SHAPE Selection (SHAPES) enrich for RNA structure signal in SHAPE sequencing-based probing data

Selective Arylation of RNA 2'-OH Groups via SNAr Reaction with Trialkylammonium Heterocycles

Small-molecule reactions at the 2'-OH groups of RNA enable useful applications for transcriptome technology and biology. To date, all reactions have involved carbonyl acylation and mechanistically related sulfonylation, limiting the types of modifications and properties that can be achieved. Here we report that electron-deficient heteroaryl species selectively react with 2'-OH groups of RNA in water via SNAr chemistry. In particular, trialkyl-ammonium (TAA)-activated aromatic heterocycles, prepared in one step from aryl chloride precursors, give high conversions to aryl ether adducts with RNAs in aqueous buffer in ~2-3 h. Remarkably, a TAA triazine previously used only for reaction with carboxylic acids, shows unprecedented selectivity for RNA over water, reacting rapidly with 2'-OH groups while exhibiting a half-life in water of >10 days. We further show that a triazine aryl species can be used as a probe at trace-level yields to map RNA structure in vitro. Finally, we prepare a number of functionalized trialkylammonium triazine reagents and show that they can be used to covalently label RNA efficiently for use in vitro and in living cells. This direct arylation chemistry offers a simple and distinct structural scaffold for post-synthetic RNA modification, with potential utility in multiple applications in transcriptome research.

Second-Generation Chiral Amino Acid Derivatives Afford High Stereoselectivity and Stability in Aqueous RNA Acylation

Activated acyl species have proven versatile in the esterification of 2'-OH groups in RNA, enabling structure mapping, caging, profiling, and labeling of the biopolymer. Nearly all reagents developed for this reaction have been achiral; however, a recent study reported that simple chiral amino acid acylimidazole derivatives could yield diastereoselective reactions at RNA 2'-OH in water, enabling up to 4:1 selectivity in screening. Here, we investigated the effect of steric bulk on the stereoselectivity of RNA reaction and on the stability of adducts with a library of 36 chiral acylimidazole scaffolds with increasing steric demand. The results document the highest stereoselectivity yet achieved in RNA acylation reactions, with as high as >99:1 diastereoselectivity at >70% conversion. Also notably, the bulky adducts were found to have markedly improved stability on RNA.

Aqueous Activation of RNA 2'-OH for Conjugation with Amines and Thiols

Strategies for covalent modification of RNA are important for enabling biological studies of the biopolymer and for enhancing properties of therapeutic RNAs. While a number of electrophiles have been observed to react with RNA, few methods exist for reaction with nucleophiles. Here, we describe new reagents that enable efficient conjugation of amines and other nucleophiles to unmodified RNA postsynthetically via transient activation of 2'-OH groups. Reaction of single-stranded RNA in aqueous solution with phenolic imidazolecarbamates at room temperature results in stoichiometric and superstoichiometric yields of imidazolecarbonyl group adducts, and control experiments with DNA confirm the site of reaction in RNA as 2'-OH. Subsequent incubation of imidazolecarbonyl-activated RNAs with primary or selected secondary amines results in rapid, high-yield conversion to carbamate conjugates. The activation and subsequent nucleophile reaction can be carried out either stepwise or in a one-pot reaction. Thiols and phenol species react to yield (thio)carbonate adducts, and amino acid sidechains also react, suggesting possible future utility for protein conjugates and analysis of protein-RNA interactions. The activation method is found to be selective to unpaired regions of RNA, and can be directed to a specific location in a strand by use of a loop-inducing helper DNA. The results establish novel and efficient reagents and methods for modifying RNA postsynthetically with nucleophiles.

Efficient post-synthesis incorporation and conjugation of reactive ketones in RNA via 2'-acylation

Despite the broad utility of ketones in bioconjugation, few methods exist to introduce them into RNA. Here we develop highly reactive 2'-OH acylating reagents containing strained-ring ketones, and employ them as versatile labeling handles for RNA.

