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Polyglutamine spinocerebellar ataxias (PolyQ SCAs) represent a group of monogenetic diseases in which the expanded polyglutamine repeats give rise to a mutated protein. The abnormally expanded polyglutamine protein produces aggregates and toxic species, causing neuronal dysfunction and neuronal death. The main symptoms of these disorders include progressive ataxia, motor dysfunction, oculomotor impairment, and swallowing problems. Nowadays, the current treatments are restricted to symptomatic alleviation, and no existing therapeutic strategies can reduce or stop the disease progression. Even though the origin of these disorders has been associated with polyglutamine-induced toxicity, RNA toxicity has recently gained relevance in polyQ SCAs molecular pathogenesis. Therefore, the research's focus on RNA metabolism has been increasing, especially on RNA-binding proteins (RBPs). The present review summarizes RNA metabolism, exposing the different processes and the main RBPs involved. We also explore the mechanisms by which RBPs are dysregulated in PolyQ SCAs. Finally, possible therapies targeting the RNA metabolism are presented as strategies to reverse neuropathological anomalies and mitigate physical symptoms., (© 2023 International Society for Neurochemistry.)

Germinal centers (GCs) are essential for the establishment of long-lasting antibody responses. GC B cells rely on post-transcriptional RNA mechanisms to translate activation-associated transcriptional programs into functional changes in the cell proteome. However, the critical proteins driving these key mechanisms are still unknown. Here, we show that the RNA binding proteins TIA1 and TIAL1 are required for the generation of long-lasting GC responses. TIA1- and TIAL1-deficient GC B cells fail to undergo antigen-mediated positive selection, expansion and differentiation into B-cell clones producing high-affinity antibodies. Mechanistically, TIA1 and TIAL1 control the transcriptional identity of dark- and light-zone GC B cells and enable timely expression of the prosurvival molecule MCL1. Thus, we demonstrate here that TIA1 and TIAL1 are key players in the post-transcriptional program that selects high-affinity antigen-specific GC B cells., (© 2023. The Author(s).)

Matrin3 is an RNA- and DNA-binding nuclear matrix protein found to be associated with neural and muscular degenerative diseases. A number of possible functions of Matrin3 have been suggested, but no widespread role in RNA metabolism has yet been clearly demonstrated. We identified Matrin3 by its interaction with the second RRM domain of the splicing regulator PTB. Using a combination of RNAi knockdown, transcriptome profiling and iCLIP, we find that Matrin3 is a regulator of hundreds of alternative splicing events, principally acting as a splicing repressor with only a small proportion of targeted events being co-regulated by PTB. In contrast to other splicing regulators, Matrin3 binds to an extended region within repressed exons and flanking introns with no sharply defined peaks. The identification of this clear molecular function of Matrin3 should help to clarify the molecular pathology of ALS and other diseases caused by mutations of Matrin3., (© 2015 The Authors. Published under the terms of the CC BY 4.0 license.)

In metazoans, fertilization initiates vast remodeling of the embryonic proteome and transcriptome. This is accomplished via complex post-transcriptional regulation of maternal and zygotic RNA. RNA-binding proteins (RBPs) are one of the major mediators of embryonic post-transcriptional RNA regulation. Thus, elucidation of the molecular mechanisms by which maternal and zygotic transcripts change their translational capacities and expression levels requires thorough and precise determination of the targets and binding sites of individual RBPs in embryonic transcriptomes. Here, I provide a detailed protocol for the UV crosslinking-based method, named iCLIP, to study RBP functions during early zebrafish embryogenesis.

Hundreds of canonical RNA binding proteins facilitate diverse and essential RNA processing steps in cells forming a central regulatory point in gene expression. However, recent discoveries including the identification of a large number of noncanonical proteins bound to RNA have changed our view on RNA-protein interactions merely as necessary steps in RNA biogenesis. As the list of proteins interacting with RNA has expanded, so has the scope of regulation through RNA-protein interactions. In addition to facilitating RNA metabolism, RNA binding proteins help to form subcellular structures and membraneless organelles, and provide means to recruit components of macromolecular complexes to their sites of action. Moreover, RNA-protein interactions are not static in cells but the ribonucleoprotein (RNP) complexes are highly dynamic in response to cellular cues. The identification of novel proteins in complex with RNA and ways cells use these interactions to control cellular functions continues to broaden the scope of RNA regulation in cells and the current challenge is to move from cataloguing the components of RNPs into assigning them functions. This will not only facilitate our understanding of cellular homeostasis but may bring in key insights into human disease conditions where RNP components play a central role. This review brings together the classical view of regulation accomplished through RNA-protein interactions with the novel insights gained from the identification of RNA binding interactomes. We discuss the challenges in combining molecular mechanism with cellular functions on the journey towards a comprehensive understanding of the regulatory functions of RNA-protein interactions in cells. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications aRNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes RNA Interactions with Proteins and Other Molecules > Protein-RNA Recognition., (© 2019 Wiley Periodicals, Inc.)

The unique composition and spatial arrangement of RNA-binding proteins (RBPs) on a transcript guide the diverse aspects of post-transcriptional regulation. Therefore, an essential step towards understanding transcript regulation at the molecular level is to gain positional information on the binding sites of RBPs. Protein-RNA interactions can be studied using biochemical methods, but these approaches do not address RNA binding in its native cellular context. Initial attempts to study protein-RNA complexes in their cellular environment employed affinity purification or immunoprecipitation combined with differential display or microarray analysis (RIP-CHIP). These approaches were prone to identifying indirect or non-physiological interactions. In order to increase the specificity and positional resolution, a strategy referred to as CLIP (UV cross-linking and immunoprecipitation) was introduced. CLIP combines UV cross-linking of proteins and RNA molecules with rigorous purification schemes including denaturing polyacrylamide gel electrophoresis. In combination with high-throughput sequencing technologies, CLIP has proven as a powerful tool to study protein-RNA interactions on a genome-wide scale (referred to as HITS-CLIP or CLIP-seq). Recently, PAR-CLIP was introduced that uses photoreactive ribonucleoside analogs for cross-linking. Despite the high specificity of the obtained data, CLIP experiments often generate cDNA libraries of limited sequence complexity. This is partly due to the restricted amount of co-purified RNA and the two inefficient RNA ligation reactions required for library preparation. In addition, primer extension assays indicated that many cDNAs truncate prematurely at the crosslinked nucleotide. Such truncated cDNAs are lost during the standard CLIP library preparation protocol. We recently developed iCLIP (individual-nucleotide resolution CLIP), which captures the truncated cDNAs by replacing one of the inefficient intermolecular RNA ligation steps with a more efficient intramolecular cDNA circularization (Figure 1). Importantly, sequencing the truncated cDNAs provides insights into the position of the cross-link site at nucleotide resolution. We successfully applied iCLIP to study hnRNP C particle organization on a genome-wide scale and assess its role in splicing regulation.

The regulation of alternative splicing involves interactions between RNA-binding proteins and pre-mRNA positions close to the splice sites. T-cell intracellular antigen 1 (TIA1) and TIA1-like 1 (TIAL1) locally enhance exon inclusion by recruiting U1 snRNP to 5' splice sites. However, effects of TIA proteins on splicing of distal exons have not yet been explored. We used UV-crosslinking and immunoprecipitation (iCLIP) to find that TIA1 and TIAL1 bind at the same positions on human RNAs. Binding downstream of 5' splice sites was used to predict the effects of TIA proteins in enhancing inclusion of proximal exons and silencing inclusion of distal exons. The predictions were validated in an unbiased manner using splice-junction microarrays, RT-PCR, and minigene constructs, which showed that TIA proteins maintain splicing fidelity and regulate alternative splicing by binding exclusively downstream of 5' splice sites. Surprisingly, TIA binding at 5' splice sites silenced distal cassette and variable-length exons without binding in proximity to the regulated alternative 3' splice sites. Using transcriptome-wide high-resolution mapping of TIA-RNA interactions we evaluated the distal splicing effects of TIA proteins. These data are consistent with a model where TIA proteins shorten the time available for definition of an alternative exon by enhancing recognition of the preceding 5' splice site. Thus, our findings indicate that changes in splicing kinetics could mediate the distal regulation of alternative splicing., Competing Interests: The authors have declared that no competing interests exist.

