ViroidDB: a database of viroids and viroid-like circular RNAs

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.

CRBPDL: Identification of circRNA-RBP interaction sites using an ensemble neural network approach

Circular RNAs (circRNAs) are non-coding RNAs with a special circular structure produced formed by the reverse splicing mechanism. Increasing evidence shows that circular RNAs can directly bind to RNA-binding proteins (RBP) and play an important role in a variety of biological activities. The interactions between circRNAs and RBPs are key to comprehending the mechanism of posttranscriptional regulation. Accurately identifying binding sites is very useful for analyzing interactions. In past research, some predictors on the basis of machine learning (ML) have been presented, but prediction accuracy still needs to be ameliorated. Therefore, we present a novel calculation model, CRBPDL, which uses an Adaboost integrated deep hierarchical network to identify the binding sites of circular RNA-RBP. CRBPDL combines five different feature encoding schemes to encode the original RNA sequence, uses deep multiscale residual networks (MSRN) and bidirectional gating recurrent units (BiGRUs) to effectively learn high-level feature representations, it is sufficient to extract local and global context information at the same time. Additionally, a self-attention mechanism is employed to train the robustness of the CRBPDL. Ultimately, the Adaboost algorithm is applied to integrate deep learning (DL) model to improve prediction performance and reliability of the model. To verify the usefulness of CRBPDL, we compared the efficiency with state-of-the-art methods on 37 circular RNA data sets and 31 linear RNA data sets. Moreover, results display that CRBPDL is capable of performing universal, reliable, and robust. The code and data sets are obtainable at https://github.com/nmt315320/CRBPDL.git.

More and more evidences show that circular RNA can directly bind to proteins and participate in countless different biological processes. The calculation method can quickly and accurately predict the binding site of circular RNA and RBP. In order to identify the interaction of circRNA with 37 different types of circRNA binding proteins, we developed an integrated deep learning network based on hierarchical network, called CRBPDL. It can effectively learn high-level feature representations. The performance of the model was verified through comparative experiments of different feature extraction algorithms, different deep learning models and classifier models. Moreover, the CRBPDL model was applied to 31 linear RNAs, and the effectiveness of our method was proved by comparison with the results of current excellent algorithms. It is expected that the CRBPDL model can effectively predict the binding site of circular RNA-RBP and provide reliable candidates for further biological experiments.

circFL-seq reveals full-length circular RNAs with rolling circular reverse transcription and nanopore sequencing

Circular RNAs (circRNAs) act through multiple mechanisms via their sequence features to fine-tune gene expression networks. Due to overlapping sequences with linear cognates, identifying internal sequences of circRNAs remains a challenge, which hinders a comprehensive understanding of circRNA functions and mechanisms. Here, based on rolling circular reverse transcription and nanopore sequencing, we developed circFL-seq, a full-length circRNA sequencing method, to profile circRNA at the isoform level. With a customized computational pipeline to directly identify full-length sequences from rolling circular reads, we reconstructed 77,606 high-quality circRNAs from seven human cell lines and two human tissues. circFL-seq benefits from rolling circles and long-read sequencing, and the results showed more than tenfold enrichment of circRNA reads and advantages for both detection and quantification at the isoform level compared to those for short-read RNA sequencing. The concordance of the RT-qPCR and circFL-seq results for the identification of differential alternative splicing suggested wide application prospects for functional studies of internal variants in circRNAs. Moreover, the detection of fusion circRNAs at the omics scale may further expand the application of circFL-seq. Taken together, the accurate identification and quantification of full-length circRNAs make circFL-seq a potential tool for large-scale screening of functional circRNAs.

Circular L-RNA aptamer promotes target recognition and controls gene activity

Rational design of aptamers to incorporate unnatural nucleotides and special chemical moieties can expand their functional complexity and diversity. Spiegelmer (L-RNA aptamer) is a unique class of aptamer that is composed of unnatural L-RNA nucleotides, and so far there are limited L-RNA aptamer candidates and applications being reported. Moreover, the target binding properties of current L-RNA aptamers require significant improvement. Here, using L-Apt.4-1c as an example, we develop a simple and robust strategy to generate the first circular L-RNA aptamer, cycL-Apt.4-1c, quantitatively, demonstrate substantial enhancement in binding affinity and selectivity toward its target, and notably report novel applications of circular L-RNA aptamer in controlling RNA-protein interaction, and gene activity including telomerase activity and gene expression. Our approach and findings will be applicable to any L-RNA aptamers and open up a new avenue for diverse applications.