Observation of coordinated RNA folding events by systematic cotranscriptional RNA structure probing

RNA begins to fold as it is transcribed by an RNA polymerase. Consequently, RNA folding is constrained by the direction and rate of transcription. Understanding how RNA folds into secondary and tertiary structures therefore requires methods for determining the structure of cotranscriptional folding intermediates. Cotranscriptional RNA chemical probing methods accomplish this by systematically probing the structure of nascent RNA that is displayed from an RNA polymerase. Here, we describe a concise, high-resolution cotranscriptional RNA chemical probing procedure called variable length Transcription Elongation Complex RNA structure probing (TECprobe-VL). We demonstrate the accuracy and resolution of TECprobe-VL by replicating and extending previous analyses of ZTP and fluoride riboswitch folding and mapping the folding pathway of a ppGpp-sensing riboswitch. In each system, we show that TECprobe-VL identifies coordinated cotranscriptional folding events that mediate transcription antitermination. Our findings establish TECprobe-VL as an accessible method for mapping cotranscriptional RNA folding pathways.

Plant YTHDF proteins are direct effectors of antiviral immunity against an N6-methyladenosine-containing RNA virus

In virus-host interactions, nucleic acid-directed first lines of defense that allow viral clearance without compromising growth are of paramount importance. Plants use the RNA interference pathway as a basal antiviral immune system, but additional RNA-based mechanisms of defense also exist. The infectivity of a plant positive-strand RNA virus, alfalfa mosaic virus (AMV), relies on the demethylation of viral RNA by the recruitment of the cellular N6-methyladenosine (m6 A) demethylase ALKBH9B, but how demethylation of viral RNA promotes AMV infection remains unknown. Here, we show that inactivation of the Arabidopsis cytoplasmic YT521-B homology domain (YTH)-containing m6 A-binding proteins ECT2, ECT3, and ECT5 is sufficient to restore AMV infectivity in partially resistant alkbh9b mutants. We further show that the antiviral function of ECT2 is distinct from its previously demonstrated function in the promotion of primordial cell proliferation: an ect2 mutant carrying a small deletion in its intrinsically disordered region is partially compromised for antiviral defense but not for developmental functions. These results indicate that the m6 A-YTHDF axis constitutes a novel branch of basal antiviral immunity in plants.

How does precursor RNA structure influence RNA processing and gene expression?

RNA is a fundamental biomolecule that has many purposes within cells. Due to its single-stranded and flexible nature, RNA naturally folds into complex and dynamic structures. Recent technological and computational advances have produced an explosion of RNA structural data. Many RNA structures have regulatory and functional properties. Studying the structure of nascent RNAs is particularly challenging due to their low abundance and long length, but their structures are important because they can influence RNA processing. Precursor RNA processing is a nexus of pathways that determines mature isoform composition and that controls gene expression. In this review, we examine what is known about human nascent RNA structure and the influence of RNA structure on processing of precursor RNAs. These known structures provide examples of how other nascent RNAs may be structured and show how novel RNA structures may influence RNA processing including splicing and polyadenylation. RNA structures can be targeted therapeutically to treat disease.

Native RNA or cDNA Sequencing for Transcriptomic Analysis: A Case Study on Saccharomyces cerevisiae

Direct sequencing of single molecules through nanopores allows for accurate quantification and full-length characterization of native RNA or complementary DNA (cDNA) without amplification. Both nanopore-based native RNA and cDNA approaches involve complex transcriptome procedures at a lower cost. However, there are several differences between the two approaches. In this study, we perform matched native RNA sequencing and cDNA sequencing to enable relevant comparisons and evaluation. Using Saccharomyces cerevisiae, a eukaryotic model organism widely used in industrial biotechnology, two different growing conditions are considered for comparison, including the poly-A messenger RNA isolated from yeast cells grown in minimum media under respirofermentative conditions supplemented with glucose (glucose growth conditions) and from cells that had shifted to ethanol as a carbon source (ethanol growth conditions). Library preparation for direct RNA sequencing is shorter than that for direct cDNA sequencing. The sequence characteristics of the two methods were different, such as sequence yields, quality score of reads, read length distribution, and mapped on reference ability of reads. However, differential gene expression analyses derived from the two approaches are comparable. The unique feature of direct RNA sequencing is RNA modification; we found that the RNA modification at the 5' end of a transcript was underestimated due to the 3' bias behavior of the direct RNA sequencing. Our comprehensive evaluation from this work could help researchers make informed choices when selecting an appropriate long-read sequencing method for understanding gene functions, pathways, and detailed functional characterization.

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.

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.

