Regulatory network of miRNA, lncRNA, transcription factor and target immune response genes in bovine mastitis
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ABSTRACT:
SUBMITTER: Tucker A
PROVIDER: S-EPMC8578396 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundTranscription factors (TFs) play a crucial role in the occurrence and progression of lung adenocarcinoma (LUAD), and targeting TFs is an important direction for treating LUAD. However, targeting a single TF often fails to achieve satisfactory therapeutic outcomes. Furthermore, the regulatory TF-target gene networks involved in the development of LUAD is complex and not yet fully understood.MethodsIn this study, we performed RNA sequencing (RNA-seq) to analyze the transcriptome profile of human LUAD tissues and matched adjacent nontumor tissues. We selected the differentially expressed TFs, performed enrichment analysis and survival curve analysis, and predicted the regulatory networks of the top differential TFs with their target genes. Finally, alternative splicing analyses were also performed.ResultsWe found that TFs GRHL3, SIX1, SIX2, SPDEF, and ETV4 were upregulated, while TAL1, EPAS1, SOX17, NR4A1, and EGR3 were significantly downregulated in LUAD tissues compared to normal tissues. We propose a potential GRHL3-CDH15-Wnt-β-catenin pro-oncogenic signaling axis and a potential TAL1-ADAMTS1-vascular antioncogenic signaling axis. In addition, we found that alternative splicing of intron retention (IR), approximate IR (XIR), multi-IR (MIR), approximate MIR (XMIR), and approximate alternative exon ends (XAE) showed abnormally increased frequencies in LUAD tissues.ConclusionsThese findings revealed a novel TF-target gene regulatory axis related to tumorigenesis and provided potential therapeutic targets and mechanisms for LUAD.
| S-EPMC10797383 | biostudies-literature
Project description:Aimwe aimed to construct a bioinformatics-based co-regulatory network of mRNAs and non coding RNAs (ncRNAs), which is implicated in the pathogenesis of non-alcoholic fatty liver disease (NAFLD), followed by its validation in a NAFLD animal model.Materials and methodsThe mRNAs-miRNAs-lncRNAs regulatory network involved in NAFLD was retrieved and constructed utilizing bioinformatics tools. Then, we validated this network using an NAFLD animal model, high sucrose and high fat diet (HSHF)-fed rats. Finally, the expression level of the network players was assessed in the liver tissues using reverse transcriptase real-time polymerase chain reaction.Resultsin-silico constructed network revealed six mRNAs (YAP1, FOXA2, AMOTL2, TEAD2, SMAD4 and NF2), two miRNAs (miR-650 and miR-1205), and two lncRNAs (RPARP-AS1 and SRD5A3-AS1) that play important roles as a co-regulatory network in NAFLD pathogenesis. Moreover, the expression level of these constructed network-players was significantly different between NAFLD and normal control. Conclusion and future perspectives: this study provides new insight into the molecular mechanism of NAFLD pathogenesis and valuable clues for the potential use of the constructed RNA network in effective diagnostic or management strategies of NAFLD.
| S-EPMC8269036 | biostudies-literature
Project description:PurposeNasopharyngeal carcinoma (NPC) is one of the most common malignant tumors of the head and neck. This study aimed to investigate the crucial genes and regulatory networks involved in the carcinogenesis of NPC using a bioinformatics approach.MethodsFive mRNA and two miRNA expression datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and miRNAs (DEMs) between NPC and normal samples were analyzed using R software. The WebGestalt tool was used for functional enrichment analysis, and protein-protein interaction (PPI) network analysis of DEGs was performed using STRING database. Transcription factors (TFs) were predicted using TRRUST and Transcriptional Regulatory Element Database (TRED). Kinases were identified using X2Kgui. The miRNAs of DEGs were predicted using miRWalk database. A kinase-TF-mRNA-miRNA integrated network was constructed, and hub nodes were selected. The hub genes were validated using NPC datasets from the GEO and Oncomine databases. Finally, candidate small-molecule agents were predicted using CMap.ResultsA total of 122 DEGs and 44 DEMs were identified. DEGs were associated with the immune response, leukocyte activation, endoplasmic reticulum stress in GO analysis, and the NF-κB signaling pathway in KEGG analysis. Four significant modules were identified using PPI network analysis. Subsequently, 26 TFs, 73 kinases, and 2499 miRNAs were predicted. The predicted miRNAs were cross-referenced with DEMs, and seven overlapping miRNAs were selected. In the kinase-TF-mRNA-miRNA integrated network, eight genes (PTGS2, FN1, MMP1, PLAU, MMP3, CD19, BMP2, and PIGR) were identified as hub genes. Hub genes were validated with consistent results, indicating the reliability of our findings. Finally, six candidate small-molecule agents (phenoxybenzamine, luteolin, thioguanosine, reserpine, blebbistatin, and camptothecin) were predicted.ConclusionWe identified DEGs and an NPC regulatory network involving kinases, TFs, mRNAs, and miRNAs, which might provide promising insight into the pathogenesis, treatment, and prognosis of NPC.
