Improved circRNA Identification by Combining Prediction Algorithms

EasyCircR: Detection and reconstruction of circular RNAs post-transcriptional regulatory interaction networks

Circular RNAs (circRNAs) are regulatory RNAs that play a crucial role in various biological activities and have been identified as potential biomarkers for neurological disorders and cancer. CircRNAs have emerged as significant regulators of gene expression through different mechanisms, including regulation of transcription and splicing, modulation of translation, and post-translational modifications. Additionally, some circRNAs operate as microRNA (miRNA) sponges in the cytoplasm, boosting post-transcriptional expression of target genes by inhibiting miRNA activity. Although existing pipelines can reconstruct circRNAs, identify miRNAs sponged by them, retrieve cascade-regulated mRNAs, and represent the regulatory interactions as complex circRNA-miRNA-mRNA networks, none of the state-of-the-art approaches can discriminate the biological level at which the mRNAs involved in the interactions are regulated, avoiding considering potential target mRNAs not regulated at the post-transcriptional level. EasyCircR is a novel R package that combines circRNA detection and reconstruction with post-transcriptional gene expression analysis (exon-intron split analysis) and miRNA response element prediction. The package enables estimation and visualization of circRNA-miRNA-mRNA interactions through an intuitive Shiny application, leveraging the post-transcriptional regulatory nature of circRNA-miRNA relationship and excluding unrealistic regulatory interactions at the biological level. EasyCircR source code, Docker container and user guide are available at: https://github.com/InfOmics/EasyCircR.

Chromosome-scale genome assembly reveals how repeat elements shape non-coding RNA landscapes active during newt limb regeneration

Newts have large genomes harboring many repeat elements. How these elements shape the genome and relate to newts' unique regeneration ability remains unknown. We present here the chromosome-scale assembly of the 20.3 Gb genome of the Iberian ribbed newt, Pleurodeles waltl, with a hitherto unprecedented contiguity and completeness among giant genomes. Utilizing this assembly, we demonstrate conserved synteny as well as genetic rearrangements, such as in the major histocompatibility complex locus. We provide evidence suggesting that intronic repeat elements drive newt-specific circular RNA (circRNA) biogenesis and show their regeneration-specific expression. We also present a comprehensive in-depth annotation and chromosomal mapping of microRNAs, highlighting genomic expansion profiles as well as a distinct regulatory pattern in the regenerating limb. These data reveal links between repeat elements, non-coding RNAs, and adult regeneration and provide key resources for addressing developmental, regenerative, and evolutionary principles.

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.

The importance of the circRNA/Wnt axis in gliomas: Biological functions and clinical opportunities

Gliomas are among the most common cancers in the central nervous system, arising through various signaling pathways. One significant pathway is Wnt signaling, a tightly regulated process that plays a crucial role in gliomagenesis and development. The current study aims to explore the relationship between circular RNAs (circRNAs) and the Wnt/β-catenin signaling pathway in gliomas, considering the growing recognition of circRNAs in disease pathogenesis. A comprehensive review of recent research was conducted to investigate the roles of circRNAs in gliomas, focusing on their expression patterns and interactions with the Wnt signaling pathway. The analysis included studies examining circRNAs' function as microRNA sponges and their impact on glioma biology. The findings reveal that circRNAs are differentially expressed in gliomas and significantly influence the occurrence, growth, and metastasis of these tumors. Specifically, circRNAs interact with the Wnt signaling pathway, affecting glioma development and progression. This interaction highlights the importance of circRNAs in glioma pathophysiology. Understanding the regulatory network involving circRNAs and Wnt signaling offers valuable insights into glioma pathophysiology. CircRNAs hold promise as diagnostic and prognostic biomarkers and may serve as targets for novel therapeutic strategies in glioma treatment.

Circular RNAs regulate neuron size and migration of midbrain dopamine neurons during development

Midbrain dopamine (mDA) neurons play an essential role in cognitive and motor behaviours and are linked to different brain disorders. However, the molecular mechanisms underlying their development, and in particular the role of non-coding RNAs (ncRNAs), remain incompletely understood. Here, we establish the transcriptomic landscape and alternative splicing patterns of circular RNAs (circRNAs) at key developmental timepoints in mouse mDA neurons in vivo using fluorescence-activated cell sorting followed by short- and long-read RNA sequencing. In situ hybridisation shows expression of several circRNAs during early mDA neuron development and post-transcriptional silencing unveils roles for different circRNAs in regulating mDA neuron morphology. Finally, in utero electroporation and time-lapse imaging implicate circRmst, a circRNA with widespread morphological effects, in the migration of developing mDA neurons in vivo. Together, these data for the first time suggest a functional role for circRNAs in developing mDA neurons and characterise poorly defined aspects of mDA neuron development.

Exploring the prognostic value of circular RNAs in pancreatic ductal adenocarcinoma using genome-wide expression profiling

BACKGROUND/OBJECTIVES

Median survival of pancreatic ductal adenocarcinoma (PDAC) is around eight months and new prognostic tools are needed. Circular RNAs (circRNAs) have gained interest in different types of cancer. However, only a few studies have evaluated their potential in PDAC. We aimed to identify the most differentially expressed circRNAs in PDAC compared to controls and to explore their potential as prognostic markers.

METHODS

Using frozen specimens with PDAC and controls, we performed RNA sequencing and identified 20,440 unique circRNAs. A custom code set of capture- and reporter probes for NanoString nCounter analysis was designed to target 152 circRNAs, based on abundancy, differential expression and a literature study. Expression of these 152 circRNAs was examined in 108 formalin-fixed and paraffin-embedded surgical PDAC specimens and controls. The spatial expression of one of the most promising candidates, ciRS-7 (hsa_circ_0001946), was evaluated by chromogenic in situ hybridization (CISH) using multi-punch tissue microarrays (TMAs) and digital imaging analysis.

RESULTS

Based on circRNA expression profiles, we identified different PDAC subclusters. The 30 most differentially expressed circRNAs showed log2 fold changes from -3.43 to 0.94, where circNRIP1 (hsa_circ_0004771), circMBOAT2 (hsa_circ_0007334) and circRUNX1 (hsa_circ_0002360) held significant prognostic value in multivariate analysis. CiRS-7 was absent in PDAC cells but highly expressed in the tumor microenvironment.

CONCLUSIONS

We identified several new circRNAs with biomarker potential in surgically treated PDAC, three of which showed an independent prognostic value. We also found that ciRS-7 is absent in cancer cells but abundant in tumor microenvironment and may hold potential as marker of activated stroma.

circPCMTD1 : A protein-coding circular RNA that regulates DNA damage response in BCR/ABL -positive leukemias

Circular RNAs are a novel class of RNA transcripts, which regulate important cellular functions in health and disease. Herein, we report on the functional relevance of the circPCMTD1 transcript in acute leukemias. In screening experiments, we found that circPCMTD1 depletion strongly inhibited the proliferative capacity of leukemic cells with BCR-ABL translocations. Mass cytometry experiments identified the aberrant activation of the DNA damage response as an early downstream event of circPCMTD1 depletion. In in vivo experiments, circPCMTD1 targeting prolonged the survival of mice engrafted with leukemic blasts harboring the Philadelphia chromosome. Mechanistically, we found that circPCMTD1 was enriched in the cytoplasm and associated with the ribosomes of the leukemic cells. We detected a cryptic open reading frame within the circPCMTD1 sequence and found that circPCMTD1 could generate a peptide product. The circPCMTD 1-derived peptide interacted with proteins of the BTR complex and enhanced BTR complex formation, thereby increasing tolerance to genotoxic stress.

