Accurate quantification of circular RNAs identifies extensive circular isoform switching events

Circular RNAs from bovine blastocysts can interact with miRNAs/tsRNAs from embryonic extracellular vesicles and regulate hatching

Circular RNAs (circRNAs) are endogenous biological macromolecules that regulate various biological processes including embryo development. However, little is known about which circRNAs are present in bovine preimplantation embryos and their respective roles. Here, we characterized the expression profile of circRNAs in bovine blastocysts for the first time. We detected 25,700 circRNAs in total, with 12,630 circRNAs uniquely expressed in blastocysts compared to degenerated embryos. CircRNA alternative splicing (AS) events were also found more frequently in blastocysts than in degenerated embryos (299 vs 258). Additionally, 410 circRNAs, among which 11 circRNAs with a high potential to encode polypeptides, were found differentially expressed between blastocysts and degenerated embryos. We further predicted and constructed a circRNA-miRNA-mRNA network, wherein differentially expressed circRNAs were shown to bind to bovine preimplantation embryo development-related miRNAs. Employing bioinformatic algorithms we found that differentially expressed circRNAs are associated with differentially expressed miRNAs and transfer RNA-derived small RNAs (tsRNAs) enclosed in embryonic extracellular vesicles (EVs). Furthermore, functional analysis revealed that knockdown of the evolutionarily conserved circAGO2 can inhibit blastocyst hatching. Overall, our study provides the first landscape of circRNAs in bovine preimplantation embryos and highlights the novel role of circRNAs as tsRNA binding partners influencing small RNA sorting and loading into EVs, with circAGO2 playing a regulatory role in bovine blastocyst hatching.

The endogenous association among MMP2/miR-1248/Circ_0087558/miR-643/ MAP2K6 axis can contribute to brain metastasis in basal-like subtype of breast cancer

Brain metastasis in basal-like breast cancer poses a significant challenge in cancer management due to its aggressive nature and limited treatment options. This study conducted a comprehensive analysis to explore the potential role of circular RNAs (circRNAs) as members of endogenous networks in developing breast cancer brain metastasis. Here, we utilized RNA sequencing data from primary breast cancer and brain metastasis tissue with basal-like subtype (n = 11). After quality controlling and preprocessing of fastq files, gene expression of mRNA and circRNAs were extracted from matched samples and normalized. Then, we employed the weighted gene co-expression network analysis approach to identify brain metastasis-associated circRNA modules ( S p e a r m a n Correlation > 0.5 , P - value < 0.05 ). Moreover, we found five protein-coding genes of PHLDA1, SLC12A2, MMP2, RGP1, and MAP2K6, significantly upregulated in brain metastatic tissues compared to primary breast cancer ( FDR < 0.05 ). These genes were enriched in the "GnRH signaling pathway" and "Fluid shear stress and atherosclerosis" pathways ( FDR < 0.05 ). Next, to explore the potential interactions between circRNAs and protein-coding genes, we reconstructed a competing endogenous RNA (ceRNA) network using mutual miRNAs between the circRNA module and upregulated mRNAs. Notably, we could detect two axes of circ_0087558/miR-604/MMP2 and MMP2/miR-1248/Circ_0087558/miR-643/MAP2K6 in ceRNA network. In conclusion, the identified circRNA-miRNA-mRNA axes might be therapeutic targets or diagnostic biomarkers for this challenging subtype of breast cancer. However, due to the small number of samples, further experimental validations are essential.

Decoding the Non-coding: Tools and Databases Unveiling the Hidden World of "Junk" RNAs for Innovative Therapeutic Exploration

Non-coding RNAs are pivotal regulators of gene and protein expression, exerting crucial influences on diverse biological processes. Their dysregulation is frequently implicated in the onset and progression of diseases, notably cancer. A profound comprehension of the intricate mechanisms governing ncRNAs is imperative for devising innovative therapeutic interventions against these debilitating conditions. Significantly, nearly 80% of our genome comprises ncRNAs, underscoring their centrality in cellular processes. The elucidation of ncRNA functions is pivotal for grasping the complexities of gene regulation and its implications for human health. Modern genome sequencing techniques yield vast datasets, stored in specialized databases. To harness this wealth of information and to understand the crosstalk of non-coding RNAs, knowledge of available databases is required, and many new sophisticated computational tools have emerged. These tools play a pivotal role in the identification, prediction, and annotation of ncRNAs, thereby facilitating their experimental validation. This Review succinctly outlines the current understanding of ncRNAs, emphasizing their involvement in disease development. It also highlights the databases and tools instrumental in classifying, annotating, and evaluating ncRNAs. By extracting meaningful biological insights from seemingly "junk" data, these tools empower scientists to unravel the intricate roles of ncRNAs in shaping human health.

Multi-tissue transcriptome profiling linked the association between tissue-specific circRNAs and the heterosis for feed intake and efficiency in chicken

Heterosis has been widely utilized in chickens. The nonadditive inheritance of genes contributes to this biological phenomenon. However, the role of circRNAs played in the heterosis is poorly determined. In this study, we observed divergent heterosis for residual feed intake (RFI) between 2 crossbreds derived from a reciprocal cross between White Leghorns and Beijing You chickens. Then, circRNA landscape for 120 samples covering the hypothalamus, liver, duodenum mucosa and ovary were profiled to elucidate the regulatory mechanisms of heterosis. We detected that a small proportion of circRNAs (7.83-20.35%) were additively and non-additively expressed, in which non-additivity was a major inheritance of circRNAs in the crossbreds. Tissue-specific expression of circRNAs was prevalent across 4 tissues. Weighted gene co-expression network analysis revealed circRNA-mRNA co-expression modules associated with feed intake and RFI in the hypothalamus and liver, and the co-expressed genes were enriched in oxidative phosphorylation pathway. We further identified 8 nonadditive circRNAs highly correlated with 16 nonadditive genes regulating negative heterosis for RFI in the 2 tissues. Circ-ITSN2 was validated in the liver tissue for its significantly positive correlation with PGPEP1L. Moreover, the bioinformatic analysis indicated that candidate circRNAs might be functioned by binding the microRNAs and interacting with the RNA binding proteins. The integration of multi-tissue transcriptome firstly linked the association between tissue-specific circRNAs and the heterosis for feed intake and efficiency in chicken, which provide novel insights into the molecular mechanism underlying heterosis for feed efficiency. The validated circRNAs can act as potential biomarkers for predicting RFI and its heterosis.

