ceRNA Regulatory Network Research Articles

Integrative Analysis of the Age-Related Dysregulated Genes Reveals an Inflammation and Immunity-Associated Regulatory Network in Alzheimer's Disease.

Alzheimer's disease (AD) is a neurodegenerative disease with a long incubation period. While extensive research has led to the construction of long non-coding RNA (lncRNA)-associated competing endogenous RNA (ceRNA) regulatory networks, which primarily derived from differential analyses between clinical AD patients and control individuals or mice, there remains a critical knowledge gap pertaining to the dynamic alterations in transcript expression profiles that occur with age, spanning from the pre-symptomatic stage to the onset of AD. In the present study, we examined the transcriptomic changes in AD model mice at three distinct stages: the unaffected (un-) stage, the pre-onset stage, and the late-onset stage, and identified 14, 57, and 99 differentially expressed mRNAs (DEmRs) in AD model mice at 3, 6, and 12months, respectively. Among these, we pinpointed 16 mRNAs closely associated with inflammation and immunity and excavated their lncRNA-mRNA regulatory network based on a comprehensive analysis. Notably, our preliminary analysis suggested that four lncRNAs (NONMMUT102943, ENSMUST00000160309, NONMMUT083044, and NONMMUT126468), eight miRNAs (miR-34a-5p, miR-22-5p, miR-302a/b-3p, miR-340-5p, miR-376a/b-5p, and miR-487b-5p), and four mRNAs (C1qa, Cd68, Ctss, and Slc11a1) may play pivotal roles in orchestrating immune and inflammatory responses during the early stages of AD. Our study has unveiled age-related AD risk genes, and provided an analytical framework for constructing lncRNA-mRNA networks using time series data and correlation analysis. Most notably, we have successfully constructed a comprehensive regulatory ceRNA network comprising genes intricately linked to inflammatory and immune functions in AD.

Analysis and Regulatory Mechanisms of Platelet-Related Genes in Patients with Ischemic Stroke.

It was found that ischemic stroke (IS) was associated with abnormal platelet activity and thrombosis. However, the potential significance of platelet-related genes (PRGs) in IS still needs to be more thorough. This study extracted IS-related transcriptome datasets from the Gene Expression Omnibus (GEO) database. The target genes were obtained by intersecting the differentially expressed genes (DEGs), the module genes related to IS, and PRGs, where the key genes of IS were screened by two machine learning algorithms. The key genes-based diagnostic model was constructed. Gene set enrichment analysis (GSEA) and the immune microenvironment analyses were analyzed targeting key genes in IS. The co-expression, TF-mRNA, and competitive endogenous RNAs (ceRNA) regulatory networks were constructed to reveal the potential regulation of key genes. Potential drugs targeting key genes were predicted as well. Totals of eight target genes were obtained and were associated with immune-related functions. Four platelet-related key genes were acquired, which were related to immunity and energy metabolism. The abnormal expressions of DOCK8, GIMAP5, ICOS were determined by the quantitative real-time polymerase chain reaction (qRT-PCR), and the significant correlations among these key genes were identified. Notably, hsa-miR-17-3p, hsa-miR-3158-3p, hsa-miR-423-3p, and hsa-miR-193a-8p could regulate all key genes at the same time. In addition, Caffeine, Carboplatin, and Vopratelimab were the targeted drugs of these key genes. This study identified four platelet-related key genes of IS, which might help to deepen the understanding of the role of platelet-related genes in the molecular mechanism of IS.

Systematic Analysis to Identify the MIR99AHG-has-miR-21-5p-EHD1 CeRNA Regulatory Network as Potential Biomarkers in Lung Cancer.

