Intrinsic Regulatory Role of RNA Structural Arrangement in Alternative Splicing Control

RNA structure in alternative splicing regulation: from mechanism to therapy

Alternative splicing is a highly intricate process that plays a crucial role in post-transcriptional regulation and significantly expands the functional proteome of a limited number of coding genes in eukaryotes. Its regulation is multifactorial, with RNA structure exerting a significant impact. Aberrant RNA conformations lead to dysregulation of splicing patterns, which directly affects the manifestation of disease symptoms. In this review, the molecular mechanisms of RNA secondary structure-mediated splicing regulation are summarized, with a focus on the complex interplay between aberrant RNA conformations and disease phenotypes resulted from splicing defects. This study also explores additional factors that reshape structural conformations, enriching our understanding of the mechanistic network underlying structure-mediated splicing regulation. In addition, an emphasis has been placed on the clinical role of targeting aberrant splicing corrections in human diseases. The principal mechanisms of action behind this phenomenon are described, followed by a discussion of prospective development strategies and pertinent challenges.

RNATACs: Multispecific small molecules targeting RNA by induced proximity

RNA-targeting small molecules (rSMs) have become an attractive modality to tackle traditionally undruggable proteins and expand the druggable space. Among many innovative concepts, RNA-targeting chimeras (RNATACs) represent a new class of multispecific, induced proximity small molecules that act by chemically bringing RNA targets into proximity with an endogenous RNA effector, such as a ribonuclease (RNase). Depending on the RNA effector, RNATACs can alter the stability, localization, translation, or splicing of the target RNA. Although still in its infancy, this new modality has the potential for broad applications in the future to treat diseases with high unmet need. In this review, we discuss potential advantages of RNATACs, recent progress in the field, and challenges to this cutting-edge technology.

Modulatory role of RNA helicases in MBNL-dependent alternative splicing regulation

Muscleblind-like splicing regulators (MBNLs) activate or repress the inclusion of alternative splicing (AS) events, enabling the developmental transition of fetal mRNA splicing isoforms to their adult forms. Herein, we sought to elaborate the mechanism by which MBNLs mediate AS related to biological processes. We evaluated the functional role of DEAD-box (DDX) RNA helicases, DDX5 and DDX17 in MBNL-dependent AS regulation. Whole-transcriptome analysis and validation approaches revealed a handful of MBNLs-dependent AS events to be affected by DDX5 and DDX17 in mostly an opposite manner. The opposite expression patterns of these two groups of factors during muscle development and coordination of fetal-to-adult splicing transition indicate the importance of these proteins at early stages of development. The identified pathways of how the helicases modulate MBNL splicing activity include DDX5 and DDX17-dependent changes in the ratio of MBNL splicing isoforms and most likely changes in accessibility of MBNL-binding sites. Another pathway involves the mode of action of the helicases independent of MBNL activity. These findings lead to a deeper understanding of the network of interdependencies between RNA-binding proteins and constitute a valuable element in the discussion on developmental homeostasis and pathological states in which the studied protein factors play a significant role.

Integrative solution structure of PTBP1-IRES complex reveals strong compaction and ordering with residual conformational flexibility

RNA-binding proteins (RBPs) are crucial regulators of gene expression, often composed of defined domains interspersed with flexible, intrinsically disordered regions. Determining the structure of ribonucleoprotein (RNP) complexes involving such RBPs necessitates integrative structural modeling due to their lack of a single stable state. In this study, we integrate magnetic resonance, mass spectrometry, and small-angle scattering data to determine the solution structure of the polypyrimidine-tract binding protein 1 (PTBP1/hnRNP I) bound to an RNA fragment from the internal ribosome entry site (IRES) of the encephalomyocarditis virus (EMCV). This binding, essential for enhancing the translation of viral RNA, leads to a complex structure that demonstrates RNA and protein compaction, while maintaining pronounced conformational flexibility. Acting as an RNA chaperone, PTBP1 orchestrates the IRES RNA into a few distinct conformations, exposing the RNA stems outward. This conformational diversity is likely common among RNP structures and functionally important. Our approach enables atomic-level characterization of heterogeneous RNP structures.