Computational approaches and challenges in the analysis of circRNA data

Circular RNAs (circRNA) are a class of non-coding RNA, forming a single-stranded covalently closed loop structure generated via back-splicing. Advancements in sequencing methods and technologies in conjunction with algorithmic developments of bioinformatics tools have enabled researchers to characterise the origin and function of circRNAs, with practical applications as a biomarker of diseases becoming increasingly relevant. Computational methods developed for circRNA analysis are predicated on detecting the chimeric back-splice junction of circRNAs whilst mitigating false-positive sequencing artefacts. In this review, we discuss in detail the computational strategies developed for circRNA identification, highlighting a selection of tool strengths, weaknesses and assumptions. In addition to circRNA identification tools, we describe methods for characterising the role of circRNAs within the competing endogenous RNA (ceRNA) network, their interactions with RNA-binding proteins, and publicly available databases for rich circRNA annotation.

CircInpp5b Ameliorates Renal Interstitial Fibrosis by Promoting the Lysosomal Degradation of DDX1

Renal interstitial fibrosis (RIF) is a classic pathophysiological process of chronic kidney disease (CKD). However, the mechanisms underlying RIF remain unclear. The present study found that a novel circular RNA, cirInpp5b, might be involved in RIF by high-throughput sequencing. Subsequent experiments revealed that circInpp5b was reduced in UUO mouse kidney tissues and TGF-β1-treated proximal tubular cells. The overexpression of circInpp5b inhibited RIF in UUO mice and prevented extracellular matrix (ECM) deposition in TGF-β1-treated proximal tubular cells. Furthermore, overexpression of circInpp5b down-regulated the protein level of DDX1. Mechanistically, circInpp5b bound to the DDX1 protein and promoted its lysosomal degradation. Collectively, the findings of our study demonstrate that circInpp5b ameliorates RIF by binding to the DDX1 protein and promoting its lysosomal degradation.

DeepCMI: a graph-based model for accurate prediction of circRNA-miRNA interactions with multiple information

Recently, the role of competing endogenous RNAs in regulating gene expression through the interaction of microRNAs has been closely associated with the expression of circular RNAs (circRNAs) in various biological processes such as reproduction and apoptosis. While the number of confirmed circRNA-miRNA interactions (CMIs) continues to increase, the conventional in vitro approaches for discovery are expensive, labor intensive, and time consuming. Therefore, there is an urgent need for effective prediction of potential CMIs through appropriate data modeling and prediction based on known information. In this study, we proposed a novel model, called DeepCMI, that utilizes multi-source information on circRNA/miRNA to predict potential CMIs. Comprehensive evaluations on the CMI-9905 and CMI-9589 datasets demonstrated that DeepCMI successfully infers potential CMIs. Specifically, DeepCMI achieved AUC values of 90.54% and 94.8% on the CMI-9905 and CMI-9589 datasets, respectively. These results suggest that DeepCMI is an effective model for predicting potential CMIs and has the potential to significantly reduce the need for downstream in vitro studies. To facilitate the use of our trained model and data, we have constructed a computational platform, which is available at http://120.77.11.78/DeepCMI/. The source code and datasets used in this work are available at https://github.com/LiYuechao1998/DeepCMI.

Comprehensive machine learning-based preoperative blood features predict the prognosis for ovarian cancer

PURPOSE

Significant advancements in improving ovarian cancer (OC) outcomes have been limited over the past decade. To predict prognosis and improve outcomes of OC, we plan to develop and validate a robust prognosis signature based on blood features.

METHODS

We screened age and 33 blood features from 331 OC patients. Using ten machine learning algorithms, 88 combinations were generated, from which one was selected to construct a blood risk score (BRS) according to the highest C-index in the test dataset.

RESULTS

Stepcox (both) and Enet (alpha = 0.7) performed the best in the test dataset with a C-index of 0.711. Meanwhile, the low RBS group possessed observably prolonged survival in this model. Compared to traditional prognostic-related features such as age, stage, grade, and CA125, our combined model had the highest AUC values at 3, 5, and 7 years. According to the results of the model, BRS can provide accurate predictions of OC prognosis. BRS was also capable of identifying various prognostic stratifications in different stages and grades. Importantly, developing the nomogram may improve performance by combining BRS and stage.

CONCLUSION

This study provides a valuable combined machine-learning model that can be used for predicting the individualized prognosis of OC patients.

Biological role and regulation of circular RNA as an emerging biomarker and potential therapeutic target for cancer

Circular RNAs (circRNAs) are a unique family of endogenous RNAs devoid of 3' poly-A tails and 5' end caps. These single-stranded circRNAs, found in the cytoplasm, are synthesized via back-splicing mechanisms, merging introns, exons, or both, resulting in covalently closed circular loops. They are profusely expressed across the eukaryotic transcriptome and offer heightened stability against exonuclease RNase R compared to linear RNA counterparts. This review endeavors to provide a comprehensive overview of circRNAs' characteristics, biogenesis, and mechanisms of action. Furthermore, aimed to shed light on the potential of circRNAs as significant biomarkers in various cancer types. It has been performed an exhaustive literature review, drawing on recent studies and findings related to circRNA characteristics, synthesis, function, evaluation techniques, and their associations with oncogenesis. CircRNAs are intricately associated with tumor progression and development. Their multifaceted roles encompass gene regulation through the sponging of proteins and microRNAs, controlling transcription and splicing, interacting with RNA binding proteins (RBPs), and facilitating gene translation. Due to these varied roles, circRNAs have become a focal point in tumor pathology investigations, given their promising potential as both biomarkers and therapeutic agents. CircRNAs, due to their unique biogenesis and multifunctionality, hold immense promise in the realm of oncology. Their stability, widespread expression, and intricate involvement in gene regulation underscore their prospective utility as reliable biomarkers and therapeutic targets in cancer. As our understanding of circRNAs deepens, advanced techniques for their detection, evaluation, and manipulation will likely emerge. These advancements might catalyze the translation of circRNA-based diagnostics and therapeutics into clinical practice, potentially revolutionizing cancer care and prognosis.

FL-circAS: an integrative resource and analysis for full-length sequences and alternative splicing of circular RNAs with nanopore sequencing

Circular RNAs (circRNAs) are RNA molecules with a continuous loop structure characterized by back-splice junctions (BSJs). While analyses of short-read RNA sequencing have identified millions of BSJ events, it is inherently challenging to determine exact full-length sequences and alternatively spliced (AS) isoforms of circRNAs. Recent advances in nanopore long-read sequencing with circRNA enrichment bring an unprecedented opportunity for investigating the issues. Here, we developed FL-circAS (https://cosbi.ee.ncku.edu.tw/FL-circAS/), which collected such long-read sequencing data of 20 cell lines/tissues and thereby identified 884 636 BSJs with 1 853 692 full-length circRNA isoforms in human and 115 173 BSJs with 135 617 full-length circRNA isoforms in mouse. FL-circAS also provides multiple circRNA features. For circRNA expression, FL-circAS calculates expression levels for each circRNA isoform, cell line/tissue specificity at both the BSJ and isoform levels, and AS entropy for each BSJ across samples. For circRNA biogenesis, FL-circAS identifies reverse complementary sequences and RNA binding protein (RBP) binding sites residing in flanking sequences of BSJs. For functional patterns, FL-circAS identifies potential microRNA/RBP binding sites and several types of evidence for circRNA translation on each full-length circRNA isoform. FL-circAS provides user-friendly interfaces for browsing, searching, analyzing, and downloading data, serving as the first resource for discovering full-length circRNAs at the isoform level.