Lung cancer (LC) remains an extremely lethal disease worldwide, and effective prognostic biomarkers are at top priority. With the rapid development of high-throughput sequencing and bioinformatic analysis methods, the quest to characterize cancer transcriptomes continues to move forward. However, the integrated systematic analysis of lncRNA-miRNA-mRNA regulatory network in LC is lacking. In this study, we collected samples of cancer tissues and adjacent normal tissues from patients with lung cancer and conducted transcriptome and small RNA sequencing to identify differentially expressed genes (DEGs), miRNAs (DEMs), and lncRNAs (DELs). The regulatory roles of miRNAs in LC were explained by functional analysis on DEM-targeted genes. The lncRNA-miRNA pairs, miRNA-mRNA pairs, and lncRNA-mRNA pairs were identified and combined to construct the interplay of lncRNA-miRNA-mRNA. We evaluated the prognostic value of selected lncRNA-miRNA-mRNA by Kaplan-Meier analysis. Finally, we analyzed the expression levels of selected DEM, DELs, and DEGs in lung cancer patients and healthy people to verify our findings. A total of 1492 DEGs, 12 DEMs, and 604 DELs were identified in LC patients. Based on the bioinformatic analysis and the regulatory mechanism of ceRNAs, 3 lncRNAs (GATA2-AS1, LINC00632, MIR99AHG), 1 miRNA (hsa-miR-21-5p) and 5 targeted genes (RECK, TIMP3, EHD1, RASGRP1 and ERG) were figured out first. Through further Kaplan-Meier analysis screening the prognostic value, we finally found the hub subnetwork (MIR99AHG-hsa-miR-21-5p-EHD1) by collating lncRNA-miRNA pairs, miRNA-mRNA pairs and lncRNA-mRNA pairs. As the key of ceRNA regulatory network, the expression of miRNA-21-5p in lung cancer patients was significantly higher than that in healthy people (P < 0.01), and its high expression was significantly associated with poor prognosis (P = 0.0025). Our study successfully constructed a MIR99AHG-hsa-miR-21-5p-EHD1 mutually regulatory network, suggesting the potential efficient biomarkers in LC.

Unraveling the H19/GAS1 axis in recurrent implantation failure: A potential biomarker for diagnosis and insight into immune microenvironment alteration.

Recurrent implantation failure (RIF) presents a significant clinical challenge due to the lack of established diagnostic and therapeutic guidelines. Emerging evidence underscores the crucial role of competitive endogenous RNA (ceRNA) regulatory networks in non-cancerous female reproductive disorders, yet the intricacies and operational characteristics of these networks in RIF are not fully understood. This study aims to demystify the ceRNA regulatory network and identify potential biomarkers for its diagnosis. We analyzed expression profiles of three RNA types (long noncoding RNAs [lncRNAs], microRNAs [miRNAs], and mRNAs) sourced from the GEO database, leading to the identification of the H19-hsa-miR-301a-3p-GAS1 ceRNA network. This network demonstrates significant diagnostic relevance for RIF. Notably, the H19/GAS1 axis within this ceRNA network, identified through correlation analysis, emerged as a promising diagnostic marker, as evidenced by operating receiver operator characteristic (ROC) curve analysis. Further investigation into the binding potential of miR-301a-3p with H19 and GAS1 revealed a close association of these genes with endometrial disorders and embryo loss, as per the Comparative Toxicogenomics Database. Additionally, our immune infiltration analysis revealed a lower proportion of T cells gamma delta (γδ) in RIF, along with distinct differences in the expression of immune cell type-specific markers between fertile patients and those with RIF. We also observed a correlation between aberrant expression of H19/GAS1 and these immune markers, suggesting that the H19/GAS1 axis might play a role in modifying the immune microenvironment, contributing to the pathogenesis of RIF. In conclusion, the ceRNA-based H19/GAS1 axis holds promise as a novel diagnostic biomarker for RIF, potentially enhancing our understanding of its underlying mechanisms and improving the success rates of implantation.

Insights into the role of non-coding RNAs in the development of insecticide resistance in insects.

Pest control heavily relies on chemical pesticides has been going on for decades. However, the indiscriminate use of chemical pesticides often results in the development of resistance in pests. Almost all pests have developed some degree of resistance to pesticides. Research showed that the mechanisms of insecticide resistance in insects encompass metabolic resistance, behavioral resistance, penetration resistance and target-site resistance. Research on the these mechanisms has been mainly focused on the cis-regulatory or trans-regulatory for the insecticide resistance-related genes, with less attention paid to non-coding RNAs (ncRNAs), such as microRNA (miRNA), long non-coding RNA (lncRNA), and circular RNA (circRNA). There has been increased studies focus on understanding how these ncRNAs are involved in post-transcriptional regulation of insecticide resistance-related genes. Besides, the formatted endogenous RNA (ceRNA) regulatory networks (lncRNA/circRNA-miRNA-mRNA) has been identified as a key player in governing insect resistance formation. This review delves into the functions and underlying mechanisms of miRNA, lncRNA, and circRNA in regulating insect resistance. ncRNAs orchestrate insect resistance by modulating the expression of detoxification enzyme genes, insecticide target genes, as well as receptor genes, effectively regulating both target-site, metabolic and penetration resistance in insects. It also explores the regulatory mechanisms of ceRNA networks in the development of resistance. By enhancing our understanding of the mechanisms of ncRNAs in insecticide resistance, it will not only provide valuable insights into the new mechanisms of insecticide resistance but also help to enrich new directions in ncRNAs gene regulation research.

