Circular RNAs: Characterization, cellular roles, and applications.

Most circular RNAs are produced from the back-splicing of exons of precursor mRNAs. Recent technological advances have in part overcome problems with their circular conformation and sequence overlap with linear cognate mRNAs, allowing a better understanding of their cellular roles. Depending on their localization and specific interactions with DNA, RNA, and proteins, circular RNAs can modulate transcription and splicing, regulate stability and translation of cytoplasmic mRNAs, interfere with signaling pathways, and serve as templates for translation in different biological and pathophysiological contexts. Emerging applications of RNA circles to interfere with cellular processes, modulate immune responses, and direct translation into proteins shed new light on biomedical research. In this review, we discuss approaches used in circular RNA studies and the current understanding of their regulatory roles and potential applications.

In vivo structural characterization of the SARS-CoV-2 RNA genome identifies host proteins vulnerable to repurposed drugs.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the ongoing coronavirus disease 2019 (COVID-19) pandemic. Understanding of the RNA virus and its interactions with host proteins could improve therapeutic interventions for COVID-19. By using icSHAPE, we determined the structural landscape of SARS-CoV-2 RNA in infected human cells and from refolded RNAs, as well as the regulatory untranslated regions of SARS-CoV-2 and six other coronaviruses. We validated several structural elements predicted in silico and discovered structural features that affect the translation and abundance of subgenomic viral RNAs in cells. The structural data informed a deep-learning tool to predict 42 host proteins that bind to SARS-CoV-2 RNA. Strikingly, antisense oligonucleotides targeting the structural elements and FDA-approved drugs inhibiting the SARS-CoV-2 RNA binding proteins dramatically reduced SARS-CoV-2 infection in cells derived from human liver and lung tumors. Our findings thus shed light on coronavirus and reveal multiple candidate therapeutics for COVID-19 treatment.

Pervasive Chromatin-RNA Binding Protein Interactions Enable RNA-Based Regulation of Transcription.

Increasing evidence suggests that transcriptional control and chromatin activities at large involve regulatory RNAs, which likely enlist specific RNA-binding proteins (RBPs). Although multiple RBPs have been implicated in transcription control, it has remained unclear how extensively RBPs directly act on chromatin. We embarked on a large-scale RBP ChIP-seq analysis, revealing widespread RBP presence in active chromatin regions in the human genome. Like transcription factors (TFs), RBPs also show strong preference for hotspots in the genome, particularly gene promoters, where their association is frequently linked to transcriptional output. Unsupervised clustering reveals extensive co-association between TFs and RBPs, as exemplified by YY1, a known RNA-dependent TF, and RBM25, an RBP involved in splicing regulation. Remarkably, RBM25 depletion attenuates all YY1-dependent activities, including chromatin binding, DNA looping, and transcription. We propose that various RBPs may enhance network interaction through harnessing regulatory RNAs to control transcription.

The p53-induced RNA-binding protein ZMAT3 is a splicing regulator that inhibits the splicing of oncogenic CD44 variants in colorectal carcinoma.

p53 is an intensely studied tumor-suppressive transcription factor. Recent studies suggest that the RNA-binding protein (RBP) ZMAT3 is important in mediating the tumor-suppressive effects of p53. Here, we globally identify ZMAT3-regulated RNAs and their binding sites at nucleotide resolution in intact colorectal cancer (CRC) cells. ZMAT3 binds to thousands of mRNA precursors, mainly at intronic uridine-rich sequences and affects their splicing. The strongest alternatively spliced ZMAT3 target was CD44, a cell adhesion gene and stem cell marker that controls tumorigenesis. Silencing ZMAT3 increased inclusion of CD44 variant exons, resulting in significant up-regulation of oncogenic CD44 isoforms (CD44v) and increased CRC cell growth that was rescued by concurrent knockdown of CD44v Silencing p53 phenocopied the loss of ZMAT3 with respect to CD44 alternative splicing, suggesting that ZMAT3-mediated regulation of CD44 splicing is vital for p53 function. Collectively, our findings uncover a p53-ZMAT3-CD44 axis in growth suppression in CRC cells.

Overlapping Activities of ELAV/Hu Family RNA Binding Proteins Specify the Extended Neuronal 3' UTR Landscape in Drosophila.

