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

Michael addition-activated alkylation of G-quadruplex DNA with methylamine-protected vinyl-quinazolinone derivatives

The role of G-quadruplex (G4) in cellular processes can be investigated by the covalent modification of G4-DNA using alkylating reagents. Controllable alkylating reagents activated by external stimuli can react elegantly and selectively. Herein, we report a chemical activation system that can significantly boost the reaction rate of methylamine-protected vinyl-quinazolinone (VQ) derivative for the alkylation of G4-DNA. The two screened activators can transform low-reactive VQ-NHR' to highly reactive intermediates following the Michael addition mechanism. This approach expands the toolbox of activable G4 alkylating reagents.

Mitochondrial sequencing identifies long noncoding RNA features that promote binding to PNPase

Extranuclear localization of long noncoding RNAs (lncRNAs) is poorly understood. Based on machine learning evaluations, we propose a lncRNA-mitochondrial interaction pathway where polynucleotide phosphorylase (PNPase), through domains that provide specificity for primary sequence and secondary structure, binds nuclear-encoded lncRNAs to facilitate mitochondrial import. Using FVB/NJ mouse and human cardiac tissues, RNA from isolated subcellular compartments (cytoplasmic and mitochondrial) and cross-linked immunoprecipitate (CLIP) with PNPase within the mitochondrion were sequenced on the Illumina HiSeq and MiSeq, respectively. lncRNA sequence and structure were evaluated through supervised [classification and regression trees (CART) and support vector machines (SVM)] machine learning algorithms. In HL-1 cells, quantitative PCR of PNPase CLIP knockout mutants (KH and S1) was performed. In vitro fluorescence assays assessed PNPase RNA binding capacity and verified with PNPase CLIP. One hundred twelve (mouse) and 1,548 (human) lncRNAs were identified in the mitochondrion with Malat1 being the most abundant. Most noncoding RNAs binding PNPase were lncRNAs, including Malat1. lncRNA fragments bound to PNPase compared against randomly generated sequences of similar length showed stratification with SVM and CART algorithms. The lncRNAs bound to PNPase were used to create a criterion for binding, with experimental validation revealing increased binding affinity of RNA designed to bind PNPase compared to control RNA. The binding of lncRNAs to PNPase was decreased through the knockout of RNA binding domains KH and S1. In conclusion, sequence and secondary structural features identified by machine learning enhance the likelihood of nuclear-encoded lncRNAs binding to PNPase and undergoing import into the mitochondrion.NEW & NOTEWORTHY Long noncoding RNAs (lncRNAs) are relatively novel RNAs with increasingly prominent roles in regulating genetic expression, mainly in the nucleus but more recently in regions such as the mitochondrion. This study explores how lncRNAs interact with polynucleotide phosphorylase (PNPase), a protein that regulates RNA import into the mitochondrion. Machine learning identified several RNA structural features that improved lncRNA binding to PNPase, which may be useful in targeting RNA therapeutics to the mitochondrion.

RNA tertiary structure and conformational dynamics revealed by BASH MaP

The functional effects of an RNA can arise from complex three-dimensional folds known as tertiary structures. However, predicting the tertiary structure of an RNA and whether an RNA adopts distinct tertiary conformations remains challenging. To address this, we developed BASH MaP, a single-molecule dimethyl sulfate (DMS) footprinting method and DAGGER, a computational pipeline, to identify alternative tertiary structures adopted by different molecules of RNA. BASH MaP utilizes potassium borohydride to reveal the chemical accessibility of the N7 position of guanosine, a key mediator of tertiary structures. We used BASH MaP to identify diverse conformational states and dynamics of RNA G-quadruplexes, an important RNA tertiary motif, in vitro and in cells. BASH MaP and DAGGER analysis of the fluorogenic aptamer Spinach reveals that it adopts alternative tertiary conformations which determine its fluorescence states. BASH MaP thus provides an approach for structural analysis of RNA by revealing previously undetectable tertiary structures.

Hfq mediates transcriptome-wide RNA structurome reprogramming under virulence-inducing conditions in a phytopathogen

Although RNA structures play important roles in regulating gene expression, the mechanism and function of mRNA folding in plant bacterial pathogens remain elusive. Therefore, we perform dimethyl sulfate sequencing (DMS-seq) on the Pseudomonas syringae under nutrition-rich and -deficient conditions, revealing that the mRNA structure changes substantially in the minimal medium (MM) that tunes global translation efficiency (TE), thereby inducing virulence. This process is led by the increased expression of hfq, which is directly activated by transcription regulators RpoS and CysB. The co-occurrence of Hfq and RpoS in diverse bacteria and the deep conservation of Hfq Y25 is critical for RNA-mediated regulation and implicates the wider biological importance of mRNA structure and feedback loops in the control of global gene expression.

The human mitochondrial mRNA structurome reveals mechanisms of gene expression

The human mitochondrial genome encodes crucial oxidative phosphorylation system proteins, pivotal for aerobic energy transduction. They are translated from nine monocistronic and two bicistronic transcripts whose native structures remain unexplored, posing a gap in understanding mitochondrial gene expression. In this work, we devised the mitochondrial dimethyl sulfate mutational profiling with sequencing (mitoDMS-MaPseq) method and applied detection of RNA folding ensembles using expectation-maximization (DREEM) clustering to unravel the native mitochondrial messenger RNA (mt-mRNA) structurome in wild-type (WT) and leucine-rich pentatricopeptide repeat-containing protein (LRPPRC)-deficient cells. Our findings elucidate LRPPRC's role as a holdase contributing to maintaining mt-mRNA folding and efficient translation. mt-mRNA structural insights in WT mitochondria, coupled with metabolic labeling, unveil potential mRNA-programmed translational pausing and a distinct programmed ribosomal frameshifting mechanism. Our data define a critical layer of mitochondrial gene expression regulation. These mt-mRNA folding maps provide a reference for studying mt-mRNA structures in diverse physiological and pathological contexts.

A systematic search for RNA structural switches across the human transcriptome

RNA structural switches are key regulators of gene expression in bacteria, but their characterization in Metazoa remains limited. Here, we present SwitchSeeker, a comprehensive computational and experimental approach for systematic identification of functional RNA structural switches. We applied SwitchSeeker to the human transcriptome and identified 245 putative RNA switches. To validate our approach, we characterized a previously unknown RNA switch in the 3' untranslated region of the RORC (RAR-related orphan receptor C) transcript. In vivo dimethyl sulfate (DMS) mutational profiling with sequencing (DMS-MaPseq), coupled with cryogenic electron microscopy, confirmed its existence as two alternative structural conformations. Furthermore, we used genome-scale CRISPR screens to identify trans factors that regulate gene expression through this RNA structural switch. We found that nonsense-mediated messenger RNA decay acts on this element in a conformation-specific manner. SwitchSeeker provides an unbiased, experimentally driven method for discovering RNA structural switches that shape the eukaryotic gene expression landscape.