Genome-wide association studies reveal the role of polymorphisms affecting factor H binding protein expression in host invasion by Neisseria meningitidis

Many invasive bacterial diseases are caused by organisms that are ordinarily harmless components of the human microbiome. Effective interventions against these microbes require an understanding of the processes whereby symbiotic or commensal relationships transition into pathology. Here, we describe bacterial genome-wide association studies (GWAS) of Neisseria meningitidis, a common commensal of the human respiratory tract that is nevertheless a leading cause of meningitis and sepsis. An initial GWAS discovered bacterial genetic variants, including single nucleotide polymorphisms (SNPs), associated with invasive meningococcal disease (IMD) versus carriage in several loci across the meningococcal genome, encoding antigens and other extracellular components, confirming the polygenic nature of the invasive phenotype. In particular, there was a significant peak of association around the fHbp locus, encoding factor H binding protein (fHbp), which promotes bacterial immune evasion of human complement by recruiting complement factor H (CFH) to the meningococcal surface. The association around fHbp with IMD was confirmed by a validation GWAS, and we found that the SNPs identified in the validation affected the 5' region of fHbp mRNA, altering secondary RNA structures, thereby increasing fHbp expression and enhancing bacterial escape from complement-mediated killing. This finding is consistent with the known link between complement deficiencies and CFH variation with human susceptibility to IMD. These observations demonstrate the importance of human and bacterial genetic variation across the fHbp:CFH interface in determining IMD susceptibility, the transition from carriage to disease.

Chemical and Enzymatic Probing of Viral RNAs: From Infancy to Maturity and Beyond

RNA molecules are key players in a variety of biological events, and this is particularly true for viral RNAs. To better understand the replication of those pathogens and try to block them, special attention has been paid to the structure of their RNAs. Methods to probe RNA structures have been developed since the 1960s; even if they have evolved over the years, they are still in use today and provide useful information on the folding of RNA molecules, including viral RNAs. The aim of this review is to offer a historical perspective on the structural probing methods used to decipher RNA structures before the development of the selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) methodology and to show how they have influenced the current probing techniques. Actually, these technological breakthroughs, which involved advanced detection methods, were made possible thanks to the development of next-generation sequencing (NGS) but also to the previous works accumulated in the field of structural RNA biology. Finally, we will also discuss how high-throughput SHAPE (hSHAPE) paved the way for the development of sophisticated RNA structural techniques.

Machine learning a model for RNA structure prediction

RNA function crucially depends on its structure. Thermodynamic models currently used for secondary structure prediction rely on computing the partition function of folding ensembles, and can thus estimate minimum free-energy structures and ensemble populations. These models sometimes fail in identifying native structures unless complemented by auxiliary experimental data. Here, we build a set of models that combine thermodynamic parameters, chemical probing data (DMS and SHAPE) and co-evolutionary data (direct coupling analysis) through a network that outputs perturbations to the ensemble free energy. Perturbations are trained to increase the ensemble populations of a representative set of known native RNA structures. In the chemical probing nodes of the network, a convolutional window combines neighboring reactivities, enlightening their structural information content and the contribution of local conformational ensembles. Regularization is used to limit overfitting and improve transferability. The most transferable model is selected through a cross-validation strategy that estimates the performance of models on systems on which they are not trained. With the selected model we obtain increased ensemble populations for native structures and more accurate predictions in an independent validation set. The flexibility of the approach allows the model to be easily retrained and adapted to incorporate arbitrary experimental information.

Light-Dependent Translation Change of Arabidopsis psbA Correlates with RNA Structure Alterations at the Translation Initiation Region

mRNA secondary structure influences translation. Proteins that modulate the mRNA secondary structure around the translation initiation region may regulate translation in plastids. To test this hypothesis, we exposed Arabidopsis thaliana to high light, which induces translation of psbA mRNA encoding the D1 subunit of photosystem II. We assayed translation by ribosome profiling and applied two complementary methods to analyze in vivo RNA secondary structure: DMS-MaPseq and SHAPE-seq. We detected increased accessibility of the translation initiation region of psbA after high light treatment, likely contributing to the observed increase in translation by facilitating translation initiation. Furthermore, we identified the footprint of a putative regulatory protein in the 5' UTR of psbA at a position where occlusion of the nucleotide sequence would cause the structure of the translation initiation region to open up, thereby facilitating ribosome access. Moreover, we show that other plastid genes with weak Shine-Dalgarno sequences (SD) are likely to exhibit psbA-like regulation, while those with strong SDs do not. This supports the idea that changes in mRNA secondary structure might represent a general mechanism for translational regulation of psbA and other plastid genes.

