Sensitive, reliable and robust circRNA detection from RNA-seq with CirComPara2

The function and mechanism of circRNAs in 5-fluorouracil resistance in tumors: Biological mechanisms and future potential

5-Fluorouracil (5-FU) is a well-known chemotherapy drug extensively used in the treatment of breast cancer. It works by inhibiting cancer cell proliferation and inducing cell death through direct incorporation into DNA and RNA via thymidylate synthase (TS). Circular RNAs (circRNAs), a novel family of endogenous non-coding RNAs (ncRNAs) with limited protein-coding potential, contribute to 5-FU resistance. Their identification and targeting are crucial for enhancing chemosensitivity. CircRNAs can regulate tumor formation and invasion by adhering to microRNAs (miRNAs) and interacting with RNA-binding proteins, regulating transcription and translation. MiRNAs can influence enzymes responsible for 5-FU metabolism in cancer cells, affecting their sensitivity or resistance to the drug. In the context of 5-FU resistance, circRNAs can target miRNAs and regulate biological processes such as cell proliferation, cell death, glucose metabolism, hypoxia, epithelial-to-mesenchymal transition (EMT), and drug efflux. This review focuses on the function of circRNAs in 5-FU resistance, discussing the underlying molecular pathways and biological mechanisms. It also presents recent circRNA/miRNA-targeted cancer therapeutic strategies for future clinical application.

Identification of a circular RNA isoform of WASHC2A as a prognostic factor for high-risk paediatric B-ALL patients

Pediatric B-cell acute lymphoblastic leukemia (B-ALL) is a serious disease for which a better understanding of prognostic factors and new therapeutic targets is needed. Circular RNAs (circRNAs) are promising markers due to their stability and differential expression patterns in various diseases. However, their role in pediatric B-ALL patients, particularly in risk stratification and relapse prediction, remains poorly understood. In this study, we comprehensively examined the circRNA landscape in pediatric B-ALL patients, focusing on both high-risk and standard-risk patients. Using advanced sequencing techniques and sophisticated bioinformatics tools, we identified thousands of circRNAs, including a novel circRNA derived from the WASHC2A gene, termed circWASHC2A. CircWASHC2A showed differential expression between high-risk and standard-risk patients and exhibited potential for predicting relapse in high-risk patients. Functional experiments highlighted a role for circWASHC2A in regulating cell cycle progression and mitochondrial respiratory activity in leukaemic cells. Transcriptomic analysis further supported these findings, suggesting the involvement of circWASHC2A in signalling pathways relevant to leukaemia pathogenesis. This study provides in-depth insights into the circRNA landscape of pediatric B-ALL patients and identifies circWASHC2A as a potential biomarker for risk stratification and relapse prediction, with significant implications for tailoring diagnostic and therapeutic strategies in this patient population.

Circular RNA regulatory role in pathological cardiac remodelling

Cardiac remodelling involves structural, cellular and molecular alterations in the heart after injury, resulting in progressive loss of heart function and ultimately leading to heart failure. Circular RNAs (circRNAs) are a recently rediscovered class of non-coding RNAs that play regulatory roles in the pathogenesis of cardiovascular diseases, including heart failure. Thus, a more comprehensive understanding of the role of circRNAs in the processes governing cardiac remodelling may set the ground for the development of circRNA-based diagnostic and therapeutic strategies. In this review, the current knowledge about circRNA origin, conservation, characteristics and function is summarized. Bioinformatics and wet-lab methods used in circRNA research are discussed. The regulatory function of circRNAs in cardiac remodelling mechanisms such as cell death, cardiomyocyte hypertrophy, inflammation, fibrosis and metabolism is highlighted. Finally, key challenges and opportunities in circRNA research are discussed, and orientations for future work to address the pharmacological potential of circRNAs in heart failure are proposed.

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.

Functional relevance of circRNA aberrant expression in pediatric acute leukemia with KMT2A::AFF1 fusion

ABSTRACT

Circular RNAs (circRNAs) are emerging molecular players in leukemogenesis and promising therapeutic targets. In KMT2A::AFF1 (MLL::AF4)-rearranged leukemia, an aggressive disease compared with other pediatric B-cell precursor (BCP) acute lymphoblastic leukemia (ALL), data about circRNAs are limited. Here, we disclose the circRNA landscape of infant patients with KMT2A::AFF1 translocated BCP-ALL showing dysregulated, mostly ectopically expressed, circRNAs in leukemia cells. Most of these circRNAs, apart from circHIPK3 and circZNF609, previously associated with oncogenic behavior in ALL, are still uncharacterized. An in vitro loss-of-function screening identified an oncogenic role of circFKBP5, circKLHL2, circNR3C1, and circPAN3 in KMT2A::AFF1 ALL, whose silencing affected cell proliferation and apoptosis. Further study in an extended cohort disclosed a significantly correlated expression of these oncogenic circRNAs and their putative involvement in common regulatory networks. Moreover, it showed that circAFF1 upregulation occurs in a subset of cases with HOXA KMT2A::AFF1 ALL. Collectively, functional analyses and patient data reveal oncogenic circRNA upregulation as a relevant mechanism that sustains the malignant cell phenotype in KMT2A::AFF1 ALL.