Parallel degradome-seq and DMS-MaPseq substantially revise the miRNA biogenesis atlas in Arabidopsis

MicroRNAs (miRNAs) are produced from highly structured primary transcripts (pri-miRNAs) and regulate numerous biological processes in eukaryotes. Due to the extreme heterogeneity of these structures, the initial processing sites of plant pri-miRNAs and the structural rules that determine their processing have been predicted for many miRNAs but remain elusive for others. Here we used semi-active DCL1 mutants and advanced degradome-sequencing strategies to accurately identify the initial processing sites for 147 of 326 previously annotated Arabidopsis miRNAs and to illustrate their associated pri-miRNA cleavage patterns. Elucidating the in vivo RNA secondary structures of 73 pri-miRNAs revealed that about 95% of them differ from in silico predictions, and that the revised structures offer clearer interpretation of the processing sites and patterns. Finally, DCL1 partners Serrate and HYL1 could synergistically and independently impact processing patterns and in vivo RNA secondary structures of pri-miRNAs. Together, our work sheds light on the precise processing mechanisms of plant pri-miRNAs.

Co-transcriptional gene regulation in eukaryotes and prokaryotes

Many steps of RNA processing occur during transcription by RNA polymerases. Co-transcriptional activities are deemed commonplace in prokaryotes, in which the lack of membrane barriers allows mixing of all gene expression steps, from transcription to translation. In the past decade, an extraordinary level of coordination between transcription and RNA processing has emerged in eukaryotes. In this Review, we discuss recent developments in our understanding of co-transcriptional gene regulation in both eukaryotes and prokaryotes, comparing methodologies and mechanisms, and highlight striking parallels in how RNA polymerases interact with the machineries that act on nascent RNA. The development of RNA sequencing and imaging techniques that detect transient transcription and RNA processing intermediates has facilitated discoveries of transcription coordination with splicing, 3'-end cleavage and dynamic RNA folding and revealed physical contacts between processing machineries and RNA polymerases. Such studies indicate that intron retention in a given nascent transcript can prevent 3'-end cleavage and cause transcriptional readthrough, which is a hallmark of eukaryotic cellular stress responses. We also discuss how coordination between nascent RNA biogenesis and transcription drives fundamental aspects of gene expression in both prokaryotes and eukaryotes.

An intricate balancing act: Upstream and downstream frameshift co-regulatory elements

Targeting ribosomal frameshifting has emerged as a potential therapeutic intervention strategy against Covid-19. During ribosomal translation, a fraction of elongating ribosomes slips by one base in the 5' direction and enters a new reading frame for viral protein synthesis. Any interference with this process profoundly affects viral replication and propagation. For Covid-19, two RNA sites associated with ribosomal frameshifting for SARS-CoV-2 are positioned on the 5' and 3' of the frameshifting residues. Although much attention has been on the 3' frameshift element (FSE), the 5' stem-loop (attenuator hairpin, AH) can play a role. The formation of AH has been suggested to occur as refolding of the 3' RNA structure is triggered by ribosomal unwinding. However, the attenuation activity and the relationship between the two regions are unknown. To gain more insight into these two related viral RNAs and to further enrich our understanding of ribosomal frameshifting for SARS-CoV-2, we explore the RNA folding of both 5' and 3' regions associated with frameshifting. Using our graph-theory-based modeling tools to represent RNA secondary structures, "RAG" (RNA- As-Graphs), and conformational landscapes to analyze length-dependent conformational distributions, we show that AH coexists with the 3-stem pseudoknot of the 3' FSE (graph 3_6 in our dual graph notation) and alternative pseudoknot (graph 3_3) but less likely with other 3' FSE alternative folds (such as 3-way junction 3_5). This is because an alternative length-dependent Stem 1 (AS1) can disrupt the FSE pseudoknots and trigger other folds. In addition, we design four mutants for long lengths that stabilize or disrupt AH, AS1 or FSE pseudoknot to illustrate the deduced AH/AS1 roles and favor the 3_5, 3_6 or stem-loop. These mutants further show how a strengthened pseudoknot can result from a weakened AS1, while a dominant stem-loop occurs with a strengthened AS1. These structural and mutational insights into both ends of the FSE in SARS-CoV-2 advance our understanding of the SARS-CoV-2 frameshifting mechanism by suggesting a sequence of length-dependent folds, which in turn define potential therapeutic intervention techniques involving both elements. Our work also highlights the complexity of viral landscapes with length-dependent folds, and challenges in analyzing these multiple conformations.

Identification of RNA structures and their roles in RNA functions

The development of high-throughput RNA structure profiling methods in the past decade has greatly facilitated our ability to map and characterize different aspects of RNA structures transcriptome-wide in cell populations, single cells and single molecules. The resulting high-resolution data have provided insights into the static and dynamic nature of RNA structures, revealing their complexity as they perform their respective functions in the cell. In this Review, we discuss recent technical advances in the determination of RNA structures, and the roles of RNA structures in RNA biogenesis and functions, including in transcription, processing, translation, degradation, localization and RNA structure-dependent condensates. We also discuss the current understanding of how RNA structures could guide drug design for treating genetic diseases and battling pathogenic viruses, and highlight existing challenges and future directions in RNA structure research.

The RNA secondary structure of androgen receptor-FL and V7 transcripts reveals novel regulatory regions

The androgen receptor (AR) is a ligand-dependent nuclear transcription factor belonging to the steroid hormone nuclear receptor family. Due to its roles in regulating cell proliferation and differentiation, AR is tightly regulated to maintain proper levels of itself and the many genes it controls. AR dysregulation is a driver of many human diseases including prostate cancer. Though this dysregulation often occurs at the RNA level, there are many unknowns surrounding post-transcriptional regulation of AR mRNA, particularly the role that RNA secondary structure plays. Thus, a comprehensive analysis of AR transcript secondary structure is needed. We address this through the computational and experimental analyses of two key isoforms, full length (AR-FL) and truncated (AR-V7). Here, a combination of in-cell RNA secondary structure probing experiments (targeted DMS-MaPseq) and computational predictions were used to characterize the static structural landscape and conformational dynamics of both isoforms. Additionally, in-cell assays were used to identify functionally relevant structures in the 5' and 3' UTRs of AR-FL. A notable example is a conserved stem loop structure in the 5'UTR of AR-FL that can bind to Poly(RC) Binding Protein 2 (PCBP2). Taken together, our results reveal novel features that regulate AR expression.