Study of LY9 as a potential biomarker for prognosis and prediction of immunotherapy efficacy in lung adenocarcinoma.

Lymphocyte antigen 9 (LY9) participates in the development of several tumors and diseases but has not been reported yet in lung adenocarcinoma (LUAD). First, we analyzed the expression and prognostic value of LY9 in pan-cancer, including LUAD. Additionally, we conducted a correlation analysis of LY9 expression in LUAD with immune cell infiltration using the TIMER database and the CIBERSORT algorithm, and with immune checkpoints using the GEPIA database. Also, we constructed a potential ceRNA network for LY9. Furthermore, we explored LY9-related pathways by Gene Set Enrichment Analysis (GSEA). Finally, validation of differential expression at the mRNA level was obtained from the GEO database. We collected LUAD tissues for Quantitative Real-time PCR (qRT-PCR) to verify the expression of LY9, CD8, and CD4 and calculated the correlation between them. We also conducted immunohistochemistry (IHC) to verify the protein expression of LY9. Results showed that LY9 was highly expressed in various tumors, including LUAD. Besides, patients with high LY9 expression presented longer overall survival (OS) and more multiple lymphocyte infiltrations. The expression of LY9 in LUAD strongly and positively correlates with multiple immune cell infiltration and immune checkpoints. The functional enrichment analysis indicated that LY9 was involved in multiple immune-related pathways and non-small cell lung cancer. Moreover, a ceRNA regulatory network of LINC00943-hsa-miR-141-3p-LY9 might be involved. Finally, GSE68465 dataset confirmed differential expression of LY9 mRNA levels in LUAD and the qRT-PCR results verified LY9 had a strong and positive correlation with CD4 and CD8 T cells. Unfortunately, IHC did not detect the expression of LY9 protein level in tumor tissues and WB experiments validated the protein expression of LY9 in the OCI-AML-2 cell line. Therefore, we hypothesized that LY9 could serve as a potential, novel prognostic biomarker for LUAD and could predict immunotherapy efficacy at the mRNA level.

LncRNA AP000842.3 Triggers the Malignant Progression of Prostate Cancer by Regulating Cuproptosis Related Gene NFAT5.

Prostate cancer (PRAD) is a highly malignant disease with poor prognosis, and its development is regulated by a complex network of genes and signaling pathways. LncRNAs and miRNAs have significant regulatory roles in PRAD through the ceRNA network. Cuproptosis is a unique form of programmed cell death that is involved in various signaling pathways and biological processes related to tumor development. Nuclear factor of activated T cells 5 (NFAT5), a transcription factor that activates T cells, has been implicated in cuproptosis. However, the regulatory mechanism by which NFAT5 is involved in the ceRNA network in PRAD remains unclear. Through bioinformatics analysis, we found the ceRNA axis that regulates cuproptosis. By performing ROS assay and copper ion concentration assay, we demonstrated that inhibiting NFAT5 can increase the sensitivity of PRAD to cuproptosis inducers. By using luciferase assay, we discovered that AP000842.3 acts as the ceRNA of miR-206 to regulate the expression of NFAT5. In this study, we found that lncRNA AP000842.3, as a ceRNA of miR-206, was involved in the regulation of levels of the transcription factor NFAT5 associated with cuproptosis in PRAD. First, knocking down NFAT5 can increase the sensitivity of PRAD to cuproptosis inducers. Meanwhile, changes in the expression of AP000842.3 and miR-206 could affect the proliferation of PRAD by regulating NFAT5. Mechanistically, AP000842.3 acts as the ceRNA of miR-206 to regulate the expression of NFAT5. In addition, the effects of lncRNA AP000842.3 on malignant progression of PRAD and NFAT5 were partially dependent on miR-206. Taken together, our study reveals a key ceRNA regulatory network in PRAD and can be regarded as a new potential target for PRAD diagnosis and treatment.

