Backsplice Junctions Research Articles

CircRNA expression and regulatory mechanisms in the protozoan parasite Entamoeba histolytica

Entamoeba histolytica is the etiologic agent of amoebiasis which still causes over 55,000 annual deaths worldwide, and 2.2 million disability-adjusted life years. To differentiate E. histolytica from the non-pathogenic commensal E. dispar requires costly and laborious diagnostic tools. Apart from housekeeping ncRNA, the E. histolytica ncRNA inventory includes microRNAs and stress-induced self-circularized 5ʹ-externally transcribed spacer rRNAs, therefore we searched for as many circRNA types as we could detect in this parasite with potential value for diagnostic purposes, as drug targets, and as markers between virulent vs non-virulent strains. CircRNAs are a type of transcripts widely conserved in eukaryotic cells and in E. histolytica we expected to identify potential circRNAs candidates for diagnosis. Using circular RT-PCR with divergent primers, we identified post-splicing derived full-length intronic circles (flicRNAs). In vivo splicing assays and several biochemical approaches revealed that the highly conserved GU-rich intronic 5'ss is required for flicRNA biogenesis, possibly slowing down intron lariat debranching enzyme activity, thus facilitating intron circularization. Similar approaches, and CLIP analyses using an HA-tagged Pol II CTD construct, showed that some flicRNAs interact with the transcription machinery and silence their parental genes in cis. We also found cytoplasmic flicRNAs whose functions remain to be uncovered. To expand our searches, we mined the available Entamoeba transcriptomes with the CIRIFull software, and identified 199 exonic and intergenic circular RNAs from the reptile parasite E. invadens, as well as 310 circRNAs from both virulent (HMI:IMSS) and avirulent (Rahman) E. histolytica strains (inclusion criteria: > 2 Back Splice Junctions, with Reverse Overlaps). A small proportion of the E. histolytica circRNAs were differentially expressed between strains, and some of these were validated by circular RT-PCR. Altogether, our data suggest that E. histolytica expresses a complex repertoire of circRNAs with diverse functions, involved in multiple biochemical pathways.

Overexpression-based detection of translatable circular RNAs is vulnerable to coexistent linear RNA byproducts

In RNA field, the demarcation between coding and non-coding has been negotiated by the recent discovery of occasionally translated circular RNAs (circRNAs). Although absent of 5’ cap structure, circRNAs can be translated cap-independently. Complementary intron-mediated overexpression is one of the most utilized methodologies for circRNA research but not without bearing echoing skepticism for its poorly defined mechanism and latent coexistent side products. In this study, leveraging such circRNA overexpression system, we have interrogated the protein-coding potential of 30 human circRNAs containing infinite open reading frames in HEK293T cells. Surprisingly, pervasive translation signals are detected by immunoblotting. However, intensive mutagenesis reveals that numerous translation signals are generated independently of circRNA synthesis. We have developed a dual tag strategy to isolate translation noise and directly demonstrate that the spurious translation signals originate from cryptically spliced linear transcripts. The concomitant linear RNA byproducts, presumably concatemers, can be translated to allow pseudo rolling circle translation signals, and can involve backsplicing junction (BSJ) to disqualify the BSJ-based evidence for circRNA translation. We also find non-AUG start codons may engage in the translation initiation of circRNAs. Taken together, our systematic evaluation sheds light on heterogeneous translational outputs from circRNA overexpression vector and comes with a caveat that ectopic overexpression technique necessitates extremely rigorous control setup in circRNA translation and functional investigation.

Titin Circular RNAs Create a Back-Splice Motif Essential for SRSF10 Splicing.

