A two-dimensional mutate-and-map strategy for non-coding RNA structure

The role of structure in regulatory RNA elements

Regulatory RNA elements fulfill functions such as translational regulation, control of transcript levels, and regulation of viral genome replication. Trans-acting factors (i.e., RNA-binding proteins) bind the so-called cis elements and confer functionality to the complex. The specificity during protein-RNA complex (RNP) formation often exploits the structural plasticity of RNA. Functional integrity of cis-trans pairs depends on the availability of properly folded RNA elements, and RNA conformational transitions can cause diseases. Knowledge of RNA structure and the conformational space is needed for understanding complex formation and deducing functional effects. However, structure determination of RNAs under in vivo conditions remains challenging. This review provides an overview of structured eukaryotic and viral RNA cis elements and discusses the effect of RNA structural equilibria on RNP formation. We showcase implications of RNA structural changes for diseases, outline strategies for RNA structure-based drug targeting, and summarize the methodological toolbox for deciphering RNA structures.

The future of integrated structural biology

Instruct-ERIC, "the European Research Infrastructure Consortium for Structural biology research," is a pan-European distributed research infrastructure making high-end technologies and methods in structural biology available to users. Here, we describe the current state-of-the-art of integrated structural biology and discuss potential future scientific developments as an impulse for the scientific community, many of which are located in Europe and are associated with Instruct. We reflect on where to focus scientific and technological initiatives within the distributed Instruct research infrastructure. This review does not intend to make recommendations on funding requirements or initiatives directly, neither at the national nor the European level. However, it addresses future challenges and opportunities for the field, and foresees the need for a stronger coordination within the European and international research field of integrated structural biology to be able to respond timely to thematic topics that are often prioritized by calls for funding addressing societal needs.

Evaluating Performance of Different RNA Secondary Structure Prediction Programs Using Self-cleaving Ribozymes

Accurate identification of the correct, biologically relevant RNA structures is critical to understanding various aspects of RNA biology since proper folding represents the key to the functionality of all types of RNA molecules and plays pivotal roles in many essential biological processes. Thus, a plethora of approaches have been developed to predict, identify, or solve RNA structures based on various computational, molecular, genetic, chemical, or physicochemical strategies. Purely computational approaches hold distinct advantages over all other strategies in terms of the ease of implementation, time, speed, cost, and throughput, but they strongly underperform in terms of accuracy that significantly limits their broader application. Nonetheless, the advantages of these methods led to a steady development of multiple in silico RNA secondary structure prediction approaches including recent deep learning-based programs. Here, we compared the accuracy of predictions of biologically relevant secondary structures of dozens of self-cleaving ribozyme sequences using seven in silico RNA folding prediction tools with tasks of varying complexity. We found that while many programs performed well in relatively simple tasks, their performance varied significantly in more complex RNA folding problems. However, in general, a modern deep learning method outperformed the other programs in the complex tasks in predicting the RNA secondary structures, at least based on the specific class of sequences tested, suggesting that it may represent the future of RNA structure prediction algorithms.

Diversity of ribosomes at the level of rRNA variation associated with human health and disease

With hundreds of copies of rDNA, it is unknown whether they possess sequence variations that form different types of ribosomes. Here, we developed an algorithm for long-read variant calling, termed RGA, which revealed that variations in human rDNA loci are predominantly insertion-deletion (indel) variants. We developed full-length rRNA sequencing (RIBO-RT) and in situ sequencing (SWITCH-seq), which showed that translating ribosomes possess variation in rRNA. Over 1,000 variants are lowly expressed. However, tens of variants are abundant and form distinct rRNA subtypes with different structures near indels as revealed by long-read rRNA structure probing coupled to dimethyl sulfate sequencing. rRNA subtypes show differential expression in endoderm/ectoderm-derived tissues, and in cancer, low-abundance rRNA variants can become highly expressed. Together, this study identifies the diversity of ribosomes at the level of rRNA variants, their chromosomal location, and unique structure as well as the association of ribosome variation with tissue-specific biology and cancer.

Ribonanza: deep learning of RNA structure through dual crowdsourcing

Prediction of RNA structure from sequence remains an unsolved problem, and progress has been slowed by a paucity of experimental data. Here, we present Ribonanza, a dataset of chemical mapping measurements on two million diverse RNA sequences collected through Eterna and other crowdsourced initiatives. Ribonanza measurements enabled solicitation, training, and prospective evaluation of diverse deep neural networks through a Kaggle challenge, followed by distillation into a single, self-contained model called RibonanzaNet. When fine tuned on auxiliary datasets, RibonanzaNet achieves state-of-the-art performance in modeling experimental sequence dropout, RNA hydrolytic degradation, and RNA secondary structure, with implications for modeling RNA tertiary structure.

Rational design of oligonucleotides for enhanced in vitro transcription of small RNA

All kinds of RNA molecules can be produced by in vitro transcription using T7 RNA polymerase using DNA templates obtained by solid-phase chemical synthesis, primer extension, PCR, or DNA cloning. The oligonucleotide design, however, is a challenge to nonexperts as this relies on a set of rules that have been established empirically over time. Here, we describe a Python program to facilitate the rational design of oligonucleotides, calculated with kinetic parameters for enhanced in vitro transcription (ROCKET). The Python tool uses thermodynamic parameters, performs folding-energy calculations, and selects oligonucleotides suitable for the polymerase extension reaction. These oligonucleotides improve yields of template DNA. With the oligonucleotides selected by the program, the tRNA transcripts can be prepared by a one-pot reaction of the DNA polymerase extension reaction and the transcription reaction. Also, the ROCKET-selected oligonucleotides provide greater transcription yields than that from oligonucleotides selected by Primerize, a leading software for designing oligonucleotides for in vitro transcription, due to the enhancement of template DNA synthesis. Apart from over 50 tRNA genes tested, an in vitro transcribed self-cleaving ribozyme was found to have catalytic activity. In addition, the program can be applied to the synthesis of mRNA, demonstrating the wide applicability of the ROCKET software.

