summarize several experimental techniques that individually inform on key physicochemical features of viral RNA genomes and their interactions with proteins. Each of these techniques provide important vantage points to understand the complexities of virus-host interactions, but we attempt to make the case that by integrating these and similar methods, more vivid descriptions of how viruses reprogram the cellular environment emerges. These vivid descriptions should expedite the identification of novel therapeutic targets.

Advances in RNA 3D Structure Modeling Using Experimental Data

RNA is a unique bio-macromolecule that can both record genetic information and perform biological functions in a variety of molecular processes, including transcription, splicing, translation, and even regulating protein function. RNAs adopt specific three-dimensional conformations to enable their functions. Experimental determination of high-resolution RNA structures using x-ray crystallography is both laborious and demands expertise, thus, hindering our comprehension of RNA structural biology. The computational modeling of RNA structure was a milestone in the birth of bioinformatics. Although computational modeling has been greatly improved over the last decade showing many successful cases, the accuracy of such computational modeling is not only length-dependent but also varies according to the complexity of the structure. To increase credibility, various experimental data were integrated into computational modeling. In this review, we summarize the experiments that can be integrated into RNA structure modeling as well as the computational methods based on these experimental data. We also demonstrate how computational modeling can help the experimental determination of RNA structure. We highlight the recent advances in computational modeling which can offer reliable structure models using high-throughput experimental data.

Determination of isoform-specific RNA structure with nanopore long reads

Current methods for determining RNA structure with short-read sequencing cannot capture most differences between distinct transcript isoforms. Here we present RNA structure analysis using nanopore sequencing (PORE-cupine), which combines structure probing using chemical modifications with direct long-read RNA sequencing and machine learning to detect secondary structures in cellular RNAs. PORE-cupine also captures global structural features, such as RNA-binding-protein binding sites and reactivity differences at single-nucleotide variants. We show that shared sequences in different transcript isoforms of the same gene can fold into different structures, highlighting the importance of long-read sequencing for obtaining phase information. We also demonstrate that structural differences between transcript isoforms of the same gene lead to differences in translation efficiency. By revealing isoform-specific RNA structure, PORE-cupine will deepen understanding of the role of structures in controlling gene regulation.

Solid-Phase Synthesis of Sequence-Defined Informational Oligomers

Genetic biopolymers utilize defined sequences and monomer-specific molecular recognition to store and transfer information. Synthetic polymers that mimic these attributes using reversible covalent chemistry for base-pairing pose unique synthetic challenges. Here, we describe a solid-phase synthesis methodology for the efficient construction of ethynyl benzene oligomers with specific sequences of aniline and benzaldehyde subunits. Handling these oligomers is complicated by the fact that they often exhibit multiple conformations because of intra- or intermolecular pairing. We describe conditions that allow the dynamic behavior of these oligomers to be controlled so that they may be manipulated and characterized without needing to mask the recognition units with protecting groups.

On the Way to Understanding the Interplay between the RNA Structure and Functions in Cells: A Genome-Wide Perspective

RNAs adopt specific structures in order to perform their biological activities. The structure of RNA is an important layer of gene expression regulation, and can impact a plethora of cellular processes, starting with transcription, RNA processing, and translation, and ending with RNA turnover. The development of high-throughput technologies has enabled a deeper insight into the sophisticated interplay between the structure of the cellular transcriptome and the living cells environment. In this review, we present the current view on the RNA structure in vivo resulting from the most recent transcriptome-wide studies in different organisms, including mammalians, yeast, plants, and bacteria. We focus on the relationship between the mRNA structure and translation, mRNA stability and degradation, protein binding, and RNA posttranscriptional modifications.

Design of a small molecule that stimulates vascular endothelial growth factor A enabled by screening RNA fold-small molecule interactions

Vascular endothelial growth factor A (VEGFA) stimulates angiogenesis in human endothelial cells, and increasing its expression is a potential treatment for heart failure. Here, we report the design of a small molecule (TGP-377) that specifically and potently enhances VEGFA expression by the targeting of a non-coding microRNA that regulates its expression. A selection-based screen, named two-dimensional combinatorial screening, revealed preferences in small-molecule chemotypes that bind RNA and preferences in the RNA motifs that bind small molecules. The screening program increased the dataset of known RNA motif–small molecule binding partners by 20-fold. Analysis of this dataset against the RNA-mediated pathways that regulate VEGFA defined that the microRNA-377 precursor, which represses Vegfa messenger RNA translation, is druggable in a selective manner. We designed TGP-377 to potently and specifically upregulate VEGFA in human umbilical vein endothelial cells. These studies illustrate the power of two-dimensional combinatorial screening to define molecular recognition events between ‘undruggable’ biomolecules and small molecules, and the ability of sequence-based design to deliver efficacious structure-specific compounds.