TTN (Titin), the largest protein in humans, forms the molecular spring that spans half of the sarcomere to provide passive elasticity to the cardiomyocyte. Mutations that disrupt the TTN transcript are the most frequent cause of hereditary heart failure. We showed before that TTN produces a class of circular RNAs (circRNAs) that depend on RBM20 to be formed. In this study, we show that the back-splice junction formed by this class of circRNAs creates a unique motif that binds SRSF10 to enable it to regulate splicing. Furthermore, we show that one of these circRNAs (cTTN1) distorts both localization of and splicing by RBM20. We calculated genetic constraint of the identified motif in 125 748 exomes collected from the gnomAD database. Furthermore, we focused on the highest expressed RBM20-dependent circRNA in the human heart, which we named cTTN1. We used shRNAs directed to the back-splice junction to induce selective loss of cTTN1 in human induced pluripotent stem cell-derived cardiomyocytes. Human genetics suggests reduced genetic tolerance of the generated motif, indicating that mutations in this motif might lead to disease. RNA immunoprecipitation confirmed binding of circRNAs with this motif to SRSF10. Selective loss of cTTN1 in human induced pluripotent stem cell-derived cardiomyocytes induced structural abnormalities, apoptosis, and reduced contractile force in engineered heart tissue. In line with its SRSF10 binding, loss of cTTN1 caused abnormal splicing of important cardiomyocyte SRSF10 targets such as MEF2A and CASQ2. Strikingly, loss of cTTN1 also caused abnormal splicing of TTN itself. Mechanistically, we show that loss of cTTN1 distorts both localization of and splicing by RBM20. We demonstrate that circRNAs formed from the TTN transcript are essential for normal splicing of key muscle genes by enabling splice regulators RBM20 and SRSF10. This shows that the TTN transcript also has regulatory roles, besides its well-known signaling and structural function. In addition, we demonstrate that the specific sequence created by the back-splice junction of these circRNAs has important functions. This highlights the existence of functionally important sequences that cannot be recognized as such in the human genome but provides an as-yet unrecognized source for functional sequence variation.

CIRCexplorer pipelines for circRNA annotation and quantification from non-polyadenylated RNA-seq datasets

Covalently closed circular RNAs (circRNAs) produced by back-splicing of exon(s) are co-expressed with their cognate linear RNAs from the same gene loci. Most circRNAs are fully overlapped with their cognate linear RNAs in sequences except the back-spliced junction (BSJ) site, thus challenging the computational detection, experimental validation and hence functional evaluation of circRNAs. Nevertheless, specific bioinformatic pipelines were developed to identify fragments mapped to circRNA-featured BSJ sites, and circRNAs were pervasively identified from non-polyadenylated RNA-seq datasets in different cell lines/tissues and across species. Precise identification and quantification of circRNAs provide a basis to further understand their functions. Here, we describe detailed computational steps to annotate and quantify circRNAs using a series of CIRCexplorer pipelines.

Novel Identified Circular Transcript of RCAN2, circ-RCAN2, Shows Deviated Expression Pattern in Pig Reperfused Infarcted Myocardium and Hypoxic Porcine Cardiac Progenitor Cells In Vitro.

Circular RNAs (circRNAs) are crucial in gene regulatory networks and disease development, yet circRNA expression in myocardial infarction (MI) is poorly understood. Here, we harvested myocardium samples from domestic pigs 3 days after closed-chest reperfused MI or sham surgery. Cardiac circRNAs were identified by RNA-sequencing of rRNA-depleted RNA from infarcted and healthy myocardium tissue samples. Bioinformatics analysis was performed using the CIRIfull and KNIFE algorithms, and circRNAs identified with both algorithms were subjected to differential expression (DE) analysis and validation by qPCR. Circ-RCAN2 and circ-C12orf29 expressions were significantly downregulated in infarcted tissue compared to healthy pig heart. Sanger sequencing was performed to identify the backsplice junctions of circular transcripts. Finally, we compared the expressions of circ-C12orf29 and circ-RCAN2 between porcine cardiac progenitor cells (pCPCs) that were incubated in a hypoxia chamber for different time periods versus normoxic pCPCs. Circ-C12orf29 did not show significant DE in vitro, whereas circ-RCAN2 exhibited significant ischemia-time-dependent upregulation in hypoxic pCPCs. Overall, our results revealed novel cardiac circRNAs with DE patterns in pCPCs, and in infarcted and healthy myocardium. Circ-RCAN2 exhibited differential regulation by myocardial infarction in vivo and by hypoxia in vitro. These results will improve our understanding of circRNA regulation during acute MI.

Optimized RNA-targeting CRISPR/Cas13d technology outperforms shRNA in identifying functional circRNAs

Short hairpin RNAs (shRNAs) are used to deplete circRNAs by targeting back-splicing junction (BSJ) sites. However, frequent discrepancies exist between shRNA-mediated circRNA knockdown and the corresponding biological effect, querying their robustness. By leveraging CRISPR/Cas13d tool and optimizing the strategy for designing single-guide RNAs against circRNA BSJ sites, we markedly enhance specificity of circRNA silencing. This specificity is validated in parallel screenings by shRNA and CRISPR/Cas13d libraries. Using a CRISPR/Cas13d screening library targeting > 2500 human hepatocellular carcinoma-related circRNAs, we subsequently identify a subset of sorafenib-resistant circRNAs. Thus, CRISPR/Cas13d represents an effective approach for high-throughput study of functional circRNAs.