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).

High-throughput determination of RNA structures

RNA performs and regulates a diverse range of cellular processes, with new functional roles being uncovered at a rapid pace. Interest is growing in how these functions are linked to RNA structures that form in the complex cellular environment. A growing suite of technologies that use advances in RNA structural probes, high-throughput sequencing and new computational approaches to interrogate RNA structure at unprecedented throughput are beginning to provide insights into RNA structures at new spatial, temporal and cellular scales.

Excess primer degradation by Exo I improves the preparation of 3' cDNA ligation-based sequencing libraries

RNA sequencing library construction using single-stranded ligation of a DNA adapter to 3' ends of cDNAs often produces primer-adapter byproducts, which compete with cDNA-adapter ligation products during library amplification and, therefore, reduces the number of informative sequencing reads. We find that Escherichia coli Exo I digestion efficiently and selectively removes surplus reverse transcription primer and thereby reduces the primer-adapter product contamination in 3' cDNA ligation-based sequencing libraries, including small RNA libraries, which are typically similar in size to the primer-adapter products. We further demonstrate that Exo I treatment does not lead to trimming of the cDNA 3' end when duplexed with the RNA template. Exo I digestion is easy to perform and implement in other protocols and could facilitate a more widespread use of 3' cDNA ligation for sequencing-based applications.

Guidelines for SHAPE Reagent Choice and Detection Strategy for RNA Structure Probing Studies

Chemical probing is an important tool for characterizing the complex folded structures of RNA molecules, many of which play key cellular roles. Electrophilic SHAPE reagents create adducts at the 2'-hydroxyl position on the RNA backbone of flexible ribonucleotides with relatively little dependence on nucleotide identity. Strategies for adduct detection such as mutational profiling (MaP) allow accurate, automated calculation of relative adduct frequencies for each nucleotide in a given RNA or group of RNAs. A number of alternative reagents and adduct detection strategies have been proposed, especially for use in living cells. Here we evaluate five SHAPE reagents: three previously well-validated reagents 1M7 (1-methyl-7-nitroisatoic anhydride), 1M6 (1-methyl-6-nitroisatoic anhydride), and NMIA ( N-methylisatoic anhydride), one more recently proposed NAI (2-methylnicotinic acid imidazolide), and one novel reagent 5NIA (5-nitroisatoic anhydride). We clarify the importance of carefully designed software in reading out SHAPE experiments using massively parallel sequencing approaches. We examine SHAPE modification in living cells in diverse cell lines, compare MaP and reverse transcription-truncation as SHAPE adduct detection strategies, make recommendations for SHAPE reagent choice, and outline areas for future development.

Sensitive detection of structural features and rearrangements in long, structured RNA molecules

Technical innovations in structural probing have drastically advanced the field of RNA structure analysis. These advances have led to parallel approaches developed in separate labs for analyzing RNA structure and dynamics. With the wealth of methodologies available, it can be difficult to determine which is best suited for a given application. Here, using a long, highly structured viral RNA as an example (the positive strand genome of Hepatitis C Virus), we present a semi-comprehensive analysis and describe the major approaches for analyzing the architecture of RNA that is modified with structure-sensitive probes. Additionally, we present an updated method for generating in vitro transcribed and folded RNA that maintains native secondary structures in long RNA molecules. We anticipate that the methods described here will streamline the use of current approaches and help investigators who are unfamiliar with structure probing, obviating the need for time-consuming and expensive optimization.

dStruct: identifying differentially reactive regions from RNA structurome profiling data

RNA biology is revolutionized by recent developments of diverse high-throughput technologies for transcriptome-wide profiling of molecular RNA structures. RNA structurome profiling data can be used to identify differentially structured regions between groups of samples. Existing methods are limited in scope to specific technologies and/or do not account for biological variation. Here, we present dStruct which is the first broadly applicable method for differential analysis accounting for biological variation in structurome profiling data. dStruct is compatible with diverse profiling technologies, is validated with experimental data and simulations, and outperforms existing methods.

