Linear RNA Research Articles

Evaluation of the Biological Effect of a Nicotinamide-Containing Broad-Spectrum Sunscreen on Photodamaged Skin.

UVA-UVB increases skin matrix metalloproteinases and breaks down extracellular proteins and fibrillar type1 collagen, leading to photodamage. Topical application of nicotinamide prevents UV-induced immunosuppression. Several studies have demonstrated the importance of protection against UV. This study aims to determine the biological effect of a high broad-spectrum UVB-UVA sunscreen containing nicotinamide and panthenol (SSNP) on photodamaged skin using linear confocal optical coherence tomography (LC-OCT), immunohistochemistry, and RNA profiling. Two areas of severely photodamaged forearm skin (L01 and L02) and one less sun-damaged (naturally protected) area on the inner part of the forearm (L03) were identified in 14 subjects. These areas were imaged using LC-OCT and L01 and L03 were biopsied at baseline. After 4weeks of treatment with SSNP, L02 was reimaged using LC-OCT, and biopsied. Histology, immunostaining with p21, p53, PCNA, and CPD, and RNA sequencing were performed in all samples. LC-OCT analysis showed that epidermis thickness and the number of keratinocytes is higher in the sun-exposed areas than in the non-exposed areas. Comparing before and after treatment, even though there is a trend towards normalization, the differences were not statistically significant. The expression of p21, PCNA, p53, and CPD increased in severely photodamaged skin compared to less-damaged skin. When comparing before and after treatment, only p21 showed a trend to decrease expression. RNA sequencing analysis identified 1552 significant genes correlating with the progression from non-visibly photodamaged skin to post-treatment and pre-treatment samples; in the analysis comparing pre- and post-treatment samples, 5429 genes were found to be significantly associated. A total of 1115 genes are common in these two analyses. Additionally, nine significant genes from the first analysis and eight from the second are related to collagen. Six of these collagen genes are common in the two analyses. MAPK and cGMP-PKG signalling pathways are upregulated in the progression to photodamage analysis. In the pre- and post-treatment analysis, 32 pathways are downregulated after treatment, the most statistically significant being the ErbB, Hippo, NOD-like receptor, TNF, and NF-kB signalling pathways. This study demonstrates the role of SSNP in collagen generation, highlights the relevance of the cGMP-PKG and MAPK signalling pathways in photodamage, and shows the ability of SSNP to downregulate pathways activated by UV exposure. Additionally, it deepens our understanding of the effect of SSNP on immune-related pathways.

Comprehensive circular RNA profiling in various sheep tissues

Despite the scientific relevance of circular RNAs (circRNAs), the study of these RNAs in non-model organisms, especially in sheep, is still in its infancy. On the other hand, while some studies have focused on sheep circRNA identification in a limited number of tissues, there is a lack of comprehensive analysis that profile circRNA expression patterns across the tissues not yet investigated. In this study, 61 public RNA sequencing datasets from 12 different tissues were uniformly analyzed to identify circRNAs, profile their expression and investigate their various characteristics. We reported for the first time a circRNA expression landscape with functional annotation in sheep tissues not yet investigated including hippocampus, BonMarrowMacrophage, left-ventricle, thymus, ileum, reticulum and 23-day-embryo. A stringent computational pipeline was employed and 8919 exon-derived circRNAs with high confidence were identified, including 88 novel circRNAs. Tissue-specificity analysis revealed that 3059 circRNAs were tissue-specific, which were also more specific to the tissues than linear RNAs. The highest number of tissue-specific circRNAs was found in kidney, hippocampus and thymus, respectively. Co-expression analysis revealed that expression of circRNAs may not be affected by their host genes. While most of the host genes produced more than one isoform, only one isoform had dominant expression across the tissues. The host genes of the tissue-specific circRNAs were significantly enriched in biological/pathways terms linked to the important functions of their corresponding tissues, suggesting potential roles of circRNAs in modulating physiological activity of those tissues. Interestingly, functional terms related to the regulation and various signaling pathways were significantly enriched in all tissues, suggesting some common regulatory mechanisms of circRNAs to modulate the physiological functions of tissues. Finding of the present study provide a valuable resource for depicting the complexity of circRNAs expression across tissues of sheep, which can be useful for the field of sheep genomic and veterinary research.