Protein-RNA interactions have critical roles in all aspects of gene expression. However, applying biochemical methods to understand such interactions in living tissues has been challenging. Here we develop a genome-wide means of mapping protein-RNA binding sites in vivo, by high-throughput sequencing of RNA isolated by crosslinking immunoprecipitation (HITS-CLIP). HITS-CLIP analysis of the neuron-specific splicing factor Nova revealed extremely reproducible RNA-binding maps in multiple mouse brains. These maps provide genome-wide in vivo biochemical footprints confirming the previous prediction that the position of Nova binding determines the outcome of alternative splicing; moreover, they are sufficiently powerful to predict Nova action de novo. HITS-CLIP revealed a large number of Nova-RNA interactions in 3' untranslated regions, leading to the discovery that Nova regulates alternative polyadenylation in the brain. HITS-CLIP, therefore, provides a robust, unbiased means to identify functional protein-RNA interactions in vivo.

Mutations in the nuclear matrix protein Matrin 3 (MATR3) have been identified in amyotrophic lateral sclerosis and myopathy. To investigate the mechanisms underlying MATR3 mutations in neuromuscular diseases and efficiently screen for modifiers of MATR3 toxicity, we generated transgenic MATR3 flies. Our findings indicate that expression of wild-type or mutant MATR3 in motor neurons reduces climbing ability and lifespan of flies, while their expression in indirect flight muscles (IFM) results in abnormal wing positioning and muscle degeneration. In both motor neurons and IFM, mutant MATR3 expression results in more severe phenotypes than wild-type MATR3, demonstrating that the disease-linked mutations confer pathogenicity. We conducted a targeted candidate screen for modifiers of the MATR3 abnormal wing phenotype and identified multiple enhancers involved in axonal transport. Knockdown of these genes enhanced protein levels and insolubility of mutant MATR3. These results suggest that accumulation of mutant MATR3 contributes to toxicity and implicate axonal transport dysfunction in disease pathogenesis., (© 2020 The Authors. FEBS Letters published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.)

RNA-binding proteins (RBPs) mediate important co- and post-transcriptional gene regulation by binding pre-mRNA in a sequence- and/or structure-specific manner. For a comprehensive understanding of RBP function, transcriptome-wide mapping of the RNA-binding sites is essential, and CLIP-seq methods have been developed to elucidate protein/RNA interactions at high resolution. CLIP-seq combines protein/RNA UV-crosslinking with immunoprecipitation (CLIP) followed by high-throughput sequencing of crosslinked RNA fragments. To overcome the limitations of low RNA-protein crosslinking efficiency in standard CLIP-seq, photoactivatable-ribonucleoside-enhanced CLIP (PAR-CLIP) has been developed. Here, living cells or whole organisms are fed photo-activatable nucleoside analogs that are incorporated into nascent RNA transcripts before UV treatment. This allows greater crosslinking efficiency at comparable radiation doses for enhanced RNA recovery and separation of crosslinked target RNA fragments from background RNA degradation products. Moreover, it facilitates the generation of specific UV-induced mutations that mark the crosslinking nucleotide and allow transcriptome-wide identification of RBP binding sites at single-nucleotide resolution. © by 2017 John Wiley & Sons, Inc., (Copyright © 2017 John Wiley & Sons, Inc.)

Inferring the driving regulatory programs from comparative analysis of gene expression data is a cornerstone of systems biology. Many computational frameworks were developed to address this problem, including our iPAGE (information-theoretic Pathway Analysis of Gene Expression) toolset that uses information theory to detect non-random patterns of expression associated with given pathways or regulons. Our recent observations, however, indicate that existing approaches are susceptible to the technical biases that are inherent to most real world annotations. To address this, we have extended our information-theoretic framework to account for specific biases and artifacts in biological networks using the concept of conditional information. To showcase pyPAGE, we performed a comprehensive analysis of regulatory perturbations that underlie the molecular etiology of Alzheimer's disease (AD). pyPAGE successfully recapitulated several known AD-associated gene expression programs. We also discovered several additional regulons whose differential activity is significantly associated with AD. We further explored how these regulators relate to pathological processes in AD through cell-type specific analysis of single cell and spatial gene expression datasets. Our findings showcase the utility of pyPAGE as a precise and reliable biomarker discovery in complex diseases such as Alzheimer's disease. Author summary: Biological regulation is governed by a complex network of interactions involving transcription factors, RNA-binding proteins, and microRNAs. To reveal the regulatory programs underlying gene expression modulations, researchers often take advantage of gene-set enrichment analysis, an approach that studies concerted changes in a group of genes rather than observing genes in isolation. Previously, we developed a tool called iPAGE to facilitate this analysis. However, both iPAGE and other similar tools implicitly assume that different genes have uniform gene-set membership. Our recent observations challenge this assumption, revealing that some genes form regulatory networks far more frequently than others. These technical biases and redundancies in gene-set annotations complicate the accurate inference of true regulatory relationships in specific contexts. To overcome these limitations, we introduced pyPAGE, an enhanced method that extends our information-theoretic framework by incorporating conditional mutual information to account for specific biases and artifacts. We applied pyPAGE to Alzheimer's disease, a neurodegenerative disorder marked by its complexity and characterized by progressive cognitive decline, memory loss, and behavioral changes. Pathological processes of Alzheimer's disease involve various cell types and diverse molecular mechanisms, which pose significant challenges for study. In our study we took advantage of our newly developed framework pyPAGE, performing analysis of gene expression changes at both tissue and cell type levels. This way we were able to describe regulation patterns of known regulators of Alzheimer's as well as several new ones. Additionally, we performed a cohort study of the association between the enrichment of the identified regulons and survival prognosis for patients, showing that increased activity of a subset of RBPs is positively associated with a lifespan. In total the results highlight the utility of pyPAGE and provide a valuable set of biomarkers for Alzheimer's disease. [ABSTRACT FROM AUTHOR]

Alternative splicing is a complex gene regulatory process that distinguishes itself from canonical splicing by rearranging the introns and exons of an immature pre-mRNA transcript. This process plays a vital role in enhancing transcriptomic and proteomic diversity from the genome. Alternative splicing has emerged as a pivotal mechanism governing complex biological processes during both heart development and the development of cardiovascular diseases. Multiple alternative splicing factors are involved in a synergistic or antagonistic manner in the regulation of important genes in relevant physiological processes. Notably, circular RNAs have only recently garnered attention for their tissue-specific expression patterns and regulatory functions. This resurgence of interest has prompted a reevaluation of the topic. Here, we provide an overview of our current understanding of alternative splicing mechanisms and the regulatory roles of alternative splicing factors in cardiovascular development and pathological process of different cardiovascular diseases, including cardiomyopathy, myocardial infarction, heart failure and atherosclerosis. [ABSTRACT FROM AUTHOR]

The dysfunction of many RNA-binding proteins (RBPs) that are heavily disordered, including TDP-43 and FUS, are implicated in amyotrophic lateral sclerosis and frontotemporal dementia (ALS/FTD). These proteins serve many important roles in the cell, and their capacity to form biomolecular condensates (BMCs) is key to their function, but also a vulnerability that can lead to misregulation and disease. Matrin-3 (MATR3) is an intrinsically disordered RBP implicated both genetically and pathologically in ALS/FTD, though it is relatively understudied as compared with TDP-43 and FUS. In addition to binding RNA, MATR3 also binds DNA and is implicated in many cellular processes including the DNA damage response, transcription, splicing, and cell differentiation. It is unclear if MATR3 localizes to BMCs under physiological conditions, which is brought further into question due to its lack of a prion-like domain. Here, we review recent studies regarding MATR3 and its roles in numerous physiological processes, as well as its implication in a range of diseases. [ABSTRACT FROM AUTHOR]

RNA-binding proteins and chemical modifications to RNA play vital roles in the co- and post-transcriptional regulation of genes. In order to fully decipher their biological roles, it is an essential task to catalogue their precise target locations along with their preferred contexts and sequence-based determinants. Recently, deep learning approaches have significantly advanced in this field. These methods can predict the presence or absence of modification at specific genomic regions based on diverse features, particularly sequence and secondary structure, allowing us to decipher the highly non-linear sequence patterns and structures that underlie site preferences. This article provides an overview of how deep learning is being applied to this area, with a particular focus on the problem of mRNA-RBP binding, while also considering other types of chemical modification to RNA. It discusses how different types of model can handle sequence-based and/or secondary-structure-based inputs, the process of model training, including choice of negative regions and separating sets for testing and training, and offers recommendations for developing biologically relevant models. Finally, it highlights four key areas that are crucial for advancing the field. [ABSTRACT FROM AUTHOR]

