Unveiling Circular RNA-Mediated Regulatory Mechanisms in Necroptosis in Premature Ovarian Failure

BACKGROUND

Necroptosis is a programmed necrotic cell death, in which dying cells rupture and release intracellular components that trigger a proinflammatory response. The current study aimed at probing the circular RNA (circRNA)-mediated regulatory mechanisms in necroptosis in premature ovarian failure (POF).

METHODS

CircRNA sequencing analysis was conducted in ovarian tissues of control and POF rats and transcriptome microarrays were acquired from the GSE33423 dataset. Differential expression analysis of circRNAs and mRNAs was executed between the POF and control data. Both a necroptosis-based circRNA-microRNA (miRNA)-mRNA network and a protein-protein interaction (PPI) network were established. Then, the functional annotation and immunological traits were analyzed.

RESULTS

Totally, 1266 upregulated and 1283 downregulated circRNAs as well as 1101 upregulated and 1168 downregulated mRNAs were determined in the POF rats versus the controls. The differentially expressed mRNAs predominantly correlated with necroptosis. The circRNA-miRNA-mRNA networks of downregulated necroptosis genes (comprising rno_circRNA_004995-rno-miR-148b-5p-H2afy2, rno_circRNA_016998-rno-miR-29a-5p-Hmgb1, and rno_circRNA_017593-rno-miR-29a-5p-Hmgb1) and upregulated necroptosis genes (comprising rno_circRNA_015900-rno-miR-935-Stat1, rno_circRNA_007946-rno-miR-328a-3p-Stat5a, rno_circRNA_007947-rno-miR-328a-3p-Stat5a, rno_circRNA_005064-rno-miR-18a-5p-Stat1, rno_circRNA_005064-rno-miR-18a-5p-Stat5a, rno_circRNA_005115-rno-miR-22-3p-Stat1, rno_circRNA_009028-rno-miR-342-5p-Stat1, rno_circRNA_011240-rno-miR-1224-Stat5a, rno_circRNA_016078-rno-miR-711-Stat5a) were built. POF-specific necroptosis genes (STAT1, STAT5A, PLA2G4A, HMG1L1, HMGB1, AGER, EGFR, HDAC7, IFNA1, IL10RB, IL27RA, PYGL, SOCS1, TRADD, CXCL10, DDX5, EZH2, FADS2, FER, H2AFY2, HIST1H2AF, IFI44L, IL27, IRGM, MX1, NFKB2, PAFAH2, PEMT, PGM2L1, PGR, PHKA2, and PLB1) were selected since they displayed notable associations with most immune cells, immune checkpoints, chemokines, human leukocyte antigen (HLA) molecules, and immune receptors.

CONCLUSIONS

Altogether, we proposed the presence of widespread regulatory mechanisms of circRNAs in necroptosis and demonstrated that altered circRNA biogenesis might contribute to POF by affecting necroptosis.

Whole Transcriptome Sequencing Identified CircRNA Profiles and the Related Networks in Schizophrenia

Schizophrenia (SCZ) is a complex psychiatric syndrome with uncertain etiology. This study aimed to uncover the expression profiles and related regulatory networks of circular RNA (circRNA) in SCZ. Whole transcriptome sequencing was performed to assess the expression profiles of circRNAs and microRNAs (miRNAs) in the peripheral blood of three patients with SCZ and three healthy controls. Five circRNAs were validated by quantitative real-time PCR (RT-qPCR). TargetScan, RNAhybrid, and miRanda were performed to predict the target miRNAs of the top 10 dysregulated circRNAs. MiRTarBase was applied to predict the target mRNAs of miRNAs to construct circRNA-miRNA-mRNA (ceRNA) networks. CatRAPID and StarBase were used to predict the target RNA-binding proteins (RBPs) of circRNAs to construct circRNA-RBP networks. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to predict the potential functions of the maternal genes of circRNAs and target mRNAs. In total, 450 circRNAs and 160 miRNAs were found to be significantly differentially expressed, with hsa_circ_0003999 and hsa_circ_0030042 being significantly different between patients with SCZ and healthy controls (P < 0.05). The PI3K-AKT, MAPK, and cell cycle pathways were predicted to be associated with SCZ. GO analysis showed that focal adhesion was related to SCZ. The ceRNA networks, especially hsa_circ_0006151/hsa-miR-4685-3p/ZBTB16, hsa_circ_0000008/hsa-miR-1976/ZBTB16, and the hsa_circ_0007963/hsa-miR-3127-3p/UBE2K axes have the greatest probability of being involved in the pathophysiology of SCZ. The RBP networks, FXR1, FXR2, DGCR8, XRN2, FMR1, and QKI were the RBPs associated with SCZ. In conclusion, the circRNAs, ceRNAs, and RBP network expression patterns and related pathways indicate the potential role of circRNAs in the pathogenesis and development of SCZ.

Identification of Potential Immune-Related circRNA-miRNA-mRNA Regulatory Network in Intestine of Paralichthys olivaceus During Edwardsiella tarda Infection

Olive flounder (Paralichthys olivaceus) is an important economical flatfish in Japan, Korea, and China, but its production has been greatly threatened by disease outbreaks. In this research, we aimed to explore the immune responsive mechanism of P. olivaceus against Edwardsiella tarda infection by profiling the expression of circRNA, miRNA, and mRNA by RNA-seq and constructing a regulatory circular circRNA–miRNA–mRNA network. Illumina sequencing of samples from normal control (H0), 2 h (H2), 8 h (H8), and 12 h (H12) post-challenge was conducted. Differentially expressed (DE) circRNA (DE–circRNAs), miRNAs (DE–miRNAs), and mRNAs [differential expression genes (DEGs)] between challenge and control groups were identified, resulting in a total of 62 DE–circRNAs, 39 DE–miRNAs, and 3,011 DEGs. Based on the differentially expressed gene results, miRNA target interactions (circRNA–miRNA pairs and miRNA–mRNA pairs) were predicted by MiRanda software. Once these paired were combined, a preliminary circRNA–miRNA–mRNA network was generated with 198 circRNA–miRNA edges and 3,873 miRNA–mRNA edges, including 44 DE–circRNAs, 32 DE–miRNAs, and 1,774 DEGs. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was performed to evaluate the function of the DEGs in this network, and we focused and identified two important intestinal immune pathways (herpes simplex infection and intestinal immune network for IgA production) that showed statistical significance between the challenge and control groups. Furthermore, three critical DEGs (nectin2, MHC II α-chain, and MHC II β-chain) were identified, mapped into the preliminary circRNA–miRNA–mRNA network, and new circRNA–miRNA–mRNA regulatory networks were constructed. In conclusion, we, for the first time, identified circRNA–miRNA–mRNA network from P. olivaceus in the pathogenesis of E. tarda and provided valuable resources for further analyses of the molecular mechanisms and signaling networks.