Droplet Digital PCR for the Detection and Quantification of Bona Fide CircRNAs

CircRNAs are covalently closed RNA molecules gaining increasing attention over the years. Initially considered mere splicing errors, circRNAs are now recognized as a novel class of endogenous, conserved RNAs, expressed in many different species. The unique structure, the low levels of expression, and the almost complete sequence overlap with the cognate linear RNA make their detection and quantification challenging. Moreover, it has become crucial to prove the circular nature of the targeted transcript and unequivocally distinguish the circRNA from its linear counterpart. Nowadays, the most widely used technique to quantify circRNA expression is real-time quantitative PCR (qPCR). However, in the particular case of quantification of circles, it shows several technical shortcomings which affect the accuracy of the quantification. To precisely assess circRNA expression level, droplet digital PCR (ddPCR) is rapidly taking over for the more popular qPCR. In this chapter, we describe the detailed procedure based on droplets partitioning to quantify both linear and circRNA abundancy and demonstrate the circularity of the transcript under study with high precision, in a single experiment.

A systematic analysis of circRNAs in subnuclear compartments

CircRNAs are an important class of RNAs with diverse cellular functions in human physiology and disease. A thorough knowledge of circRNAs including their biogenesis and subcellular distribution is important to understand their roles in a wide variety of processes. However, the analysis of circRNAs from total RNA sequencing data remains challenging. Therefore, we developed Calcifer, a versatile workflow for circRNA annotation. Using Calcifer, we analysed APEX-Seq data to compare circRNA occurrence between whole cells, nucleus and subnuclear compartments. We generally find that circRNAs show higher abundance in whole cells compared to nuclear samples, consistent with their accumulation in the cytoplasm. The notable exception is the single-exon circRNA circCANX(9), which is unexpectedly enriched in the nucleus. In addition, we observe that circFIRRE prevails over the linear lncRNA FIRRE in both the cytoplasm and the nucleus. Zooming in on the subnuclear compartments, we show that circRNAs are strongly depleted from nuclear speckles, indicating that excess splicing factors in this compartment counteract back-splicing. Our results thereby provide valuable insights into the subnuclear distribution of circRNAs. Regarding circRNA function, we surprisingly find that the majority of all detected circRNAs possess complete open reading frames with potential for cap-independent translation. Overall, we show that Calcifer is an easy-to-use, versatile and sustainable workflow for the annotation of circRNAs which expands the repertoire of circRNA tools and allows to gain new insights into circRNA distribution and function.

Approaches and challenges in genome-wide circular RNA identification and quantification

Numerous circular RNAs (circRNAs) produced from back-splicing of exon(s) have been recently revealed on a genome-wide scale across species. Although generally expressed at a low level, some relatively abundant circRNAs can play regulatory roles in various biological processes, prompting continuous profiling of circRNA in broader conditions. Over the past decade, distinct strategies have been applied in both transcriptome enrichment and bioinformatic tools for detecting and quantifying circRNAs. Understanding the scope and limitations of these strategies is crucial for the subsequent annotation and characterization of circRNAs, especially those with functional potential. Here, we provide an overview of different transcriptome enrichment, deep sequencing and computational approaches for genome-wide circRNA identification, and discuss strategies for accurate quantification and characterization of circRNA.

Construction of a molecular regulatory network related to fat deposition by multi-tissue transcriptome sequencing of Jiaxian red cattle

Intramuscular fat (IMF) refers to the fat that accumulates between muscle bundles or within muscle cells, whose content significantly impacts the taste, tenderness, and flavor of meat products, making it a crucial economic characteristic in livestock production. However, the intricate mechanisms governing IMF deposition, involving non-coding RNAs (ncRNAs), genes, and complex regulatory networks, remain largely enigmatic. Identifying adipose tissue-specific genes and ncRNAs is paramount to unravel these molecular mysteries. This study, conducted on Jiaxian red cattle, harnessed whole transcriptome sequencing to unearth the nuances of circRNAs and miRNAs across seven distinct tissues. The interplay of these ncRNAs was assessed through differential expression analysis and network analysis. These findings are not only pivotal in unveiling the intricacies of fat deposition mechanisms but also lay a robust foundation for future research, setting the stage for enhancing IMF content in Jiaxian red cattle breeding.

An integrative pipeline for circular RNA quantitative trait locus discovery with application in human T cells

MOTIVATION

Molecular quantitative trait locus (QTL) mapping has proven to be a powerful approach for prioritizing genetic regulatory variants and causal genes identified by genome-wide association studies. Recently, this success has been extended to circular RNA (circRNA), a potential group of RNAs that can serve as markers for the diagnosis, prognosis, or therapeutic targets of various human diseases. However, a well-developed computational pipeline for circRNA QTL (circQTL) discovery is still lacking.

RESULTS

We introduce an integrative method for circQTL mapping and implement it as an automated pipeline based on Nextflow, named cscQTL. The proposed method has two main advantages. Firstly, cscQTL improves the specificity by systematically combining outputs of multiple circRNA calling algorithms to obtain highly confident circRNA annotations. Secondly, cscQTL improves the sensitivity by accurately quantifying circRNA expression with the help of pseudo references. Compared to the single method approach, cscQTL effectively identifies circQTLs with an increase of 20%-100% circQTLs detected and recovered all circQTLs that are highly supported by the single method approach. We apply cscQTL to a dataset of human T cells and discover genetic variants that control the expression of 55 circRNAs. By colocalization tests, we further identify circBACH2 and circYY1AP1 as potential candidates for immune disease regulation.

AVAILABILITY AND IMPLEMENTATION

cscQTL is freely available at: https://github.com/datngu/cscQTL and https://doi.org/10.5281/zenodo.7851982.

Circular RNAs: A New Approach to Multiple Sclerosis

Multiple sclerosis, a condition characterised by demyelination and axonal damage in the central nervous system, is due to autoreactive immune cells that recognise myelin antigens. Alteration of the immune balance can promote the onset of immune deficiencies, loss of immunosurveillance, and/or development of autoimmune disorders such as MS. Numerous enzymes, transcription factors, signal transducers, and membrane proteins contribute to the control of immune system activity. The "transcriptional machine" of eukaryotic cells is a complex system composed not only of mRNA but also of non-coding elements grouped together in the set of non-coding RNAs. Recent studies demonstrate that ncRNAs play a crucial role in numerous cellular functions, gene expression, and the pathogenesis of many immune disorders. The main purpose of this review is to investigate the role of circular RNAs, a previously unknown class of non-coding RNAs, in MS's pathogenesis. CircRNAs influence post-transcriptional control, expression, and functionality of a microRNA and epigenetic factors, promoting the development of typical MS abnormalities such as neuroinflammation, damage to neuronal cells, and microglial dysfunction. The increase in our knowledge of the role of circRNAs in multiple sclerosis could, in the future, modify the common diagnostic-therapeutic criteria, paving the way to a new vision of this neuroimmune pathology.

Dysregulation of circular RNAs in inflammation and cancers

Emerging lines of evidence have shown that the production of the covalently closed single-stranded circular RNAs is not splicing errors, but rather a regulated process with distinct biogenesis and turnover. Circular RNAs are expressed in a cell type- and tissue-specific manner and often localize to specific subcellular regions or organelles for functions. The dysregulation of circular RNAs from birth to death is linked to the pathogenesis and progression of diverse diseases. This review outlines how aberrant circular RNA biogenesis, subcellular location, and degradation are linked to disease progression, focusing on metaflammation and cancers. We also discuss potential therapeutic strategies and obstacles in targeting such disease-related circular RNAs.

Blood RNA-Seq profiling reveals a set of circular RNAs differentially expressed in frail individuals

BACKGROUND

Frailty is an intermediate and reversible geriatric syndrome that often precedes dependence. Therefore, its identification is essential to prevent dependence. Several molecules have been proposed as biomarkers of frailty, but none of them have reached clinical practice. Recently, circular RNAs have emerged as new non-coding RNAs. Their regulatory role together with their high stability in biofluids makes them good candidates as biomarkers for various processes, but, to date, no study has characterized the expression of circRNA in frailty.