Diversity and modularity of tyrosine-accepting tRNA-like structures

Certain positive-sense single-stranded RNA viruses contain elements at their 3' termini that structurally mimic tRNAs. These tRNA-like structures (TLSs) are classified based on which amino acid is covalently added to the 3' end by host aminoacyl-tRNA synthetase. Recently, a cryoEM reconstruction of a representative tyrosine-accepting tRNA-like structure (TLSTyr) from brome mosaic virus (BMV) revealed a unique mode of recognition of the viral anticodon-mimicking domain by tyrosyl-tRNA synthetase. Some viruses in the hordeivirus genus of Virgaviridae are also selectively aminoacylated with tyrosine, yet these TLS RNAs have a different architecture in the 5' domain that comprises the atypical anticodon loop mimic. Herein, we present bioinformatic and biochemical data supporting a distinct secondary structure for the 5' domain of the hordeivirus TLSTyr compared to those in Bromoviridae Despite forming a different secondary structure, the 5' domain is necessary to achieve robust in vitro aminoacylation. Furthermore, a chimeric RNA containing the 5' domain from the BMV TLSTyr and the 3' domain from a hordeivirus TLSTyr are aminoacylated, illustrating modularity in these structured RNA elements. We propose that the structurally distinct 5' domain of the hordeivirus TLSTyrs performs the same role in mimicking the anticodon loop as its counterpart in the BMV TLSTyr Finally, these structurally and phylogenetically divergent types of TLSTyr provide insight into the evolutionary connections between all classes of viral tRNA-like structures.

RNA structure determination: From 2D to 3D

RNA molecules serve a wide range of functions that are closely linked to their structures. The basic structural units of RNA consist of single- and double-stranded regions. In order to carry out advanced functions such as catalysis and ligand binding, certain types of RNAs can adopt higher-order structures. The analysis of RNA structures has progressed alongside advancements in structural biology techniques, but it comes with its own set of challenges and corresponding solutions. In this review, we will discuss recent advances in RNA structure analysis techniques, including structural probing methods, X-ray crystallography, nuclear magnetic resonance, cryo-electron microscopy, and small-angle X-ray scattering. Often, a combination of multiple techniques is employed for the integrated analysis of RNA structures. We also survey important RNA structures that have been recently determined using various techniques.

Chemical crosslinking and ligation methods for in vivo analysis of RNA structures and interactions

RNA structures and interactions in living cells drive a variety of biological processes and play critical roles in physiology and disease states. However, studies of RNA structures and interactions have been challenging due to limitations in available technologies. Direct determination of structures in vitro has been only possible to a small number of RNAs with limited sizes and conformations. We recently introduced two chemical crosslink-ligation techniques that enabled studies of transcriptome-wide secondary and tertiary structures and their dynamics. In a dramatically improved version of the psoralen analysis of RNA interactions and structures (PARIS2) method, we detailed the synthesis and use of amotosalen, a highly soluble psoralen analogue, and enhanced enzymology for higher efficiency duplex capture. We also introduced spatial 2'-hydroxyl acylation reversible crosslinking (SHARC) with exonuclease (exo) trimming, a method which utilizes a novel crosslinker class that targets the 2'-OH to capture three-dimensional (3D) structures. Both are powerful orthogonal approaches for solving in vivo RNA structure and interactions, integrating crosslinking, exo trimming, proximity ligation, and high throughput sequencing. In this chapter, we present a detailed protocol for the methods and highlight steps that outperform existing crosslink-ligation approaches.

Measuring intramolecular connectivity in long RNA molecules using two-dimensional DNA patch-probe arrays

We describe a simple method to infer intramolecular connections in a population of long RNA molecules in vitro. First we add DNA oligonucleotide "patches" that perturb the RNA connections, then we use a microarray containing a complete set of DNA oligonucleotide "probes" to record where perturbations occur. The pattern of perturbations reveals couplings between different regions of the RNA sequence, from which we infer connections as well as their prevalences in the population. We validate this patch-probe method using the 1,058-nucleotide RNA genome of satellite tobacco mosaic virus (STMV), which has previously been shown to have multiple long-range connections. Our results not only indicate long duplexes that agree with previous structures but also reveal the prevalence of competing connections. Together, these results suggest that globally-folded and locally-folded structures coexist in solution. We show that the prevalence of connections changes when pseudouridine, an important component of natural and synthetic RNA molecules, is substituted for uridine in STMV RNA.

Full-Length Model of SaCas9-sgRNA-DNA Complex in Cleavage State

Staphylococcus aureus Cas9 (SaCas9) is a widely used genome editing tool. Understanding its molecular mechanisms of DNA cleavage could effectively guide the engineering optimization of this system. Here, we determined the first cryo-electron microscopy structure of the SaCas9-sgRNA-DNA ternary complex. This structure reveals that the HNH nuclease domain is tightly bound to the cleavage site of the target DNA strand, and is in close contact with the WED and REC domains. Moreover, it captures the complete structure of the sgRNA, including the previously unresolved stem-loop 2. Based on this structure, we build a full-length model for the ternary complex in cleavage state. This model enables identification of the residues for the interactions between the HNH domain and the WED and REC domains. Moreover, we found that the stem-loop 2 of the sgRNA tightly binds to the PI and RuvC domains and may also regulate the position shift of the RuvC domain. Further mutagenesis and molecular dynamics simulations supported the idea that the interactions of the HNH domain with the WED and REC domains play an important role in the DNA cleavage. Thus, this study provides new mechanistic insights into the DNA cleavage of SaCas9 and is also useful for guiding the future engineering of SaCas9-mediated gene editing systems.

Programmable antivirals targeting critical conserved viral RNA secondary structures from influenza A virus and SARS-CoV-2

Influenza A virus's (IAV's) frequent genetic changes challenge vaccine strategies and engender resistance to current drugs. We sought to identify conserved and essential RNA secondary structures within IAV's genome that are predicted to have greater constraints on mutation in response to therapeutic targeting. We identified and genetically validated an RNA structure (packaging stem-loop 2 (PSL2)) that mediates in vitro packaging and in vivo disease and is conserved across all known IAV isolates. A PSL2-targeting locked nucleic acid (LNA), administered 3 d after, or 14 d before, a lethal IAV inoculum provided 100% survival in mice, led to the development of strong immunity to rechallenge with a tenfold lethal inoculum, evaded attempts to select for resistance and retained full potency against neuraminidase inhibitor-resistant virus. Use of an analogous approach to target SARS-CoV-2, prophylactic administration of LNAs specific for highly conserved RNA structures in the viral genome, protected hamsters from efficient transmission of the SARS-CoV-2 USA_WA1/2020 variant. These findings highlight the potential applicability of this approach to any virus of interest via a process we term 'programmable antivirals', with implications for antiviral prophylaxis and post-exposure therapy.

