ceRNA Network Research Articles

Identification of immune characteristic biomarkers and therapeutic targets in cuproptosis for sepsis by integrated bioinformatics analysis and single-cell RNA sequencing analysis

BackgroundCuproptosis is a copper-dependent cell death that is connected to the development and immune response of multiple diseases. However, the function of cuproptosis in the immune characteristics of sepsis remains unclear. MethodWe obtained two sepsis datasets (GSE9960 and GSE134347) from the GEO database and classified the raw data with R packages. Cuproptosis-related genes were manually curated, and differentially expressed cuproptosis-related genes (DECuGs) were identified. Afterwards, we applied enrichment analysis and identified key DECuGs by performing machine learning techniques. Then, the immune cell infiltrations and correlation between DECuGs and immunocyte features were created by the CIBERSORT algorithm. Subsequently, unsupervised hierarchical clustering analysis was performed based on key DECuGs. We then constructed a ceRNA network based on key DECuGs by using multi-step computational strategies and predicted potential drugs in the DrugBank database. Finally, the role of these key genes in immune cells was validated at the single-cell RNA level between septic patients and healthy controls. ResultsOverall, 16 DECuGs were obtained, and most of them had lower expression levels in sepsis samples. Afterwards, we obtained six key DECuGs by performing machine learning. Then, the LIPT1-T-cell CD4 memory resting was the most positively correlated DECuG–immunocyte pair. Subsequently, two different subclusters were identified by six DECuGs. Bioinformatics analysis revealed that there were different immune characteristics between the two subclusters. Moreover, we identified the key lncRNA OIP5-AS1 within the ceRNA network and obtained 4 drugs that may represent novel drugs for sepsis. Finally, these key DECuGs were statistically significantly dysregulated in another validation set and showed a major distribution in monocytes, T cells, B cells, NK cells and platelets at the single-cell RNA level. ConclusionThese findings suggest that cuproptosis might promote the progression of sepsis by affecting the immune system and metabolic dysfunction, which provides a new direction for understanding potential pathogenic processes and therapeutic targets in sepsis.

Construction of circular RNA‐based competing endogenous RNA network in colon cancer

AbstractCircular RNAs (CircRNAs) are now under discussion as novel promising biomarkers for patients with various tumors. Our study aimed to identify circRNAs related to the progression of colon cancer and to further investigate their roles in the development of colon cancer base on The Cancer Genome Atlas database. The competing endogenous RNA (ceRNA) network was constructed based on 4 circRNAs, 14 miRNAs, and 229 mRNAs. Meanwhile, three hub genes were identified via the protein protein interaction networks (PPI) network. It should be noted that only RUNX1 targeted by circ‐0084615 and mir‐330‐3p was confirmed as a survival‐related gene. Further analyses indicated the possible function of RUNX1 in colon progression, such as angiogenesis, epithelial–mesenchymal transition, hedgehog signaling and so on. Further investigations were conducted into the correlation between RUNX1 expression profiles and immune cells. Finally, we validated the expression of the circ‐0084615/mir‐330‐3p/RUNX1 axis in clinical specimens. In conclusion, we constructed ceRNA network and revealed that the circ‐0084615/mir‐330‐3p/RUNX1 axis serves as a critical role in colon cancer.

The Critical Role of Pyroptosis in Peri-Implantitis.

Peri-implantitis (PI) is a prevalent complication of implant treatment. Pyroptosis, a distinctive inflammatory programmed cell death, is crucial to the pathophysiology of PI. Despite its importance, the pyroptosis-related genes (PRGs) influencing PI's progression remain largely unexplored. This study conducted histological staining and transcriptome analyze from three datasets. The intersection of differentially expressed genes (DEGs) and PRGs was identified as pyroptosis-related differentially expressed genes (PRDEGs). Functional enrichment analyses were conducted to shed light on potential underlying mechanisms. Weighted Gene Co-expression Network Analysis (WGCNA) and a pyroptotic macrophage model were utilized to identify and validate hub PRDEGs. Immune cell infiltration in PI and its relationship with hub PRDEGs were also examined. Furthermore, consensus clustering was performed to identify new PI subtypes. Protein-protein interaction (PPI) network, competing endogenous RNA (ceRNA) network, mRNA-mRNA binding protein regulatory (RBP) network, and mRNA-drugs regulatory network of hub PRDEGs were also analyzed. Eight hub PRDEGs were identified: PGF, DPEP1, IL36B, IFIH1, TCEA3, RIPK3, NET7, and TLR3, which are instrumental in the PI's progression. Two PI subtypes were distinguished, with Cluster 1 exhibiting higher immune cell activation. The exploration of regulatory networks provided novel mechanisms and therapeutic targets in PI. Our research highlights the critical role of pyroptosis and identifies eight hub PRDEGs in PI's progression, offering insights into novel immunotherapy targets and laying the foundation for advanced diagnostic and treatment strategies. This contributes to our understanding of PI and underscores the potential for personalized clinical management.