The evolution of RNA structural probing methods: From gels to next-generation sequencing

RNA molecules are important players in all domains of life and the study of the relationship between their multiple flexible states and the associated biological roles has increased in recent years. For several decades, chemical and enzymatic structural probing experiments have been used to determine RNA structure. During this time, there has been a steady improvement in probing reagents and experimental methods, and today the structural biologist community has a large range of tools at its disposal to probe the secondary structure of RNAs in vitro and in cells. Early experiments used radioactive labeling and polyacrylamide gel electrophoresis as read-out methods. This was superseded by capillary electrophoresis, and more recently by next-generation sequencing. Today, powerful structural probing methods can characterize RNA structure on a genome-wide scale. In this review, we will provide an overview of RNA structural probing methodologies from a historical and technical perspective. This article is categorized under: RNA Structure and Dynamics > RNA Structure, Dynamics, and Chemistry RNA Methods > RNA Analyses in vitro and In Silico RNA Methods > RNA Analyses in Cells.

nextPARS: parallel probing of RNA structures in Illumina

RNA molecules play important roles in virtually every cellular process. These functions are often mediated through the adoption of specific structures that enable RNAs to interact with other molecules. Thus, determining the secondary structures of RNAs is central to understanding their function and evolution. In recent years several sequencing-based approaches have been developed that allow probing structural features of thousands of RNA molecules present in a sample. Here, we describe nextPARS, a novel Illumina-based implementation of in vitro parallel probing of RNA structures. Our approach achieves comparable accuracy to previous implementations, while enabling higher throughput and sample multiplexing.

Facile synthesis and evaluation of a dual-functioning furoyl probe for in-cell SHAPE

Recent analysis of transcriptomes has revealed that RNA molecules perform a myriad of functions beyond coding for proteins. RNA molecules can fold into complex secondary and tertiary structures, which are critical for regulating their function. Selective Hydroxyl Acylation analyzed by Primer Extension, or SHAPE is a common method for probing RNA structure in and outside of cells. Recent developments in SHAPE include the design of acyl imidazole acylating electrophiles with alkyl azides to enrich the sites of SHAPE adduct formation. Enrichment is key for next-generation sequencing experiments as it dramatically improves the signal. In a recent comparison of different structures of such reagents, we realized that furoyl acylating reagents form hyper-stable ester adducts with hydroxyls. This prompted us to design, synthesize and test a novel dual-functioning SHAPE probe (FAI-N₃), which has the stable furoyl scaffold and the alkyl azide for enrichment. Herein we present the results that show FAI-N₃ is a suitable probe for RNA structure analysis by SHAPE and that it can be used for enrichment of SHAPE adducts. These results strongly demonstrate that FAI-N₃ is an ideal probe for structure probing in cells and will be very useful for sequencing-based analysis of SHAPE.

Accurate detection of chemical modifications in RNA by mutational profiling (MaP) with ShapeMapper 2

Mutational profiling (MaP) enables detection of sites of chemical modification in RNA as sequence changes during reverse transcription (RT), subsequently read out by massively parallel sequencing. We introduce ShapeMapper 2, which integrates careful handling of all classes of adduct-induced sequence changes, sequence variant correction, basecall quality filters, and quality-control warnings to now identify RNA adduct sites as accurately as achieved by careful manual analysis of electrophoresis data, the prior highest-accuracy standard. MaP and ShapeMapper 2 provide a robust, experimentally concise, and accurate approach for reading out nucleic acid chemical probing experiments.

Structure-seq2: sensitive and accurate genome-wide profiling of RNA structure in vivo

RNA serves many functions in biology such as splicing, temperature sensing, and innate immunity. These functions are often determined by the structure of RNA. There is thus a pressing need to understand RNA structure and how it changes during diverse biological processes both in vivo and genome-wide. Here, we present Structure-seq2, which provides nucleotide-resolution RNA structural information in vivo and genome-wide. This optimized version of our original Structure-seq method increases sensitivity by at least 4-fold and improves data quality by minimizing formation of a deleterious by-product, reducing ligation bias, and improving read coverage. We also present a variation of Structure-seq2 in which a biotinylated nucleotide is incorporated during reverse transcription, which greatly facilitates the protocol by eliminating two PAGE purification steps. We benchmark Structure-seq2 on both mRNA and rRNA structure in rice (Oryza sativa). We demonstrate that Structure-seq2 can lead to new biological insights. Our Structure-seq2 datasets uncover hidden breaks in chloroplast rRNA and identify a previously unreported N¹-methyladenosine (m¹A) in a nuclear-encoded Oryza sativa rRNA. Overall, Structure-seq2 is a rapid, sensitive, and unbiased method to probe RNA in vivo and genome-wide that facilitates new insights into RNA biology.