Biogenesis and Function of circRNAs in Pulmonary Fibrosis

Pulmonary fibrosis is a class of fibrosing interstitial lung diseases caused by many pathogenic factors inside and outside the lung, with unknown mechanisms and without effective treatment. Therefore, a comprehensive understanding of the molecular mechanism implicated in pulmonary fibrosis pathogenesis is urgently needed to develop new and effective measures. Although circRNAs have been widely acknowledged as new contributors to the occurrence and development of diseases, only a small number of circRNAs have been functionally characterized in pulmonary fibrosis. Here, we systematically review the biogenesis and functions of circRNAs and focus on how circRNAs participate in pulmonary fibrogenesis by influencing various cell fates. Meanwhile, we analyze the current exploration of circRNAs as a diagnostic biomarker, vaccine, and therapeutic target in pulmonary fibrosis and objectively discuss the challenges of circRNA- based therapy for pulmonary fibrosis. We hope that the review of the implication of circRNAs will provide new insights into the development circRNA-based approaches to treat pulmonary fibrosis.

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.

New insight into circRNAs: characterization, strategies, and biomedical applications

Circular RNAs (circRNAs) are a class of covalently closed, endogenous ncRNAs. Most circRNAs are derived from exonic or intronic sequences by precursor RNA back-splicing. Advanced high-throughput RNA sequencing and experimental technologies have enabled the extensive identification and characterization of circRNAs, such as novel types of biogenesis, tissue-specific and cell-specific expression patterns, epigenetic regulation, translation potential, localization and metabolism. Increasing evidence has revealed that circRNAs participate in diverse cellular processes, and their dysregulation is involved in the pathogenesis of various diseases, particularly cancer. In this review, we systematically discuss the characterization of circRNAs, databases, challenges for circRNA discovery, new insight into strategies used in circRNA studies and biomedical applications. Although recent studies have advanced the understanding of circRNAs, advanced knowledge and approaches for circRNA annotation, functional characterization and biomedical applications are continuously needed to provide new insights into circRNAs. The emergence of circRNA-based protein translation strategy will be a promising direction in the field of biomedicine.

JCcirc: circRNA full-length sequence assembly through integrated junction contigs

Recent studies have shed light on the potential of circular RNA (circRNA) as a biomarker for disease diagnosis and as a nucleic acid vaccine. The exploration of these functionalities requires correct circRNA full-length sequences; however, existing assembly tools can only correctly assemble some circRNAs, and their performance can be further improved. Here, we introduce a novel feature known as the junction contig (JC), which is an extension of the back-splice junction (BSJ). Leveraging the strengths of both BSJ and JC, we present a novel method called JCcirc (https://github.com/cbbzhang/JCcirc). It enables efficient reconstruction of all types of circRNA full-length sequences and their alternative isoforms using splice graphs and fragment coverage. Our findings demonstrate the superiority of JCcirc over existing methods on human simulation datasets, and its average F1 score surpasses CircAST by 0.40 and outperforms both CIRI-full and circRNAfull by 0.13. For circRNAs below 400 bp, 400-800 bp, 800 bp-1200 bp and above 1200 bp, the correct assembly rates are 0.13, 0.09, 0.04 and 0.03 higher, respectively, than those achieved by existing methods. Moreover, JCcirc also outperforms existing assembly tools on other five model species datasets and real sequencing datasets. These results show that JCcirc is a robust tool for accurately assembling circRNA full-length sequences, laying the foundation for the functional analysis of circRNAs.