| S-EPMC8566004 | biostudies-literature
Project description:Coronaviruses are RNA viruses that cause significant disease within many species, including cattle. Bovine coronavirus (BCoV) infects cattle and wild ruminants, both as a respiratory and enteric pathogen, and possesses a significant economic threat to the cattle industry. Transcription factors are proteins that activate or inhibit transcription through DNA binding and have become new targets for disease therapies. This study utilized in silico tools to identify potential transcription factors that can serve as biomarkers for regulation of BCoV pathogenesis in cattle, both for testing and treatment. A total of 11 genes were identified as significantly expressed during BCoV infection through literature searches and functional analyses. Eleven transcription factors were predicted to target those genes (AREB6, YY1, LMO2, C-Rel, NKX2-5, E47, RORAlpha1, HLF, E4BP4, ARNT, CREB). Function, network, and phylogenetic analyses established the significance of many transcription factors within the immune response. This study establishes new information on the transcription factors and genes related to host-pathogen interactome in BCoV infection, particularly transcription factors YY1, AREB6, LMO2, and NKX2, which appear to have strong potential as diagnostic markers, and YY1 as a potential target for drug therapies.
| S-EPMC7564962 | biostudies-literature
Project description:Colorectal cancer (CRC) is a malignant tumor with high morbidity and mortality worldwide. Recent studies have shown that long noncoding RNAs (lncRNAs) play an important role in almost all human tumors, including CRC. Competitive endogenous RNA (ceRNA) regulatory networks have become hot topics in cancer research. Tumor-infiltrating immune cells (TICs) have also been reported to be closely related to the survival and prognosis of CRC patients. In this study, we used the lncRNA-miRNA-mRNA regulatory network combined with tumor immune cell infiltration to predict the survival and prognosis of 598 CRC patients. First, we downloaded the lncRNA, mRNA, and miRNA transcriptome data of CRC patients from The Cancer Genome Atlas (TCGA) database and identified differentially expressed genes through "limma" package of R software. The ceRNA regulatory network was established by using the "GDCRNATools" R package. Then, univariate Cox analysis and least absolute shrinkage and selection operator analysis were performed to identify the optimal prognostic network nodes, including SRPX, UST, H19, SNHG7, hsa-miR-29b-3p, and TTYH3. Next, we analyzed the differences in 22 types of TICs between 58 normal subjects and 206 CRC patients and included memory CD4 T cells, dendritic cells and neutrophils in the construction of a prognostic model. Finally, we identified the relationship between the ceRNA prognostic model and the infiltrating immune cell prognostic model. In conclusion, we constructed two prognostic models that provide insights on the prognosis and treatment strategy of CRC.
| S-EPMC8281064 | biostudies-literature
Project description:BACKGROUND:Primary open angle glaucoma (POAG) is a multifactorial disorder characterized by a progressive permanent degeneration of retinal ganglion cell (RGCs) death. An increasing number of studies have suggested that long noncoding RNAs (lncRNAs) have the ability to regulate gene expression; however, thus far, the mechanisms and functions of lncRNAs in the development of POAG are still unclear. METHODS:Using the data from Gene Expression Omnibus (GEO), differentially expressed lncRNAs and differentially expressed mRNAs between POAG patients and controls were identified. Then, the lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network was constructed, and the key lncRNAs in POAG were identified. A Gene Ontology (GO) analysis and a Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to assess the enriched biological functions of mRNA in the ceRNA network. RESULTS:During this study, a POAG-related ceRNA network with 37 miRNA nodes, 248 lncRNA nodes, 178 mRNA nodes, and 1985 edges was constructed. In addition, four lncRNAs (DNAJC27-AS1, AF121898, OIP5-AS1, and SNX29P2) were established as hub RNAs in this ceRNA network. The functional assay showed that 18 GO terms and 17 pathways were enriched. CONCLUSION:This study provides novel insights into the lncRNA-related ceRNA network in POAG, and the four lncRNAs were identified in the development of POAG.
