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Circular RNAs (circRNAs), which are single-stranded RNA molecules that have individually formed into a covalently closed continuous loop, act as sponges of microRNAs to regulate transcription and translation. CircRNAs are important molecules in the field of cancer diagnosis, as growing evidence suggests that they are closely related to pathological cancer features. Therefore, they have high potential for clinical use as novel cancer biomarkers. In this article, we present our updates to CircNet (version 2.0), into which circRNAs from circAtlas and MiOncoCirc, and novel circRNAs from The Cancer Genome Atlas database have been integrated. In total, 2732 samples from 37 types of cancers were integrated into CircNet 2.0 and analyzed using several of the most reliable circRNA detection algorithms. Furthermore, target miRNAs were predicted from the full-length circRNA sequence using three reliable tools (PITA, miRanda and TargetScan). Additionally, 384 897 experimentally verified miRNA-target interactions from miRTarBase were integrated into our database to facilitate the construction of high-quality circRNA-miRNA-gene regulatory networks. These improvements, along with the user-friendly interactive web interface for data presentation, search, and visualization, showcase the updated CircNet database as a powerful, experimentally validated resource, for providing strong data support in the biomedical fields. CircNet 2.0 is currently accessible at https://awi.cuhk.edu.cn/∼CircNet., (© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.)

The significant function of circRNAs in cancer was recognized in recent work, so a well-organized resource is required for characterizing the interactions between circRNAs and other functional molecules (such as microRNA and RNA-binding protein) in cancer. We previously developed cancer-specific circRNA database (CSCD), a comprehensive database for cancer-specific circRNAs, which is widely used in circRNA research. Here, we updated CSCD to CSCD2 (http://geneyun.net/CSCD2 or http://gb.whu.edu.cn/CSCD2), which includes significantly more cancer-specific circRNAs identified from a large number of human cancer and normal tissues/cell lines. CSCD2 contains >1000 samples (825 tissues and 288 cell lines) and identifies a large number of circRNAs: 1 013 461 cancer-specific circRNAs, 1 533 704 circRNAs from only normal samples and 354 422 circRNAs from both cancer and normal samples. In addition, CSCD2 predicts potential miRNA-circRNA and RBP-circRNA interactions using binding motifs from >200 RBPs and 2000 microRNAs. Furthermore, the potential full-length and open reading frame sequence of these circRNAs were also predicted. Collectively, CSCD2 provides a significantly enhanced resource for exploring the function and regulation of circRNAs in cancer., (© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Extracellular vesicles (EVs) are small membranous vesicles that contain an abundant cargo of different RNA species with specialized functions and clinical implications. Here, we introduce an updated online database (http://www.exoRBase.org), exoRBase 2.0, which is a repository of EV long RNAs (termed exLRs) derived from RNA-seq data analyses of diverse human body fluids. In exoRBase 2.0, the number of exLRs has increased to 19 643 messenger RNAs (mRNAs), 15 645 long non-coding RNAs (lncRNAs) and 79 084 circular RNAs (circRNAs) obtained from ∼1000 human blood, urine, cerebrospinal fluid (CSF) and bile samples. Importantly, exoRBase 2.0 not only integrates and compares exLR expression profiles but also visualizes the pathway-level functional changes and the heterogeneity of origins of circulating EVs in the context of different physiological and pathological conditions. Our database provides an attractive platform for the identification of novel exLR signatures from human biofluids that will aid in the discovery of new circulating biomarkers to improve disease diagnosis and therapy., (© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.)

We introduce ViroidDB, a value-added database that attempts to collect all known viroid and viroid-like circular RNA sequences into a single resource. Spanning about 10 000 unique sequences, ViroidDB includes viroids, retroviroid-like elements, small circular satellite RNAs, ribozyviruses, and retrozymes. Each sequence's secondary structure, ribozyme content, and cluster membership are predicted via a custom pipeline optimized for handling circular RNAs. The data can be explored via a purpose-built user interface that features visualizations, multiple sequence alignments, and a portal for downloading bulk data. Users can browse the data by sequence type, taxon, or typo-tolerant search of metadata fields. The database is freely accessible at https://viroids.org., (Published by Oxford University Press on behalf of Nucleic Acids Research 2021.)