The tissue-specific deployment of highly extended neural 3' UTR isoforms, generated by alternative polyadenylation (APA), is a broad and conserved feature of metazoan genomes. However, the factors and mechanisms that control neural APA isoforms are not well understood. Here, we show that three ELAV/Hu RNA binding proteins (Elav, Rbp9, and Fne) have similar capacities to induce a lengthened 3' UTR landscape in an ectopic setting. These factors promote accumulation of chromatin-associated, 3' UTR-extended, nascent transcripts, through inhibition of proximal polyadenylation site (PAS) usage. Notably, Elav represses an unannotated splice isoform of fne, switching the normally cytoplasmic Fne toward the nucleus in elav mutants. We use genomic profiling to reveal strong and broad loss of neural APA in elav/fne double mutant CNS, the first genetic background to largely abrogate this distinct APA signature. Overall, we demonstrate how regulatory interplay and functionally overlapping activities of neural ELAV/Hu RBPs drives the neural APA landscape.

Zmat3 Is a Key Splicing Regulator in the p53 Tumor Suppression Program.

Although TP53 is the most commonly mutated gene in human cancers, the p53-dependent transcriptional programs mediating tumor suppression remain incompletely understood. Here, to uncover critical components downstream of p53 in tumor suppression, we perform unbiased RNAi and CRISPR-Cas9-based genetic screens in vivo. These screens converge upon the p53-inducible gene Zmat3, encoding an RNA-binding protein, and we demonstrate that ZMAT3 is an important tumor suppressor downstream of p53 in mouse KrasG12D-driven lung and liver cancers and human carcinomas. Integrative analysis of the ZMAT3 RNA-binding landscape and transcriptomic profiling reveals that ZMAT3 directly modulates exon inclusion in transcripts encoding proteins of diverse functions, including the p53 inhibitors MDM4 and MDM2, splicing regulators, and components of varied cellular processes. Interestingly, these exons are enriched in NMD signals, and, accordingly, ZMAT3 broadly affects target transcript stability. Collectively, these studies reveal ZMAT3 as a novel RNA-splicing and homeostasis regulator and a key component of p53-mediated tumor suppression.

The impact of IDR phosphorylation on the RNA binding profiles of proteins.

Due to their capacity to mediate repetitive protein interactions, intrinsically disordered regions (IDRs) are crucial for the formation of various types of protein-RNA complexes. The functions of IDRs are strongly modulated by post-translational modifications (PTMs). Phosphorylation is the most common and well-studied modification of IDRs, which can alter homomeric or heteromeric interactions of proteins and impact their ability to phase separate. Moreover, phosphorylation can influence the RNA-binding properties of proteins, and recent studies demonstrated its selective impact on the global profiles of protein-RNA binding and regulation. These findings highlight the need for further integrative approaches to understand how signalling remodels protein-RNA networks in cells.

Dosage sensitivity to Pumilio1 variants in the mouse brain reflects distinct molecular mechanisms.

Different mutations in the RNA-binding protein Pumilio1 (PUM1) cause divergent phenotypes whose severity tracks with dosage: a mutation that reduces PUM1 levels by 25% causes late-onset ataxia, whereas haploinsufficiency causes developmental delay and seizures. Yet PUM1 targets are derepressed to equal degrees in both cases, and the more severe mutation does not hinder PUM1's RNA-binding ability. We therefore considered the possibility that the severe mutation might disrupt PUM1 interactions, and identified PUM1 interactors in the murine brain. We find that mild PUM1 loss derepresses PUM1-specific targets, but the severe mutation disrupts interactions with several RNA-binding proteins and the regulation of their targets. In patient-derived cell lines, restoring PUM1 levels restores these interactors and their targets to normal levels. Our results demonstrate that dosage sensitivity does not always signify a linear relationship with protein abundance but can involve distinct mechanisms. We propose that to understand the functions of RNA-binding proteins in a physiological context will require studying their interactions as well as their targets.

RNA Targets Ribogenesis Factor WDR43 to Chromatin for Transcription and Pluripotency Control.

Transcription regulation underlies stem cell function and development. Here, we elucidate an unexpected role of an essential ribogenesis factor, WDR43, as a chromatin-associated RNA-binding protein (RBP) and release factor in modulating the polymerase (Pol) II activity for pluripotency regulation. WDR43 binds prominently to promoter-associated noncoding/nascent RNAs, occupies thousands of gene promoters and enhancers, and interacts with the Pol II machinery in embryonic stem cells (ESCs). Nascent transcripts and transcription recruit WDR43 to active promoters, where WDR43 facilitates releases of the elongation factor P-TEFb and paused Pol II. Knockdown of WDR43 causes genome-wide defects in Pol II release and pluripotency-associated gene expression. Importantly, auxin-mediated rapid degradation of WDR43 drastically reduces Pol II activity, precluding indirect consequences. These results reveal an RNA-mediated recruitment and feedforward regulation on transcription and demonstrate an unforeseen role of an RBP in promoting Pol II elongation and coordinating high-level transcription and translation in ESC pluripotency.

