CircRNA cPWWP2A: an emerging player in diabetes mellitus.
ABSTRACT: Circular RNAs(CircRNAs), a new class of non-coding RNAs, possess significant capabilities of gene regulation and are disrupted in various diseases, including diabetes mellitus (DM). However, the underlying mechanism of CircRNAs in DM and diabetic complications remains illusive. A recent study published by Liu et al. (Proc Natl Acad Sci USA 116:7455-7464, 2019) shown that a novel diabetic retinopathy (DR)-associated CircRNA cPWWP2A, which could act as a competing endogenous RNA interacting with miR-579 to promote the DR-induced retinal vascular dysfunction through up-regulating the expression of Angiopoietin 1, Occludin, and SIRT1. Their findings may provide new insight into the potential use of CircRNA cPWWP2A for the targeted therapy of DR. However, those promising findings may need to be further evaluated detailedly for the following reason. (1) This study doesn't well clarify why the most significantly up-regulated CircRNA mmu _circ_0000254 the fold change of which is 160.581 is excluded,while the cPWWP2A the fold change of which is only 3.487 is chosen. (2) It is difficult to conclude that cPWWP2A competing with miR-579 only by the analysis of colocalization in pericytes.
Project description:Circular RNAs (circRNAs) are a large class of animal RNAs. To investigate possible circRNA functions, it is important to understand circRNA biogenesis. Besides human Alu repeats, sequence features that promote exon circularization are largely unknown. We experimentally identified new circRNAs in C. elegans. Reverse complementary sequences between introns bracketing circRNAs were significantly enriched compared to linear controls. By scoring the presence of reverse complementary sequences in human introns we predicted and experimentally validated novel circRNAs. We show that introns bracketing circRNAs are highly enriched in RNA editing or hyper-editing events. Knockdown of the double-strand RNA editing ADAR1 enzyme significantly and specifically up-regulated circRNA expression. Together, our data support a model of animal circRNA biogenesis in which competing RNA:RNA interactions of introns form larger structures which promote circularization of embedded exons, while ADAR1 antagonizes circRNA expression by melting stems within these interactions. Thus, we assign a new function to ADAR1. Examination of 12 samples in different stages of C.elegans development.
Project description:Diabetic cardiomyopathy (DCM) is a severe cardiovascular complication of diabetes mellitus (DM). Detecting DCM during the early stages of the disease remains a challenge, as the molecular mechanisms underlying early?stage DCM are not clearly understood. Circular RNA (circRNA), a type of non?coding RNA, has been confirmed to be associated with numerous diseases. However, it is still unclear how circRNAs are involved in early?stage DCM. In the present study, heart tissues harvested from BKS?db/db knock?out mice were identified through high?throughput RNA sequencing technology. A total of 58 significantly differentially expressed circRNAs were identified in the db/db sample. Among these, six upregulated circRNAs and seven downregulated circRNAs were detected by reverse transcription?quantitative PCR and analyzed using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. Furthermore, based on the predicted binding site with microRNAs (miRNAs) involved in DCM, five circRNAs (mmu_circ_0000652, mmu_circ_0000547, mmu_circ_0001058, mmu_circ_0000680 and novel_circ_0004285) were shown to serve as competing endogenous (ce)RNAs. The corresponding miRNAs and mRNAs of the ceRNAs were also verified, and two promising circRNA?miRNA?mRNA regulatory networks were determined. Finally, internal ribosome entry site prediction combined with open reading frame prediction indicated that it was highly possible that mmu_circ_0001160 encoded a protein. In the present study, a comprehensive analysis of the circRNA expression profile during the early phase of DCM was performed, and two promising circRNA?miRNA?mRNA regulatory networks were identified. These results lay the foundation for unravelling the underlying pathogenesis of DCM, and highlight potential biomarkers and therapeutic targets for the treatment of DCM at an early stage.
Project description:Circular RNAs (circRNAs) are involved in the development of various diseases, but there is little knowledge of circRNAs in osteoarthritis (OA). The aim of study was to identify circRNA expression in articular cartilage and to explore the function of chondrocyte extracellular matrix (ECM)-related circRNAs (circRNA-CER) in cartilage. To identify circRNAs that are specifically expressed in cartilage, we compared the expression of circRNAs in OA cartilage with that in normal cartilage. Bioinformatics was employed to predict the interaction of circRNAs and mRNAs in cartilage. Loss-of-function and rescue experiments for circRNA-CER were performed in vitro. A total of 71 circRNAs were differentially expressed in OA and normal cartilage. CircRNA-CER expression increased with interleukin-1 and tumor necrosis factor levels in chondrocytes. Silencing of circRNA-CER using small interfering RNA suppressed MMP13 expression and increased ECM formation. CircRNA-CER could compete for miR-136 with MMP13. Our results demonstrated that circRNA-CER regulated MMP13 expression by functioning as a competing endogenous RNA (ceRNA) and participated in the process of chondrocyte ECM degradation. We propose that circRNA-CER could be used as a potential target in OA therapy.