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., (© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Many circRNA transcriptome data were deposited in public resources, but these data show great heterogeneity. Researchers without bioinformatics skills have difficulty in investigating these invaluable data or their own data. Here, we specifically designed circMine (http://hpcc.siat.ac.cn/circmine and http://www.biomedical-web.com/circmine/) that provides 1 821 448 entries formed by 136 871 circRNAs, 87 diseases and 120 circRNA transcriptome datasets of 1107 samples across 31 human body sites. circMine further provides 13 online analytical functions to comprehensively investigate these datasets to evaluate the clinical and biological significance of circRNA. To improve the data applicability, each dataset was standardized and annotated with relevant clinical information. All of the 13 analytic functions allow users to group samples based on their clinical data and assign different parameters for different analyses, and enable them to perform these analyses using their own circRNA transcriptomes. Moreover, three additional tools were developed in circMine to systematically discover the circRNA-miRNA interaction and circRNA translatability. For example, we systematically discovered five potential translatable circRNAs associated with prostate cancer progression using circMine. In summary, circMine provides user-friendly web interfaces to browse, search, analyze and download data freely, and submit new data for further integration, and it can be an important resource to discover significant circRNA in different diseases., (© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Circular RNA (circRNA) is a distinguishable circular formed long non-coding RNA (lncRNA), which has specific roles in transcriptional regulation, multiple biological processes. The identification of circRNA from other lncRNA is necessary for relevant research. In this study, we designed attention-based multi-instance learning (MIL) network architecture fed with a raw sequence, to learn the sparse features of RNA sequences and to accomplish the circRNAs identification task. The model outperformed the state-of-art models. Moreover, following the validation of the attention mechanism effectiveness by the handwritten digit dataset, the key sequence loci underlying circRNA's recognition were obtained based on the corresponding attention score. Then, motif enrichment analysis identified some of the key motifs for circRNA formation. In conclusion, we designed deep learning network architecture suitable for learning gene sequences with sparse features and implemented it for the circRNA identification task, and the model has strong representation capability in the indication of some key loci.

Emerging research shows that circular RNA (circRNA) plays a crucial role in the diagnosis, occurrence and prognosis of complex human diseases. Compared with traditional biological experiments, the computational method of fusing multi-source biological data to identify the association between circRNA and disease can effectively reduce cost and save time. Considering the limitations of existing computational models, we propose a semi-supervised generative adversarial network (GAN) model SGANRDA for predicting circRNA-disease association. This model first fused the natural language features of the circRNA sequence and the features of disease semantics, circRNA and disease Gaussian interaction profile kernel, and then used all circRNA-disease pairs to pre-train the GAN network, and fine-tune the network parameters through labeled samples. Finally, the extreme learning machine classifier is employed to obtain the prediction result. Compared with the previous supervision model, SGANRDA innovatively introduced circRNA sequences and utilized all the information of circRNA-disease pairs during the pre-training process. This step can increase the information content of the feature to some extent and reduce the impact of too few known associations on the model performance. SGANRDA obtained AUC scores of 0.9411 and 0.9223 in leave-one-out cross-validation and 5-fold cross-validation, respectively. Prediction results on the benchmark dataset show that SGANRDA outperforms other existing models. In addition, 25 of the top 30 circRNA-disease pairs with the highest scores of SGANRDA in case studies were verified by recent literature. These experimental results demonstrate that SGANRDA is a useful model to predict the circRNA-disease association and can provide reliable candidates for biological experiments., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

As consequence of the various genomic sequencing projects, an increasing volume of biological sequence data is being produced. Although machine learning algorithms have been successfully applied to a large number of genomic sequence-related problems, the results are largely affected by the type and number of features extracted. This effect has motivated new algorithms and pipeline proposals, mainly involving feature extraction problems, in which extracting significant discriminatory information from a biological set is challenging. Considering this, our work proposes a new study of feature extraction approaches based on mathematical features (numerical mapping with Fourier, entropy and complex networks). As a case study, we analyze long non-coding RNA sequences. Moreover, we separated this work into three studies. First, we assessed our proposal with the most addressed problem in our review, e.g. lncRNA and mRNA; second, we also validate the mathematical features in different classification problems, to predict the class of lncRNA, e.g. circular RNAs sequences; third, we analyze its robustness in scenarios with imbalanced data. The experimental results demonstrated three main contributions: first, an in-depth study of several mathematical features; second, a new feature extraction pipeline; and third, its high performance and robustness for distinct RNA sequence classification. Availability:https://github.com/Bonidia/FeatureExtraction_BiologicalSequences., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Noncoding RNAs, including microRNAs (miRNAs), small interference RNAs (siRNAs), circular RNA (circRNA), and long noncoding RNAs (lncRNAs), control gene expression at the transcription, post-transcription, and translation levels. Apart from protein-coding genes, accumulating evidence supports ncRNAs playing a critical role in shaping plant growth and development and biotic and abiotic stress responses in various species, including legume crops. Noncoding RNAs (ncRNAs) interact with DNA, RNA, and proteins, modulating their target genes. However, the regulatory mechanisms controlling these cellular processes are not well understood. Here, we discuss the features of various ncRNAs, including their emerging role in contributing to biotic/abiotic stress response and plant growth and development, in addition to the molecular mechanisms involved, focusing on legume crops. Unravelling the underlying molecular mechanisms and functional implications of ncRNAs will enhance our understanding of the coordinated regulation of plant defences against various biotic and abiotic stresses and for key growth and development processes to better design various legume crops for global food security.

