RNA Structure Research Articles

Accelerated Simulations Reveal Physicochemical Factors Governing Stability and Composition of RNA Clusters.

Under certain conditions, RNA repeat sequences phase separate, yielding protein-free biomolecular condensates. Importantly, RNA repeat sequences have also been implicated in neurological disorders, such as Huntington's disease. Thus, mapping repeat sequences to their phase behavior, functions, and dysfunctions is an active area of research. However, despite several advances, it remains challenging to characterize the RNA phase behavior at a submolecular resolution. Here, we have implemented a residue-resolution coarse-grained model in LAMMPS─that incorporates both the RNA sequence and structure─to study the clustering propensities of protein-free RNA systems. Importantly, we achieve a multifold speedup in the simulation time compared to previous work. Leveraging this efficiency, we study the clustering propensity of all 20 nonredundant trinucleotide repeat sequences. Our results align with findings from experiments, emphasizing that canonical base-pairing and G-U wobble pairs play dominant roles in regulating cluster formation of RNA repeat sequences. Strikingly, we find strong entropic contributions to the stability and composition of RNA clusters, which is demonstrated for single-component RNA systems as well as binary mixtures of trinucleotide repeats. Additionally, we investigate the clustering behaviors of trinucleotide (odd) repeats and their quadranucleotide (even) counterparts. We observe that odd repeats exhibit stronger clustering tendencies, attributed to the presence of consecutive base pairs in their sequences that are disrupted in even repeat sequences. Altogether, our work extends the set of computational tools for probing RNA cluster formation at submolecular resolution and uncovers physicochemical principles that govern the stability and composition of the resulting clusters.

REDalign: accurate RNA structural alignment using residual encoder-decoder network

BackgroundRNA secondary structural alignment serves as a foundational procedure in identifying conserved structural motifs among RNA sequences, crucially advancing our understanding of novel RNAs via comparative genomic analysis. While various computational strategies for RNA structural alignment exist, they often come with high computational complexity. Specifically, when addressing a set of RNAs with unknown structures, the task of simultaneously predicting their consensus secondary structure and determining the optimal sequence alignment requires an overwhelming computational effort of O(L6)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$O(L^6)$$\\end{document} for each RNA pair. Such an extremely high computational complexity makes these methods impractical for large-scale analysis despite their accurate alignment capabilities.ResultsIn this paper, we introduce REDalign, an innovative approach based on deep learning for RNA secondary structural alignment. By utilizing a residual encoder-decoder network, REDalign can efficiently capture consensus structures and optimize structural alignments. In this learning model, the encoder network leverages a hierarchical pyramid to assimilate high-level structural features. Concurrently, the decoder network, enhanced with residual skip connections, integrates multi-level encoded features to learn detailed feature hierarchies with fewer parameter sets. REDalign significantly reduces computational complexity compared to Sankoff-style algorithms and effectively handles non-nested structures, including pseudoknots, which are challenging for traditional alignment methods. Extensive evaluations demonstrate that REDalign provides superior accuracy and substantial computational efficiency.ConclusionREDalign presents a significant advancement in RNA secondary structural alignment, balancing high alignment accuracy with lower computational demands. Its ability to handle complex RNA structures, including pseudoknots, makes it an effective tool for large-scale RNA analysis, with potential implications for accelerating discoveries in RNA research and comparative genomics.

Alternative substrate kinetics of SARS-CoV-2 Nsp15 endonuclease reveals a specificity landscape dominated by RNA structure.

Coronavirus endoribonuclease Nsp15 contributes to the evasion of host innate immunity by suppressing levels of viral dsRNA. Nsp15 cleaves both ssRNA and dsRNA in vitro with a strong preference for unpaired or bulged U residues, and its activity is stimulated by divalent ions. Here, we systematically quantified effects of RNA sequence and structure context that define its specificity. The results show that sequence preference for U↓A/G, observed previously, contributes only ca. 2-fold to kcat/Km. In contrast, dsRNA structure flanking a bulged U residue increases kcat/Km by an order of magnitude compared to ssRNA while base pairing in dsRNA essentially blocks cleavage. Despite enormous differences in multiple turnover kinetics, the effect of RNA structure on the cleavage step is minimal. Surprisingly, although divalent ion activation of Nsp15 is widely considered to be important for its biological function, the effect on kcat/Km is only ∼2-fold and independent of RNA structure. These results reveal a specificity landscape dominated by RNA structure and provide a quantitative framework for identifying interactions that underlie specificity, determining mechanisms of inhibition and resistance and defining targets important for coronavirus biology.