Large-scale comparative evaluation of user-friendly tools for predicting variant-induced alterations of splicing regulatory elements

Discriminating which nucleotide variants cause disease or contribute to phenotypic traits remains a major challenge in human genetics. In theory, any intragenic variant can potentially affect RNA splicing by altering splicing regulatory elements (SREs). However, these alterations are often ignored mainly because pioneer SRE predictors have proved inefficient. Here, we report the first large-scale comparative evaluation of four user-friendly SRE-dedicated algorithms (QUEPASA, HEXplorer, SPANR, and HAL) tested both as standalone tools and in multiple combined ways based on two independent benchmark datasets adding up to >1,300 exonic variants studied at the messenger RNA level and mapping to 89 different disease-causing genes. These methods display good predictive power, based on decision thresholds derived from the receiver operating characteristics curve analyses, with QUEPASA and HAL having the best accuracies either as standalone or in combination. Still, overall there was a tight race between the four predictors, suggesting that all methods may be of use. Additionally, QUEPASA and HEXplorer may be beneficial as well for predicting variant-induced creation of pseudoexons deep within introns. Our study highlights the potential of SRE predictors as filtering tools for identifying disease-causing candidates among the plethora of variants detected by high-throughput DNA sequencing and provides guidance for their use in genomic medicine settings.

Intrinsic Regulatory Role of RNA Structural Arrangement in Alternative Splicing Control

Alternative splicing is a highly sophisticated process, playing a significant role in posttranscriptional gene expression and underlying the diversity and complexity of organisms. Its regulation is multilayered, including an intrinsic role of RNA structural arrangement which undergoes time- and tissue-specific alterations. In this review, we describe the principles of RNA structural arrangement and briefly decipher its cis- and trans-acting cellular modulators which serve as crucial determinants of biological functionality of the RNA structure. Subsequently, we engage in a discussion about the RNA structure-mediated mechanisms of alternative splicing regulation. On one hand, the impairment of formation of optimal RNA structures may have critical consequences for the splicing outcome and further contribute to understanding the pathomechanism of severe disorders. On the other hand, the structural aspects of RNA became significant features taken into consideration in the endeavor of finding potential therapeutic treatments. Both aspects have been addressed by us emphasizing the importance of ongoing studies in both fields.

mRNA structural dynamics shape Argonaute-target interactions

Small interfering RNAs (siRNAs) promote RNA degradation in a variety of processes and have important clinical applications. siRNAs direct cleavage of target RNAs by guiding Argonaute2 (AGO2) to its target site. Target site accessibility is critical for AGO2-target interactions, but how target site accessibility is controlled in vivo is poorly understood. Here, we use live-cell single-molecule imaging in human cells to determine rate constants of the AGO2 cleavage cycle in vivo. We find that the rate-limiting step in mRNA cleavage frequently involves unmasking of target sites by translating ribosomes. Target site masking is caused by heterogeneous intramolecular RNA-RNA interactions, which can conceal target sites for many minutes in the absence of translation. Our results uncover how dynamic changes in mRNA structure shape AGO2-target recognition, provide estimates of mRNA folding and unfolding rates in vivo, and provide experimental evidence for the role of mRNA structural dynamics in control of mRNA-protein interactions.

Lead-seq: transcriptome-wide structure probing in vivo using lead(II) ions

The dynamic conformation of RNA molecules within living cells is key to their function. Recent advances in probing the RNA structurome in vivo, including the use of SHAPE (Selective 2'-Hydroxyl Acylation analyzed by Primer Extension) or kethoxal reagents or DMS (dimethyl sulfate), provided unprecedented insights into the architecture of RNA molecules in the living cell. Here, we report the establishment of lead probing in a global RNA structuromics approach. In order to elucidate the transcriptome-wide RNA landscape in the enteric pathogen Yersinia pseudotuberculosis, we combined lead(II) acetate-mediated cleavage of single-stranded RNA regions with high-throughput sequencing. This new approach, termed 'Lead-seq', provides structural information independent of base identity. We show that the method recapitulates secondary structures of tRNAs, RNase P RNA, tmRNA, 16S rRNA and the rpsT 5'-untranslated region, and that it reveals global structural features of mRNAs. The application of Lead-seq to Y. pseudotuberculosis cells grown at two different temperatures unveiled the first temperature-responsive in vivo RNA structurome of a bacterial pathogen. The translation of candidate genes derived from this approach was confirmed to be temperature regulated. Overall, this study establishes Lead-seq as complementary approach to interrogate intracellular RNA structures on a global scale.