NOVA2 regulates neural circRNA biogenesis

Circular RNAs (circRNAs) are highly expressed in the brain and their expression increases during neuronal differentiation. The factors regulating circRNAs in the developing mouse brain are unknown. NOVA1 and NOVA2 are neural-enriched RNA-binding proteins with well-characterized roles in alternative splicing. Profiling of circRNAs from RNA-seq data revealed that global circRNA levels were reduced in embryonic cortex of Nova2 but not Nova1 knockout mice. Analysis of isolated inhibitory and excitatory cortical neurons lacking NOVA2 revealed an even more dramatic reduction of circRNAs and establishes a widespread role for NOVA2 in enhancing circRNA biogenesis. To investigate the cis-elements controlling NOVA2-regulation of circRNA biogenesis, we generated a backsplicing reporter based on the Efnb2 gene. We found that NOVA2-mediated backsplicing of circEfnb2 was impaired when YCAY clusters located in flanking introns were mutagenized. CLIP (cross-linking and immunoprecipitation) and additional reporter analyses demonstrated the importance of NOVA2 binding sites located in both flanking introns of circRNA loci. NOVA2 is the first RNA-binding protein identified to globally promote circRNA biogenesis in the developing brain.

catRAPID omics v2.0: going deeper and wider in the prediction of protein-RNA interactions

Prediction of protein-RNA interactions is important to understand post-transcriptional events taking place in the cell. Here we introduce catRAPID omics v2.0, an update of our web server dedicated to the computation of protein-RNA interaction propensities at the transcriptome- and RNA-binding proteome-level in 8 model organisms. The server accepts multiple input protein or RNA sequences and computes their catRAPID interaction scores on updated precompiled libraries. Additionally, it is now possible to predict the interactions between a custom protein set and a custom RNA set. Considerable effort has been put into the generation of a new database of RNA-binding motifs that are searched within the predicted RNA targets of proteins. In this update, the sequence fragmentation scheme of the catRAPID fragment module has been included, which allows the server to handle long linear RNAs and to analyse circular RNAs. For the top-scoring protein-RNA pairs, the web server shows the predicted binding sites in both protein and RNA sequences and reports whether the predicted interactions are conserved in orthologous protein-RNA pairs. The catRAPID omics v2.0 web server is a powerful tool for the characterization and classification of RNA-protein interactions and is freely available at http://service.tartaglialab.com/page/catrapid_omics2_group along with documentation and tutorial.

Micro-Raman Characterization of Structural Features of High-k Stack Layer of SOI Nanowire Chip, Designed to Detect Circular RNA Associated with the Development of Glioma

The application of micro-Raman spectroscopy was used for characterization of structural features of the high-k stack (h-k) layer of "silicon-on-insulator" (SOI) nanowire (NW) chip (h-k-SOI-NW chip), including Al₂O₃ and HfO₂ in various combinations after heat treatment from 425 to 1000 °C. After that, the NW structures h-k-SOI-NW chip was created using gas plasma etching optical lithography. The stability of the signals from the monocrine phase of HfO₂ was shown. Significant differences were found in the elastic stresses of the silicon layers for very thick (>200 nm) Al₂O₃ layers. In the UV spectra of SOI layers of a silicon substrate with HfO₂, shoulders in the Raman spectrum were observed at 480-490 cm^-1 of single-phonon scattering. The h-k-SOI-NW chip created in this way has been used for the detection of DNA-oligonucleotide sequences (oDNA), that became a synthetic analog of circular RNA-circ-SHKBP1 associated with the development of glioma at a concentration of 1.1 × 10^-16 M. The possibility of using such h-k-SOI NW chips for the detection of circ-SHKBP1 in blood plasma of patients diagnosed with neoplasm of uncertain nature of the brain and central nervous system was shown.

Closing the circle: current state and perspectives of circular RNA databases

Circular RNAs (circRNAs) are covalently closed RNA molecules that have been linked to various diseases, including cancer. However, a precise function and working mechanism are lacking for the larger majority. Following many different experimental and computational approaches to identify circRNAs, multiple circRNA databases were developed as well. Unfortunately, there are several major issues with the current circRNA databases, which substantially hamper progression in the field. First, as the overlap in content is limited, a true reference set of circRNAs is lacking. This results from the low abundance and highly specific expression of circRNAs, and varying sequencing methods, data-analysis pipelines, and circRNA detection tools. A second major issue is the use of ambiguous nomenclature. Thus, redundant or even conflicting names for circRNAs across different databases contribute to the reproducibility crisis. Third, circRNA databases, in essence, rely on the position of the circRNA back-splice junction, whereas alternative splicing could result in circRNAs with different length and sequence. To uniquely identify a circRNA molecule, the full circular sequence is required. Fourth, circRNA databases annotate circRNAs' microRNA binding and protein-coding potential, but these annotations are generally based on presumed circRNA sequences. Finally, several databases are not regularly updated, contain incomplete data or suffer from connectivity issues. In this review, we present a comprehensive overview of the current circRNA databases and their content, features, and usability. In addition to discussing the current issues regarding circRNA databases, we come with important suggestions to streamline further research in this growing field.

