Detecting circular RNAs: bioinformatic and experimental challenges.
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ABSTRACT:
SUBMITTER: Szabo L
PROVIDER: S-EPMC5565156 | biostudies-other | 2016 Oct
REPOSITORIES: biostudies-other
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Project description:Circular RNAs (circRNAs) are covalently closed single-strand RNA molecules identified in eukaryotes. Here we report 10 sequences of chloroplast genome (cpDNA) encoded circRNAs (cp-circRNA) from 3-day-old Arabidopsis thaliana seedlings via next-generation sequencing. Their parental sequences were referred to as exonic, intronic, and intergenic gene sequences. Due to the very low level of cp-circRNA expression, we attempted to use a digital polymerase chain reaction technique to validate their existence. Four of these circRNAs were confirmed: ath_circ_476, ath_circ_477, ath_circ_478, and ath_circ_480. Their expression levels in etiolated and de-etiolated seedlings were quantified using digital PCR. Of the four, the exonic circRNA ath_circ_476 was highly expressed in etiolated seedlings. Its parental gene, cytochrome C assembly protein (ycf5), has expression trends similar to ath_circ_476. Given that ycf5 is a single-exon gene, we propose that the circularization of ath_circ_476 occurs via an unknown process rather than via RNA-splicing-based mechanisms. Therefore, we provided a reliable method for detecting cp-circRNAs in low copies and implied an unknown circularisation mechanism of RNA in chloroplasts.
| S-EPMC6619943 | biostudies-literature
Project description:Circular RNAs (circRNAs) are covalently linked RNAs that exhibit individual strand with a closed-loop framework compared with a conserving, steady and abundant linear counterpart. In recent years, as high-throughput sequencing advancement has been developing, functional circRNAs have been increasingly recognized, and more extensive analyses expounded their effect on different diseases. However, the study on the function of circRNAs in the immune system remains insufficient. This study discusses the basic principles of circRNAs regulation and the systems involved in physiology-related and pathology-related processes. The effect of circRNAs on immune regulation is elucidated. The ongoing development of circRNAs and basic immunology has multiplied their potential in treating diseases. Such perspective will summarize the status and effect of circRNAs on various immune cells in cancer, autoimmune diseases and infections. Moreover, this study will primarily expound the system of circRNAs in T lymphocytes, macrophages and other immune cells, which creates a novel perspective and lay a theoretical basis for treating diseases.
| S-EPMC7348111 | biostudies-literature
Project description:BackgroundCircular RNAs (circRNAs) may play important roles in the progression of pulmonary arterial hypertension. However, the potential roles they play in childhood pulmonary arterial hypertension associated congenital heart disease (CHD) progression remains unclear.MethodsThirteen human plasma samples including eight from pulmonary arterial hypertension secondary to CHD patients and five from a control group were analyzed using the Arraystar Human circRNA array. The relative expression levels of five differentially expressed circRNAs in pulmonary arterial hypertension were detected using real-time polymerase chain reaction (PCR) analysis. In parallel, these levels were also taken on control samples from 32 CHD patients. We used miRanda and TargetScan software packages to predict potential microRNA (miRNA)targets, which were then combined into a circRNA-miRNA-messenger RNA (mRNA) network.ResultsTwenty-seven circRNAs (three upregulated and 24 downregulated) were differentially expressed between the pulmonary arterial hypertension and control groups. Compared to control group levels, circ_003416 expression in the pulmonary arterial hypertension group was significantly downregulated, while circ_005372 expression, in contrast, was significantly upregulated. The differential expression of these circRNAs was mainly linked to variation in levels of oxidative phosphorylation and tight junction signaling.ConclusionsWe identified one overexpressed and one underexpressed circRNA in plasma samples from children with CHD associated pulmonary arterial hypertension. Bioinformatic analysis indicated these dysregulated circRNAs might be associated with the occurrence and regulation of pulmonary arterial hypertension.