Structural Insights into RNA Dimerization: Motifs, Interfaces and Functions

In comparison with the pervasive use of protein dimers and multimers in all domains of life, functional RNA oligomers have so far rarely been observed in nature. Their diminished occurrence contrasts starkly with the robust intrinsic potential of RNA to multimerize through long-range base-pairing ("kissing") interactions, self-annealing of palindromic or complementary sequences, and stable tertiary contact motifs, such as the GNRA tetraloop-receptors. To explore the general mechanics of RNA dimerization, we performed a meta-analysis of a collection of exemplary RNA homodimer structures consisting of viral genomic elements, ribozymes, riboswitches, etc., encompassing both functional and fortuitous dimers. Globally, we found that domain-swapped dimers and antiparallel, head-to-tail arrangements are predominant architectural themes. Locally, we observed that the same structural motifs, interfaces and forces that enable tertiary RNA folding also drive their higher-order assemblies. These feature prominently long-range kissing loops, pseudoknots, reciprocal base intercalations and A-minor interactions. We postulate that the scarcity of functional RNA multimers and limited diversity in multimerization motifs may reflect evolutionary constraints imposed by host antiviral immune surveillance and stress sensing. A deepening mechanistic understanding of RNA multimerization is expected to facilitate investigations into RNA and RNP assemblies, condensates, and granules and enable their potential therapeutical targeting.

Combating the Coronavirus Pandemic: Early Detection, Medical Treatment, and a Concerted Effort by the Global Community

The World Health Organization (WHO) has declared the outbreak of 2019 novel coronavirus, known as 2019-nCoV, a pandemic, as the coronavirus has now infected over 2.6 million people globally and caused more than 185,000 fatalities as of April 23, 2020. Coronavirus disease 2019 (COVID-19) causes a respiratory illness with symptoms such as dry cough, fever, sudden loss of smell, and, in more severe cases, difficulty breathing. To date, there is no specific vaccine or treatment proven effective against this viral disease. Early and accurate diagnosis of COVID-19 is thus critical to curbing its spread and improving health outcomes. Reverse transcription-polymerase chain reaction (RT-PCR) is commonly used to detect the presence of COVID-19. Other techniques, such as recombinase polymerase amplification (RPA), loop-mediated isothermal amplification (LAMP), clustered regularly interspaced short palindromic repeats (CRISPR), and microfluidics, have allowed better disease diagnosis. Here, as part of the effort to expand screening capacity, we review advances and challenges in the rapid detection of COVID-19 by targeting nucleic acids, antigens, or antibodies. We also summarize potential treatments and vaccines against COVID-19 and discuss ongoing clinical trials of interventions to reduce viral progression.

Anomalous Reverse Transcription through Chemical Modifications in Polyadenosine Stretches

Thermostable reverse transcriptases are workhorse enzymes underlying nearly all modern techniques for RNA structure mapping and for the transcriptome-wide discovery of RNA chemical modifications. Despite their wide use, these enzymes' behaviors at chemical modified nucleotides remain poorly understood. Wellington-Oguri et al. recently reported an apparent loss of chemical modification within putatively unstructured polyadenosine stretches modified by dimethyl sulfate or 2' hydroxyl acylation, as probed by reverse transcription. Here, reanalysis of these and other publicly available data, capillary electrophoresis experiments on chemically modified RNAs, and nuclear magnetic resonance spectroscopy on (A)₁₂ and variants show that this effect is unlikely to arise from an unusual structure of polyadenosine. Instead, tests of different reverse transcriptases on chemically modified RNAs and molecules synthesized with single 1-methyladenosines implicate a previously uncharacterized reverse transcriptase behavior: near-quantitative bypass through chemical modifications within polyadenosine stretches. All tested natural and engineered reverse transcriptases (MMLV; SuperScript II, III, and IV; TGIRT-III; and MarathonRT) exhibit this anomalous bypass behavior. Accurate DMS-guided structure modeling of the polyadenylated HIV-1 3' untranslated region requires taking into account this anomaly. Our results suggest that poly(rA-dT) hybrid duplexes can trigger an unexpectedly effective reverse transcriptase bypass and that chemical modifications in mRNA poly(A) tails may be generally undercounted.