RESULTS

We studied RNA from leukocytes of 35 frails and 35 robust individuals. After RNA-Sequencing, circRNA detection was performed by CIRI2 and Circexplorer2 and differential expression analysis by DESeq2. Validation was performed by Quantitative-PCR. Linear Discriminant Analysis was performed to determine the best circRNA combination to discriminate frail from robust. In addition, CircRNA candidates were studied in 13 additional elder donors before and after a 3-month physical intervention. We found 89 differentially expressed circRNAs (p-value<0.05, FC>|1.5|) with frailty. Upregulation of hsa_circ_0007817, hsa_circ_0101802 and hsa_circ_0060527 in frail individuals was validated. The combination of hsa_circ_0079284, hsa_circ_0007817 and hsa_circ_0075737 levels showed a great biomarker value with a 95.9% probability of correctly classifying frail and robust individuals. Moreover, hsa_circ_0079284 levels decreased after physical intervention in concordance with an improvement in frailty scores.

CONCLUSIONS

This work describes for the first time a different expression pattern of circular RNA (circRNAs) between frail and robust individuals. Moreover, the level of some circRNAs is modulated after a physical intervention. These results suggest that they could be used as minimally invasive biomarkers of frailty.

Circular RNAs arising from synaptic host genes during human neuronal differentiation are modulated by SFPQ RNA-binding protein

BACKGROUND

Circular RNA (circRNA) molecules, generated through non-canonical back-splicing of exon-exon junctions, have recently been implicated in diverse biological functions including transcriptional regulation and modulation of protein interactions. CircRNAs are emerging as a key component of the complex neural transcriptome implicated in brain development. However, the specific expression patterns and functions of circRNAs in human neuronal differentiation have not been explored.

RESULTS

Using total RNA sequencing analysis, we identified expressed circRNAs during the differentiation of human neuroepithelial stem (NES) cells into developing neurons and discovered that many circRNAs originated from host genes associated with synaptic function. Interestingly, when assessing population data, exons giving rise to circRNAs in our dataset had a higher frequency of genetic variants. Additionally, screening for RNA-binding protein sites identified enrichment of Splicing Factor Proline and Glutamine Rich (SFPQ) motifs in increased circRNAs, several of which were reduced by SFPQ knockdown and enriched in SFPQ ribonucleoprotein complexes.

CONCLUSIONS

Our study provides an in-depth characterisation of circRNAs in a human neuronal differentiation model and highlights SFPQ as both a regulator and binding partner of circRNAs elevated during neuronal maturation.

Computational approaches for circRNAs prediction and in silico characterization

Circular RNAs (circRNAs) are single-stranded and covalently closed non-coding RNA molecules originated from RNA splicing. Their functions include regulatory potential over other RNA species, such as microRNAs, messenger RNAs and RNA binding proteins. For circRNA identification, several algorithms are available and can be classified in two major types: pseudo-reference-based and split-alignment-based approaches. In general, the data generated from circRNA transcriptome initiatives is deposited on public specific databases, which provide a large amount of information on different species and functional annotations. In this review, we describe the main computational resources for the identification and characterization of circRNAs, covering the algorithms and predictive tools to evaluate its potential role in a particular transcriptomics project, including the public repositories containing relevant data and information for circRNAs, recapitulating their characteristics, reliability and amount of data reported.

Circular RNA Expression Profiling by Microarray-A Technical and Practical Perspective

Circular RNAs, as covalently circularized RNA loops, have many unique biochemical properties. Many circRNA biological functions and clinical indications are being continually discovered. Increasingly, circRNAs are being used as a new class of biomarkers, which are potentially superior to linear RNAs due to the unusual cell/tissue/disease specificities and the exonuclease-resistant stabilized circular form in the biofluids. Profiling circRNA expression has been a common step in circRNA research to provide much needed insight into circRNA biology and to facilitate rapid advances in the circRNA field. We will review circRNA microarrays as a practical and effective circRNA profiling technology for regularly equipped biological or clinical research labs, share valuable experiences, and highlight the significant findings from the profiling studies.

Identification of circular RNAs of Cannabis sativa L. potentially involved in the biosynthesis of cannabinoids

We identified circRNAs in the Cannabis sativa L. genome and examined their association with 28 cannabinoids in three tissues of C. sativa. Nine circRNAs are potentially involved in the biosynthesis of six cannabinoids. Cannabis sativa L. has been widely used in the production of medicine, textiles, and food for over 2500 years. The main bioactive compounds in C. sativa are cannabinoids, which have multiple important pharmacological actions. Circular RNAs (circRNAs) play essential roles in growth and development, stress resistance, and the biosynthesis of secondary metabolites. However, the circRNAs in C. sativa remain unknown. In this study, to explore the role of circRNAs in cannabinoid biosynthesis, we performed RNA-Seq and metabolomics analysis on the leaves, roots, and stems of C. sativa. We identified 741 overlapping circRNAs by three tools, of which 717, 16, and 8 circRNAs were derived from exonic, intronic, and intergenic, respectively. Functional enrichment analysis indicated that the parental genes (PGs) of circRNAs were enriched in many processes related to biological stress responses. We found that most of the circRNAs showed tissue-specific expression and 65 circRNAs were significantly correlated with their PGs (P < 0.05, |r|≥ 0.5). We also determined 28 cannabinoids by High-performance liquid chromatography-ESI-triple quadrupole-linear ion trap mass spectrometry. Ten circRNAs, including ciR0159, ciR0212, ciR0153, ciR0149, ciR0016, ciR0044, ciR0022, ciR0381, ciR0006, and ciR0025 were found to be associated with six cannabinoids by weighted gene co-expression network analysis. Twenty-nine of 53 candidate circRNAs, including 9 cannabinoids related were validated successfully using PCR amplification and Sanger sequencing. Taken together, all these results would help to enhance our acknowledge of the regulation of circRNAs, and lay the foundation for breeding new C. sativa cultivars with high cannabinoids through manipulating circRNAs.

Assessing the impacts of various factors on circular RNA reliability

Circular RNAs (circRNAs) are non-polyadenylated RNAs with a continuous loop structure characterized by a non-colinear back-splice junction (BSJ). Although millions of circRNA candidates have been identified, it remains a major challenge for determining circRNA reliability because of various types of false positives. Here, we systematically assess the impacts of numerous factors related to circRNA identification, conservation, biogenesis, and function on circRNA reliability by comparisons of circRNA expression from mock and the corresponding colinear/polyadenylated RNA-depleted datasets based on three different RNA treatment approaches. Eight important indicators of circRNA reliability are determined. The relative contribution to variability explained analyses reveal that the relative importance of these factors in affecting circRNA reliability in descending order is the conservation level of circRNA, full-length circular sequences, supporting BSJ read count, both BSJ donor and acceptor splice sites at the same colinear transcript isoforms, both BSJ donor and acceptor splice sites at the annotated exon boundaries, BSJs detected by multiple tools, supporting functional features, and both BSJ donor and acceptor splice sites undergoing alternative splicing. This study thus provides a useful guideline and an important resource for selecting high-confidence circRNAs for further investigations.

Systematic benchmarking of statistical methods to assess differential expression of circular RNAs

Circular RNAs (circRNAs) are covalently closed transcripts involved in critical regulatory axes, cancer pathways and disease mechanisms. CircRNA expression measured with RNA-seq has particular characteristics that might hamper the performance of standard biostatistical differential expression assessment methods (DEMs). We compared 38 DEM pipelines configured to fit circRNA expression data's statistical properties, including bulk RNA-seq, single-cell RNA-seq (scRNA-seq) and metagenomics DEMs. The DEMs performed poorly on data sets of typical size. Widely used DEMs, such as DESeq2, edgeR and Limma-Voom, gave scarce results, unreliable predictions or even contravened the expected behaviour with some parameter configurations. Limma-Voom achieved the most consistent performance throughout different benchmark data sets and, as well as SAMseq, reasonably balanced false discovery rate (FDR) and recall rate. Interestingly, a few scRNA-seq DEMs obtained results comparable with the best-performing bulk RNA-seq tools. Almost all DEMs' performance improved when increasing the number of replicates. CircRNA expression studies require careful design, choice of DEM and DEM configuration. This analysis can guide scientists in selecting the appropriate tools to investigate circRNA differential expression with RNA-seq experiments.