Novel circRNA discovery in sheep shows evidence of high backsplice junction conservation

Circular RNAs (circRNAs) are covalently closed circular non-coding RNAs. Due to their structure, circRNAs are more stable and have longer half-lives than linear RNAs making them good candidates for disease biomarkers. Despite the scientific relevance of these molecules, the study of circRNAs in non-model organisms is still in its infancy. Here, we analyse total RNA-seq data to identify circRNAs in sheep from peripheral blood mononuclear cells (PBMCs) and parietal lobe cortex. Out of 2510 and 3403 circRNAs detected in parietal lobe cortex and in PBMCs, a total of 1379 novel circRNAs were discovered. Remarkably, around 63% of all detected circRNAs were found to be completely homologous to a circRNA annotated in human. Functional enrichment analysis was conducted for both tissues based on GO terms and KEGG pathways. The enriched terms suggest an important role of circRNAs from encephalon in synaptic functions and the involvement of circRNAs from PBMCs in basic immune system functions. In addition to this, we investigated the role of circRNAs in repetitive vaccination experiments via differential expression analysis and did not detect any significant relationship. At last, our results support both the miRNA sponge and the miRNA shuttle functions of CDR1-AS in sheep brain. To our knowledge, this is the first study on circRNA annotation in sheep PBMCs or parietal lobe cortex samples.

A PCR-free screen-printed magnetic electrode for the detection of circular RNA from hepatocellular cancer based on a back-splice junction.

Circular RNA (circRNA) has the potential to be applied to disease diagnosis and therapy. However, the currently available circRNA detection techniques are limited. This work proposes a sensitive and selective approach for circRNA detection based on gold nanoparticle-modified screen-printed magnetic electrodes (AuNPs-SPME). Magnetic beads (MBs) with capture probes based on specific back-splice junction (BSJ) sites were employed to identify and selectively isolate the target circRNA, which could be directly adsorbed onto the AuNPs-SPME. Then, the circRNA attached to the surface was detected by changes in the methylene blue redox signal. The simple and time-saving AuNPs-SPME is highly sensitive (LOD = 1.0 pM) to circCDYL, one of the biomarkers of hepatocellular cancer (HCC). The analytical performance of the method presented has also been verified in human serum samples, holding great promise for clinical diagnosis.

Comprehensive Identification of Translatable Circular RNAs Using Polysome Profiling.

Circular RNAs (circRNAs), a special type of RNAs without 5'- and 3'-ends, are widely present in eukaryotes and known to function as noncoding RNAs to regulate gene expression, including as miRNA sponges. Recent studies showed that many exonic circRNAs, generated by back-splicing of pre-mRNAs, can be translated in a cap-independent fashion through IRESs or m6A RNA methylation. However, the scope of the translatable circRNAs and the biological function of their translation products are still unclear in different cells and tissues. Ribosome footprinting and proteomic analysis were usually used to globally identify translatable circRNAs. However, both methods have low sensitivity due to the low efficiency in the discovery of circRNA specific reads or peptides (i.e., the back-splicing junctions are difficult to recover by the short reads of ribosome footprinting and the limitation of proteomic analysis). Here, we described an alternative method to identify translatable circRNAs using polysome profiling and circRNA-seq. Generally, polysome-associated RNAs were separated with sucrose gradients. Then polysome-bound circRNAs were enriched by an RNase R treatment and identified through paired-end deep sequencing. Thus, this method is more sensitive than ribosome footprint and proteomic analyses for the identification of translatable circRNAs.

Antisense Oligo Pulldown of Circular RNA for Downstream Analysis.