AC024896.1/miR-363-3p Axis Regulates the Malignant Progression of Acute Myeloid Leukemia by Cuproptosis-Related Gene MYO1B.

Acute myeloid leukemia (AML) is a hematological malignancy with poor patient prognosis. Cuprotosis is a newly discovered cell death that regulates the proliferation and progression of tumor cells. Long non-coding RNAs (lncRNAs) are key molecules and potential biomarkers for the diagnosis and treatment of various diseases. However, the effect of cuprotosis-associated lncRNAs on AML remains unclear. The aim of this study was to investigate the relationship between the expression of cuprotosis-related gene and the prognosis of AML. Consensus cluster analysis was performed on AML patients according to the cuprotosis-related gene expression matrix, and survival analysis and differential gene analysis were performed. Then lncRNA and miRNA related to AML tumor progression were screened according to univariate COX regression analysis. After that, Kaplan-Meier analysis, correlation analysis, and AUC curve were used to determine the ceRNA network that might regulate AML. The regulatory relationship of ceRNA was verified in AML cell lines by RT-qPCR and Western blotting. The AC024896.1/miR-363-3p axis drives MYO1B to promote the malignant progression of AML. First, a change in the expression of AC024896.1 and miR-363-3p can affect the proliferation of AML by regulating MYO1B. Mechanistically, AC024896.1 regulates the expression of MYO1B as the ceRNA of miR-363-3p. Moreover, the regulation of AC024896.1 in the malignant progression of AML depends partly on miR-363-3p. In summary, our study reveals AC024896.1/miR-363-3p/MYO1B Axis in AML, which can be regarded as a new potential target for the diagnosis and treatment of AML.

Development Immune-Related Prognostic Model and LncRNA-miRNA-mRNA ceRNA Network for Cervical Cancer

Development Immune-Related Prognostic Model and LncRNA-miRNA-mRNA ceRNA Network for Cervical Cancer

Transcriptomic Analyses and Experimental Validation Identified Immune-Related lncRNA-mRNA Pair MIR210HG-BPIFC Regulating the Progression of Hypertrophic Cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is a disease in which the myocardium of the heart becomes asymmetrically thickened, malformed, disordered, and loses its normal structure and function. Recent studies have demonstrated the significant involvement of inflammatory responses in HCM. However, the precise role of immune-related long non-coding RNAs (lncRNAs) in the pathogenesis of HCM remains unclear. In this study, we performed a comprehensive analysis of immune-related lncRNAs in HCM. First, transcriptomic RNA-Seq data from both HCM patients and healthy individuals (GSE180313) were reanalyzed thoroughly. Key HCM-related modules were identified using weighted gene co-expression network analysis (WGCNA). A screening for immune-related lncRNAs was conducted within the key modules using immune-related mRNA co-expression analysis. Based on lncRNA-mRNA pairs that exhibit shared regulatory microRNAs (miRNAs), we constructed a competing endogenous RNA (ceRNA) network, comprising 9 lncRNAs and 17 mRNAs that were significantly correlated. Among the 26 lncRNA-mRNA pairs, only the MIR210HG-BPIFC pair was verified by another HCM dataset (GSE130036) and the isoprenaline (ISO)-induced HCM cell model. Furthermore, knockdown of MIR210HG increased the regulatory miRNAs and decreased the mRNA expression of BPIFC correspondingly in AC16 cells. Additionally, the analysis of immune cell infiltration indicated that the MIR210HG-BPIFC pair was potentially involved in the infiltration of naïve CD4+ T cells and CD8+ T cells. Together, our findings indicate that the decreased expression of the lncRNA-mRNA pair MIR210HG-BPIFC was significantly correlated with the pathogenesis of the disease and may be involved in the immune cell infiltration in the mechanism of HCM.