Simple Summary: T-cell intracellular antigen 1 (TIA1/TIA-1) and its paralog TIA1-related/like protein (TIAL1/TIAR) have been implicated in the regulation and/or modulation of gene expression through aspects of RNA metabolism, such as (1) transcription, through their interaction with DNA and RNA polymerase II; (2) alternative processing of messenger pre-mRNAs, through selection of canonical and atypical 5′ and 3′ splice sites; (3) localization, stability and/or translation of eukaryotic messenger RNAs, through interaction with 5′ and 3′ untranslatable regions; and (4) control of biological programs fundamental to cell viability (i.e., development, inflammation, proliferation/differentiation, apoptosis, autophagy, responses to stress or viral infections). It is therefore essential to understand the role played by these multifunctional regulators in the establishment and adaptation of the diversity of the transcriptome, translatome, proteome and interactome, which represents a key step in understanding the differences in functional heterogeneity between cells, tissues and organisms with similar genetic complexities. In other words, it is necessary to highlight the importance of identifying the early and late cellular processes and molecular mechanisms where TIA proteins participate and how they contribute to maintain homeostasis, preventing the development and/or progression of deleterious phenotypes. Knowledge of the regulatory dynamics associated with these intracellular antigens will serve as a basis for the identification of future therapeutic strategies. T-cell intracellular antigen 1 (TIA1) and TIA1-like/related protein (TIAL1/TIAR) are two members of the classical family of RNA binding proteins. Through their selective interactions with distinct RNAs and proteins, these multifunctional regulators are involved in chromatin remodeling, RNA splicing and processing and translation regulation, linking them to a wide range of diseases including neuronal disorders, cancer and other pathologies. From their discovery to the present day, many studies have focused on the behavior of these proteins in order to understand their impact on molecular and cellular processes and to understand their relationship to human pathologies. The volume of research on these proteins in various fields, including molecular biology, biochemistry, cell biology, immunology and cancer, has steadily increased, indicating a growing interest in these gene expression regulators among researchers. This information can be used to know the most productive institutions working in the field, understand the focus of research, identify key areas of involvement, delve deeper into their relationship and impact on different diseases, and to establish the level of study associated with them. [ABSTRACT FROM AUTHOR]

TDP-43 is an essential RNA-binding protein strongly implicated in the pathogenesis of neurodegenerative disorders characterized by cytoplasmic aggregates and loss of nuclear TDP-43. The protein shuttles between nucleus and cytoplasm, yet maintaining predominantly nuclear TDP-43 localization is important for TDP-43 function and for inhibiting cytoplasmic aggregation. We previously demonstrated that specific RNA binding mediates TDP-43 self-assembly and biomolecular condensation, requiring multivalent interactions via N- and C-terminal domains. Here, we show that these complexes play a key role in TDP-43 nuclear retention. TDP-43 forms macromolecular complexes with a wide range of size distribution in cells and we find that defects in RNA binding or inter-domain interactions, including phase separation, impair the assembly of the largest species. Our findings suggest that recruitment into these macromolecular complexes prevents cytoplasmic egress of TDP-43 in a size-dependent manner. Our observations uncover fundamental mechanisms controlling TDP-43 cellular homeostasis, whereby regulation of RNA-mediated self-assembly modulates TDP-43 nucleocytoplasmic distribution. Moreover, these findings highlight pathways that may be implicated in TDP-43 proteinopathies and identify potential therapeutic targets. TDP-43 nuclear localization is crucial for its function during RNA processing and pathogenesis of neurodegenerative disorders. This manuscript demonstrates that RNA binding and macromolecular assembly, through multivalent interactions and liquid-liquid phase separation, play a central role in TDP-43 nuclear retention. [ABSTRACT FROM AUTHOR]

Amyotrophic lateral sclerosis (ALS) is a progressive, lethal neurodegenerative disease mostly affecting people around 50–60 years of age. TDP-43, an RNA-binding protein involved in pre-mRNA splicing and controlling mRNA stability and translation, forms neuronal cytoplasmic inclusions in an overwhelming majority of ALS patients, a phenomenon referred to as TDP-43 proteinopathy. These cytoplasmic aggregates disrupt mRNA transport and localization. The axon, like dendrites, is a site of mRNA translation, permitting the local synthesis of selected proteins. This is especially relevant in upper and lower motor neurons, whose axon spans long distances, likely accentuating their susceptibility to ALS-related noxae. In this work we have generated and characterized two cellular models, consisting of virtually pure populations of primary mouse cortical neurons expressing a human TDP-43 fusion protein, wt or carrying an ALS mutation. Both forms facilitate cytoplasmic aggregate formation, unlike the corresponding native proteins, giving rise to bona fide primary culture models of TDP-43 proteinopathy. Neurons expressing TDP-43 fusion proteins exhibit a global impairment in axonal protein synthesis, an increase in oxidative stress, and defects in presynaptic function and electrical activity. These changes correlate with deregulation of axonal levels of polysome-engaged mRNAs playing relevant roles in the same processes. Our data support the emerging notion that deregulation of mRNA metabolism and of axonal mRNA transport may trigger the dying-back neuropathy that initiates motor neuron degeneration in ALS. [ABSTRACT FROM AUTHOR]

Simple Summary: RNA-binding proteins play crucial roles in essential biological processes, and disruptions in their functionality can lead to various diseases, including cancer. Despite the significant progress that computational deep learning methods have made in identifying their binding sites, obtaining high-quality data in sufficient amounts remains a major challenge, impeding development of accurate predictive models for many proteins. In this work, we present a novel approach to address the limited availability of training samples by leveraging transfer learning for predicting RBP binding sites. Using three input features and a sophisticated network architecture, we demonstrate the substantial advantages of employing transfer learning in a reusable and interpretable manner, as showcased on two prominent benchmark datasets for RNA-binding proteins. RNA-binding proteins are vital regulators in numerous biological processes. Their disfunction can result in diverse diseases, such as cancer or neurodegenerative disorders, making the prediction of their binding sites of high importance. Deep learning (DL) has brought about a revolution in various biological domains, including the field of protein–RNA interactions. Nonetheless, several challenges persist, such as the limited availability of experimentally validated binding sites to train well-performing DL models for the majority of proteins. Here, we present a novel training approach based on transfer learning (TL) to address the issue of limited data. Employing a sophisticated and interpretable architecture, we compare the performance of our method trained using two distinct approaches: training from scratch (SCR) and utilizing TL. Additionally, we benchmark our results against the current state-of-the-art methods. Furthermore, we tackle the challenges associated with selecting appropriate input features and determining optimal interval sizes. Our results show that TL enhances model performance, particularly in datasets with minimal training data, where satisfactory results can be achieved with just a few hundred RNA binding sites. Moreover, we demonstrate that integrating both sequence and evolutionary conservation information leads to superior performance. Additionally, we showcase how incorporating an attention layer into the model facilitates the interpretation of predictions within a biologically relevant context. [ABSTRACT FROM AUTHOR]

RNA‐binding proteins (RBPs) govern the lifespan of nearly all transcripts and play key roles in adaptive responses in microbes. A robust approach to examine protein–RNA interactions involves irradiating cells with UV light to form covalent adducts between RBPs and their cognate RNAs. Combined with RNA or protein purification, these procedures can provide global RBP censuses or transcriptomic maps for all target sequences of a single protein in living cells. The recent development of novel methods has quickly populated the RBP landscape in microorganisms. Here, we provide an overview of prominent UV cross‐linking techniques which have been applied to investigate RNA interactomes in microbes. By assessing their advantages and caveats, this technical evaluation intends to guide the selection of appropriate methods and experimental design as well as to encourage the use of complementary UV‐dependent techniques to inspect RNA‐binding activity. [ABSTRACT FROM AUTHOR]