WTAP and m6A-modified circRNAs modulation during stress response in acute myeloid leukemia progenitor cells

N6-methyladenosine (m6A) is one of the most prevalent and conserved RNA modifications. It controls several biological processes, including the biogenesis and function of circular RNAs (circRNAs), which are a class of covalently closed-single stranded RNAs. Several studies have revealed that proteotoxic stress response induction could be a relevant anticancer therapy in Acute Myeloid Leukemia (AML). Furthermore, a strong molecular interaction between the m6A mRNA modification factors and the suppression of the proteotoxic stress response has emerged. Since the proteasome inhibition leading to the imbalance in protein homeostasis is strictly linked to the stress response induction, we investigated the role of Bortezomib (Btz) on m6A regulation and in particular its impact on the modulation of m6A-modified circRNAs expression. Here, we show that treating AML cells with Btz downregulated the expression of the m6A regulator WTAP at translational level, mainly because of increased oxidative stress. Indeed, Btz treatment promoted oxidative stress, with ROS generation and HMOX-1 activation and administration of the reducing agent N-acetylcysteine restored WTAP expression. Additionally, we identified m6A-modified circRNAs modulated by Btz treatment, including circHIPK3, which is implicated in protein folding and oxidative stress regulation. These results highlight the intricate molecular networks involved in oxidative and ER stress induction in AML cells following proteotoxic stress response, laying the groundwork for future therapeutic strategies targeting these pathways.

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.

Computational tools for plant genomics and breeding

Plant genomics and crop breeding are at the intersection of biotechnology and information technology. Driven by a combination of high-throughput sequencing, molecular biology and data science, great advances have been made in omics technologies at every step along the central dogma, especially in genome assembling, genome annotation, epigenomic profiling, and transcriptome profiling. These advances further revolutionized three directions of development. One is genetic dissection of complex traits in crops, along with genomic prediction and selection. The second is comparative genomics and evolution, which open up new opportunities to depict the evolutionary constraints of biological sequences for deleterious variant discovery. The third direction is the development of deep learning approaches for the rational design of biological sequences, especially proteins, for synthetic biology. All three directions of development serve as the foundation for a new era of crop breeding where agronomic traits are enhanced by genome design.

ciRS-7 and miR-7 regulate ischemia-induced neuronal death via glutamatergic signaling

Brain functionality relies on finely tuned regulation of gene expression by networks of non-coding RNAs (ncRNAs) such as the one composed by the circular RNA ciRS-7 (also known as CDR1as), the microRNA miR-7, and the long ncRNA Cyrano. We describe ischemia-induced alterations in the ncRNA network both in vitro and in vivo and in transgenic mice lacking ciRS-7 or miR-7. Our data show that cortical neurons downregulate ciRS-7 and Cyrano and upregulate miR-7 expression during ischemia. Mice lacking ciRS-7 exhibit reduced lesion size and motor impairment, while the absence of miR-7 alone results in increased ischemia-induced neuronal death. Moreover, miR-7 levels in pyramidal excitatory neurons regulate neurite morphology and glutamatergic signaling, suggesting a potential molecular link to the in vivo phenotype. Our data reveal the role of ciRS-7 and miR-7 in modulating ischemic stroke outcome, shedding light on the pathophysiological function of intracellular ncRNA networks in the brain.

Circular RNA as a source of neoantigens for cancer vaccines

BACKGROUND

The effectiveness of somatic neoantigen-based immunotherapy is often hindered by the limited number of mutations in tumors with low to moderate mutation burden. Focusing on microsatellite-stable colorectal cancer (CRC), this study investigates the potential of tumor-associated circular RNAs (circRNAs) as an alternative source of neoepitopes in CRC.

METHODS

Tumor-associated circRNAs in CRC were identified using the MiOncoCirc database and ribo-depletion RNA sequencing of paired clinical normal and tumor samples. Candidate circRNA expression was validated by quantitative real-time PCR (RT-qPCR) using divergent primers. TransCirc database was used for translation prediction. Human leukocyte antigen binding affinity of open reading frames from potentially translatable circRNA was predicted using pVACtools. Strong binders from messenger RNA-encoded proteins were excluded using BlastP. The immunogenicity of the candidate antigens was functionally validated through stimulation of naïve CD8+ T cells against the predicted neoepitopes and subsequent analysis of the T cells through enzyme-linked immunospot (ELISpot) assay, intracellular cytokine staining (ICS) and granzyme B (GZMB) reporter. The cytotoxicity of T cells trained with antigen peptides was further tested using patient-derived organoids.

RESULTS

We identified a neoepitope from circRAPGEF5 that is upregulated in CRC tumor samples from MiOncoCirc database, and two neoepitopes from circMYH9, which is upregulated across various tumor samples from our matched clinical samples. The translation potential of candidate peptides was supported by Clinical Proteomic Tumor Analysis Consortium database using PepQuery. The candidate peptides elicited antigen-specific T cells response and expansion, evidenced by various assays including ELISpot, ICS and GZMB reporter. Furthermore, T cells trained with circMYH9 peptides were able to specifically target and eliminate tumor-derived organoids but not match normal organoids. This observation underscores the potential of circRNAs as a source of immunogenic neoantigens. Lastly, circMYH9 was enriched in the liquid biopsies of patients with CRC, thus enabling a detection-to-vaccination treatment strategy for patients with CRC.

CONCLUSIONS

Our findings underscore the feasibility of tumor-associated circRNAs as an alternative source of neoantigens for cancer vaccines targeting tumors with moderate mutation levels.

Identification and Characterisation of the CircRNAs Involved in the Regulation of Leaf Colour in Quercus mongolica

Circular RNAs (circRNAs) are important regulatory molecules involved in various biological processes. However, the potential function of circRNAs in the turning red process of Quercus mongolica leaves is unclear. This study used RNA-seq data to identify 6228 circRNAs in leaf samples from four different developmental stages and showed that 88 circRNAs were differentially expressed. A correlation analysis was performed between anthocyanins and the circRNAs. A total of 16 circRNAs that may be involved in regulating the colour of Mongolian oak leaves were identified. CircRNAs may affect the colour of Q. mongolica leaves by regulating auxin, cytokinin, gibberellin, ethylene, and abscisic acid. This study revealed the potential role of circRNAs in the colour change of Q. mongolica leaves.

cirCodAn: A GHMM-based tool for accurate prediction of coding regions in circRNA

Studies focusing on characterizing circRNAs with the potential to translate into peptides are quickly advancing. It is helping to elucidate the roles played by circRNAs in several biological processes, especially in the emergence and development of diseases. While various tools are accessible for predicting coding regions within linear sequences, none have demonstrated accurate open reading frame detection in circular sequences, such as circRNAs. Here, we present cirCodAn, a novel tool designed to predict coding regions in circRNAs. We evaluated the performance of cirCodAn using datasets of circRNAs with strong translation evidence and showed that cirCodAn outperformed the other tools available to perform a similar task. Our findings demonstrate the applicability of cirCodAn to identify coding regions in circRNAs, which reveals the potential of use of cirCodAn in future research focusing on elucidating the biological roles of circRNAs and their encoded proteins. cirCodAn is freely available at https://github.com/denilsonfbar/cirCodAn.

