POSTAR: a platform for exploring post-transcriptional regulation coordinated by RNA-binding proteins

Gas5 regulates early-life stress-induced anxiety and spatial memory

Early-life stress (ES) induced by maternal separation (MS) remains a proven causality of anxiety and memory deficits at later stages of life. Emerging studies have shown that MS-induced gene expression in the hippocampus is operated at the level of transcription. However, the extent of involvement of non-coding RNAs in MS-induced behavioural deficits remains unexplored. Here, we have investigated the role of synapse-enriched long non-coding RNAs (lncRNAs) in anxiety and memory upon MS. We observed that MS led to an enhancement of expression of the lncRNA growth arrest specific 5 (Gas5) in the hippocampus; accompanied by increased levels of anxiety and deficits in spatial memory. Gas5 knockdown in early life was able to reduce anxiety and partially rescue the spatial memory deficits of maternally separated adult mice. However, the reversal of MS-induced anxiety and memory deficits is not attributed to Gas5 activity during neuronal development as Gas5 RNAi did not influence spine development. Gene Ontology analysis revealed that Gas5 exerts its function by regulating RNA metabolism and translation. Our study highlights the importance of MS-regulated lncRNA in anxiety and spatial memory.

Determinants of gastric cancer immune escape identified from non-coding immune-landscape quantitative trait loci

The landscape of non-coding mutations in cancer progression and immune evasion is largely unexplored. Here, we identify transcrptome-wide somatic and germline 3' untranslated region (3'-UTR) variants from 375 gastric cancer patients from The Cancer Genome Atlas. By performing gene expression quantitative trait loci (eQTL) and immune landscape QTL (ilQTL) analysis, we discover 3'-UTR variants with cis effects on expression and immune landscape phenotypes, such as immune cell infiltration and T cell receptor diversity. Using a massively parallel reporter assay, we distinguish between causal and correlative effects of 3'-UTR eQTLs in immune-related genes. Our approach identifies numerous 3'-UTR eQTLs and ilQTLs, providing a unique resource for the identification of immunotherapeutic targets and biomarkers. A prioritized ilQTL variant signature predicts response to immunotherapy better than standard-of-care PD-L1 expression in independent patient cohorts, showcasing the untapped potential of non-coding mutations in cancer.

Improved discovery of RNA-binding protein binding sites in eCLIP data using DEWSeq

Enhanced crosslinking and immunoprecipitation (eCLIP) sequencing is a method for transcriptome-wide detection of binding sites of RNA-binding proteins (RBPs). However, identified crosslink sites can deviate from experimentally established functional elements of even well-studied RBPs. Current peak-calling strategies result in low replication and high false positive rates. Here, we present the R/Bioconductor package DEWSeq that makes use of replicate information and size-matched input controls. We benchmarked DEWSeq on 107 RBPs for which both eCLIP data and RNA sequence motifs are available and were able to more than double the number of motif-containing binding regions relative to standard eCLIP processing. The improvement not only relates to the number of binding sites (3.1-fold with known motifs for RBFOX2), but also their subcellular localization (1.9-fold of mitochondrial genes for FASTKD2) and structural targets (2.2-fold increase of stem-loop regions for SLBP. On several orthogonal CLIP-seq datasets, DEWSeq recovers a larger number of motif-containing binding sites (3.3-fold). DEWSeq is a well-documented R/Bioconductor package, scalable to adequate numbers of replicates, and tends to substantially increase the proportion and total number of RBP binding sites containing biologically relevant features.

Computational prediction and experimental validation identify functionally conserved lncRNAs from zebrafish to human

Functional studies of long noncoding RNAs (lncRNAs) have been hindered by the lack of methods to assess their evolution. Here we present lncRNA Homology Explorer (lncHOME), a computational pipeline that identifies a unique class of long noncoding RNAs (lncRNAs) with conserved genomic locations and patterns of RNA-binding protein (RBP) binding sites (coPARSE-lncRNAs). Remarkably, several hundred human coPARSE-lncRNAs can be evolutionarily traced to zebrafish. Using CRISPR-Cas12a knockout and rescue assays, we found that knocking out many human coPARSE-lncRNAs led to cell proliferation defects, which were subsequently rescued by predicted zebrafish homologs. Knocking down coPARSE-lncRNAs in zebrafish embryos caused severe developmental delays that were rescued by human homologs. Furthermore, we verified that human, mouse and zebrafish coPARSE-lncRNA homologs tend to bind similar RBPs with their conserved functions relying on specific RBP-binding sites. Overall, our study demonstrates a comprehensive approach for studying the functional conservation of lncRNAs and implicates numerous lncRNAs in regulating vertebrate physiology.

Shining a spotlight on m6A and the vital role of RNA modification in endometrial cancer: a review

RNA modifications are mostly dynamically reversible post-transcriptional modifications, of which m6A is the most prevalent in eukaryotic mRNAs. A growing number of studies indicate that RNA modification can finely tune gene expression and modulate RNA metabolic homeostasis, which in turn affects the self-renewal, proliferation, apoptosis, migration, and invasion of tumor cells. Endometrial carcinoma (EC) is the most common gynecologic tumor in developed countries. Although it can be diagnosed early in the onset and have a preferable prognosis, some cases might develop and become metastatic or recurrent, with a worse prognosis. Fortunately, immunotherapy and targeted therapy are promising methods of treating endometrial cancer patients. Gene modifications may also contribute to these treatments, as is especially the case with recent developments of new targeted therapeutic genes and diagnostic biomarkers for EC, even though current findings on the relationship between RNA modification and EC are still very limited, especially m6A. For example, what is the elaborate mechanism by which RNA modification affects EC progression? Taking m6A modification as an example, what is the conversion mode of methylation and demethylation for RNAs, and how to achieve selective recognition of specific RNA? Understanding how they cope with various stimuli as part of in vivo and in vitro biological development, disease or tumor occurrence and development, and other processes is valuable and RNA modifications provide a distinctive insight into genetic information. The roles of these processes in coping with various stimuli, biological development, disease, or tumor development in vivo and in vitro are self-evident and may become a new direction for cancer in the future. In this review, we summarize the category, characteristics, and therapeutic precis of RNA modification, m6A in particular, with the purpose of seeking the systematic regulation axis related to RNA modification to provide a better solution for the treatment of EC.

CAG repeat expansion in the Huntington's disease gene shapes linear and circular RNAs biogenesis

Alternative splicing (AS) appears to be altered in Huntington's disease (HD), but its significance for early, pre-symptomatic disease stages has not been inspected. Here, taking advantage of Htt CAG knock-in mouse in vitro and in vivo models, we demonstrate a correlation between Htt CAG repeat length and increased aberrant linear AS, specifically affecting neural progenitors and, in vivo, the striatum prior to overt behavioral phenotypes stages. Remarkably, a significant proportion (36%) of the aberrantly spliced isoforms are not-functional and meant to non-sense mediated decay (NMD). The expanded Htt CAG repeats further reflect on a previously neglected, global impairment of back-splicing, leading to decreased circular RNAs production in neural progenitors. Integrative transcriptomic analyses unveil a network of transcriptionally altered micro-RNAs and RNA-binding proteins (Celf, hnRNPs, Ptbp, Srsf, Upf1, Ythd2) which might influence the AS machinery, primarily in neural cells. We suggest that this unbalanced expression of linear and circular RNAs might alter neural fitness, contributing to HD pathogenesis.