Circular RNA landscape in extracellular vesicles from human biofluids

BackgroundCircular RNAs (circRNAs) have emerged as a prominent class of covalently closed single-stranded RNA molecules that exhibit tissue-specific expression and potential as biomarkers in extracellular vesicles (EVs) derived from liquid biopsies. Still, their characteristics and applications in EVs remain to be unveiled.MethodsWe performed a comprehensive analysis of EV-derived circRNAs (EV-circRNAs) using transcriptomics data obtained from 1082 human body fluids, including plasma, urine, cerebrospinal fluid (CSF), and bile. Our validation strategy utilized RT-qPCR and RNA immunoprecipitation assays, complemented by computational techniques for analyzing EV-circRNA features and RNA-binding protein interactions.ResultsWe identified 136,327 EV-circRNAs from various human body fluids. Significantly, a considerable amount of circRNAs with a high back-splicing ratio are highly enriched in EVs compared to linear RNAs. Additionally, we discovered brain-specific circRNAs enriched in plasma EVs and cancer-associated EV-circRNAs linked to clinical outcomes. Moreover, we demonstrated that EV-circRNAs have the potential to serve as biomarkers for evaluating immunotherapy efficacy in non-small cell lung cancer (NSCLC). Importantly, we identified the involvement of RBPs, particularly YBX1, in the sorting mechanism of circRNAs into EVs.ConclusionsThis study unveils the extensive repertoire of EV-circRNAs across human biofluids, offering insights into their potential as disease biomarkers and their mechanistic roles within EVs. The identification of specific circRNAs and the elucidation of RBP-mediated sorting mechanisms open new avenues for the clinical application of EV-circRNAs in disease diagnostics and therapeutics.

IsRNAcirc: 3D structure prediction of circular RNAs based on coarse-grained molecular dynamics simulation.

As an emerging class of RNA molecules, circular RNAs play pivotal roles in various biological processes, thereby determining their three-dimensional (3D) structure is crucial for a deep understanding of their biological significances. Similar to linear RNAs, the development of computational methods for circular RNA 3D structure prediction is challenging, especially considering the inherent flexibility and potentially long length of circular RNAs. Here, we introduce an extension of our previous IsRNA2 model, named IsRNAcirc, to enable circular RNA 3D structure predictions through coarse-grained molecular dynamics simulations. The workflow of IsRNAcirc consists of four main steps, including input preparation, end closure, structure prediction, and model refinement. Our results demonstrate that IsRNAcirc can provide reasonable 3D structure predictions for circular RNAs, which significantly reduce the locally irrational elements contained in the initial input. Moreover, for a validation test set comprising 34 circular RNAs, our IsRNAcirc can generate 3D models with better scores than the template-based 3dRNA method. These findings demonstrate that our IsRNAcirc method is a promising tool to explore the structural details along with intricate interactions of circular RNAs.

Circular RNA circASH1L(4,5) protects microRNA-129-5p from target-directed microRNA degradation in human skin wound healing.

Skin wound healing involves a complex gene expression program that remains largely undiscovered in humans. Circular RNAs (circRNAs) and microRNAs (miRNAs) are key players in this process. To understand the functions and potential interactions of circRNAs and miRNAs in human skin wound healing. CircRNA, linear RNA, and miRNA expression in human acute and chronic wounds were analyzed using RNA sequencing and qRT-PCR. The roles of circASH1L(4,5) and miR-129-5p were studied in human primary keratinocytes (proliferation and migration assays, microarray analysis) and ex vivo wound models (histological analysis). The interaction between circASH1L(4,5) and miR-129-5p was examined using luciferase reporter and RNA pull-down assays. We identified circASH1L(4,5) and its interaction with miR-129-5p, both of which increased during human skin wound healing. Unlike typical miRNA sponging, circASH1L enhanced miR-129 stability and silencing activity by protecting it from target-directed degradation triggered by NR6A1 mRNA. TGF-β signaling, crucial in wound healing, promoted circASH1L expression while suppressing NR6A1, thereby increasing miR-129 abundance at the post-transcriptional level. CircASH1L and miR-129 enhanced keratinocyte migration and proliferation, crucial for re-epithelialization of human wounds. Our study uncovers a novel role for circRNAs as protectors of miRNAs and highlights the importance of regulated miRNA degradation in skin wound healing.