TransCirc: an interactive database for translatable circular RNAs based on multi-omics evidence

TransCirc (https://www.biosino.org/transcirc/) is a specialized database that provide comprehensive evidences supporting the translation potential of circular RNAs (circRNAs). This database was generated by integrating various direct and indirect evidences to predict coding potential of each human circRNA and the putative translation products. Seven types of evidences for circRNA translation were included: (i) ribosome/polysome binding evidences supporting the occupancy of ribosomes onto circRNAs; (ii) experimentally mapped translation initiation sites on circRNAs; (iii) internal ribosome entry site on circRNAs; (iv) published N-6-methyladenosine modification data in circRNA that promote translation initiation; (v) lengths of the circRNA specific open reading frames; (vi) sequence composition scores from a machine learning prediction of all potential open reading frames; (vii) mass spectrometry data that directly support the circRNA encoded peptides across back-splice junctions. TransCirc provides a user-friendly searching/browsing interface and independent lines of evidences to predicte how likely a circRNA can be translated. In addition, several flexible tools have been developed to aid retrieval and analysis of the data. TransCirc can serve as an important resource for investigating the translation capacity of circRNAs and the potential circRNA-encoded peptides, and can be expanded to include new evidences or additional species in the future.

Preferential production of RNA rings by T4 RNA ligase 2 without any splint through rational design of precursor strand

Rings of single-stranded RNA are promising for many practical applications, but the methods to prepare them in preparative scale have never been established. Previously, RNA circularization was achieved by T4 RNA ligase 2 (Rnl2, a dsRNA ligase) using splints, but the yield was low due to concurrent intermolecular polymerization. Here, various functional RNAs (siRNA, miRNA, ribozyme, etc.) are dominantly converted by Rnl2 to the rings without significant limitations in sizes and sequences. The key is to design a precursor RNA, which is highly activated for the efficient circularization without any splint. First, secondary structure of target RNA ring is simulated by Mfold, and then hypothetically cut at one site so that a few intramolecular base pairs are formed at the terminal. Simply by treating this RNA with Rnl2, the target ring was selectively and efficiently produced. Unexpectedly, circular RNA can be obtained in high yield (>90%), even when only 2 bp form in the 3'-OH side and no full match base pair forms in the 5'-phosphate side. Formation of polymeric by-products was further suppressed by diluting conventional Rnl2 buffer to abnormally low concentrations. Even at high-RNA concentrations (e.g. 50 μM), enormously high selectivity (>95%) was accomplished.

circSamd4 represses myogenic transcriptional activity of PUR proteins

By interacting with proteins and nucleic acids, the vast family of mammalian circRNAs is proposed to influence many biological processes. Here, RNA sequencing analysis of circRNAs differentially expressed during myogenesis revealed that circSamd4 expression increased robustly in mouse C2C12 myoblasts differentiating into myotubes. Moreover, silencing circSamd4, which is conserved between human and mouse, delayed myogenesis and lowered the expression of myogenic markers in cultured myoblasts from both species. Affinity pulldown followed by mass spectrometry revealed that circSamd4 associated with PURA and PURB, two repressors of myogenesis that inhibit transcription of the myosin heavy chain (MHC) protein family. Supporting the hypothesis that circSamd4 might complex with PUR proteins and thereby prevent their interaction with DNA, silencing circSamd4 enhanced the association of PUR proteins with the Mhc promoter, while overexpressing circSamd4 interfered with the binding of PUR proteins to the Mhc promoter. These effects were abrogated when using a mutant circSamd4 lacking the PUR binding site. Our results indicate that the association of PUR proteins with circSamd4 enhances myogenesis by contributing to the derepression of MHC transcription.

Structure-Mediated Degradation of CircRNAs

The elaborate control of biogenesis and turnover is essential for circular RNAs (circRNAs) to exert their functions properly in eukaryotic cells, whereas how circRNAs are degraded remains unclear. A recent study by Fischer et al. reveals a novel structure-mediated circRNA decay that selectively degrades highly structured RNAs by UPF1 and G3BP1.