Self-demixing of mRNA copies buffers mRNA:mRNA and mRNA:regulator stoichiometries

Cellular homeostasis requires the robust control of biomolecule concentrations, but how do millions of mRNAs coordinate their stoichiometries in the face of dynamic translational changes? Here, we identified a two-tiered mechanism controlling mRNA:mRNA and mRNA:protein stoichiometries where mRNAs super-assemble into condensates with buffering capacity and sorting selectivity through phase-transition mechanisms. Using C. elegans oogenesis arrest as a model, we investigated the transcriptome cytosolic reorganization through the sequencing of RNA super-assemblies coupled with single mRNA imaging. Tightly repressed mRNAs self-assembled into same-sequence nanoclusters that further co-assembled into multiphase condensates. mRNA self-sorting was concentration dependent, providing a self-buffering mechanism that is selective to sequence identity and controls mRNA:mRNA stoichiometries. The cooperative sharing of limiting translation repressors between clustered mRNAs prevented the disruption of mRNA:repressor stoichiometries in the cytosol. Robust control of mRNA:mRNA and mRNA:protein stoichiometries emerges from mRNA self-demixing and cooperative super-assembly into multiphase multiscale condensates with dynamic storage capacity.

Application of sequence semantic and integrated cellular geography approach to study alternative biogenesis of exonic circular RNA

BACKGROUND

Concurrent existence of lncRNA and circular RNA at both nucleus and cytosol within a cell at different proportions is well reported. Previous studies showed that circular RNAs are synthesized in nucleus followed by transportation across the nuclear membrane and the export is primarily defined by their length. lncRNAs primarily originated through inefficient splicing and seem to use NXF1 for cytoplasm export. However, it is not clear whether circularization of lncRNA happens only in nucleus or it also occurs in cytoplasm. Studies indicate that circular RNAs arise when the splicing apparatus undergoes a phenomenon of back splicing. Minor spliceosome (U12 type) mediated splicing occurs in cytoplasm and is responsible for the splicing of 0.5% of introns of human cells. Therefore, possibility of cRNA biogenesis mediated by minor spliceosome at cytoplasm cannot be ruled out. Secondly, information on genes transcribing both circular and lncRNAs along with total number of RBP binding sites for both of these RNA types is extractable from databases. This study showed how these apparently unconnected pieces of reports could be put together to build a model for exploring biogenesis of circular RNA.

RESULTS

As a result of this study, a model was built under the premises that, sequences with special semantics were molecular precursors in biogenesis of circular RNA which occurred through catalytic role of some specific RBPs. The model outcome was further strengthened by fulfillment of three logical lemmas which were extracted and assimilated in this work using a novel data analytic approach, Integrated Cellular Geography. Result of the study was found to be in well agreement with proposed model. Furthermore this study also indicated that biogenesis of circular RNA was a post-transcriptional event.

CONCLUSIONS

Overall, this study provides a novel systems biology based model under the paradigm of Integrated Cellular Geography which can assimilate independently performed experimental results and data published by global researchers on RNA biology to provide important information on biogenesis of circular RNAs considering lncRNAs as precursor molecule. This study also suggests the possible RBP-mediated circularization of RNA in the cytoplasm through back-splicing using minor spliceosome.

Predictive model of transcriptional elongation control identifies trans regulatory factors from chromatin signatures

Promoter-proximal Polymerase II (Pol II) pausing is a key rate-limiting step for gene expression. DNA and RNA-binding trans-acting factors regulating the extent of pausing have been identified. However, we lack a quantitative model of how interactions of these factors determine pausing, therefore the relative importance of implicated factors is unknown. Moreover, previously unknown regulators might exist. Here we address this gap with a machine learning model that accurately predicts the extent of promoter-proximal Pol II pausing from large-scale genome and transcriptome binding maps and gene annotation and sequence composition features. We demonstrate high accuracy and generalizability of the model by validation on an independent cell line which reveals the model's cell line agnostic character. Model interpretation in light of prior knowledge about molecular functions of regulatory factors confirms the interconnection of pausing with other RNA processing steps. Harnessing underlying feature contributions, we assess the relative importance of each factor, quantify their predictive effects and systematically identify previously unknown regulators of pausing. We additionally identify 16 previously unknown 7SK ncRNA interacting RNA-binding proteins predictive of pausing. Our work provides a framework to further our understanding of the regulation of the critical early steps in transcriptional elongation.

Functional Relationships between Long Non-Coding RNAs and Estrogen Receptor Alpha: A New Frontier in Hormone-Responsive Breast Cancer Management

In the complex and articulated machinery of the human genome, less than 2% of the transcriptome encodes for proteins, while at least 75% is actively transcribed into non-coding RNAs (ncRNAs). Among the non-coding transcripts, those ≥200 nucleotides long (lncRNAs) are receiving growing attention for their involvement in human diseases, particularly cancer. Genomic studies have revealed the multiplicity of processes, including neoplastic transformation and tumor progression, in which lncRNAs are involved by regulating gene expression at epigenetic, transcriptional, and post-transcriptional levels by mechanism(s) that still need to be clarified. In breast cancer, several lncRNAs were identified and demonstrated to have either oncogenic or tumor-suppressive roles. The functional understanding of the mechanisms of lncRNA action in this disease could represent a potential for translational applications, as these molecules may serve as novel biomarkers of clinical use and potential therapeutic targets. This review highlights the relationship between lncRNAs and the principal hallmark of the luminal breast cancer phenotype, estrogen receptor α (ERα), providing an overview of new potential ways to inhibit estrogenic signaling via this nuclear receptor toward escaping resistance to endocrine therapy.

N6-Methyladenosine-modified lncRNA LINREP promotes Glioblastoma progression by recruiting the PTBP1/HuR complex

Glioblastoma multiforme (GBM) is acknowledged as the most aggressive primary brain tumor in adults. It is typically characterized by the high heterogeneity which corresponds to extensive genetic mutations and complex alternative splicing (AS) profiles. Known as a major repressive splicing factor in AS, polypyrimidine tract-binding protein 1 (PTBP1) is involved in the exon skipping events of multiple precursor mRNAs (pre-mRNAs) in GBM. However, precise mechanisms that modulate the expression and activity of PTBP1 remain to be elucidated. In present study, we provided evidences for the role of a long intergenic noncoding RNA (LINREP) implicated in the regulation of PTBP1-induced AS. LINREP interacted with PTBP1 and human antigen R (HuR, ELAVL1) protein complex and protected PTBP1 from the ubiquitin-proteasome degradation. Consequently, a broad spectrum of PTBP1-induced spliced variants was generated by exon skipping, especially for the skipping of reticulon 4 (RTN4) exon 3. Interestingly, LINREP also promoted the dissociation of nuclear UPF1 from PTBP1, which increased the binding of PTBP1 to RTN4 transcripts, thus enhancing the skipping of RTN4 exon 3 to some extent. Besides, HuR recruitment was essential for the stabilization of LINREP via a manner dependent on N6-methyladenosine (m6A) formation and identification. Taken together, our results demonstrated the functional significance of LINREP in human GBM for its dual regulation of PTBP1-induced AS and its m6A modification modality, implicating that HuR/LINREP/PTBP1 axis might serve as a potential therapeutic target for GBM.