N6-methyladenosine modification of a parvovirus-encoded small noncoding RNA facilitates viral DNA replication through recruiting Y-family DNA polymerases

Human bocavirus 1 (HBoV1) is a human parvovirus that causes lower respiratory tract infections in young children. It contains a single-stranded (ss) DNA genome of ~5.5 kb that encodes a small noncoding RNA of 140 nucleotides known as bocavirus-encoded small RNA (BocaSR), in addition to viral proteins. Here, we determined the secondary structure of BocaSR in vivo by using DMS-MaPseq. Our findings reveal that BocaSR undergoes N6-methyladenosine (m6A) modification at multiple sites, which is critical for viral DNA replication in both dividing HEK293 cells and nondividing cells of the human airway epithelium. Mechanistically, we found that m6A-modified BocaSR serves as a mediator for recruiting Y-family DNA repair DNA polymerase (Pol) η and Pol κ likely through a direct interaction between BocaSR and the viral DNA replication origin at the right terminus of the viral genome. Thus, this report represents direct involvement of a viral small noncoding RNA in viral DNA replication through m6A modification.

A new reagent for in vivo structure probing of RNA G and U residues that improves RNA structure prediction alone and combined with DMS

A key to understanding the roles of RNA in regulating gene expression is knowing their structures in vivo. One way to obtain this information is through probing the structures of RNA with chemicals. To probe RNA structure directly in cells, membrane-permeable reagents that modify the Watson-Crick (WC) face of unpaired nucleotides can be used. Although dimethyl sulfate (DMS) has led to substantial insight into RNA structure, it has limited nucleotide specificity in vivo, with WC face reactivity only at adenine (A) and cytosine (C) at neutral pH. The reagent 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC) was recently shown to modify the WC face of guanine (G) and uracil (U). Although useful at lower concentrations in experiments that measure chemical modifications by reverse transcription (RT) stops, at higher concentrations necessary for detection by mutational profiling (MaP), EDC treatment leads to degradation of RNA. Here, we demonstrate EDC-stimulated degradation of RNA in Gram-negative and Gram-positive bacteria. In an attempt to overcome these limitations, we developed a new carbodiimide reagent, 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide methiodide (ETC), which we show specifically modifies unpaired Gs and Us in vivo without substantial degradation of RNA. We establish ETC as a probe for MaP and optimize the RT conditions and computational analysis in Escherichia coli Importantly, we demonstrate the utility of ETC as a probe for improving RNA structure prediction both alone and with DMS.

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.

Molecular insights into regulatory RNAs in the cellular machinery

It is apparent that various functional units within the cellular machinery are derived from RNAs. The evolution of sequencing techniques has resulted in significant insights into approaches for transcriptome studies. Organisms utilize RNA to govern cellular systems, and a heterogeneous class of RNAs is involved in regulatory functions. In particular, regulatory RNAs are increasingly recognized to participate in intricately functioning machinery across almost all levels of biological systems. These systems include those mediating chromatin arrangement, transcription, suborganelle stabilization, and posttranscriptional modifications. Any class of RNA exhibiting regulatory activity can be termed a class of regulatory RNA and is typically represented by noncoding RNAs, which constitute a substantial portion of the genome. These RNAs function based on the principle of structural changes through cis and/or trans regulation to facilitate mutual RNA‒RNA, RNA‒DNA, and RNA‒protein interactions. It has not been clearly elucidated whether regulatory RNAs identified through deep sequencing actually function in the anticipated mechanisms. This review addresses the dominant properties of regulatory RNAs at various layers of the cellular machinery and covers regulatory activities, structural dynamics, modifications, associated molecules, and further challenges related to therapeutics and deep learning.

Probing RNA structure and dynamics using nanopore and next generation sequencing

It has become increasingly evident that the structures RNAs adopt are conformationally dynamic; the various structured states that RNAs sample govern their interactions with other nucleic acids, proteins, and ligands to regulate a myriad of biological processes. Although several biophysical approaches have been developed and used to study the dynamic landscape of structured RNAs, technical limitations have limited their application to all classes of RNA due to variable size and flexibility. Recent advances combining chemical probing experiments with next-generation- and direct sequencing have emerged as an alternative approach to exploring the conformational dynamics of RNA. In this review, we provide a methodological overview of the sequencing-based techniques used to study RNA conformational dynamics. We discuss how different techniques have enabled us to better understand the propensity of RNAs from a variety of different classes to sample multiple conformational states. Finally, we present examples of the ways these techniques have reshaped how we think about RNA structure.

Isoform-specific RNA structure determination using Nano-DMS-MaP

RNA structure determination is essential to understand how RNA carries out its diverse biological functions. In cells, RNA isoforms are readily expressed with partial variations within their sequences due, for example, to alternative splicing, heterogeneity in the transcription start site, RNA processing or differential termination/polyadenylation. Nanopore dimethyl sulfate mutational profiling (Nano-DMS-MaP) is a method for in situ isoform-specific RNA structure determination. Unlike similar methods that rely on short sequencing reads, Nano-DMS-MaP employs nanopore sequencing to resolve the structures of long and highly similar RNA molecules to reveal their previously hidden structural differences. This Protocol describes the development and applications of Nano-DMS-MaP and outlines the main considerations for designing and implementing a successful experiment: from bench to data analysis. In cell probing experiments can be carried out by an experienced molecular biologist in 3-4 d. Data analysis requires good knowledge of command line tools and Python scripts and requires a further 3-5 d.

Quantification of tRNA m1A modification by templated-ligation qPCR

N1-methyladenosine (m1A) is a widespread modification in all eukaryotic, many archaeal, and some bacterial tRNAs. m1A is generally located in the T loop of cytosolic tRNA and between the acceptor and D stems of mitochondrial tRNAs; it is involved in the tertiary interaction that stabilizes tRNA. Human tRNA m1A levels are dynamically regulated that fine-tune translation and can also serve as biomarkers for infectious disease. Although many methods have been used to measure m1A, a PCR method to assess m1A levels quantitatively in specific tRNAs has been lacking. Here we develop a templated-ligation followed by a qPCR method (TL-qPCR) that measures m1A levels in target tRNAs. Our method uses the SplintR ligase that efficiently ligates two tRNA complementary DNA oligonucleotides using tRNA as the template, followed by qPCR using the ligation product as the template. m1A interferes with the ligation in specific ways, allowing for the quantitative assessment of m1A levels using subnanogram amounts of total RNA. We identify the features of specificity and quantitation for m1A-modified model RNAs and apply these to total RNA samples from human cells. Our method enables easy access to study the dynamics and function of this pervasive tRNA modification.