An in-silico Approach for Recognition of Long non-coding RNA-Associated Competing Endogenous RNA Axes in Prostate Cancer.

Prostate cancer is among the most central sources of cancer-related mortalities. In order to find novel candidates for therapeutic strategies in this kind of cancer, we developed an in-silico method for identification of competing endogenous RNA network. According to the microarray data analyses between prostate tumor and normal specimens, we attained 1312 differentially expressed (DE)mRNAs, including 778 down-regulated DEmRNAs (such as CXCL13 and BMP5) and 584 up-regulated DEmRNAs (such as OR51E2 and LUZP2), 39 DElncRNAs, including 10 down-regulated DElncRNAs (such as UBXN10-AS1 and FENDRR) and 29 up-regulated DElncRNAs (such as PCA3 and LINC00992) and 10 DEmiRNAs, including 2 down-regulated DEmiRNAs (such as MIR675 and MIR1908) and 8 up-regulated DEmiRNAs (such as MIR6773 and MIR4683). We constructed the ceRNA network between these transcripts. We also evaluated the related signaling pathways and the significance of these RNAs in prediction of survival of patients with prostate cancer. This study provides novel candidates for construction of specific treatment routes for prostate cancer.

Bioinformatic analysis and construction of competitive endogenous RNA network reveals protective effect of Jiangtang Sanhao Formula on the liver of diabetic mice

IntroductionJiangtang Sanhao Formula (JTSHF), composed of Panax ginseng, Atractylodes macrocephala, Coptis chinensis, Salvia miltiorrhiza and several other herbs, is a traditional Chinese medicine formula commonly used to treat type 2 diabetes. This compound shows significant clinical efficacy in the treatment of diabetic, however, its target and pharmacological mechanism are still unclear. The present study explored the therapeutic effect of JTSHF on diabetic mice and conducted RNA sequencing to investigate the potential mechanism. MethodsThe T2DM mice model was established using a high-fat diet combined with an intraperitoneal injection of low-dose STZ. Fasting blood glucose (FBG), serum insulin, glucose tolerance, and blood lipids in mice from different groups were examined. Then the effects of JTSHF on oxidative stress and liver histopathology in diabetic mice were observed. Next, transcriptome analysis was performed to identify differentially expressed genes (DEG), which were validated using real-time quantitative PCR (RT-qPCR). By using pathway enrichment analysis, we identified several key pathways which are essential in the JTSHF effect on T2DM. Finally, we constructed ceRNA network to illustrate the regulatory effect of JTSHF on transcriptional profile in diabetic liver. ResultsJTSHF reduced FBG level and blood lipid contents, ameliorated glucose tolerance and improved insulin sensitivity in diabetic mice. It also showed protective effects on fatty livers induced by high-fat diet and diabetes. For the first time, we revealed that JTSHF exerts anti-T2DM role in the liver of diabetic mice, which is associated with multiple molecular targets and signaling pathways. Enrichment analysis and treatment-based mRNA-ncRNA-miRNA ceRNA networks revealed that JTSHF might exerts therapeutic effect by modulating lipid metabolism. DiscussionOur research found that JTSHF exerts anti-T2DM effect by affecting multiple pathways. Among these, lipid metabolism and oxidative stress might be involved. The present study provided novel insights for the mechanism of JTSHF, and the differentially expressed genes identified can be potential therapeutic targets in the treatment of T2DM in future.

Hsa_circ_0087100/hsa-miR-6743-5p affects Th1 cell differentiation by regulating STAT1 in diabetic retinopathy.