Identification of cuproptosis-related genes and immune infiltration in dilated cardiomyopathy

BackgroundDilated cardiomyopathy (DCM) is a leading cause of heart failure. Cuproptosis is involved in various diseases, although its role in DCM is still unclear. Here, this study aims to investigate the feasibility of using genes related to cuproptosis as diagnostic biomarkers for DCM and the association of their expression with immune infiltration and drug target in cardiac tissue. MethodsGene expression data from nonfailure (NF) and DCM samples were retrieved from the GEO database. Cuproptosis scores were calculated using single-sample gene set enrichment analysis (ssGSEA). Weighted gene co-expression network analysis (WGCNA) was used to screen key modules associated with DCM and cuproptosis. Random forest and least absolute shrinkage and selection operator (LASSO) were applied to identify signature genes. Finally, immune cell infiltration was assessed using ssGSEA. mRNA-miRNA-lncRNA regulatory networks and chemical-drug regulatory networks based on signature genes were analyzed by Cytoscape. Results8 modules were aggregated by WGCNA, among which MEblue was significantly associated with cuproptosis scores and DCM. A diagnostic model made up of six signature genes including SEPTIN1, CLEC11A, ISG15, P3H3, SDSL, and INKA1 was selected. Furthermore, immune infiltration studies showed significant differences between DCM and NF. Drugs networks and ceRNA regulatory network based on six signature genes were successfully constructed. ConclusionSix signature genes (SEPTIN1, CLEC11A, ISG15, P3H3, SDSL, and INKA1) were identified as novel diagnostic biomarkers in DCM. In addition, the expression of these genes was associated with immune cell infiltration, suggesting that cuproptosis may be involved in the immune regulation of DCM.

Comprehensive Analysis of PANoptosis-Related Gene Signature of Ulcerative Colitis.

Accumulating evidence shows that the abnormal increase in the mortality of intestinal epithelial cells (IECs) caused by apoptosis, pyroptosis, and necroptosis is closely related to the function of mucous membrane immunity and barrier function in patients with ulcerative colitis (UC). As a procedural death path that integrates the above-mentioned many deaths, the role of PANoptosis in UC has not been clarified. This study aims to explore the characterization of PANoptosis patterns and determine the potential biomarkers and therapeutic targets. We constructed a PANoptosis gene set and revealed significant activation of PANoptosis in UC patients based on multiple transcriptome profiles of intestinal mucosal biopsies from the GEO database. Comprehensive bioinformatics analysis revealed five key genes (ZBP1, AIM2, CASP1/8, IRF1) of PANoptosome with good diagnostic value and were highly correlated with an increase in pro-inflammatory immune cells and factors. In addition, we established a reliable ceRNA regulatory network of PANoptosis and predicted three potential small-molecule drugs sharing calcium channel blockers that were identified, among which flunarizine exhibited the highest correlation with a high binding affinity to the targets. Finally, we used the DSS-induced colitis model to validate our findings. This study identifies key genes of PANoptosis associated with UC development and hypothesizes that IRF1 as a TF promotes PANoptosome multicomponent expression, activates PANoptosis, and then induces IECs excessive death.

Study of molecular patterns associated with ferroptosis in Parkinson's disease and its immune signature.

Parkinson's disease is the second most common neurodegenerative disease in the world. We downloaded data on Parkinson's disease and Ferroptosis-related genes from the GEO and FerrDb databases. We used WCGAN and Random Forest algorithm to screen out five Parkinson's disease ferroptosis-related hub genes. Two genes were identified for the first time as possibly playing a role in Braak staging progression. Unsupervised clustering analysis based on hub genes yielded ferroptosis isoforms, and immune infiltration analysis indicated that these isoforms are associated with immune cells and may represent different immune patterns. FRHGs scores were obtained to quantify the level of ferroptosis modifications in each individual. In addition, differences in interleukin expression were found between the two ferroptosis subtypes. The biological functions involved in the hub gene are analyzed. The ceRNA regulatory network of hub genes was mapped. The disease classification diagnosis model and risk prediction model were also constructed by applying hub genes based on logistic regression. Multiple external datasets validated the hub gene and classification diagnostic model with some accuracy. This study explored hub genes associated with ferroptosis in Parkinson's disease and their molecular patterns and immune signatures to provide new ideas for finding new targets for intervention and predictive biomarkers.