Exosomal circ-PTPN22 and circ-ADAMTS6 mark T cell exhaustion and neutrophil extracellular traps in Asian intrahepatic cholangiocarcinoma

Intrahepatic cholangiocarcinoma (ICC) is a liver tumor featured by challenges of non-invasive early diagnosis and a higher prevalence rate in Asian countries. These characteristics necessitate the development of liquid biopsy and immunotherapy methods to improve the prognosis of patients with ICC. Herein, we conducted a pilot study on the transcriptome of tumor tissues, adjacent normal tissues, and plasma exosomes of Asian patients with ICC from northern and southern China. We identified a subgroup of immunogenic Asian ICC, which is different from Caucasian ICC and is characterized by T cell exhaustion and neutrophil extracellular traps. The levels of circ-PTPN22 (hsa_circ_0110529) and circ-ADAMTS6 (hsa_circ_0072688), potential circRNA biomarkers, were elevated in the ICC tumor tissues and plasma exosomes of this subgroup than in the other subgroups and normal controls. These circRNAs were derived from post-transcriptional backsplicing of PTPN22 and ADAMTS6 that were expressed in T cells and endothelial cells, respectively, in the ICC microenvironment. Our results revealed a subgroup of Asian ICC characterized by T cell exhaustion and neutrophil extracellular traps and marked by elevated levels of circ-PTPN22 and circ-ADAMTS6 in tumor tissues and plasma exosomes. This subgroup is potentially detectable by plasma exosomal circRNAs and treatable with immune checkpoint blockade.

CircRNA: a rising star in plant biology

Circular RNAs (circRNAs) are covalently closed single-stranded RNA molecules, which are widespread in eukaryotic cells. As regulatory molecules, circRNAs have various functions, such as regulating gene expression, binding miRNAs or proteins, and being translated into proteins, which are important for cell proliferation and cell differentiation, individual growth and development, as well as many other biological processes. However, compared with that in animal models, studies of circRNAs in plants lags behind and, particularly, the regulatory mechanisms of biogenesis and molecular functions of plant circRNAs remain elusive. Recent studies have shown that circRNAs are wide spread in plants with tissue- or development-specific expression patterns and are responsive to a variety of environmental stresses. In this review, we summarize these advances, focusing on the regulatory mechanisms of biogenesis, molecular and biological functions of circRNAs, and the methods for investigating circRNAs. We also discuss the challenges and the prospects of plant circRNA studies.

HSV-1 and influenza infection induce linear and circular splicing of the long NEAT1 isoform

The herpes simplex virus 1 (HSV-1) virion host shut-off (vhs) protein cleaves both cellular and viral mRNAs by a translation-initiation-dependent mechanism, which should spare circular RNAs (circRNAs). Here, we show that vhs-mediated degradation of linear mRNAs leads to an enrichment of circRNAs relative to linear mRNAs during HSV-1 infection. This was also observed in influenza A virus (IAV) infection, likely due to degradation of linear host mRNAs mediated by the IAV PA-X protein and cap-snatching RNA-dependent RNA polymerase. For most circRNAs, enrichment was not due to increased circRNA synthesis but due to a general loss of linear RNAs. In contrast, biogenesis of a circRNA originating from the long isoform (NEAT1_2) of the nuclear paraspeckle assembly transcript 1 (NEAT1) was induced both in HSV-1 infection-in a vhs-independent manner-and in IAV infection. This was associated with induction of novel linear splicing of NEAT1_2 both within and downstream of the circRNA. NEAT1_2 forms a scaffold for paraspeckles, nuclear bodies located in the interchromatin space, must likely remain unspliced for paraspeckle assembly and is up-regulated in HSV-1 and IAV infection. We show that NEAT1_2 splicing and up-regulation can be induced by ectopic co-expression of the HSV-1 immediate-early proteins ICP22 and ICP27, potentially linking increased expression and splicing of NEAT1_2. To identify other conditions with NEAT1_2 splicing, we performed a large-scale screen of published RNA-seq data. This uncovered both induction of NEAT1_2 splicing and poly(A) read-through similar to HSV-1 and IAV infection in cancer cells upon inhibition or knockdown of CDK7 or the MED1 subunit of the Mediator complex phosphorylated by CDK7. In summary, our study reveals induction of novel circular and linear NEAT1_2 splicing isoforms as a common characteristic of HSV-1 and IAV infection and highlights a potential role of CDK7 in HSV-1 or IAV infection.

Biogenesis and Regulatory Roles of Circular RNAs

Covalently closed, single-stranded circular RNAs can be produced from viral RNA genomes as well as from the processing of cellular housekeeping noncoding RNAs and precursor messenger RNAs. Recent transcriptomic studies have surprisingly uncovered that many protein-coding genes can be subjected to backsplicing, leading to widespread expression of a specific type of circular RNAs (circRNAs) in eukaryotic cells. Here, we discuss experimental strategies used to discover and characterize diverse circRNAs at both the genome and individual gene scales. We further highlight the current understanding of how circRNAs are generated and how the mature transcripts function. Some circRNAs act as noncoding RNAs to impact gene regulation by serving as decoys or competitors for microRNAs and proteins. Others form extensive networks of ribonucleoprotein complexes or encode functional peptides that are translated in response to certain cellular stresses. Overall, circRNAs have emerged as an important class of RNAmolecules in gene expression regulation that impact many physiological processes, including early development, immune responses, neurogenesis, and tumorigenesis.

Best practice standards for circular RNA research

Circular RNAs (circRNAs) are formed in all domains of life and via different mechanisms. There has been an explosion in the number of circRNA papers in recent years; however, as a relatively young field, circRNA biology has an urgent need for common experimental standards for isolating, analyzing, expressing and depleting circRNAs. Here we propose a set of guidelines for circRNA studies based on the authors' experience. This Perspective will specifically address the major class of circRNAs in Eukarya that are generated by a spliceosome-catalyzed back-splicing event. We hope that the implementation of best practice principles for circRNA research will help move the field forward and allow a better functional understanding of this fascinating group of RNAs.

A Review and In Silico Analysis of Tissue and Exosomal Circular RNAs: Opportunities and Challenges in Thyroid Cancer

Simple Summary

Thyroid cancer is the most common endocrine neoplasm. Recently, knowledge of the molecular genetic changes of thyroid cancer has dramatically improved. Understanding the roles of these molecular changes in thyroid cancer tumorigenesis and progression is essential in developing a successful treatment strategy and improving disease outcomes. As a family of non-coding RNAs, circular RNAs (circRNAs) have been involved in several aspects of the physiological and pathological processes of the cells. The roles of circRNAs in cancer development and progress are evident. In the current review, we aimed to explore the clinical potential of circRNAs as potential diagnostic, prognostic, and therapeutic targets in thyroid cancer. Furthermore, screening the genome-wide circRNAs and performing functional enrichment analyses for all associated dysregulated circRNAs in thyroid cancer have been done. Given the unique advantages circRNAs have, such as superior stability, higher abundance, and presence in different body fluids, this family of non-coding RNAs could be promising diagnostic and prognostic biomarkers and potential therapeutic targets for thyroid cancer.