DirectRMDB: a database of post-transcriptional RNA modifications unveiled from direct RNA sequencing technology

With advanced technologies to map RNA modifications, our understanding of them has been revolutionized, and they are seen to be far more widespread and important than previously thought. Current next-generation sequencing (NGS)-based modification profiling methods are blind to RNA modifications and thus require selective chemical treatment or antibody immunoprecipitation methods for particular modification types. They also face the problem of short read length, isoform ambiguities, biases and artifacts. Direct RNA sequencing (DRS) technologies, commercialized by Oxford Nanopore Technologies (ONT), enable the direct interrogation of any given modification present in individual transcripts and promise to address the limitations of previous NGS-based methods. Here, we present the first ONT-based database of quantitative RNA modification profiles, DirectRMDB, which includes 16 types of modification and a total of 904,712 modification sites in 25 species identified from 39 independent studies. In addition to standard functions adopted by existing databases, such as gene annotations and post-transcriptional association analysis, we provide a fresh view of RNA modifications, which enables exploration of the epitranscriptome in an isoform-specific manner. The DirectRMDB database is freely available at: http://www.rnamd.org/directRMDB/.

Deciphering the impact of genetic variation on human polyadenylation using APARENT2

BACKGROUND

3'-end processing by cleavage and polyadenylation is an important and finely tuned regulatory process during mRNA maturation. Numerous genetic variants are known to cause or contribute to human disorders by disrupting the cis-regulatory code of polyadenylation signals. Yet, due to the complexity of this code, variant interpretation remains challenging.

RESULTS

We introduce a residual neural network model, APARENT2, that can infer 3'-cleavage and polyadenylation from DNA sequence more accurately than any previous model. This model generalizes to the case of alternative polyadenylation (APA) for a variable number of polyadenylation signals. We demonstrate APARENT2's performance on several variant datasets, including functional reporter data and human 3' aQTLs from GTEx. We apply neural network interpretation methods to gain insights into disrupted or protective higher-order features of polyadenylation. We fine-tune APARENT2 on human tissue-resolved transcriptomic data to elucidate tissue-specific variant effects. By combining APARENT2 with models of mRNA stability, we extend aQTL effect size predictions to the entire 3' untranslated region. Finally, we perform in silico saturation mutagenesis of all human polyadenylation signals and compare the predicted effects of [Formula: see text] million variants against gnomAD. While loss-of-function variants were generally selected against, we also find specific clinical conditions linked to gain-of-function mutations. For example, we detect an association between gain-of-function mutations in the 3'-end and autism spectrum disorder. To experimentally validate APARENT2's predictions, we assayed clinically relevant variants in multiple cell lines, including microglia-derived cells.

CONCLUSIONS

A sequence-to-function model based on deep residual learning enables accurate functional interpretation of genetic variants in polyadenylation signals and, when coupled with large human variation databases, elucidates the link between functional 3'-end mutations and human health.

Widespread autogenous mRNA-protein interactions detected by CLIP-seq

Autogenous interactions between mRNAs and the proteins they encode are implicated in cellular feedback-loop regulation, but their extent and mechanistic foundation are unclear. It was recently hypothesized that such interactions may be common, reflecting the role of intrinsic nucleobase-amino acid affinities in shaping the genetic code's structure. Here we analyze a comprehensive set of CLIP-seq experiments involving multiple protocols and report on widespread autogenous interactions across different organisms. Specifically, 230 of 341 (67%) studied RNA-binding proteins (RBPs) interact with their own mRNAs, with a heavy enrichment among high-confidence hits and a preference for coding sequence binding. We account for different confounding variables, including physical (overexpression and proximity during translation), methodological (difference in CLIP protocols, peak callers and cell types) and statistical (treatment of null backgrounds). In particular, we demonstrate a high statistical significance of autogenous interactions by sampling null distributions of fixed-margin interaction matrices. Furthermore, we study the dependence of autogenous binding on the presence of RNA-binding motifs and structured domains in RBPs. Finally, we show that intrinsic nucleobase-amino acid affinities favor co-aligned binding between mRNA coding regions and the proteins they encode. Our results suggest a central role for autogenous interactions in RBP regulation and support the possibility of a fundamental connection between coding and binding.

The Future of Biomarkers in Veterinary Medicine: Emerging Approaches and Associated Challenges

Simple Summary

In this review we seek to outline the role of new technologies in biomarker discovery, particularly within the veterinary field and with an emphasis on ‘omics’, as well as to examine why many biomarkers-despite much excitement-have not yet made it to clinical practice. Further we emphasise the critical need for close collaboration between clinicians, researchers and funding bodies and the need to set clear goals for biomarker requirements and realistic application in the clinical setting, ensuring that biomarker type, method of detection and clinical utility are compatible, and adequate funding, time and sample size are available for all phases of development.

Abstract

New biomarkers promise to transform veterinary practice through rapid diagnosis of diseases, effective monitoring of animal health and improved welfare and production efficiency. However, the road from biomarker discovery to translation is not always straightforward. This review focuses on molecular biomarkers under development in the veterinary field, introduces the emerging technological approaches transforming this space and the role of ‘omics platforms in novel biomarker discovery. The vast majority of veterinary biomarkers are at preliminary stages of development and not yet ready to be deployed into clinical translation. Hence, we examine the major challenges encountered in the process of biomarker development from discovery, through validation and translation to clinical practice, including the hurdles specific to veterinary practice and to each of the ‘omics platforms–transcriptomics, proteomics, lipidomics and metabolomics. Finally, recommendations are made for the planning and execution of biomarker studies with a view to assisting the success of novel biomarkers in reaching their full potential.

DNA- and RNA-Binding Proteins Linked Transcriptional Control and Alternative Splicing Together in a Two-Layer Regulatory Network System of Chronic Myeloid Leukemia

DNA- and RNA-binding proteins (DRBPs) typically possess multiple functions to bind both DNA and RNA and regulate gene expression from more than one level. They are controllers for post-transcriptional processes, such as splicing, polyadenylation, transportation, translation, and degradation of RNA transcripts in eukaryotic organisms, as well as regulators on the transcriptional level. Although DRBPs are reported to play critical roles in various developmental processes and diseases, it is still unclear how they work with DNAs and RNAs simultaneously and regulate genes at the transcriptional and post-transcriptional levels. To investigate the functional mechanism of DRBPs, we collected data from a variety of databases and literature and identified 118 DRBPs, which function as both transcription factors (TFs) and splicing factors (SFs), thus called DRBP-SF. Extensive investigations were conducted on four DRBP-SFs that were highly expressed in chronic myeloid leukemia (CML), heterogeneous nuclear ribonucleoprotein K (HNRNPK), heterogeneous nuclear ribonucleoprotein L (HNRNPL), non-POU domain–containing octamer–binding protein (NONO), and TAR DNA-binding protein 43 (TARDBP). By integrating and analyzing ChIP-seq, CLIP-seq, RNA-seq, and shRNA-seq data in K562 using binding and expression target analysis and Statistical Utility for RBP Functions, we discovered a two-layer regulatory network system centered on these four DRBP-SFs and proposed three possible regulatory models where DRBP-SFs can connect transcriptional and alternative splicing regulatory networks cooperatively in CML. The exploration of the identified DRBP-SFs provides new ideas for studying DRBP and regulatory networks, holding promise for further mechanistic discoveries of the two-layer gene regulatory system that may play critical roles in the occurrence and development of CML.