CircRNA in Digestive Diseases: Recent Advances in Fundamental Mechanism and Clinical Potential.

Circular RNAs (circRNAs), a class of non-coding RNAs characterized by their closed-loop structure, are widely present in the body and exhibit greater stability compared to conventional linear RNAs. With the development of molecular biology, circRNAs are gradually considered as a prognostic indicator and therapeutic target for various diseases. Research on the mechanism of circRNA in various diseases has become an important direction. In addition, digestive diseases are becoming more common as people's eating habits change, and the incidence and mortality of severe digestive system tumors are increasing year by year. The study of circRNA in digestive diseases provides us with a new way to improve the diagnosis and treatment of digestive diseases. This article provides a comprehensive review of the research literature on circRNAs in digestive system diseases over the past five years (2019- 2023) and covers aspects such as circRNA functions and underlying mechanisms. CircRNA has been implicated in a variety of digestive diseases. In these diseases, circRNA primarily acts as a microRNA (miRNA) sponge, interacting with miRNA to regulate the expression levels of genes associated with signaling pathways, and there is abundant research on the effects of circRNAs on drug resistance, cell proliferation, invasion, apoptosis, and poor prognosis. This article aima to discuss the current status of research on circular RNA and its key areas in digestive system diseases. The review aims to provide valuable insights for further research on the role of circular RNA in digestive system diseases and a reference for subsequent research.

Unraveling the Bivalent and Rapid Interactions Between a Multivalent RNA Recognition Motif and RNA: A Kinetic Approach.

The kinetics of the interaction between Musashi-1 (MSI1) and RNA have been characterized using surface plasmon resonance biosensor analysis. Truncated variants of human MSI1 encompassing the two homologous RNA recognition motifs (RRM1 and RRM2) in tandem (aa 1-200), and the two RRMs in isolation (aa 1-103 and aa 104-200, respectively) were produced. The proteins were injected over sensor surfaces with immobilized RNA, varying in sequence and length, and with one or two RRM binding motifs. The interactions of the individual RRMs with all RNA variants were well described by a 1:1 interaction model. The interaction between the MSI1 variant encompassing both RRM motifs was bivalent and rapid for all RNA variants. Due to difficulties in fitting this complex data using standard procedures, we devised a new method to quantify the interactions. It revealed that two RRMs in tandem resulted in a significantly longer residence time than a single RRM. It also showed that RNA with double UAG binding motifs and potential hairpin structures forms less stable bivalent complexes with MSI1 than the single UAG motif containing linear RNA. Substituting the UAG binding motif with a CAG sequence resulted in a reduction of the affinity of the individual RRMs, but for MSI1, this reduction was strongly enhanced, demonstrating the importance of bivalency for specificity. This study has provided new insights into the interaction between MSI1 and RNA and an understanding of how individual domains contribute to the overall interaction. It provides an explanation for why many RNA-binding proteins contain dual RRMs.

HEXIM1 homodimer binds two sites on 7SK RNA to release autoinhibition for P-TEFb inactivation.