De novo design of DNA aptamers that target okadaic acid (OA) by docking-then-assembling of single nucleotides

Okadaic acid (OA) is a diarrhetic shellfish poison widespread in ocean, so its detection is of great significance to seafood safety. Because of good sensitivity and low cost, biosensors using nucleic-acid aptamers as the recognition molecules are emerging as an important detection tool. However, the traditional SELEX screening method for acquiring OA high-affinity aptamers is time- and resource-intensive. Alternatively, here we developed a de novo design method based on the 3D structure of a target molecule, such as OA. Without experimental screening, this method designs OA aptamers by a computational approach of docking-then-assembling (DTA) of single nucleotides (A, C, G and T) as: (1) determining the high-affinity nucleotide binding sites of the target molecule via saturated molecular docking; (2) assembling the bound nucleotides into binding units to the target molecule; (3) constructing full-length aptamers by introducing stabilizing units to connect these binding units. In this way, five OA aptamers were designed, and microscale thermophoresis (MST) experiments verified that their K_d values are in the range of 100-600 nM; and one of them (named 9CGAT_4_a) could specifically bind to OA with low affinities for the other three marine biotoxins. Therefore, this study provides high-affinity and specific aptamers for the development of OA biosensors, and presents a promising de novo design method applicable to other target molecules.

Crowdsourced RNA design discovers diverse, reversible, efficient, self-contained molecular switches

Internet-based scientific communities promise a means to apply distributed, diverse human intelligence toward previously intractable scientific problems. However, current implementations have not allowed communities to propose experiments to test all emerging hypotheses at scale or to modify hypotheses in response to experiments. We report high-throughput methods for molecular characterization of nucleic acids that enable the large-scale video game–based crowdsourcing of RNA sensor design, followed by high-throughput functional characterization. Iterative design testing of thousands of crowdsourced RNA sensor designs produced near–thermodynamically optimal and reversible RNA switches that act as self-contained molecular sensors and couple five distinct small molecule inputs to three distinct protein binding and fluorogenic outputs. This work suggests a paradigm for widely distributed experimental bioscience.

Protein synthesis control in cancer: selectivity and therapeutic targeting

Translational control of mRNAs is a point of convergence for many oncogenic signals through which cancer cells tune protein expression in tumorigenesis. Cancer cells rely on translational control to appropriately adapt to limited resources while maintaining cell growth and survival, which creates a selective therapeutic window compared to non-transformed cells. In this review, we first discuss how cancer cells modulate the translational machinery to rapidly and selectively synthesize proteins in response to internal oncogenic demands and external factors in the tumor microenvironment. We highlight the clinical potential of compounds that target different translation factors as anti-cancer therapies. Next, we detail how RNA sequence and structural elements interface with the translational machinery and RNA-binding proteins to coordinate the translation of specific pro-survival and pro-growth programs. Finally, we provide an overview of the current and emerging technologies that can be used to illuminate the mechanisms of selective translational control in cancer cells as well as within the microenvironment.

Chemical reversible crosslinking enables measurement of RNA 3D distances and alternative conformations in cells

Three-dimensional (3D) structures dictate the functions of RNA molecules in a wide variety of biological processes. However, direct determination of RNA 3D structures in vivo is difficult due to their large sizes, conformational heterogeneity, and dynamics. Here we present a method, Spatial 2'-Hydroxyl Acylation Reversible Crosslinking (SHARC), which uses chemical crosslinkers of defined lengths to measure distances between nucleotides in cellular RNA. Integrating crosslinking, exonuclease (exo) trimming, proximity ligation, and high throughput sequencing, SHARC enables transcriptome-wide tertiary structure contact maps at high accuracy and precision, revealing heterogeneous RNA structures and interactions. SHARC data provide constraints that improves Rosetta-based RNA 3D structure modeling at near-nanometer resolution. Integrating SHARC-exo with other crosslinking-based methods, we discover compact folding of the 7SK RNA, a critical regulator of transcriptional elongation. These results establish a strategy for measuring RNA 3D distances and alternative conformations in their native cellular context.

Short- and long-range interactions in the HIV-1 5' UTR regulate genome dimerization and packaging

RNA dimerization is the noncovalent association of two human immunodeficiency virus-1 (HIV-1) genomes. It is a conserved step in the HIV-1 life cycle and assumed to be a prerequisite for binding to the viral structural protein Pr55^Gag during genome packaging. Here, we developed functional analysis of RNA structure-sequencing (FARS-seq) to comprehensively identify sequences and structures within the HIV-1 5' untranslated region (UTR) that regulate this critical step. Using FARS-seq, we found nucleotides important for dimerization throughout the HIV-1 5' UTR and identified distinct structural conformations in monomeric and dimeric RNA. In the dimeric RNA, key functional domains, such as stem-loop 1 (SL1), polyadenylation signal (polyA) and primer binding site (PBS), folded into independent structural motifs. In the monomeric RNA, SL1 was reconfigured into long- and short-range base pairings with polyA and PBS, respectively. We show that these interactions disrupt genome packaging, and additionally show that the PBS-SL1 interaction unexpectedly couples the PBS with dimerization and Pr55^Gag binding. Altogether, our data provide insights into late stages of HIV-1 life cycle and a mechanistic explanation for the link between RNA dimerization and packaging.

U2 snRNA structure is influenced by SF3A and SF3B proteins but not by SF3B inhibitors

U2 snRNP is an essential component of the spliceosome. It is responsible for branch point recognition in the spliceosome A-complex via base-pairing of U2 snRNA with an intron to form the branch helix. Small molecule inhibitors target the SF3B component of the U2 snRNP and interfere with A-complex formation during spliceosome assembly. We previously found that the first SF3B inhibited-complex is less stable than A-complex and hypothesized that SF3B inhibitors interfere with U2 snRNA secondary structure changes required to form the branch helix. Using RNA chemical modifiers, we probed U2 snRNA structure in A-complex and SF3B inhibited splicing complexes. The reactivity pattern for U2 snRNA in the SF3B inhibited-complex is indistinguishable from that of A-complex, suggesting that they have the same secondary structure conformation, including the branch helix. This observation suggests SF3B inhibited-complex instability does not stem from an alternate RNA conformation and instead points to the inhibitors interfering with protein component interactions that normally stabilize U2 snRNP’s association with an intron. In addition, we probed U2 snRNA in the free U2 snRNP in the presence of SF3B inhibitor and again saw no differences. However, increased protection of nucleotides upstream of Stem I in the absence of SF3A and SF3B proteins suggests a change of secondary structure at the very 5′ end of U2 snRNA. Chemical probing of synthetic U2 snRNA in the absence of proteins results in similar protections and predicts a previously uncharacterized extension of Stem I. Because this stem must be disrupted for SF3A and SF3B proteins to stably join the snRNP, the structure has the potential to influence snRNP assembly and recycling after spliceosome disassembly.

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.

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 .