CLIPreg: Constructing translational regulatory networks from CLIP-, Ribo- and RNA-seq

MOTIVATION

The creation and analysis of gene regulatory networks have been the focus of bioinformatics research and underpins much of what is known about gene regulation. However, as a result of a bias in the availability of data-types that are collected, the vast majority of gene regulatory network resources and tools have focused on either transcriptional regulation or protein-protein interactions. This has left other areas of regulation, for instance, translational regulation, vastly underrepresented despite them having been shown to play a critical role in both health and disease.

RESULTS

In order to address this we have developed CLIPreg, a package that integrates RNA, Ribo and CLIP- sequencing data in order to construct translational regulatory networks coordinated by RNA-binding proteins and micro-RNAs. This is the first tool of its type to be created, allowing for detailed investigation into a previously unseen layer of regulation.

AVAILABILITY AND IMPLEMENTATION

CLIPreg is available at https://github.com/SGDDNB/CLIPreg.

Pan-cancer pervasive upregulation of 3' UTR splicing drives tumourigenesis

Most mammalian genes generate messenger RNAs with variable untranslated regions (UTRs) that are important post-transcriptional regulators. In cancer, shortening at 3′ UTR ends via alternative polyadenylation can activate oncogenes. However, internal 3′ UTR splicing remains poorly understood as splicing studies have traditionally focused on protein-coding alterations. Here we systematically map the pan-cancer landscape of 3′ UTR splicing and present this in SpUR (http://www.cbrc.kaust.edu.sa/spur/home/). 3′ UTR splicing is widespread, upregulated in cancers, correlated with poor prognosis and more prevalent in oncogenes. We show that antisense oligonucleotide-mediated inhibition of 3′ UTR splicing efficiently reduces oncogene expression and impedes tumour progression. Notably, CTNNB1 3′ UTR splicing is the most consistently dysregulated event across cancers. We validate its upregulation in hepatocellular carcinoma and colon adenocarcinoma, and show that the spliced 3′ UTR variant is the predominant contributor to its oncogenic functions. Overall, our study highlights the importance of 3′ UTR splicing in cancer and may launch new avenues for RNA-based anti-cancer therapeutics.

Chan et al. report that 3′ UTR splicing is widespread and enhanced across different cancer types and is associated with more advanced tumour progression.

FMRP ligand circZNF609 destabilizes RAC1 mRNA to reduce metastasis in acral melanoma and cutaneous melanoma

BACKGROUND

Melanoma is a type of malignant tumor with high aggressiveness and poor prognosis. At present, metastasis of melanoma is still an important cause of death in melanoma patients. However, the potential functions and molecular mechanisms of most circular RNAs (circRNAs) in melanoma metastasis remain unknown.

METHODS

circRNAs dysregulated in melanoma cell subgroups with different metastatic abilities according to a screening model based on repeated Transwell assays were identified with a circRNA array. The expression and prognostic significance of circZNF609 in skin cutaneous melanoma and acral melanoma cells and tissues were determined by qRT-PCR, nucleoplasmic separation assays and fluorescence in situ hybridization. In vitro wound healing, Transwell and 3D invasion assays were used to analyse melanoma cell metastasis ability. Tail vein injection and intrasplenic injection were used to study in vivo lung metastasis and liver metastasis, respectively. The mechanism of circZNF609 was further evaluated via RNA immunoprecipitation, RNA pull-down, silver staining, and immunofluorescence colocalization assays.

RESULTS

circZNF609 was stably expressed at low levels in melanoma tissues and cells and was negatively correlated with Breslow depth, clinical stage and prognosis of melanoma patients. circZNF609 inhibited metastasis of acral and cutaneous melanoma in vivo and in vitro. Mechanistically, circZNF609 promoted the binding of FMRP protein and RAC1 mRNA, thereby enhancing the inhibitory effect of FMRP protein on the stability of RAC1 mRNA and ultimately inhibiting melanoma metastasis.

CONCLUSIONS

Our findings revealed that circZNF609 plays a vital role in the metastasis of acral and cutaneous melanoma through the circRNF609-FMRP-RAC1 axis and indicated that circZNF609 regulates the stability of RAC1 mRNA by combining with FMRP, which might provide insight into melanoma pathogenesis and a new potential target for treatment of melanoma.

The dual role of glioma exosomal microRNAs: glioma eliminates tumor suppressor miR-1298-5p via exosomes to promote immunosuppressive effects of MDSCs

Clear evidence shows that tumors could secrete microRNAs (miRNAs) via exosomes to modulate the tumor microenvironment (TME). However, the mechanisms sorting specific miRNAs into exosomes are still unclear. In order to study the biological function and characterization of exosomal miRNAs, we performed whole-transcriptome sequencing in 59 patients' whole-course cerebrospinal fluid (CSF) small extracellular vesicles (sEV) and matched glioma tissue samples. The results demonstrate that miRNAs could be divided into exosome-enriched miRNAs (ExomiRNAs) and intracellular-retained miRNAs (CLmiRNAs), and exosome-enriched miRNAs generally play a dual role. Among them, miR-1298-5p was enriched in CSF exosomes and suppressed glioma progression in vitro and vivo experiments. Interestingly, exosomal miR-1298-5p could promote the immunosuppressive effects of myeloid-derived suppressor cells (MDSCs) to facilitate glioma. Therefore, we found miR-1298-5p had different effects on glioma cells and MDSCs. Mechanically, downstream signaling pathway analyses showed that miR-1298-5p plays distinct roles in glioma cells and MDSCs via targeting SETD7 and MSH2, respectively. Moreover, reverse verification was performed on the intracellular-retained miRNA miR-9-5p. Thus, we confirmed that tumor-suppressive miRNAs in glioma cells could be eliminated through exosomes and target tumor-associated immune cells to induce tumor-promoting phenotypes. Glioma could get double benefit from it. These findings uncover the mechanisms that glioma selectively sorts miRNAs into exosomes and modulates tumor immunity.

RNAscope for VEGF-A Detection in Human Tumor Bioptic Specimens

Different pro-angiogenic factors, such as vascular endothelial growth factor-A (VEGF-A), have been related to microvascular density, clinicopathologic factors, and poor prognosis in many tumors. VEGF-A binds its receptor 2 (VEGFR2) to induce neo-angiogenesis, a constant hallmark of tumor initiation and progression. Based on VEGF-A/VEGFR2 relevance in tumor angiogenesis, several inhibitors were developed. However, the clinical benefits of anti-angiogenic therapies are limited because tumors activate different mechanisms of drug resistance.The need for understanding tumor biology, limitation or failure of anti-angiogenic therapies, and the demand for a personalized therapeutic approach has boosted the search for robust biomarkers for patient stratification as responder or non-responder to anti-VEGF therapies.This chapter presents a detailed protocol to perform chromogenic VEGF-A mRNA detection and quantification in human tumor bioptic specimens using RNAscope technology and RNA-in situ hybridization (ISH) algorithm. RNAscope for VEGF-A detection, even for small amounts, is compatible with precious clinical samples and diagnostic laboratory workflows.

TRACE-seq: A transgenic system for unbiased and non-invasive transcriptome profiling of living cells

Dynamic profiling of changes in gene expression in response to stressors in specific microenvironments without requiring cellular destruction remains challenging. Current methodologies that seek to interrogate gene expression at a molecular level require sampling of cellular transcriptome and therefore lysis of the cell, preventing serial analysis of cellular transcriptome. To address this area of unmet need, we have recently developed a technology allowing transcriptomic analysis over time without cellular destruction. Our method, TRACE-seq (TRanscriptomic Analysis Captured in Extracellular vesicles using sequencing), is characterized by a cell-type specific transgene expression. It provides data on the transcriptome inside extracellular vesicles that provides an accurate representation of stress-responsive cellular transcriptomic changes. Thus, the transcriptome of cells expressing TRACE can be followed over time without destroying the source cell, which is a powerful tool for many fields of fundamental and translational biology research.