Dawn of the in vivo RNA structurome and interactome

RNA is one of the most fascinating biomolecules in living systems given its structural versatility to fold into elaborate architectures for important biological functions such as gene regulation, catalysis, and information storage. Knowledge of RNA structures and interactions can provide deep insights into their functional roles in vivo For decades, RNA structural studies have been conducted on a transcript-by-transcript basis. The advent of next-generation sequencing (NGS) has enabled the development of transcriptome-wide structural probing methods to profile the global landscape of RNA structures and interactions, also known as the RNA structurome and interactome, which transformed our understanding of the RNA structure-function relationship on a transcriptomic scale. In this review, molecular tools and NGS methods used for RNA structure probing are presented, novel insights uncovered by RNA structurome and interactome studies are highlighted, and perspectives on current challenges and potential future directions are discussed. A more complete understanding of the RNA structures and interactions in vivo will help illuminate the novel roles of RNA in gene regulation, development, and diseases.

PROBer Provides a General Toolkit for Analyzing Sequencing-Based Toeprinting Assays

A number of sequencing-based transcriptase drop-off assays have recently been developed to probe post-transcriptional dynamics of RNA-protein interaction, RNA structure, and RNA modification. Although these assays survey a diverse set of epitranscriptomic marks, we use the term toeprinting assays since they share methodological similarities. Their interpretation is predicated on addressing a similar computational challenge: how to learn isoform-specific chemical modification profiles in the face of complex read multi-mapping. We introduce PROBer, a statistical model and associated software, that addresses this challenge for the analysis of toeprinting assays. PROBer takes sequencing data as input and outputs estimated transcript abundances and isoform-specific modification profiles. Results on both simulated and biological data demonstrate that PROBer significantly outperforms individual methods tailored for specific toeprinting assays. Since the space of toeprinting assays is ever expanding and these assays are likely to be performed and analyzed together, we believe PROBer's unified data analysis solution will be valuable to the RNA community.

RNA structure through multidimensional chemical mapping

The discoveries of myriad non-coding RNA molecules, each transiting through multiple flexible states in cells or virions, present major challenges for structure determination. Advances in high-throughput chemical mapping give new routes for characterizing entire transcriptomes in vivo, but the resulting one-dimensional data generally remain too information-poor to allow accurate de novo structure determination. Multidimensional chemical mapping (MCM) methods seek to address this challenge. Mutate-and-map (M2), RNA interaction groups by mutational profiling (RING-MaP and MaP-2D analysis) and multiplexed •OH cleavage analysis (MOHCA) measure how the chemical reactivities of every nucleotide in an RNA molecule change in response to modifications at every other nucleotide. A growing body of in vitro blind tests and compensatory mutation/rescue experiments indicate that MCM methods give consistently accurate secondary structures and global tertiary structures for ribozymes, ribosomal domains and ligand-bound riboswitch aptamers up to 200 nucleotides in length. Importantly, MCM analyses provide detailed information on structurally heterogeneous RNA states, such as ligand-free riboswitches that are functionally important but difficult to resolve with other approaches. The sequencing requirements of currently available MCM protocols scale at least quadratically with RNA length, precluding general application to transcriptomes or viral genomes at present. We propose a modify-cross-link-map (MXM) expansion to overcome this and other current limitations to resolving the in vivo 'RNA structurome'.

Measuring RNA structure transcriptome-wide with icSHAPE

RNA molecules can be found at the heart of nearly every aspect of gene regulation: from gene expression to protein translation. The ability of RNA molecules to fold into intricate structures guides their function. Chemical methods to measure RNA structure have been part of the RNA biologists toolkit for several decades. These methods, although often cumbersome and difficult to perform on large RNAs, are notable for their accuracy and precision of structural measurements. Recent extension of these methods to transcriptome-wide analyses has opened the door to interrogating the structure of complete RNA molecules inside cells. Within this manuscript we describe the biochemical basis for the methodology behind a novel technology, icSHAPE, which measures RNA flexibility and single-strandedness in RNA. Novel methods such as icSHAPE have greatly expanded our understanding of RNA function and have paved the way to expansive analyses of large groups of RNA structures as they function inside the native environment of the cell.