A spliceosome-associated gene signature aids in predicting prognosis and tumor microenvironment of hepatocellular carcinoma

Splicing alterations have been shown to be key tumorigenesis drivers. In this study, we identified a novel spliceosome-related genes (SRGs) signature to predict the overall survival (OS) of patients with hepatocellular carcinoma (HCC). A total of 25 SRGs were identified from the GSE14520 dataset (training set). Univariate and least absolute shrinkage and selection operator (LASSO) regression analyses were utilized to construct the signature using genes with predictive significance. We then constructed a risk model using six SRGs (BUB3, IGF2BP3, RBM3, ILF3, ZC3H13, and CCT3). The reliability and predictive power of the gene signature were validated in two validation sets (TCGA and GSE76427 dataset). Patients in training and validation sets were divided into high and low-risk groups based on the gene signature. Patients in high-risk groups exhibited a poorer OS than in low-risk groups both in the training set and two validation sets. Next, risk score, BCLC staging, TNM staging, and multinodular were combined in a nomogram for OS prediction, and the decision curve analysis (DCA) curve exhibited the excellent prediction performance of the nomogram. The functional enrichment analyses demonstrated high-risk score patients were closely related to multiple oncology characteristics and invasive-related pathways, such as Cell cycle, DNA replication, and Spliceosome. Different compositions of the tumor microenvironment and immunocyte infiltration ratio might contribute to the prognostic difference between high and low-risk score groups. In conclusion, a spliceosome-related six-gene signature exhibited good performance for predicting the OS of patients with HCC, which may aid in clinical decision-making for individual treatment.

A Key Molecular Regulator, RNA G-Quadruplex and Its Function in Plants

RNA structure plays key roles in plant growth, development, and adaptation. One of the complex RNA structures is the RNA G-quadruplex (RG4) where guanine-rich sequences are folded into two or more layers of G-quartets. Previous computational predictions of RG4 revealed that it is widespread across the whole transcriptomes in many plant species, raising the hypothesis that RG4 is likely to be an important regulatory motif in plants. Recently, with the advances in both high-throughput sequencing and cell imaging technologies, RG4 can be detected in living cells as well as at the genome-wide scale. Here, we provide a comprehensive review of recent developments in new methods for detecting RG4 in plants. We also summarize the new functions of RG4 in regulating plant growth and development. We then discuss the possible role of RG4 in adapting to environmental conditions along with evolutionary perspectives.

Quantitative prediction of variant effects on alternative splicing in MAPT using endogenous pre-messenger RNA structure probing

Splicing is highly regulated and is modulated by numerous factors. Quantitative predictions for how a mutation will affect precursor mRNA (pre-mRNA) structure and downstream function are particularly challenging. Here, we use a novel chemical probing strategy to visualize endogenous precursor and mature MAPT mRNA structures in cells. We used these data to estimate Boltzmann suboptimal structural ensembles, which were then analyzed to predict consequences of mutations on pre-mRNA structure. Further analysis of recent cryo-EM structures of the spliceosome at different stages of the splicing cycle revealed that the footprint of the B^act complex with pre-mRNA best predicted alternative splicing outcomes for exon 10 inclusion of the alternatively spliced MAPT gene, achieving 74% accuracy. We further developed a β-regression weighting framework that incorporates splice site strength, RNA structure, and exonic/intronic splicing regulatory elements capable of predicting, with 90% accuracy, the effects of 47 known and 6 newly discovered mutations on inclusion of exon 10 of MAPT. This combined experimental and computational framework represents a path forward for accurate prediction of splicing-related disease-causing variants.