Objective: To elucidate the role of the competitive endogenous RNA (ceRNA) network in immune infiltration of diabetic retinopathy (DR). Methods: We obtained differentially expressed (DE) circRNAs, miRNAs and mRNAs from the Gene Expression Omnibus database. Then, we identified immune infiltration by CIBERSORT and single-sample gene set enrichment analysis and discovered co-expression genes by weighted gene co-expression network analysis. Furthermore, STAT1-mediated Th1 differentiation was determined in DR cell models, DR patients and DR mouse models. Results: hsa_circ_0087100/hsa-miR-6743-5p/STAT1 was involved in immune infiltration of Th1 cells. Aberrant expression of the ceRNA network and STAT1-mediated Th1 differentiation was thus verified in vitro and in vivo. Conclusion: hsa_circ_0087100/hsa-miR-6743-5p/STAT1 may affect Th1 cell differentiation in DR.

Comprehensive Analysis of circRNA, lncRNA, miRNA and mRNA Expression Profiles and Their Competing Endogenous RNA Networks in Hepatitis B Virus-Related Hepatocellular Carcinoma.

Pursuing knowledge about circular RNA (circRNA), long non-coding RNA (lncRNA), microRNA (miRNA), and messenger RNA (mRNA) expression profiles and their competing endogenous RNA (ceRNA) networks in hepatitis B virus-related hepatocellular carcinoma (HBV-related HCC) was the focus of this research. Expression patterns of circRNAs, lncRNAs, miRNAs, and mRNAs were searched for in relation to HBV-related HCC using whole-transcriptome sequencing. The expression levels of chosen circRNA, lncRNA, miRNA, and mRNA were analyzed using quantitative reverse transcription-polymerase chain reaction (qRT-PCR). The potential connections and roles of ceRNA were deduced via bioinformatics research. The sum of 284 circRNAs, 2,927 lncRNAs, 693 miRNAs, and 5566 mRNAs were discovered to be expressed at considerably different levels in HBV-related HCC tissue and adjacent normal tissue. And the most significantly up- and down-regulated circRNAs, lncRNAs, miRNAs, and mRNAs were verified in HBV-related HCC by qRT-PCR. The circRNA/miRNA/mRNA and lncRNA/miRNA/mRNA networks of HBV-related HCC were established, and the ceRNA regulatory networks revealed the gene expression mechanisms controlled by ncRNAs. Collectively, we revealed the contribution of various circRNA, lncRNA, miRNA, and mRNA expression profiles and identified their ceRNA regulatory networks in HBV-related HCC, providing a theoretical basis for further exploration.

Identification of circRNA-associated ceRNA networks in the longissimus dorsi of yak under different feeding systems

BackgroundYaks (Bos grunniens), prized for their ability to thrive in high-altitude environments, are indispensable livestock in the plateau region. Modifying their feeding systems holds significant promise for improving their growth and meat quality. Tenderness, a key determinant of yak meat quality and consumer appeal, is demonstrably influenced by dietary regimen. Indoor feeding regimes have been shown to enhance tenderness by lowering shear stress and optimizing pH values. CircRNAs, well-known modulators of circulatory function, also play a crucial role in skeletal muscle development across various animal species. However, their functional significance in yak skeletal muscle remains largely unexplored.ResultsIn this study, we identified a total of 5,534 circRNAs within the longissimus dorsi muscle, and we found 51 differentially expressed circRNAs (20 up-regulated and 31 down-regulated) between the two feeding groups. Constructing a comprehensive ceRNA network illuminated intricate regulatory mechanisms, with PGP and circRNA_0617 converging on bta-miR-2285q, mirrored by KLF15/circRNA_0345/bta-miR-20b and CTSF/circRNA_0348/bta-miR-146a. These findings shed light on the potential of circRNAs to influence yak muscle development and meat quality, offering valuable insights for future research.ConclusionsThis investigation unraveled a complex interaction network between circRNAs、mRNAs and miRNAs in yak skeletal muscle. We further elucidated the target genes regulated by these target genes within the network, offering valuable insights into the potential regulatory mechanisms governing muscle development and meat quality-related traits in yaks.