Comparative and integrative analysis of RNA structural profiling data: current practices and emerging questions

BACKGROUND

Structure profiling experiments provide single-nucleotide information on RNA structure. Recent advances in chemistry combined with application of high-throughput sequencing have enabled structure profiling at transcriptome scale and in living cells, creating unprecedented opportunities for RNA biology. Propelled by these experimental advances, massive data with ever-increasing diversity and complexity have been generated, which give rise to new challenges in interpreting and analyzing these data.

RESULTS

We review current practices in analysis of structure profiling data with emphasis on comparative and integrative analysis as well as highlight emerging questions. Comparative analysis has revealed structural patterns across transcriptomes and has become an integral component of recent profiling studies. Additionally, profiling data can be integrated into traditional structure prediction algorithms to improve prediction accuracy.

CONCLUSIONS

To keep pace with experimental developments, methods to facilitate, enhance and refine such analyses are needed. Parallel advances in analysis methodology will complement profiling technologies and help them reach their full potential.

DMS-MaPseq for genome-wide or targeted RNA structure probing in vivo

Coupling of structure-specific in vivo chemical modification to next-generation sequencing is transforming RNA secondary structure studies in living cells. The dominant strategy for detecting in vivo chemical modifications uses reverse transcriptase truncation products, which introduce biases and necessitate population-average assessments of RNA structure. Here we present dimethyl sulfate (DMS) mutational profiling with sequencing (DMS-MaPseq), which encodes DMS modifications as mismatches using a thermostable group II intron reverse transcriptase. DMS-MaPseq yields a high signal-to-noise ratio, can report multiple structural features per molecule, and allows both genome-wide studies and focused in vivo investigations of even low-abundance RNAs. We apply DMS-MaPseq for the first analysis of RNA structure within an animal tissue and to identify a functional structure involved in noncanonical translation initiation. Additionally, we use DMS-MaPseq to compare the in vivo structure of pre-mRNAs with their mature isoforms. These applications illustrate DMS-MaPseq's capacity to dramatically expand in vivo analysis of RNA structure.

Metrics for rapid quality control in RNA structure probing experiments

MOTIVATION

The diverse functionalities of RNA can be attributed to its capacity to form complex and varied structures. The recent proliferation of new structure probing techniques coupled with high-throughput sequencing has helped RNA studies expand in both scope and depth. Despite differences in techniques, most experiments face similar challenges in reproducibility due to the stochastic nature of chemical probing and sequencing. As these protocols expand to transcriptome-wide studies, quality control becomes a more daunting task. General and efficient methodologies are needed to quantify variability and quality in the wide range of current and emerging structure probing experiments.

RESULTS

We develop metrics to rapidly and quantitatively evaluate data quality from structure probing experiments, demonstrating their efficacy on both small synthetic libraries and transcriptome-wide datasets. We use a signal-to-noise ratio concept to evaluate replicate agreement, which has the capacity to identify high-quality data. We also consider and compare two methods to assess variability inherent in probing experiments, which we then utilize to evaluate the coverage adjustments needed to meet desired quality. The developed metrics and tools will be useful in summarizing large-scale datasets and will help standardize quality control in the field.

AVAILABILITY AND IMPLEMENTATION

The data and methods used in this article are freely available at: http://bme.ucdavis.edu/aviranlab/SPEQC_software CONTACT: saviran@ucdavis.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Data-directed RNA secondary structure prediction using probabilistic modeling

Structure dictates the function of many RNAs, but secondary RNA structure analysis is either labor intensive and costly or relies on computational predictions that are often inaccurate. These limitations are alleviated by integration of structure probing data into prediction algorithms. However, existing algorithms are optimized for a specific type of probing data. Recently, new chemistries combined with advances in sequencing have facilitated structure probing at unprecedented scale and sensitivity. These novel technologies and anticipated wealth of data highlight a need for algorithms that readily accommodate more complex and diverse input sources. We implemented and investigated a recently outlined probabilistic framework for RNA secondary structure prediction and extended it to accommodate further refinement of structural information. This framework utilizes direct likelihood-based calculations of pseudo-energy terms per considered structural context and can readily accommodate diverse data types and complex data dependencies. We use real data in conjunction with simulations to evaluate performances of several implementations and to show that proper integration of structural contexts can lead to improvements. Our tests also reveal discrepancies between real data and simulations, which we show can be alleviated by refined modeling. We then propose statistical preprocessing approaches to standardize data interpretation and integration into such a generic framework. We further systematically quantify the information content of data subsets, demonstrating that high reactivities are major drivers of SHAPE-directed predictions and that better understanding of less informative reactivities is key to further improvements. Finally, we provide evidence for the adaptive capability of our framework using mock probe simulations.