Accurate Assembly of Circular RNAs with TERRACE

Circular RNA (circRNA) is a class of RNA molecules that forms a closed loop with its 5' and 3' ends covalently bonded. Due to this specific structure circRNAs are more stable than linear RNAs, admit distinct biological properties and functions, and have been proven to be promising biomarkers. Circular RNAs were severely overlooked previously owing to the biases in the RNA-seq protocols and in the detection algorithms, but recently gained tremendous attentions in both aspects. However, most existing methods for assembling circRNAs heavily rely on the annotated transcriptomes, and hence exhibit unsatisfactory accuracy when a high-quality transcriptome is unavailable. Here we present TERRACE, a new algorithm for full-length assembly of circRNAs from paired-end total RNA-seq data. TERRACE uses the splice graph as the underlying data structure to organize the splicing and coverage information. We transform the problem of assembling circRNAs into finding two paths that "bridge" the three fragments in the splice graph induced by back-spliced reads. To solve this formulation, we adopted a definition for optimal bridging paths and a dynamic programming algorithm to calculate such paths, an approach that was proven useful for assembling linear RNAs. TERRACE features an efficient algorithm to detect back-spliced reads that are missed by RNA-seq aligners, contributing to its much improved sensitivity. It also incorporates a new machine-learning approach that is trained to assign a confidence score to each assembled circRNA, which is shown superior to using abundance for scoring. TERRACE is compared with leading circRNA detection methods on both simulations and biological datasets. Our method consistently outperforms by a large margin in sensitivity while maintaining better or comparable precision. In particular, when the annotations are not provided, TERRACE can assemble 123%-412% more correct circRNAs than state-of-the-art methods on human tissues. TERRACE presents a major leap on assembling full-length circRNAs from RNA-seq data, and we expect it to be widely used in the downstream research on circRNAs.

Early-stage idiopathic Parkinson's disease is associated with reduced circular RNA expression

Neurodegeneration in Parkinson's disease (PD) precedes diagnosis by years. Early neurodegeneration may be reflected in RNA levels and measurable as a biomarker. Here, we present the largest quantification of whole blood linear and circular RNAs (circRNA) in early-stage idiopathic PD, using RNA sequencing data from two cohorts (PPMI = 259 PD, 161 Controls; ICICLE-PD = 48 PD, 48 Controls). We identified a replicable increase in TMEM252 and LMNB1 gene expression in PD. We identified novel differences in the expression of circRNAs from ESYT2, BMS1P1 and CCDC9, and replicated trends of previously reported circRNAs. Overall, using circRNA as a diagnostic biomarker in PD did not show any clear improvement over linear RNA, minimising its potential clinical utility. More interestingly, we observed a general reduction in circRNA expression in both PD cohorts, accompanied by an increase in RNASEL expression. This imbalance implicates the activation of an innate antiviral immune response and suggests a previously unknown aspect of circRNA regulation in PD.

Novel Insights into the Circadian Rhythms Based on Long Noncoding and Circular RNA Profiling

Circadian rhythm disorders pose major risks to human health and animal production activity, and the hypothalamus is the center of circadian rhythm regulation. However, the epigenetic regulation of circadian rhythm based on farm animal models has been poorly investigated. We collected chicken hypothalamus samples at seven time points in one light/dark cycle and performed long noncoding RNA (lncRNA), circular RNA (circRNA), and mRNA sequencing to detect biomarkers associated with circadian rhythm. We enhanced the comprehensive expression profiling of ncRNAs and mRNAs in the hypothalamus and found two gene sets (circadian rhythm and retinal metabolism) associated with the light/dark cycle. Noncoding RNA networks with circadian expression patterns were identified by differential expression and circadian analysis was provided that included 38 lncRNAs, 15 circRNAs, and 200 candidate genes. Three lncRNAs (ENSGALT00000098661, ENSGALT00000100816, and MSTRG.16980.1) and one circRNA (novel_circ_010168) in the ncRNA-mRNA regulatory network were identified as key molecules influencing circadian rhythm by regulating AOX1 in retinal metabolism. These ncRNAs were predicted to be related to pernicious anemia, gonadal, eye disease and other disorders in humans. Together, the findings of this study provide insights into the epigenetic mechanisms of circadian rhythm and reveal AOX1 as a promising target of circadian rhythm regulation.

TCCIA: a comprehensive resource for exploring CircRNA in cancer immunotherapy

BACKGROUND

Immunotherapies targeting immune checkpoints have gained increasing attention in cancer treatment, emphasizing the need for predictive biomarkers. Circular RNAs (circRNAs) have emerged as critical regulators of tumor immunity, particularly in the PD-1/PD-L1 pathway, and have shown potential in predicting immunotherapy efficacy. Yet, the detailed roles of circRNAs in cancer immunotherapy are not fully understood. While existing databases focus on either circRNA profiles or immunotherapy cohorts, there is currently no platform that enables the exploration of the intricate interplay between circRNAs and anti-tumor immunotherapy. A comprehensive resource combining circRNA profiles, immunotherapy responses, and clinical outcomes is essential to advance our understanding of circRNA-mediated tumor-immune interactions and to develop effective biomarkers.

METHODS

To address these gaps, we constructed The Cancer CircRNA Immunome Atlas (TCCIA), the first database that combines circRNA profiles, immunotherapy response data, and clinical outcomes across multicancer types. The construction of TCCIA involved applying standardized preprocessing to the raw sequencing FASTQ files, characterizing circRNA profiles using an ensemble approach based on four established circRNA detection tools, analyzing tumor immunophenotypes, and compiling immunotherapy response data from diverse cohorts treated with immune checkpoint blockades (ICBs).

RESULTS

TCCIA encompasses over 4,000 clinical samples obtained from 25 cohorts treated with ICBs along with other treatment modalities. The database provides researchers and clinicians with a cloud-based platform that enables interactive exploration of circRNA data in the context of ICB. The platform offers a range of analytical tools, including browse of identified circRNAs, visualization of circRNA abundance and correlation, association analysis between circRNAs and clinical variables, assessment of the tumor immune microenvironment, exploration of tumor molecular signatures, evaluation of treatment response or prognosis, and identification of altered circRNAs in immunotherapy-sensitive and resistant tumors. To illustrate the utility of TCCIA, we showcase two examples, including circTMTC3 and circMGA, by employing analysis of large-scale melanoma and bladder cancer cohorts, which unveil distinct impacts and clinical implications of different circRNA expression in cancer immunotherapy.

CONCLUSIONS

TCCIA represents a significant advancement over existing resources, providing a comprehensive platform to investigate the role of circRNAs in immuno-oncology.

circAtlas 3.0: a gateway to 3 million curated vertebrate circular RNAs based on a standardized nomenclature scheme

Recent studies have demonstrated the important regulatory role of circRNAs, but an in-depth understanding of the comprehensive landscape of circRNAs across various species still remains unexplored. The current circRNA databases are often species-restricted or based on outdated datasets. To address this challenge, we have developed the circAtlas 3.0 database, which contains a rich collection of 2674 circRNA sequencing datasets, curated to delineate the landscape of circRNAs within 33 distinct tissues spanning 10 vertebrate species. Notably, circAtlas 3.0 represents a substantial advancement over its precursor, circAtlas 2.0, with the number of cataloged circRNAs escalating from 1 007 087 to 3 179 560, with 2 527 528 of them being reconstructed into full-length isoforms. circAtlas 3.0 also introduces several notable enhancements, including: (i) integration of both Illumina and Nanopore sequencing datasets to detect circRNAs of extended lengths; (ii) employment of a standardized nomenclature scheme for circRNAs, providing information of the host gene and full-length circular exons; (iii) inclusion of clinical cancer samples to explore the biological function of circRNAs within the context of cancer and (iv) links to other useful resources to enable user-friendly analysis of target circRNAs. The updated circAtlas 3.0 provides an important platform for exploring the evolution and biological implications of vertebrate circRNAs, and is freely available at http://circatlas.biols.ac.cn and https://ngdc.cncb.ac.cn/circatlas.