Hexim proteins are RNA-dependent regulators whose main target is 7SK long non-coding RNA, a major regulator of eukaryotic mRNA transcription. 7SK RNPs control available intracellular concentrations of the kinase P-TEFb (Cdk9-CyclinT1/2) by sequestering it in an inactive form. Active P-TEFb phosphorylates NELF, DSIF, and the RNA polymerase II CTD to transition it from promoter-proximal pausing to productive elongation. P-TEFb associates with 7SK RNP via Hexim, which directly binds 7SK RNA. However, free Hexim is in an autoinhibited state that cannot inactivate P-TEFb, and how Hexim autoinhibition is released by 7SK remains unknown. Here, we show that one Hexim1 homodimer binds two sites on linear 7SK RNA in a manner that exposes the Cdk9 binding sites, which are otherwise masked within the autoinhibited dimer. These results provide mechanistic insights into Hexim-RNA specificity and explain how P-TEFb can be effectively regulated to respond to changing levels of transcriptional signaling.

A Representation Learning Approach for Predicting circRNA Back-Splicing Event via Sequence-Interaction-Aware Dual Encoder.

Circular RNAs (circRNAs) play a crucial role in gene regulation and association with diseases because of their unique closed continuous loop structure, which is more stable and conserved than ordinary linear RNAs. As fundamental work to clarify their functions, a large number of computational approaches for identifying circRNA formation have been proposed. However, these methods fail to fully utilize the important characteristics of back-splicing events, i.e., the positional information of the splice sites and the interaction features of its flanking sequences, for predicting circRNAs. To this end, we hereby propose a novel approach called SIDE for predicting circRNA back-splicing events using only raw RNA sequences. Technically, SIDE employs a dual encoder to capture global and interactive features of the RNA sequence, and then a decoder designed by the contrastive learning to fuse out discriminative features improving the prediction of circRNAs formation. Empirical results on three real-world datasets show the effectiveness of SIDE. Further analysis also reveals that the effectiveness of SIDE.

Predicting the potential associations between circRNA and drug sensitivity using a multisource feature-based approach.

The unique non-coding RNA molecule known as circular RNA (circRNA) is distinguished from conventional linear RNA by having a longer half-life, greater degree of conservation and inherent solidity. Extensive research has demonstrated the profound impact of circRNA expression on cellular drug sensitivity and therapeutic efficacy. There is an immediate need for the creation of efficient computational techniques to anticipate the potential correlations between circRNA and drug sensitivity, as classical biological research approaches are time-consuming and costly. In this work, we introduce a novel deep learning model called SNMGCDA, which aims to forecast the relationships between circRNA and drug sensitivity. SNMGCDA incorporates a diverse range of similarity networks, enabling the derivation of feature vectors for circRNAs and drugs using three distinct calculation methods. First, we utilize a sparse autoencoder for the extraction of drug characteristics. Subsequently, the application of non-negative matrix factorization (NMF) enables the identification of relationships between circRNAs and drugs based on their shared features. Additionally, the multi-head graph attention network is employed to capture the characteristics of circRNAs. After acquiring the characteristics from these three separate components, we combine them to form a unified and inclusive feature vector for each cluster of circRNA and drug. Finally, the relevant feature vectors and labels are inputted into a multilayer perceptron (MLP) to make predictions. The outcomes of the experiment, obtained through 5-fold cross-validation (5-fold CV) and 10-fold cross-validation (10-fold CV), demonstrate SNMGCDA outperforms five other state-of-art methods in terms of performance. Additionally, the majority of case studies have predominantly confirmed newly discovered correlations by SNMGCDA, thereby emphasizing its reliability in predicting potential relationships between circRNAs and drugs.

Human cells contain myriad excised linear intron RNAs with links to gene regulation and potential utility as biomarkers.