Circular RNAs (circRNAs) are a large family of noncoding RNA molecules that have emerged as novel regulators of gene expression by sequestering microRNAs (miRNAs) and RNA-binding proteins (RBPs). Several computational tools have been developed to predict circRNA interaction with target miRNAs and RBPs with a view to studying their potential effect on downstream target genes and cellular physiology. Biochemical assays, including reporter assays, AGO2 pulldown, ribonucleoprotein pulldown, and biotin-labeled RNA pulldown, are used to capture the association of miRNAs and RBPs with circRNAs. Only a few studies have used circRNA pulldown assays to capture the associated miRNAs and RBPs under physiological conditions. In this detailed protocol, the circRNA of interest (e.g., circHipk2) was captured using a biotin-labeled antisense oligo (ASO) targeting the circHipk2 backsplice junction sequence followed by pulldown with streptavidin-conjugated magnetic beads. The specific enrichment of circRNA was analyzed using reverse transcription quantitative PCR (RT-qPCR). Furthermore, the ASO pulldown assay can be coupled to miRNA RT-qPCR and western blotting analysis to confirm the association of miRNAs and RBPs predicted to interact with the target circRNA. In summary, the specific pulldown of circRNA using this quick and easy method makes it a useful tool for identifying and validating circRNA interaction with specific miRNAs and RBPs.

Bioinformatic Analysis of Circular RNA Expression.

Circular RNAs (circRNAs) are stable RNA molecules generated by backsplicing that play regulatory functions through interaction with other RNA and proteins, as well as by encoding peptides. Dysregulation of circRNA expression can drive cancer development and progression with different mechanisms. CircRNAs are currently regarded as extremely attractive molecules in cancer research for the identification of new and possibly targetable disease regulatory networks and for the development of biomarkers for cancer diagnosis, prognosis definition, and monitoring. Using specific experimental and computational protocols, circRNAs can be identified through RNA-seq by spotting the reads spanning backsplice junctions, which are specific to circular molecules. In this chapter, we report a state-of-the-art computational protocol for a genome-wide analysis of circRNAs from RNA-seq data, which considers circRNA detection, quantification, and differential expression testing. Finally, we indicate how to determine circular transcript sequences and the resources for an in silico functional characterization of circRNAs.

Screening for functional circular RNAs using the CRISPR-Cas13 system.

Circular RNAs (circRNAs) produced from back-spliced exons are widely expressed, but individual circRNA functions remain poorly understood owing to the lack of adequate methods for distinguishing circRNAs from cognate messenger RNAs with overlapping exons. Here, we report that CRISPR-RfxCas13d can effectively discriminate circRNAs from mRNAs by using guide RNAs targeting sequences spanning back-splicing junction (BSJ) sites featured in RNA circles. Using a lentiviral library that targets sequences across BSJ sites of highly expressed human circRNAs, we show that a group of circRNAs are important for cell growth mostly in a cell-type-specific manner and that a common oncogenic circRNA, circFAM120A, promotes cell proliferation by preventing the mRNA for family with sequence similarity 120A (FAM120A) from binding the translation inhibitor IGF2BP2. Further application of RfxCas13d-BSJ-gRNA screening has uncovered circMan1a2, which has regulatory potential in mouse embryo preimplantation development. Together, these results establish CRISPR-RfxCas13d as a useful tool for the discovery and functional study of circRNAs at both individual and large-scale levels.

Revealing Epigenetic Factors of circRNA Expression by Machine Learning in Various Cellular Contexts.

SummaryCircular RNAs (circRNAs) have been identified as naturally occurring RNAs that are highly represented in the eukaryotic transcriptome. Although a large number of circRNAs have been reported, the underlying regulatory mechanism of circRNAs biogenesis remains largely unknown. Here, we integrated in-depth multi-omics data including epigenome, transcriptome, and non-coding RNA and identified candidate circRNAs in six cellular contexts. Next, circRNAs were divided into two classes (high versus low) with different expression levels. Machine learning models were constructed that predicted circRNA expression levels based on 11 different histone modifications and host gene expression. We found that the models achieve great accuracy in predicting high versus low expressed circRNAs. Furthermore, the expression levels of host genes of circRNAs, H3k36me3, H3k79me2, and H4k20me1 contributed greatly to the classification models in six cellular contexts. In summary, all these results suggest that epigenetic modifications, particularly histone modifications, can effectively predict expression levels of circRNAs.

RNAi Screening to Identify Factors That Control Circular RNA Localization.