A New Case of Mitochondrial RNA Helicase SUPV3L1-Associated Neurodegenerative Disease: Ataxia, Spasticity, Optic Atrophy, and Skin Hypopigmentation (ASOASH)

Background: The SUPV3L1 gene encodes ATP-dependent RNA helicase SUPV3L1, which is a part of the mitochondrial degradosome complex or SUV3. SUPV3L1 unwinds secondary structures of mitochondrial RNA (mtRNA) and facilitates the degradation of mtRNA molecules. A nonsense homozygous variant in the SUPV3L1 gene was recently associated with mitochondrial disease. Our study presents the second documented case of SUPV3L1 pathology in humans. Methods: Whole-genome sequencing was performed on the NovaSeq 6000 platform using pair-end reading. Data analysis was performed with an in-house developed pipeline. Results: The 17-year-old female patient exhibited a diverse array of symptoms, including ataxia, spastic paraparesis, cognitive deficit, optic atrophy, and horizontal gaze-evoked nystagmus. Early onset of symptoms, such as ataxic gait and nystagmus, was noted, with subsequent progression of neurological manifestations. At the time of the observation, the proband had extensive regions of hypopigmented skin patches on the body and extremities, which have progressed over time. Whole-genome sequencing revealed compound heterozygous variants in the SUPV3L1 gene: c.272-2A>G and c.1924A>C; p.(Ser642Arg). RNA analysis demonstrated splicing changes attributable to the c.272-2A>G variant. ELISA assay showed increased Complex I content in the patient’s fibroblasts. This case underscores the phenotypic diversity associated with SUPV3L1 mutations, emphasizing the importance of considering mitochondrial RNA helicase dysfunction in the differential diagnosis of neurodegenerative disorders. Further elucidation of the molecular mechanisms underlying SUPV3L1-associated pathology may provide valuable insights into targeted therapeutic interventions.

Viral RNA Interactome: The Ultimate Researcher’s Guide to RNA–Protein Interactions

RNA molecules in the cell are bound by a multitude of RNA-binding proteins (RBPs) with a variety of regulatory consequences. Often, interactions with these RNA-binding proteins are facilitated by the complex secondary and tertiary structures of RNA molecules. Viral RNAs especially are known to be heavily structured and interact with many RBPs, with roles including genome packaging, immune evasion, enhancing replication and transcription, and increasing translation efficiency. As such, the RNA–protein interactome represents a critical facet of the viral replication cycle. Characterization of these interactions is necessary for the development of novel therapeutics targeted at the disruption of essential replication cycle events. In this review, we aim to summarize the various roles of RNA structures in shaping the RNA–protein interactome, the regulatory roles of these interactions, as well as up-to-date methods developed for the characterization of the interactome and directions for novel, RNA-directed therapeutics.

RPS 2.0: an updated database of RNAs involved in liquid-liquid phase separation.

Liquid-liquid phase separation (LLPS) is a crucial process for the formation of biomolecular condensates such as coacervate droplets, P-bodies and stress granules, which play critical roles in many physiological and pathological processes. Increasing studies have shown that not only proteins but also RNAs play a critical role in LLPS. To host LLPS-associated RNAs, we previously developed a database named 'RPS' in 2021. In this study, we present an updated version RPS 2.0 (https://rps.renlab.cn/) to incorporate the newly generated data and to host new LLPS-associated RNAs driven by post-transcriptional regulatory mechanisms. Currently, RPS 2.0 hosts 171 301 entries of LLPS-associated RNAs in 24 different biomolecular condensates with four evidence types, including 'Reviewed', 'High-throughput (LLPS enrichment)', 'High-throughput (LLPS perturbation)' and 'Predicted', and five event types, including 'Expression', 'APA', 'AS', 'A-to-I' and 'Modification'. Additionally, extensive annotations of LLPS-associated RNAs are provided in RPS 2.0, including RNA sequence and structure features, RNA-protein/RNA-RNA interactions, RNA modifications, as well as diseases related annotations. We expect that RPS 2.0 will further promote research of LLPS-associated RNAs and deepen our understanding of the biological functions and regulatory mechanisms of LLPS.