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TRanscriptomic Analysis Captured in Extracellular vesicles using RNA-sequencing

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Excellent correlation of cellular and EV transcriptome using this method

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Accurate profiling of gene expression changes in response to stress signals

POSTAR3: an updated platform for exploring post-transcriptional regulation coordinated by RNA-binding proteins

RNA-binding proteins (RBPs) play key roles in post-transcriptional regulation. Accurate identification of RBP binding sites in multiple cell lines and tissue types from diverse species is a fundamental endeavor towards understanding the regulatory mechanisms of RBPs under both physiological and pathological conditions. Our POSTAR annotation processes make use of publicly available large-scale CLIP-seq datasets and external functional genomic annotations to generate a comprehensive map of RBP binding sites and their association with other regulatory events as well as functional variants. Here, we present POSTAR3, an updated database with improvements in data collection, annotation infrastructure, and analysis that support the annotation of post-transcriptional regulation in multiple species including: we made a comprehensive update on the CLIP-seq and Ribo-seq datasets which cover more biological conditions, technologies, and species; we added RNA secondary structure profiling for RBP binding sites; we provided miRNA-mediated degradation events validated by degradome-seq; we included RBP binding sites at circRNA junction regions; we expanded the annotation of RBP binding sites, particularly using updated genomic variants and mutations associated with diseases. POSTAR3 is freely available at http://postar.ncrnalab.org.

A long noncoding RNA-microRNA expression signature predicts metastatic signature in pheochromocytomas and paragangliomas

PURPOSE

In hopes of discovering new markers for metastatic or aggressive phenotypes of pheochromocytomas and paragangliomas (PCPG), we analyzed the noncoding transcriptome from patient gene expression data in The Cancer Genome Atlas.

METHODS

Differential expression of miRNAs was observed between PCPG molecular subtypes. We specifically characterized candidate miRNAs that are upregulated in pseudohypoxic PCPGs with mutations in succinate dehydrogenase complex subunits, B and/or D (SDHB and/or SDHD, respectively), which are mutations associated with unfavorable clinical outcomes.

RESULTS

Our computational analysis identified four candidate miRNAs that showed elevated expression in metastatic compared to non-metastatic PCPGs: miR-182, miR-183, miR-96, and miR-383. We also found six candidate lncRNAs harboring opposite expression patterns from the miRNAs when we analyzed the expression profiles of their predicted target lncRNAs. Three of these lncRNA candidates, USP3-AS1, LINC00877, and AC009312.1, were validated to have reduced expression in metastatic compared to non-metastatic PCPGs. Finally, using univariate and multivariate analysis, we found miRNA miR-182 to be an independent predictor of metastasis-free survival in PCPGs.

CONCLUSIONS

We identified candidate miRNA and lncRNAs associated with metastasis-free survival in PCPGs.

ELK4-mediated lncRNA SNHG22 promotes gastric cancer progression through interacting with EZH2 and regulating miR-200c-3p/Notch1 axis

Long non-coding RNAs (lncRNAs) play important regulatory roles in the initiation and progression of various cancers. However, the biological roles and the potential mechanisms of lncRNAs in gastric cancers remain unclear. Here, we report that the expression of lncRNA SNHG22 (small nucleolar RNA host gene 22) was significantly increased in GC (Gastric Cancer) tissues and cells, which confers poor prognosis of patients. Knockdown of SNHG22 inhibited the proliferation and invasion ability of GC cells. Moreover, we identified that the transcriptional factor, ELK4 (ETS transcription factor ELK4), could promote SNHG22 expression in GC cells. In addition, using RNA pull-down followed MS assay, we found that SNHG22 directly bound to EZH2 (enhancer of zeste 2 polycomb repressive complex 2 subunit) to suppress the expression of tumor suppressor genes. At the same time, SNHG22 sponged miR-200c-3p to increase Notch1 (notch receptor 1) expression. Taken together, our findings demonstrated the role of SNHG22 on promoting proliferation and invasion of GC cells. And we revealed a new regulatory mechanism of SNHG22 in GC cells. SNHG22 is a promising lncRNA biomarker for diagnosis and prognosis and a potential target for GC treatment.

A Survey of Current Resources to Study lncRNA-Protein Interactions

Phenotypes are driven by regulated gene expression, which in turn are mediated by complex interactions between diverse biological molecules. Protein-DNA interactions such as histone and transcription factor binding are well studied, along with RNA-RNA interactions in short RNA silencing of genes. In contrast, lncRNA-protein interaction (LPI) mechanisms are comparatively unknown, likely directed by the difficulties in studying LPI. However, LPI are emerging as key interactions in epigenetic mechanisms, playing a role in development and disease. Their importance is further highlighted by their conservation across kingdoms. Hence, interest in LPI research is increasing. We therefore review the current state of the art in lncRNA-protein interactions. We specifically surveyed recent computational methods and databases which researchers can exploit for LPI investigation. We discovered that algorithm development is heavily reliant on a few generic databases containing curated LPI information. Additionally, these databases house information at gene-level as opposed to transcript-level annotations. We show that early methods predict LPI using molecular docking, have limited scope and are slow, creating a data processing bottleneck. Recently, machine learning has become the strategy of choice in LPI prediction, likely due to the rapid growth in machine learning infrastructure and expertise. While many of these methods have notable limitations, machine learning is expected to be the basis of modern LPI prediction algorithms.

Predicting dynamic cellular protein-RNA interactions by deep learning using in vivo RNA structures

Interactions with RNA-binding proteins (RBPs) are integral to RNA function and cellular regulation, and dynamically reflect specific cellular conditions. However, presently available tools for predicting RBP-RNA interactions employ RNA sequence and/or predicted RNA structures, and therefore do not capture their condition-dependent nature. Here, after profiling transcriptome-wide in vivo RNA secondary structures in seven cell types, we developed PrismNet, a deep learning tool that integrates experimental in vivo RNA structure data and RBP binding data for matched cells to accurately predict dynamic RBP binding in various cellular conditions. PrismNet results for 168 RBPs support its utility for both understanding CLIP-seq results and largely extending such interaction data to accurately analyze additional cell types. Further, PrismNet employs an "attention" strategy to computationally identify exact RBP-binding nucleotides, and we discovered enrichment among dynamic RBP-binding sites for structure-changing variants (riboSNitches), which can link genetic diseases with dysregulated RBP bindings. Our rich profiling data and deep learning-based prediction tool provide access to a previously inaccessible layer of cell-type-specific RBP-RNA interactions, with clear utility for understanding and treating human diseases.

Relative Information Gain: Shannon entropy-based measure of the relative structural conservation in RNA alignments

Structural characterization of RNAs is a dynamic field, offering many modelling possibilities. RNA secondary structure models are usually characterized by an encoding that depicts structural information of the molecule through string representations or graphs. In this work, we provide a generalization of the BEAR encoding (a context-aware structural encoding we previously developed) by expanding the set of alignments used for the construction of substitution matrices and then applying it to secondary structure encodings ranging from fine-grained to more coarse-grained representations. We also introduce a re-interpretation of the Shannon Information applied on RNA alignments, proposing a new scoring metric, the Relative Information Gain (RIG). The RIG score is available for any position in an alignment, showing how different levels of detail encoded in the RNA representation can contribute differently to convey structural information. The approaches presented in this study can be used alongside state-of-the-art tools to synergistically gain insights into the structural elements that RNAs and RNA families are composed of. This additional information could potentially contribute to their improvement or increase the degree of confidence in the secondary structure of families and any set of aligned RNAs.