A previous study using Thermostable Group II Intron Reverse Transcriptase sequencing (TGIRT-seq) found human plasma contains short (≤300 nt) structured full-length excised linear intron (FLEXI) RNAs with potential to serve as blood-based biomarkers. Here, TGIRT-seq identified >9,000 different FLEXI RNAs in human cell lines, including relatively abundant FLEXIs with cell-type-specific expression patterns. Analysis of public CLIP-seq datasets identified 126 RNA-binding proteins (RBPs) that have binding sites within the region corresponding to the FLEXI or overlapping FLEXI splice sites in pre-mRNAs, including 53 RBPs with binding sites for ≥30 different FLEXIs. These included splicing factors, transcription factors, a chromatin remodeling protein, cellular growth regulators, and proteins with cytoplasmic functions. Analysis of ENCODE datasets identified subsets of these RBPs whose knockdown impacted FLEXI host gene mRNA levels or proximate alternative splicing, indicating functional interactions. Hierarchical clustering identified six subsets of RBPs whose FLEXI binding sites were co-enriched in six subsets of functionally related host genes: AGO1-4 and DICER, including but not limited to agotrons or mirtron pre-miRNAs; DKC1, NOLC1, SMNDC1, and AATF (Apoptosis Antagonizing Transcription Factor), including but not limited to snoRNA-encoding FLEXIs; two subsets of alternative splicing factors; and two subsets that included RBPs with cytoplasmic functions (e.g., LARP4, PABPC4, METAP2, and ZNF622) together with regulatory proteins. Cell fractionation experiments showed cytoplasmic enrichment of FLEXI RNAs with binding sites for RBPs with cytoplasmic functions. The subsets of host genes encoding FLEXIs with binding sites for different subsets of RBPs were co-enriched with non-FLEXI other short and long introns with binding sites for the same RBPs, suggesting overarching mechanisms for coordinately regulating expression of functionally related genes. Our findings identify FLEXIs as a previously unrecognized large class of cellular RNAs and provide a comprehensive roadmap for further analyzing their biological functions and the relationship of their RBPs to cellular regulatory mechanisms.

Research progress on the role and mechanism of circular RNA in drug resistance of head and neck squamous cell carcinoma.

Drug resistance in tumors constitutes a significant obstacle to tumor therapy. Head and neck squamous cell carcinoma (HNSCC) presents a major challenge due to its deep anatomical location, limited space, and complex structure. These factors complicate surgical procedures and hinder the effectiveness of chemoradiotherapy, leading to poor prognosis and reduced quality of life. However, there is hope in the form of circular RNAs (circRNAs), non-coding RNA molecules with a closed-loop structure that exhibits superior stability and resistance to degradation compared to linear RNAs. Recent advances in high-throughput sequencing and bioinformatics technology revealed that circRNAs participate in tumor proliferation, invasion, migration, and drug resistance. This review aims to summarize current research progress on the involvement of circRNAs in drug resistance of HNSCC and provide valuable insights for the prevention and mitigation of drug resistance in HNSCC.

In Vitro Self-Circularization Methods Based on Self-Splicing Ribozyme.

In vitro circular RNA (circRNA) preparation methods have been gaining a lot of attention recently as several reports suggest that circRNAs are more stable, with better performances in cells and in vivo, than linear RNAs in various biomedical applications. Self-splicing ribozymes are considered a major in vitro circRNA generation method for biomedical applications due to their simplicity and efficiency in the circularization of the gene of interest. This review summarizes, updates, and discusses the recently developed self-circularization methods based on the self-splicing ribozyme, such as group I and II intron ribozymes, and the pros and cons of each method in preparing circRNA in vitro.

Emerging Roles of Circular RNA in Macrophage Activation and Inflammatory Lung Responses.

Circular RNA (circRNA) is a type of single-stranded RNA that forms a covalently closed continuous loop, unlike linear RNA. The expression of circRNAs in mammals is often conserved across species and shows tissue and cell specificity. Some circRNA serve as gene regulators. However, the biological function of most circRNAs is unclear. CircRNA does not have 5' or 3' ends. The unique structure of circRNAs provides them with a much longer half-life and more resistance to RNase R than linear RNAs. Inflammatory lung responses occur in the pathogenesis and recovery of many lung diseases. Macrophages form the first line of host defense/innate immune responses and initiate/mediate lung inflammation. For example, in bacterial pneumonia, upon pro-inflammatory activation, they release early response cytokines/chemokines that recruit neutrophils, macrophages, and lymphocytes to sites of infection and clear pathogens. The functional effects and mechanisms by which circRNAs exert physiological or pathological roles in macrophage activation and lung inflammation remain poorly understood. In this article, we will review the current understanding and progress of circRNA biogenesis, regulation, secretion, and degradation. Furthermore, we will review the current reports on the role of circRNAs in macrophage activation and polarization, as well as in the process of inflammatory lung responses.