Integrated analysis and validation of ferroptosis-related genes and immune infiltration in acute myocardial infarction

BackgroundAcute myocardial infarction (AMI) is indeed a significant cause of mortality and morbidity in individuals with coronary heart disease. Ferroptosis, an iron-dependent cell death, is characterized by the accumulation of intracellular lipid peroxides, which is implicated in cardiomyocyte injury. This study aims to identify biomarkers that are indicative of ferroptosis in the context of AMI, and to examine their potential roles in immune infiltration.MethodsFirstly, the GSE59867 dataset was used to identify differentially expressed ferroptosis-related genes (DE-FRGs) in AMI. We then performed gene ontology (GO) and functional enrichment analysis on these DE-FRGs. Secondly, we analyzed the GSE76591 dataset and used bioinformatic methods to build ceRNA networks. Thirdly, we identified hub genes in protein–protein interaction (PPI) network. After obtaining the key DE-FRGs through the junction of hub genes with ceRNA and least absolute shrinkage and selection operator (LASSO). ImmucellAI was applied to estimate the immune cell infiltration in each sample and examine the relationship between key DE-FRGs and 24 immunocyte subsets. The diagnostic performance of these genes was further evaluated using the receiver operating characteristic (ROC) curve analysis. Ultimately, we identified an immune-related ceRNA regulatory axis linked to ferroptosis in AMI.ResultsAmong 56 DE-FRGs identified in AMI, 41 of them were integrated into the construction of competitive endogenous RNA (ceRNA) networks. TLR4 and PIK3CA were identified as key DE-FRGs and PIK3CA was confirmed as a diagnostic biomarker for AMI. Moreover, CD4_native cells, nTreg cells, Th2 cells, Th17 cells, central-memory cells, effector-memory cells, and CD8_T cells had higher infiltrates in AMI samples compared to control samples. In contrast, exhausted cells, iTreg cells, and Tfh cells had lower infiltrates in AMI samples. Spearman analysis confirmed the correlation between 24 immune cells and PIK3CA/TLR4. Ultimately, we constructed an immune-related regulatory axis involving XIST and OIP5-AS1/miR-216a/PIK3CA.ConclusionOur comprehensive analysis has identified PIK3CA as a robust and promising biomarker for this condition. Moreover, we have also identified an immune-related regulatory axis involving XIST and OIP5-AS1/miR-216a/PIK3CA, which may play a key role in regulating ferroptosis during AMI progression.

Integrated analysis of circRNA- related ceRNA network targeting neuroinflammation in medial temporal lobe epilepsy

Backgroundmedial temporal lobe epilepsy (mTLE) is among the most common types of temporal lobe epilepsy (TLE) ，it is generally resistant to drug treatment, which significantly impacts the quality of life and treatment. Research on novel therapeutic approaches for mTLE has become a current focus. Our study aims to construct and analyze a competing endogenous RNA (ceRNA) network that targets neuroinflammation using publicly available data, which may offer a novel therapeutic approach for mTLE. Methodswe utilized the R package to analyze GSE186334 downloaded from Gene Expression Omnibus database, subsequently constructing and identifying hub network within the ceRNA network using public databases. Lastly, we validated the expressions and interactions of some nodes within the hub ceRNA network in Sombati cell model. Resultsour transcriptome analysis identified 649 differentially expressed (DE) mRNAs (273 up-regulated, 376 down-regulated) and 36 DE circRNAs (11 up-regulated, 25 down-regulated) among mTLE patients. A total of 23 candidate DE mRNAs associated with neuroinflammation were screened, and two ceRNA networks were constructed. A hub network was further screened which included 3 mRNAs, 22 miRNAs, and 11 circRNAs. Finally, we confirmed the hsa-miR-149–5p is crucial in the regulatory effect of hsa_circ_0005145 on IL - 1α in the hub network. ConclusionsIn summary, our study identified a hub ceRNA network and validated a potential circRNA-miRNA-mRNA axis targeting neuroinflammation. The results of our research may serve as a potential therapeutic target for mTLE.

Construction of an immune-related prognostic signature and lncRNA-miRNA-mRNA ceRNA network in acute myeloid leukemia.

