Circular RNA and mRNA profiling reveal competing endogenous RNA networks during avian leukosis virus, subgroup J-induced tumorigenesis in chickens.
ABSTRACT: Avian leukosis virus subgroup J (ALV-J) can induce myeloid tumors and hemangiomas in chickens and causes severe economic losses with commercial layer chickens and meat-type chickens. Here, we generated ribominus RNA sequencing data from three normal chicken spleen tissues and three ALV-J-infected chicken spleen tissues. Structure analysis of transcripts showed that, compared to mRNAs and lncRNAs, chicken circRNAs shared relatively shorter transcripts and similar GC content. Differentially expression analysis showed 152 differentially expressed circRNAs with 106 circRNAs up regulated and 46 circRNAs down regulated. Through comparing differentially expressed circRNA host genes and mRNAs and performed ceRNA network analysis, we found several tumor or immune-related genes, in which, there were four genes existed in both differentially expressed mRNAs and circRNA host genes (Dock4, Fmr1, Zfhx3, Ralb) and two genes (Mll, Aoc3) involved in ceRNA network. We further characterized one exon-intron circRNA derived from HRH4 gene in the ceRNA network, termed circHRH4, which is an abundant and stable circRNA expressed in various tissues and cells in chicken and localizes in cytoplasm. Our results provide new insight into the pathology of ALV-J infection and circRNAs may also mediate tumorigenesis in chicken.
Project description:Circular RNAs (circRNAs) serve as competing endogenous RNAs (ceRNAs) and indirectly regulate gene expression through shared microRNAs (miRNAs). However, the potential circRNAs functioning as ceRNAs in osteoporosis remain unclear. The bone marrow mesenchymal stem cells (BMSCs) were isolated from ovariectomy (OVX) mice and controls. We systematically analyzed RNA-seq and miRNA-microarray data, miRNA-target interactions, and prominently coexpressed gene pairs to identify aberrantly expressed circRNAs, miRNAs, and messenger RNAs (mRNAs) between the OVX mice and controls. A total of 45 circRNAs, 22 miRNAs, and 548 mRNAs were significantly dysregulated (fold change?>?1.5; p?<?0.05). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were conducted for differentially expressed mRNAs, and subsequently a circRNA-associated ceRNA network involved in osteoporosis was constructed. We identified two ceRNA regulatory pathways in this osteoporosis mouse model-novel circRNA 0020/miR-206-3p/Nnmt and circRNA 3832/miR-3473e/Runx3, which were validated by real-time PCR. This is the first study to elucidate the circRNA-associated ceRNA network in OVX and control mice using deep RNA-seq and RNA-microarray analysis. The data further expanded the understanding of circRNA-associated ceRNA networks, and the regulatory functions of circRNAs, miRNAs and mRNAs in the pathogenesis and pathology of osteoporosis.
Project description:BACKGROUND:Circular RNAs (circRNAs) have been shown to interact with microRNAs (miRNA) as competitive endogenous RNAs (ceRNAs) to regulate target gene expression and participate in tumorigenesis. However, the role of circRNA-mediated ceRNAs in bladder cancer (BC) remains unknown. Accordingly, the aim of this study was to elucidate the regulatory mechanisms in BC based on construction of the ceRNA network. METHODS:The RNA expression profiles were obtained from public datasets in the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) database, and were used to establish a circRNA-miRNA-mRNA network. The interactions among proteins were analyzed using the STRING database and hubgenes were extracted using the cytoHubba application. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of differentially expressed mRNAs in BC and normal tissue samples were performed to determine the functions of the intersecting mRNAs. RESULTS:A total of 27 circRNAs, 76 miRNAs, and 4744 mRNAs were found to be differentially expressed between BC and normal tissues. The circRNA-miRNA-mRNA ceRNA network was established based on 21 circRNAs, 14 miRNAs, and 150 mRNAs differentially expressed in BC. We also established a protein-protein interaction network and identified 10 hubgenes, which were used to construct circRNA-miRNA-hubgene regulatory modules. The most enriched biological process GO term was strand displacement (P<0.05), and the homologous recombination and Fanconi anemia pathways were significantly enriched (P<0.05) for the differentially expressed genes in BC. CONCLUSIONS:We screened several dysregulated circRNAs and established a circRNA-associated ceRNA network by bioinformatics analysis. The identified ceRNAs are likely critical in the pathogenesis of BC and may serve as future therapeutic biomarkers.