Project description:Atherosclerosis is a chronic and multifactorial inflammatory disease and is closely associated with cardiovascular and cerebrovascular diseases. circRNAs can act as competing endogenous RNAs to mRNAs and function in various diseases. However, there is little known about the function of circRNAs in atherosclerosis. In this study, three rabbits in the case group were fed a high-fat diet to induce atherosclerosis and another three rabbits were fed a normal diet. To explore the biological functions of circRNAs in atherosclerosis, we analyzed the circRNA, miRNA and mRNA expression profiles using RNA-seq. Many miRNAs, mRNAs and circRNAs were identified as significantly changed in atherosclerosis. We next predicted miRNA-target interactions with the miRanda tool and constructed a differentially expressed circRNA-miRNA-mRNA triple network. A gene ontology enrichment analysis showed that genes in the network were involved in cell adhesion, cell activation and the immune response. Furthermore, we generated a dysregulated circRNA-related ceRNAs network and found seven circRNAs (ocu-cirR-novel-18038, -18298, -15993, -17934, -17879, -18036 and -14389) were related to atherosclerosis. We found these circRNAs also functioned in cell adhesion, cell activation and the immune response. These results show that the crosstalk between circRNAs and their competing mRNAs might play crucial roles in the development of atherosclerosis.
Project description:BACKGROUND:Many evidences have demonstrated that circRNAs (circular RNA) play important roles in controlling gene expression of human, mouse and nematode. More importantly, circRNAs are also involved in many diseases through fine tuning of post-transcriptional gene expression by sequestering the miRNAs which associate with diseases. Therefore, identifying the circRNA-disease associations is very appealing to comprehensively understand the mechanism, treatment and diagnose of diseases, yet challenging. As the complex mechanism between circRNAs and diseases, wet-lab experiments are expensive and time-consuming to discover novel circRNA-disease associations. Therefore, it is of dire need to employ the computational methods to discover novel circRNA-disease associations. RESULT:In this study, we develop a method (DWNN-RLS) to predict circRNA-disease associations based on Regularized Least Squares of Kronecker product kernel. The similarity of circRNAs is computed from the Gaussian Interaction Profile(GIP) based on known circRNA-disease associations. In addition, the similarity of diseases is integrated by the mean of GIP similarity and sematic similarity which is computed by the direct acyclic graph (DAG) representation of diseases. The kernels of circRNA-disease pairs are constructed from the Kronecker product of the kernels of circRNAs and diseases. DWNN (decreasing weight k-nearest neighbor) method is adopted to calculate the initial relational score for new circRNAs and diseases. The Kronecker product kernel based regularised least squares approach is used to predict new circRNA-disease associations. We adopt 5-fold cross validation (5CV), 10-fold cross validation (10CV) and leave one out cross validation (LOOCV) to assess the prediction performance of our method, and compare it with other six competing methods (RLS-avg, RLS-Kron, NetLapRLS, KATZ, NBI, WP). CONLUSION:The experiment results show that DWNN-RLS reaches the AUC values of 0.8854, 0.9205 and 0.9701 in 5CV, 10CV and LOOCV, respectively, which illustrates that DWNN-RLS is superior to the competing methods RLS-avg, RLS-Kron, NetLapRLS, KATZ, NBI, WP. In addition, case studies also show that DWNN-RLS is an effective method to predict new circRNA-disease associations.
Project description:Many circular RNAs (circRNAs) have been discovered in various tissues and cell types in pig. However, the temporal expression pattern of circRNAs during porcine embryonic muscle development remains unclear. Here, we present a panorama view of circRNA expression in embryonic muscle development at 33-, 65-, and 90-days post-coitus (dpc) from Duroc pigs. An unbiased analysis reveals that more than 5,000 circRNAs specifically express in embryonic muscle development. The amount and complexity of circRNA expression is most pronounced in skeletal muscle at day 33 of gestation. Our circRNAs annotation analyses show that "hot-spot" genes produce multiple circRNA isoforms and RNA binding protein (RBPs) may regulate the biogenesis of circRNAs. Furthermore, we observed that host genes of differentially expressed circRNA across porcine muscle development are enriched in skeletal muscle function. A competing endogenous RNA (ceRNA) network analysis of circRNAs reveals that circRNAs regulate muscle gene expression by functioning as miRNA sponges. Finally, our experimental validation demonstrated that circTUT7 regulate the expression of HMG20B in a ceRNA mechanism. Our analyses show that circRNAs are dynamically expressed and interacting with muscle genes through ceRNA manner, suggesting their critical functions in embryonic skeletal muscle development.