Circular RNAs (circRNAs) are a class of endogenous noncoding RNA, which were previously considered as a byproduct of RNA splicing error. Numerous studies have demonstrated the altered expression of circRNAs in organ tissues during pathological conditions and their involvements in disease pathogenesis and progression, including cancers. In colorectal cancer (CRC), multiple circRNAs have been identified and characterized as "oncogenic", given their involvements in the downregulation of tumor suppressor genes and induction of tumor initiation, progression, invasion, and metastasis. Additionally, other circRNAs have been identified in CRC and characterized as "tumor suppressive" based on their ability of inhibiting the expression of oncogenic genes and suppressing tumor growth and proliferation. circRNAs could serve as potential diagnostic and prognostic biomarkers, and therapeutic targets or vectors to be utilized in cancer therapies. This review briefly describes the dynamic changes of the tumor microenvironment inducing immunosuppression and tumorigenesis, and outlines the biogenesis and characteristics of circRNAs and recent findings indicating their roles and functions in the CRC tumor microenvironment. It also discusses strategies and technologies, which could be employed in the future to overcome current cancer therapy challenges associated with circRNAs., (Copyright © 2021 The Authors. Published by Elsevier Masson SAS.. All rights reserved.)

Transcription factor p63 has critical functions in epidermal, hindgut/anorectal, and limb development. Human mutations in P63 correlate with congenital syndromes affecting the skin, anorectal, and limbs. Nevertheless, less are detected regarding networks and functions controlled by P63 mutations in dermal fibroblasts, which are closely related to skin physiology. To screen for new targets, we employed microarray technology to investigate the R226Q P63 mutation with regards to the resulting circular RNA (circRNA) profiles from P63 point mutations in human dermal fibroblasts (HDFs). In this study, we show that P63-mutant HDFs display reduced proliferation, collagen synthesis, and myofibroblast differentiation; circAMD1 was also downregulated in P63-mutant HDFs compared with wild-type HDFs. Furthermore, overexpressing circAMD1 rescued the functional and phenotypic alterations of p63-mutant HDFs. We as well determined that miR-27a-3p was circAMD1 target involved in effects of circAMD1 in P63-mutant HDFs. Collectively, our data show that circAMD1 functions as a miR-27a-3p sponge that inhibits the functional and phenotypical alteration of P63-mutant HDFs and may be a critical marker in pathogenesis regarding P63-associated traits., (Copyright © 2021. Published by Elsevier B.V.)

Objective: Intracranial aneurysm (IA) is a fatal disease owing to vascular rupture and subarachnoid hemorrhage. Much attention has been given to circular RNAs (circRNAs) because they may be potential biomarkers for many diseases, but their mechanism in the formation of IA remains unknown., Methods: circRNA expression profile analysis of blood samples was conducted between patients with IA and controls. Overall, 235 differentially expressed circRNAs were confirmed between IA patients and the control group. The reliability of the microarray results was demonstrated by quantitative real-time polymerase chain reaction (qRT-PCR)., Results: Of 235 differentially expressed genes, 150 were upregulated, while the other 85 were downregulated. Five miRNAs matched to every differential expression of circRNAs, and related MREs were predicted. We performed gene ontology (GO) analysis to identify the functions of their targeted genes, with the terms "Homophilic cell adhesion via plasma membrane adhesion molecules" and "Positive regulation of cellular process" showing the highest fold enrichment., Conclusions: This study demonstrated the role of circRNA expression profiling in the formation of IA and revealed that the mTOR pathway can be a latent therapeutic strategy for IA., Competing Interests: The authors have no financial conflicts of interest., (Copyright © 2021 Yonggang Ma et al.)