A Circulating Panel of circRNA Biomarkers for the Noninvasive and Early Detection of Pancreatic Ductal Adenocarcinoma

BACKGROUND & AIMS

Pancreatic ductal adenocarcinoma (PDAC) is one of the most fatal malignancies. Delayed manifestation of symptoms and lack of specific diagnostic markers lead patients being diagnosed with PDAC at advanced stages. This study aimed to develop a circular RNA (circRNA)-based biomarker panel to facilitate noninvasive and early detection of PDAC.

METHODS

A systematic genome-wide discovery of circRNAs overexpressed in patients with PDAC was conducted. Subsequently, validation of the candidate markers in the primary tumors from patients with PDAC was performed, followed by their translation into a plasma-based liquid biopsy assay by analyzing 2 independent clinical cohorts of patients with PDAC and nondisease controls. The performance of the circRNA panel was assessed in conjunction with the plasma levels of cancer antigen 19-9 for the early detection of PDAC.

RESULTS

Initially, a panel of 10 circRNA candidates was identified during the discovery phase. Subsequently, the panel was reduced to 5 circRNAs in the liquid biopsy-based assay, which robustly identified patients with PDAC and distinguished between early-stage (stage I/II) and late-stage (stage III/IV) disease. The areas under the curve of this diagnostic panel for the detection of early-stage PDAC were 0.83 and 0.81 in the training and validation cohorts, respectively. Moreover, when this panel was combined with cancer antigen 19-9 levels, the diagnostic performance for identifying patients with PDAC improved remarkably (area under the curve, 0.94) for patients in the validation cohort. Furthermore, the circRNA panel could also efficiently identify patients with PDAC (area under the curve, 0.85) who were otherwise deemed clinically cancer antigen 19-9-negative (<37 U/mL).

CONCLUSIONS

A circRNA-based biomarker panel with a robust noninvasive diagnostic potential for identifying patients with early-stage PDAC was developed.

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.

Expression of circular RNAs in myelodysplastic neoplasms and their association with mutations in the splicing factor gene SF3B1

Mutations in the splicing factor 3b subunit 1 (SF3B1) gene are frequent in myelodysplastic neoplasms (MDS). Because the splicing process is involved in the production of circular RNAs (circRNAs), we investigated the impact of SF3B1 mutations on circRNA processing. Using RNA sequencing, we measured circRNA expression in CD34+ bone marrow MDS cells. We defined circRNAs deregulated in a heterogeneous group of MDS patients and described increased circRNA formation in higher-risk MDS. We showed that the presence of SF3B1 mutations did not affect the global production of circRNAs; however, deregulation of specific circRNAs was observed. Particularly, we demonstrated that strong upregulation of circRNAs processed from the zinc finger E-box binding homeobox 1 (ZEB1) transcription factor; this upregulation was exclusive to SF3B1-mutated patients and was not observed in those with mutations in other splicing factors or other recurrently mutated genes, or with other clinical variables. Furthermore, we focused on the most upregulated ZEB1-circRNA, hsa_circ_0000228, and, by its knockdown, we demonstrated that its expression is related to mitochondrial activity. Using microRNA analyses, we proposed miR-1248 as a direct target of hsa_circ_0000228. To conclude, we demonstrated that mutated SF3B1 leads to deregulation of ZEB1-circRNAs, potentially contributing to the defects in mitochondrial metabolism observed in SF3B1-mutated MDS.

A CircRNA-miRNA-mRNA Network for Exploring Doxorubicin- and Myocet-Induced Cardiotoxicity in a Translational Porcine Model

Despite the widespread use of doxorubicin (DOX) as a chemotherapeutic agent, its severe cumulative cardiotoxicity represents a significant limitation. While the liposomal encapsulation of doxorubicin (Myocet, MYO) reduces cardiotoxicity, it is crucial to understand the molecular background of doxorubicin-induced cardiotoxicity. Here, we examined circular RNA expression in a translational model of pigs treated with either DOX or MYO and its potential impact on the global gene expression pattern in the myocardium. This study furthers our knowledge about the regulatory network of circRNA/miRNA/mRNA and its interaction with chemotherapeutics. Domestic pigs were treated with three cycles of anthracycline drugs (DOX, n = 5; MYO, n = 5) to induce cardiotoxicity. Untreated animals served as controls (control, n = 3). We applied a bulk mRNA-seq approach and the CIRIquant algorithm to identify circRNAs. The most differentially regulated circRNAs were validated under cell culture conditions, following forecasting of the circRNA-miRNA-mRNA network. We identified eight novel significantly regulated circRNAs from exonic and mitochondrial regions in the porcine myocardium. The forecasted circRNA-miRNA-mRNA network suggested candidate circRNAs that sponge miR-17, miR-15b, miR-130b, the let-7 family, and miR125, together with their mRNA targets. The identified circRNA-miRNA-mRNA network provides an updated, coherent view of the mechanisms involved in anthracycline-induced cardiotoxicity.

circRNA-miRNA-mRNA Deregulated Network in Ischemic Heart Failure Patients

Noncoding RNAs (ncRNAs), which include circular RNAs (circRNAs) and microRNAs (miRNAs), regulate the development of cardiovascular diseases (CVD). Notably, circRNAs can interact with miRNAs, influencing their specific mRNA targets' levels and shaping a competing endogenous RNAs (ceRNA) network. However, these interactions and their respective functions remain largely unexplored in ischemic heart failure (IHF). This study is aimed at identifying circRNA-centered ceRNA networks in non-end-stage IHF. Approximately 662 circRNA-miRNA-mRNA interactions were identified in the heart by combining state-of-the-art bioinformatics tools with experimental data. Importantly, KEGG terms of the enriched mRNA indicated CVD-related signaling pathways. A specific network centered on circBPTF was validated experimentally. The levels of let-7a-5p, miR-18a-3p, miR-146b-5p, and miR-196b-5p were enriched in circBPTF pull-down experiments, and circBPTF silencing inhibited the expression of HDAC9 and LRRC17, which are targets of miR-196b-5p. Furthermore, as suggested by the enriched pathway terms of the circBPTF ceRNA network, circBPTF inhibition elicited endothelial cell cycle arrest. circBPTF expression increased in endothelial cells exposed to hypoxia, and its upregulation was confirmed in cardiac samples of 36 end-stage IHF patients compared to healthy controls. In conclusion, circRNAs act as miRNA sponges, regulating the functions of multiple mRNA targets, thus providing a novel vision of HF pathogenesis and laying the theoretical foundation for further experimental studies.