Whole-Transcriptome Sequencing of Ovary Reveals the ceRNA Regulation Network in Egg Production of Gaoyou Duck.

To investigate the regulatory mechanism of the competing endogenous RNAs (ceRNAs) on the egg performance of Gaoyou ducks, full transcriptome sequencing was performed to analyze the ovarian tissues in Gaoyou ducks. The ducks were categorized into high- and low-yield groups based on the individual in-cage egg production records and the hematoxylin-eosin (HE) staining results. The differentially expressed genes (DEGs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs) were further processed by GO (gene ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analyses. In total, 72 DEmRNAs; 23 DElncRNAs; 4 DEcircRNAs; and 5 signaling pathways, including the ovarian steroidogenesis, PI3K-Akt, hedgehog, tryptophan metabolism, and oocyte meiosis signaling pathways, were significantly enriched. These results suggest that they could be associated with the Gaoyou duck's ovarian function and affect the total egg production or double-yolked egg production. Furthermore, a coregulation network based on the related candidate ceRNAs across the high- and low-yield egg production groups was constructed. Our findings provide new insights into the mechanisms underlying the molecular regulation of related circRNA/lncRNA-miRNA-mRNA in the egg production and double-yolked egg traits of Gaoyou ducks.

Whole-transcriptome characterization and functional analysis of lncRNA-miRNA-mRNA regulatory networks responsive to sugarcane mosaic virus in maize resistant and susceptible inbred lines

Sugarcane mosaic virus (SCMV) is one of the most important pathogens causing maize dwarf mosaic disease, which seriously affects the yield and quality of maize. Currently, the molecular mechanism of non-coding RNAs (ncRNAs) responding to SCMV infection in maize is still uncovered. In this study, a total of 112 differentially expressed (DE)-long non-coding RNAs (lncRNAs), 24 DE-microRNAs (miRNAs), and 1822 DE-messenger RNAs (mRNAs), and 363 DE-lncRNAs, 230 DE-miRNAs, and 4376 DE-mRNAs were identified in maize resistant (Chang7-2) and susceptible (Mo17) inbred lines in response to SCMV infection through whole-transcriptome RNA sequencing, respectively. Moreover, 4874 mRNAs potentially targeted by 635 miRNAs were obtained by degradome sequencing. Subsequently, several crucial SCMV-responsive lncRNA-miRNA-mRNA networks were established, of which the expression levels of lncRNA10865-miR166j-3p-HDZ25/69 (class III homeodomain-leucine zipper 25/69) module, and lncRNA14234-miR394a-5p-SPL11 (squamosal promoter-binding protein-like 11) module were further verified. Additionally, silencing lncRNA10865 increased the accumulations of SCMV and miR166j-3p, while silencing lncRNA14234 decreased the accumulations of SCMV and SPL11 targeted by miR394a-5p. This study revealed the interactions of lncRNAs, miRNAs and mRNAs in maize resistant and susceptible materials, providing novel clues to reveal the mechanism of maize in resistance to SCMV from the perspective of competing endogenous RNA (ceRNA) regulatory networks.

Construction of a ceRNA regulatory network to explore potential pathogenesis mechanisms involved in human hepatocellular carcinoma

Worldwide, primary liver cancer is the third leading cause of cancer-related death. Hepatocellular carcinoma (HCC) accounts for the majority of primary liver cancers. Recent studies have shown that circular RNAs (circRNAs) that interact with microRNAs (miRNAs) are involved in the occurrence and development of various tumours. Transcriptional profile analysis was used to analyse expression of circRNAs in HCC in this study. The top ten upregulated circRNAs were selected and validated by quantitative reverse transcription polymerase chain reaction (qRT-PCR) in another 34 HCC patients. MiRNAs and mRNAs downstream of these circRNAs were explored through database analysis, and finally, the competitive endogenous RNA (ceRNA) networks were constructed for 5 selected circRNAs. We identified 9658 differentially expressed circRNAs by transcriptional profile analysis. QRT-PCR was performed to validate the top ten upregulated circRNAs, and five circRNAs were selected for further analysis. The miRNAs and mRNAs downstream of these five circRNAs were predicted to construct ceRNA network diagrams. Further analysis revealed five circRNA–miRNA–mRNA axes that correlate negatively with HCC prognosis. Numerous differentially expressed circRNAs exist in HCC, and they can regulate the biological behaviour of HCC through ceRNA networks. Bioinformatics analysis showed that ceRNA regulatory axes involved in HCC have high diagnostic and prognostic value and deserve further exploration.