An updated Lnc2Cancer 3.0 (http://www.bio-bigdata.net/lnc2cancer or http://bio-bigdata.hrbmu.edu.cn/lnc2cancer) database, which includes comprehensive data on experimentally supported long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) associated with human cancers. In addition, web tools for analyzing lncRNA expression by high-throughput RNA sequencing (RNA-seq) and single-cell RNA-seq (scRNA-seq) are described. Lnc2Cancer 3.0 was updated with several new features, including (i) Increased cancer-associated lncRNA entries over the previous version. The current release includes 9254 lncRNA-cancer associations, with 2659 lncRNAs and 216 cancer subtypes. (ii) Newly adding 1049 experimentally supported circRNA-cancer associations, with 743 circRNAs and 70 cancer subtypes. (iii) Experimentally supported regulatory mechanisms of cancer-related lncRNAs and circRNAs, involving microRNAs, transcription factors (TF), genetic variants, methylation and enhancers were included. (iv) Appending experimentally supported biological functions of cancer-related lncRNAs and circRNAs including cell growth, apoptosis, autophagy, epithelial mesenchymal transformation (EMT), immunity and coding ability. (v) Experimentally supported clinical relevance of cancer-related lncRNAs and circRNAs in metastasis, recurrence, circulation, drug resistance, and prognosis was included. Additionally, two flexible online tools, including RNA-seq and scRNA-seq web tools, were developed to enable fast and customizable analysis and visualization of lncRNAs in cancers. Lnc2Cancer 3.0 is a valuable resource for elucidating the associations between lncRNA, circRNA and cancer., (© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Many studies have indicated that non-coding RNA (ncRNA) dysfunction is closely related to numerous diseases. Recently, accumulated ncRNA-disease associations have made related databases insufficient to meet the demands of biomedical research. The constant updating of ncRNA-disease resources has become essential. Here, we have updated the mammal ncRNA-disease repository (MNDR, http://www.rna-society.org/mndr/) to version 3.0, containing more than one million entries, four-fold increment in data compared to the previous version. Experimental and predicted circRNA-disease associations have been integrated, increasing the number of categories of ncRNAs to five, and the number of mammalian species to 11. Moreover, ncRNA-disease related drug annotations and associations, as well as ncRNA subcellular localizations and interactions, were added. In addition, three ncRNA-disease (miRNA/lncRNA/circRNA) prediction tools were provided, and the website was also optimized, making it more practical and user-friendly. In summary, MNDR v3.0 will be a valuable resource for the investigation of disease mechanisms and clinical treatment strategies., (© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.)

We describe an updated comprehensive database, LincSNP 3.0 (http://bioinfo.hrbmu.edu.cn/LincSNP), which aims to document and annotate disease or phenotype-associated variants in human long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) or their regulatory elements. LincSNP 3.0 has updated with several novel features, including (i) more types of variants including single nucleotide polymorphisms (SNPs), linkage disequilibrium SNPs (LD SNPs), somatic mutations and RNA editing sites have been expanded; (ii) more regulatory elements including transcription factor binding sites (TFBSs), enhancers, DNase I hypersensitive sites (DHSs), topologically associated domains (TADs), footprintss, methylations and open chromatin regions have been added; (iii) the associations among circRNAs, regulatory elements and variants have been identified; (iv) more experimentally supported variant-lncRNA/circRNA-disease/phenotype associations have been manually collected; (v) the sources of lncRNAs, circRNAs, SNPs, somatic mutations and RNA editing sites have been updated. Moreover, four flexible online tools including Genome Browser, Variant Mapper, Circos Plotter and Functional Annotation have been developed to retrieve, visualize and analyze the data. Collectively, LincSNP 3.0 provides associations among functional variants, regulatory elements, lncRNAs and circRNAs in diseases. It will serve as an important and continually updated resource for investigating functions and mechanisms of lncRNAs and circRNAs in diseases., (© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.)