Three-dimensional structure of a flavivirus dumbbell RNA reveals molecular details of an RNA regulator of replication

Mosquito-borne flaviviruses (MBFVs) including dengue, West Nile, yellow fever, and Zika viruses have an RNA genome encoding one open reading frame flanked by 5' and 3' untranslated regions (UTRs). The 3' UTRs of MBFVs contain regions of high sequence conservation in structured RNA elements known as dumbbells (DBs). DBs regulate translation and replication of the viral RNA genome, functions proposed to depend on the formation of an RNA pseudoknot. To understand how DB structure provides this function, we solved the x-ray crystal structure of the Donggang virus DB to 2.1Å resolution and used structural modeling to reveal the details of its three-dimensional fold. The structure confirmed the predicted pseudoknot and molecular modeling revealed how conserved sequences form a four-way junction that appears to stabilize the pseudoknot. Single-molecule FRET suggests that the DB pseudoknot is a stable element that can regulate the switch between translation and replication during the viral lifecycle by modulating long-range RNA conformational changes.

Direct Mapping of Higher-Order RNA Interactions by SHAPE-JuMP

Higher-order structure governs function for many RNAs. However, discerning this structure for large RNA molecules in solution is an unresolved challenge. Here, we present SHAPE-JuMP (selective 2'-hydroxyl acylation analyzed by primer extension and juxtaposed merged pairs) to interrogate through-space RNA tertiary interactions. A bifunctional small molecule is used to chemically link proximal nucleotides in an RNA structure. The RNA cross-link site is then encoded into complementary DNA (cDNA) in a single, direct step using an engineered reverse transcriptase that "jumps" across cross-linked nucleotides. The resulting cDNAs contain a deletion relative to the native RNA sequence, which can be detected by sequencing, that indicates the sites of cross-linked nucleotides. SHAPE-JuMP measures RNA tertiary structure proximity concisely across large RNA molecules at nanometer resolution. SHAPE-JuMP is especially effective at measuring interactions in multihelix junctions and loop-to-helix packing, enables modeling of the global fold for RNAs up to several hundred nucleotides in length, facilitates ranking of structural models by consistency with through-space restraints, and is poised to enable solution-phase structural interrogation and modeling of complex RNAs.

An expanded class of histidine-accepting viral tRNA-like structures

Structured RNA elements are common in the genomes of RNA viruses, often playing critical roles during viral infection. Some viral RNA elements use forms of tRNA mimicry, but the diverse ways this mimicry can be achieved are poorly understood. Histidine-accepting tRNA-like structures (TLS^His) are examples found at the 3' termini of some positive-sense single-stranded RNA (+ssRNA) viruses where they interact with several host proteins, induce histidylation of the RNA genome, and facilitate processes important for infection, to include genome replication. As only five TLS^His examples had been reported, we explored the possible larger phylogenetic distribution and diversity of this TLS class using bioinformatic approaches. We identified many new examples of TLS^His, yielding a rigorous consensus sequence and secondary structure model that we validated by chemical probing of representative TLS^His RNAs. We confirmed new examples as authentic TLS^His by demonstrating their ability to be histidylated in vitro, then used mutational analyses to imply a tertiary interaction that is likely analogous to the D- and T-loop interaction found in canonical tRNAs. These results expand our understanding of how diverse RNA sequences achieve tRNA-like structure and function in the context of viral RNA genomes and lay the groundwork for high-resolution structural studies of tRNA mimicry by histidine-accepting TLSs.

Learning cis-regulatory principles of ADAR-based RNA editing from CRISPR-mediated mutagenesis

Adenosine-to-inosine (A-to-I) RNA editing catalyzed by ADAR enzymes occurs in double-stranded RNAs. Despite a compelling need towards predictive understanding of natural and engineered editing events, how the RNA sequence and structure determine the editing efficiency and specificity (i.e., cis-regulation) is poorly understood. We apply a CRISPR/Cas9-mediated saturation mutagenesis approach to generate libraries of mutations near three natural editing substrates at their endogenous genomic loci. We use machine learning to integrate diverse RNA sequence and structure features to model editing levels measured by deep sequencing. We confirm known features and identify new features important for RNA editing. Training and testing XGBoost algorithm within the same substrate yield models that explain 68 to 86 percent of substrate-specific variation in editing levels. However, the models do not generalize across substrates, suggesting complex and context-dependent regulation patterns. Our integrative approach can be applied to larger scale experiments towards deciphering the RNA editing code.

Functional and structural basis of extreme conservation in vertebrate 5' untranslated regions

The lack of knowledge about extreme conservation in genomes remains a major gap in our understanding of the evolution of gene regulation. Here, we reveal an unexpected role of extremely conserved 5' untranslated regions (UTRs) in noncanonical translational regulation that is linked to the emergence of essential developmental features in vertebrate species. Endogenous deletion of conserved elements within these 5' UTRs decreased gene expression, and extremely conserved 5' UTRs possess cis-regulatory elements that promote cell-type-specific regulation of translation. We further developed in-cell mutate-and-map (icM²), a new methodology that maps RNA structure inside cells. Using icM², we determined that an extremely conserved 5' UTR encodes multiple alternative structures and that each single nucleotide within the conserved element maintains the balance of alternative structures important to control the dynamic range of protein expression. These results explain how extreme sequence conservation can lead to RNA-level biological functions encoded in the untranslated regions of vertebrate genomes.

IsRNA1: De Novo Prediction and Blind Screening of RNA 3D Structures

Modeling structures and functions of large ribonucleic acid (RNAs) especially with complicated topologies is highly challenging due to the inefficiency of large conformational sampling and the presence of complicated tertiary interactions. To address this problem, one highly promising approach is coarse-grained modeling. Here, following an iterative simulated reference state approach to decipher the correlations between different structural parameters, we developed a potent coarse-grained RNA model named as IsRNA1 for RNA studies. Molecular dynamics simulations in the IsRNA1 can predict the native structures of small RNAs from a sequence and fold medium-sized RNAs into near-native tertiary structures with the assistance of secondary structure constraints. A large-scale benchmark test on RNA 3D structure prediction shows that IsRNA1 exhibits improved performance for relatively large RNAs of complicated topologies, such as large stem-loop structures and structures containing long-range tertiary interactions. The advantages of IsRNA1 include the consideration of the correlations between the different structural variables, the appropriate characterization of canonical base-pairing and base-stacking interactions, and the better sampling for the backbone conformations. Moreover, a blind screening protocol was developed based on IsRNA1 to identify good structural models from a pool of candidates without prior knowledge of the native structures.