Integrated multiplexed assays of variant effect reveal determinants of catechol-O-methyltransferase gene expression

Multiplexed assays of variant effect are powerful methods to profile the consequences of rare variants on gene expression and organismal fitness. Yet, few studies have integrated several multiplexed assays to map variant effects on gene expression in coding sequences. Here, we pioneered a multiplexed assay based on polysome profiling to measure variant effects on translation at scale, uncovering single-nucleotide variants that increase or decrease ribosome load. By combining high-throughput ribosome load data with multiplexed mRNA and protein abundance readouts, we mapped the cis-regulatory landscape of thousands of catechol-O-methyltransferase (COMT) variants from RNA to protein and found numerous coding variants that alter COMT expression. Finally, we trained machine learning models to map signatures of variant effects on COMT gene expression and uncovered both directional and divergent impacts across expression layers. Our analyses reveal expression phenotypes for thousands of variants in COMT and highlight variant effects on both single and multiple layers of expression. Our findings prompt future studies that integrate several multiplexed assays for the readout of gene expression.

Unveiling hidden structural patterns in the SARS-CoV-2 genome: Computational insights and comparative analysis

SARS-CoV-2, the causative agent of COVID-19, is known to exhibit secondary structures in its 5' and 3' untranslated regions, along with the frameshifting stimulatory element situated between ORF1a and 1b. To identify additional regions containing conserved structures, we utilized a multiple sequence alignment with related coronaviruses as a starting point. We applied a computational pipeline developed for identifying non-coding RNA elements. Our pipeline employed three different RNA structural prediction approaches. We identified forty genomic regions likely to harbor structures, with ten of them showing three-way consensus substructure predictions among our predictive utilities. We conducted intracomparisons of the predictive utilities within the pipeline and intercomparisons with four previously published SARS-CoV-2 structural datasets. While there was limited agreement on the precise structure, different approaches seemed to converge on regions likely to contain structures in the viral genome. By comparing and combining various computational approaches, we can predict regions most likely to form structures, as well as a probable structure or ensemble of structures. These predictions can be used to guide surveillance, prophylactic measures, or therapeutic efforts. Data and scripts employed in this study may be found at https://doi.org/10.5281/zenodo.8298680.

Abolished frameshifting for predicted structure-stabilizing SARS-CoV-2 mutants: Implications to alternative conformations and their statistical structural analyses

The SARS-CoV-2 frameshifting element (FSE) has been intensely studied and explored as a therapeutic target for coronavirus diseases including COVID-19. Besides the intriguing virology, this small RNA is known to adopt many length-dependent conformations, as verified by multiple experimental and computational approaches. However, the role these alternative conformations play in the frameshifting mechanism and how to quantify this structural abundance has been an ongoing challenge. Here, we show by DMS and dual-luciferase functional assays that previously predicted FSE mutants (using the RAG graph theory approach) suppress structural transitions and abolish frameshifting. Furthermore, correlated mutation analysis of DMS data by three programs (DREEM, DRACO, and DANCE-MaP) reveals important differences in their estimation of specific RNA conformations, suggesting caution in the interpretation of such complex conformational landscapes. Overall, the abolished frameshifting in three different mutants confirms that all alternative conformations play a role in the pathways of ribosomal transition.

Structural atlas of human primary microRNAs generated by SHAPE-MaP

MicroRNA (miRNA) maturation is critically dependent on structural features of primary transcripts (pri-miRNAs). However, the scarcity of determined pri-miRNA structures has limited our understanding of miRNA maturation. Here, we employed selective 2'-hydroxyl acylation analyzed by primer extension and mutational profiling (SHAPE-MaP), a high-throughput RNA structure probing method, to unravel the secondary structures of 476 high-confidence human pri-miRNAs. Our SHAPE-based structures diverge substantially from those inferred solely from computation, particularly in the apical loop and basal segments, underlining the need for experimental data in RNA structure prediction. By comparing the structures with high-throughput processing data, we determined the optimal structural features of pri-miRNAs. The sequence determinants are influenced substantially by their structural contexts. Moreover, we identified an element termed the bulged GWG motif (bGWG) with a 3' bulge in the lower stem, which promotes processing. Our structure-function mapping better annotates the determinants of pri-miRNA processing and offers practical implications for designing small hairpin RNAs and predicting the impacts of miRNA mutations.

Bipartite viral RNA genome heterodimerization influences genome packaging and virion thermostability

Multi-segmented viruses often multimerize their genomic segments to ensure efficient and stoichiometric packaging of the correct genetic cargo. In the bipartite Nodaviridae family, genome heterodimerization is also observed and conserved among different species. However, the nucleotide composition and biological function for this heterodimer remain unclear. Using Flock House virus as a model system, we developed a next-generation sequencing approach ("XL-ClickSeq") to probe heterodimer site sequences. We identified an intermolecular base-pairing site which contributed to heterodimerization in both wild-type and defective virus particles. Mutagenic disruption of this heterodimer site exhibited significant deficiencies in genome packaging and encapsidation specificity to viral genomic RNAs. Furthermore, the disruption of this intermolecular interaction directly impacts the thermostability of the mature virions. These results demonstrate that the intermolecular RNA-RNA interactions within the encapsidated genome of an RNA virus have an important role on virus particle integrity and thus may impact its transmission to a new host.IMPORTANCEFlock House virus is a member of Nodaviridae family of viruses, which provides a well-studied model virus for non-enveloped RNA virus assembly, cell entry, and replication. The Flock House virus genome consists of two separate RNA molecules, which can form a heterodimer upon heating of virus particles. Although similar RNA dimerization is utilized by other viruses (such as retroviruses) as a packaging mechanism and is conserved among Nodaviruses, the role of heterodimerization in the Nodavirus replication cycle is unclear. In this research, we identified the RNA sequences contributing to Flock House virus genome heterodimerization and discovered that such RNA-RNA interaction plays an essential role in virus packaging efficiency and particle integrity. This provides significant insight into how the interaction of packaged viral RNA may have a broader impact on the structural and functional properties of virus particles.

Quantitative profiling of human translation initiation reveals regulatory elements that potently affect endogenous and therapeutically modified mRNAs

mRNA therapeutics offer a potentially universal strategy for the efficient development and delivery of therapeutic proteins. Current mRNA vaccines include chemically modified nucleotides to reduce cellular immunogenicity. Here, we develop an efficient, high-throughput method to measure human translation initiation on therapeutically modified as well as endogenous RNAs. Using systems-level biochemistry, we quantify ribosome recruitment to tens of thousands of human 5' untranslated regions and identify sequences that mediate 250-fold effects. We observe widespread effects of coding sequences on translation initiation and identify small regulatory elements of 3-6 nucleotides that are sufficient to potently affect translational output. Incorporation of N1-methylpseudouridine (m1Ψ) selectively enhances translation by specific 5' UTRs that we demonstrate surpass those of current mRNA vaccines. Our approach is broadly applicable to dissect mechanisms of human translation initiation and engineer more potent therapeutic mRNAs.