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 RNA transcriptome across multiple tissues reveal skeletal muscle-specific circPSME4 regulating myogenesis

There are significant differences in meat production, growth rate and other traits between Western commercial pigs and Chinese local pigs. Comparative transcriptome approaches have identified many coding and non-coding candidate genes associated various traits. However, the expression and function of circular RNAs (circRNAs) in different pig tissues are largely unknown. In this study, we conducted a comprehensive analysis of the genome-wide circRNA expression profile across ten tissues in Luchuan (a Chinese local breed) and Duroc (a Western commercial breed) pigs. We identified a total of 56,254 circRNAs, of which 42.9 % were not previously annotated. We found that 33.7 % of these circRNAs were differentially expressed. Enrichment analysis revealed that differentially expressed circRNAs might contribute to the phenotypic differentiation between Luchuan and Duroc pigs. We identified 538 tissue-specific circRNAs, most of which were specifically expressed in the brain and skeletal muscle. Competitive endogenous RNA network analysis suggested that skeletal muscle-specific circPSME4 was co-expressed with MYOD1 and targeted by ssc-miR-181d-3p. Functional analysis revealed that circPSME4 knockdown could promote the proliferation and differentiation of myoblasts. Together, our findings provide valuable resources of circRNAs for animal breeding and biomedical research. We demonstrated that circPSME4 is a novel regulator of skeletal muscle development.

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.

Current perspectives on mass spectrometry-based immunopeptidomics: the computational angle to tumor antigen discovery

Identification of tumor antigens presented by the human leucocyte antigen (HLA) molecules is essential for the design of effective and safe cancer immunotherapies that rely on T cell recognition and killing of tumor cells. Mass spectrometry (MS)-based immunopeptidomics enables high-throughput, direct identification of HLA-bound peptides from a variety of cell lines, tumor tissues, and healthy tissues. It involves immunoaffinity purification of HLA complexes followed by MS profiling of the extracted peptides using data-dependent acquisition, data-independent acquisition, or targeted approaches. By incorporating DNA, RNA, and ribosome sequencing data into immunopeptidomics data analysis, the proteogenomic approach provides a powerful means for identifying tumor antigens encoded within the canonical open reading frames of annotated coding genes and non-canonical tumor antigens derived from presumably non-coding regions of our genome. We discuss emerging computational challenges in immunopeptidomics data analysis and tumor antigen identification, highlighting key considerations in the proteogenomics-based approach, including accurate DNA, RNA and ribosomal sequencing data analysis, careful incorporation of predicted novel protein sequences into reference protein database, special quality control in MS data analysis due to the expanded and heterogeneous search space, cancer-specificity determination, and immunogenicity prediction. The advancements in technology and computation is continually enabling us to identify tumor antigens with higher sensitivity and accuracy, paving the way toward the development of more effective cancer immunotherapies.

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.

Circular stable intronic RNAs possess distinct biological features and are deregulated in bladder cancer

Until recently, intronic lariats were regarded as short-lasting splicing byproducts with no apparent function; however, increasing evidence of stable derivatives suggests regulatory roles. Yet little is known about their characteristics, functions, distribution, and expression in healthy and tumor tissue. Here, we profiled and characterized circular stable intronic sequence RNAs (sisRNAs) using total RNA-Seq data from bladder cancer (BC; n = 457, UROMOL cohort), healthy tissue (n = 46), and fractionated cell lines (n = 5). We found that the recently-discovered full-length intronic circles and the stable lariats formed distinct subclasses, with a surprisingly high intronic circle fraction in BC (∼45%) compared to healthy tissues (0-20%). The stable lariats and their host introns were characterized by small transcript sizes, highly conserved BP regions, enriched BP motifs, and localization in multiple cell fractions. Additionally, circular sisRNAs showed tissue-specific expression patterns. We found nine circular sisRNAs as differentially expressed across early-stage BC patients with different prognoses, and sisHNRNPK expression correlated with progression-free survival. In conclusion, we identify distinguishing biological features of circular sisRNAs and point to specific candidates (incl. sisHNRNPK, sisWDR13 and sisMBNL1) that were highly expressed, had evolutionary conserved sequences, or had clinical correlations, which may facilitate future studies and further insights into their functional roles.

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.

Screening Linear and Circular RNA Transcripts from Stress Granules

Stress granules (SGs) are cytoplasmic ribonucleoprotein assemblies formed under stress conditions and are related to various biological processes and human diseases. Previous studies have reported the regulatory role of some proteins and linear RNAs in SG assembly. However, the relationship between circular RNAs (circRNAs) and SGs has not been discovered. Here, we screened both linear RNAs and circRNAs in SGs using improved total RNA sequencing of purified SG cores in mammalian cells and identified circular transcripts specifically localized in SGs. circRNAs with higher SG-related RNA-binding protein (RBP) binding abilities are more likely to be enriched in SGs. Furthermore, some SG-enriched circRNAs are differentially expressed in hepatocellular carcinoma (HCC) and adjacent tissues. These results suggest the regulatory role of circRNAs in SG formation and provide insights into the biological function of circRNAs and SGs in HCC.

Circular RNA encoded MET variant promotes glioblastoma tumorigenesis

Activated by its single ligand, hepatocyte growth factor (HGF), the receptor tyrosine kinase MET is pivotal in promoting glioblastoma (GBM) stem cell self-renewal, invasiveness and tumorigenicity. Nevertheless, HGF/MET-targeted therapy has shown limited clinical benefits in GBM patients, suggesting hidden mechanisms of MET signalling in GBM. Here, we show that circular MET RNA (circMET) encodes a 404-amino-acid MET variant (MET404) facilitated by the N⁶-methyladenosine (m⁶A) reader YTHDF2. Genetic ablation of circMET inhibits MET404 expression in mice and attenuates MET signalling. Conversely, MET404 knock-in (KI) plus P53 knock-out (KO) in mouse astrocytes initiates GBM tumorigenesis and shortens the overall survival. MET404 directly interacts with the MET β subunit and forms a constitutively activated MET receptor whose activity does not require HGF stimulation. High MET404 expression predicts poor prognosis in GBM patients, indicating its clinical relevance. Targeting MET404 through a neutralizing antibody or genetic ablation reduces GBM tumorigenicity in vitro and in vivo, and combinatorial benefits are obtained with the addition of a traditional MET inhibitor. Overall, we identify a MET variant that promotes GBM tumorigenicity, offering a potential therapeutic strategy for GBM patients, especially those with MET hyperactivation.

Retinitis pigmentosa-associated mutations in mouse Prpf8 cause misexpression of circRNAs and degeneration of cerebellar granule cells

A subset of patients with retinitis pigmentosa (RP) carry mutations in several spliceosomal components including the PRPF8 protein. Here, we established two alleles of murine Prpf8 that genocopy or mimic aberrant PRPF8 found in RP patients-the substitution p.Tyr2334Asn and an extended protein variant p.Glu2331ValfsX15. Homozygous mice expressing the aberrant Prpf8 variants developed within the first 2 mo progressive atrophy of the cerebellum because of extensive granule cell loss, whereas other cerebellar cells remained unaffected. We further show that a subset of circRNAs were deregulated in the cerebellum of both Prpf8-RP mouse strains. To identify potential risk factors that sensitize the cerebellum for Prpf8 mutations, we monitored the expression of several splicing proteins during the first 8 wk. We observed down-regulation of all selected splicing proteins in the WT cerebellum, which coincided with neurodegeneration onset. The decrease in splicing protein expression was further pronounced in mouse strains expressing mutated Prpf8. Collectively, we propose a model where physiological reduction in spliceosomal components during postnatal tissue maturation sensitizes cells to the expression of aberrant Prpf8 and the subsequent deregulation of circRNAs triggers neuronal death.