ICRBP-LKHA: Large convolutional kernel and hybrid channel-spatial attention for identifying circRNA-RBP interaction sites.

Circular RNAs (circRNAs) play vital roles in transcription and translation. Identification of circRNA-RBP (RNA-binding protein) interaction sites has become a fundamental step in molecular and cell biology. Deep learning (DL)-based methods have been proposed to predict circRNA-RBP interaction sites and achieved impressive identification performance. However, those methods cannot effectively capture long-distance dependencies, and cannot effectively utilize the interaction information of multiple features. To overcome those limitations, we propose a DL-based model iCRBP-LKHA using deep hybrid networks for identifying circRNA-RBP interaction sites. iCRBP-LKHA adopts five encoding schemes. Meanwhile, the neural network architecture, which consists of large kernel convolutional neural network (LKCNN), convolutional block attention module with one-dimensional convolution (CBAM-1D) and bidirectional gating recurrent unit (BiGRU), can explore local information, global context information and multiple features interaction information automatically. To verify the effectiveness of iCRBP-LKHA, we compared its performance with shallow learning algorithms on 37 circRNAs datasets and 37 circRNAs stringent datasets. And we compared its performance with state-of-the-art DL-based methods on 37 circRNAs datasets, 37 circRNAs stringent datasets and 31 linear RNAs datasets. The experimental results not only show that iCRBP-LKHA outperforms other competing methods, but also demonstrate the potential of this model in identifying other RNA-RBP interaction sites.

The Expanding Mycovirome of Aspergilli.

Mycoviruses are viruses that infect fungi and are widespread across all major fungal taxa, exhibiting great biological diversity. Since their discovery in the 1960s, researchers have observed a myriad of fungal phenotypes altered due to mycoviral infection. In this review, we examine the nuanced world of mycoviruses in the context of the medically and agriculturally important fungal genus, Aspergillus. The advent of RNA sequencing has revealed a previous underestimate of viral prevalence in fungi, in particular linear single-stranded RNA viruses, and here we outline the diverse viral families known to date that contain mycoviruses infecting Aspergillus. Furthermore, we describe these novel mycoviruses, highlighting those with peculiar genome structures, such as a split RNA dependent RNA polymerase gene. Next, we delineate notable mycovirus-mediated phenotypes in Aspergillus, in particular reporting on observations of mycoviruses that affect their fungal host's virulence and explore how this may relate to virus-mediated decreased stress tolerance. Furthermore, mycovirus effects on microbial competition and antifungal resistance are discussed. The factors that influence the manifestation of these phenotypes, such as temperature, fungal life stage, and infection with multiple viruses, among others, are also evaluated. In addition, we attempt to elucidate the molecular mechanisms that underpin these phenotypes, examining how mycoviruses can be targets, triggers, and even suppressors of RNA silencing and how this can affect fungal gene expression and phenotypes. Finally, we highlight the potential therapeutic applications of mycoviruses and how, in an approach analogous to bacteriophage therapy, their ability to produce hypovirulence in Aspergillus might be used to attenuate invasive aspergillosis infections in humans.

MSTCRB: Predicting circRNA-RBP interaction by extracting multi-scale features based on transformer and attention mechanism