Nucleotide composition plays a crucial role in the structure, function and recognition of RNA molecules. During infection, virus RNA is exposed to multiple endogenous proteins that detect local or global compositional biases and interfere with virus replication. Recent advancements in RNA:protein mapping technologies have enabled the identification of general RNA-binding preferences in the human proteome at basal level and in the context of virus infection. In this review, we explore how cellular proteins recognise nucleotide composition in virus RNA and the impact these interactions have on virus replication. Protein-binding G-rich and C-rich sequences are common examples of how host factors detect and limit infection, and, in contrast, viruses may have evolved to purge their genomes from such motifs. We also give examples of how human RNA-binding proteins inhibit virus replication, not only by destabilising virus RNA, but also by interfering with viral protein translation and genome encapsidation. Understanding the interplay between cellular proteins and virus RNA composition can provide insights into host–virus interactions and uncover potential targets for antiviral strategies. [ABSTRACT FROM AUTHOR]

Oncogenic RAS signaling reprograms gene expression through both transcriptional and post‐transcriptional mechanisms. While transcriptional regulation downstream of RAS is relatively well characterized, how RAS post‐transcriptionally modulates gene expression to promote malignancy remains largely unclear. Using quantitative RNA interactome capture analysis, we here reveal that oncogenic RAS signaling reshapes the RNA‐bound proteomic landscape of pancreatic cancer cells, with a network of nuclear proteins centered around nucleolin displaying enhanced RNA‐binding activity. We show that nucleolin is phosphorylated downstream of RAS, which increases its binding to pre‐ribosomal RNA (rRNA), boosts rRNA production, and promotes ribosome biogenesis. This nucleolin‐dependent enhancement of ribosome biogenesis is crucial for RAS‐induced pancreatic cancer cell proliferation and can be targeted therapeutically to inhibit tumor growth. Our results reveal that oncogenic RAS signaling drives ribosome biogenesis by regulating the RNA‐binding activity of nucleolin and highlight a crucial role for this mechanism in RAS‐mediated tumorigenesis. Synopsis: Oncogenic RAS‐induced ERK1/2 activity promotes the phosphorylation and RNA‐binding activity of nucleolin (NCL), boosting ribosome biogenesis, protein synthesis, and pancreatic tumorigenesis. Oncogenic KRAS reshapes the RNA‐bound proteomic landscape of pancreatic ductal adenocarcinoma cells, increasing the activity of RNA‐binding proteins, including NCL.NCL is phosphorylated downstream of oncogenic KRAS, via ERK1/2‐mediated activation of casein kinase 2, enhancing its binding to pre‐rRNA.Increased NCL–pre‐rRNA binding boosts nascent pre‐rRNA levels, leading to increased ribosome biogenesis and protein synthesis.NCL‐promoted ribosome biogenesis is required for KRAS‐driven tumorigenesis and can be therapeutically exploited. [ABSTRACT FROM AUTHOR]

As a master regulator in cells, RNA-binding protein (RBP) plays critical roles in organismal development, metabolism and various diseases. It regulates gene expression at various levels mostly by specific recognition of target RNA. The traditional CLIP-seq method to detect transcriptome-wide RNA targets of RBP is less efficient in yeast due to the low UV transmissivity of their cell walls. Here, we established an efficient HyperTRIBE (Targets of RNA-binding proteins Identified By Editing) in yeast, by fusing an RBP to the hyper-active catalytic domain of human RNA editing enzyme ADAR2 and expressing the fusion protein in yeast cells. The target transcripts of RBP were marked with new RNA editing events and identified by high-throughput sequencing. We successfully applied HyperTRIBE to identifying the RNA targets of two yeast RBPs, KHD1 and BFR1. The antibody-free HyperTRIBE has competitive advantages including a low background, high sensitivity and reproducibility, as well as a simple library preparation procedure, providing a reliable strategy for RBP target identification in Saccharomyces cerevisiae. [ABSTRACT FROM AUTHOR]

Myotonic dystrophy (DM) is a highly variable, multisystemic disorder that clinically affects one in 8000 individuals. While research has predominantly focused on the symptoms and pathological mechanisms affecting striated muscle and brain, DM patient surveys have identified a high prevalence for gastrointestinal (GI) symptoms amongst affected individuals. Clinical studies have identified chronic and progressive dysfunction of the esophagus, stomach, liver and gallbladder, small and large intestine, and rectum and anal sphincters. Despite the high incidence of GI dysmotility in DM, little is known regarding the pathological mechanisms leading to GI dysfunction. In this review, we summarize results from clinical and molecular analyses of GI dysfunction in both genetic forms of DM, DM type 1 (DM1) and DM type 2 (DM2). Based on current knowledge of DM primary pathological mechanisms in other affected tissues and GI tissue studies, we suggest that misregulation of alternative splicing in smooth muscle resulting from the dysregulation of RNA binding proteins muscleblind-like and CUGBP-elav-like is likely to contribute to GI dysfunction in DM. We propose that a combinatorial approach using clinical and molecular analysis of DM GI tissues and model organisms that recapitulate DM GI manifestations will provide important insight into defects impacting DM GI motility. [ABSTRACT FROM AUTHOR]

Transcriptome-wide analysis of RNA-binding partners is commonly achieved using UV crosslinking and immunoprecipitation (CLIP). Individual-nucleotide-resolution CLIP (iCLIP)enables identification of the specific position of the protein–RNA interaction. In addition to RNA-binding proteins (RBPs), microRNA (miRNA)–mRNA interactions also play a crucial role in the regulation of gene expression. Argonaute-2 (Ago2) mediates miRNA binding to a multitude of mRNA target sites, enabling the identification of miRNA–mRNA interactions by employing modified Ago2-CLIP protocols. Here, we describe an Ago2-specific CLIP protocol optimized for the use of small quantities of cell material, targeting endogenous Ago2 while avoiding possible methodological biases such as metabolic labeling or Ago2 overexpression and applying the latest advances in CLIP library preparation, the iCLIP2 protocol. In particular, we focus on the optimization of lysis conditions and improved radioactive labeling of the 5′ end of the miRNA. [ABSTRACT FROM AUTHOR]

TAR DNA binding protein 43 (TDP-43) is a DNA/RNA binding protein involved in pivotal cellular functions, especially in RNA metabolism. Hyperphosphorylated and ubiquitinated TDP-43-positive neuronal cytoplasmic inclusions are identified in the brain and spinal cord in most cases of amyotrophic lateral sclerosis (ALS) and a substantial proportion of frontotemporal lobar degeneration (FTLD) cases. TDP-43 dysfunctions and cytoplasmic aggregation seem to be the central pathogenicity in ALS and FTLD. Therefore, unraveling both the physiological and pathological mechanisms of TDP-43 may enable the exploration of novel therapeutic strategies. This review highlights the current understanding of TDP-43 biology and pathology, describing the cellular processes involved in the pathogeneses of ALS and FTLD, such as post-translational modifications, RNA metabolism, liquid–liquid phase separation, proteolysis, and the potential prion-like propagation propensity of the TDP-43 inclusions. [ABSTRACT FROM AUTHOR]

Spinal muscular atrophy (SMA) is a devastating neuromuscular disorder caused by recessive mutations in the SMN1 gene, globally affecting ~8–14 newborns per 100,000. The severity of the disease depends on the residual levels of functional survival of motor neuron protein, SMN. SMN is a ubiquitously expressed RNA binding protein involved in a plethora of cellular processes. In this review, we discuss the effects of SMN loss on mitochondrial functions in the neuronal and muscular systems that are the most affected in patients with spinal muscular atrophy. Our aim is to highlight how mitochondrial defects may contribute to disease progression and how restoring mitochondrial functionality may be a promising approach to develop new therapies. We also collected from previous studies a list of transcripts encoding mitochondrial proteins affected in various SMA models. Moreover, we speculate that in adulthood, when motor neurons require only very low SMN levels, the natural deterioration of mitochondria associated with aging may be a crucial triggering factor for adult spinal muscular atrophy, and this requires particular attention for therapeutic strategies. [ABSTRACT FROM AUTHOR]