RNA fold prediction by Monte Carlo in graph space and the statistical mechanics of tertiary interactions.

Using a graph representation of RNA structures, we have studied the ensembles of secondary and tertiary graphs two sets of RNA with Monte Carlo simulations. The first consisted of 91 target ribozyme and riboswitch sequences of moderate lengths (< 150 nt) having a variety of secondary, H-type pseudoknots and kissing loop interactions. The second set consisted of 71 more diverse sequences across many RNA families. Using a simple empirical energy model for tertiary interactions and only sequence information for each target as input, the simulations examined how tertiary interactions impact the statistical mechanics of the fold ensembles. The results show that the graphs proliferate enormously when tertiary interactions are possible, producing an entropic driving force for the ensemble to access folds having tertiary structures even though they are overall energetically unfavorable in the energy model. For each of the targets in the two test sets, we assessed the quality of the model and the simulations by examining how well the simulated structures were able to predict the native fold and compared the results to fold predictions from ViennaRNA. Our model generated good or excellent predictions in a large majority of the targets. Overall, this method was able to produce predictions of comparable quality to Vienna, but it outperformed Vienna for structures with H-type pseudoknots. The results suggest that while tertiary interactions are predicated on real-space contacts, their impacts on the folded structure of RNA can be captured by graph space information for sequences of moderate lengths, using a simple tertiary energy model for the loops, the base pairs and base stacks.

Translation of HIV-1 unspliced RNA is regulated by 5' untranslated region structure.

HIV-1 must generate infectious virions to spread to new hosts and HIV-1 unspliced RNA (HIV-1 RNA) plays two central roles in this process. HIV-1 RNA serves as an mRNA that is translated to generate proteins essential for particle production and replication, and it is packaged into particles as the viral genome. HIV-1 uses several transcription start sites to generate multiple RNAs that differ by a few nucleotides at the 5' end, including those with one (1G) or three (3G) 5' guanosines. The virus relies on host machinery to translate its RNAs in a cap-dependent manner. Here, we demonstrate that the 5' context of HIV-1 RNA affects the efficiency of translation both in vitro and in cells. Although both RNAs are competent for translation, 3G RNA is translated more efficiently than 1G RNA. The 5' untranslated region (UTR) of 1G and 3G RNAs has previously been shown to fold into distinct structural ensembles. We show that HIV-1 mutants in which the 5' UTR of 1G and 3G RNAs fold into similar structures were translated at similar efficiencies. Thus, the host machinery translates two 99.9% identical HIV-1 RNAs with different efficiencies, and the translation efficiency is regulated by the 5' UTR structure.IMPORTANCEHIV-1 unspliced RNA contains all the viral genetic information and encodes virion structural proteins and enzymes. Thus, the unspliced RNA serves distinct roles as viral genome and translation template, both critical for viral replication. HIV-1 generates two major unspliced RNAs with a 2-nt difference at the 5' end (3G RNA and 1G RNA). The 1G transcript is known to be preferentially packaged over the 3G transcript. Here, we showed that 3G RNA is favorably translated over 1G RNA based on its 5' untranslated region (UTR) RNA structure. In HIV-1 mutants in which the two major transcripts have similar 5' UTR structures, 1G and 3G RNAs are translated similarly. Therefore, HIV-1 generates two 9-kb RNAs with a 2-nt difference, each serving a distinct role dictated by differential 5' UTR structures.

Template switching enables chemical probing of native RNA structures.