CircRNAs play vital roles in biological system mainly through binding RNA-binding protein (RBP), which is essential for regulating physiological processes in vivo and for identifying causal disease variants. Therefore, predicting interactions between circRNA and RBP is a critical step for the discovery of new therapeutic agents. Application of various deep-learning models in bioinformatics has significantly improved prediction and classification performance. However, most of existing prediction models are only applicable to specific type of RNA or RNA with simple characteristics. In this study, we proposed an attractive deep learning model, MSTCRB, based on transformer and attention mechanism for extracting multi-scale features to predict circRNA-RBP interactions. Therein, K-mer and KNF encoding are employed to capture the global sequence features of circRNA, NCP and DPCP encoding are utilized to extract local sequence features, and the CDPfold method is applied to extract structural features. In order to improve prediction performance, optimized transformer framework and attention mechanism were used to integrate these multi-scale features. We compared our model's performance with other five state-of-the-art methods on 37 circRNA datasets and 31 linear RNA datasets. The results show that the average AUC value of MSTCRB reaches 98.45 %, which is better than other comparative methods. All of above datasets are deposited in https://github.com/chy001228/MSTCRB_database.git and source code are available from https://github.com/chy001228/MSTCRB.git.

A cis-acting ligase ribozyme generates circular RNA in vitro for ectopic protein functioning

Delivering synthetic protein-coding RNA bypassing the DNA stage for ectopic protein functioning is a novel therapeutic strategy. Joining the linear RNA head-to-tail covalently could be a state-of-the-art strategy for functioning longer. Here we enroll a cis-acting ligase ribozyme (RzL) to generate circular RNA (circRNA) in vitro for ectopic protein expression. The RNA circularization is confirmed by masking the 5’ phosphate group, resisting exonuclease RNase R digestion, failing for further tailing, and sequencing the RT-PCR products of the joined region. Interestingly, one internal ribosome entry site (IRES) renders circRNA translation competent, but two IRES in cis, not trans, hamper the translation. The circRNA with highly potent in translation is conferred for antiviral functioning. Accompanying specific guided RNA, a circRNA expressing ribonuclease Cas13 shows excellent potential against the corresponding RNA virus, further extending circRNA functioning in its growing list of applications.

Three-way junction-mediated three-letter coded SDA cascade CRISPR/Cas12a system for circRNA detection

Circular RNAs (circRNAs), a special type of non-coding RNAs with covalently closed circular structure, have emerged as promising liquid biopsy biomarker. However, the precise detection of circRNAs is severely hampered by interference from homologous linear RNAs, posing a significant obstacle for their applications in molecular diagnostics. Herein, a strategy named three-way junction (TWJ)-mediated three-letter coded strand displacement amplification (SDA) cascade CRISPR/Cas12a system (TTSC) has been devised to achieve precise detection of circRNAs. Three-letter coded SDA (TC-SDA) has been originally designed in this study for eliminating undesired interference from linear RNA and performing dual functionality in both discrimination and amplification. With this design, the proposed strategy elegantly distinguishes between circRNA and homologous linear RNA through proximity effect of TWJ structure and non-specific amplification blocking ability of the three-letter code. Ultimately, this strategy successfully identified circRNA down to 0.1 % abundance. In addition, benefiting from the synergistically accelerated multiple signal amplification in one step, TTSC strategy exhibited good linear relationship of 0.5–1000 pM with a detection limit of 80.6 fM. Notably, the recovery test indicated that the proposed strategy has good prospects for clinical applications. Therefore, TTSC is expected to provide an ideal platform for circRNA detection in biotechnology research and molecular diagnostics.

Circular RNA in cancer.

Over the past decade, circular RNA (circRNA) research has evolved into a bona fide research field shedding light on the functional consequence of this unique family of RNA molecules in cancer. Although the methodof formation and the abundance of circRNAs can differ from their cognate linear mRNA, the spectrum of interacting partners and their resultant cellular functions in oncogenesis are analogous. However, with 10 times more diversity in circRNA variants compared with linear RNA variants, combined with their hyperstability in the cell, circRNAs are equipped to influence every stage of oncogenesis. This is an opportune time to address the breadth of circRNA in cancer focused on their spatiotemporal expression, mutations in biogenesis factors and contemporary functions through each stage of cancer. In this Review, we highlight examples of functional circRNAs in specific cancers, which satisfy critical criteria, including their physical co-association with the target and circRNA abundance at stoichiometrically valid quantities. These considerations are essential to develop strategies for the therapeutic exploitation of circRNAs as biomarkers and targeted anticancer agents.