The KDM5A/RBP2 histone demethylase represses NOTCH signaling to sustain neuroendocrine differentiation and promote small cell lung cancer tumorigenesis.

More than 90% of small cell lung cancers (SCLCs) harbor loss-of-function mutations in the tumor suppressor gene RB1 The canonical function of the RB1 gene product, pRB, is to repress the E2F transcription factor family, but pRB also functions to regulate cellular differentiation in part through its binding to the histone demethylase KDM5A (also known as RBP2 or JARID1A). We show that KDM5A promotes SCLC proliferation and SCLC's neuroendocrine differentiation phenotype in part by sustaining expression of the neuroendocrine transcription factor ASCL1. Mechanistically, we found that KDM5A sustains ASCL1 levels and neuroendocrine differentiation by repressing NOTCH2 and NOTCH target genes. To test the role of KDM5A in SCLC tumorigenesis in vivo, we developed a CRISPR/Cas9-based mouse model of SCLC by delivering an adenovirus (or an adeno-associated virus [AAV]) that expresses Cre recombinase and sgRNAs targeting Rb1, Tp53, and Rbl2 into the lungs of Lox-Stop-Lox Cas9 mice. Coinclusion of a KDM5A sgRNA decreased SCLC tumorigenesis and metastasis, and the SCLCs that formed despite the absence of KDM5A had higher NOTCH activity compared to KDM5A+/+ SCLCs. This work establishes a role for KDM5A in SCLC tumorigenesis and suggests that KDM5 inhibitors should be explored as treatments for SCLC.

Post-translational modifications on RNA-binding proteins: accelerators, brakes, or passengers in neurodegeneration?

RNA-binding proteins (RBPs) are critical players in RNA expression and metabolism, thus, the proper regulation of this class of proteins is critical for cellular health. Regulation of RBPs often occurs through post-translational modifications (PTMs), which allow the cell to quickly and efficiently respond to cellular and environmental stimuli. PTMs have recently emerged as important regulators of RBPs implicated in neurodegenerative disorders, in particular amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Here, we summarize how disease-associated PTMs influence the biophysical properties, molecular interactions, subcellular localization, and function of ALS/FTD-linked RBPs, such as FUS and TDP-43. We will discuss how PTMs are believed to play pathological, protective, or ambiguous roles in these neurodegenerative disorders.

Eif4enif1 haploinsufficiency disrupts oocyte mitochondrial dynamics and leads to subfertility.

Infertility affects couples worldwide. Premature ovarian insufficiency (POI) refers to loss of ovarian function before 40 years of age and is a contributing factor to infertility. Several case studies have reported dominant-inherited POI symptoms in families with heterozygous EIF4ENIF1 (4E-T) mutations. However, the effects of EIF4ENIF1 haploinsufficiency have rarely been studied in animal models to reveal the underlying molecular changes related to infertility. Here, we demonstrate that Eif4enif1 haploinsufficiency causes mouse subfertility, impairs oocyte maturation and partially arrests early embryonic development. Using dual-omic sequencing, we observed that Eif4enif1 haploinsufficiency significantly altered both transcriptome and translatome in mouse oocytes, by which we further revealed oocyte mitochondrial hyperfusion and mitochondria-associated ribonucleoprotein domain distribution alteration in Eif4enif1-deficient oocytes. This study provides new insights into the molecular mechanisms underlying clinical fertility failure and new avenues to pursue new therapeutic targets to address infertility.

Improved prediction of DNA and RNA binding proteins with deep learning models.

Nucleic acid-binding proteins (NABPs), including DNA-binding proteins (DBPs) and RNA-binding proteins (RBPs), play important roles in essential biological processes. To facilitate functional annotation and accurate prediction of different types of NABPs, many machine learning-based computational approaches have been developed. However, the datasets used for training and testing as well as the prediction scopes in these studies have limited their applications. In this paper, we developed new strategies to overcome these limitations by generating more accurate and robust datasets and developing deep learning-based methods including both hierarchical and multi-class approaches to predict the types of NABPs for any given protein. The deep learning models employ two layers of convolutional neural network and one layer of long short-term memory. Our approaches outperform existing DBP and RBP predictors with a balanced prediction between DBPs and RBPs, and are more practically useful in identifying novel NABPs. The multi-class approach greatly improves the prediction accuracy of DBPs and RBPs, especially for the DBPs with ~12% improvement. Moreover, we explored the prediction accuracy of single-stranded DNA binding proteins and their effect on the overall prediction accuracy of NABP predictions.