Abstract

Thyroid cancer (TC) is the most common endocrine tumor. The genetic and epigenetic molecular alterations of TC have become more evident in recent years. However, a deeper understanding of the roles these molecular changes play in TC tumorigenesis and progression is essential in developing a successful treatment strategy and improving patients’ prognoses. Circular RNAs (circRNAs), a family of non-coding RNAs, have been implicated in several aspects of carcinogenesis in multiple cancers, including TC. In the current review, we aimed to explore the clinical potential of circRNAs as putative diagnostic, prognostic, and therapeutic targets in TC. The current analyses, including genome-wide circRNA screening and functional enrichment for all deregulated circRNA expression signatures, show that circRNAs display atypical contributions, such as sponging for microRNAs, regulating transcription and translation processes, and decoying for proteins. Given their exceptional clinical advantages, such as higher stability, wider abundance, and occurrence in several body fluids, circRNAs are promising prognostic and theranostic biomarkers for TC.

Sex chromosome aneuploidies give rise to changes in the circular RNA profile: A circular transcriptome-wide study of Turner and Klinefelter syndrome across different tissues

Purpose: The landscape of circular RNAs (circRNAs), an important class of non-coding RNAs that regulate gene expression, has never been described in human disorders of sex chromosome aneuploidies. We profiled circRNAs in Turner syndrome females (45,X; TS) and Klinefelter syndrome males (47,XXY; KS) to investigate how circRNAs respond to a missing or an extra X chromosome.

Methods: Samples of blood, muscle and fat were collected from individuals with TS (n = 33) and KS (n = 22) and from male (n = 16) and female (n = 44) controls. CircRNAs were identified using a combination of circRNA identification pipelines (CIRI2, CIRCexplorer2 and circRNA_finder).

Results: Differential expression of circRNAs was observed throughout the genome in TS and KS, in all tissues. The host-genes from which several of these circRNAs were derived, were associated with known phenotypic traits. Furthermore, several differentially expressed circRNAs had the potential to capture micro RNAs that targeted protein-coding genes with altered expression in TS and KS.

Conclusion: Sex chromosome aneuploidies introduce changes in the circRNA transcriptome, demonstrating that the genomic changes in these syndromes are more complex than hitherto thought. CircRNAs may help explain some of the genomic and phenotypic traits observed in these syndromes.

Usability evaluation of circRNA identification tools: Development of a heuristic-based framework and analysis

BACKGROUND AND OBJECTIVE

Circular RNAs (circRNAs) are endogenous molecules of non-coding RNA that form a covalently closed loop at the 3' and 5' ends. Recently, the role of these molecules in the regulation of gene expression and their involvement in several human pathologies has gained notoriety. The identification of circRNAs is highly dependent on computational methods for analyzing RNA sequencing data. However, bioinformatics software is known to be problematic in terms of usability. Evidence points out that tools for identifying circRNAs can have such problems, negatively impacting researchers in this field. Here we present a heuristic-based framework for evaluating the usability of command-line circRNA identification software.

METHODS

We used heuristics evaluation to comprehensively identify the usability issues in a sample of circRNA identification tools.

RESULTS

We identified 46 usability issues presented individually in four tools. Most of the issues had cosmetic or minor severity. These are unlikely to challenge experienced users but may cause inconvenience for novice users. We also identified severe issues with the potential to harm users regardless of their experience. The areas most affected were the documentation and the installability of the tools.

CONCLUSIONS

With the proposed framework, we formally describe, for the first time, the usability problems that can affect users in this area of circRNA research. We hope that our framework can help researchers evaluate their software's usability during development.

Circular RNAs: Characterization, cellular roles, and applications

Most circular RNAs are produced from the back-splicing of exons of precursor mRNAs. Recent technological advances have in part overcome problems with their circular conformation and sequence overlap with linear cognate mRNAs, allowing a better understanding of their cellular roles. Depending on their localization and specific interactions with DNA, RNA, and proteins, circular RNAs can modulate transcription and splicing, regulate stability and translation of cytoplasmic mRNAs, interfere with signaling pathways, and serve as templates for translation in different biological and pathophysiological contexts. Emerging applications of RNA circles to interfere with cellular processes, modulate immune responses, and direct translation into proteins shed new light on biomedical research. In this review, we discuss approaches used in circular RNA studies and the current understanding of their regulatory roles and potential applications.

Cost-Effective Transcriptome-Wide Profiling of Circular RNAs by the Improved-tdMDA-NGS Method

Covalently closed circular RNAs are neoteric to the eukaryotic family of long non-coding RNAs emerging as a result of 5′–3′ backsplicing from exonic, intronic, or intergenic regions spanning the parental gene. Owing to their unique structure and stability, circular RNAs have a multitude of functional properties such as micro-RNA and protein sponges, direct and indirect modulators of gene expression, protein translation, and many unproven activities apart from being potential biomarkers. However, due to their low abundance, most of the global circular RNA identification is carried out by high-throughput NGS-based approaches requiring millions of sequencing reads. This lag in methodological advancements demands for newer, more refined, and efficient identification techniques. Here, we aim to show an improved version of our previously reported template-dependent multiple displacement amplification (tdMDA)-NGS method by superimposing the ribosomal depletion step and use of H minus reverse transcriptase and RNase H. Implication of tdMDA using highly replicative Phi29 DNA polymerase after minimizing the linear and ribosomal RNA content further intensifies its detection limit toward even the abysmally expressing circular RNA at a low NGS depth, thereby decreasing the cost of identifying a single circular RNA. A >11-fold and >6-fold increase in total circular RNA was identified from the improved-tdMDA-NGS method over the traditional method of circRNA sequencing using DCC and CIRI2 pipelines, respectively, from Oryza sativa subsp. Indica. Furthermore, the reliability of the improved-tdMDA-NGS method was also asserted in HeLa cell lines, showing a significant fold difference in comparison with the existing traditional method of circRNA sequencing. Among the identified circular RNAs, a significant percentage from both rice (∼58%) and HeLa cell lines (∼84%) is found to be matched with the previously reported circular RNAs, suggesting that the improved-tdMDA-NGS method can be adapted to detect and characterize the circular RNAs from different biological systems.

A Circ-0007022/miR-338-3p/Neuropilin-1 Axis Reduces the Radiosensitivity of Esophageal Squamous Cell Carcinoma by Activating Epithelial-To-Mesenchymal Transition and PI3K/AKT Pathway

Radiotherapy resistance is an important cause of treatment failure in esophageal squamous cell carcinoma (ESCC). Circular RNAs have attracted a lot of attention in cancer research, but their role in ESCC radiosensitivity has not been elucidated yet. Here, we aimed to evaluated the functional impacts of circ-0007022 on ESCC radiosensitivity. In this study, a stable radiotherapy-resistant cell line was established and verified by a series of functional experiments. Subsequently, high-throughput sequencing revealed that circ-0007022 was significantly overexpressed in the radiotherapy-resistant cell line and this conclusion was verified in ESCC patients’ tumor tissues by real-time quantitative PCR. Moreover, loss-of-function and overexpression experiments in vitro and in vivo revealed that, after irradiation, the abilities of proliferation and migration in circ-0007022-overexpressing stable transgenic strain were significantly higher than that in circ-0007022-knockdown stable transgenic strain. Additionally, RNA Immunoprecipitation, RNA pull-down, luciferase reporter assays, and fluorescence in situ hybridization experiments demonstrated the mechanism of how circ-0007022 could sponge miR-338-3p and upregulate downstream target of miR-338-3p, neuropilin-1 (NRP1). Moreover, NRP1 led to poor prognosis for ESCC patients receiving radiotherapy, and NRP1 knock-down enhanced radiosensitivity of ESCC cells. Furthermore, circ-0007022 overexpression activated Epithelial-to-mesenchymal transition and PI3K/Akt pathway, and NRP1 knock-down could reversed this phenomenon. Finally, Akt Inhibitor reversed circ-0007022s role in radiotherapy in ESCC cells. Taken together, the circ-0007022/miR-338-3p/NRP1 axis enhances the radiation resistance of ESCC cells via regulating EMT and PI3K/Akt pathway. The new circRNA circ-0007022 is thus expected to be a therapeutic target for ESCC patients.