Highlights

Measurement of >30,000 human 5' UTRs reveals a 250-fold range of translation outputSystematic mutagenesis demonstrates the causality of short (3-6nt) regulatory elementsN1-methylpseudouridine alters translation initiation in a sequence-specific mannerOptimal modified 5' UTRs outperform those in the current class of mRNA vaccines.

Small RNA structural biochemistry in a post-sequencing era

High-throughput sequencing has had an enormous impact on small RNA research during the past decade. However, sequencing only offers a one-dimensional view of the transcriptome and is often highly biased. Additionally, the 'sequence, map and annotate' approach, used widely in small RNA research, can lead to flawed interpretations of the data, lacking biological plausibility, due in part to database issues. Even in the absence of technical biases, the loss of three-dimensional information is a major limitation to understanding RNA stability, turnover and function. For example, noncoding RNA-derived fragments seem to exist mainly as dimers, tetramers or as nicked forms of their parental RNAs, contrary to widespread assumptions. In this perspective, we will discuss main sources of bias during small RNA-sequencing, present several useful bias-reducing strategies and provide guidance on the interpretation of small RNA-sequencing results, with emphasis on RNA fragmentomics. As sequencing offers a one-dimensional projection of a four-dimensional reality, prior structure-level knowledge is often needed to make sense of the data. Consequently, while less-biased sequencing methods are welcomed, integration of orthologous experimental techniques is also strongly recommended.

RNA structure profiling at single-cell resolution reveals new determinants of cell identity

RNA structure is critical for multiple steps in gene regulation. However, how the structures of transcripts differ both within and between individual cells is unknown. Here we develop a SHAPE-inspired method called single-cell structure probing of RNA transcripts that enables simultaneous determination of transcript secondary structure and abundance at single-cell resolution. We apply single-cell structure probing of RNA transcripts to human embryonic stem cells and differentiating neurons. Remarkably, RNA structure is more homogeneous in human embryonic stem cells compared with neurons, with the greatest homogeneity found in coding regions. More extensive heterogeneity is found within 3' untranslated regions and is determined by specific RNA-binding proteins. Overall RNA structure profiles better discriminate cell type identity and differentiation stage than gene expression profiles alone. We further discover a cell-type variable region of 18S ribosomal RNA that is associated with cell cycle and translation control. Our method opens the door to the systematic characterization of RNA structure-function relationships at single-cell resolution.

Graph Convolutional Network for predicting secondary structure of RNA

The prediction of RNA secondary structures is essential for understanding its underlying principles and applications in diverse fields, including molecular diagnostics and RNA-based therapeutic strategies. However, the complexity of the search space presents a challenge. This work proposes a Graph Convolutional Network (GCNfold) for predicting the RNA secondary structure. GCNfold considers an RNA sequence as graph-structured data and predicts posterior base-pairing probabilities given the prior base-pairing probabilities, calculated using McCaskill's partition function. The performance of GCNfold surpasses that of the state-of-the-art folding algorithms, as we have incorporated minimum free energy information into the richly parameterized network, enhancing its robustness in predicting non-homologous RNA secondary structures. A Symmetric Argmax Post-processing algorithm ensures that GCNfold formulates valid structures. To validate our algorithm, we applied it to the SARS-CoV-2 E gene and determined the secondary structure of the E-gene across the Betacoronavirus subgenera.

Structured 3' UTRs destabilize mRNAs in plants

BACKGROUND

RNA secondary structure (RSS) can influence the regulation of transcription, RNA processing, and protein synthesis, among other processes. 3' untranslated regions (3' UTRs) of mRNA also hold the key for many aspects of gene regulation. However, there are often contradictory results regarding the roles of RSS in 3' UTRs in gene expression in different organisms and/or contexts.

RESULTS

Here, we incidentally observe that the primary substrate of miR159a (pri-miR159a), when embedded in a 3' UTR, could promote mRNA accumulation. The enhanced expression is attributed to the earlier polyadenylation of the transcript within the hybrid pri-miR159a-3' UTR and, resultantly, a poorly structured 3' UTR. RNA decay assays indicate that poorly structured 3' UTRs could promote mRNA stability, whereas highly structured 3' UTRs destabilize mRNA in vivo. Genome-wide DMS-MaPseq also reveals the prevailing inverse relationship between 3' UTRs' RSS and transcript accumulation in the transcriptomes of Arabidopsis, rice, and even human. Mechanistically, transcripts with highly structured 3' UTRs are preferentially degraded by 3'-5' exoribonuclease SOV and 5'-3' exoribonuclease XRN4, leading to decreased expression in Arabidopsis. Finally, we engineer different structured 3' UTRs to an endogenous FT gene and alter the FT-regulated flowering time in Arabidopsis.

CONCLUSIONS

We conclude that highly structured 3' UTRs typically cause reduced accumulation of the harbored transcripts in Arabidopsis. This pattern extends to rice and even mammals. Furthermore, our study provides a new strategy of engineering the 3' UTRs' RSS to modify plant traits in agricultural production and mRNA stability in biotechnology.

Analysis of Telomerase RNA Structure in Physcomitrium patens Indicates Functionally Relevant Transitions Between OPEN and CLOSED Conformations

Telomerase RNA (TR) conformation determines its function as a template for telomere synthesis and as a scaffold for the assembly of the telomerase nucleoprotein complex. Experimental analyses of TR secondary structure using DMS-Map Seq and SHAPE-Map Seq techniques show its CLOSED conformation as the consensus structure where the template region cannot perform its function. Our data show that the apparent discrepancy between experimental results and predicted TR functional conformation, mostly ignored in published studies, can be explained using data analysis based on single-molecule structure prediction from individual sequencing reads by the recently established DaVinci method. This method results in several clusters of secondary structures reflecting the structural dynamics of TR, possibly related to its multiple functional states. Interestingly, the presumed active (OPEN) conformation of TR corresponds to a minor fraction of TR under in vivo conditions. Therefore, structural polymorphism and dynamic TR transitions between CLOSED and OPEN conformations may be involved in telomerase activity regulation as a switch that functions independently of total TR transcript levels.

RNA G-quadruplexes and stress: emerging mechanisms and functions

RNA G-quadruplexes (rG4s) are noncanonical secondary structures formed by guanine-rich sequences that are found in different regions of RNA molecules. These structures have been implicated in diverse biological processes, including translation, splicing, and RNA stability. Recent studies have suggested that rG4s play a role in the cellular response to stress. This review summarizes the current knowledge on rG4s under stress, focusing on their formation, regulation, and potential functions in stress response pathways. We discuss the molecular mechanisms that regulate the formation of rG4 under different stress conditions and the impact of these structures on RNA metabolism, gene expression, and cell survival. Finally, we highlight the potential therapeutic implications of targeting rG4s for the treatment of stress-related diseases through modulating cell survival.

