RNA2DMut: a web tool for the design and analysis of RNA structure mutations

Frontiers and Challenges of Computing ncRNAs Biogenesis, Function and Modulation

Non-coding RNAs (ncRNAs), generated from nonprotein coding DNA sequences, constitute 98-99% of the human genome. Non-coding RNAs encompass diverse functional classes, including microRNAs, small interfering RNAs, PIWI-interacting RNAs, small nuclear RNAs, small nucleolar RNAs, and long non-coding RNAs. With critical involvement in gene expression and regulation across various biological and physiopathological contexts, such as neuronal disorders, immune responses, cardiovascular diseases, and cancer, non-coding RNAs are emerging as disease biomarkers and therapeutic targets. In this review, after providing an overview of non-coding RNAs' role in cell homeostasis, we illustrate the potential and the challenges of state-of-the-art computational methods exploited to study non-coding RNAs biogenesis, function, and modulation. This can be done by directly targeting them with small molecules or by altering their expression by targeting the cellular engines underlying their biosynthesis. Drawing from applications, also taken from our work, we showcase the significance and role of computer simulations in uncovering fundamental facets of ncRNA mechanisms and modulation. This information may set the basis to advance gene modulation tools and therapeutic strategies to address unmet medical needs.

Splicing factor TRA2A contributes to esophageal cancer progression via a noncanonical role in lncRNA m6 A methylation

Transformer 2 alpha homolog (TRA2A), a member of the serine/arginine-rich splicing factor family, has been shown to control mRNA splicing in development and cancers. However, it remains unclear whether TRA2A is involved in lncRNA regulation. In the present study, we found that TRA2A was upregulated and correlated with poor prognosis in esophageal cancer. Downregulation of TRA2A suppressed the tumor growth in xenograft nude mice. Epitranscriptomic microarray showed that depletion of TRA2A affected global lncRNA methylation similarly to the key m⁶ A methyltransferase, METTL3, by silencing. MeRIP-qPCR, RNA pull-down, CLIP analyses, and stability assays indicated that ablation of TRA2A reduced m⁶ A-modification of the oncogenic lncRNA MALAT1, thus inducing structural alterations and reduced stability. Furthermore, Co-IP experiments showed TRA2A directly interacted with METTL3 and RBMX, which also affected the writer KIAA1429 expression. Knockdown of TRA2A inhibited cell proliferation in a manner restored by RBMX/KIAA1429 overexpression. Clinically, MALAT1, RBMX, and KIAA1429 were prognostic factors of worse survival in ESCA patients. Structural similarity-based virtual screening in FDA-approved drugs repurposed nebivolol, a β₁ -adrenergic receptor antagonist, as a potent compound to suppress the proliferation of esophageal cancer cells. Cellular thermal shift and RIP assay indicated that nebivolol may compete with MALAT1 to bind TRA2A. In conclusion, our study revealed the noncanonical function of TRA2A, which coordinates with multiple methylation proteins to promote oncogenic MALAT1 during ESCA carcinogenesis.

Analyses of human cancer driver genes uncovers evolutionarily conserved RNA structural elements involved in posttranscriptional control

Experimental breakthroughs have provided unprecedented insights into the genes involved in cancer. The identification of such cancer driver genes is a major step in gaining a fuller understanding of oncogenesis and provides novel lists of potential therapeutic targets. A key area that requires additional study is the posttranscriptional control mechanisms at work in cancer driver genes. This is important not only for basic insights into the biology of cancer, but also to advance new therapeutic modalities that target RNA—an emerging field with great promise toward the treatment of various cancers. In the current study we performed an in silico analysis on the transcripts associated with 800 cancer driver genes (10,390 unique transcripts) that identified 179,190 secondary structural motifs with evidence of evolutionarily ordered structures with unusual thermodynamic stability. Narrowing to one transcript per gene, 35,426 predicted structures were subjected to phylogenetic comparisons of sequence and structural conservation. This identified 7,001 RNA secondary structures embedded in transcripts with evidence of covariation between paired sites, supporting structure models and suggesting functional significance. A select set of seven structures were tested in vitro for their ability to regulate gene expression; all were found to have significant effects. These results indicate potentially widespread roles for RNA structure in posttranscriptional control of human cancer driver genes.