RNA structural dynamics regulate early embryogenesis through controlling transcriptome fate and function

BACKGROUND

Vertebrate early embryogenesis is initially directed by a set of maternal RNAs and proteins, yet the mechanisms controlling this program remain largely unknown. Recent transcriptome-wide studies on RNA structure have revealed its pervasive and crucial roles in RNA processing and functions, but whether and how RNA structure regulates the fate of the maternal transcriptome have yet to be determined.

RESULTS

Here we establish the global map of four nucleotide-based mRNA structures by icSHAPE during zebrafish early embryogenesis. Strikingly, we observe that RNA structurally variable regions are enriched in the 3' UTR and contain cis-regulatory elements important for maternal-to-zygotic transition (MZT). We find that the RNA-binding protein Elavl1a stabilizes maternal mRNAs by binding to the cis-elements. Conversely, RNA structure formation suppresses Elavl1a's binding leading to the decay of its maternal targets.

CONCLUSIONS

Our study finds that RNA structurally variable regions are enriched in mRNA 3' UTRs and contain cis-regulatory elements during zebrafish early embryogenesis. We reveal that Elavl1a regulates maternal RNA stability in an RNA structure-dependent fashion. Overall, our findings reveal a broad and fundamental role of RNA structure-based regulation in vertebrate early embryogenesis.

Stability and nuclear localization of yeast telomerase depend on protein components of RNase P/MRP

RNase P and MRP are highly conserved, multi-protein/RNA complexes with essential roles in processing ribosomal and tRNAs. Three proteins found in both complexes, Pop1, Pop6, and Pop7 are also telomerase-associated. Here, we determine how temperature sensitive POP1 and POP6 alleles affect yeast telomerase. At permissive temperatures, mutant Pop1/6 have little or no effect on cell growth, global protein levels, the abundance of Est1 and Est2 (telomerase proteins), and the processing of TLC1 (telomerase RNA). However, in pop mutants, TLC1 is more abundant, telomeres are short, and TLC1 accumulates in the cytoplasm. Although Est1/2 binding to TLC1 occurs at normal levels, Est1 (and hence Est3) binding is highly unstable. We propose that Pop-mediated stabilization of Est1 binding to TLC1 is a pre-requisite for formation and nuclear localization of the telomerase holoenzyme. Furthermore, Pop proteins affect TLC1 and the RNA subunits of RNase P/MRP in very different ways.

RNA Conformation Capture by Proximity Ligation

RNA proximity ligation is a set of molecular biology techniques used to analyze the conformations and spatial proximity of RNA molecules within cells. A typical experiment starts with cross-linking of a biological sample using UV light or psoralen, followed by partial fragmentation of RNA, RNA-RNA ligation, library preparation, and high-throughput sequencing. In the past decade, proximity ligation has been used to study structures of individual RNAs, networks of interactions between small RNAs and their targets, and whole RNA-RNA interactomes, in models ranging from bacteria to animal tissues and whole animals. Here, we provide an overview of the field, highlight the main findings, review the recent experimental and computational developments, and provide troubleshooting advice for new users. In the final section, we draw parallels between DNA and RNA proximity ligation and speculate on possible future research directions.

Viral RNA structure analysis using DMS-MaPseq

RNA structure is critically important to RNA viruses in every part of the replication cycle. RNA structure is also utilized by DNA viruses in order to regulate gene expression and interact with host factors. Advances in next-generation sequencing have greatly enhanced the utility of chemical probing in order to analyze RNA structure. This review will cover some recent viral RNA structural studies using chemical probing and next-generation sequencing as well as the advantages of dimethyl sulfate (DMS)-mutational profiling and sequencing (MaPseq). DMS-MaPseq is a robust assay that can easily modify RNA in vitro, in cell and in virion. A detailed protocol for whole-genome DMS-MaPseq from cells transfected with HIV-1 and the structure of TAR as determined by DMS-MaPseq is presented. DMS-MaPseq has the ability to answer a variety of integral questions about viral RNA, including how they change in different environments and when interacting with different host factors.