Characterization of cell-type specific circular RNAs associated with colorectal cancer metastasis

Colorectal cancer (CRC) is the most common gastrointestinal malignancy and a leading cause of cancer deaths in the United States. More than half of CRC patients develop metastatic disease (mCRC) with an average 5-year survival rate of 13%. Circular RNAs (circRNAs) have recently emerged as important tumorigenesis regulators; however, their role in mCRC progression remains poorly characterized. Further, little is known about their cell-type specificity to elucidate their functions in the tumor microenvironment (TME). To address this, we performed total RNA sequencing (RNA-seq) on 30 matched normal, primary and metastatic samples from 14 mCRC patients. Additionally, five CRC cell lines were sequenced to construct a circRNA catalog in CRC. We detected 47 869 circRNAs, with 51% previously unannotated in CRC and 14% novel candidates when compared to existing circRNA databases. We identified 362 circRNAs differentially expressed in primary and/or metastatic tissues, termed circular RNAs associated with metastasis (CRAMS). We performed cell-type deconvolution using published single-cell RNA-seq datasets and applied a non-negative least squares statistical model to estimate cell-type specific circRNA expression. This predicted 667 circRNAs as exclusively expressed in a single cell type. Collectively, this serves as a valuable resource, TMECircDB (accessible at https://www.maherlab.com/tmecircdb-overview), for functional characterization of circRNAs in mCRC, specifically in the TME.

Localised Cdr1as activity is required for fear extinction memory

Circular RNAs (circRNAs) comprise a novel class of regulatory RNAs that are abundant in the brain, particularly within synapses. They are highly stable, dynamically regulated, and display a range of functions, including serving as decoys for microRNAs and proteins and, in some cases, circRNAs also undergo translation. Early work in animal models revealed an association between circRNAs and neurodegenerative and neuropsychiatric disorders; however, little is known about the link between circRNA function and memory. To address this, we examined circRNA in synaptosomes derived from the medial prefrontal cortex of fear extinction-trained male C57BL/6J mice and found 12837 circRNAs that were enriched at the synapse, including cerebellar degeneration-related protein 1 antisense RNA (Cdr1as). Targeted knockdown of Cdr1as in the neural processes of the infralimbic cortex led to impaired fear extinction memory. These findings highlight the involvement of localised circRNA activity at the synapse in memory formation.

Identification and Characterization of circRNAs in Non-Lactating Dairy Goat Mammary Glands Reveal Their Regulatory Role in Mammary Cell Involution and Remodeling

This study conducted transcriptome sequencing of goat-mammary-gland tissue at the late lactation (LL), dry period (DP), and late gestation (LG) stages to reveal the expression characteristics and molecular functions of circRNAs during mammary involution. A total of 11,756 circRNAs were identified in this study, of which 2528 circRNAs were expressed in all three stages. The number of exonic circRNAs was the largest, and the least identified circRNAs were antisense circRNAs. circRNA source gene analysis found that 9282 circRNAs were derived from 3889 genes, and 127 circRNAs' source genes were unknown. Gene Ontology (GO) terms, such as histone modification, regulation of GTPase activity, and establishment or maintenance of cell polarity, were significantly enriched (FDR < 0.05), which indicates the functional diversity of circRNAs' source genes. A total of 218 differentially expressed circRNAs were identified during the non-lactation period. The number of specifically expressed circRNAs was the highest in the DP and the lowest in LL stages. These indicated temporal specificity of circRNA expression in mammary gland tissues at different developmental stages. In addition, this study also constructed circRNA-miRNA-mRNA competitive endogenous RNA (ceRNA) regulatory networks related to mammary development, immunity, substance metabolism, and apoptosis. These findings help understand the regulatory role of circRNAs in mammary cell involution and remodeling.

Aal-circRNA-407 regulates ovarian development of Aedes albopictus, a major arbovirus vector, via the miR-9a-5p/Foxl axis

Aedes albopictus shows a rapid global expansion and dramatic vectorial capacity for various arboviruses, thus posing a severe threat to global health. Although many noncoding RNAs have been confirmed to play functional roles in various biological processes in Ae. albopictus, the roles of circRNA remain a mystery. In the present study, we first performed high-throughput circRNA sequencing in Ae. albopictus. Then, we identified a cysteine desulfurase (CsdA) superfamily gene-originated circRNA, named aal-circRNA-407, which was the third most abundant circRNA in adult females and displayed a fat body highly expressed manifestation and blood feeding-dependent onset. SiRNA-mediated knockdown of circRNA-407 resulted in a decrease in the number of developing follicles and a reduction in follicle size post blood meal. Furthermore, we demonstrated that circRNA-407 can act as a sponge of aal-miR-9a-5p to promote the expression of its target gene Foxl and eventually regulate ovarian development. Our study is the first to report a functional circRNA in mosquitoes, expanding our current understanding of important biological roles in mosquitoes and providing an alternative genetic strategy for mosquito control.

Alzheimer's disease pathogenetic progression is associated with changes in regulated retained introns and editing of circular RNAs

Introduction

The molecular changes leading to Alzheimer's disease (AD) progression are poorly understood. A decisive factor in the disease occurs when neurofibrillary tangles (NFT) composed of microtubule associated protein tau (MAPT) form in the entorhinal cortex and then spread throughout the brain.

Methods

We therefore determined mRNA and circular RNA changes during AD progression, comparing Braak NFT stages I-VI. Total RNA was isolated from human brain (entorhinal and frontotemporal cortex). Poly(A)+ RNA was subjected to Nanopore sequencing, and total RNA was analyzed by standard Illumina sequencing. Circular RNAs were sequenced from RNase R treated and rRNA depleted total RNA. The sequences were analyzed using different bioinformatic tools, and expression constructs for circRNAs were analyzed in transfection experiments.

Results

We detected 11,873 circRNAs of which 276 correlated with Braak NFT stages. Adenosine to inosine RNA editing increased about threefold in circRNAs during AD progression. Importantly, this correlation cannot be detected with mRNAs. CircMAN2A1 expression correlated with AD progression and transfection experiments indicated that RNA editing promoted its translation using start codons out of frame with linear mRNAs, which generates novel proteins.

Discussion

Thus, we identified novel regulated retained introns that correlate with NFT Braak stages and provide evidence for a role of translated circRNAs in AD development.

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.