RNA endowed with both protein-coding and noncoding functions is referred to as 'dual-function RNA', 'binary functional RNA (bifunctional RNA)' or 'cncRNA (coding and noncoding RNA)'. Recently, an increasing number of cncRNAs have been identified, including both translated ncRNAs (ncRNAs with coding functions) and untranslated mRNAs (mRNAs with noncoding functions). However, an appropriate database for storing and organizing cncRNAs is still lacking. Here, we developed cncRNAdb, a manually curated database of experimentally supported cncRNAs, which aims to provide a resource for efficient manipulation, browsing and analysis of cncRNAs. The current version of cncRNAdb documents about 2600 manually curated entries of cncRNA functions with experimental evidence, involving more than 2,000 RNAs (including over 1300 translated ncRNAs and over 600 untranslated mRNAs) across over 20 species. In summary, we believe that cncRNAdb will help elucidate the functions and mechanisms of cncRNAs and develop new prediction methods. The database is available at http://www.rna-society.org/cncrnadb/., (© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Long non-coding RNAs (lncRNAs) play important functional roles in many diverse biological processes. However, not all expressed lncRNAs are functional. Thus, it is necessary to manually collect all experimentally validated functional lncRNAs (EVlncRNA) with their sequences, structures, and functions annotated in a central database. The first release of such a database (EVLncRNAs) was made using the literature prior to 1 May 2016. Since then (till 15 May 2020), 19 245 articles related to lncRNAs have been published. In EVLncRNAs 2.0, these articles were manually examined for a major expansion of the data collected. Specifically, the number of annotated EVlncRNAs, associated diseases, lncRNA-disease associations, and interaction records were increased by 260%, 320%, 484% and 537%, respectively. Moreover, the database has added several new categories: 8 lncRNA structures, 33 exosomal lncRNAs, 188 circular RNAs, and 1079 drug-resistant, chemoresistant, and stress-resistant lncRNAs. All records have checked against known retraction and fake articles. This release also comes with a highly interactive visual interaction network that facilitates users to track the underlying relations among lncRNAs, miRNAs, proteins, genes and other functional elements. Furthermore, it provides links to four new bioinformatics tools with improved data browsing and searching functionality. EVLncRNAs 2.0 is freely available at https://www.sdklab-biophysics-dzu.net/EVLncRNAs2/., (© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Circular RNA (circRNA) plays an important role in the regulation of multiple biological processes. However, circRNA profiling and the potential biological role of circRNA in influenza A virus (IAV)-induced lung injury have not been investigated. In the present study, circRNA expression profiles in lung tissues from mice with and without IAV-induced lung injury were analyzed using high-throughput sequencing, and differentially expressed circRNAs were verified by quantitative PCR. The gene homology of candidate circRNAs was investigated and the expression of plasma circRNAs from patients with IAV-induced acute respiratory distress syndrome (ARDS) was detected. The target microRNAs (miRNAs) of circRNAs were predicted. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed. In total, 781 circRNAs were differentially expressed between ARDS mice and control (467 were up-regulated and 314 were down-regulated). Moreover, the candidate circRNAs (Slco3a1, Nfatc2, Wdr33, and Dmd) expression showed the same trend with the sequencing results. The isoforms of circRNA Slco3a1 and Wdr33 were highly conserved between humans and mice. Plasma circRNA Slco3a1 and Wdr33 presented differential expression in patients with IAV-induced ARDS compared to control. The circRNAmiRNA interaction network and GO and KEGG analyses indicated the potential biological role of circRNAs in the development of IAV-induced lung injury. Taken together, a large number of differentially expressed circRNAs were identified in our study. CircRNA Slco3a1 and Wdr33 had significantly different expression in specimens from mice and humans, and showed a potential biological role in IAV-induced lung injury by bioinformatics analysis.

As one of the most prevalent gastrointestinal diseases, gastric cancer (GC) is the second leading cause of cancer-related deaths worldwide. Since GC has no clinical manifestations in the early stage of the disease, most patients are detected in the later phases of disease and have an unfortunately lower chance of recovery. Circular RNAs (circRNAs), a novel category of non-coding RNAs (ncRNAs), are mainly engaged in the regulation of gene expression at the transcriptional and post-transcriptional levels. Numerous evidences have revealed that circRNAs play key roles in GC as they are involved in cell proliferation, growth, and apoptosis via modulating the expression of some target genes, miRNAs, and proteins. Many studies have addressed the impact of circRNA dysregulation on GC initiation, progression, and invasion via binding to miRNAs or RNA binding proteins. Moreover, changes in circRNA expression are associated with pathological and clinical features of GC highlighting their potentials as diagnostic or prognostic biomarkers in GC. In the current study, the recent findings on the significance of circRNAs in the development and progression of GC are reviewed. We focus on the implications of circRNAs as potential diagnostic or prognostic biomarkers in this malignancy.