Understanding the Functions of Long Non-Coding RNAs through Their Higher-Order Structures

Although thousands of long non-coding RNAs (lncRNAs) have been discovered in eukaryotes, very few molecular mechanisms have been characterized due to an insufficient understanding of lncRNA structure. Therefore, investigations of lncRNA structure and subsequent elucidation of the regulatory mechanisms are urgently needed. However, since lncRNA are high molecular weight molecules, which makes their crystallization difficult, obtaining information about their structure is extremely challenging, and the structures of only several lncRNAs have been determined so far. Here, we review the structure-function relationships of the widely studied lncRNAs found in the animal and plant kingdoms, focusing on the principles and applications of both in vitro and in vivo technologies for the study of RNA structures, including dimethyl sulfate-sequencing (DMS-seq), selective 2'-hydroxyl acylation analyzed by primer extension-sequencing (SHAPE-seq), parallel analysis of RNA structure (PARS), and fragmentation sequencing (FragSeq). The aim of this review is to provide a better understanding of lncRNA biological functions by studying them at the structural level.

Transcriptome-wide interrogation of RNA secondary structure in living cells with icSHAPE

icSHAPE (in vivo click selective 2-hydroxyl acylation and profiling experiment) captures RNA secondary structure at a transcriptome-wide level by measuring nucleotide flexibility at base resolution. Living cells are treated with the icSHAPE chemical NAI-N3 followed by selective chemical enrichment of NAI-N3-modified RNA, which provides an improved signal-to-noise ratio compared with similar methods leveraging deep sequencing. Purified RNA is then reverse-transcribed to produce cDNA, with SHAPE-modified bases leading to truncated cDNA. After deep sequencing of cDNA, computational analysis yields flexibility scores for every base across the starting RNA population. The entire experimental procedure can be completed in ∼5 d, and the sequencing and bioinformatics data analysis take an additional 4-5 d with no extensive computational skills required. Comparing in vivo and in vitro icSHAPE measurements can reveal in vivo RNA-binding protein imprints or facilitate the dissection of RNA post-transcriptional modifications. icSHAPE reactivities can additionally be used to constrain and improve RNA secondary structure prediction models.

High-Throughput Nuclease Probing of RNA Structures Using FragSeq

High-throughput sequencing of cDNA (RNA-Seq) can be used to generate nuclease accessibility data for many distinct transcripts in the same mixture simultaneously. Such assays accelerate RNA structure analysis and provide researchers with new technologies to tackle biological questions on a transcriptome-wide scale. FragSeq is an experimental assay for transcriptome-wide RNA structure probing using RNA-Seq, coupled with data analysis tools that allow quantitative determination of nuclease accessibility at single-base resolution. We provide a practical guide to designing and carrying out FragSeq experiments and data analysis.

Reproducible Analysis of Sequencing-Based RNA Structure Probing Data with User-Friendly Tools

RNA structure-probing data can improve the prediction of RNA secondary and tertiary structure and allow structural changes to be identified and investigated. In recent years, massive parallel sequencing has dramatically improved the throughput of RNA structure probing experiments, but at the same time also made analysis of the data challenging for scientists without formal training in computational biology. Here, we discuss different strategies for data analysis of massive parallel sequencing-based structure-probing data. To facilitate reproducible and standardized analysis of this type of data, we have made a collection of tools, which allow raw sequencing reads to be converted to normalized probing values using different published strategies. In addition, we also provide tools for visualization of the probing data in the UCSC Genome Browser and for converting RNA coordinates to genomic coordinates and vice versa. The collection is implemented as functions in the R statistical environment and as tools in the Galaxy platform, making them easily accessible for the scientific community. We demonstrate the usefulness of the collection by applying it to the analysis of sequencing-based hydroxyl radical probing data and comparing different normalization strategies.