Genome-wide analysis of circular RNAs involved in Marek's disease tumourigenesis in chickens

Marek's disease (MD), induced by Marek's disease virus (MDV), is a lymphotropic neoplastic disease and causes huge economic losses to the poultry industry. Non-coding RNAs (ncRNAs) play important regulatory roles in disease pathogenesis. To investigate host circular RNA (circRNA) and microRNA (miRNA) expression profile, RNA sequencing was performed in tumourous spleens (TS), spleens from the survivors (SS) without any lesion after MDV infection, and non-infected chicken spleens (NS). A total of 2,169 circRNAs were identified and more than 80% of circRNAs were derived from exon. The flanking introns of 1,744 exonic circRNAs possessed 579 reverse complementary matches (RCMs), which mainly overlapped with chicken repeat 1 family (CR1F). It suggested that CR1F mediated the cyclization of exons by intron pairing. Out of 2,169 circRNAs, 113 were differentially expressed circRNAs (DECs). The Q-PCR and Rnase R digestion experiments showed circRNA possessed high stability compared with their linear RNAs. Integrated with previous transcriptome data, we profiled regulatory networks of circRNA/long non-coding RNA (lncRNA)-miRNA-mRNA. Extensive competing endogenous RNA (ceRNA) networks were predicted to be involved in MD tumourigenesis. Interestingly, circZMYM3, an intronic circRNA, interacted with seven miRNAs which targeted some immune genes, such as SWAP70 and CCL4. Gga-miR-155 not only interacted with circGTDC1 and circMYO1B, but also targeted immune-related genes, such as GATA4, which indicated the roles of non-coding RNAs played to mediate immune responsive genes. Collectively, this is the first study that integrated RNA expression profiles in MD model. Our results provided comprehensive interactions of ncRNAs and mRNA in MD tumourigenesis.

Circular RNAs in Cancer: Biogenesis, Function, and Clinical Significance

Circular RNA (circRNA) is a class of single-stranded molecules with tissue/development-specific expression patterns. Unlike linear RNA, circRNA forms a covalently closed loop produced from 'back-splicing' of primary transcripts, conferring on them inherent resistance to exonucleolytic RNA decay. Increasing evidence demonstrates that many circRNAs exert important biological functions by acting as miRNA inhibitors ('sponges'), protein 'decoys', or by encoding small peptides. Importantly, circRNAs are aberrantly expressed in cancer and play indispensable oncogenic or tumor suppressive roles during tumor development and progression. In this review, we summarize the biogenesis, turnover, and involvements of circRNAs in cancer and also discuss their potential as diagnostic biomarkers or therapeutic targets.

CircNF1-419 improves the gut microbiome structure and function in AD-like mice

Our pre-experiments found that the brain circRNA sequence profiles and gut microbiota in AD-like mice were changed, as circNF1-419 could enhance autophagy to ameliorate senile dementia in AD-like mice, so we conclude that there might some connections between circRNA and gut microbiome. Therefore, we use the over-expressed circNF1-419 adeno-associated virus (AAV) animal system with the aim of identifying possible connections. Our results showed that over-expression of circNF1-419 in brain not only influenced the cholinergic system of brain, but also changed the gut microbiota composition as the Candidatus Arthromitus, Lachnospiraceae FCS020 group, Lachnospiraceae UCG-006, and [Eubacterium] xylanophilum group, and the intestinal homeostasis and physiology, and even the gut microbiota trajectory in new born mice. These findings demonstrate a link between circRNA and gut microbiome, enlarge the 'microbiome- transcriptome' linkage library and provide more information on gut-brain axis.

Free circular introns with an unusual branchpoint in neuronal projections

The polarized structure of axons and dendrites in neuronal cells depends in part on RNA localization. Previous studies have looked at which polyadenylated RNAs are enriched in neuronal projections or at synapses, but less is known about the distribution of non-adenylated RNAs. By physically dissecting projections from cell bodies of primary rat hippocampal neurons and sequencing total RNA, we found an unexpected set of free circular introns with a non-canonical branchpoint enriched in neuronal projections. These introns appear to be tailless lariats that escape debranching. They lack ribosome occupancy, sequence conservation, and known localization signals, and their function, if any, is not known. Nonetheless, their enrichment in projections has important implications for our understanding of the mechanisms by which RNAs reach distal compartments of asymmetric cells.