Circular RNAs (circRNAs) encompass a widespread and conserved class of RNAs, which are generated by back-splicing of downstream 5' to upstream 3' splice sites. CircRNAs are tissue-specific and have been implicated in diseases including cancer. They can function as sponges for microRNAs (miRNAs) or RNA binding proteins (RBPs), for example. Moreover, some contain open reading frames (ORFs) and might be translated. The functional relevance of such peptides, however, remains largely elusive. Here, we report that the ORF of circZNF609 is efficiently translated when expressed from a circZNF609 overexpression construct. However, endogenous proteins could not be detected. Moreover, initiation of circZNF609 translation is independent of m6A-generating enzyme METTL3 or RNA sequence elements such as internal ribosome entry sites (IRESs). Surprisingly, a comprehensive mutational analysis revealed that deletion constructs, which are deficient in producing circZNF609, still generate the observed protein products. This suggests that the apparent circZNF609 translation originates from trans-splicing by-products of the overexpression plasmids and underline that circRNA overexpression constructs need to be evaluated carefully, particularly when functional studies are performed., (© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.)

BACKGROUND Gastric cancer (GC) remains one of the most fatal digestive cancers in the world; nevertheless, its etiology remains vague. With the development of bioinformatics analysis, numerous circular RNAs (circRNAs) have been found to be dysregulated in GC. However, the functions of a large portion of dysregulated circRNAs in GC need further validation. In this study, we aimed to validate the biological functions of circ_0005556, which was previously identified to be dysregulated in GC. MATERIAL AND METHODS Levels of circRNAs and miRNAs in GC tissues and cells were estimated by qRT-PCR. The target miRNAs of circ_0005556 were predicted by bioinformatics methods. The interplay between circ_0005556 and miR-767-5p was validated by dual-luciferase reporter and circRNA immunoprecipitation assays. The effects of circ_0005556 and miR-767-5p on GC cell viability, apoptosis, migration, and invasion were assessed by MTT, flow cytometry, wound-healing and in vitro transwell experiments, respectively. RESULTS The upregulation of circ_0005556 was validated by qRT-PCR in GC tissues and cells, and a higher circ_0005556 level indicated a poorer prognosis. miR-767-5p was demonstrated to target circ_0005556 in GC cells, and a negative correlation was found between their expression levels in GC tissues. Knockdown of circ_0005556 promoted miR-767-5p expression in GC cells. Knockdown of circ_0005556 was revealed to repress GC cell viability, invasion, and migration and to promote GC cell apoptosis. Moreover, overexpression of miR-767-5p could significantly augment the repressive impacts of circ_0005556 knockdown on GC cell progression in vitro. CONCLUSIONS The in vitro knockdown of circ_0005556 remarkably repressed GC cell progression by increasing the expression of miR-767-5p.

In recent years, accumulating evidences have shown that microRNA (miRNA) plays an important role in the exploration and treatment of diseases, so detection of the associations between miRNA and disease has been drawn more and more attentions. However, traditional experimental methods have the limitations of high cost and time- consuming, a computational method can help us more systematically and effectively predict the potential miRNA-disease associations. In this work, we proposed a novel network embedding-based heterogeneous information integration method to predict miRNA-disease associations. More specifically, a heterogeneous information network is constructed by combining the known associations among lncRNA, drug, protein, disease, and miRNA. After that, the network embedding method Learning Graph Representations with Global Structural Information (GraRep) is employed to learn embeddings of nodes in heterogeneous information network. In this way, the embedding representations of miRNA and disease are integrated with the attribute information of miRNA and disease (e.g. miRNA sequence information and disease semantic similarity) to represent miRNA-disease association pairs. Finally, the Random Forest (RF) classifier is used for predicting potential miRNA-disease associations. Under the 5-fold cross validation, our method obtained 85.11% prediction accuracy with 80.41% sensitivity at the AUC of 91.25%. In addition, in case studies of three major Human diseases, 45 (Colon Neoplasms), 42 (Breast Neoplasms) and 44 (Esophageal Neoplasms) of top-50 predicted miRNAs are respectively verified by other miRNA-disease association databases. In conclusion, the experimental results suggest that our method can be a powerful and useful tool for predicting potential miRNA-disease associations.