RNAs are often studied in non-native sequence contexts to facilitate structural studies. However, seemingly innocuous changes to an RNA sequence may perturb the native structure and generate inaccurate or ambiguous structural models. To facilitate the investigation of native RNA secondary structure by selective 2' hydroxyl acylation analyzed by primer extension (SHAPE), we engineered an approach that couples minimal enzymatic steps to RNA chemical probing and mutational profiling (MaP) reverse transcription (RT) methods - a process we call template switching and mutational profiling (Switch-MaP). In Switch-MaP, RT templates and additional library sequences are added post-probing through ligation and template switching, capturing reactivities for every nucleotide. For a candidate SAM-I riboswitch, we compared RNA structure models generated by the Switch-MaP approach to those of traditional primer-based MaP, including RNAs with or without appended structure cassettes. Primer-based MaP masked reactivity data in the 5' and 3' ends of the RNA, producing ambiguous ensembles inconsistent with the conserved SAM-I riboswitch secondary structure. Structure cassettes enabled unambiguous modeling of an aptamer-only construct but introduced non-native interactions in the full length riboswitch. In contrast, Switch-MaP provided reactivity data for all nucleotides in each RNA and enabled unambiguous modeling of secondary structure, consistent with the conserved SAM-I fold. Switch-MaP is a straightforward alternative approach to primer-based and cassette-based chemical probing methods that precludes primer masking and the formation of alternative secondary structures due to non-native sequence elements.

DDX RNA helicases: key players in cellular homeostasis and innate antiviral immunity.

RNA helicases are integral in RNA metabolism, performing important roles in cellular homeostasis and stress responses. In particular, the DExD/H-box (DDX) helicase family possesses a conserved catalytic core that binds structural features rather than specific sequences in RNA targets. DDXs have critical roles in all aspects of RNA metabolism including ribosome biogenesis, translation, RNA export, and RNA stability. Importantly, functional specialization within this family arises from divergent N and C termini and is driven at least in part by gene duplications with 18 of the 42 human helicases having paralogs. In addition to their key roles in the homeostatic control of cellular RNA, these factors have critical roles in RNA virus infection. The canonical RIG-I-like receptors (RLRs) play pivotal roles in cytoplasmic sensing of viral RNA structures, inducing antiviral gene expression. Additional RNA helicases function as viral sensors or regulators, further diversifying the innate immune defense arsenal. Moreover, some of these helicases have been coopted by viruses to facilitate their replication. Altogether, DDX helicases exhibit functional specificity, playing intricate roles in RNA metabolism and host defense. This review will discuss the mechanisms by which these RNA helicases recognize diverse RNA structures in cellular and viral RNAs, and how this impacts RNA processing and innate immune responses.

Sequential structure probing of cotranscriptional RNA folding intermediates.

Cotranscriptional RNA folding pathways typically involve the sequential formation of folding intermediates. Existing methods for cotranscriptional RNA structure probing map the structure of nascent RNA in the context of a terminally arrested transcription elongation complex. Consequently, the rearrangement of RNA structures as nucleotides are added to the transcript can be inferred but is not assessed directly. To address this limitation, we have developed linked- m ultipoint T ranscription E longation C omplex RNA structure prob ing (TECprobe-LM), which assesses the cotranscriptional rearrangement of RNA structures by sequentially positioning E. coli RNAP at two or more points within a DNA template so that nascent RNA can be chemically probed. We validated TECprobe-LM by measuring known folding events that occur within the E. coli signal recognition particle RNA, Clostridium beijerinckii pfl ZTP riboswitch, and Bacillus cereus crcB fluoride riboswitch folding pathways. Our findings establish TECprobe-LM as a strategy for detecting cotranscriptional RNA folding events directly using chemical probing.

Platinum(II)-Salphen Complexes as DNA Binders and Photosensitisers.