RNA circuits and RNA-binding proteins in T cells.

RNA is integral to the regulatory circuits that control cell identity and behavior. Cis-regulatory elements in mRNAs interact with RNA-binding proteins (RBPs) that can alter RNA sequence, stability, and translation into protein. Similarly, long noncoding RNAs (lncRNAs) scaffold ribonucleoprotein complexes that mediate transcriptional and post-transcriptional regulation of gene expression. Indeed, cell programming is fundamental to multicellular life and, in this era of cellular therapies, it is of particular interest in T cells. Here, we review key concepts and recent advances in our understanding of the RNA circuits and RBPs that govern mammalian T cell differentiation and immune function.

Adipocyte HSL is required for maintaining circulating vitamin A and RBP4 levels during fasting.

Vitamin A (retinol) is distributed via the blood bound to its specific carrier protein, retinol-binding protein 4 (RBP4). Retinol-loaded RBP4 is secreted into the circulation exclusively from hepatocytes, thereby mobilizing hepatic retinoid stores that represent the major vitamin A reserves in the body. The relevance of extrahepatic retinoid stores for circulating retinol and RBP4 levels that are usually kept within narrow physiological limits is unknown. Here, we show that fasting affects retinoid mobilization in a tissue-specific manner, and that hormone-sensitive lipase (HSL) in adipose tissue is required to maintain serum concentrations of retinol and RBP4 during fasting in mice. We found that extracellular retinol-free apo-RBP4 induces retinol release by adipocytes in an HSL-dependent manner. Consistently, global or adipocyte-specific HSL deficiency leads to an accumulation of retinoids in adipose tissue and a drop of serum retinol and RBP4 during fasting, which affects retinoid-responsive gene expression in eye and kidney and lowers renal retinoid content. These findings establish a novel crosstalk between liver and adipose tissue retinoid stores for the maintenance of systemic vitamin A homeostasis during fasting.

Positioning of pyrimidine motifs around cassette exons defines their PTB-dependent splicing in Arabidopsis.

Alternative splicing (AS) is a complex process that generates transcript variants from a single pre-mRNA and is involved in numerous biological functions. Many RNA-binding proteins are known to regulate AS; however, little is known about the underlying mechanisms, especially outside the mammalian clade. Here, we show that polypyrimidine tract binding proteins (PTBs) from Arabidopsis thaliana regulate AS of cassette exons via pyrimidine (Py)-rich motifs close to the alternative splice sites. Mutational studies on three PTB-dependent cassette exon events revealed that only some of the Py motifs in this region are critical for AS. Moreover, in vitro binding of PTBs did not reflect a motif's impact on AS in vivo. Our mutational studies and bioinformatic investigation of all known PTB-regulated cassette exons from A. thaliana and human suggested that the binding position of PTBs relative to a cassette exon defines whether its inclusion or skipping is induced. Accordingly, exon skipping is associated with a higher frequency of Py stretches within the cassette exon, and in human also upstream of it, whereas exon inclusion is characterized by increased Py motif occurrence downstream of said exon. Enrichment of Py motifs downstream of PTB-activated 5' splice sites is also seen for PTB-dependent intron removal and alternative 5' splice site events from A. thaliana, suggesting this is a common step of exon definition. In conclusion, the position-dependent AS regulatory mechanism by PTB homologs has been conserved during the separate evolution of plants and mammals, while other critical features, in particular intron length, have considerably changed.

Tissue Usage Preference and Intrinsically Disordered Region Remodeling of Alternative Splicing Derived Proteoforms in the Heart.

A computational analysis of mass spectrometry data was performed to uncover alternative splicing derived protein variants across chambers of the human heart. Evidence for 216 non-canonical isoforms was apparent in the atrium and the ventricle, including 52 isoforms not documented on SwissProt and recovered using an RNA sequencing derived database. Among non-canonical isoforms, 29 show signs of regulation based on statistically significant preferences in tissue usage, including a ventricular enriched protein isoform of tensin-1 (TNS1) and an atrium-enriched PDZ and LIM Domain 3 (PDLIM3) isoform 2 (PDLIM3-2/ALP-H). Examined variant regions that differ between alternative and canonical isoforms are highly enriched with intrinsically disordered regions. Moreover, over two-thirds of such regions are predicted to function in protein binding and RNA binding. The analysis here lends further credence to the notion that alternative splicing diversifies the proteome by rewiring intrinsically disordered regions, which are increasingly recognized to play important roles in the generation of biological function from protein sequences.