Thousands of eukaryotic protein-coding genes are noncanonically spliced to generate circular RNAs that have covalently linked ends. These transcripts are resistant to degradation by exonucleases, which enables some to accumulate to higher levels than the associated linear mRNA. In general, exonic circular RNAs accumulate in the cytoplasm, but functions for most of these transcripts remain unknown. It has been proposed that some may modulate the activity of microRNAs or RNA-binding proteins, be translated to yield protein products, or regulate innate immune responses. Recent work has revealed that circular RNAs are exported from the nucleus in a length-dependent manner and that the subcellular localization of these transcripts can be controlled by the DExH/D-box helicase Hel25E in Drosophila. Here, we describe how RNAi screening combined with subcellular fractionation and quantitative reverse transcription PCR (RT-qPCR) can be used to identify regulators of circular RNA localization in Drosophila cells. Long double-stranded RNAs (dsRNAs) that activate the RNA interference (RNAi) pathway are used to deplete factors of interest followed by biochemical fractionation to separate nuclear and cytoplasmic RNAs. RT-qPCR primers that amplify across the backsplicing junction of specific circular RNAs are then used to quantify the relative amounts of these transcripts in the nuclear and cytoplasmic compartments. In total, this approach can be broadly used to characterize circular RNA nuclear export and localization mechanisms, including to identify novel regulatory factors and their breadth of circular RNA targets.

SRRM4 Expands the Repertoire of Circular RNAs by Regulating Microexon Inclusion.

High-throughput RNA sequencing (RNA-seq) and dedicated bioinformatics pipelines have synergized to identify an expansive repertoire of unique circular RNAs (circRNAs), exceeding 100,000 variants. While the vast majority of these circRNAs comprise canonical exonic and intronic sequences, microexons (MEs)—which occur in 30% of functional mRNA transcripts—have been entirely overlooked. CircRNAs which contain these known MEs (ME-circRNAs) could be identified with commonly utilized circRNA prediction pipelines, CIRCexplorer2 and CIRI2, but were not previously recognized as ME-circRNAs. In addition, when employing a bespoke bioinformatics pipeline for identifying RNA chimeras, called Hyb, we could also identify over 2000 ME-circRNAs which contain novel MEs at their backsplice junctions, that are uncalled by either CIRCexplorer2 or CIRI2. Analysis of circRNA-seq datasets from gliomas of varying clinical grades compared with matched control tissue has shown circRNAs have potential as prognostic markers for stratifying tumor from healthy tissue. Furthermore, the abundance of microexon-containing circRNAs (ME-circRNAs) between tumor and normal tissues is correlated with the expression of a splicing associated factor, Serine/arginine repetitive matrix 4 (SRRM4). Overexpressing SRRM4, known for regulating ME inclusion in mRNAs critical for neural differentiation, in human HEK293 cells resulted in the biogenesis of over 2000 novel ME-circRNAs, including ME-circEIF4G3, and changes in the abundance of many canonical circRNAs, including circSETDB2 and circLRBA. This shows SRRM4, in which its expression is correlated with poor prognosis in gliomas, acts as a bona fide circRNA biogenesis factor. Given the known roles of MEs and circRNAs in oncogenesis, the identification of these previously unrecognized ME-circRNAs further increases the complexity and functional purview of this non-coding RNA family.

RJunBase: a database of RNA splice junctions in human normal and cancerous tissues.

Splicing is an essential step of RNA processing for multi-exon genes, in which introns are removed from a precursor RNA, thereby producing mature RNAs containing splice junctions. Here, we develope the RJunBase (www.RJunBase.org), a web-accessible database of three types of RNA splice junctions (linear, back-splice, and fusion junctions) that are derived from RNA-seq data of non-cancerous and cancerous tissues. The RJunBase aims to integrate and characterize all RNA splice junctions of both healthy or pathological human cells and tissues. This new database facilitates the visualization of the gene-level splicing pattern and the junction-level expression profile, as well as the demonstration of unannotated and tumor-specific junctions. The first release of RJunBase contains 682 017 linear junctions, 225 949 back-splice junctions and 34 733 fusion junctions across 18 084 non-cancerous and 11 540 cancerous samples. RJunBase can aid researchers in discovering new splicing-associated targets and provide insights into the identification and assessment of potential neoepitopes for cancer treatment.

Comprehensive analysis of circular RNA in oral leukoplakia: upregulated circHLA-C as a potential biomarker for diagnosis and prognosis.