Introduction : In recent years, circular RNAs (circRNAs) have emerged in the field of RNA research and their biological functions are now being gradually identified. circRNAs are divided into three categories: exonic circular RNAs (ecircRNAs), exon-intron circular RNAs (EIciRNAs), and intronic circular RNAs (ciRNAs). The circular structure of circRNAs confers unique biological characteristics upon them, such as enhanced stability over linear RNAs. Areas covered : circRNAs function to competitively bind with microRNAs (miRNAs) and proteins, participate in protein coding, regulate transcription, and form pseudogenes after reverse transcription. In gastric cancer, the circRNA-miRNA-mRNA axis is the most studied mechanisms underlying gastric cancer occurrence and development. Some specific and sensitive circRNAs, such as hsa_circ_102958, hsa_circ_0000520, and hsa_circ_0001017 may have potential diagnostic potential in early-stage gastric cancer. Abnormal expression of some circRNAs, including circ-LMTK2, circ-PSMC3, and circ-DLST are associated with the development of gastric cancer. Other circRNAs, such as hsa_circ_0001368, circ-ZFR, and circ-ERBB2, may also play important roles in gastric cancer treatment. Expert opinion : Exploring the roles of circRNAs in gastric cancer occurrence and development will help us to elucidate the functions of circRNAs and develop potential tools for early diagnosis and effective treatment of gastric cancer.

Non-coding regulatory RNAs are generated as a core output of the eukaryotic genomes, being essential players in cell biology. At the organism level, they are key functional actors in those tissues and organs with limited proliferation capabilities such as the heart. The role of regulatory networks mediated by non-coding RNAs in the pathophysiology of cardiovascular conditions is starting to be unveiled. However, a deeper knowledge of the functional interactions among the diverse non-coding RNA families and their phenotypic consequences is required. This review presents the current knowledge about the functional crosstalk between circRNAs and other biomolecules in the framework of the cardiovascular diseases.

Motivation: Over the past two decades, a circular form of RNA (circular RNA), produced through alternative splicing, has become the focus of scientific studies due to its major role as a microRNA (miRNA) activity modulator and its association with various diseases including cancer. Therefore, the detection of circular RNAs is vital to understanding their biogenesis and purpose. Prediction of circular RNA can be achieved in three steps: distinguishing non-coding RNAs from protein coding gene transcripts, separating short and long non-coding RNAs and predicting circular RNAs from other long non-coding RNAs (lncRNAs). However, the available tools are less than 80 percent accurate for distinguishing circular RNAs from other lncRNAs due to difficulty of classification. Therefore, the availability of a more accurate and fast machine learning method for the identification of circular RNAs, which considers the specific features of circular RNA, is essential to the development of systematic annotation., Results: Here we present an End-to-End deep learning framework, circDeep, to classify circular RNA from other lncRNA. circDeep fuses an RCM descriptor, ACNN-BLSTM sequence descriptor and a conservation descriptor into high level abstraction descriptors, where the shared representations across different modalities are integrated. The experiments show that circDeep is not only faster than existing tools but also performs at an unprecedented level of accuracy by achieving a 12 percent increase in accuracy over the other tools., Availability and Implementation: https://github.com/UofLBioinformatics/circDeep., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2019. Published by Oxford University Press.)

Circular RNAs (circRNAs) have a covalently closed circular conformation and are structurally stable. Those circRNAs with tumor-suppressive properties play an important role in tumorigenesis and metastasis and thus may be used as therapeutic targets of cancers. Herein, we review the current understanding of the classification of circRNAs and summarize the functions and mechanisms of circRNAs that have tumor-suppressive roles in various cancers, including liver cancer (circARSP91, circADAMTS13, circADAMTS14, circMTO1, hsa_circ_0079299, and circC3P1), bladder cancer (circFNDC3B, circITCH, circHIPK3, circRNA-3, cdrlas, and circLPAR1), gastric cancer (circLARP4, circYAP1, hsa_cric_0000096, hsa_circ_0000993, and circPSMC3), breast cancer (circ_000911, hsa_circ_0072309, and circASS1), lung cancer (hsa_circ_0000977, circPTK2, circ_0001649, hsa_circ_100395, and circ_0006916), glioma (circ_0001946, circSHPRH, and circFBXW7), and colorectal cancer (circITGA7 and hsa_circ_0014717). Thanks to their structural stability, these tumor-suppressive circRNAs may be used as potential and potent therapeutic targets. Moreover, we propose a new method for the classification of circRNAs. Based on whether they can be translated, circRNAs can be divided into noncoding circRNAs and coding circRNAs., (© 2019 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.)