Amyotrophic lateral sclerosis (ALS) is a fatal disease characterized by aberrant alternative splicing (AS). Nuclear loss and cytoplasmic accumulation of the splicing factor TDP-43 in motor neurons (MN) are hallmarks of ALS at late stages of the disease. However, it is unknown if altered AS is present before TDP-43 pathology occurs. Here, we investigate altered AS and its origins in early stages of ALS using human induced pluripotent stem cell-derived motor neurons (MNs) from sporadic and familial ALS patients. We find high levels of the RNA-binding proteins NOVA1, NOVA2, and RBFOX2 in the insoluble protein fractions and observe that AS events in ALS-associated MNs are enriched for binding sites of these proteins. Our study points to an early disrupted function of NOVA1 that drives AS changes in a complex fashion, including events caused by a consistent loss of NOVA1 function. NOVA1 exhibits increased cytoplasmic protein levels in early stage MNs without TDP-43 pathology in ALS postmortem tissue. As nuclear TDP-43 protein level depletes, NOVA1 is reduced. Potential indications for a reduction of NOVA1 also came from mice over-expressing TDP-43 lacking its nuclear localization signal and iPSC-MN stressed with puromycin. This study highlights that additional RBP-RNA perturbations in ALS occur in parallel to TDP-43. [ABSTRACT FROM AUTHOR]

Amyotrophic lateral sclerosis (ALS) is a progressive and fatal neuromuscular disorder with no cure available and limited treatment options. ALS is a highly heterogeneous disease, whereby patients present with vastly different phenotypes. Despite this heterogeneity, over 97% of patients will exhibit pathological TAR-DNA binding protein-43 (TDP-43) cytoplasmic inclusions. TDP-43 is a ubiquitously expressed RNA binding protein with the capacity to bind over 6000 RNA and DNA targets—particularly those involved in RNA, mitochondrial, and lipid metabolism. Here, we review the unique structure and function of TDP-43 and its role in affecting the aforementioned metabolic processes in ALS. Considering evidence published specifically in TDP-43-relevant in vitro, in vivo, and ex vivo models we posit that TDP-43 acts in a positive feedback loop with mRNA transcription/translation, stress granules, cytoplasmic aggregates, and mitochondrial proteins causing a relentless cycle of disease-like pathology eventuating in neuronal toxicity. Given its undeniable presence in ALS pathology, TDP-43 presents as a promising target for mechanistic disease modelling and future therapeutic investigations. [ABSTRACT FROM AUTHOR]

T-cell intracellular antigen 1 (TIA1)-related/like (TIAR/TIAL1) protein is a multifunctional RNA-binding protein (RBP) involved in regulating many aspects of gene expression, independently or in combination with its paralog TIA1. TIAR was first described in 1992 by Paul Anderson's lab in relation to the development of a cell death phenotype in immune system cells, as it possesses nucleolytic activity against cytotoxic lymphocyte target cells. Similar to TIA1, it is characterized by a subcellular nucleo-cytoplasmic localization and ubiquitous expression in the cells of different tissues of higher organisms. In this paper, we review the relevant structural and functional information available about TIAR from a triple perspective (molecular, cellular and pathophysiological), paying special attention to its expression and regulation in cellular events and processes linked to human pathophysiology. [ABSTRACT FROM AUTHOR]

RNA molecules can adopt stable secondary and tertiary structures, which are essential in mediating physical interactions with other partners such as RNA binding proteins (RBPs) and in carrying out their cellular functions. In vivo and in vitro experiments such as RNAcompete and eCLIP have revealed in vitro binding preferences of RBPs to RNA oligomers and in vivo binding sites in cells. Analysis of these binding data showed that the structure properties of the RNAs in these binding sites are important determinants of the binding events; however, it has been a challenge to incorporate the structure information into an interpretable model. Here we describe a new approach, RNANetMotif, which takes predicted secondary structure of thousands of RNA sequences bound by an RBP as input and uses a graph theory approach to recognize enriched subgraphs. These enriched subgraphs are in essence shared sequence-structure elements that are important in RBP-RNA binding. To validate our approach, we performed RNA structure modeling via coarse-grained molecular dynamics folding simulations for selected 4 RBPs, and RNA-protein docking for LIN28B. The simulation results, e.g., solvent accessibility and energetics, further support the biological relevance of the discovered network subgraphs. Author summary: RNA binding proteins (RBPs) regulate every aspect of RNA biology, including splicing, translation, transportation, and degradation. High-throughput technologies such as eCLIP have identified thousands of binding sites for a given RBP throughout the genome. It has been shown by earlier studies that, in addition to nucleotide sequences, the structure and conformation of RNAs also play important role in RBP-RNA interactions. Analogous to protein-protein interactions or protein-DNA interactions, it is likely that there exist intrinsic sequence-structure motifs common to these RNAs that underlie their binding specificity to specific RBPs. It is known that RNAs form energetically favorable secondary structures, which can be represented as graphs, with nucleotides being nodes and backbone covalent bonds and base-pairing hydrogen bonds representing edges. We hypothesize that these graphs can be mined by graph theory approaches to identify sequence-structure motifs as enriched sub-graphs. In this article, we described the details of this approach, termed RNANetMotif and associated new concepts, namely EKS (Extended K-mer Subgraph) and GraphK graph algorithm. To test the utility of our approach, we conducted 3D structure modeling of selected RNA sequences through molecular dynamics (MD) folding simulation and evaluated the significance of the discovered RNA motifs by comparing their spatial exposure with other regions on the RNA. We believe that this approach has the novelty of treating the RNA sequence as a graph and RBP binding sites as enriched subgraph, which has broader applications beyond RBP-RNA interactions. [ABSTRACT FROM AUTHOR]

RNA-binding proteins (RBPs) form complex interactions with RNA to regulate the cell's activities including cell development and disease resistance. RNA-binding proteome (RBPome) aims to profile and characterize the RNAs and proteins that interact with each other to carry out biological functions. Generally, RNA-centric and protein-centric ribonomic approaches have been successfully developed to profile RBPome in different organisms including plants and animals. Further, more and more novel methods that were firstly devised and applied in mammalians have shown great potential to unravel RBPome in plants such as RNA-interactome capture (RIC) and orthogonal organic phase separation (OOPS). Despise the development of various robust and state-of-the-art ribonomics techniques, genome-wide RBP identifications and characterizations in plants are relatively fewer than those in other eukaryotes, indicating that ribonomics techniques have great opportunities in unraveling and characterizing the RNA–protein interactions in plant species. Here, we review all the available approaches for analyzing RBPs in living organisms. Additionally, we summarize the transcriptome-wide approaches to characterize both the coding and non-coding RBPs in plants and the promising use of RBPome for booming agriculture. [ABSTRACT FROM AUTHOR]

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

Post‐translational modifications (PTMs) have emerged as key modulators of protein phase separation and have been linked to protein aggregation in neurodegenerative disorders. The major aggregating protein in amyotrophic lateral sclerosis and frontotemporal dementia, the RNA‐binding protein TAR DNA‐binding protein (TDP‐43), is hyperphosphorylated in disease on several C‐terminal serine residues, a process generally believed to promote TDP‐43 aggregation. Here, we however find that Casein kinase 1δ‐mediated TDP‐43 hyperphosphorylation or C‐terminal phosphomimetic mutations reduce TDP‐43 phase separation and aggregation, and instead render TDP‐43 condensates more liquid‐like and dynamic. Multi‐scale molecular dynamics simulations reveal reduced homotypic interactions of TDP‐43 low‐complexity domains through enhanced solvation of phosphomimetic residues. Cellular experiments show that phosphomimetic substitutions do not affect nuclear import or RNA regulatory functions of TDP‐43, but suppress accumulation of TDP‐43 in membrane‐less organelles and promote its solubility in neurons. We speculate that TDP‐43 hyperphosphorylation may be a protective cellular response to counteract TDP‐43 aggregation. Synopsis: C‐terminal hyperphosphorylation of TDP‐43, a pathological hallmark of several neurodegenerative disorders, enhances the liquidity of TDP‐43 condensates and suppresses TDP‐43 condensation and aggregation, shedding a new light on this TDP‐43 disease‐linked posttranslational modification. TDP‐43 phosphorylation by CK1δ or C‐terminal phosphomimetic mutations suppress TDP‐43 phase separation and aggregation.C‐terminal phosphomimetic mutations enhance liquidity and dynamics of TDP‐43 condensates.Suppression of phase separation is associated with loss of protein‐protein interactions in the C‐terminus and enhanced solvation of negatively charged groups.TDP‐43 bearing C‐terminal phosphomimetic mutations fails to condense into stress‐induced membrane‐less compartments and remains dispersed. [ABSTRACT FROM AUTHOR]