Visualizing a two-state conformational ensemble in stem-loop 3 of the transcriptional regulator 7SK RNA

Structural plasticity is integral to RNA function; however, there are currently few methods to quantitatively resolve RNAs that have multiple structural states. NMR spectroscopy is a powerful approach for resolving conformational ensembles but is size-limited. Chemical probing is well-suited for large RNAs but provides limited structural and kinetics information. Here, we integrate the two approaches to visualize a two-state conformational ensemble for the central stem-loop 3 (SL3) of 7SK RNA, a critical element for 7SK RNA function in transcription regulation. We find that the SL3 distal end exchanges between two equally populated yet structurally distinct states in both isolated SL3 constructs and full-length 7SK RNA. We rationally designed constructs that lock SL3 into a single state and demonstrate that both chemical probing and NMR data fit to a linear combination of the two states. Comparison of vertebrate 7SK RNA sequences shows either or both states are highly conserved. These results provide new insights into 7SK RNA structural dynamics and demonstrate the utility of integrating chemical probing with NMR spectroscopy to gain quantitative insights into RNA conformational ensembles.

Dbp1 is a low performance paralog of RNA helicase Ded1 that drives impaired translation and heat stress response

Ded1 and Dbp1 are paralogous conserved RNA helicases that enable translation initiation in yeast. Ded1 has been heavily studied but the role of Dbp1 is poorly understood. We find that the expression of these two helicases is controlled in an inverse and condition-specific manner. In meiosis and other long-term starvation states, Dbp1 expression is upregulated and Ded1 is downregulated, whereas in mitotic cells, Dbp1 expression is extremely low. Inserting the DBP1 ORF in place of the DED1 ORF cannot replace the function of Ded1 in supporting translation, partly due to inefficient mitotic translation of the DBP1 mRNA, dependent on features of its ORF sequence but independent of codon optimality. Global measurements of translation rates and 5' leader translation, activity of mRNA-tethered helicases, ribosome association, and low temperature growth assays show that-even at matched protein levels-Ded1 is more effective than Dbp1 at activating translation, especially for mRNAs with structured 5' leaders. Ded1 supports halting of translation and cell growth in response to heat stress, but Dbp1 lacks this function, as well. These functional differences in the ability to efficiently mediate translation activation and braking can be ascribed to the divergent, disordered N- and C-terminal regions of these two helicases. Altogether, our data show that Dbp1 is a "low performance" version of Ded1 that cells employ in place of Ded1 under long-term conditions of nutrient deficiency.

Late consolidation of rRNA structure during co-transcriptional assembly in E. coli by time-resolved DMS footprinting

The production of new ribosomes requires proper folding of the rRNA and the addition of more than 50 ribosomal proteins. The structures of some assembly intermediates have been determined by cryo-electron microscopy, yet these structures do not provide information on the folding dynamics of the rRNA. To visualize the changes in rRNA structure during ribosome assembly in E. coli cells, transcripts were pulse-labeled with 4-thiouridine and the structure of newly made rRNA probed at various times by dimethyl sulfate modification and mutational profiling sequencing (4U-DMS-MaPseq). The in-cell DMS modification patterns revealed that many long-range rRNA tertiary interactions and protein binding sites through the 16S and 23S rRNA remain partially unfolded 1.5 min after transcription. By contrast, the active sites were continually shielded from DMS modification, suggesting that these critical regions are guarded by cellular factors throughout assembly. Later, bases near the peptidyl tRNA site exhibited specific rearrangements consistent with the binding and release of assembly factors. Time-dependent structure-probing in cells suggests that many tertiary interactions throughout the new ribosomal subunits remain mobile or unfolded until the late stages of subunit maturation.

A compact regulatory RNA element in mouse Hsp70 mRNA

Hsp70 (70 kDa heat shock protein) performs molecular chaperone functions by assisting the folding of newly synthesized and misfolded proteins, thereby counteracting various cell stresses and preventing multiple diseases, including neurodegenerative disorders and cancers. It is well established that, immediately after heat shock, Hsp70 gene expression is mediated by a canonical mechanism of cap-dependent translation. However, the molecular mechanism of Hsp70 expression during heat shock remains elusive. Intriguingly, the 5' end of Hsp70 messenger RNA (mRNA) appears to form a compact structure with the potential to regulate protein expression in a cap-independent manner. Here, we determined the minimal length of the mHsp70 5'-terminal mRNA sequence that is required for RNA folding into a highly compact structure. This span of this RNA element was mapped and the secondary structure characterized by chemical probing, resulting in a secondary structural model that includes multiple stable stems, including one containing the canonical start codon. All of these components, including a short stretch of the 5' open reading frame (ORF), were shown to be vital for RNA folding. This work provides a structural basis for future investigations on the role of translational regulatory structures in the 5' untranslated region and ORF sequences of Hsp70 during heat shock.

RNA Secondary Structure Modeling Following the IPANEMAP Workflow

The structure of RNA molecules and their complexes are crucial for understanding biology at the molecular level. Resolving these structures holds the key to understanding their manifold structure-mediated functions ranging from regulating gene expression to catalyzing biochemical processes. Predicting RNA secondary structure is a prerequisite and a key step to accurately model their three dimensional structure. Although dedicated modelling software are making fast and significant progresses, predicting an accurate secondary structure from the sequence remains a challenge. Their performance can be significantly improved by the incorporation of experimental RNA structure probing data. Many different chemical and enzymatic probes have been developed; however, only one set of quantitative data can be incorporated as constraints for computer-assisted modelling. IPANEMAP is a recent workflow based on RNAfold that can take into account several quantitative or qualitative data sets to model RNA secondary structure. This chapter details the methods for popular chemical probing (DMS, CMCT, SHAPE-CE, and SHAPE-Map) and the subsequent analysis and structure prediction using IPANEMAP.

The myriad roles of RNA structure in the flavivirus life cycle

As positive-sense RNA viruses, the genomes of flaviviruses serve as the template for all stages of the viral life cycle, including translation, replication, and infectious particle production. Yet, they encode just 10 proteins, suggesting that the structure and dynamics of the viral RNA itself helps shepherd the viral genome through these stages. Herein, we highlight advances in our understanding of flavivirus RNA structural elements through the lens of their impact on the viral life cycle. We highlight how RNA structures impact translation, the switch from translation to replication, negative- and positive-strand RNA synthesis, and virion assembly. Consequently, we describe three major themes regarding the roles of RNA structure in flavivirus infections: 1) providing a layer of specificity; 2) increasing the functional capacity; and 3) providing a mechanism to support genome compaction. While the interactions described herein are specific to flaviviruses, these themes appear to extend more broadly across RNA viruses.