Crosstalk of cuproptosis-related prognostic signature and competing endogenous RNAs regulation in hepatocellular carcinoma.

Cuproptosis is a new type of programmed cell death involved in the regulation of neuroendocrine tumors, immune microenvironment, and substance metabolism. However, the role of cuproptosis-related genes (CRGs) in Hepatocellular carcinoma (HCC) remains unclear. Through multiple bioinformatics analysis, we constructed a prognostic gene model and competing endogenous RNA (ceRNA) network. The correlation between CRGs and prognosis, immune infiltration, immune checkpoints, microsatellite instability (MSI) and tumor mutational burden (TMB) was analyzed by Kaplan-Meier curve, univariate Cox, multivariate regression, and Spearman's analysis in HCC patients. Besides, the qRT-PCR and immunohistochemistry assays were used to determine prognostic CRGs mRNA and protein expression in HCC. We established a novel 3-gene signature related to CRGs for evaluating the prognosis of HCC patients. HCC patients with high risk scores had a poor prognosis with an area under the curve of 0.737, 0.646, and 0.634 on 1-year, 3-year, and 5-year receiver operating characteristic curves. Significant correlation was observed between prognostic CRGs and immune infiltration, immune checkpoints, MSI and TMB. We also developed five ceRNA networks to regulate the occurrence and progression of HCC. CDKN2A, DLAT, and PDHA1 protein expression was up-regulated in HCC versus normal tissues. Besides, the mRNA expression levels of CDKN2A, DLAT, GLS, and PDHA1 were elevated in the HCC cell lines compared to the normal liver cell lines. This novel prognostic CRGs signature could be accurately predict the prognosis of patients with HCC. The ceRNA regulatory network might be potential prognostic biomarkers and therapeutic targets for HCC patients.

Identification of potential immune-related hub genes in Parkinson's disease based on machine learning and development and validation of a diagnostic classification model.

Parkinson's disease is the second most common neurodegenerative disease in the world. However, current diagnostic methods are still limited, and available treatments can only mitigate the symptoms of the disease, not reverse it at the root. The immune function has been identified as playing a role in PD, but the exact mechanism is unknown. This study aimed to search for potential immune-related hub genes in Parkinson's disease, find relevant immune infiltration patterns, and develop a categorical diagnostic model. We downloaded the GSE8397 dataset from the GEO database, which contains gene expression microarray data for 15 healthy human SN samples and 24 PD patient SN samples. Screening for PD-related DEGs using WGCNA and differential expression analysis. These PD-related DEGs were analyzed for GO and KEGG enrichment. Subsequently, hub genes (dld, dlk1, iars and ttd19) were screened by LASSO and mSVM-RFE machine learning algorithms. We used the ssGSEA algorithm to calculate and evaluate the differences in nigrostriatal immune cell types in the GSE8397 dataset. The association between dld, dlk1, iars and ttc19 and 28 immune cells was investigated. Using the GSEA and GSVA algorithms, we analyzed the biological functions associated with immune-related hub genes. Establishment of a ceRNA regulatory network for immune-related hub genes. Finally, a logistic regression model was used to develop a PD classification diagnostic model, and the accuracy of the model was verified in three independent data sets. The three independent datasets are GES49036 (containing 8 healthy human nigrostriatal tissue samples and 15 PD patient nigrostriatal tissue samples), GSE20292 (containing 18 healthy human nigrostriatal tissue samples and 11 PD patient nigrostriatal tissue samples) and GSE7621 (containing 9 healthy human nigrostriatal tissue samples and 16 PD patient nigrostriatal tissue samples). Ultimately, we screened for four immune-related Parkinson's disease hub genes. Among them, the AUC values of dlk1, dld and ttc19 in GSE8397 and three other independent external datasets were all greater than 0.7, indicating that these three genes have a certain level of accuracy. The iars gene had an AUC value greater than 0.7 in GES8397 and one independent external data while the AUC values in the other two independent external data sets ranged between 0.5 and 0.7. These results suggest that iars also has some research value. We successfully constructed a categorical diagnostic model based on these four immune-related Parkinson's disease hub genes, and the AUC values of the joint diagnostic model were greater than 0.9 in both GSE8397 and three independent external datasets. These results indicate that the categorical diagnostic model has a good ability to distinguish between healthy individuals and Parkinson's disease patients. In addition, ceRNA networks reveal complex regulatory relationships based on immune-related hub genes. In this study, four immune-related PD hub genes (dld, dlk1, iars and ttd19) were obtained. A reliable diagnostic model for PD classification was developed. This study provides algorithmic-level support to explore the immune-related mechanisms of PD and the prediction of immune-related drug targets.