Circular RNAs (circRNAs) are abundantly expressed in the haematopoietic compartment, but knowledge on their diversity among blood cell types is still limited. Nevertheless, emerging data indicate an array of circRNA functions exerted through interactions with other RNAs and proteins, by translation into peptides, and circRNA involvement as regulatory molecules in many biological processes and cancer mechanisms. Interestingly, the role of specific circRNAs in leukemogenesis has been disclosed by a few studies, mostly in acute myeloid leukemia. In this study, circRNA expression in B-cells, T-cells and monocytes of healthy subjects is described, including putative new circRNA genes. Expression comparison considered 6,228 circRNAs and highlighted cell population-specific expression and exon usage patterns. Differential expression has been confirmed by qRT-PCR for circRNAs specific of B-cells (circPAX5, circAFF3, circIL4R, and circSETBP1) or T-cells (circIKZF1, circTNIK, circTXK, and circFBXW7), and for circRNAs from intronic (circBCL2) and intergenic regions that were overexpressed in lymphocytes. Starting from this resource of circRNA expression in mature blood cell populations, targeted examination identified striking and generalized upregulated expression of circPAX5, circPVT1 and circHIPK3 in pediatric B-precursor acute lymphoblastic leukemia, and disclosed circRNAs with variable expression across cytogenetic subtypes.

Osteoarthritis (OA) is the utmost commonly arising joint disease. Knee condyles play an essential role during OA progression. Circular RNA (or circRNA) is a novel kind of RNA, which, unlike the well-known linear RNA, plays an important regulatory role in OA on the basis of a previous research. In our study, expression of circRNAs in OA knee condyle was measured by illumine sequencing platform. A total of 197 differentially expressed circRNAs, such as hg38_circ_0007474 and hg38_circ_0000118 were identified, and 21 target miRNAs, 2466 source genes and 166 394 circRNA-miRNA-mRNA pairs were predicted. Further analysis was applied on three OA-related circRNAs (hsa_circ_0045714, hsa_circ_0002485, and hsa_circ_0005567). The results were partly verified by previous studies. Further biological research is needed to unfold the possible pathway and therapeutic target of OA., (© 2019 Wiley Periodicals, Inc.)

Circular RNAs (circRNAs) differ structurally from other types of RNAs and are resistant against exoribonucleases. Although they have been detected in all domains of life, it remains unclear how circularization affects or changes functions of these ubiquitous nucleic acid circles. The biogenesis of circRNAs has been mostly described as a backsplicing event, but in archaea, where RNA splicing is a rare phenomenon, a second pathway for circRNA formation was described in the cases of rRNAs processing, tRNA intron excision, and Box C/D RNAs formation. At least in some archaeal species, circRNAs are formed by a ligation step catalyzed by an atypic homodimeric RNA ligase belonging to Rnl3 family. In this review, we describe archaeal circRNA transcriptomes obtained using high throughput sequencing technologies on Sulfolobus solfataricus, Pyrococcus abyssi and Nanoarchaeum equitans cells. We will discuss the distribution of circular RNAs among the different RNA categories and present the Rnl3 ligase family implicated in the circularization activity. Special focus is given for the description of phylogenetic distributions, protein structures, and substrate specificities of archaeal RNA ligases., (Copyright © 2019 Elsevier B.V. and Société Française de Biochimie et Biologie Moléculaire (SFBBM). All rights reserved.)

The alterations in expression and function of circular RNA (circRNA) in human dental pulp cells (hDPCs) during odontogenic differentiation were investigated. To induce odontogenic differentiation, hDPCs (passage 3) were cultured for 14 days in odontogenic induction medium. circRNA high‑throughput sequencing was performed using Illumina HiSeqseq™ 2000. Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were used to evaluate the bio‑functions of the identified circRNAs. To validate the results of circRNA sequencing, reverse transcription‑quantitative polymerase chain reaction (RT‑qPCR) was performed for two selected differentially expressed circRNAs. The RNA sequencing results revealed that 1,314 and 1,780 circRNAs were upregulated and downregulated, respectively, during odontogenic induction. Their predicted target miRNAs and genes are involved in several biological functions and signaling pathways, including the mitogen‑associated protein kinase signaling pathway. The RT‑qPCR results of the two selected circRNAs (hsa_circ_0015260 and hsa_circ_0006984) were consistent with the expression trend obtained using high‑throughput sequencing. The results of the present study add to the current understanding of the regulatory mechanisms underlying hDPCs differentiation.

Impact Statement: Circular RNAs are important regulators of multiple biological processes such as organogenesis and oncogenesis. Although the bulk of concerning studies focused on revealing their diversified roles in various types of cancers, reports began to accumulate in cardiovascular field these days. We summarize circular RNAs implicated in cardiovascular diseases, aiming to highlight the advances in the knowledge of such diseases and their potential of being promising target for diagnosis and therapy.