Identifying Cancer-Specific circRNA-RBP Binding Sites Based on Deep Learning

Circular RNAs (circRNAs) are extensively expressed in cells and tissues, and play crucial roles in human diseases and biological processes. Recent studies have reported that circRNAs could function as RNA binding protein (RBP) sponges, meanwhile RBPs can also be involved in back-splicing. The interaction with RBPs is also considered an important factor for investigating the function of circRNAs. Hence, it is necessary to understand the interaction mechanisms of circRNAs and RBPs, especially in human cancers. Here, we present a novel method based on deep learning to identify cancer-specific circRNA-RBP binding sites (CSCRSites), only using the nucleotide sequences as the input. In CSCRSites, an architecture with multiple convolution layers is utilized to detect the features of the raw circRNA sequence fragments, and further identify the binding sites through a fully connected layer with the softmax output. The experimental results show that CSCRSites outperform the conventional machine learning classifiers and some representative deep learning methods on the benchmark data. In addition, the features learnt by CSCRSites are converted to sequence motifs, some of which can match to human known RNA motifs involved in human diseases, especially cancer. Therefore, as a deep learning-based tool, CSCRSites could significantly contribute to the function analysis of cancer-associated circRNAs.

CIRCexplorer3: A CLEAR Pipeline for Direct Comparison of Circular and Linear RNA Expression

Sequences of circular RNAs (circRNAs) produced from back-splicing of exon(s) completely overlap with those from cognate linear RNAs transcribed from the same gene loci with the exception of their back-splicing junction (BSJ) sites. Therefore, examination of global circRNA expression from RNA-seq datasets generally relies on the detection of RNA-seq fragments spanning BSJ sites, which is different from the quantification of linear RNA expression by normalized RNA-seq fragments mapped to whole gene bodies. Thus, direct comparison of circular and linear RNA expression from the same gene loci in a genome-wide manner has remained challenging. Here, we update the previously-reported CIRCexplorer pipeline to version 3 for circular and linear RNA expression analysis from ribosomal-RNA depleted RNA-seq (CIRCexplorer3-CLEAR). A new quantitation parameter, fragments per billion mapped bases (FPB), is applied to evaluate circular and linear RNA expression individually by fragments mapped to circRNA-specific BSJ sites or to linear RNA-specific splicing junction (SJ) sites. Comparison of circular and linear RNA expression levels is directly achieved by dividing FPBcirc by FPBlinear to generate a CIRCscore, which indicates the relative circRNA expression level using linear RNA expression level as the background. Highly-expressed circRNAs with low cognate linear RNA expression background can be readily identified by CIRCexplorer3-CLEAR for further investigation. CIRCexplorer3-CLEAR is publically available at https://github.com/YangLab/CLEAR.

A universal approach to investigate circRNA protein coding function

Circular RNAs (circRNAs) are an emerging class of RNA molecules that have been linked to human diseases and important regulatory pathways. Their functional roles are still under investigation, often hampered by inefficient circRNA formation in and ex vivo. We generated an intron-mediated enhancement (IME) system that-in comparison to previously published methods-increases circRNA formation up to 5-fold. This strategy also revealed previously undetected translation of circRNA, e.g., circRtn4. Substantiated by Western blots and mass spectrometry we showed that in mammalian cells, translation of circRtn4 containing a potential "infinite" circular reading frame resulted in "monomers" and extended proteins, presumably "multimer" tandem repeats. In order to achieve high levels of circRNA formation and translation of other natural or recombinant circRNAs, we constructed a versatile circRNA expression vector-pCircRNA-DMo. We demonstrated the general applicability of this method by efficiently generating two additional circRNAs exhibiting high expression levels. The circRNA expression vector will be an important tool to investigate different aspects of circRNA biogenesis and to gain insights into mechanisms of circular RNA translation.

Parsimonious Scenario for the Emergence of Viroid-Like Replicons De Novo

Viroids are small, non-coding, circular RNA molecules that infect plants. Different hypotheses for their evolutionary origin have been put forward, such as an early emergence in a precellular RNA World or several de novo independent evolutionary origins in plants. Here, we discuss the plausibility of de novo emergence of viroid-like replicons by giving theoretical support to the likelihood of different steps along a parsimonious evolutionary pathway. While Avsunviroidae-like structures are relatively easy to obtain through evolution of a population of random RNA sequences of fixed length, rod-like structures typical of Pospiviroidae are difficult to fix. Using different quantitative approaches, we evaluated the likelihood that RNA sequences fold into a rod-like structure and bear specific sequence motifs facilitating interactions with other molecules, e.g., RNA polymerases, RNases, and ligases. By means of numerical simulations, we show that circular RNA replicons analogous to Pospiviroidae emerge if evolution is seeded with minimal circular RNAs that grow through the gradual addition of nucleotides. Further, these rod-like replicons often maintain their structure if independent functional modules are acquired that impose selective constraints. The evolutionary scenario we propose here is consistent with the structural and biochemical properties of viroids described to date.