From traditional pharmacological towards nucleic acid-based therapies for cardiovascular diseases

Nucleic acid-based therapeutics are currently developed at large scale for prevention and management of cardiovascular diseases (CVDs), since: (i) genetic studies have highlighted novel therapeutic targets suggested to be causal for CVD; (ii) there is a substantial recent progress in delivery, efficacy, and safety of nucleic acid-based therapies; (iii) they enable effective modulation of therapeutic targets that cannot be sufficiently or optimally addressed using traditional small molecule drugs or antibodies. Nucleic acid-based therapeutics include (i) RNA-targeted therapeutics for gene silencing; (ii) microRNA-modulating and epigenetic therapies; (iii) gene therapies; and (iv) genome-editing approaches (e.g. CRISPR-Cas-based): (i) RNA-targeted therapeutics: several large-scale clinical development programmes, using antisense oligonucleotides (ASO) or short interfering RNA (siRNA) therapeutics for prevention and management of CVD have been initiated. These include ASO and/or siRNA molecules to lower apolipoprotein (a) [apo(a)], proprotein convertase subtilisin/kexin type 9 (PCSK9), apoCIII, ANGPTL3, or transthyretin (TTR) for prevention and treatment of patients with atherosclerotic CVD or TTR amyloidosis. (ii) MicroRNA-modulating and epigenetic therapies: novel potential therapeutic targets are continually arising from human non-coding genome and epigenetic research. First microRNA-based therapeutics or therapies targeting epigenetic regulatory pathways are in clinical studies. (iii) Gene therapies: EMA/FDA have approved gene therapies for non-cardiac monogenic diseases and LDL receptor gene therapy is currently being examined in patients with homozygous hypercholesterolaemia. In experimental studies, gene therapy has significantly improved cardiac function in heart failure animal models. (iv) Genome editing approaches: these technologies, such as using CRISPR-Cas, have proven powerful in stem cells, however, important challenges are remaining, e.g. low rates of homology-directed repair in somatic cells such as cardiomyocytes. In summary, RNA-targeted therapies (e.g. apo(a)-ASO and PCSK9-siRNA) are now in large-scale clinical outcome trials and will most likely become a novel effective and safe therapeutic option for CVD in the near future. MicroRNA-modulating, epigenetic, and gene therapies are tested in early clinical studies for CVD. CRISPR-Cas-mediated genome editing is highly effective in stem cells, but major challenges are remaining in somatic cells, however, this field is rapidly advancing.

Optimized photochemistry enables efficient analysis of dynamic RNA structuromes and interactomes in genetic and infectious diseases

Direct determination of RNA structures and interactions in living cells is critical for understanding their functions in normal physiology and disease states. Here, we present PARIS2, a dramatically improved method for RNA duplex determination in vivo with >4000-fold higher efficiency than previous methods. PARIS2 captures ribosome binding sites on mRNAs, reporting translation status on a transcriptome scale. Applying PARIS2 to the U8 snoRNA mutated in the neurological disorder LCC, we discover a network of dynamic RNA structures and interactions which are destabilized by patient mutations. We report the first whole genome structure of enterovirus D68, an RNA virus that causes polio-like symptoms, revealing highly dynamic conformations altered by antiviral drugs and different pathogenic strains. We also discover a replication-associated asymmetry on the (+) and (-) strands of the viral genome. This study establishes a powerful technology for efficient interrogation of the RNA structurome and interactome in human diseases.