Project description:Objective:Long noncoding RNA (lncRNA) and circular RNA (circRNA) are receiving increasing attention in diabetes research. However, there are still many unknown lncRNAs and circRNAs that need further study. The aim of this study is to identify new lncRNAs and circRNAs and their potential biological functions in type 2 diabetes mellitus (T2DM). Methods:RNA sequencing and differential expression analysis were used to identify the noncoding RNAs (ncRNAs) and mRNAs that were expressed abnormally between the T2DM and control groups. The competitive endogenous RNA (ceRNA) regulatory network revealed the mechanism of lncRNA and circRNA coregulating gene expression. The biological functions of lncRNA and circRNA were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The candidate hub mRNAs were selected by the protein-protein interaction (PPI) network and validated by using the Gene Expression Omnibus (GEO) database. Results:Differential expression analysis results showed that 441 lncRNAs (366 upregulated and 75 downregulated), 683 circRNAs (354 upregulated and 329 downregulated), 93 miRNAs (63 upregulated and 30 downregulated), and 2923 mRNAs (1156 upregulated and 1779 downregulated) were identified as remarkably differentially expressed in the T2DM group. The ceRNA regulatory network showed that a single lncRNA and circRNA can be associated with multiple miRNAs, and then, they coregulate more mRNAs. Functional analysis showed that differentially expressed lncRNA (DElncRNA) and differentially expressed circRNA (DEcircRNA) may play important roles in the mTOR signaling pathway, lysosomal pathway, apoptosis pathway, and tuberculosis pathway. In addition, PIK3R5, AKT2, and CLTA were hub mRNAs screened out that were enriched in an important pathway by establishing the PPI network. Conclusions:This study is the first study to explore the molecular mechanisms of lncRNA and circRNA in T2DM through the ceRNA network cofounded by lncRNA and circRNA. Our study provides a novel insight into the T2DM from the ceRNA regulatory network.
Project description:Alzheimer's disease (AD), a degenerative disease of the central nervous system, is the most common form of dementia in old age. The complexity and behavior of circular RNA (circRNA)-associated competing endogenous RNA (ceRNA) network remained poorly characterized in AD. The aim of this study was to elucidate the regulatory networks of dysregulated circRNAs from ceRNA view and identify potential risk circRNAs involved in AD pathogenesis. Consistent differentially expressed genes (CDEGs) were obtained using meta-analysis for multiple microarrays, and differentially expressed miRNAs (DEmiRs) were identified using empirical Bayes method. The circRNA-associated ceRNA network (cirCeNET) was constructed based on "ceRNA hypothesis" using an integrated system biology method. A total of 1,872 CDEGs and 48 DEmiRs were screened across different datasets. By mapping CDEGs and DEmiRs into the cirCeNET, an AD-related circRNA-associated ceRNA network (ADcirCeNET) was constructed, including 3,907 edges and 1,407 nodes (276 circRNAs, 14 miRNAs and 1,117 mRNAs). By prioritizing AD risk circRNA-associated ceRNAs, we found that the circRNA KIAA1586 occurred most frequently in the AD risk circRNA-associated ceRNAs and function as a ceRNA that operates by competitively binding three known AD-risk miRNAs. In silico functional analysis suggested that circRNA KIAA1586-related ceRNA network was significantly enriched in known AD-associated biological processes. Our study provided a global view and systematic dissection of circRNA-associated ceRNA network. The identified circRNA KIAA1586 may be a key risk factor involved in AD pathogenesis.