Comprehensive comparison of two types of algorithm for circRNA detection from short-read RNA-Seq

MOTIVATION

Circular RNA is generally formed by the "back-splicing" process between the upstream splice acceptor and the downstream donor in/not in the regulation of the corresponding RNA-binding proteins or cis-elements. Therefore, more and more software packages have been developed and they are mostly based on the identification of the back-spliced junction reads. However, recent studies developed two software tools that can detect circRNA candidates by constructing k-mer table or/and de bruijn graph rather than reads mapping.

RESULTS

Here, we compared the precision, sensitivity and detection efficiency between software tools based on different algorithms. Eleven representative detection tools with two types of algorithm were selected for the overall pipeline analysis of RNA-seq datasets with/without RNase R treatment in two cell lines. Precision, sensitivity, AUC, F1 score and detection efficiency metrics were assessed to compare the prediction tools. Meanwhile, the sensitivity and distribution of highly expressed circRNAs before and after RNase R treatment were also revealed by their enrichment, unaffected and depleted candidate frequencies. Eventually, we found that compared to the k-mer based tools, CIRI2 and KNIFE based on reads mapping had relatively superior and more balanced detection performance regardless of the cell line or RNase R (-/+) datasets.

AVAILABILITY AND IMPLEMENTATION

All predicted results and source codes can be retrieved from https://github.com/luffy563/circRNA_tools_comparison.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Identification of potentially functional circRNAs and prediction of circRNA-miRNA-mRNA regulatory network in periodontitis: Bridging the gap between bioinformatics and clinical needs

Background and Objective

Periodontitis is a multifactorial chronic inflammatory disease that can lead to the irreversible destruction of dental support tissues. As an epigenetic factor, the expression of circRNA is tissue‐dependent and disease‐dependent. This study aimed to identify novel periodontitis‐associated circRNAs and predict relevant circRNA‐periodontitis regulatory network by using recently developed bioinformatic tools and integrating sequencing profiling with clinical information for getting a better and more thorough image of periodontitis pathogenesis, from gene to clinic.

Material and Methods

High‐throughput sequencing and RT‐qPCR were conducted to identify differentially expressed circRNAs in gingival tissues from periodontitis patients. The relationship between upregulated circRNAs expression and probing depth (PD) was performed using Spearman's correlation analysis. Bioinformatic analyses including GO analysis, circRNA‐disease association prediction, and circRNA‐miRNA‐mRNA network prediction were performed to clarify potential regulatory functions of identified circRNAs in periodontitis. A receiver‐operating characteristic (ROC) curve was established to assess the diagnostic significance of identified circRNAs.

Results

High‐throughput sequencing identified 70 differentially expressed circRNAs (68 upregulated and 2 downregulated circRNAs) in human periodontitis (fold change >2.0 and p < .05). The top five upregulated circRNAs were validated by RT‐qPCR that had strong associations with multiple human diseases, including periodontitis. The upregulation of circRNAs were positively correlated with PD (R = .40–.69, p < .05, moderate). A circRNA‐miRNA‐mRNA network with the top five upregulated circRNAs, differentially expressed mRNAs, and overlapped predicted miRNAs indicated potential roles of circRNAs in immune response, cell apoptosis, migration, adhesion, and reaction to oxidative stress. The ROC curve showed that circRNAs had potential value in periodontitis diagnosis (AUC = 0.7321–0.8667, p < .05).

Conclusion

CircRNA‐disease associations were predicted by online bioinformatic tools. Positive correlation between upregulated circRNAs, circPTP4A2, chr22:23101560‐23135351+, circARHGEF28, circBARD1 and circRASA2, and PD suggested function of circRNAs in periodontitis. Network prediction further focused on downstream targets regulated by circRNAs during periodontitis pathogenesis.

Medulloblastoma cerebrospinal fluid reveals metabolites and lipids indicative of hypoxia and cancer-specific RNAs

Medulloblastoma (MB) is the most common malignant brain tumor in children. There remains an unmet need for diagnostics to sensitively detect the disease, particularly recurrences. Cerebrospinal fluid (CSF) provides a window into the central nervous system, and liquid biopsy of CSF could provide a relatively non-invasive means for disease diagnosis. There has yet to be an integrated analysis of the transcriptomic, metabolomic, and lipidomic changes occurring in the CSF of children with MB. CSF samples from patients with (n = 40) or without (n = 11; no cancer) MB were subjected to RNA-sequencing and high-resolution mass spectrometry to identify RNA, metabolite, and lipid profiles. Differentially expressed transcripts, metabolites, and lipids were identified and their biological significance assessed by pathway analysis. The DIABLO multivariate analysis package (R package mixOmics) was used to integrate the molecular changes characterizing the CSF of MB patients. Differentially expressed transcripts, metabolites, and lipids in CSF were discriminatory for the presence of MB but not the exact molecular subtype. One hundred and ten genes and ten circular RNAs were differentially expressed in MB CSF compared with normal, representing TGF-β signaling, TNF-α signaling via NF-kB, and adipogenesis pathways. Tricarboxylic acid cycle and other metabolites (malate, fumarate, succinate, α-ketoglutarate, hydroxypyruvate, N-acetyl-aspartate) and total triacylglycerols were significantly upregulated in MB CSF compared with normal CSF. Although separating MBs into subgroups using transcriptomic, metabolomic, and lipid signatures in CSF was challenging, we were able to identify a group of omics signatures that could separate cancer from normal CSF. Metabolic and lipidomic profiles both contained indicators of tumor hypoxia. Our approach provides several candidate signatures that deserve further validation, including the novel circular RNA circ_463, and insights into the impact of MB on the CSF microenvironment.

Evaluation of methods to detect circular RNAs from single-end RNA-sequencing data

Background

Circular RNA (circRNA), a class of RNA molecule with a loop structure, has recently attracted researchers due to its diverse biological functions and potential biomarkers of human diseases. Most of the current circRNA detection methods from RNA-sequencing (RNA-Seq) data utilize the mapping information of paired-end (PE) reads to eliminate false positives. However, much of the practical RNA-Seq data such as cross-linking immunoprecipitation sequencing (CLIP-Seq) data usually contain single-end (SE) reads. It is not clear how well these tools perform on SE RNA-Seq data.

Results

In this study, we present a systematic evaluation of six advanced RNA-based methods and two CLIP-Seq based methods for detecting circRNAs from SE RNA-Seq data. The performances of the methods are rigorously assessed based on precision, sensitivity, F1 score, and true discovery rate. We investigate the impacts of read length, false positive ratio, sequencing depth and PE mapping information on the performances of the methods using simulated SE RNA-Seq simulated datasets. The real datasets used in this study consist of four experimental RNA-Seq datasets with ≥100bp read length and 124 CLIP-Seq samples from 45 studies that contain mostly short-read (≤50bp) RNA-Seq data. The simulation study shows that the sensitivities of most of the methods can be improved by increasing either read length or sequencing depth, and that the levels of false positive rates significantly affect the precision of all methods. Furthermore, the PE mapping information can improve the method’s precision but can not always guarantee the increase of F1 score. Overall, no method is dominant for all SE RNA-Seq data. The RNA-based methods perform better for the long-read datasets but are worse for the short-read datasets. In contrast, the CLIP-Seq based methods outperform the RNA-Seq based methods for all the short-read samples. Combining the results of these methods can significantly improve precision in the CLIP-Seq data.