Project description:Circular RNAs (circRNAs) belong to the ever-growing class of naturally occurring noncoding RNAs (ncRNAs) molecules. Unlike linear RNA, circRNAs are covalently closed transcripts mostly generated from precursor-mRNA by a non-canonical event called back-splicing. They are highly stable, evolutionarily conserved, and widely distributed in eukaryotes. Some circRNAs are believed to fulfill a variety of functions inside the cell mainly by acting as microRNAs (miRNAs) or RNA-binding proteins (RBPs) sponges. Furthermore, mounting evidence suggests that the misregulation of circRNAs is among the first alterations in various metabolic disorders including obesity, hypertension, and cardiovascular diseases. More recent research has revealed that circRNAs also play a substantial role in the pathogenesis of diabetes mellitus (DM) and related vascular complications. These findings have added a new layer of complexity to our understanding of DM and underscored the need to reexamine the molecular pathways that lead to this disorder in the context of epigenetics and circRNA regulatory mechanisms. Here, I review current knowledge about circRNAs dysregulation in diabetes and describe their potential role as innovative biomarkers to predict diabetes-related cardiovascular (CV) events. Finally, I discuss some of the actual limitations to the promise of these RNA transcripts as emerging therapeutics and provide recommendations for future research on circRNA-based medicine.
Project description:Circular RNA (circRNA) is a novel type of endogenous noncoding RNA with covalently closed loop structures, which are widely expressed in various tissues and have functional implications in cellular processes. Acting as competing endogenous RNAs (ceRNAs), circRNAs are important regulators of miRNA activities. The identification of these circRNAs underlines the increasing complexity of ncRNA-mediated regulatory networks. However, more biological evidence is required to infer direct circRNA-miRNA associations while little attention has been paid to circRNAs in plants as compared to the abundant research in mammals. PlantCircNet is presented as an integrated database that provides visualized plant circRNA-miRNA-mRNA regulatory networks containing identified circRNAs in eight model plants. The bioinformatics integration of data from multiple sources reveals circRNA-miRNA-mRNA regulatory networks and helps identify mechanisms underlying metabolic effects of circRNAs. An enrichment analysis tool was implemented to detect significantly overrepresented Gene Ontology categories of miRNA targets. The genomic annotations, sequences and isoforms of circRNAs were also investigated. PlantCircNet provides a user-friendly interface for querying detailed information of specific plant circRNAs. The database may serve as a resource to facilitate plant circRNA research. Several circRNAs were identified to play potential regulatory roles in flower development and response to environmental stress from regulatory networks related with miR156a and AT5G59720, respectively. This present research indicated that circRNAs could be involved in diverse biological processes. Database URL: http://bis.zju.edu.cn/plantcircnet/index.php.
Project description:Circular RNA (circRNA) is a new class of non-coding RNA that has recently attracted researchers' interest. Studies have demonstrated that circRNA can function as microRNA sponges or competing endogenous RNAs. Although circRNA has been explored in some species and tissues, the genetic basis of testis development and spermatogenesis in cattle remains unknown. We performed ribo-depleted total RNA-Seq to detect circRNA expression profiles of neonatal (one week old) and adult (4 years old) Qinchuan cattle testes. We obtained 91 112 596 and 80 485 868 clean reads and detected 21 753 circRNAs. A total of 4248 circRNAs were significantly differentially expressed between neonatal and adult cattle testes. Among these circRNAs, 2225 were upregulated, and 2023 were downregulated in adult cattle testis. Genomic feature, length distribution and other characteristics of the circRNAs in cattle testis were studied. Moreover, Gene Ontology and KEGG pathway analyses were performed for source genes of circRNAs. These source genes were mainly involved in tight junction, adherens junction, TGFβ signalling pathway and reproduction, such as PIWIL1, DPY19L2, SLC26A8, IFT81, SMC1B, IQCG and TTLL5. CircRNA expression patterns were validated by RT-qPCR. Our discoveries provide a solid foundation for the identification and characterization of key circRNAs involved in testis development or spermatogenesis.
Project description:Splicing aberrations induced as a consequence of the sequestration of muscleblind-like splicing factors on the dystrophia myotonica protein kinase transcript, which contains expanded CUG repeats, present a major pathomechanism of myotonic dystrophy type 1 (DM1). As muscleblind-like factors may also be important factors involved in the biogenesis of circular RNAs (circRNAs), we hypothesized that the level of circRNAs would be decreased in DM1. To test this hypothesis, we selected 20 well-validated circRNAs and analyzed their levels in several experimental systems (e.g., cell lines, DM muscle tissues, and a mouse model of DM1) using droplet digital PCR assays. We also explored the global level of circRNAs using two RNA-Seq datasets of DM1 muscle samples. Contrary to our original hypothesis, our results consistently showed a global increase in circRNA levels in DM1, and we identified numerous circRNAs that were increased in DM1. We also identified many genes (including muscle-specific genes) giving rise to numerous (>10) circRNAs. Thus, this study is the first to show an increase in global circRNA levels in DM1. We also provided preliminary results showing the association of circRNA level with muscle weakness and alternative splicing changes that are biomarkers of DM1 severity.