Prognostic Signatures of Alternative Splicing Events in Esophageal Carcinoma Based on TCGA Splice-Seq Data

An alternative splicing (AS) event is a highly complex process that plays an essential role in post-transcriptional gene expression. Several studies have suggested that abnormal AS events were the primary element in the pathological process of cancer. However, few works are dedicated to the study of AS events in esophageal carcinoma (EC). In the present study, clinical information and RNA-seq data of EC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The percent spliced in (PSI) values of AS events were acquired from the TCGA Splice-seq. A total of 183 EC patients were enrolled in this study, and 2,212 AS events were found significantly associated with the overall survival of these patients by univariate Cox regression analysis. The prognostic signatures based on AS events were built by multivariate Cox analysis. Receiver operating characteristic (ROC) curves displayed that the area under the curve (AUC) of the following prognostic signatures, including exon skip (ES), alternate terminator (AT), alternate acceptor site (AA), alternate promoter (AP), alternate donor site (AD), retained intron (RI), and total events, was greater than 0.8, suggesting that these seven signatures had valuable prognosis prediction capacity. Finally, the risk score of prognostic signatures was indicated as an independent risk factor of survival. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to explore the function of splicing factors (SFs) that were associated with AS events. Also, the interactive network between AS events and SFs identified several hub genes and AS events which need further study. This was a comprehensive study that explored prognosis-related AS events and established valuable prognosis signatures in EC patients. The network of interactions between AS events and SFs might offer novel insights into the fundamental mechanisms of tumorigenesis and progression of EC.

Comprehensive Analysis of Splicing Factor and Alternative Splicing Event to Construct Subtype-Specific Prognosis-Predicting Models for Breast Cancer

Recent evidence suggests that splicing factors (SFs) and alternative splicing (AS) play important roles in cancer progression. We constructed four SF-risk-models using 12 survival-related SFs. In Luminal-A, Luminal-B, Her-2, and Basal-Like BRCA, SF-risk-models for three genes (PAXBP1, NKAP, and NCBP2), four genes (RBM15B, PNN, ACIN1, and SRSF8), three genes (LSM3, SNRNP200, and SNU13), and three genes (SRPK3, PUF60, and PNN) were constructed. These models have a promising prognosis-predicting power. The co-expression and protein-protein interaction analysis suggest that the 12 SFs are highly functional-connected. Pathway analysis and gene set enrichment analysis suggests that the functional role of the selected 12 SFs is highly context-dependent among different BRCA subtypes. We further constructed four AS-risk-models with good prognosis predicting ability in four BRCA subtypes by integrating the four SF-risk-models and 21 survival-related AS-events. This study proposed that SFs and ASs were potential multidimensional biomarkers for the diagnosis, prognosis, and treatment of BRCA.

A Survey of Autoencoder Algorithms to Pave the Diagnosis of Rare Diseases

Rare diseases (RDs) concern a broad range of disorders and can result from various origins. For a long time, the scientific community was unaware of RDs. Impressive progress has already been made for certain RDs; however, due to the lack of sufficient knowledge, many patients are not diagnosed. Nowadays, the advances in high-throughput sequencing technologies such as whole genome sequencing, single-cell and others, have boosted the understanding of RDs. To extract biological meaning using the data generated by these methods, different analysis techniques have been proposed, including machine learning algorithms. These methods have recently proven to be valuable in the medical field. Among such approaches, unsupervised learning methods via neural networks including autoencoders (AEs) or variational autoencoders (VAEs) have shown promising performances with applications on various type of data and in different contexts, from cancer to healthy patient tissues. In this review, we discuss how AEs and VAEs have been used in biomedical settings. Specifically, we discuss their current applications and the improvements achieved in diagnostic and survival of patients. We focus on the applications in the field of RDs, and we discuss how the employment of AEs and VAEs would enhance RD understanding and diagnosis.

Action and function of helicases on RNA G-quadruplexes

•

Methodological progresses and piling evidence prove the rG4 biology in vivo.