Current anticancer therapies suffer from issues such as off-target side effects and the emergence of drug resistance; therefore, the discovery of alternative therapeutic approaches is vital. These can include the development of drugs with different modes of action, and the exploration of new biomolecular targets. For the former, there has been increasing interest in drugs that are activated by an external stimulus (e. g. light irradiation) to generate cytotoxic chemicals such as reactive oxygen species (ROS). For the latter, significant efforts are being directed to explore non-canonical DNA and RNA structures (e. g. guanine-quadruplexes), as alternative biomolecular targets. Herein we report the synthesis of a library of 21 new platinum(II)-Salphen complexes (square planar platinum(II) complexes coordinated to tetradentate O,N,N,O-Schiff base ligands), and the investigation, for all complexes, of their photophysical and photochemical properties, their interactions with duplex and quadruplex DNA, and their cytotoxicity against HeLa cancer cells both in the dark and upon light irradiation. Thanks to the intrinsic phosphorescence of the platinum(II) complexes, confocal microscopy was used for six of the complexes to determine their cellular permeability and localisation in two cancer cell lines (HeLa and U2OS). Altogether, these studies have allowed us to identify two lead platinum(II) complexes with high guanine-quadruplex DNA affinity and selectivity, good cell permeability and nuclear localisation, and high cytotoxicity against HeLa cancer cells upon irradiation with no detected cytotoxicity in the dark.

OpenASO: RNA Rescue - designing splice-modulating antisense oligonucleotides through community science.

Splice-modulating antisense oligonucleotides (ASOs) are precision RNA-based drugs that are becoming an established modality to treat human disease. Previously, we reported the discovery of ASOs that target a novel, putative intronic RNA structure to rescue splicing of multiple pathogenic variants of F8 exon 16 that cause hemophilia A. However, the conventional approach to discovering splice-modulating ASOs is both laborious and expensive. Here, we describe an alternative paradigm that integrates data-driven RNA structure prediction and community science to discover splice-modulating ASOs. Using a splicing-deficient pathogenic variant of F8 exon 16 as a model, we show that 25% of the top-scoring molecules designed in the Eterna OpenASO challenge have a statistically significant impact on enhancing exon 16 splicing. Additionally, we show that a distinct combination of ASOs designed by Eterna players can additively enhance the inclusion of the splicing-deficient exon 16 variant. Together, our data suggests that crowdsourcing designs from a community of citizen scientists may accelerate the discovery of splice-modulating ASOs with potential to treat human disease.

Pan-flavivirus analysis reveals sfRNA-independent, 3' UTR-biased siRNA production from an insect-specific flavivirus.

RNA interference (RNAi) plays an essential role in mosquito antiviral immunity, but it is not known whether viral small interfering RNA (siRNA) profiles differ between mosquito-borne and mosquito-specific viruses. A pan-Orthoflavivirus analysis in Aedes albopictus cells revealed that viral siRNAs were evenly distributed across the viral genome of most representatives of the Flavivirus genus. In contrast, siRNA production was biased toward the 3' untranslated region (UTR) of the genomes of classical insect-specific flaviviruses (cISF), which was most pronounced for Kamiti River virus (KRV), a virus with a unique, 1.2 kb long 3' UTR. KRV-derived siRNAs were produced in high quantities and almost exclusively mapped to the 3' UTR. We mapped the 5' end of KRV subgenomic flavivirus RNAs (sfRNAs), products of the 5'-3' exoribonuclease XRN1/Pacman stalling on secondary RNA structures in the 3' UTR of the viral genome. We found that KRV produces high copy numbers of a long, 1,017 nt sfRNA1 and a short, 421 nt sfRNA2, corresponding to two predicted XRN1-resistant elements. Expression of both sfRNA1 and sfRNA2 was reduced in Pacman-deficient Aedes albopictus cells; however, this did not correlate with a shift in viral siRNA profiles. We suggest that cISFs, particularly KRV, developed a unique mechanism to produce high amounts of siRNAs as a decoy for the antiviral RNAi response in an sfRNA-independent manner.IMPORTANCEThe Flavivirus genus contains diverse mosquito viruses ranging from insect-specific viruses circulating exclusively in mosquito populations to mosquito-borne viruses that cause disease in humans and animals. Studying the mechanisms of virus replication and antiviral immunity in mosquitoes is important to understand arbovirus transmission and may inform the development of disease control strategies. In insects, RNA interference (RNAi) provides broad antiviral activity and constitutes a major immune response against viruses. Comparing diverse members of the Flavivirus genus, we found that all flaviviruses are targeted by RNAi. However, the insect-specific Kamiti River virus was unique in that small interfering RNAs are highly skewed toward its uniquely long 3' untranslated region. These results suggest that mosquito-specific viruses have evolved unique mechanisms for genome replication and immune evasion.