The progression of acute myeloid leukemia (AML) is influenced by the immune microenvironment in the bone marrow and dysregulated intracellular competing endogenous RNA (ceRNA) networks. Our study utilized data from UCSC Xena, The Cancer Genome Atlas Program, the Gene Expression Omnibus, and the Immunology Database and Analysis Portal. Using Cox regression analysis, we identified an immune-related prognostic signature. Genomic analysis of prognostic messenger RNA (mRNA) was conducted through Gene Set Cancer Analysis (GSCA), and a prognostic ceRNA network was constructed using the Encyclopedia of RNA Interactomes. Correlations between signature mRNAs and immune cell infiltration, checkpoints, and drug sensitivity were assessed using R software, gene expression profiling interactive analysis (GEPIA), and CellMiner, respectively. Adhering to the ceRNA hypothesis, we established a potential long noncoding RNA (lncRNA)/microRNA (miRNA)/mRNA regulatory axis. Our findings pinpointed 9 immune-related prognostic mRNAs (KIR2DL1, CSRP1, APOBEC3G, CKLF, PLXNC1, PNOC, ANGPT1, IL1R2, and IL3RA). GSCA analysis revealed the impact of copy number variations and methylation on AML. The ceRNA network comprised 14 prognostic differentially expressed lncRNAs (DE-lncRNAs), 6 prognostic DE-miRNAs, and 3 prognostic immune-related DE-mRNAs. Correlation analyses linked these mRNAs' expression to 22 immune cell types and 6 immune checkpoints, with potential sensitivity to 27 antitumor drugs. Finally, we identified a potential LINC00963/hsa-miR-431-5p/CSRP1 axis. This study offers innovative insights for AML diagnosis and treatment through a novel immune-related signature and ceRNA axis. Identified novel biomarkers, including 2 mRNAs (CKLF, PNOC), 1 miRNA (hsa-miR-323a-3p), and 10 lncRNAs (SNHG25, LINC01857, AL390728.6, AC127024.5, Z83843.1, AP002884.1, AC007038.1, AC112512, AC020659.1, AC005921.3) present promising candidates as potential targets for precision medicine, contributing to the ongoing advancements in the field.

Identification and validation of NAD+ metabolism-related biomarkers in patients with diabetic peripheral neuropathy.

The mechanism of Nicotinamide Adenine Dinucleotide (NAD+) metabolism-related genes (NMRGs) in diabetic peripheral neuropathy (DPN) is unclear. This study aimed to find new NMRGs biomarkers in DPN. DPN related datasets GSE95849 and GSE185011 were acquired from the Gene Expression Omnibus (GEO) database. 51 NMRGs were collected from a previous article. To explore NMRGs expression in DPN and control samples, differential expression analysis was completed in GSE95849 to obtain differentially expressed genes (DEGs), and the intersection of DEGs and NMRGs was regarded as DE-NMRGs. Next, a protein-protein interaction (PPI) network based on DE-NMRGs was constructed and biomarkers were screened by eight algorithms. Additionally, Gene Set Enrichment Analysis (GSEA) enrichment analysis was completed, biomarker-based column line graphs were constructed, lncRNA-miRNA-mRNA and competing endogenouse (ce) RNA networks were constructed, and drug prediction was completed. Finally, biomarkers expression validation was completed in GSE95849 and GSE185011. 5217 DEGs were obtained from GSE95849 and 21 overlapping genes of DEGs and NMRGs were DE-NMRGs. Functional enrichment analysis revealed that DE-NMRGs were associated with glycosyl compound metabolic process. The PPI network contained 93 protein-interaction pairs and 21 nodes, with strong interactions between NMNAT1 and NAMPT, NADK and NMNAT3, ENPP3 and NUDT12 as biomarkers based on 8 algorithms. Expression validation suggested that ENPP3 and NUDT12 were upregulated in DPN samples (P < 0.05). Moreover, an alignment diagram with good diagnostic efficacy based on ENPP3 and NUDT12 were identified was constructed. GSEA suggested that ENPP3 was enriched in Toll like receptor (TLR) pathway, NUDT12 was enriched in maturity onset diabetes of the young and insulin pathway. Furthermore, 18 potential miRNAs and 36 Transcription factors (TFs) were predicted and the miRNA-mRNA-TF networks were constructed, suggesting that ENPP3 might regulate hsa-miR-34a-5p by affecting MYNN. The ceRNA network suggested that XLOC_013024 might regulate hsa-let-7b-5p by affecting NUDT12. 15 drugs were predicted, with 8 drugs affecting NUDT12 such as resveratrol, and 13 drugs affecting ENPP3 such as troglitazone. ENPP3 and NUDT12 might play key roles in DPN, which provides reference for further research on DPN.