•

rG4s step in virtually every aspect of RNA biology.

•

Helicases unwinding of rG4s is a fine regulatory layer to the downstream processes and general cell homeostasis.

•

The current knowledge is however limited to a few cell lines.

•

The regulation of helicases themselves is delineating as a important question.

•

Non-helicase rG4-processing proteins likely play a role.

The nucleic acid structure called G-quadruplex (G4) is currently discussed to function in nucleic acid-based mechanisms that influence several cellular processes. They can modulate the cellular machinery either positively or negatively, both at the DNA and RNA level. The majority of what we know about G4 biology comes from DNA G4 (dG4) research. RNA G4s (rG4), on the other hand, are gaining interest as researchers become more aware of their role in several aspects of cellular homeostasis. In either case, the correct regulation of G4 structures within cells is essential and demands specialized proteins able to resolve them. Small changes in the formation and unfolding of G4 structures can have severe consequences for the cells that could even stimulate genome instability, apoptosis or proliferation. Helicases are the most relevant negative G4 regulators, which prevent and unfold G4 formation within cells during different pathways. Yet, and despite their importance only a handful of rG4 unwinding helicases have been identified and characterized thus far. This review addresses the current knowledge on rG4s-processing helicases with a focus on methodological approaches. An example of a non-helicase rG4s-unwinding protein is also briefly described.

Complex Conformational Dynamics of the Heart Failure-Associated Pre-miRNA-377 Hairpin Revealed by Single-Molecule Optical Tweezers

Pre-miRNA-377 is a hairpin-shaped regulatory RNA associated with heart failure. Here, we use single-molecule optical tweezers to unzip pre-miRNA-377 and study its stability and dynamics. We show that magnesium ions have a strong stabilizing effect, and that sodium ions stabilize the hairpin more than potassium ions. The hairpin unfolds in a single step, regardless of buffer composition. Interestingly, hairpin folding occurs either in a single step (type 1) or through the formation of intermediates, in multiple steps (type 2) or gradually (type 3). Type 3 occurs only in the presence of both sodium and magnesium, while type 1 and 2 take place in all buffers, with type 1 being the most prevalent. By reducing the size of the native hairpin loop from fourteen to four nucleotides, we demonstrate that the folding heterogeneity originates from the large size of the hairpin loop. Further, while efficient pre-miRNA-377 binders are lacking, we demonstrate that the recently developed C2 ligand displays bimodal activity: it enhances the mechanical stability of the pre-miRNA-377 hairpin and perturbs its folding. The knowledge regarding pre-miRNA stability and dynamics that we provide is important in understanding its regulatory function and how it can be modulated to achieve a therapeutic effect, e.g., in heart failure treatment.

Graph Theoretical Methods and Workflows for Searching and Annotation of RNA Tertiary Base Motifs and Substructures

The increasing number and complexity of structures containing RNA chains in the Protein Data Bank (PDB) have led to the need for automated structure annotation methods to replace or complement expert visual curation. This is especially true when searching for tertiary base motifs and substructures. Such base arrangements and motifs have diverse roles that range from contributions to structural stability to more direct involvement in the molecule's functions, such as the sites for ligand binding and catalytic activity. We review the utility of computational approaches in annotating RNA tertiary base motifs in a dataset of PDB structures, particularly the use of graph theoretical algorithms that can search for such base motifs and annotate them or find and annotate clusters of hydrogen-bond-connected bases. We also demonstrate how such graph theoretical algorithms can be integrated into a workflow that allows for functional analysis and comparisons of base arrangements and sub-structures, such as those involved in ligand binding. The capacity to carry out such automatic curations has led to the discovery of novel motifs and can give new context to known motifs as well as enable the rapid compilation of RNA 3D motifs into a database.