Translational efficiency in gas-fermenting bacteria: Adding a new layer of regulation to gene expression in acetogens

Major advances in mastering metabolism of single carbon (C1) gaseous feedstocks in acetogenic microorganisms are primed to fuel the transition toward environmentally sustainable and cost-efficient production schemes of biofuels and value-added biochemicals. Since acetogens grow under autotrophic energy-limited conditions, protein synthesis is expected to be controlled. This survey integrated publicly available RNA sequencing and ribosome profiling studies of several acetogens, providing data on genome-scale transcriptional and translational responses of A. woodii, E. limosum, C. drakei, and C. ljungdahlii to autotrophic and heterotrophic growth conditions. The extent of translational efficiency turned out to vary across key functional modules in acetogens' metabolism. Translational control was confirmed to support stoichiometric protein production in multimeric complexes. Comparing the autotrophic to the heterotrophic growth condition revealed growth-dependent regulation of translational efficiency, pointing at translational buffering as a widespread phenomenon shared by acetogens.

AliNA - a deep learning program for RNA secondary structure prediction

Nowadays there are numerous discovered natural RNA variations participating in different cellular processes and artificial RNA, e. g., aptamers, riboswitches. One of the required tasks in the investigation of their functions and mechanism of influence on cells and interaction with targets is the prediction of RNA secondary structures. The classic thermodynamic-based prediction algorithms do not consider the specificity of biological folding and deep learning methods that were designed to resolve this issue suffer from homology-based methods problems. Herein, we present a method for RNA secondary structure prediction based on deep learning - AliNA (ALIgned Nucleic Acids). Our method successfully predicts secondary structures for non-homologous to train-data RNA families thanks to usage of the data augmentation techniques. Augmentation extends existing datasets with easily-accessible simulated data. The proposed method shows a high quality of prediction across different benchmarks including pseudoknots. The method is available on GitHub for free (https://github.com/Arty40m/AliNA).

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.

Integrated multiplexed assays of variant effect reveal cis-regulatory determinants of catechol-O-methyltransferase gene expression

Multiplexed assays of variant effect are powerful methods to profile the consequences of rare variants on gene expression and organismal fitness. Yet, few studies have integrated several multiplexed assays to map variant effects on gene expression in coding sequences. Here, we pioneered a multiplexed assay based on polysome profiling to measure variant effects on translation at scale, uncovering single-nucleotide variants that increase and decrease ribosome load. By combining high-throughput ribosome load data with multiplexed mRNA and protein abundance readouts, we mapped the cis-regulatory landscape of thousands of catechol-O-methyltransferase (COMT) variants from RNA to protein and found numerous coding variants that alter COMT expression. Finally, we trained machine learning models to map signatures of variant effects on COMT gene expression and uncovered both directional and divergent impacts across expression layers. Our analyses reveal expression phenotypes for thousands of variants in COMT and highlight variant effects on both single and multiple layers of expression. Our findings prompt future studies that integrate several multiplexed assays for the readout of gene expression.

In vivo-like nearest neighbor parameters improve prediction of fractional RNA base-pairing in cells

We conducted a thermodynamic analysis of RNA stability in Eco80 artificial cytoplasm, which mimics in vivo conditions, and compared it to transcriptome-wide probing of mRNA. Eco80 contains 80% of Escherichia coli metabolites, with biological concentrations of metal ions, including 2 mM free Mg2+ and 29 mM metabolite-chelated Mg2+. Fluorescence-detected binding isotherms (FDBI) were used to conduct a thermodynamic analysis of 24 RNA helices and found that these helices, which have an average stability of -12.3 kcal/mol, are less stable by ΔΔGo37 ∼1 kcal/mol. The FDBI data was used to determine a set of Watson-Crick free energy nearest neighbor parameters (NNPs), which revealed that Eco80 reduces the stability of three NNPs. This information was used to adjust the NN model using the RNAstructure package. The in vivo-like adjustments have minimal effects on the prediction of RNA secondary structures determined in vitro and in silico, but markedly improve prediction of fractional RNA base pairing in E. coli, as benchmarked with our in vivo DMS and EDC RNA chemical probing data. In summary, our thermodynamic and chemical probing analyses of RNA helices indicate that RNA secondary structures are less stable in cells than in artificially stable in vitro buffer conditions.

The human mitochondrial mRNA structurome reveals mechanisms of gene expression

The mammalian mitochondrial genome encodes thirteen oxidative phosphorylation system proteins, crucial in aerobic energy transduction. These proteins are translated from 9 monocistronic and 2 bicistronic transcripts, whose native structures remain unexplored, leaving fundamental molecular determinants of mitochondrial gene expression unknown. To address this gap, we developed a mitoDMS-MaPseq approach and used DREEM clustering to resolve the native human mitochondrial mt-mRNA structurome. We gained insights into mt-mRNA biology and translation regulatory mechanisms, including a unique programmed ribosomal frameshifting for the ATP8/ATP6 transcript. Furthermore, absence of the mt-mRNA maintenance factor LRPPRC led to a mitochondrial transcriptome structured differently, with specific mRNA regions exhibiting increased or decreased structuredness. This highlights the role of LRPPRC in maintaining mRNA folding to promote mt-mRNA stabilization and efficient translation. In conclusion, our mt-mRNA folding maps reveal novel mitochondrial gene expression mechanisms, serving as a detailed reference and tool for studying them in different physiological and pathological contexts.

Dissecting telomerase RNA structural heterogeneity in living human cells with DMS-MaPseq

Telomerase is a specialized reverse transcriptase that uses an intrinsic RNA subunit as the template for telomeric DNA synthesis. Biogenesis of human telomerase requires its RNA subunit (hTR) to fold into a multi-domain architecture that includes the template-containing pseudoknot (t/PK) and the three-way junction (CR4/5). These two hTR domains bind the telomerase reverse transcriptase (hTERT) protein and are thus essential for telomerase catalytic activity. Here, we probe the structure of hTR in living cells using dimethyl sulfate mutational profiling with sequencing (DMS-MaPseq) and ensemble deconvolution analysis. Unexpectedly, approximately 15% of the steady state population of hTR has a CR4/5 conformation lacking features required for hTERT binding. Mutagenesis demonstrates that stabilization of the alternative CR4/5 conformation is detrimental to telomerase assembly and activity. We propose that this misfolded portion of the cellular hTR pool is either slowly refolded or degraded. Thus, kinetic traps for RNA folding that have been so well-studied in vitro may also present barriers for assembly of ribonucleoprotein complexes in vivo.