Loss of TDP-43 protein homeostasis and dysfunction, in particular TDP-43 aggregation, are tied to amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). TDP-43 is an RNA binding protein tightly controlling its own expression levels through a negative feedback loop, involving TDP-43 recruitment to the 3′ untranslated region of its own transcript. Aberrant TDP-43 expression caused by autoregulation defects are linked to TDP-43 pathology. Therefore, interactions between TDP-43 and its own transcript are crucial to prevent TDP-43 aggregation and loss of function. However, the mechanisms that mediate this interaction remain ill-defined. We find that a central RNA sequence in the 3′ UTR, which mediates TDP-43 autoregulation, increases the liquid properties of TDP-43 phase separation. Furthermore, binding to this RNA sequence induces TDP-43 condensation in human cell lysates, suggesting that this interaction promotes TDP-43 self-assembly into dynamic ribonucleoprotein granules. In agreement with these findings, our experiments show that TDP-43 oligomerization and phase separation, mediated by the amino and carboxy-terminal domains, respectively, are essential for TDP-43 autoregulation. According to our additional observations, CLIP34-associated phase separation and autoregulation may be efficiently controlled by phosphorylation of the N-terminal domain. Importantly, we find that specific ALS-associated TDP-43 mutations, mainly M337V, and a shortened TDP-43 isoform recently tied to motor neuron toxicity in ALS, disrupt the liquid properties of TDP-43-RNA condensates as well as autoregulatory function. In addition, we find that M337V decreases the cellular clearance of TDP-43 and other RNA binding proteins associated with ALS/FTD. These observations suggest that loss of liquid properties in M337V condensates strongly affects protein homeostasis. Together, this work provides evidence for the central role of TDP-43 oligomerization and liquid-liquid phase separation linked to RNA binding in autoregulation. These mechanisms may be impaired by TDP-43 disease variants and controlled by specific cellular signaling. [ABSTRACT FROM AUTHOR]

Due to challenges in early-stage detection, aggressive behavior, and poor response to systemic therapy, pancreatic cancer is one of the most fatal cancer types globally. The role of RNA-binding protein (RBP) transcription and translation of cancer cells has been well demonstrated, although their roles in pancreatic cancer is less well understood. In this study, we found that heterogeneous nuclear ribonucleoprotein C (hnRNPC), a RBP, is highly expressed in pancreatic ductal adenocarcinoma (PDAC) tissues and cells. In addition, we discovered that overexpression of hnRNPC in PDAC cells in vitro increased cell proliferation, migration, invasion, and metastasis. The presence of hnRNPC promoted tumorigenesis of pancreatic cells in metastatic in vivo models, which was also validated. In silico analyses revealed that hnRNPC is a strong positive regulator of IQ Motif Containing GTPase Activating Protein 3 (IQGAP3) activity. The experimental confirmation of this association revealed a direct interaction of IQGAP3 and hnRNPC to induce cell growth and invasion in PDAC cells by activating the epithelial-mesenchymal transition. In light of the findings that hnRNPC accelerates PDAC progression by interfering with IQGAP3, it appears that this technique for diagnosis and treatment of PDAC may have promise. [ABSTRACT FROM AUTHOR]

TDP-43 (also known as TARDBP) is a nuclear splicing factor functioning in pre-mRNA processing. Its C-terminal 35-kDa fragment (TDP-35) forms inclusions or aggregates in cytoplasm, and sequesters full-length TDP-43 into the inclusions through binding with RNA. We extended the research to investigate whether TDP-35 inclusions sequester other RNA-binding proteins (RBPs) and how RNA-binding specificity has a role in this sequestration process. We have characterized T-cell restricted intracellular antigen-1 (TIA1) and other RBPs that can be sequestered into the TDP-35 inclusions through specific RNA binding, and found that this sequestration leads to the dysfunction of TIA1 in maturation of target pre-mRNA. Moreover, we directly visualized the dynamic sequestration of TDP- 43 by the cytoplasmic TDP-35 inclusions by live-cell imaging. Our results demonstrate that TDP-35 sequesters some specific RBPs and this sequestration is assisted by binding with RNA in a sequence-specific manner. This study provides further evidence in supporting the hijacking hypothesis for RNA-assisted sequestration and will be beneficial to further understanding of the TDP-43 proteinopathies. [ABSTRACT FROM AUTHOR]

Precise identification of target sites of RNA-binding proteins (RBP) is important to understand their biochemical and cellular functions. A large amount of experimental data is generated by in vivo and in vitro approaches. The binding preferences determined from these platforms share similar patterns but there are discernable differences between these datasets. Computational methods trained on one dataset do not always work well on another dataset. To address this problem which resembles the classic "domain shift" in deep learning, we adopted the adversarial domain adaptation (ADDA) technique and developed a framework (RBP-ADDA) that can extract RBP binding preferences from an integration of in vivo and vitro datasets. Compared with conventional methods, ADDA has the advantage of working with two input datasets, as it trains the initial neural network for each dataset individually, projects the two datasets onto a feature space, and uses an adversarial framework to derive an optimal network that achieves an optimal discriminative predictive power. In the first step, for each RBP, we include only the in vitro data to pre-train a source network and a task predictor. Next, for the same RBP, we initiate the target network by using the source network and use adversarial domain adaptation to update the target network using both in vitro and in vivo data. These two steps help leverage the in vitro data to improve the prediction on in vivo data, which is typically challenging with a lower signal-to-noise ratio. Finally, to further take the advantage of the fused source and target data, we fine-tune the task predictor using both data. We showed that RBP-ADDA achieved better performance in modeling in vivo RBP binding data than other existing methods as judged by Pearson correlations. It also improved predictive performance on in vitro datasets. We further applied augmentation operations on RBPs with less in vivo data to expand the input data and showed that it can improve prediction performances. Lastly, we explored the predictive interpretability of RBP-ADDA, where we quantified the contribution of the input features by Integrated Gradients and identified nucleotide positions that are important for RBP recognition. Author summary: RNA binding proteins (RBPs) regulate every aspect of RNA biology, including splicing, translation, transportation, and degradation. To fully understand the function of RBPs and the mechanism of RBP-RNA recognition, an accurate knowledge of the RBP-RNA binding preferences is essential. There are in vitro and in vivo experimental approaches such as RNAcompete or eCLIP that can determine RBP-RNA binding preferences in a high-through manner. However, because of the intrinsic differences between in vitro and in vivo experimental conditions, the binding preferences determined from in vitro and in vivo do not always agree with each other. To solve this problem and best utilize both types of data, we have adopted the adversarial domain adaptation (ADDA) technique into the analysis of RNA binding proteins and developed a framework (RBP-ADDA) that can extract RBP binding preferences from an integration of in vivo and vitro datasets. We showed that RBP-ADDA outperforms other contemporary methods in predicting RBA binding preferences on both in vivo and in vitro data. To the best of our knowledge, this is the first time that adversarial domain adaptation has been applied to the computational study of gene regulations. [ABSTRACT FROM AUTHOR]

The process of alternative polyadenylation (APA) generates multiple 3' UTR isoforms for a given locus, which can alter regulatory capacity and on occasion change coding potential. APA was initially characterized for a few genes, but in the past decade, has been found to be the rule for metazoan genes. While numerous differences in APA profiles have been catalogued across genetic conditions, perturbations, and diseases, our knowledge of APA mechanisms and biology is far from complete. In this review, we highlight recent findings regarding the role of the conserved ELAV/Hu family of RNA binding proteins (RBPs) in generating the broad landscape of lengthened 3' UTRs that is characteristic of neurons. We relate this to their established roles in alternative splicing, and summarize ongoing directions that will further elucidate the molecular strategies for neural APA, the in vivo functions of ELAV/Hu RBPs, and the phenotypic consequences of these regulatory paradigms in neurons. [ABSTRACT FROM AUTHOR]