| S-EPMC9173884 | biostudies-literature
Project description:The lack of an accurate biomarker in hepatocellular carcinoma (HCC) has hindered early detection, diagnosis, and treatment. Circular RNAs (circRNAs), which can be used as novel biomarkers in liquid biopsies, have been brought to light as a result of the advances in research on molecular biomarkers and the progression of genomic medicine. We conducted a meta-analysis of the diagnostic accuracy of serum/plasma circRNAs or the combination of circRNAs and α-fetoprotein (AFP) in HCC. We identified eight studies that met the inclusion/exclusion criteria from PubMed, Web of Science, EMBASE, and Cochrane Library databases. The data were pooled, and the sensitivity, specificity, diagnostic odds ratio (DOR), positive likelihood ratio (+LR), and negative likelihood ratio (-LR) with 95% confidence intervals (CIs) were calculated. The areas under the summary receiver operator characteristic (SROC) curves (AUCs) were also calculated. The sensitivity of circRNAs was 0.82 (95% CI: 0.78-0.85), and the specificity was 0.82 (95% CI: 0.78-0.86). The sensitivity of AFP was 0.65 (95% CI: 0.61-0.68), and the specificity was 0.90 (95% CI: 0.85-0.93). The AUC was 0.89 (95% CI: 0.86-0.91) for circRNAs and 0.77 (95% CI: 0.74-0.81) for AFP. The sensitivity of the combination of circRNAs and AFP was 0.88 (95% CI: 0.84-0.92), specificity was 0.86 (95% CI: 0.80-0.91), and AUC was 0.94 (95% CI: 0.91-0.96). Additionally, a subgroup analysis was conducted based on the control groups used; the diagnostic accuracy was particularly high in the comparison of HCC vs. healthy controls. In summary, serum/plasma circRNAs are accurate biomarkers suitable for clinical use for detecting HCC, and the combination of circRNAs and AFP improved the diagnostic accuracy.
| S-EPMC8514948 | biostudies-literature
Project description:Over the past two decades, researchers have discovered a special form of alternative splicing that produces a circular form of RNA. Although these circular RNAs (circRNAs) have garnered considerable attention in the scientific community for their biogenesis and functions, the focus of current studies has been on the tissue-specific circRNAs that exist only in one tissue but not in other tissues or on the disease-specific circRNAs that exist in certain disease conditions, such as cancer, but not under normal conditions. This approach was conducted in the relative absence of methods that analyze a group of common circRNAs that exist in both conditions, but are more abundant in one condition relative to another (differentially expressed). Studies of differentially expressed circRNAs (DECs) between two conditions would serve as a significant first step in filling this void. Here, we introduce a novel computational tool, seekCRIT (seek for differentially expressed CircRNAs In Transcriptome), that identifies the DECs between two conditions from high-throughput sequencing data. Using rat retina RNA-seq data from ischemic and normal conditions, we show that over 74% of identifiable circRNAs are expressed in both conditions and over 40 circRNAs are differentially expressed between two conditions. We also obtain a high qPCR validation rate of 90% for DECs with a FDR of < 5%. Our results demonstrate that seekCRIT is a novel and efficient approach to detect DECs using rRNA depleted RNA-seq data. seekCRIT is freely downloadable at https://github.com/UofLBioinformatics/seekCRIT. The source code is licensed under the MIT License. seekCRIT is developed and tested on Linux CentOS-7.
| S-EPMC7598922 | biostudies-literature
Project description:Circular RNAs (circRNAs) are a class of single-stranded, covalently closed RNA molecules with a variety of biological functions. Studies have shown that circRNAs are involved in a variety of biological processes and play an important role in the development of various complex diseases, so the identification of circRNA-disease associations would contribute to the diagnosis and treatment of diseases. In this review, we summarize the discovery, classifications and functions of circRNAs and introduce four important diseases associated with circRNAs. Then, we list some significant and publicly accessible databases containing comprehensive annotation resources of circRNAs and experimentally validated circRNA-disease associations. Next, we introduce some state-of-the-art computational models for predicting novel circRNA-disease associations and divide them into two categories, namely network algorithm-based and machine learning-based models. Subsequently, several evaluation methods of prediction performance of these computational models are summarized. Finally, we analyze the advantages and disadvantages of different types of computational models and provide some suggestions to promote the development of circRNA-disease association identification from the perspective of the construction of new computational models and the accumulation of circRNA-related data.
| S-EPMC8575014 | biostudies-literature
Project description: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.
| S-EPMC9136258 | biostudies-literature
Project description:Recently, it has been demonstrated that genomes of many species express single stranded RNAs with covalently closed ends, named circular RNAs. Their regulatory potential and functional relevance are just starting to be revealed. Here we present a novel computational tool, seekCRIT (seek for differentially expressed Circular RNAs In Transcriptome), that identifies circular RNAs and detects their differential expression between two conditions. Using seekCRIT we identified the circular RNAs that are expressed in the neural retina and determined that the majority of them (74%) are expressed in both, ischemic and normal conditions. We identified over 40 circular RNAs that were differentially expressed between both conditions and validated these experimentally using qRT-PCR. The high validation rate of 90% with a false discovery rate (FDR) of < 5% demonstrates the accuracy and reliability of seekCRIT.