The role of CELF family in neurodevelopment and neurodevelopmental disorders.

RNA-binding proteins (RBPs) bind to RNAs and are crucial for regulating RNA splicing, stability, translation, and transport. Among these proteins, the CUGBP Elav-like family (CELF) is a highly conserved group crucial for posttranscriptional regulation by binding to CUG repeats. Comprising CELF1-6, this family exhibits diverse expression patterns and functions. Dysregulation of CELF has been implicated in various neural disorders, encompassing both neurodegenerative and neurodevelopmental conditions, such as Alzheimer's disease and autism. This article aims to provide a comprehensive summary of the CELF family's role in neurodevelopment and neurodevelopmental disorders. Understanding CELF's mechanisms may offer clues for potential therapeutic strategies by regulating their targets in neurodevelopmental disorders.

HCRNet: high-throughput circRNA-binding event identification from CLIP-seq data using deep temporal convolutional network.

Identifying genome-wide binding events between circular RNAs (circRNAs) and RNA-binding proteins (RBPs) can greatly facilitate our understanding of functional mechanisms within circRNAs. Thanks to the development of cross-linked immunoprecipitation sequencing technology, large amounts of genome-wide circRNA binding event data have accumulated, providing opportunities for designing high-performance computational models to discriminate RBP interaction sites and thus to interpret the biological significance of circRNAs. Unfortunately, there are still no computational models sufficiently flexible to accommodate circRNAs from different data scales and with various degrees of feature representation. Here, we present HCRNet, a novel end-to-end framework for identification of circRNA-RBP binding events. To capture the hierarchical relationships, the multi-source biological information is fused to represent circRNAs, including various natural language sequence features. Furthermore, a deep temporal convolutional network incorporating global expectation pooling was developed to exploit the latent nucleotide dependencies in an exhaustive manner. We benchmarked HCRNet on 37 circRNA datasets and 31 linear RNA datasets to demonstrate the effectiveness of our proposed method. To evaluate further the model's robustness, we performed HCRNet on a full-length dataset containing 740 circRNAs. Results indicate that HCRNet generally outperforms existing methods. In addition, motif analyses were conducted to exhibit the interpretability of HCRNet on circRNAs. All supporting source code and data can be downloaded from https://github.com/yangyn533/HCRNet and https://doi.org/10.6084/m9.figshare.16943722.v1. And the web server of HCRNet is publicly accessible at http://39.104.118.143:5001/.

circRNA-binding protein site prediction based on multi-view deep learning, subspace learning and multi-view classifier.

Circular RNAs (circRNAs) generally bind to RNA-binding proteins (RBPs) to play an important role in the regulation of autoimmune diseases. Thus, it is crucial to study the binding sites of RBPs on circRNAs. Although many methods, including traditional machine learning and deep learning, have been developed to predict the interactions between RNAs and RBPs, and most of them are focused on linear RNAs. At present, few studies have been done on the binding relationships between circRNAs and RBPs. Thus, in-depth research is urgently needed. In the existing circRNA-RBP binding site prediction methods, circRNA sequences are the main research subjects, but the relevant characteristics of circRNAs have not been fully exploited, such as the structure and composition information of circRNA sequences. Some methods have extracted different views to construct recognition models, but how to efficiently use the multi-view data to construct recognition models is still not well studied. Considering the above problems, this paper proposes a multi-view classification method called DMSK based on multi-view deep learning, subspace learning and multi-view classifier for the identification of circRNA-RBP interaction sites. In the DMSK method, first, we converted circRNA sequences into pseudo-amino acid sequences and pseudo-dipeptide components for extracting high-dimensional sequence features and component features of circRNAs, respectively. Then, the structure prediction method RNAfold was used to predict the secondary structure of the RNA sequences, and the sequence embedding model was used to extract the context-dependent features. Next, we fed the above four views' raw features to a hybrid network, which is composed of a convolutional neural network and a long short-term memory network, to obtain the deep features of circRNAs. Furthermore, we used view-weighted generalized canonical correlation analysis to extract four views' common features by subspace learning. Finally, the learned subspace common features and multi-view deep features were fed to train the downstream multi-view TSK fuzzy system to construct a fuzzy rule and fuzzy inference-based multi-view classifier. The trained classifier was used to predict the specific positions of the RBP binding sites on the circRNAs. The experiments show that the prediction performance of the proposed method DMSK has been improved compared with the existing methods. The code and dataset of this study are available at https://github.com/Rebecca3150/DMSK.