Identification of CircRNA signature associated with tumor immune infiltration to predict therapeutic efficacy of immunotherapy

Circular RNAs (circRNAs) play important roles in the regulation of cancer. However, the clinical implications and regulatory networks of circRNAs in cancer patients receiving immune checkpoint blockades (ICB) have not been fully elucidated. Here, we characterize circRNA expression profiles in two independent cohorts of 157 ICB-treated advanced melanoma patients and reveal overall overexpression of circRNAs in ICB non-responders in both pre-treatment and early during therapy. Then, we construct circRNA-miRNA-mRNA regulatory networks to reveal circRNA-related signaling pathways in the context of ICB treatment. Further, we construct an ICB-related circRNA signature (ICBcircSig) score model based on progression-free survival-related circRNAs to predict immunotherapy efficacy. Mechanistically, the overexpression of ICBcircSig circTMTC3 and circFAM117B could increase PD-L1 expression via the miR-142-5p/PD-L1 axis, thus reducing T cell activity and leading to immune escape. Overall, our study characterizes circRNA profiles and regulatory networks in ICB-treated patients, and highlights the clinical utility of circRNAs as predictive biomarkers of immunotherapy.

Comprehensive RNA-Seq Analysis Pipeline for Non-Model Organisms and Its Application in Schmidtea mediterranea

RNA sequencing (RNA-seq) is a high-throughput technology that provides in-depth information on transcriptome. The advancement and dropping costs of RNA sequencing, accompanied by more available reference genomes for different species, make transcriptome analysis in non-model organisms possible. Current obstacles in analyzing RNA-seq data include a lack of functional annotation, which may complicate the process of linking genes to corresponding functions. Here, we provide a one-stop RNA-seq analysis pipeline, PipeOne-NM, for transcriptome functional annotation, non-coding RNA identification, and transcripts alternative splicing analysis of non-model organisms, intended for use with Illumina platform-based RNA-seq data. We performed PipeOne-NM on 237 Schmidtea mediterranea RNA-seq runs and assembled a transcriptome with 84,827 sequences from 49,320 genes, identifying 64,582 mRNA from 35,485 genes, 20,217 lncRNA from 17,084 genes, and 3481 circRNAs from 1103 genes. In addition, we performed a co-expression analysis of lncRNA and mRNA and identified that 1319 lncRNA co-express with at least one mRNA. Further analysis of samples from S. mediterranea sexual and asexual strains revealed the role of sexual reproduction in gene expression profiles. Samples from different parts of asexual S. mediterranea revealed that differential expression profiles of different body parts correlated with the function of conduction of nerve impulses. In conclusion, PipeOne-NM has the potential to provide comprehensive transcriptome information for non-model organisms on a single platform.

Application of sequence semantic and integrated cellular geography approach to study alternative biogenesis of exonic circular RNA

BACKGROUND

Concurrent existence of lncRNA and circular RNA at both nucleus and cytosol within a cell at different proportions is well reported. Previous studies showed that circular RNAs are synthesized in nucleus followed by transportation across the nuclear membrane and the export is primarily defined by their length. lncRNAs primarily originated through inefficient splicing and seem to use NXF1 for cytoplasm export. However, it is not clear whether circularization of lncRNA happens only in nucleus or it also occurs in cytoplasm. Studies indicate that circular RNAs arise when the splicing apparatus undergoes a phenomenon of back splicing. Minor spliceosome (U12 type) mediated splicing occurs in cytoplasm and is responsible for the splicing of 0.5% of introns of human cells. Therefore, possibility of cRNA biogenesis mediated by minor spliceosome at cytoplasm cannot be ruled out. Secondly, information on genes transcribing both circular and lncRNAs along with total number of RBP binding sites for both of these RNA types is extractable from databases. This study showed how these apparently unconnected pieces of reports could be put together to build a model for exploring biogenesis of circular RNA.

RESULTS

As a result of this study, a model was built under the premises that, sequences with special semantics were molecular precursors in biogenesis of circular RNA which occurred through catalytic role of some specific RBPs. The model outcome was further strengthened by fulfillment of three logical lemmas which were extracted and assimilated in this work using a novel data analytic approach, Integrated Cellular Geography. Result of the study was found to be in well agreement with proposed model. Furthermore this study also indicated that biogenesis of circular RNA was a post-transcriptional event.

CONCLUSIONS

Overall, this study provides a novel systems biology based model under the paradigm of Integrated Cellular Geography which can assimilate independently performed experimental results and data published by global researchers on RNA biology to provide important information on biogenesis of circular RNAs considering lncRNAs as precursor molecule. This study also suggests the possible RBP-mediated circularization of RNA in the cytoplasm through back-splicing using minor spliceosome.

PARP1 Regulates Circular RNA Biogenesis though Control of Transcriptional Dynamics

Circular RNAs (circRNAs) are a recently discovered class of RNAs derived from protein-coding genes that have important biological and pathological roles. They are formed through backsplicing during co-transcriptional alternative splicing; however, the unified mechanism that accounts for backsplicing decisions remains unclear. Factors that regulate the transcriptional timing and spatial organization of pre-mRNA, including RNAPII kinetics, the availability of splicing factors, and features of gene architecture, have been shown to influence backsplicing decisions. Poly (ADP-ribose) polymerase I (PARP1) regulates alternative splicing through both its presence on chromatin as well as its PARylation activity. However, no studies have investigated PARP1's possible role in regulating circRNA biogenesis. Here, we hypothesized that PARP1's role in splicing extends to circRNA biogenesis. Our results identify many unique circRNAs in PARP1 depletion and PARylation-inhibited conditions compared to the wild type. We found that while all genes producing circRNAs share gene architecture features common to circRNA host genes, genes producing circRNAs in PARP1 knockdown conditions had longer upstream introns than downstream introns, whereas flanking introns in wild type host genes were symmetrical. Interestingly, we found that the behavior of PARP1 in regulating RNAPII pausing is distinct between these two classes of host genes. We conclude that the PARP1 pausing of RNAPII works within the context of gene architecture to regulate transcriptional kinetics, and therefore circRNA biogenesis. Furthermore, this regulation of PARP1 within host genes acts to fine tune their transcriptional output with implications in gene function.

Full-length circular RNA profiling by nanopore sequencing with CIRI-long

Circular RNAs (circRNAs) have important roles in regulating developmental processes and disease progression. As most circRNA sequences are highly similar to their cognate linear transcripts, the current short-read sequencing-based methods rely on the back-spliced junction signal for distinguishing circular and linear reads, which does not allow circRNAs' full-length structure to be effectively reconstructed. Here we describe a long-read sequencing-based protocol, CIRI-long, for the detection of full-length circular RNAs. The CIRI-long protocol combines rolling circular reverse transcription and nanopore sequencing to capture full-length circRNA sequences. After poly(A) tailing, RNase R treatment, and size selection of polymerase chain reaction products, CIRI-long achieves an increased percentage (6%) of circular reads in the constructed library, which is 20-fold higher compared with previous Illumina-based strategies. This method can be applied in cell lines or tissue samples, enabling accurate detection of full-length circRNAs in the range of 100-3,000 bp. The entire protocol can be completed in 1 d, and can be scaled up for large-scale analysis using the nanopore barcoding kit and PromethION sequencing device. CIRI-long can serve as an effective and user-friendly protocol for characterizing full-length circRNAs, generating direct and convincing evidence for the existence of detected circRNAs. The analytical pipeline offers convenient functions for identification of full-length circRNA isoforms and integration of multiple datasets. The assembled full-length transcripts and their splicing patterns provide indispensable information to explore the biological function of circRNAs.