High-Throughput Analysis and Engineering of Ribozymes and Deoxyribozymes by Sequencing

Ribozymes and deoxyribozymes are catalytic RNA and DNA, respectively, that catalyze chemical reactions such as self-cleavage or ligation reactions. While some ribozymes are found in nature, a larger variety of ribozymes and deoxyribozymes have been discovered by in vitro selection from random sequences. These catalytic nucleic acids, especially ribozymes, are of fundamental interest because they are crucial for the RNA world hypothesis, which suggests that RNA played a central role in both the propagation of genetic information and catalyzing metabolic reactions in primordial life prior to the emergence of proteins and DNA. On the practical side, catalytic nucleic acids have been extensively engineered for various applications, such as biosensors and genetic devices for synthetic biology. Therefore, it is important to gain a deeper understanding of the sequence-function relationships of ribozymes and deoxyribozymes.Mutational analysis, or measurements of activities of catalytic nucleic acid mutants, is one of the most fundamental approaches for that purpose. Mutations that abolish, reduce, retain, or even increase activity provide useful information about nucleic acid catalysts for engineering and other purposes. However, methods for mutational analysis of ribozymes and deoxyribozymes have not evolved much for decades, requiring tedious and low-throughput assays (e.g., gel electrophoresis) of individually prepared mutants. This has prevented researchers from performing quantitative mutational analysis of ribozymes and deoxyribozymes on a large scale.To address this limitation, we developed a massively parallel ribozyme and deoxyribozyme assay strategy that allows >10⁴ assays using high-throughput sequencing (HTS). We used HTS to literally count the number of cleaved (or ligated) and uncleaved (or unligated) ribozyme (or deoxyribozyme) sequences and calculated the activities of each mutant in a reaction mixture. This simple yet powerful strategy was applied to analyze the mutational effects of various natural and synthetic ribozymes and deoxyribozymes at scales impossible for conventional mutational analysis. These large-scale sequence-function data sets were used to better understand the functional consequences of mutations and to engineer ribozymes for practical applications. Furthermore, these newly available data are motivating researchers to employ more rigorous computational methods to extract additional insights such as structural information and nonlinear effects of multiple mutations. The new HTS-based assay strategy is distinct from and complementary to a related strategy that uses HTS to analyze ribozyme and deoxyribozyme populations subjected to in vitro selection. Postselection sequencing can cover a larger sequence space, although it does not directly quantify the activities of ribozyme and deoxyribozyme mutants. With further advances in DNA sequencing technologies and computational methods, there should be more opportunities to harness the power of HTS to deepen our understanding of catalytic nucleic acids and enhance our ability to engineer them for even more applications.

Folding heterogeneity in the essential human telomerase RNA three-way junction

Telomeres safeguard the genome by suppressing illicit DNA damage responses at chromosome termini. To compensate for incomplete DNA replication at telomeres, most continually dividing cells, including many cancers, express the telomerase ribonucleoprotein (RNP) complex. Telomerase maintains telomere length by catalyzing de novo synthesis of short DNA repeats using an internal telomerase RNA (TR) template. TRs from diverse species harbor structurally conserved domains that contribute to RNP biogenesis and function. In vertebrate TRs, the conserved regions 4 and 5 (CR4/5) fold into a three-way junction (TWJ) that binds directly to the telomerase catalytic protein subunit and is required for telomerase function. We have analyzed the structural properties of the human TR (hTR) CR4/5 domain using a combination of in vitro chemical mapping, secondary structural modeling, and single-molecule structural analysis. Our data suggest the essential P6.1 stem-loop within CR4/5 is not stably folded in the absence of the telomerase reverse transcriptase in vitro. Rather, the hTR CR4/5 domain adopts a heterogeneous ensemble of conformations. Finally, single-molecule FRET measurements of CR4/5 and a mutant designed to stabilize the P6.1 stem demonstrate that TERT binding selects for a structural conformation of CR4/5 that is not the dominant state of the TERT-free in vitro RNA ensemble.

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.

Comprehensive sequence-to-function mapping of cofactor-dependent RNA catalysis in the glmS ribozyme

Massively parallel, quantitative measurements of biomolecular activity across sequence space can greatly expand our understanding of RNA sequence-function relationships. We report the development of an RNA-array assay to perform such measurements and its application to a model RNA: the core glmS ribozyme riboswitch, which performs a ligand-dependent self-cleavage reaction. We measure the cleavage rates for all possible single and double mutants of this ribozyme across a series of ligand concentrations, determining kcat and KM values for active variants. These systematic measurements suggest that evolutionary conservation in the consensus sequence is driven by maintenance of the cleavage rate. Analysis of double-mutant rates and associated mutational interactions produces a structural and functional mapping of the ribozyme sequence, revealing the catalytic consequences of specific tertiary interactions, and allowing us to infer structural rearrangements that permit certain sequence variants to maintain activity.

An RNA pseudoknot stimulates HTLV-1 pro-pol programmed -1 ribosomal frameshifting

Programmed -1 ribosomal frameshifts (-1 PRFs) are commonly used by viruses to regulate their enzymatic and structural protein levels. Human T-cell leukemia virus type 1 (HTLV-1) is a carcinogenic retrovirus that uses two independent -1 PRFs to express viral enzymes critical to establishing new HTLV-1 infections. How the cis-acting RNA elements in this viral transcript function to induce frameshifting is unknown. The objective of this work was to conclusively define the 3' boundary of and the RNA elements within the HTLV-1 pro-pol frameshift site. We hypothesized that the frameshift site structure was a pseudoknot and that its 3' boundary would be defined by the pseudoknot's 3' end. To test these hypotheses, the in vitro frameshift efficiencies of three HTLV-1 pro-pol frameshift sites with different 3' boundaries were quantified. The results indicated that nucleotides included in the longest construct were essential to highly efficient frameshift stimulation. Interestingly, only this construct could form the putative frameshift site pseudoknot. Next, the secondary structure of this frameshift site was determined. The dominant structure was an H-type pseudoknot which, together with the slippery sequence, stimulated frameshifting to 19.4(±0.3)%. The pseudoknot's critical role in frameshift stimulation was directly revealed by examining the impact of structural changes on HTLV-1 pro-pol -1 PRF. As predicted, mutations that occluded pseudoknot formation drastically reduced the frameshift efficiency. These results are significant because they demonstrate that a pseudoknot is important to HTLV-1 pro-pol -1 PRF and define the frameshift site's 3' boundary.