Project description:BACKGROUND:The events in early HIV infection (EHI) are important determinants of disease severity and progression rate to AIDS, but the mechanisms of pathogenesis in EHI have not been fully understood. Circular RNAs (circRNAs) have been verified as "microRNA sponges" that regulate gene expression through competing endogenous RNA (ceRNA) networks, but circRNA expression profiles and their contribution to EHI pathogenesis are still unclear. METHODS:Two different libraries were constructed with RNA from human peripheral blood mononuclear cells from 3 HARRT-naive EHI patients and 3 healthy controls (HCs). The complete transcriptomes were sequenced with RNA sequencing (RNA-Seq) and miRNA sequencing (miRNA-Seq). The differentially expressed (DE) RNAs were validated with RT-qPCR. The circRNA profile and circRNA-associated-ceRNA network in EHI were analyzed with the integrated data of RNA-Seq and miRNA-Seq. Gene ontology (GO) analysis was used to annotate the circRNAs involved in the circRNA-associated-ceRNA networks. RESULTS:A total of 1365 circRNAs, 30 miRNAs, and 2049 mRNAs were differentially expressed between HARRT-naive EHI patients and HCs. A ceRNA network was constructed with 516 DE circRNAs and 903 DE mRNAs that shared miR response elements with 21 DE miRNAs. GO analysis demonstrated the multiple roles of the circRNAs enriched in EHI with circRNA-associated-ceRNA networks, such as immune response, inflammatory response and defense responses to virus, 67 circRNAs were revealed to be potentially involved in HIV-1 replication through regulating the expression of CCNK, CDKN1A and IL-15. CONCLUSIONS:This study, for the first time, revealed a large circRNA profile and complex pathogenesis roles of circRNAs in EHI. A group of enriched circRNAs and associated circRNA-associated-ceRNA networks might contribute to HIV replication regulation and provide novel potential targets for both the pathogenesis of EHI and antiviral therapy.
Project description:Purpose:Accumulating evidence has indicated that circRNAs are closely involved in tumorigenesis and progression of human cancers. However, the molecular mechanism underlying function of circRNAs in breast cancer has not been thoroughly elucidated. Currently, we aimed to characterize the circRNA-related competing endogenous RNA (ceRNA) regulatory network in breast cancer and to construct prognostic model. Materials and Methods:First, we constructed circRNA expression profiles for paired breast cancer in a Chinese population using a human circRNA microarray. Expression profiles of circRNAs, miRNAs, and mRNAs were retrieved from our circRNA dataset, the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. We applied the limma and edgeR packages to identify differentially expressed RNAs. Weighted gene correlation network analysis (WGCNA) was used to identify critical modules of mRNAs. Next, a ceRNA network was established based on circRNA-miRNA and miRNA-mRNA intersections. Both Cox regression analysis and ROC curve analysis were performed to generate prognostic model. Additionally, we performed Gene Set Enrichment Analysis (GSEA) on prognostic signatures. Results:Total of 59 circRNAs, 98 miRNAs and 3966 mRNAs were identified as differentially expressed RNAs. We first identified 38 miRNA-mRNA pairs and 38 circRNA-miRNA pairs to construct the circRNA-miRNA-mRNA regulatory network and then generated a prognostic model based on 7 signatures (MMD, SLC29A4, CREB5, FOS, ANKRD29, MYOCD, and PIGR), and patients with high-risk scores presented poor prognosis. Several cancer-related pathways were enriched, including the TGF-? pathway, the focal adhesion pathway, and the JAK-STAT signaling pathway, and 20 prognostic ceRNA regulatory networks were subsequently identified. Conclusion:In all, we screened a series of dysregulated circRNAs, miRNAs, and mRNAs, and constructed circRNA-related ceRNA network in breast cancer. Our findings may help to deepen the understanding of circRNA-related regulatory mechanisms. Moreover, we generated a prognostic model that provided new insight into postoperative management for breast cancer.
Project description:Circular RNAs (circRNAs) have displayed dysregulated expression in several types of cancer. However, the functions of the majority of circRNAs in pancreatic ductal adenocarcinoma (PDAC) remain unknown. The present study aimed to investigate the expression, functions and molecular mechanisms of circRNAs in PDAC. The circRNAs, mRNAs and the microRNA (miRNAs) expression profiles were obtained from three Gene Expression Omnibus microarray datasets, and a circRNA-miRNA-mRNA and circRNA-miRNA-hubgene network was established. The interactions between proteins were analyzed using the Search Tool for the Retrieval of Interacting Genes/Proteins database, and hubgenes were identified using the MCODE plugin. A total of eight differentially expressed circRNAs (DEcircRNAs), 44 differentially expressed miRNAs (DEmiRNAs), and 2,052 differentially expressed mRNAs (DEmRNAs) were identified. The present study successfully constructed a circRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network based on four circRNAs, six miRNAs and 111 mRNAs in PDAC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathways analyses indicated that DEmRNAs may participate in the pathogenesis and progression of PDAC. The protein-protein interaction network and module analysis identified six hubgenes (THBS1, FN1, TIMP3, TGFB2, ITGA1 and ITGA3). Furthermore, the circRNA-miRNA-hubgene regulatory modules were constructed based on the three DEcircRNAs, one DEmiRNAs and five DEmRNAs. In conclusion, the results of the present study improve the current understanding of the pathogenesis of PDAC.