Investigating Circular RNAs Using qRT-PCR; Roundup of Optimization and Processing Steps

Circular RNAs (circRNAs) have gained recent attraction due to their functional versatility and particular structure connected to human diseases. Current investigations are focused on the interplay between their ability to sponge smaller species of RNAs, such as microRNAs (miRNAs), thus influencing their regulatory activity on gene expression and protein templates. Therefore, their reported implication in various biological processes axis has resulted in an accumulating number of studies. While the testing and annotation methods of novel circular transcripts are still under development, there is still a plethora of transcript candidates suitable for investigation in human disease. The discordance in the literature regarding the approaches used in circRNAs quantification and validation methods, especially regarding qRT-PCR, the current golden standard procedure, leads to high result variability and undermines the replicability of the studies. Therefore, our study will offer several valuable insights into bioinformatic data for experimental design for circRNA investigation and in vitro aspects. Specifically, we will highlight key aspects such as circRNA database annotation divergent primer design and several processing steps, such as RNAse R treatment optimization and circRNA enrichment assessment. Additionally, we will provide insights into the exploration of circRNA-miRNA interactions, a prerequisite for further functional investigations. With this, we aim to contribute to the methodological consensus in a currently expanding field with possible implications for assessing therapeutic targets and biomarker discovery.

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.

Łabaj P, Mangul S. RNA-seq data science: From raw data to effective interpretation

RNA sequencing (RNA-seq) has become an exemplary technology in modern biology and clinical science. Its immense popularity is due in large part to the continuous efforts of the bioinformatics community to develop accurate and scalable computational tools to analyze the enormous amounts of transcriptomic data that it produces. RNA-seq analysis enables genes and their corresponding transcripts to be probed for a variety of purposes, such as detecting novel exons or whole transcripts, assessing expression of genes and alternative transcripts, and studying alternative splicing structure. It can be a challenge, however, to obtain meaningful biological signals from raw RNA-seq data because of the enormous scale of the data as well as the inherent limitations of different sequencing technologies, such as amplification bias or biases of library preparation. The need to overcome these technical challenges has pushed the rapid development of novel computational tools, which have evolved and diversified in accordance with technological advancements, leading to the current myriad of RNA-seq tools. These tools, combined with the diverse computational skill sets of biomedical researchers, help to unlock the full potential of RNA-seq. The purpose of this review is to explain basic concepts in the computational analysis of RNA-seq data and define discipline-specific jargon.

The transcriptomic landscape of neurons carrying PSEN1 mutations reveals changes in extracellular matrix components and non-coding gene expression

Alzheimer's disease (AD) is a progressive and irreversible brain disorder, which can occur either sporadically, due to a complex combination of environmental, genetic, and epigenetic factors, or because of rare genetic variants in specific genes (familial AD, or fAD). A key hallmark of AD is the accumulation of amyloid beta (Aβ) and Tau hyperphosphorylated tangles in the brain, but the underlying pathomechanisms and interdependencies remain poorly understood. Here, we identify and characterise gene expression changes related to two fAD mutations (A79V and L150P) in the Presenilin-1 (PSEN1) gene. We do this by comparing the transcriptomes of glutamatergic forebrain neurons derived from fAD-mutant human induced pluripotent stem cells (hiPSCs) and their individual isogenic controls generated via precision CRISPR/Cas9 genome editing. Our analysis of Poly(A) RNA-seq data detects 1111 differentially expressed coding and non-coding genes significantly altered in fAD. Functional characterisation and pathway analysis of these genes reveal profound expression changes in constituents of the extracellular matrix, important to maintain the morphology, structural integrity, and plasticity of neurons, and in genes involved in calcium homeostasis and mitochondrial oxidative stress. Furthermore, by analysing total RNA-seq data we reveal that 30 out of 31 differentially expressed circular RNA genes are significantly upregulated in the fAD lines, and that these may contribute to the observed protein-coding gene expression changes. The results presented in this study contribute to a better understanding of the cellular mechanisms impacted in AD neurons, ultimately leading to neuronal damage and death.

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 .

The hitchhikers' guide to RNA sequencing and functional analysis

DNA and RNA sequencing technologies have revolutionized biology and biomedical sciences, sequencing full genomes and transcriptomes at very high speeds and reasonably low costs. RNA sequencing (RNA-Seq) enables transcript identification and quantification, but once sequencing has concluded researchers can be easily overwhelmed with questions such as how to go from raw data to differential expression (DE), pathway analysis and interpretation. Several pipelines and procedures have been developed to this effect. Even though there is no unique way to perform RNA-Seq analysis, it usually follows these steps: 1) raw reads quality check, 2) alignment of reads to a reference genome, 3) aligned reads' summarization according to an annotation file, 4) DE analysis and 5) gene set analysis and/or functional enrichment analysis. Each step requires researchers to make decisions, and the wide variety of options and resulting large volumes of data often lead to interpretation challenges. There also seems to be insufficient guidance on how best to obtain relevant information and derive actionable knowledge from transcription experiments. In this paper, we explain RNA-Seq steps in detail and outline differences and similarities of different popular options, as well as advantages and disadvantages. We also discuss non-coding RNA analysis, multi-omics, meta-transcriptomics and the use of artificial intelligence methods complementing the arsenal of tools available to researchers. Lastly, we perform a complete analysis from raw reads to DE and functional enrichment analysis, visually illustrating how results are not absolute truths and how algorithmic decisions can greatly impact results and interpretation.

Evolutionary Landscape of Tea Circular RNAs and Its Contribution to Chilling Tolerance of Tea Plant

Chilling stress threatens the yield and distribution pattern of global crops, including the tea plant (Camellia sinensis), one of the most important cash crops around the world. Circular RNA (circRNA) plays roles in regulating plant growth and biotic/abiotic stress responses. Understanding the evolutionary characteristics of circRNA and its feedbacks to chilling stress in the tea plant will help to elucidate the vital roles of circRNAs. In the current report, we systematically identified 2702 high-confidence circRNAs under chilling stress in the tea plant, and interestingly found that the generation of tea plant circRNAs was associated with the length of their flanking introns. Repetitive sequences annotation and DNA methylation analysis revealed that the longer flanking introns of circRNAs present more repetitive sequences and higher methylation levels, which suggested that repeat-elements-mediated DNA methylation might promote the circRNAs biogenesis in the tea plant. We further detected 250 differentially expressed circRNAs under chilling stress, which were functionally enriched in GO terms related to cold/stress responses. Constructing a circRNA-miRNA-mRNA interaction network discovered 139 differentially expressed circRNAs harboring potential miRNA binding sites, which further identified 14 circRNAs that might contribute to tea plant chilling responses. We further characterized a key circRNA, CSS-circFAB1, which was significantly induced under chilling stress. FISH and silencing experiments revealed that CSS-circFAB1 was potentially involved in chilling tolerance of the tea plant. Our study emphasizes the importance of circRNA and its preliminary role against low-temperature stress, providing new insights for tea plant cold tolerance breeding.

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.