Comprehensive analysis of differentially expressed mRNA, lncRNA and miRNA, and their ceRNA networks in the regulation of shell color in the Manila clam (Ruditapes philippinarum)

The regulatory mechanism of ceRNA network plays an important role in molecular function and biological processes, however, the molecular mechanism in the shell color of Ruditapes philippinarum has not yet been reported. In this study, we performed transcriptome sequencing on the mantle of R. philippinarum with different shell colors, and screened for mRNA, miRNA, and lncRNA. A total of 61 mRNAs, 3725 lncRNAs and 90 miRNAs were obtained from all the shell color comparison groups (all mRNAs, lncRNAs and miRNAs P < 0.05), and 7 mRNAs, 8 lncRNAs, and 4 miRNAs of the porphyrin pathway and melanin pathway were screened for competitive endogenous RNA (ceRNA) network construction. The results indicate that the ceRNA network composed of mRNA and lncRNA, centered around efu-miR-101, mle-bantam-3p, egr-miR-9-5p, and sma-miR-75p, may play a crucial regulatory role in shell color formation. This study reveals for the first time the mechanism of ceRNA regulatory networks in the shell color of R. philippinarum and providing important reference data for molecular breeding of shell color in R. philippinarum.

The identification of regulatory ceRNA network involved in Drosophila Toll immune responses

Non-coding RNAs play important roles in the innate immunity of Drosophila, with various lncRNAs and miRNAs identified to maintain Drosophila innate immune homeostasis by regulating protein functions. However, it remains unclear whether interactions between lncRNAs and miRNAs give rise to a ceRNA network. In our previous study, we observed the highest differential expression levels of lncRNA-CR11538, lncRNA-CR33942, and lncRNA-CR46018 in wild-type flies after Gram-positive bacterial infection, prompting us to investigate their role in the regulation of Drosophila Toll immune response through RNA-seq analysis. Herein, our comprehensive bioinformatics analysis revealed that lncRNA-CR11538, lncRNA-CR33942, and lncRNA-CR46018 are involved in defense mechanisms and stimulus response. Moreover, lncRNA-CR11538 and lncRNA-CR46018 can also participate in the metabolic recovery processes following Gram-positive bacterial infection. Subsequently, we employed GSEA screening and RT-qPCR to identify seven miRNAs (miR-957, miR-1015, miR-982, miR-993, miR-1007, miR-193, and miR-978) that may be regulated by these three lncRNAs. Furthermore, we predicted the potential target genes in the Toll signaling pathway for these miRNAs and their interaction with the three lncRNAs using TargetScan and miRanda software and preliminary verification. As a result, we established a potential ceRNA regulatory network for Toll immune responses in Drosophila, comprising three lncRNAs and seven miRNAs. This study provides evidence of a ceRNA regulatory network in Drosophila Toll immune responses and offers novel insights into understanding the regulatory networks involved in the innate immunity of other animals.