Secondary Structure of Chloroplast mRNAs In Vivo and In Vitro

mRNA secondary structure can influence gene expression, e.g., by influencing translation initiation. The probing of in vivo mRNA secondary structures is therefore necessary to understand what determines the efficiency and regulation of gene expression. Here, in vivo mRNA secondary structure was analyzed using dimethyl sulfate (DMS)-MaPseq and compared to in vitro-folded RNA. We used an approach to analyze specific, full-length transcripts. To test this approach, we chose low, medium, and high abundant mRNAs. We included both monocistronic and multicistronic transcripts. Because of the slightly alkaline pH of the chloroplast stroma, we could probe all four nucleotides with DMS. The structural information gained was evaluated using the known structure of the plastid 16S rRNA. This demonstrated that the results obtained for adenosines and cytidines were more reliable than for guanosines and uridines. The majority of mRNAs analyzed were less structured in vivo than in vitro. The in vivo secondary structure of the translation initiation region of most tested genes appears to be optimized for high translation efficiency.

Probing of Nucleic Acid Structures, Dynamics, and Interactions With Environment-Sensitive Fluorescent Labels

Fluorescence labeling and probing are fundamental techniques for nucleic acid analysis and quantification. However, new fluorescent probes and approaches are urgently needed in order to accurately determine structural and conformational dynamics of DNA and RNA at the level of single nucleobases/base pairs, and to probe the interactions between nucleic acids with proteins. This review describes the means by which to achieve these goals using nucleobase replacement or modification with advanced fluorescent dyes that respond by the changing of their fluorescence parameters to their local environment (altered polarity, hydration, flipping dynamics, and formation/breaking of hydrogen bonds).

DUETT quantitatively identifies known and novel events in nascent RNA structural dynamics from chemical probing data

MOTIVATION

RNA molecules can undergo complex structural dynamics, especially during transcription, which influence their biological functions. Recently developed high-throughput chemical probing experiments that study RNA cotranscriptional folding generate nucleotide-resolution 'reactivities' for each length of a growing nascent RNA that reflect structural dynamics. However, the manual annotation and qualitative interpretation of reactivity across these large datasets can be nuanced, laborious, and difficult for new practitioners. We developed a quantitative and systematic approach to automatically detect RNA folding events from these datasets to reduce human bias/error, standardize event discovery and generate hypotheses about RNA folding trajectories for further analysis and experimental validation.

RESULTS

Detection of Unknown Events with Tunable Thresholds (DUETT) identifies RNA structural transitions in cotranscriptional RNA chemical probing datasets. DUETT employs a feedback control-inspired method and a linear regression approach and relies on interpretable and independently tunable parameter thresholds to match qualitative user expectations with quantitatively identified folding events. We validate the approach by identifying known RNA structural transitions within the cotranscriptional folding pathways of the Escherichia coli signal recognition particle RNA and the Bacillus cereus crcB fluoride riboswitch. We identify previously overlooked features of these datasets such as heightened reactivity patterns in the signal recognition particle RNA about 12 nt lengths before base-pair rearrangement. We then apply a sensitivity analysis to identify tradeoffs when choosing parameter thresholds. Finally, we show that DUETT is tunable across a wide range of contexts, enabling flexible application to study broad classes of RNA folding mechanisms.

AVAILABILITY AND IMPLEMENTATION

https://github.com/BagheriLab/DUETT.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

GraphClust2: Annotation and discovery of structured RNAs with scalable and accessible integrative clustering

BACKGROUND

RNA plays essential roles in all known forms of life. Clustering RNA sequences with common sequence and structure is an essential step towards studying RNA function. With the advent of high-throughput sequencing techniques, experimental and genomic data are expanding to complement the predictive methods. However, the existing methods do not effectively utilize and cope with the immense amount of data becoming available.

RESULTS

Hundreds of thousands of non-coding RNAs have been detected; however, their annotation is lagging behind. Here we present GraphClust2, a comprehensive approach for scalable clustering of RNAs based on sequence and structural similarities. GraphClust2 bridges the gap between high-throughput sequencing and structural RNA analysis and provides an integrative solution by incorporating diverse experimental and genomic data in an accessible manner via the Galaxy framework. GraphClust2 can efficiently cluster and annotate large datasets of RNAs and supports structure-probing data. We demonstrate that the annotation performance of clustering functional RNAs can be considerably improved. Furthermore, an off-the-shelf procedure is introduced for identifying locally conserved structure candidates in long RNAs. We suggest the presence and the sparseness of phylogenetically conserved local structures for a collection of long non-coding RNAs.

CONCLUSIONS

By clustering data from 2 cross-linking immunoprecipitation experiments, we demonstrate the benefits of GraphClust2 for motif discovery under the presence of biological and methodological biases. Finally, we uncover prominent targets of double-stranded RNA binding protein Roquin-1, such as BCOR's 3' untranslated region that contains multiple binding stem-loops that are evolutionary conserved.