Accurate inference of the full base-pairing structure of RNA by deep mutational scanning and covariation-induced deviation of activity

Despite the large number of noncoding RNAs in human genome and their roles in many diseases include cancer, we know very little about them due to lack of structural clues. The centerpiece of the structural clues is the full RNA base-pairing structure of secondary and tertiary contacts that can be precisely obtained only from costly and time-consuming 3D structure determination. Here, we performed deep mutational scanning of self-cleaving CPEB3 ribozyme by error-prone PCR and showed that a library of <5 × 104 single-to-triple mutants is sufficient to infer 25 of 26 base pairs including non-nested, nonhelical, and noncanonical base pairs with both sensitivity and precision at 96%. Such accurate inference was further confirmed by a twister ribozyme at 100% precision with only noncanonical base pairs as false negatives. The performance was resulted from analyzing covariation-induced deviation of activity by utilizing both functional and nonfunctional variants for unsupervised classification, followed by Monte Carlo (MC) simulated annealing with mutation-derived scores. Highly accurate inference can also be obtained by combining MC with evolution/direct coupling analysis, R-scape or epistasis analysis. The results highlight the usefulness of deep mutational scanning for high-accuracy structural inference of self-cleaving ribozymes with implications for other structured RNAs that permit high-throughput functional selections.

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.

Sequence- And Structure-Specific Probing of RNAs by Short Nucleobase-Modified dsRNA-Binding PNAs Incorporating a Fluorescent Light-up Uracil Analog

RNAs are emerging as important biomarkers and therapeutic targets. The strategy of directly targeting double-stranded RNA (dsRNA) by triplex-formation is relatively underexplored mainly due to the weak binding at physiological conditions for the traditional triplex-forming oligonucleotides (TFOs). Compared to DNA and RNA, peptide nucleic acids (PNAs) are chemically stable and have a neutral peptide-like backbone, and thus, they show significantly enhanced binding to natural nucleic acids. We have successfully developed nucleobase-modified dsRNA-binding PNAs (dbPNAs) to facilitate structure-specific and selective recognition of dsRNA over single-stranded RNA (ssRNA) and dsDNA regions at near-physiological conditions. The triplex formation strategy facilitates the targeting of not only the sequence but also the secondary structure of RNA. Here, we report the development of novel dbPNA-based fluorescent light-up probes through the incorporation of A-U pair-recognizing 5-benzothiophene uracil (^btU). The incorporation of ^btU into dbPNAs does not affect the binding affinity toward dsRNAs significantly, in most cases, as evidenced by our nondenaturing gel shift assay data. The blue fluorescence emission intensity of ^btU-modified dbPNAs is sequence- and structure-specifically enhanced by dsRNAs, including the influenza viral RNA panhandle duplex and HIV-1-1 ribosomal frameshift-inducing RNA hairpin, but not ssRNAs or DNAs, at 200 mM NaCl, pH 7.5. Thus, dbPNAs incorporating ^btU-modified and other further modified fluorescent nucleobases will be useful biochemical tools for probing and detecting RNA structures, interactions, and functions.

Computational modeling of RNA 3D structure based on experimental data

RNA molecules are master regulators of cells. They are involved in a variety of molecular processes: they transmit genetic information, sense cellular signals and communicate responses, and even catalyze chemical reactions. As in the case of proteins, RNA function is dictated by its structure and by its ability to adopt different conformations, which in turn is encoded in the sequence. Experimental determination of high-resolution RNA structures is both laborious and difficult, and therefore the majority of known RNAs remain structurally uncharacterized. To address this problem, predictive computational methods were developed based on the accumulated knowledge of RNA structures determined so far, the physical basis of the RNA folding, and taking into account evolutionary considerations, such as conservation of functionally important motifs. However, all theoretical methods suffer from various limitations, and they are generally unable to accurately predict structures for RNA sequences longer than 100-nt residues unless aided by additional experimental data. In this article, we review experimental methods that can generate data usable by computational methods, as well as computational approaches for RNA structure prediction that can utilize data from experimental analyses. We outline methods and data types that can be potentially useful for RNA 3D structure modeling but are not commonly used by the existing software, suggesting directions for future development.

The RNA Base-Pairing Problem and Base-Pairing Solutions

RNA molecules are folded into structures and complexes to perform a wide variety of functions. Determination of RNA structures and their interactions is a fundamental problem in RNA biology. Most RNA molecules in living cells are large and dynamic, posing unique challenges to structure analysis. Here we review progress in RNA structure analysis, focusing on methods that use the "cross-link, proximally ligate, and sequence" principle for high-throughput detection of base-pairing interactions in living cells. Beginning with a comparison of commonly used methods in structure determination and a brief historical account of psoralen cross-linking studies, we highlight the important features of cross-linking methods and new biological insights into RNA structures and interactions from recent studies. Further improvement of these cross-linking methods and application to previously intractable problems will shed new light on the mechanisms of the "modern RNA world."

Gene regulation by a glycine riboswitch singlet uses a finely tuned energetic landscape for helical switching

Riboswitches contain structured aptamer domains that, upon ligand binding, facilitate helical switching in their downstream expression platforms to alter gene expression. To fully dissect how riboswitches function requires a better understanding of the energetic landscape for helical switching. Here, we report a sequencing-based high-throughput assay for monitoring in vitro transcription termination and use it to simultaneously characterize the functional effects of all 522 single point mutants of a glycine riboswitch type-1 singlet. Mutations throughout the riboswitch cause ligand-dependent defects, but only mutations within the terminator hairpin alter readthrough efficiencies in the absence of ligand. A comprehensive analysis of the expression platform reveals that ligand binding stabilizes the antiterminator by just 2-3 kcal/mol, indicating that the competing expression platform helices must be extremely close in energy to elicit a significant ligand-dependent response. These results demonstrate that gene regulation by this riboswitch is highly constrained by the energetics of ligand binding and conformational switching. These findings exemplify the energetic parameters of RNA conformational rearrangements driven by binding events.

Ribosome-induced RNA conformational changes in a viral 3'-UTR sense and regulate translation levels

Structured RNA elements, programmed RNA conformational changes, and interactions between different RNA domains underlie many modes of regulating gene expression, mandating studies to understand the foundational principles that govern these phenomena. Exploring the structured 3' untranslated region (UTR) of a viral RNA, we discovered that different contexts of the 3'-UTR confer different abilities to enhance translation of an associated open reading frame. In one context, ribosome-induced conformational changes in a 'sensor' RNA domain affect a separate RNA 'functional' domain, altering translation efficiency. The structure of the entire 3'-UTR reveals that structurally distinct domains use a spine of continuously stacked bases and a strut-like linker to create a conduit for communication within the higher-order architecture. Thus, this 3'-UTR RNA illustrates how RNA can use programmed conformational changes to sense the translation status of an upstream open reading frame, then create a tuned functional response by communicating that information to other RNA elements.