Large-scale benchmarking of circRNA detection tools reveals large differences in sensitivity but not in precision

The detection of circular RNA molecules (circRNAs) is typically based on short-read RNA sequencing data processed using computational tools. Numerous such tools have been developed, but a systematic comparison with orthogonal validation is missing. Here, we set up a circRNA detection tool benchmarking study, in which 16 tools detected more than 315,000 unique circRNAs in three deeply sequenced human cell types. Next, 1,516 predicted circRNAs were validated using three orthogonal methods. Generally, tool-specific precision is high and similar (median of 98.8%, 96.3% and 95.5% for qPCR, RNase R and amplicon sequencing, respectively) whereas the sensitivity and number of predicted circRNAs (ranging from 1,372 to 58,032) are the most significant differentiators. Of note, precision values are lower when evaluating low-abundance circRNAs. We also show that the tools can be used complementarily to increase detection sensitivity. Finally, we offer recommendations for future circRNA detection and validation.

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.

Challenges and opportunities for circRNA identification and delivery

Circular RNAs (circRNAs) are evolutionarily conserved noncoding RNAs with tissue-specific expression patterns, and exert unique cellular functions that have the potential to become biomarkers in therapeutic applications. Therefore, accurate and sensitive detection of circRNA with facile platforms is essential for better understanding of circRNA biological processes and circRNA-related disease diagnosis and prognosis; and precise regulation of circRNA through efficient delivery of circRNA or siRNA is critical for therapeutic purposes. Here, we reviewed the current development of circRNA identification methodologies, including overviewing the purification steps, summarizing the sequencing methods of circRNA, as well as comparing the advantages and disadvantages of traditional and new detection methods. Then, we discussed the delivery and manipulation strategies for circRNAs in both research and clinic treatment. Finally, the challenges and opportunities of analyzing circRNAs were addressed.

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.

nf-core/circrna: a portable workflow for the quantification, miRNA target prediction and differential expression analysis of circular RNAs

BACKGROUND

Circular RNAs (circRNAs) are a class of covalenty closed non-coding RNAs that have garnered increased attention from the research community due to their stability, tissue-specific expression and role as transcriptional modulators via sequestration of miRNAs. Currently, multiple quantification tools capable of detecting circRNAs exist, yet none delineate circRNA-miRNA interactions, and only one employs differential expression analysis. Efforts have been made to bridge this gap by way of circRNA workflows, however these workflows are limited by both the types of analyses available and computational skills required to run them.

RESULTS

We present nf-core/circrna, a multi-functional, automated high-throughput pipeline implemented in nextflow that allows users to characterise the role of circRNAs in RNA Sequencing datasets via three analysis modules: (1) circRNA quantification, robust filtering and annotation (2) miRNA target prediction of the mature spliced sequence and (3) differential expression analysis. nf-core/circrna has been developed within the nf-core framework, ensuring robust portability across computing environments via containerisation, parallel deployment on cluster/cloud-based infrastructures, comprehensive documentation and maintenance support.

CONCLUSION

nf-core/circrna reduces the barrier to entry for researchers by providing an easy-to-use, platform-independent and scalable workflow for circRNA analyses. Source code, documentation and installation instructions are freely available at https://nf-co.re/circrna and https://github.com/nf-core/circrna .

Identification, biogenesis, function, and mechanism of action of circular RNAs in plants

Circular RNAs (circRNAs) are a class of single-stranded, closed RNA molecules with unique functions that are ubiquitously expressed in all eukaryotes. The biogenesis of circRNAs is regulated by specific cis-acting elements and trans-acting factors in humans and animals. circRNAs mainly exert their biological functions by acting as microRNA sponges, forming R-loops, interacting with RNA-binding proteins, or being translated into polypeptides or proteins in human and animal cells. Genome-wide identification of circRNAs has been performed in multiple plant species, and the results suggest that circRNAs are abundant and ubiquitously expressed in plants. There is emerging compelling evidence to suggest that circRNAs play essential roles during plant growth and development as well as in the responses to biotic and abiotic stress. However, compared with recent advances in human and animal systems, the roles of most circRNAs in plants are unclear at present. Here we review the identification, biogenesis, function, and mechanism of action of plant circRNAs, which will provide a fundamental understanding of the characteristics and complexity of circRNAs in plants.

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.