RNA architecture of porcine deltacoronavirus genome inside virions detected by vRIC-seq

Porcine deltacoronavirus (PDCoV) is a newly emerging and special delta coronavirus, which infect mammals such as pigs, cattle and humans, as well as chickens and birds. Exploring RNA structures in the viral genome benefits the understanding of the role of RNA in the lifecycle of viruses. In this study, vRIC-seq is employed to analyze the RNA-RNA interaction in the whole genome structure of PDCoV in virions. About 12.87 and 13.52 million paired reads are obtained in two biological replicates, respectively, with 17.9% and 14.8% of them are identified as valid chimeric reads. These are employed to predict the RNA secondary structure, which is compact and highly structured. A twisted-cyclized conformation is observed in the RNA-RNA interaction map of PDCoV for the first time. 77 multi-way junctions are evenly distributed in the PDCoV genome. Our work provides fundamental structural insights that are essential for understanding the genomic structure and function, genetic evolution, and packaging characteristics of PDCoV.

Functional screen for mediators of onco-mRNA translation specificity.

Oncogenic protein dosage is tightly regulated to enable cancer cells to adapt and survive. Whether this is regulated at the level of translational control and the key factors in cis and trans remain unknown. The Myc oncogene is a central paradigm of an exquisitely regulated oncogene and a major driver of pancreatic ductal adenocarcinoma (PDAC). Using a functional genome-wide CRISPRi screen in PDAC cells, we identified activators of selective MYC translation through its 5' untranslated region (5'UTR) and validated four RNA binding proteins (RBPs), including epitranscriptome modifiers. Among these RBPs, our top hit was RBM42, which is highly expressed in PDAC and predicts poor survival. Combining polysome sequencing and CLIP-seq analyses, we find that RBM42 binds and selectively regulates the translation of MYC and a precise, yet vital suite of pro-oncogenic transcripts, including JUN and EGFR . Mechanistically, employing IP-mass spectrometry analysis, we find that RMB42 is a novel ribosome-associated protein (RAP). Using DMS-Seq and mutagenesis analysis, we show that RBM42 directly binds and remodels the MYC 5'UTR RNA structure, facilitating the formation of the translation pre-initiation complex. Importantly, RBM42 is necessary for human PDAC cell growth and fitness and PDAC tumorigenesis in xenograft mouse models in a Myc-dependent manner in vivo . In PDAC patient samples, RBM42 expression is correlated with Myc protein levels and transcriptional activity. This work transforms our understanding of the translational code in cancer and offers a new therapeutic opening to target the expression of oncogenes.

Ribosomal frameshifting selectively modulates the assembly, function, and pharmacological rescue of a misfolded CFTR variant

The cotranslational misfolding of the cystic fibrosis transmembrane conductance regulator chloride channel (CFTR) plays a central role in the molecular basis of CF. The misfolding of the most common CF variant (ΔF508) remodels both the translational regulation and quality control of CFTR. Nevertheless, it is unclear how the misassembly of the nascent polypeptide may directly influence the activity of the translation machinery. In this work, we identify a structural motif within the CFTR transcript that stimulates efficient -1 ribosomal frameshifting and triggers the premature termination of translation. Though this motif does not appear to impact the interactome of wild-type CFTR, silent mutations that disrupt this RNA structure alter the association of nascent ΔF508 CFTR with numerous translation and quality control proteins. Moreover, disrupting this RNA structure enhances the functional gating of the ΔF508 CFTR channel at the plasma membrane and its pharmacological rescue by the CFTR modulators contained in the CF drug Trikafta. The effects of the RNA structure on ΔF508 CFTR appear to be attenuated in the absence of the ER membrane protein complex, which was previously found to modulate ribosome collisions during "preemptive quality control" of a misfolded CFTR homolog. Together, our results reveal that ribosomal frameshifting selectively modulates the assembly, function, and pharmacological rescue of a misfolded CFTR variant. These findings suggest that interactions between the nascent chain, quality control machinery, and ribosome may dynamically modulate ribosomal frameshifting in order to tune the processivity of translation in response to cotranslational misfolding.