Project description:Avian leukosis virus subgroup J (ALV-J) is an avian oncogenic retrovirus that induces myeloid tumors and hemangiomas in chickens and causes severe economic losses with commercial layer chickens and meat-type chickens. High-throughput sequencing followed by quantitative real-time polymerase chain reaction and bioinformatics analyses were performed to advance the understanding of regulatory networks associated with differentially expressed non-coding RNAs and mRNAs that facilitate ALV-J infection. We examined the expression of mRNAs, long non-coding RNAs (lncRNAs), and miRNAs in the spleens of 20-week-old chickens infected with ALV-J and uninfected chickens. We found that 1723 mRNAs, 7,883 lncRNAs and 13 miRNAs in the spleen were differentially expressed between the uninfected and infected groups (P < 0.05). Transcriptome analysis showed that, compared to mRNA, chicken lncRNAs shared relatively fewer exon numbers and shorter transcripts. Through competing endogenous RNA and co-expression network analyses, we identified several tumor-associated or immune-related genes and lncRNAs. Along transcripts whose expression levels significantly decreased in both ALV-J infected spleen and tumor tissues, BCL11B showed the greatest change. These results suggest that BCL11B may be mechanistically involved in tumorigenesis in chicken and neoplastic diseases, may be related to immune response, and potentially be novel biomarker for ALV-J infection. Our results provide new insight into the pathology of ALV-J infection and high-quality transcriptome resource for in-depth study of epigenetic influences on disease resistance and immune system.
Project description:Background:Osteosarcoma (OS) is a common primary malignant bone tumour. Growing evidence suggests that circular RNAs (circRNAs) are closely related to the development of tumours. However, the function of circRNAs in OS remains unknown. Here, we aimed to determine the regulatory mechanisms of circRNAs in OS. Methods:The expression profiles of OS circRNA (GSE96964), microRNA (GSE65071) and mRNA (GSE33382) were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed circRNAs, miRNAs and mRNAs in OS. A ceRNA network was constructed based on circRNA-miRNA pairs and miRNA-mRNA pairs. MRNAs with significant prognostic differences were identified by the TARGET database in the network. Functional and pathway enrichment analyses were performed, and interactions between proteins were predicted using Cytoscape. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to elucidate the possible functions of these differentially expressed circRNAs. Results:A total of 15 downregulated circRNAs, 136 upregulated miRNAs and 52 downregulated mRNAs were identified in OS. Finally, a circRNA-miRNA-mRNA network was constructed in OS based on 14 circRNAs, 24 miRNAs, and 52 mRNAs. GO and KEGG pathway analyses suggested that the mRNAs in the network may be involved in the pathogenesis and progression of OS. Four mRNAs identified by the TARGET database were significantly associated with OS survival prognosis. A circRNA-miRNA-mRNA subnetwork was constructed based on these four mRNAs. Conclusion:Our results provide a deeper understanding of the regulatory mechanisms by which circRNAs compete for endogenous RNAs in OS.
Project description:This study aimed to characterize circular RNA (circRNA) expression profiles and biological functions in head and neck squamous cell carcinoma (HNSCC). Differentially expressed circRNAs were screened using an Arraystar Human CircRNA Array and verified by reverse transcription-quantitative polymerase chain reaction. Multiple bioinformatics methods and a hypergeometric test were employed to predict the interactions between RNAs and the functional circRNA‑microRNA (miRNA)-mRNA axes in HNSCC. As a result, 287 circRNAs and 1,053 mRNAs were determined to be differentially expressed in HNSCC compared with the adjacent tissue. In addition, the expression levels of circRNA_036186 and tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, ζ polypeptide (14‑3‑3ζ) were identified to be significantly different. A competing endogenous RNA (ceRNA) network was constructed, consisting of 5 circRNAs, 385 miRNAs and 96 mRNAs. Furthermore, we predicted that miR‑193b‑3p exerts a significant effect on 14‑3‑3ζ, and was significantly associated with the Hippo signaling pathway in HNSCC. On the whole, these findings suggest that circRNA_036186 likely regulates 14‑3‑3ζ expression by functioning as a ceRNA in the development and progression of HNSCC.