In the messenger RNA (mRNA) maturation process, the 3′‐end of pre‐mRNA is cleaved and a poly(A) sequence is added, this is an important determinant of mRNA stability and its cellular functions. More than 60%–70% of human genes have three or more polyadenylation (APA) sites and can be cleaved at different sites, generating mRNA transcripts of varying lengths. This phenomenon is termed as alternative cleavage and polyadenylation (APA) and it plays role in key biological processes like gene regulation, cell proliferation, senescence, and also in various human diseases. Loss of regulatory microRNA binding sites and interactions with RNA‐binding proteins leading to APA are largely investigated in human diseases. However, the functions of the core APA machinery and related factors during disease conditions remain largely unknown. In this review, we discuss the roles of polyadenylation machinery in relation to brain disease, cardiac failure, pulmonary fibrosis, cancer, infectious conditions, and other human diseases. Collectively, we believe this review will be a useful avenue for understanding the emerging role of APA in the pathobiology of various human diseases. [ABSTRACT FROM AUTHOR]

Background: Protein-RNA interactions play key roles in many processes regulating gene expression. To understand the underlying binding preference, ultraviolet cross-linking and immunoprecipitation (CLIP)-based methods have been used to identify the binding sites for hundreds of RNA-binding proteins (RBPs) in vivo. Using these large-scale experimental data to infer RNA binding preference and predict missing binding sites has become a great challenge. Some existing deep-learning models have demonstrated high prediction accuracy for individual RBPs. However, it remains difficult to avoid significant bias due to the experimental protocol. The DeepRiPe method was recently developed to solve this problem via introducing multi-task or multi-label learning into this field. However, this method has not reached an ideal level of prediction power due to the weak neural network architecture. Results: Compared to the DeepRiPe approach, our Multi-resBind method demonstrated substantial improvements using the same large-scale PAR-CLIP dataset with respect to an increase in the area under the receiver operating characteristic curve and average precision. We conducted extensive experiments to evaluate the impact of various types of input data on the final prediction accuracy. The same approach was used to evaluate the effect of loss functions. Finally, a modified integrated gradient was employed to generate attribution maps. The patterns disentangled from relative contributions according to context offer biological insights into the underlying mechanism of protein-RNA interactions. Conclusions: Here, we propose Multi-resBind as a new multi-label deep-learning approach to infer protein-RNA binding preferences and predict novel interactions. The results clearly demonstrate that Multi-resBind is a promising tool to predict unknown binding sites in vivo and gain biology insights into why the neural network makes a given prediction. [ABSTRACT FROM AUTHOR]

Cytoplasmic aggregation of Tar-DNA/RNA binding protein 43 (TDP-43) occurs in 97 percent of amyotrophic lateral sclerosis (ALS), ~40% of frontotemporal dementia (FTD) and in many cases of Alzheimer's disease (AD). Cytoplasmic TDP-43 inclusions are seen in both sporadic and familial forms of these disorders, including those cases that are caused by repeat expansion mutations in the C9orf72 gene. To identify downstream mediators of TDP-43 toxicity, we expressed human TDP-43 in a subset of Drosophila motor neurons. Such expression causes age-dependent deficits in negative geotaxis behavior. Using this behavioral readout of locomotion, we conducted an shRNA suppressor screen and identified 32 transcripts whose knockdown was sufficient to ameliorate the neurological phenotype. The majority of these suppressors also substantially suppressed the negative effects on lifespan seen with glial TDP-43 expression. In addition to identification of a number of genes whose roles in neurodegeneration were not previously known, our screen also yielded genes involved in chromatin regulation and nuclear/import export- pathways that were previously identified in the context of cell based or neurodevelopmental suppressor screens. A notable example is SF2, a conserved orthologue of mammalian SRSF1, an RNA binding protein with roles in splicing and nuclear export. Our identification SF2/SRSF1 as a potent suppressor of both neuronal and glial TDP-43 toxicity also provides a convergence with C9orf72 expansion repeat mediated neurodegeneration, where this gene also acts as a downstream mediator. Author summary: Loss of nuclear function of TDP-43 and its mislocalization into cytoplasmic inclusions are central features to a suite of neurodegenerative disorders. We screened 2700 Drosophila genes to identify downstream mediators that suppress an age-dependent motor dysfunction phenotype when they are knocked down by RNA interference. We identified both previously implicated pathways and several novel genes whose knock down is sufficient to dramatically and robustly rescue TDP-43 toxicity both in neuronal and glial contexts. Notably, we demonstrate that SF2/SRSF1, which was previously reported as a suppressor of C9orf72 hexanucleotide expansion repeat toxicity, also is a potent suppressor of TDP-43 mediated neurodegeneration. [ABSTRACT FROM AUTHOR]

Heterogeneous nuclear ribonucleoproteins (HnRNPs) are a group of ubiquitously expressed RNA-binding proteins implicated in the regulation of all aspects of nucleic acid metabolism. HnRNP K is a member of this highly versatile hnRNP family. Pathological redistribution of hnRNP K to the cytoplasm has been linked to the pathogenesis of several malignancies but, until now, has been underexplored in the context of neurodegenerative disease. Here we show hnRNP K mislocalisation in pyramidal neurons of the frontal cortex to be a novel neuropathological feature that is associated with both frontotemporal lobar degeneration and ageing. HnRNP K mislocalisation is mutually exclusive to TDP-43 and tau pathological inclusions in neurons and was not observed to colocalise with mitochondrial, autophagosomal or stress granule markers. De-repression of cryptic exons in RNA targets following TDP-43 nuclear depletion is an emerging mechanism of potential neurotoxicity in frontotemporal lobar degeneration and the mechanistically overlapping disorder amyotrophic lateral sclerosis. We silenced hnRNP K in neuronal cells to identify the transcriptomic consequences of hnRNP K nuclear depletion. Intriguingly, by performing RNA-seq analysis we find that depletion of hnRNP K induces 101 novel cryptic exon events. We validated cryptic exon inclusion in an SH-SY5Y hnRNP K knockdown and in FTLD brain exhibiting hnRNP K nuclear depletion. We, therefore, present evidence for hnRNP K mislocalisation to be associated with FTLD and for this to induce widespread changes in splicing. [ABSTRACT FROM AUTHOR]

In this review, the fundamental basis of machine learning (ML) and data mining (DM) are summarized together with the techniques for distilling knowledge from state-of-theart omics experiments. This includes an introduction to the basic mathematical principles of unsupervised/supervised learning methods, dimensionality reduction techniques, deep neural networks architectures and the applications of these in bioinformatics. Several case studies under evaluation mainly involve next generation sequencing (NGS) experiments, like deciphering gene expression from total and single cell (scRNAseq) analysis; for the latter, a description of all recent artificial intelligence (AI) methods for the investigation of cell sub-types, biomarkers and imputation techniques are described. Other areas of interest where various ML schemes have been investigated are for providing information regarding transcription factors (TF) binding sites, chromatin organization patterns and RNA binding proteins (RBPs), while analyses on RNA sequence and structure as well as 3D dimensional protein structure predictions with the use of ML are described. Furthermore, we summarize the recent methods of using ML in clinical oncology, when taking into consideration the current omics data with pharmacogenomics to determine personalized treatments. With this review we wish to provide the scientific community with a thorough investigation of main novel ML applications which take into consideration the latest achievements in genomics, thus, unraveling the fundamental mechanisms of biology towards the understanding and cure of diseases. [ABSTRACT FROM AUTHOR]

The maturation of immature B cells and the survival of mature B cells is stringently controlled to maintain a diverse repertoire of antibody specificities while avoiding self‐reactivity. At the molecular level this is regulated by signaling from membrane Ig and the BAFF‐receptor that sustain a pro‐survival program of gene expression. Whether and how posttranscriptional mechanisms contribute to B cell maturation and survival remains poorly understood. Here, we show that the polypyrimidine tract binding proteins (PTBP) PTBP1 and PTBP3 bind to a large and overlapping set of transcripts in B cells. Both PTBP1 and PTBP3 bind to introns and exons where they are predicted to regulate alternative splicing. Moreover, they also show high‐density of binding to 3' untranslated regions suggesting they influence the transcriptome in diverse ways. We show that PTBP1 and PTBP3 are required in B cells beyond the immature cell stage to sustain transitional B cells and the B1, marginal zone and follicular B cell lineages. Therefore, PTBP1 and PTBP3 promote the maturation of quiescent B cells by regulating gene expression at the posttranscriptional level. [ABSTRACT FROM AUTHOR]