BackgroundEmerging evidence indicates that circular RNAs (circRNAs) play an indispensable role in a variety of tumors, yet the function of circRNAs in premalignant lesions is still obscure. Oral leukoplakia (OLK) is one of the most common premalignant lesions of the oral mucosa. Our study aimed to comprehensively investigate whether circRNAs contribute to the occurrence and development of OLK.MethodsWe obtained six pairs of OLK and normal oral mucosal (NOM) tissue samples and subjected them to high-throughput sequencing to detect the expression of circRNA. In total, 26 pairs of NOM and OLK tissues were used for validation. Key circRNAs were selected and further validated by real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR), ribonuclease (RNase) R digestion, and Sanger sequencing. Visualization analysis of circular human leukocyte antigen-C (circHLA-C) was performed in the UCSC Genome Browser (genome.ucsc.edu). Functional analysis of differentially expressed (DE) circRNAs were processed by Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Furthermore, TargetScan (www.targetscan.org) was applied to predict targeted micro RNAs (miRNAs) and messenger RNAs (mRNAs) of circRNAs and a competing endogenous RNA (ceRNA) network related with identified circRNAs was constructed in Cytoscape (v2.8.0).ResultsProfile data showed that 366 circRNAs were significantly altered in OLK tissues, including 65 upregulated and 301 downregulated circRNA transcripts. Compared with sequencing results, seven selected circRNAs expressed the same changing tendency. The amplest upregulated circRNA in our sequencing data, circHLA-C, was confirmed through back-splice junction sequences by Sanger sequencing after RNase R digestion. Correlation analysis demonstrated that circHLA-C correlated positively with the degree of dysplasia. Furthermore, receiver operating characteristic (ROC) curve analysis indicated that circHLA-C had potential diagnostic value with excellent accuracy and specificity.ConclusionsAccording to the literature, we were the first to uncover the expression profiles of circRNAs in OLK. Our research performed a comprehensive bioinformatics analysis of DE circRNAs in OLK and identified circHLA-C as a promising diagnostic biomarker with potential as a therapeutic genetic target for OLK.

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.

Profiling of circular RNA N6‐methyladenosine in moso bamboo (Phyllostachys edulis) using nanopore‐based direct RNA sequencing

N6 -methyladenosine (m6 A) is a prevalent modification in messenger RNAs and circular RNAs that play important roles in regulating various aspects of RNA metabolism. However, the occurrence of the m6 A modification in plant circular RNAs has not been reported. A widely used method to identify m6 A modifications relies on m6 A-specific antibodies followed by next-generation sequencing of precipitated RNAs (MeRIP-Seq). However, one limitation of MeRIP-Seq is that it does not provide the precise location of m6 A at single-nucleotide resolution. Although more recent sequencing techniques such as Nanopore-based direct RNA sequencing (DRS) can overcome such limitations, the technology does not allow sequencing of circular RNAs, as these molecules lack a poly(A) tail. Here, we developed a novel method to detect the precise location of m6 A modifications in circular RNAs using Nanopore DRS. We first enriched our samples for circular RNAs, which we then fragmented and sequenced on the Nanopore platform with a customized protocol. Using this method, we identified 470 unique circular RNAs from DRS reads based on the back-spliced junction region. Among exonic circular RNAs, about 10% contained m6 A sites, which mainly occurred around acceptor and donor splice sites. This study demonstrates the utility of our antibody-independent method in identifying total and methylated circular RNAs using Nanopore DRS. This method has the additional advantage of providing the exact location of m6 A sites at single-base resolution in circular RNAs or linear transcripts from non-coding RNA without poly(A) tails.

An in vivo strategy for knockdown of circular RNAs

Exonic circular RNAs (circRNAs) are highly abundant RNAs generated mostly from exons of protein-coding genes. Assaying the functions of circRNAs is not straightforward as common approaches for circRNA depletion tend to also alter the levels of mRNAs generated from the hosting gene. Here we describe a methodology for specific knockdown of circRNAs in vivo with tissue and cell resolution. We also describe an experimental and computational platform for determining the potential off-target effects as well as for verifying the obtained phenotypes. Briefly, we utilize shRNAs targeted to the circRNA-specific back-splice junction to specifically downregulate the circRNA. We utilized this methodology to downregulate five circRNAs that are highly expressed in Drosophila. There were no effects on the levels of their linear counterparts or any RNA with complementarity to the expressed shRNA. Interestingly, downregulation of circCtrip resulted in developmental lethality that was recapitulated with a second shRNA. Moreover, downregulation of individual circRNAs caused specific changes in the fly head transcriptome, suggesting roles for these circRNAs in the fly nervous system. Together, our results provide a methodological approach that enables the comprehensive study of circRNAs at the organismal and cellular levels and generated for the first time flies in which specific circRNAs are downregulated.