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.

Quantitative Understanding of SHAPE Mechanism from RNA Structure and Dynamics Analysis

The selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) method probes RNA local structural and dynamic information at single nucleotide resolution. To gain quantitative insights into the relationship between nucleotide flexibility, RNA 3D structure, and SHAPE reactivity, we develop a 3D Structure-SHAPE Relationship model (3DSSR) to rebuild SHAPE profiles from 3D structures. The model starts from RNA structures and combines nucleotide interaction strength and conformational propensity, ligand (SHAPE reagent) accessibility, and base-pairing pattern through a composite function to quantify the correlation between SHAPE reactivity and nucleotide conformational stability. The 3DSSR model shows the relationship between SHAPE reactivity and RNA structure and energetics. Comparisons between the 3DSSR-predicted SHAPE profile and the experimental SHAPE data show correlation, suggesting that the extracted analytical function may have captured the key factors that determine the SHAPE reactivity profile. Furthermore, the theory offers an effective method to sieve RNA 3D models and exclude models that are incompatible with experimental SHAPE data.

Atomic structures of excited state A-T Hoogsteen base pairs in duplex DNA by combining NMR relaxation dispersion, mutagenesis, and chemical shift calculations

NMR relaxation dispersion studies indicate that in canonical duplex DNA, Watson-Crick base pairs (bps) exist in dynamic equilibrium with short-lived low abundance excited state Hoogsteen bps. N1-methylated adenine (m¹A) and guanine (m¹G) are naturally occurring forms of damage that stabilize Hoogsteen bps in duplex DNA. NMR dynamic ensembles of DNA duplexes with m¹A-T Hoogsteen bps reveal significant changes in sugar pucker and backbone angles in and around the Hoogsteen bp, as well as kinking of the duplex towards the major groove. Whether these structural changes also occur upon forming excited state Hoogsteen bps in unmodified duplexes remains to be established because prior relaxation dispersion probes provided limited information regarding the sugar-backbone conformation. Here, we demonstrate measurements of C3' and C4' spin relaxation in the rotating frame (R1ρ) in uniformly ¹³C/¹⁵N labeled DNA as sensitive probes of the sugar-backbone conformation in DNA excited states. The chemical shifts, combined with structure-based predictions using an automated fragmentation quantum mechanics/molecular mechanics method, show that the dynamic ensemble of DNA duplexes containing m¹A-T Hoogsteen bps accurately model the excited state Hoogsteen conformation in two different sequence contexts. Formation of excited state A-T Hoogsteen bps is accompanied by changes in sugar-backbone conformation that allow the flipped syn adenine to form hydrogen-bonds with its partner thymine and this in turn results in overall kinking of the DNA toward the major groove. Results support the assignment of Hoogsteen bps as the excited state observed in canonical duplex DNA, provide an atomic view of DNA dynamics linked to formation of Hoogsteen bps, and lay the groundwork for a potentially general strategy for solving structures of nucleic acid excited states.

Allele-specific SHAPE-MaP assessment of the effects of somatic variation and protein binding on mRNA structure

The impact of inherited and somatic mutations on messenger RNA (mRNA) structure remains poorly understood. Recent technological advances that leverage next-generation sequencing to obtain experimental structure data, such as SHAPE-MaP, can reveal structural effects of mutations, especially when these data are incorporated into structure modeling. Here, we analyze the ability of SHAPE-MaP to detect the relatively subtle structural changes caused by single-nucleotide mutations. We find that allele-specific sorting greatly improved our detection ability. Thus, we used SHAPE-MaP with a novel combination of clone-free robotic mutagenesis and allele-specific sorting to perform a rapid, comprehensive survey of noncoding somatic and inherited riboSNitches in two cancer-associated mRNAs, TPT1 and LCP1 Using rigorous thermodynamic modeling of the Boltzmann suboptimal ensemble, we identified a subset of mutations that change TPT1 and LCP1 RNA structure, with approximately 14% of all variants identified as riboSNitches. To confirm that these in vitro structures were biologically relevant, we tested how dependent TPT1 and LCP1 mRNA structures were on their environments. We performed SHAPE-MaP on TPT1 and LCP1 mRNAs in the presence or absence of cellular proteins and found that both mRNAs have similar overall folds in all conditions. RiboSNitches identified within these mRNAs in vitro likely exist under biological conditions. Overall, these data reveal a robust mRNA structural landscape where differences in environmental conditions and most sequence variants do not significantly alter RNA structural ensembles. Finally, predicting riboSNitches in mRNAs from sequence alone remains particularly challenging; these data will provide the community with benchmarks for further algorithmic development.

Classification of RNA structure change by 'gazing' at experimental data

Motivation

Mutations (or Single Nucleotide Variants) in folded RiboNucleic Acid structures that cause local or global conformational change are riboSNitches. Predicting riboSNitches is challenging, as it requires making two, albeit related, structure predictions. The data most often used to experimentally validate riboSNitch predictions is Selective 2' Hydroxyl Acylation by Primer Extension, or SHAPE. Experimentally establishing a riboSNitch requires the quantitative comparison of two SHAPE traces: wild-type (WT) and mutant. Historically, SHAPE data was collected on electropherograms and change in structure was evaluated by 'gel gazing.' SHAPE data is now routinely collected with next generation sequencing and/or capillary sequencers. We aim to establish a classifier capable of simulating human 'gazing' by identifying features of the SHAPE profile that human experts agree 'looks' like a riboSNitch.

Results

We find strong quantitative agreement between experts when RNA scientists 'gaze' at SHAPE data and identify riboSNitches. We identify dynamic time warping and seven other features predictive of the human consensus. The classSNitch classifier reported here accurately reproduces human consensus for 167 mutant/WT comparisons with an Area Under the Curve (AUC) above 0.8. When we analyze 2019 mutant traces for 17 different RNAs, we find that features of the WT SHAPE reactivity allow us to improve thermodynamic structure predictions of riboSNitches. This is significant, as accurate RNA structural analysis and prediction is likely to become an important aspect of precision medicine.

Availability and Implementation

The classSNitch R package is freely available at http://classsnitch.r-forge.r-project.org .