STAU2 is a double-stranded RNA-binding protein enriched in the nervous system. During asymmetric divisions in the developing mouse cortex, STAU2 preferentially distributes into the intermediate progenitor cell (IPC), delivering RNA molecules that can impact IPC behavior. Corticogenesis occurs on a precise time schedule, raising the hypothesis that the cargo STAU2 delivers into IPCs changes over time. To test this, we combine RNA-immunoprecipitation with sequencing (RIP-seq) over four stages of mouse cortical development, generating a comprehensive cargo profile for STAU2. A subset of the cargo was 'stable', present at all stages, and involved in chromosome organization, macromolecule localization, translation and DNA repair. Another subset was 'dynamic', changing with cortical stage, and involved in neurogenesis, cell projection organization, neurite outgrowth, and included cortical layer markers. Notably, the dynamic STAU2 cargo included determinants of IPC versus neuronal fates and genes contributing to abnormal corticogenesis. Knockdown of one STAU2 target, Taf13, previously linked to microcephaly and impaired myelination, reduced oligodendrogenesis in vitro. We conclude that STAU2 contributes to the timing of corticogenesis by binding and delivering complex and temporally regulated RNA cargo into IPCs. [ABSTRACT FROM AUTHOR]

Amyotrophic lateral sclerosis (ALS) is a progressive and fatal neurodegenerative disease that affects upper and lower motor neurons. Familial ALS accounts for a small subset of cases (<10–15%) and is caused by dominant mutations in one of more than 10 known genes. Multiple genes have been causally or pathologically linked to both ALS and frontotemporal dementia (FTD). Many of these genes encode RNA-binding proteins, so the role of dysregulated RNA metabolism in neurodegeneration is being actively investigated. In addition to defects in RNA metabolism, recent studies provide emerging evidence into how RNA itself can contribute to the degeneration of both motor and cortical neurons. In this review, we discuss the roles of altered RNA metabolism and RNA-mediated toxicity in the context of TARDBP, FUS , and C9ORF72 mutations. Specifically, we focus on recent studies that describe toxic RNA as the potential initiator of disease, disease-associated defects in specific RNA metabolism pathways, as well as how RNA-based approaches can be used as potential therapies. Altogether, we highlight the importance of RNA-based investigations into the molecular progression of ALS, as well as the need for RNA-dependent structural studies of disease-linked RNA-binding proteins to identify clear therapeutic targets. [ABSTRACT FROM AUTHOR]

Deep neural networks have demonstrated improved performance at predicting the sequence specificities of DNA- and RNA-binding proteins compared to previous methods that rely on k-mers and position weight matrices. To gain insights into why a DNN makes a given prediction, model interpretability methods, such as attribution methods, can be employed to identify motif-like representations along a given sequence. Because explanations are given on an individual sequence basis and can vary substantially across sequences, deducing generalizable trends across the dataset and quantifying their effect size remains a challenge. Here we introduce global importance analysis (GIA), a model interpretability method that quantifies the population-level effect size that putative patterns have on model predictions. GIA provides an avenue to quantitatively test hypotheses of putative patterns and their interactions with other patterns, as well as map out specific functions the network has learned. As a case study, we demonstrate the utility of GIA on the computational task of predicting RNA-protein interactions from sequence. We first introduce a convolutional network, we call ResidualBind, and benchmark its performance against previous methods on RNAcompete data. Using GIA, we then demonstrate that in addition to sequence motifs, ResidualBind learns a model that considers the number of motifs, their spacing, and sequence context, such as RNA secondary structure and GC-bias. Author summary: Although deep neural networks are becoming widely applied in genomics, it remains unclear why they make a given prediction. For model interpretability, attribution methods reveal the independent importance of single nucleotide variants in a given sequence on model predictions. While the resultant attribution maps can help to identify representations of motifs, it remains challenging to identify generalizable patterns across the dataset and to quantify their effect size on model predictions. Here, we introduce an interpretability method called global importance analysis (GIA) to quantify the effect size that putative patterns have on model predictions across a population of sequences. GIA provides a natural follow up to current interpretability methods to quantitatively test hypotheses of putative patterns (and their interactions with other patterns). As a case study, we demonstrate how it can be used for the computational task of predicting RNA-protein interactions and show that deep learning models can learn not only sequence motifs, but also the number of motifs, their spacing, and sequence context, such as RNA secondary structure and GC-bias. [ABSTRACT FROM AUTHOR]

Pulmonary arterial hypertension (PAH) refers to a set of heterogeneous vascular diseases defined by elevation of pulmonary arterial pressure (PAP) and pulmonary vascular resistance (PVR), leading to right ventricular (RV) remodeling and often death. Early increases in pulmonary artery stiffness in PAH drive pathogenic alterations of pulmonary arterial endothelial cells (PAECs), leading to vascular remodeling. Dysregulation of microRNAs can drive PAEC dysfunction. However, the role of vascular stiffness in regulating pathogenic microRNAs in PAH is incompletely understood. Here, we demonstrated that extracellular matrix (ECM) stiffening downregulated miR-7 levels in PAECs. The RNA-binding protein quaking (QKI) has been implicated in the biogenesis of miR-7. Correspondingly, we found that ECM stiffness upregulated QKI, and QKI knockdown led to increased miR-7. Downstream of the QKI-miR-7 axis, the serine and arginine-rich splicing factor 1 (SRSF1) was identified as a direct target of miR-7. Correspondingly, SRSF1 was reciprocally upregulated in PAECs exposed to stiff ECM and was negatively correlated with miR-7. Decreased miR-7 and increased QKI and SRSF1 were observed in lungs from patients with PAH and PAH rats exposed to SU5416/hypoxia. Lastly, miR-7 upregulation inhibited human PAEC migration, whereas forced SRSF1 expression reversed this phenotype, proving that miR-7 depended upon SRSF1 to control migration. In aggregate, these results define the QKI-miR-7-SRSF1 axis as a mechanosensitive mechanism linking pulmonary arterial vascular stiffness to pathogenic endothelial function. These findings emphasize implications relevant to PAH and suggest the potential benefit of developing therapies that target this miRNA-dependent axis in PAH. [ABSTRACT FROM AUTHOR]

RNA-binding proteins are customarily regarded as important facilitators of gene expression. In recent years, RNA–protein interactions have also emerged as a pervasive force in the regulation of homeostasis. The compendium of proteins with provable RNA-binding function has swelled from the hundreds to the thousands astride the partnership of mass spectrometry-based proteomics and RNA sequencing. At the foundation of these advances is the adaptation of RNA-centric capture methods that can extract bound protein that has been cross-linked in its native environment. These methods reveal snapshots in time displaying an extensive network of regulation and a wealth of data that can be used for both the discovery of RNA-binding function and the molecular interfaces at which these interactions occur. This review will focus on the impact of these developments on our broader perception of post-transcriptional regulation, and how the technical features of current capture methods, as applied in mammalian systems, create a challenging medium for interpretation by systems biologists and target validation by experimental researchers. [ABSTRACT FROM AUTHOR]

Background: Circular RNAs (circRNAs) are widely expressed in cells and tissues and are involved in biological processes and human diseases. Recent studies have demonstrated that circRNAs can interact with RNA-binding proteins (RBPs), which is considered an important aspect for investigating the function of circRNAs. Results: In this study, we design a slight variant of the capsule network, called circRB, to identify the sequence specificities of circRNAs binding to RBPs. In this model, the sequence features of circRNAs are extracted by convolution operations, and then, two dynamic routing algorithms in a capsule network are employed to discriminate between different binding sites by analysing the convolution features of binding sites. The experimental results show that the circRB method outperforms the existing computational methods. Afterwards, the trained models are applied to detect the sequence motifs on the seven circRNA-RBP bound sequence datasets and matched to known human RNA motifs. Some motifs on circular RNAs overlap with those on linear RNAs. Finally, we also predict binding sites on the reported full-length sequences of circRNAs interacting with RBPs, attempting to assist current studies. We hope that our model will contribute to better understanding the mechanisms of the interactions between RBPs and circRNAs. Conclusion: In view of the poor studies about the sequence specificities of circRNA-binding proteins, we designed a classification framework called circRB based on the capsule network. The results show that the circRB method is an effective method, and it achieves higher prediction accuracy than other methods. [ABSTRACT FROM AUTHOR]