Structure of pre-miR-31 reveals an active role in Dicer-TRBP complex processing

As an essential posttranscriptional regulator of gene expression, microRNA (miRNA) levels must be strictly maintained. The biogenesis of many miRNAs is mediated by trans-acting protein partners through a variety of mechanisms, including remodeling of the RNA structure. miR-31 functions as an oncogene in numerous cancers, and interestingly, its biogenesis is not known to be regulated by protein-binding partners. Therefore, the intrinsic structural properties of the precursor element of miR-31 (pre-miR-31) can provide a mechanism by which its biogenesis is regulated. We determined the solution structure of pre-miR-31 to investigate the role of distinct structural elements in regulating processing by the Dicer-TRBP complex. We found that the presence or absence of mismatches within the helical stem does not strongly influence Dicer-TRBP processing of the pre-miRNAs. However, both the apical loop size and structure at the Dicing site are key elements for discrimination by the Dicer-TRBP complex. Interestingly, our NMR-derived structure reveals the presence of a triplet of base pairs that link the Dicer cleavage site and the apical loop. Mutational analysis in this region suggests that the stability of the junction region strongly influences processing by the Dicer-TRBP complex. Our results enrich our understanding of the active role that RNA structure plays in regulating miRNA biogenesis, which has direct implications for the control of gene expression.

RNA folding studies inside peptide-rich droplets reveal roles of modified nucleosides at the origin of life

Compartmentalization of RNA in biopolymer-rich membraneless organelles is now understood to be pervasive and critical for the function of extant biology and has been proposed as a prebiotically plausible way to accumulate RNA. However, compartment-RNA interactions that drive encapsulation have the potential to influence RNA structure and function in compartment- and RNA sequence-dependent ways. Here, we detail next-generation sequencing (NGS) experiments performed in membraneless compartments called complex coacervates to characterize the fold of many different transfer RNAs (tRNAs) simultaneously under the potentially denaturing conditions of these compartments. Notably, we find that natural modifications favor the native fold of tRNAs in these compartments. This suggests that covalent RNA modifications could have played a critical role in metabolic processes at the origin of life.

Genome-wide probing of eukaryotic nascent RNA structure elucidates cotranscriptional folding and its antimutagenic effect

The transcriptional intermediates of RNAs fold into secondary structures with multiple regulatory roles, yet the details of such cotranscriptional RNA folding are largely unresolved in eukaryotes. Here, we present eSPET-seq (Structural Probing of Elongating Transcripts in eukaryotes), a method to assess the cotranscriptional RNA folding in Saccharomyces cerevisiae. Our study reveals pervasive structural transitions during cotranscriptional folding and overall structural similarities between nascent and mature RNAs. Furthermore, a combined analysis with genome-wide R-loop and mutation rate approximations provides quantitative evidence for the antimutator effect of nascent RNA folding through competitive inhibition of the R-loops, known to facilitate transcription-associated mutagenesis. Taken together, we present an experimental evaluation of cotranscriptional folding in eukaryotes and demonstrate the antimutator effect of nascent RNA folding. These results suggest genome-wide coupling between the processing and transmission of genetic information through RNA folding.

Mutation signature filtering enables high-fidelity RNA structure probing at all four nucleobases with DMS

Chemical probing experiments have transformed RNA structure analysis, enabling high-throughput measurement of base-pairing in living cells. Dimethyl sulfate (DMS) is one of the most widely used structure probing reagents and has played a pivotal role in enabling next-generation single-molecule probing analyses. However, DMS has traditionally only been able to probe adenine and cytosine nucleobases. We previously showed that, using appropriate conditions, DMS can also be used to interrogate base-pairing of uracil and guanines in vitro at reduced accuracy. However, DMS remained unable to informatively probe guanines in cells. Here, we develop an improved DMS mutational profiling (MaP) strategy that leverages the unique mutational signature of N1-methylguanine DMS modifications to enable high-fidelity structure probing at all four nucleotides, including in cells. Using information theory, we show that four-base DMS reactivities convey greater structural information than current two-base DMS and SHAPE probing strategies. Four-base DMS experiments further enable improved direct base-pair detection by single-molecule PAIR analysis, and ultimately support RNA structure modeling at superior accuracy. Four-base DMS probing experiments are straightforward to perform and will broadly facilitate improved RNA structural analysis in living cells.

Transcriptome-wide probing reveals RNA thermometers that regulate translation of glycerol permease genes in Bacillus subtilis

RNA structure regulates bacterial gene expression by several distinct mechanisms via environmental and cellular stimuli, one of which is temperature. While some genome-wide studies have focused on heat shock treatments and the subsequent transcriptomic changes, soil bacteria are less likely to experience such rapid and extreme temperature changes. Though RNA thermometers (RNATs) have been found in 5' untranslated leader regions (5' UTRs) of heat shock and virulence-associated genes, this RNA-controlled mechanism could regulate other genes as well. Using Structure-seq2 and the chemical probe dimethyl sulfate (DMS) at four growth temperatures ranging from 23°C to 42°C, we captured a dynamic response of the Bacillus subtilis transcriptome to temperature. Our transcriptome-wide results show RNA structural changes across all four temperatures and reveal nonmonotonic reactivity trends with increasing temperature. Then, focusing on subregions likely to contain regulatory RNAs, we examined 5' UTRs to identify large, local reactivity changes. This approach led to the discovery of RNATs that control the expression of glpF (glycerol permease) and glpT (glycerol-3-phosphate permease); expression of both genes increased with increased temperature. Results with mutant RNATs indicate that both genes are controlled at the translational level. Increased import of glycerols at high temperatures could provide thermoprotection to proteins.

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.

Characterizing Protonation-Coupled Conformational Ensembles in RNA via pH-Differential Mutational Profiling with DMS Probing

RNA molecules undergo conformational transitions in response to cellular and environmental stimuli. Site-specific protonation, a fundamental chemical property, can alter the conformational landscape of RNA to regulate their functions. However, characterizing protonation-coupled RNA conformational ensembles on a large scale remains challenging. Here, we present pH-differential mutational profiling (PD-MaP) with dimethyl sulfate probing for high-throughput detection of protonation-coupled conformational ensembles in RNA. We demonstrated this approach on microRNA-21 precursor (pre-miR-21) and recapitulated a previously discovered A+-G-coupled conformational ensemble. Additionally, we identified a secondary protonation event involving an A+-C mismatch. We validated the occurrence of both protonation-coupled ensembles in pre-miR-21 using NMR relaxation dispersion spectroscopy. Furthermore, the application of PD-MaP on a library of well-annotated human primary microRNAs uncovered widespread protonation-coupled conformational ensembles, suggesting their potentially broad functions in biology.