Whole-transcriptome sequence analysis of pumpkin ovules in response to heat shock during unfertilized ovary culture

Unfertilized ovary culture is one of the most effective approaches to induce haploids in Cucurbitaceae. Previous studies have greatly contributed to inducing more and better haploids, but there has been less contribution to the mechanism involved. Our previous research established efficient haploid regeneration protocol of unfertilized ovary culture and found that heat shock can effectively promote ELSs’ induction. In this study, firstly, we accurately calculated the contribution of heat shock to ELSs’ induction via unfertilized ovary culture of pumpkin, and then performed whole-transcriptome sequence using “Yi-Chuan-Ling 4″, which is more sensitive to heat shock and has a higher induction rate. The results show that heat shock treatment was obviously beneficial to the unfertilized ovary culture of pumpkin, and the average induction rate in the treatment group (35°C,5d) was 26.6 times higher than in the control group (25°C,5d) . Through whole-transcriptome sequencing, we obtained 4579 differentially expressed (DE) RNAs, including 3133 mRNAs, 120 lncRNAs, 814 circRNAs, and 512 miRNAs. GO annotation analysis showed that DEmRNAs were associated with cellular processes, metabolic processes, biological regulation, response to stimulus, and so on. The ceRNA network was constructed using differential expressed RNAs. It captured the gene MSTRG.28850.1, which was related to embryogenesis and regulated by miRNA Nov-m0336–5 p. In conclusion, these findings might provide an important reference for mechanism research regarding embryogenesis induction and accelerate the application of unfertilized ovary/ovule culture in Cucurbita breeding.

LncRNA-miRNA-mRNA network in kidney transcriptome of Labeo rohita under hypersaline environment

The present study describes the kidney transcriptome of Labeo rohita, a freshwater fish, exposed to gradually increased salinity concentrations (2, 4, 6 and 8ppt). A total of 10.25 Gbps data was generated, and a suite of bioinformatics tools, including FEELnc, CPC2 and BLASTn were employed for identification of long non-coding RNAs (lncRNAs) and micro RNAs (miRNAs). Our analysis revealed a total of 170, 118, 99, and 269 differentially expressed lncRNA and 120, 118, 99, and 124 differentially expressed miRNAs in 2, 4, 6 and 8 ppt treatment groups respectively. Two competing endogenous RNA (ceRNA) networks were constructed i.e. A* ceRNA network with up-regulated lncRNAs and mRNAs, down-regulated miRNAs; and B* ceRNA network vice versa. 2ppt group had 131 and 83 lncRNA-miRNA-mRNA pairs in A* and B* networks, respectively. 4ppt group featured 163 pairs in A* network and 191 in B* network, while the 6ppt had 103 and 105 pairs. 8ppt group included 192 and 174 pairs. These networks illuminate the intricate RNA interactions in freshwater fish to varying salinity conditions.

Noncoding RNA-associated competing endogenous RNA networks in trastuzumab-induced cardiotoxicity

Trastuzumab-induced cardiotoxicity (TIC) is a common and serious disease with abnormal cardiac function. Accumulating evidence has indicated certain non-coding RNAs (ncRNAs), functioning as competing endogenous RNAs (ceRNAs), impacting the progression of cardiovascular diseases. Nonetheless, the specific involvement of ncRNA-mediated ceRNA regulatory mechanisms in TIC remains elusive. The present research aims to comprehensively investigate changes in the expressions of all ncRNA using whole-transcriptome RNA sequencing. The sequencing analysis unveiled significant dysregulation, identifying a total of 43 circular RNAs (circRNAs), 270 long noncoding RNAs (lncRNAs), 12 microRNAs (miRNAs), and 4131 mRNAs in trastuzumab-treated mouse hearts. Subsequently, circRNA-based ceRNA networks consisting of 82 nodes and 91 edges, as well as lncRNA-based ceRNA networks comprising 111 nodes and 112 edges, were constructed. Using the CytoNCA plugin, pivotal genes—miR-31-5p and miR-644-5p—were identified within these networks, exhibiting potential relevance in TIC treatment. Additionally, KEGG and GO analyses were conducted to explore the functional pathways associated with the genes within the ceRNA networks. The outcomes of the predicted ceRNAs and bioinformatics analyses elucidated the plausible involvement of ncRNAs in TIC pathogenesis. This insight contributes to a better understanding of underlying mechanisms and aids in identifying promising targets for effective prevention and treatment strategies.