The integrity of the U12 snRNA 3' stem-loop is necessary for its overall stability

Disruption of minor spliceosome functions underlies several genetic diseases with mutations in the minor spliceosome-specific small nuclear RNAs (snRNAs) and proteins. Here, we define the molecular outcome of the U12 snRNA mutation (84C>U) resulting in an early-onset form of cerebellar ataxia. To understand the molecular consequences of the U12 snRNA mutation, we created cell lines harboring the 84C>T mutation in the U12 snRNA gene (RNU12). We show that the 84C>U mutation leads to accelerated decay of the snRNA, resulting in significantly reduced steady-state U12 snRNA levels. Additionally, the mutation leads to accumulation of 3′-truncated forms of U12 snRNA, which have undergone the cytoplasmic steps of snRNP biogenesis. Our data suggests that the 84C>U-mutant snRNA is targeted for decay following reimport into the nucleus, and that the U12 snRNA fragments are decay intermediates that result from the stalling of a 3′-to-5′ exonuclease. Finally, we show that several other single-nucleotide variants in the 3′ stem-loop of U12 snRNA that are segregating in the human population are also highly destabilizing. This suggests that the 3′ stem-loop is important for the overall stability of the U12 snRNA and that additional disease-causing mutations are likely to exist in this region.

A survey of RNA secondary structural propensity encoded within human herpesvirus genomes: global comparisons and local motifs

There are nine herpesviruses known to infect humans, of which Epstein-Barr virus (EBV) is the most widely distributed (>90% of adults infected). This ubiquitous virus is implicated in a variety of cancers and autoimmune diseases. Previous analyses of the EBV genome revealed numerous regions with evidence of generating unusually stable and conserved RNA secondary structures and led to the discovery of a novel class of EBV non-coding (nc)RNAs: the stable intronic sequence (sis)RNAs. To gain a better understanding of the roles of RNA structure in EBV biology and pathogenicity, we revisit EBV using recently developed tools for genome-wide motif discovery and RNA structural characterization. This corroborated previous results and revealed novel motifs with potential functionality; one of which has been experimentally validated. Additionally, since many herpesviruses increasingly rival the seroprevalence of EBV (VZV, HHV-6 and HHV-7 being the most notable), analyses were expanded to include all sequenced human Herpesvirus RefSeq genomes, allowing for genomic comparisons. In total 10 genomes were analyzed, for EBV (types 1 and 2), HCMV, HHV-6A, HHV-6B, HHV-7, HSV-1, HSV-2, KSHV, and VZV. All resulting data were archived in the RNAStructuromeDB (https://structurome.bb.iastate.edu/herpesvirus) to make them available to a wide array of researchers.

Mapping the RNA structural landscape of viral genomes

Functional RNA structures are prevalent in viral genomes, and have been shown to play roles in almost every aspect of their biology. However, the majority of viral RNA remains structurally uncharacterized. This is likely to remain true as the cost of sequencing decreases much faster than the cost of structural characterizations. Because of this, there is a need for rapid, inexpensive methods to highlight regions of viral RNA which are ideal candidates for structure-function analyses. The ScanFold method was developed as a single sequence alternative to traditional RNA structural motif discovery pipelines, which rely heavily on well curated sequence alignments to identify conserved RNA structures. ScanFold focuses on identifying (based on their more stable than expected folding energies) the most likely functional structures encoded within a single large RNA sequence, while allowing predicted motifs to be tested for evidence of structural conservation later. Decoupling these processes can be a benefit to researchers studying viruses lacking the ideal phylogenetic depth to yield evidence of structural conservation. Here, we demonstrate how the most significant ScanFold predicted structures correspond to higher base pairing probabilities, SHAPE reactivities, and predict known functional structures within the ZIKV and HIV-1 genomes with accuracy. Best practices and examples are also shown to aid users in utilizing ScanFold for their own systems of interest. ScanFold is available as a Webserver (https://mosslabtools.bb.iastate.edu/scanfold) or can be downloaded (https://github.com/moss-lab/ScanFold) and run locally.