Conclusions

The results provide a systematic evaluation of circRNA detection methods on SE RNA-Seq data that would facilitate researchers’ strategies in circRNA analysis.

Supplementary Information

The online version contains supplementary material available at (10.1186/s12864-022-08329-7).

The pleiotropic roles of circular and long noncoding RNAs in cutaneous melanoma

Cutaneous melanoma (CM) is a very aggressive disease, often characterized by unresponsiveness to conventional therapies and high mortality rates worldwide. The identification of the activating BRAFV600 mutations in approximately 50% of CM patients has recently fueled the development of novel small-molecule inhibitors that specifically target BRAFV600 -mutant CM. In addition, a major progress in CM treatment has been made by monoclonal antibodies that regulate the immune checkpoint inhibitors. However, although target-based therapies and immunotherapeutic strategies have yielded promising results, CM treatment remains a major challenge. In the last decade, accumulating evidence points to the aberrant expression of different types of noncoding RNAs (ncRNAs) in CM. While studies on microRNAs have grown exponentially leading to significant insights on CM biology, the role of circular RNAs (circRNAs) and long noncoding RNAs (lncRNAs) in this tumor is less understood, and much remains to be discovered. Here, we summarize and critically review the available evidence on the molecular functions of circRNAs and lncRNAs in BRAFV600 -mutant CM and CM immunogenicity, providing recent updates on their functional role in targeted therapy and immunotherapy resistance. In addition, we also include an evaluation of several algorithms and databases for prediction and validation of circRNA and lncRNA functional interactions.

The transcriptional landscape and biomarker potential of circular RNAs in prostate cancer

Background

Circular RNAs (circRNAs) constitute a largely unexplored source for biomarker discovery in prostate cancer (PC). Here, we characterize the biomarker potential of circRNAs in PC, where the need for novel diagnostic and prognostic tools to facilitate more personalized management is pressing.

Methods

We profiled the transcriptomic landscape of circRNAs in PC by total RNA sequencing of 31 adjacent-normal and 143 tumor samples from localized (radical prostatectomy (RP)) and metastatic PC patients (cohort 1, training). Diagnostic and prognostic potential was evaluated in cohort 1, and 39 top circRNA candidates were selected for validation in two additional PC cohorts (cohort 2, n = 111; RP cohort 3, n = 191) by NanoString-based expression analysis. Biochemical recurrence (BCR)-free survival was assessed using Kaplan-Meier, univariate, and multivariate Cox regression analyses. The circRNA candidates were further detected in extracellular vesicle (EV)-enriched plasma samples from PC patients and controls (cohort 4, n = 54).

Results

Expression of circABCC4, circFAT3, circATRNL1, and circITGA7 was highly cancer-specific (area under the curve 0.71–0.86), while low circITGA7 expression was significantly (P < 0.05) associated with BCR in univariate analysis in two RP cohorts. Moreover, we successfully trained and validated a novel 5-circRNA prognostic signature (circKMD1A/circTULP4/circZNF532/circSUMF1/circMKLN1) significantly associated with BCR beyond routine clinicopathological variables (RP cohort 1: P = 0.02, hazard ratio = 2.1; RP cohort 3: P < 0.001, hazard ratio = 2.1). Lastly, we provide proof-of-principle for detection of candidate circRNAs in EV-enriched plasma samples from PC patients.

Conclusions

circRNAs hold great biomarker potential in PC and display both high cancer specificity and association to disease progression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-021-01009-3.

Bioinformatic Analysis of CircRNA from RNA-seq Datasets

Circular RNAs (circRNAs) are a vast class of covalently closed, noncoding RNAs expressed in specific tissues and developmental stages. The molecular, cellular, and pathophysiologic roles of circRNAs are not fully known, but their impact on gene expression programs is beginning to emerge, as circRNAs often associate with RNA-binding proteins and nucleic acids. With rising interest in identifying circRNAs associated with disease processes, it has become particularly important to identify circRNAs in RNA sequencing (RNA-seq) datasets, either generated by the investigator or reported in the literature. Here, we present a methodology to identify and analyze circRNAs in RNA-seq datasets, including those archived in repositories. We elaborate on the unique features of circRNAs that require specialized attention in RNA-seq datasets, the software packages designed for circRNA identification, the ongoing efforts to reconstruct the body of circRNAs starting from unique circularizing junctions, and the interacting factors that can be proposed from putative circRNA body sequences. We discuss the advantages and limitations of the current approaches for high-throughput circRNA analysis from RNA-sequencing datasets and identify areas that would benefit from the development of superior bioinformatic tools.

Detecting differentially expressed circular RNAs from multiple quantification methods using a generalized linear mixed model

Finding differentially expressed circular RNAs (circRNAs) is instrumental to understanding the molecular basis of phenotypic variation between conditions linked to circRNA-involving mechanisms. To date, several methods have been developed to identify circRNAs, and combining multiple tools is becoming an established approach to improve the detection rate and robustness of results in circRNA studies. However, when using a consensus strategy, it is unclear how circRNA expression estimates should be considered and integrated into downstream analysis, such as differential expression assessment. This work presents a novel solution to test circRNA differential expression using quantifications of multiple algorithms simultaneously. Our approach analyzes multiple tools’ circRNA abundance count data within a single framework by leveraging generalized linear mixed models (GLMM), which account for the sample correlation structure within and between the quantification tools. We compared the GLMM approach with three widely used differential expression models, showing its higher sensitivity in detecting and efficiently ranking significant differentially expressed circRNAs. Our strategy is the first to consider combined estimates of multiple circRNA quantification methods, and we propose it as a powerful model to improve circRNA differential expression analysis.

Using Drosophila to uncover molecular and physiological functions of circRNAs

Circular RNAs (circRNAs) are a class of covalently closed RNA molecules generated by backsplicing. circRNAs are expressed in a tissue-specific manner, accumulate with age in neural tissues, and are highly stable. In many cases, circRNAs are generated at the expense of a linear transcript as back-splicing competes with linear splicing. Some circRNAs regulate gene expression in cis, and some circRNAs can be translated into protein. The advent of deep sequencing and new bioinformatic tools has allowed detection of thousands of circRNAs in eukaryotes. Studying the functions of circRNAs is done using a combination of molecular and genetic methods. The unique genetic tools that can be used in studies of Drosophila melanogaster are ideal for deciphering the functions of circRNAs in vivo. These tools include the GAL4-UAS system, which can be used to manipulate the levels of circRNAs with exquisite temporal and spatial control, and genetic interaction screening, which could be used to identify pathways regulated by circRNAs. Research performed in Drosophila has revealed circRNAs production mechanisms, details of their translation, and their physiological functions. Due to their short lifecycle and the existence of excellent neurodegeneration models, Drosophila can also be used to study the role of circRNAs in aging and age-related disorders. Here, we review molecular and genetic tools and methods for detecting, manipulating, and studying circRNAs in Drosophila.

Quantifying full-length circular RNAs in cancer

Circular RNAs (circRNAs) are abundantly expressed in cancer. Their resistance to exonucleases enables them to have potentially stable interactions with different types of biomolecules. Alternative splicing can create different circRNA isoforms that have different sequences and unequal interaction potentials. The study of circRNA function thus requires knowledge of complete circRNA sequences. Here we describe psirc, a method that can identify full-length circRNA isoforms and quantify their expression levels from RNA sequencing data. We confirm the effectiveness and computational efficiency of psirc using both simulated and actual experimental data. Applying psirc on transcriptome profiles from nasopharyngeal carcinoma and normal nasopharynx samples, we discover and validate circRNA isoforms differentially expressed between the two groups. Compared with the assumed circular isoforms derived from linear transcript annotations, some of the alternatively spliced circular isoforms have 100 times higher expression and contain substantially fewer microRNA response elements, showing the importance of quantifying full-length circRNA isoforms.