Screening and bioinformatics analysis of a potential ceRNA network in melatonin-induced cashmere growth in Liaoning cashmere goats

Abstract. The purpose of this study was to investigate the effect of melatonin (MT) on the expression patterns of lncRNA, mRNA and miRNA in Liaoning cashmere goat (LCG) skin fibroblasts. A quantity of 200 ng L−1 MT (MT group) stimulated LCG skin fibroblasts for 48 h, and RNA sequencing was conducted with the control group (Con group) (n=3). The ceRNA network was constructed by bioinformatics analysis of the sequencing data and transmission electron microscopy observation of coated pits and endocytic vesicles. In this study, the results indicated that MT treatment significantly facilitated the proliferation of LCG skin fibroblasts and increased the number of coated pits and vesicles. A total of 775 mRNAs, 57 lncRNAs and 10 miRNAs had differential expression, as indicated by RNA sequencing of skin fibroblasts administrated on the MT group and Con group. The regulatory network of ceRNA was studied, and the results suggested that inositol phosphate metabolism, the cGMP–PKG signaling pathway, endocytosis and other pathways played a certain role in the growth and development of the LCG cashmere. Moreover, the key genes (e.g., CREB1, PIK3C3, AGAP3, MEF2A, ASAP2, IRAG1, PNISR, PIP5K1A, SRSF11, ZRANB2, RBM39 and CBL) were regulated by chi-miR-34c-5p, chi-miR-34c-3p and chi-miR-195-5p. The above mRNAs were competitively bound by 15 lncRNAs (e.g., MSTRG.28630.12, MSTRG.28660.14, MSTRG.28099.7). And through dual luciferase and other experiments, it was further confirmed that PIP5K1A is the target gene of miR-34c-5p. This finding provides new insights into the molecular mechanism by which melatonin promotes villi growth in cashmere.

Identification of functional genes in liver fibrosis based on bioinformatics analysis of a lncRNA-mediated ceRNA network

BackgroundLiver fibrosis is a major global healths problem; nevertheless, its molecular mechanism are not completely clear. This study aimed to build a lncRNA-miRNA-mRNA network, identify potentially related lncRNAs, and explore the pathogenesis of liver fibrosis.Materials and methodsWe used the Gene Expression Omnibus databases and bioinformatics analysis to identify differentially expressed genes (DEGs) between liver fibrosis and normal tissues. The ceRNA network was constructed according to the interactions between DElncRNA, miRNA, and DEmRNA. Then, these DEGs were identified using functional enrichment analysis, and a protein–protein interaction (PPI) network was established. The critical lncRNAs were verified using the quantitative real-time polymerase chain reaction (qRT-PCR).ResultsThe ceRNA network was composed of three lncRNAs, five miRNAs, and 93 mRNAs. Gene Ontology functional enrichment analysis revealed significant enhancement in cell components, molecular function, and biological process. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed pathways associated with transcriptional misregulation in cancer, including the Rap1 signaling pathway, proteoglycans in cancer, mineral absorption, HTLV-l infection, and central carbon metabolism in cancer. According to the PPI network and the GSE84044 database, seven hub genes associated with liver fibrosis were identified. In addition, qRT-PCR revealed that lncRNA AC100861 (lncRNA TNFRSF10A-DT) was explicitly decreased in liver fibrosis tissues and activated hepatic stellate cells.ConclusionsIn summary, this study preliminarily found that lncRNA TNFRSF10A-DT may be a biomarker for the diagnosis and outcome of liver fibrosis. We uncovered a novel lncRNA-mediated ceRNA regulatory mechanism in the pathogenesis of liver fibrosis.