Comprehensive analysis of circRNA-miRNA-mRNA networks in the kidney of snakehead (Channa argus) response to Nocardia seriolae challenge

Non-coding RNAs (ncRNAs) play vital roles in regulating the expression levels of genes that control essential biological functions, including immune response to bacterial infections in teleost. To dissect the roles of ncRNAs in the Channa argus (snakehead), a systematic analysis of the expression profiles of circRNA, miRNA and mRNA, as well as competing endogenous RNAs (ceRNA) regulatory networks in the kidney of snakehead following Nocardia seriolae infection were performed in the present study. A total of 111 differentially expressed circRNAs, 706 differentially expressed miRNAs, and 2548 differentially expressed mRNAs were identified in the N. seriolae infected snakehead. Based on these differently expressed RNAs, we identified 55 circRNA-mRNA pairs, 124 miRNA-mRNA pairs, and 35 circRNA-miRNA-mRNA regulatory networks, including dre-miR-103-CD302, dre-miR-27e-IGSF3, novel_circ_0005462/novel_403-IGKC, novel_circ_0001750/novel_circ_0002162-novel_477-OCLN, and novel_circ_0003847-novel_4-KCNAB3. In addition, luciferase reporter assay was employed to detect the target relationships of several circRNA-miRNA-mRNA pairs. Taken together, this study demonstrates that the genes associated with immunity and structures in the kidney of snakehead can be regulated by circRNAs and miRNAs at post-transcription levels, and provided theoretical guidance for ncRNAs studies for other teleost. However, further studies are still in great need to validate the regulatory mechanisms of ncRNAs in snakehead.

Unveiling the LncRNA-miRNA-mRNA Regulatory Network in Arsenic-Induced Nerve Injury in Rats through High-Throughput Sequencing.

Arsenic is a natural toxin which is widely distributed in the environment, incurring diverse toxicities and health problems. Previous studies have shown that long non-coding RNAs (LncRNAs) are also reported to contribute to As-induced adverse effects. LncRNAs are involved in the development of nerve injury, generally acting as sponges for microRNAs (miRNAs). This study aimed to investigate the competitive endogenous RNA (ceRNA) regulatory networks associated with arsenic-induced nerve damage. A total of 40 male Wistar rats were exposed to different doses of arsenic for 12 weeks, and samples were collected for pathological observation and high-throughput sequencing. The ceRNA network was constructed using Cytoscape, and key genes were identified through the PPI network and CytoHubba methods. A real-time quantitative PCR assay was performed to validate gene expression levels. The results showed that subchronic exposure to arsenic in drinking water resulted in pathological and ultrastructural damage to the hippocampal tissue, including changes in neuron morphology, mitochondria, and synapses. Exposure to arsenic results in the dysregulation of LncRNA and mRNA expression in the hippocampal tissues of rats. These molecules participated in multiple ceRNA axes and formed a network of ceRNAs associated with nerve injury. This study also verified key molecules within the ceRNA network and provided preliminary evidence implicating the ENRNOT-00000022622-miR-206-3p-Bdnf axis in the mechanism of neural damage induced by arsenic in rats. These findings provide novel insights into the underlying mechanism of nervous system damage induced by arsenic exposure.

Identify and validate circadian regulators as potential prognostic markers and immune infiltrates in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a heterogeneity pathological malignant cancer with leading causes of morbidity and mortality. EGFR inhibitors, immune checkpoint inhibitors have become novel treatments. However, the mechanism still remained uncertain. Several studies have confirmed that the circadian rhythms induce multiple malignancies developing. We utilized multi-omics analysis to demonstrate the crosstalk between circadian clock genes and tumor microenvironment in HNSCC. Firstly, we performed the LASSO Cox regression analysis based on the 16 important clock genes. A 7-gene risk model was successfully established in TCGA and validated in GEO datasets. Next, CIBERSORT and ESTIMATE methods were performed to display the immune landscape of high risk and low risk groups, and the results showed that high abundance of mast cells activated, dendritic cells activated and neutrophils were positively correlated with poor OS. To further identify hub genes, Kaplan Meier plot was applied in all TCGA and GEO datasets and two hub genes (PER2, and PER3) were identified, especially PER3, which was found strongly associated with immune score, PDCD1, CD4 + and CD8 + T cells in HNSCCC. Moreover, to explore the innate mechanism of circadian-induced pathway, we constructed a circadian-related ceRNA regulatory network containing 34 lncRNAs, 3 miRNAs and 4 core circadian genes. In-vitro experiments also verified that Per2 or Per3 could suppressed the proliferation, migration and invasion of HNSC. This study unraveled the association between PER3 and prognosis in patients with HNSC and the innate mechanism remains to be elucidated.