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.

Alteration of mRNA 5-Methylcytosine Modification in Neurons After OGD/R and Potential Roles in Cell Stress Response and Apoptosis

Epigenetic modifications play an important role in central nervous system disorders. As a widespread posttranscriptional RNA modification, the role of the m5C modification in cerebral ischemia-reperfusion injury (IRI) remains poorly defined. Here, we successfully constructed a neuronal oxygen-glucose deprivation/reoxygenation (OGD/R) model and obtained an overview of the transcriptome-wide m5C profiles using RNA-BS-seq. We discovered that the distribution of neuronal m5C modifications was highly conserved, significantly enriched in CG-rich regions and concentrated in the mRNA translation initiation regions. After OGD/R, modification level of m5C increased, whereas the number of methylated mRNA genes decreased. The amount of overlap of m5C sites with the binding sites of most RNA-binding proteins increased significantly, except for that of the RBM3-binding protein. Moreover, hypermethylated genes in neurons were significantly enriched in pathological processes, and the hub hypermethylated genes RPL8 and RPS9 identified by the protein-protein interaction network were significantly related to cerebral injury. Furthermore, the upregulated transcripts with hypermethylated modification were enriched in the processes involved in response to stress and regulation of apoptosis, and these processes were not identified in hypomethylated transcripts. In final, we verified that OGD/R induced neuronal apoptosis in vitro using TUNEL and western blot assays. Our study identified novel m5C mRNAs associated with ischemia-reperfusion in neurons, providing valuable perspectives for future studies on the role of the RNA methylation in cerebral IRI.

Prevalent intron retention fine-tunes gene expression and contributes to cellular senescence

Intron retention (IR) is the least well‐understood alternative splicing type in animals, and its prevalence and function in physiological and pathological processes have long been underestimated. Cellular senescence contributes to individual aging and age‐related diseases and can also serve as an important cancer prevention mechanism. Dynamic IR events have been observed in senescence models and aged tissues; however, whether and how IR impacts senescence remain unclear. Through analyzing polyA⁺ RNA‐seq data from human replicative senescence models, we found IR was prevalent and dynamically regulated during senescence and IR changes negatively correlated with expression alteration of corresponding genes. We discovered that knocking down (KD) splicing factor U2AF1, which showed higher binding density to retained introns and decreased expression during senescence, led to senescence‐associated phenotypes and global IR changes. Intriguingly, U2AF1‐KD‐induced IR changes also negatively correlated with gene expression. Furthermore, we demonstrated that U2AF1‐mediated IR of specific gene (CPNE1 as an example) contributed to cellular senescence. Decreased expression of U2AF1, higher IR of CPNE1, and reduced expression of CPNE1 were also discovered in dermal fibroblasts with age. We discovered prevalent IR could fine‐tune gene expression and contribute to senescence‐associated phenotypes, largely extending the biological significance of IR.

Intronic Determinants Coordinate Charme lncRNA Nuclear Activity through the Interaction with MATR3 and PTBP1

Chromatin architect of muscle expression (Charme) is a muscle-restricted long noncoding RNA (lncRNA) that plays an important role in myogenesis. Earlier evidence indicates that the nuclear Charme isoform, named pCharme, acts on the chromatin by assisting the formation of chromatin domains where myogenic transcription occurs. By combining RNA antisense purification (RAP) with mass spectrometry and loss-of-function analyses, we have now identified the proteins that assist these chromatin activities. These proteins—which include a sub-set of splicing regulators, principally PTBP1 and the multifunctional RNA/DNA binding protein MATR3—bind to sequences located within the alternatively spliced intron-1 to form nuclear aggregates. Consistent with the functional importance of pCharme interactome in vivo, a targeted deletion of the intron-1 by a CRISPR-Cas9 approach in mouse causes the release of pCharme from the chromatin and results in cardiac defects similar to what was observed upon knockout of the full-length transcript.

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pCharme is the chromatin-retained isoform of the muscle-specific Charme lncRNA

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Intronic signals coordinate the association of pCharme with MATR3 and PTBP1

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The particle assembly prompts pCharme intron-1 chromatin retention

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Deletion of the intron-1 by CRISPR-Cas9 leads to heart defects in mouse

A Survey of Regulatory Interactions Among RNA Binding Proteins and MicroRNAs in Cancer

Recent advances in genomics and proteomics generated a large amount of trans regulatory data such as those mediated by RNA binding proteins (RBPs) and microRNAs. Since many trans regulators target 3′ UTR of mRNA transcripts, it is likely that there would be interactions, i.e., competitive or cooperative effect, among these trans factors. We compiled the available RBP and microRNA binding sites, mapped them to the mRNA transcripts, and correlated the binding data with mRNA expression data generated by The Cancer Genome Atlas (TCGA). We separated pairs of RBPs and microRNAs into three scenarios: those that have overlapping target sites on the same mRNA transcript (overlapping), those that have target sites on the same mRNA transcript but non-overlapping (neighboring), and those that do not target the same mRNA transcript (independent). Through a regression analysis on expression profiles, we indeed observed interaction effect between RBPs and microRNAs in the majority of the cancer expression data sets. We further discussed implication of such widespread interactions in the context of cancer and diseases.

RADAR: annotation and prioritization of variants in the post-transcriptional regulome of RNA-binding proteins

RNA-binding proteins (RBPs) play key roles in post-transcriptional regulation and disease. Their binding sites cover more of the genome than coding exons; nevertheless, most noncoding variant prioritization methods only focus on transcriptional regulation. Here, we integrate the portfolio of ENCODE-RBP experiments to develop RADAR, a variant-scoring framework. RADAR uses conservation, RNA structure, network centrality, and motifs to provide an overall impact score. Then, it further incorporates tissue-specific inputs to highlight disease-specific variants. Our results demonstrate RADAR can successfully pinpoint variants, both somatic and germline, associated with RBP-function dysregulation, which cannot be found by most current prioritization methods, for example, variants affecting splicing.

Exosomal long noncoding RNA LNMAT2 promotes lymphatic metastasis in bladder cancer

Patients with bladder cancer (BCa) with clinical lymph node (LN) metastasis have an extremely poor prognosis. VEGF-C has been demonstrated to play vital roles in LN metastasis in BCa. However, approximately 20% of BCa with LN metastasis exhibits low VEGF-C expression, suggesting a VEGF-C-independent mechanism for LN metastasis of BCa. Herein, we demonstrate that BCa cell-secreted exosome-mediated lymphangiogenesis promoted LN metastasis in BCa in a VEGF-C-independent manner. We identified an exosomal long noncoding RNA (lncRNA), termed lymph node metastasis-associated transcript 2 (LNMAT2), that stimulated human lymphatic endothelial cell (HLEC) tube formation and migration in vitro and enhanced tumor lymphangiogenesis and LN metastasis in vivo. Mechanistically, LNMAT2 was loaded to BCa cell-secreted exosomes by directly interacting with heterogeneous nuclear ribonucleoprotein A2B1 (hnRNPA2B1). Subsequently, exosomal LNMAT2 was internalized by HLECs and epigenetically upregulated prospero homeobox 1 (PROX1) expression by recruitment of hnRNPA2B1 and increasing the H3K4 trimethylation level in the PROX1 promoter, ultimately resulting in lymphangiogenesis and lymphatic metastasis. Therefore, our findings highlight a VEGF-C-independent mechanism of exosomal lncRNA-mediated LN metastasis and identify LNMAT2 as a therapeutic target for LN metastasis in BCa.