2021-02-02 | GSE114896 | GEO
Project description:Epstein-Barr virus (EBV) and Kaposi's sarcoma herpesvirus (KSHV) cause ∼2% of all human cancers. RNase R-resistant RNA sequencing revealed that both gammaherpesviruses encode multiple, uniquely stable, circular RNAs (circRNA). EBV abundantly expressed both exon-only and exon-intron circRNAs from the BamHI A rightward transcript (BART) locus (circBARTs) formed from a spliced BART transcript and excluding the EBV miRNA region. The circBARTs were expressed in all verified EBV latency types, including EBV-positive posttransplant lymphoproliferative disease, Burkitt lymphoma, nasopharyngeal carcinoma, and AIDS-associated lymphoma tissues and cell lines. Only cells infected with the B95-8 EBV strain, with a 12-kb BART locus deletion, were negative for EBV circBARTs. Less abundant levels of EBV circRNAs originating from LMP2- and BHLF1-encoding genes were also identified. The circRNA sequencing of KSHV-infected primary effusion lymphoma cells revealed a KSHV-encoded circRNA from the vIRF4 locus (circvIRF4) that was constitutively expressed. In addition, KSHV polyadenylated nuclear (PAN) RNA locus generated a swarm (>100) of multiply backspliced, low-abundance RNase R-resistant circRNAs originating in both sense and antisense directions consistent with a novel hyperbacksplicing mechanism. In EBV and KSHV coinfected cells, exon-only EBV circBARTs were located more in the cytoplasm, whereas the intron-retaining circBARTs were found in the nuclear fraction. KSHV circvIRF4 and circPANs were detected in both nuclear and cytoplasmic fractions. Among viral circRNAs tested, none were found in polysome fractions from KSHV-EBV coinfected BC1 cells, although low-abundance protein translation from viral circRNAs could not be excluded. The circRNAs are a new class of viral transcripts expressed in gammaherpesvirus-related tumors that might contribute to viral oncogenesis.
| S-EPMC6140489 | biostudies-literature
Project description:The lack of accurate biomarkers impeded the screening, diagnosis and early treatment of hepatocellular carcinoma (HCC). As a result of the development of high-throughput transcriptome analysis techniques, circular RNAs, a newly discovered class of noncoding RNAs, were recognized as potential novel biomarkers. This meta-analysis was performed to update the diagnostic roles of circular RNAs for HCC. We acquired 23 articles from PubMed, Web of Science, EMBASE, and Cochrane Library databases up to September 2021. The overall sensitivity was 0.80 (95% CI: 0.77-0.84), and the specificity was 0.83 (95% CI: 0.79-0.85), with an AUC of 0.88 (0.85-0.91). Considering of the significant heterogeneity, studies were divided into four groups based on the control types. The circular RNAs in exosomes had a sensitivity of 0.69 (95% CI: 0.61-0.75), and a highest specificity of 0.91 (95% CI: 0.83-0.96). The pooled sensitivity of circular RNAs in serum/plasma was 0.84 (95% CI: 0.81-0.87), and the pooled specificity was 0.83 (95% CI: 0.79-0.86). The pooled sensitivity of circular RNAs distinguishing tumor tissue from chronic hepatitis/cirrhosis tissues was 0.56 (95% CI: 0.48-0.64), and specificity was 0.76 (95% CI: 0.67-0.82). When the controls were adjacent tissues, the sensitivity was 0.78 (95% CI: 0.70-0.84), and the specificity was 0.78 (95% CI: 0.71-0.85). Hsa_circ_0001445 with a pooled sensitivity of 0.81, a specificity of 0.76 and an AUC of 0.85 in two studies, might be a suitable diagnostic blood biomarker for HCC. Relying on function in HCC, the AUC of subgroups were 0.88 (95%CI: 0.84-0.90) (function group) and 0.87 (95%CI: 0.84-0.90) (unknown function group). As for only reported in HCC or not, these circular RNAs had an AUC of 0.89 (95%CI: 0.86-0.91) (only in HCC) and 0.85 (95%CI: 0.82-0.88) (not only in HCC). In conclusion, the results suggested that circular RNAs were acceptable biomarkers for detecting HCC, especially those circular RNAs existing in exosomes or serum/plasma.
| S-EPMC8724259 | biostudies-literature