The genetics of mitochondrial disease: dissecting mitochondrial pathology using multi-omic pipelines

Mitochondria play essential roles in numerous metabolic pathways including the synthesis of adenosine triphosphate through oxidative phosphorylation. Clinically, mitochondrial diseases occur when there is mitochondrial dysfunction – manifesting at any age and affecting any organ system; tissues with high energy requirements, such as muscle and the brain, are often affected. The clinical heterogeneity is parallel to the degree of genetic heterogeneity associated with mitochondrial dysfunction. Around 10% of human genes are predicted to have a mitochondrial function, and defects in over 300 genes are reported to cause mitochondrial disease. Some involve the mitochondrial genome (mtDNA), but the vast majority occur within the nuclear genome. Except for a few specific genetic defects, there remains no cure for mitochondrial diseases, which means that a genetic diagnosis is imperative for genetic counselling and the provision of reproductive options for at‐risk families. Next‐generation sequencing strategies, particularly exome and whole‐genome sequencing, have revolutionised mitochondrial diagnostics such that the traditional muscle biopsy has largely been replaced with a minimally‐invasive blood sample for an unbiased approach to genetic diagnosis. Where these genomic approaches have not identified a causative defect, or where there is insufficient support for pathogenicity, additional functional investigations are required. The application of supplementary ‘omics’ technologies, including transcriptomics, proteomics, and metabolomics, has the potential to greatly improve diagnostic strategies. This review aims to demonstrate that whilst a molecular diagnosis can be achieved for many cases through next‐generation sequencing of blood DNA, the use of patient tissues and an integrated, multidisciplinary multi‐omics approach is pivotal for the diagnosis of more challenging cases. Moreover, the analysis of clinically relevant tissues from affected individuals remains crucial for understanding the molecular mechanisms underlying mitochondrial pathology. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

Detection of aberrant splicing events in RNA-seq data using FRASER

Aberrant splicing is a major cause of rare diseases.  However, its prediction from genome sequence alone remains in most cases inconclusive. Recently, RNA sequencing has proven to be an effective complementary avenue to detect aberrant splicing. Here, we develop FRASER, an algorithm to detect aberrant splicing from RNA sequencing data. Unlike existing methods, FRASER captures not only alternative splicing but also intron retention events. This typically doubles the number of detected aberrant events and identified a pathogenic intron retention in MCOLN1 causing mucolipidosis. FRASER automatically controls for latent confounders, which are widespread and affect sensitivity substantially. Moreover, FRASER is based on a count distribution and multiple testing correction, thus reducing the number of calls by two orders of magnitude over commonly applied z score cutoffs, with a minor loss of sensitivity. Applying FRASER to rare disease diagnostics is demonstrated by reprioritizing a pathogenic aberrant exon truncation in TAZ from a published dataset. FRASER is easy to use and freely available.

Design of the Crosslinking Reactions for Nucleic Acids-Binding Protein and Evaluation of the Reactivity

Selective chemical reactions of biomolecules are some of the important tools for investigations by biological studies. We have developed the selective crosslinking reactions to form covalent bonds to DNA or RNA using crosslinking oligonucleotides (CFO) bearing reactive bases. In this study, we designed the cross-linkable 4-amino-6-oxo-2-vinyltriazine derivative with an acyclic linker (acyAOVT) to react with the nucleic acids-binding protein based on our previous results. We hypothesized that the acyAOVT base would form a stable base pair with guanine by three hydrogen bonds at the positions of the vinyl group in the duplex DNA major groove, and the vinyl group can react with the nucleophilic species in the proximity, for example, the cysteine or lysine residue in the nucleic acids-binding protein. The synthesized oligonucleotides bearing the acyAOVT derivative showed a higher reactivity than that of the corresponding pyrimidine derivative without one nitrogen. The duplex containing acyAOVT-guanine (G) formed complexes with Hha1 DNMT even in the presence of 2-mercaptoethanol. We expect that our system will provide a useful tool for the molecular study of nucleic acids-binding proteins.