Circular RNAs as a potential source of neoepitopes in cancer

Neoepitopes have attracted much attention as targets for immunotherapy against cancer. Therefore, efficient neoepitope screening technology is an essential step in the development of personalized vaccines. Circular RNAs (circRNAs) are generated by back-splicing and have a single-stranded continuous circular structure. So far, various circRNAs have been poorly characterized, though new evidence suggests that a few translated circRNAs may play a role in cancer. In the present study, circRNA was used as a source of neoepitope, a novel strategy as circRNA-derived neoepitopes have never been previously explored. The present study reports CIRC_neo (circRNA-derived neoepitope prediction pipeline), which is a comprehensive and automated bioinformatic pipeline for the prediction of circRNA-derived neoepitopes from RNA sequencing data. The computational prediction from sequencing data requires complex computational workflows to identify circRNAs, derive the resulting peptides, infer the types of human leukocyte antigens (HLA I and HLA II) in patients, and predict the neoepitopes binding to these antigens. The present study proposes a novel source of neoepitopes. The study focused on cancer-specific circRNAs, which have greatly expanded the source pool for neoepitope discovery. The statistical analysis of different features of circRNA-derived neoepitopes revealed that circRNAs could produce long proteins or truncated proteins. Because the peptides were completely foreign to the human body, they could be highly immunogenic. Importantly, circRNA-derived neoepitopes capable of binding to HLA were discovered. In the current study, circRNAs were systematically analyzed, revealing potential targets and novel research clues for cancer diagnosis, treatment, and prospective personalized vaccine research.

Discovery of fusion circular RNAs in leukemia with KMT2A::AFF1 rearrangements by the new software CircFusion

Chromosomal translocations in cancer genomes, key players in many types of cancers, generate chimeric proteins that drive oncogenesis. Genomes with chromosomal rearrangements can also produce fusion circular RNAs (f-circRNAs) by backsplicing of chimeric transcripts, as first shown in leukemias with PML::RARα and KMT2A::MLLT3 translocations and later in solid cancers. F-circRNAs contribute to the oncogenic processes and reinforce the oncogenic activity of chimeric proteins. In leukemia with KMT2A::AFF1 (MLL::AF4) fusions, we previously reported specific alterations of circRNA expression, but nothing was known about f-circRNAs. Due to the presence of two chimeric sequences, fusion and backsplice junctions, the identification of f-circRNAs with available tools is challenging, possibly resulting in the underestimation of this RNA species, especially when the breakpoint is not known. We developed CircFusion, a new software tool to detect linear fusion transcripts and f-circRNAs from RNA-seq data, both in samples for which the breakpoints are known and when the information about the joined exons is missing. CircFusion can detect linear and circular chimeric transcripts deriving from the main and reciprocal translocations also in the presence of multiple breakpoints, which are common in malignant cells. Benchmarking tests on simulated and real datasets of cancer samples with previously experimentally determined f-circRNAs showed that CircFusion provides reliable predictions and outperforms available methods for f-circRNA detection. We discovered and validated novel f-circRNAs in acute leukemia harboring KMT2A::AFF1 rearrangements, leading the way to future functional studies aimed to unveil their role in this malignancy.

Promising Roles of Circular RNAs as Biomarkers and Targets for Potential Diagnosis and Therapy of Tuberculosis

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb) infection, remains one of the most threatening infectious diseases worldwide. A series of challenges still exist for TB prevention, diagnosis and treatment, which therefore require more attempts to clarify the pathological and immunological mechanisms in the development and progression of TB. Circular RNAs (circRNAs) are a large class of non-coding RNA, mostly expressed in eukaryotic cells, which are generated by the spliceosome through the back-splicing of linear RNAs. Accumulating studies have identified that circRNAs are widely involved in a variety of physiological and pathological processes, acting as the sponges or decoys for microRNAs and proteins, scaffold platforms for proteins, modulators for transcription and special templates for translation. Due to the stable and widely spread characteristics of circRNAs, they are expected to serve as promising prognostic/diagnostic biomarkers and therapeutic targets for diseases. In this review, we briefly describe the biogenesis, classification, detection technology and functions of circRNAs, and, in particular, outline the dynamic, and sometimes aberrant changes of circRNAs in TB. Moreover, we further summarize the recent progress of research linking circRNAs to TB-related pathogenetic processes, as well as the potential roles of circRNAs as diagnostic biomarkers and miRNAs sponges in the case of Mtb infection, which is expected to enhance our understanding of TB and provide some novel ideas about how to overcome the challenges associated TB in the future.

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.

Circular RNA and Its Roles in the Occurrence, Development, Diagnosis of Cancer

Circular RNAs (circRNAs) are non-coding single-stranded covalently closed circular RNA, mainly produced by reverse splicing of exons of precursor mRNAs (pre-mRNAs). The characteristics of high abundance, strong specificity, and good stability of circRNAs have been discovered. A large number of studies have reported its various functions and mechanisms in biological events, such as the occurrence and development of cancer. In this review, we focus on the classification, characterization, biogenesis, functions of circRNAs, and the latest advances in cancer research. The development of circRNAs as biomarkers in cancer diagnosis and treatment also provides new ideas for studying circRNAs research.

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.