Contact

alain@email.unc.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Functional 5' UTR mRNA structures in eukaryotic translation regulation and how to find them

RNA molecules can fold into intricate shapes that can provide an additional layer of control of gene expression beyond that of their sequence. In this Review, we discuss the current mechanistic understanding of structures in 5' untranslated regions (UTRs) of eukaryotic mRNAs and the emerging methodologies used to explore them. These structures may regulate cap-dependent translation initiation through helicase-mediated remodelling of RNA structures and higher-order RNA interactions, as well as cap-independent translation initiation through internal ribosome entry sites (IRESs), mRNA modifications and other specialized translation pathways. We discuss known 5' UTR RNA structures and how new structure probing technologies coupled with prospective validation, particularly compensatory mutagenesis, are likely to identify classes of structured RNA elements that shape post-transcriptional control of gene expression and the development of multicellular organisms.

Allosteric mechanism of the V. vulnificus adenine riboswitch resolved by four-dimensional chemical mapping

The structural interconversions that mediate the gene regulatory functions of RNA molecules may be different from classic models of allostery, but the relevant structural correlations have remained elusive in even intensively studied systems. Here, we present a four-dimensional expansion of chemical mapping called lock-mutate-map-rescue (LM²R), which integrates multiple layers of mutation with nucleotide-resolution chemical mapping. This technique resolves the core mechanism of the adenine-responsive V. vulnificus add riboswitch, a paradigmatic system for which both Monod-Wyman-Changeux (MWC) conformational selection models and non-MWC alternatives have been proposed. To discriminate amongst these models, we locked each functionally important helix through designed mutations and assessed formation or depletion of other helices via compensatory rescue evaluated by chemical mapping. These LM²R measurements give strong support to the pre-existing correlations predicted by MWC models, disfavor alternative models, and suggest additional structural heterogeneities that may be general across ligand-free riboswitches.

Primerize-2D: automated primer design for RNA multidimensional chemical mapping

Summary

Rapid RNA synthesis of comprehensive single mutant libraries and targeted multiple mutant libraries is enabling new multidimensional chemical approaches to solve RNA structures. PCR assembly of DNA templates and in vitro transcription allow synthesis and purification of hundreds of RNA mutants in a cost-effective manner, with sharing of primers across constructs allowing significant reductions in expense. However, these protocols require organization of primer locations across numerous 96 well plates and guidance for pipetting, non-trivial tasks for which informatics and visualization tools can prevent costly errors. We report here an online tool to accelerate synthesis of large libraries of desired mutants through design and efficient organization of primers. The underlying program and graphical interface have been experimentally tested in our laboratory for RNA domains with lengths up to 300 nucleotides and libraries encompassing up to 960 variants. In addition to the freely available Primerize-2D server, the primer design code is available as a stand-alone Python package for broader applications.

Availability and Implementation

http://primerize2d.stanford.edu.

Contact

rhiju@stanford.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

New windows into retroviral RNA structures

Background

The multiple roles of both viral and cellular RNAs have become increasingly apparent in recent years, and techniques to model them have become significantly more powerful, enabling faster and more accurate visualization of RNA structures.

Main body

Techniques such as SHAPE (selective 2’OH acylation analysed by primer extension) have revolutionized the field, and have been used to examine RNAs belonging to many and diverse retroviruses. Secondary structure probing reagents such as these have been aided by the development of faster methods of analysis either via capillary or next-generation sequencing, allowing the analysis of entire genomes, and of retroviral RNA structures within virions. Techniques to model the three-dimensional structures of these large RNAs have also recently developed.

Conclusions

The flexibility of retroviral RNAs, both structural and functional, is clear from the results of these new experimental techniques. Retroviral RNA structures and structural changes control many stages of the lifecycle, and both the RNA structures themselves and their interactions with ligands are potential new drug targets. In addition, our growing understanding of retroviral RNA structures is aiding our knowledge of cellular RNA form and function.

RNA structure inference through chemical mapping after accidental or intentional mutations

Despite the critical roles RNA structures play in regulating gene expression, sequencing-based methods for experimentally determining RNA base pairs have remained inaccurate. Here, we describe a multidimensional chemical-mapping method called "mutate-and-map read out through next-generation sequencing" (M2-seq) that takes advantage of sparsely mutated nucleotides to induce structural perturbations at partner nucleotides and then detects these events through dimethyl sulfate (DMS) probing and mutational profiling. In special cases, fortuitous errors introduced during DNA template preparation and RNA transcription are sufficient to give M2-seq helix signatures; these signals were previously overlooked or mistaken for correlated double-DMS events. When mutations are enhanced through error-prone PCR, in vitro M2-seq experimentally resolves 33 of 68 helices in diverse structured RNAs including ribozyme domains, riboswitch aptamers, and viral RNA domains with a single false positive. These inferences do not require energy minimization algorithms and can be made by either direct visual inspection or by a neural-network-inspired algorithm called M2-net. Measurements on the P4-P6 domain of the Tetrahymena group I ribozyme embedded in Xenopus egg extract demonstrate the ability of M2-seq to detect RNA helices in a complex biological environment.

Comparative Visualization of the RNA Suboptimal Conformational Ensemble In Vivo

When a ribonucleic acid (RNA) molecule folds, it often does not adopt a single, well-defined conformation. The folding energy landscape of an RNA is highly dependent on its nucleotide sequence and molecular environment. Cellular molecules sometimes alter the energy landscape, thereby changing the ensemble of likely low-energy conformations. The effects of these energy landscape changes on the conformational ensemble are particularly challenging to visualize for large RNAs. We have created a robust approach for visualizing the conformational ensemble of RNAs that is well suited for in vitro versus in vivo comparisons. Our method creates a stable map of conformational space for a given RNA sequence. We first identify single point mutations in the RNA that maximally sample suboptimal conformational space based on the ensemble’s partition function. Then, we cluster these diverse ensembles to identify the most diverse partition functions for Boltzmann stochastic sampling. By using, to our knowledge, a novel nestedness distance metric, we iteratively add mutant suboptimal ensembles to converge on a stable 2D map of conformational space. We then compute the selective 2′ hydroxyl acylation by primer extension (SHAPE)-directed ensemble for the RNA folding under different conditions, and we project these ensembles on the map to visualize. To validate our approach, we established a conformational map of the Vibrio vulnificus add adenine riboswitch that reveals five classes of structures. In the presence of adenine, projection of the SHAPE-directed sampling correctly identified the on-conformation; without the ligand, only off-conformations were visualized. We also collected the whole-transcript in vitro and in vivo SHAPE-MaP for human β-actin messenger RNA that revealed similar global folds in both conditions. Nonetheless, a comparison of in vitro and in vivo data revealed that specific regions exhibited significantly different SHAPE-MaP profiles indicative of structural rearrangements, including rearrangement consistent with binding of the zipcode protein in a region distal to the stop codon.