Versatile interactions and bioinformatics analysis of noncoding RNAs

Advances in RNA sequencing technologies and computational methodologies have provided a huge impetus to noncoding RNA (ncRNA) study. Once regarded as inconsequential results of transcriptional promiscuity, ncRNAs were later found to exert great roles in various aspects of biological functions. They are emerging as key players in gene regulatory networks by interacting with other biomolecules (DNA, RNA or protein). Here, we provide an overview of ncRNA repertoire and highlight recent discoveries of their versatile interactions. To better investigate the ncRNA-mediated regulation, it is necessary to make full use of innovative sequencing techniques and computational tools. We further describe a comprehensive workflow for in silico ncRNA analysis, providing up-to-date platforms, databases and tools dedicated to ncRNA identification and functional annotation.

FUS ALS-causative mutations impair FUS autoregulation and splicing factor networks through intron retention

Mutations in the RNA-binding protein FUS cause amyotrophic lateral sclerosis (ALS), a devastating neurodegenerative disease. FUS plays a role in numerous aspects of RNA metabolism, including mRNA splicing. However, the impact of ALS-causative mutations on splicing has not been fully characterized, as most disease models have been based on overexpressing mutant FUS, which will alter RNA processing due to FUS autoregulation. We and others have recently created knockin models that overcome the overexpression problem, and have generated high depth RNA-sequencing on FUS mutants in parallel to FUS knockout, allowing us to compare mutation-induced changes to genuine loss of function. We find that FUS-ALS mutations induce a widespread loss of function on expression and splicing. Specifically, we find that mutant FUS directly alters intron retention levels in RNA-binding proteins. Moreover, we identify an intron retention event in FUS itself that is associated with its autoregulation. Altered FUS levels have been linked to disease, and we show here that this novel autoregulation mechanism is altered by FUS mutations. Crucially, we also observe this phenomenon in other genetic forms of ALS, including those caused by TDP-43, VCP and SOD1 mutations, supporting the concept that multiple ALS genes interact in a regulatory network.

RNAct: Protein-RNA interaction predictions for model organisms with supporting experimental data

Protein-RNA interactions are implicated in a number of physiological roles as well as diseases, with molecular mechanisms ranging from defects in RNA splicing, localization and translation to the formation of aggregates. Currently, ∼1400 human proteins have experimental evidence of RNA-binding activity. However, only ∼250 of these proteins currently have experimental data on their target RNAs from various sequencing-based methods such as eCLIP. To bridge this gap, we used an established, computationally expensive protein-RNA interaction prediction method, catRAPID, to populate a large database, RNAct. RNAct allows easy lookup of known and predicted interactions and enables global views of the human, mouse and yeast protein-RNA interactomes, expanding them in a genome-wide manner far beyond experimental data (http://rnact.crg.eu).

POSTAR2: deciphering the post-transcriptional regulatory logics

Post-transcriptional regulation of RNAs is critical to the diverse range of cellular processes. The volume of functional genomic data focusing on post-transcriptional regulation logics continues to grow in recent years. In the current database version, POSTAR2 (http://lulab.life.tsinghua.edu.cn/postar), we included the following new features and data: updated ∼500 CLIP-seq datasets (∼1200 CLIP-seq datasets in total) from six species, including human, mouse, fly, worm, Arabidopsis and yeast; added a new module ‘Translatome’, which is derived from Ribo-seq datasets and contains ∼36 million open reading frames (ORFs) in the genomes from the six species; updated and unified post-transcriptional regulation and variation data. Finally, we improved web interfaces for searching and visualizing protein–RNA interactions with multi-layer information. Meanwhile, we also merged our CLIPdb database into POSTAR2. POSTAR2 will help researchers investigate the post-transcriptional regulatory logics coordinated by RNA-binding proteins and translational landscape of cellular RNAs.

CircAtlas: an integrated resource of one million highly accurate circular RNAs from 1070 vertebrate transcriptomes

Existing circular RNA (circRNA) databases have become essential for transcriptomics. However, most are unsuitable for mining in-depth information for candidate circRNA prioritization. To address this, we integrate circular transcript collections to develop the circAtlas database based on 1070 RNA-seq samples collected from 19 normal tissues across six vertebrate species. This database contains 1,007,087 highly reliable circRNAs, of which over 81.3% have been assembled into full-length sequences. We profile their expression pattern, conservation, and functional annotation. We describe a novel multiple conservation score, co-expression, and regulatory networks for circRNA annotation and prioritization. CircAtlas can be accessed at http://circatlas.biols.ac.cn/.

Genetic Perturbation of TIA1 Reveals a Physiological Role in Fear Memory

TIA1 is a prion-related RNA-binding protein whose capacity to form various types of intracellular aggregates has been implicated in neurodegenerative disease. However, its role in normal brain function is poorly understood. Here, we show that TIA1 bidirectionally modulates stress-dependent synaptic plasticity in the hippocampus, a brain region involved in fear memory and olfactory discrimination learning. At the behavioral level, conditioned odor avoidance is potentiated by TIA1 deletion, whereas overexpression of TIA1 in the ventral hippocampus inhibits both contextual fear memory and avoidance. However, the latter genetic manipulations have little impact on other hippocampus-dependent tasks. Transcriptional profiling indicates that TIA1 presides over a large network of immune system genes with modulatory roles in synaptic plasticity and long-term memory. Our results uncover a physiological and partly sex-dependent function for TIA1 in fear memory and may provide molecular insight into stress-related psychiatric conditions, such as post-traumatic stress disorder (PTSD) and anxiety.

Upstream analysis of alternative splicing: a review of computational approaches to predict context-dependent splicing factors

Alternative splicing (AS) has shown to play a pivotal role in the development of diseases, including cancer. Specifically, all the hallmarks of cancer (angiogenesis, cell immortality, avoiding immune system response, etc.) are found to have a counterpart in aberrant splicing of key genes. Identifying the context-specific regulators of splicing provides valuable information to find new biomarkers, as well as to define alternative therapeutic strategies. The computational models to identify these regulators are not trivial and require three conceptual steps: the detection of AS events, the identification of splicing factors that potentially regulate these events and the contextualization of these pieces of information for a specific experiment. In this work, we review the different algorithmic methodologies developed for each of these tasks. Main weaknesses and strengths of the different steps of the pipeline are discussed. Finally, a case study is detailed to help the reader be aware of the potential and limitations of this computational approach.

Principles of RNA processing from analysis of enhanced CLIP maps for 150 RNA binding proteins

BACKGROUND

A critical step in uncovering rules of RNA processing is to study the in vivo regulatory networks of RNA binding proteins (RBPs). Crosslinking and immunoprecipitation (CLIP) methods enable mapping RBP targets transcriptome-wide, but methodological differences present challenges to large-scale analysis across datasets. The development of enhanced CLIP (eCLIP) enabled the mapping of targets for 150 RBPs in K562 and HepG2, creating a unique resource of RBP interactomes profiled with a standardized methodology in the same cell types.