The RNA encoding the microtubule-associated protein tau has extensive structure that affects its biology

Tauopathies are neurodegenerative diseases that affect millions of people worldwide including those with Alzheimer’s disease. While many efforts have focused on understanding the role of tau protein in neurodegeneration, there has been little done to systematically analyze and study the structures within tau’s encoding RNA and their connection to disease pathology. Knowledge of RNA structure can provide insights into disease mechanisms and how to affect protein production for therapeutic benefit. Using computational methods based on thermodynamic stability and evolutionary conservation, we identified structures throughout the tau pre-mRNA, especially at exon-intron junctions and within the 5′ and 3′ untranslated regions (UTRs). In particular, structures were identified at twenty exon-intron junctions. The 5′ UTR contains one structured region, which lies within a known internal ribosome entry site. The 3′ UTR contains eight structured regions, including one that contains a polyadenylation signal. A series of functional experiments were carried out to assess the effects of mutations associated with mis-regulation of alternative splicing of exon 10 and to identify regions of the 3′ UTR that contain cis-regulatory elements. These studies defined novel structural regions within the mRNA that affect stability and pre-mRNA splicing and may lead to new therapeutic targets for treating tau-associated diseases.

Computational approaches for the discovery of splicing regulatory RNA structures

Global RNA structure and local functional motifs mediate interactions important in determining the rates and patterns of mRNA splicing. In this review, we overview approaches for the computational prediction of RNA secondary structure with a special emphasis on the discovery of motifs important to RNA splicing. The process of identifying and modeling potential splicing regulatory structures is illustrated using a recently-developed approach for RNA structural motif discovery, the ScanFold pipeline, which is applied to the identification of a known splicing regulatory structure in influenza virus.

ScanFold: an approach for genome-wide discovery of local RNA structural elements-applications to Zika virus and HIV

In addition to encoding RNA primary structures, genomes also encode RNA secondary and tertiary structures that play roles in gene regulation and, in the case of RNA viruses, genome replication. Methods for the identification of functional RNA structures in genomes typically rely on scanning analysis windows, where multiple partially-overlapping windows are used to predict RNA structures and folding metrics to deduce regions likely to form functional structure. Separate structural models are produced for each window, where the step size can greatly affect the returned model. This makes deducing unique local structures challenging, as the same nucleotides in each window can be alternatively base paired. We are presenting here a new approach where all base pairs from analysis windows are considered and weighted by favorable folding. This results in unique base pairing throughout the genome and the generation of local regions/structures that can be ranked by their propensity to form unusually thermodynamically stable folds. We applied this approach to the Zika virus (ZIKV) and HIV-1 genomes. ZIKV is linked to a variety of neurological ailments including microcephaly and Guillain-Barré syndrome and its (+)-sense RNA genome encodes two, previously described, functionally essential structured RNA regions. HIV, the cause of AIDS, contains multiple functional RNA motifs in its genome, which have been extensively studied. Our approach is able to successfully identify and model the structures of known functional motifs in both viruses, while also finding additional regions likely to form functional structures. All data have been archived at the RNAStructuromeDB (www.structurome.bb.iastate.edu), a repository of RNA folding data for humans and their pathogens.

The ensemble diversity of non-coding RNA structure is lower than random sequence

In addition to energetically optimal structures, RNAs can fold into near energy suboptimal conformations that may be populated and play functional roles. The diversity of this structural ensemble can be estimated using a metric derived from the calculated RNA partition function: the ensemble diversity. In this report, 10 classes of functional RNAs were analyzed: the 5.8S and 5S rRNAs, ribozyme, RNase P, snoRNA, snRNA, SRP RNA, tmRNA, Vault RNA and Y RNA. Representative sequences from each class were mutagenized in two ways: firstly, all possible point mutations were generated and secondly, wild type sequences were randomized to generate multiple scrambled mutants. Compared to the mutants, the native RNA ensemble diversity was predicted to be lower. This finding held true when all available sequences (378,455 sequences) for each RNA class (archived in the RNAcentral database) were analyzed. This suggests that a compact structural ensemble is an evolved characteristic of functional RNAs.