Genome-Wide Identification of Stable RNA Secondary Structures Across Multiple Organisms Using Chemical Probing Data: Insights into Short Structural Motifs and RNA-Targeting Therapeutics.

Small molecules targeting specific RNA binding sites, including stable and transient RNA structures, are emerging as effective pharmacological approaches for modulating gene expression. However, little is understood about how stable RNA secondary structures are shared across organisms, an important factor in controlling drug selectivity. In this study, I provide an analytical pipeline named RNA Secondary Structure Finder (R2S-Finder) to discover short, stable RNA structural motifs for humans, Escherichia coli ( E. coli ), SARS-CoV-2, and Zika virus by leveraging existing in vivo and in vitro genome-wide chemical RNA-probing datasets. I found several common features across organisms. For example, apart from the well-documented tetraloops, AU-rich tetraloops are widely present in different organisms. I also found that the 5' untranslated region (UTR) contains a higher proportion of stable structures than the coding sequences in humans, SARS-CoV-2, and Zika virus. In general, stable structures predicted from in vitro (protein-free) and in vivo datasets are consistent in humans, E. coli , and SARS-CoV-2, indicating that most stable structure formation were driven by RNA folding alone, while a larger variation was found between in vitro and in vivo data with certain RNA types, such as human long intergenic non-coding RNAs (lincRNAs). Finally, I predicted stable three- and four-way RNA junctions that exist both in vivo and in vitro conditions, which can potentially serve as drug targets. All results of stable sequences, stem-loops, internal loops, bulges, and three- and four-way junctions have been collated in the R2S-Finder database ( https://github.com/JingxinWangLab/R2S-Finder ), which is coded in hyperlinked HTML pages and tabulated in CSV files.

G-quadruplex DNA and RNA in cellular senescence.

Normal cells divide, are damaged, and are repaired across their lifetime. As cells age, they enter cellular senescence, characterized by a permanent state of cell-cycle arrest triggered by various stressors. The molecular mechanisms that regulate senescent phenotypes have been actively investigated over the last several decades; however, one area that has been neglected is how G-quadruplex (G4) DNA and RNA (G4-DNA and G4-RNA) mediate senescence. These non-canonical four-stranded DNA and RNA structures regulate most normative DNA and RNA-dependent processes, such as transcription, replication, and translation, as well as pathogenic mechanisms, including genomic instability and abnormal stress granule function. This review also highlights the contribution of G4s to sex differences in age-associated diseases and emphasizes potential translational approaches to target senescence and anti-aging mechanisms through G4 manipulation.

RNAtango: Analysing and comparing RNA 3D structures via torsional angles.

RNA molecules, essential for viruses and living organisms, derive their pivotal functions from intricate 3D structures. To understand these structures, one can analyze torsion and pseudo-torsion angles, which describe rotations around bonds, whether real or virtual, thus capturing the RNA conformational flexibility. Such an analysis has been made possible by RNAtango, a web server introduced in this paper, that provides a trigonometric perspective on RNA 3D structures, giving insights into the variability of examined models and their alignment with reference targets. RNAtango offers comprehensive tools for calculating torsion and pseudo-torsion angles, generating angle statistics, comparing RNA structures based on backbone torsions, and assessing local and global structural similarities using trigonometric functions and angle measures. The system operates in three scenarios: single model analysis, model-versus-target comparison, and model-versus-model comparison, with results output in text and graphical formats. Compatible with all modern web browsers, RNAtango is accessible freely along with the source code. It supports researchers in accurately assessing structural similarities, which contributes to the precision and efficiency of RNA modeling.