RESULTS

Our analysis of 223 eCLIP datasets reveals a range of binding modalities, including highly resolved positioning around splicing signals and mRNA untranslated regions that associate with distinct RBP functions. Quantification of enrichment for repetitive and abundant multicopy elements reveals 70% of RBPs have enrichment for non-mRNA element classes, enables identification of novel ribosomal RNA processing factors and sites, and suggests that association with retrotransposable elements reflects multiple RBP mechanisms of action. Analysis of spliceosomal RBPs indicates that eCLIP resolves AQR association after intronic lariat formation, enabling identification of branch points with single-nucleotide resolution, and provides genome-wide validation for a branch point-based scanning model for 3' splice site recognition. Finally, we show that eCLIP peak co-occurrences across RBPs enable the discovery of novel co-interacting RBPs.

CONCLUSIONS

This work reveals novel insights into RNA biology by integrated analysis of eCLIP profiling of 150 RBPs with distinct functions. Further, our quantification of both mRNA and other element association will enable further research to identify novel roles of RBPs in regulating RNA processing.

Epigenetic Silencing of CDR1as Drives IGF2BP3-Mediated Melanoma Invasion and Metastasis

Metastasis is the primary cause of death of cancer patients. Dissecting mechanisms governing metastatic spread may uncover important tumor biology and/or yield promising therapeutic insights. Here, we investigated the role of circular RNAs (circRNA) in metastasis, using melanoma as a model aggressive tumor. We identified silencing of cerebellar degeneration-related 1 antisense (CDR1as), a regulator of miR-7, as a hallmark of melanoma progression. CDR1as depletion results from epigenetic silencing of LINC00632, its originating long non-coding RNA (lncRNA) and promotes invasion in vitro and metastasis in vivo through a miR-7-independent, IGF2BP3-mediated mechanism. Moreover, CDR1as levels reflect cellular states associated with distinct therapeutic responses. Our study reveals functional, prognostic, and predictive roles for CDR1as and expose circRNAs as key players in metastasis.

Accurate quantification of circular RNAs identifies extensive circular isoform switching events

Detection and quantification of circular RNAs (circRNAs) face several significant challenges, including high false discovery rate, uneven rRNA depletion and RNase R treatment efficiency, and underestimation of back-spliced junction reads. Here, we propose a novel algorithm, CIRIquant, for accurate circRNA quantification and differential expression analysis. By constructing pseudo-circular reference for re-alignment of RNA-seq reads and employing sophisticated statistical models to correct RNase R treatment biases, CIRIquant can provide more accurate expression values for circRNAs with significantly reduced false discovery rate. We further develop a one-stop differential expression analysis pipeline implementing two independent measures, which helps unveil the regulation of competitive splicing between circRNAs and their linear counterparts. We apply CIRIquant to RNA-seq datasets of hepatocellular carcinoma, and characterize two important groups of linear-circular switching and circular transcript usage switching events, which demonstrate the promising ability to explore extensive transcriptomic changes in liver tumorigenesis.

Quantification and characterization of circRNAs in sequencing data remains challenging, hindering efforts to understand their roles and regulation. The algorithm introduced here enables accurate circRNA quantification and permits insight into competitive splicing between linear and circular isoforms.

Multimodal Long Noncoding RNA Interaction Networks: Control Panels for Cell Fate Specification

Lineage specification in early development is the basis for the exquisitely precise body plan of multicellular organisms. It is therefore critical to understand cell fate decisions in early development. Moreover, for regenerative medicine, the accurate specification of cell types to replace damaged/diseased tissue is strongly dependent on identifying determinants of cell identity. Long noncoding RNAs (lncRNAs) have been shown to regulate cellular plasticity, including pluripotency establishment and maintenance, differentiation and development, yet broad phenotypic analysis and the mechanistic basis of their function remains lacking. As components of molecular condensates, lncRNAs interact with almost all classes of cellular biomolecules, including proteins, DNA, mRNAs, and microRNAs. With functions ranging from controlling alternative splicing of mRNAs, to providing scaffolding upon which chromatin modifiers are assembled, it is clear that at least a subset of lncRNAs are far from the transcriptional noise they were once deemed. This review highlights the diversity of lncRNA interactions in the context of cell fate specification, and provides examples of each type of interaction in relevant developmental contexts. Also highlighted are experimental and computational approaches to study lncRNAs.

Investigation of RNA Editing Sites within Bound Regions of RNA-Binding Proteins

Studies in epitranscriptomics indicate that RNA is modified by a variety of enzymes. Among these RNA modifications, adenosine to inosine (A-to-I) RNA editing occurs frequently in the mammalian transcriptome. These RNA editing sites can be detected directly from RNA sequencing (RNA-seq) data by examining nucleotide changes from adenosine (A) to guanine (G), which substitutes for inosine (I). However, a careful investigation of such nucleotide changes must be conducted to distinguish sequencing errors and genomic mutations from the genuine editing sites. Building upon our recent introduction of an easy-to-use bioinformatics tool, RNA Editor, to detect RNA editing events from RNA-seq data, we examined the extent by which RNA editing events affect the binding of RNA-binding proteins (RBP). Through employing bioinformatic techniques, we uncovered that RNA editing sites occur frequently in RBP-bound regions. Moreover, the presence of RNA editing sites are more frequent when RNA editing islands were examined, which are regions in which RNA editing sites are present in clusters. When the binding of one RBP, human antigen R [HuR; encoded by ELAV-like protein 1 (ELAV1)], was quantified experimentally, its binding was reduced upon silencing of the RNA editing enzyme adenosine deaminases acting on RNA (ADAR) compared to the control-suggesting that the presence of RNA editing islands influence HuR binding to its target regions. These data indicate RNA editing as an important mediator of RBP-RNA interactions-a mechanism which likely constitutes an additional mode of post-transcription gene regulation in biological systems.

Comprehensive Analysis of Human microRNA-mRNA Interactome

MicroRNAs play a key role in the regulation of gene expression. A majority of microRNA–mRNA interactions remain unidentified. Despite extensive research, our ability to predict human microRNA-mRNA interactions using computational algorithms remains limited by a complexity of the models for non-canonical interactions, and an abundance of false-positive results. Here, we present the landscape of human microRNA–mRNA interactions derived from comprehensive analysis of HEK293 and Huh7.5 datasets, along with publicly available microRNA and mRNA expression data. We show that, while only 1–2% of human genes were the most regulated by microRNAs, few cell line–specific RNAs, including EEF1A1 and HSPA1B in HEK293 and AFP, APOB, and MALAT1 genes in Huh7.5, display substantial “sponge-like” properties. We revealed a group of microRNAs that are expressed at a very high level, while interacting with only a few mRNAs, which, indeed, serve as their specific expression regulators. In order to establish reliable microRNA-binding regions, we collected and systematically analyzed the data from 79 CLIP datasets of microRNA-binding sites. We report 46,805 experimentally confirmed mRNA–miRNA duplex regions. Resulting dataset is available at http://score.generesearch.ru/services/mirna/. Our study provides initial insight into the complexity of human microRNA–mRNA interactions.

Widespread Translational Control of Fibrosis in the Human Heart by RNA-Binding Proteins

Supplemental Digital Content is available in the text.

Fibrosis is a common pathology in many cardiac disorders and is driven by the activation of resident fibroblasts. The global posttranscriptional mechanisms underlying fibroblast-to-myofibroblast conversion in the heart have not been explored.