| S-EPMC7076920 | biostudies-literature
Project description:Purpose:This research explores the aberrant expression of the long non-coding RNA (lncRNA), microRNA (miRNA), and messenger RNA (mRNA) in pterygium. A competitive endogenous RNA (ceRNA) network was constructed to elucidate the molecular mechanisms in pterygium. Methods:We obtained the differentially expressed mRNAs based on three datasets (GSE2513, GSE51995, and GSE83627), and summarized the differentially expressed miRNAs (DEmiRs) and differentially expressed lncRNAs (DELs) data by published literature. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, protein-protein interaction (PPI), and gene set enrichment analysis (GSEA) analysis were performed. DEmiRs were verified in GSE21346, and the regulatory network of hub mRNAs, DELs, and DEmiRs were constructed. Results:Overall, 40 upregulated and 40 downregulated differentially expressed genes (DEGs) were obtained. The KEGG enrichment showed the DEGs mainly involved in extracellular matrix (ECM)-receptor interaction, focal adhesion, and PI3K-Akt signaling pathway. The GSEA results showed that cornification, keratinization, and cornified envelope were significantly enriched. The validation outcome confirmed six upregulated DEmiRs (miR-766-3p, miR-184, miR-143-3p, miR-138-5p, miR-518b, and miR-1236-3p) and two downregulated DEmiRs (miR-200b-3p and miR-200a-3p). Then, a ceRNA regulatory network was constructed with 22 upregulated and 15 downregulated DEmiRs, 4 downregulated DELs, and 26 upregulated and 33 downregulated DEGs. The network showed that lncRNA SNHG1/miR-766-3p/FOS and some miRNA-mRNA axes were dysregulated in pterygium. Conclusions:Our study provides a novel perspective on the regulatory mechanism of pterygium, and lncRNA SNHG1/miR-766-3p/FOS may contribute to pterygium development.
| S-EPMC7425729 | biostudies-literature
Project description:There is growing evidence that non-coding RNAs are emerging as critical regulators of skeletal muscle development. In order to reveal their functional roles and regulatory mechanisms, we constructed a lncRNA-miRNA-mRNA network according to the ceRNA (competitive endogenous RNA) theory, using our high-throughput sequencing data. Subsequently, the network analysis, GO (Gene Ontology) analysis, and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis were performed for functional annotation and exploration of lncRNA ceRNAs. The results uncovered a scale-free characteristics network which exhibited high functional specificity for bovine skeletal muscle development: co-expression lncRNAs were significantly enriched in muscle development related biological processes and the Wnt signaling pathway. Furthermore, GSEA (Gene Set Enrichment Analysis) indicated that the risk score has a tendency to associate with myogenesis, and differentially expressed RNAs were validated by qPCR, further confirming the credibility of our network. In summary, this study provides insights into lncRNA-mediated ceRNA function and mechanisms in bovine skeletal muscle development and will expand our understanding of lncRNA biology in mammals.
| S-EPMC6391848 | biostudies-literature
Project description:Hepatocellular carcinoma (HCC) is one of the most common malignant diseases globally. Despite continuous improvement of treatment methods, high postoperative recurrence rate remains an urgent problem. In order to determine the mechanism underlying recurrence of liver cancer and identify prognostic genes, data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) were integrated and analyzed. Differentially expressed genes (DEGs) between HCC tissue and normal liver tissue were identified, and a protein-protein interaction network was constructed to find hub genes. Clinical correlation analysis and disease-free survival (DFS) analysis were performed using the R language and GEPIA to identify relapse-related genes. Correlation analysis was used to identify a potential regulatory axis. Dual-luciferase reporter gene assay was used to confirm the reliability of the long non-coding RNA (lncRNA)-microRNA (miRNA)-mRNA regulatory axis. Immune infiltration analysis was performed using the TIMER database. Correlations between immune gene markers and ASF1B were verified using quantitative real-time polymerase chain reaction (RT-qPCR). In this work, we found that nine lncRNAs and five mRNAs were significantly overexpressed in HCC tissues from patients with recurrence. SNHG3, LINC00205, ASF1B, AURKB, CCNB1, CDKN3, and DTL were also closely related to HCC grade and stage. Survival analysis showed that these seven DEGs were significantly correlated with poor DFS. Correlation analysis identified SNHG3-miR-214-3p-ASF1B as a potential regulatory axis. Dual-luciferase reporter gene assay showed that SNHG3 and ASF1B directly bound to miR-214-3p. ASF1B was negatively regulated by miRNA-214-3p, and overexpression of SNHG3 could inhibit the expression of miRNA-214-3p. In addition, ASF1B was positively correlated with immune infiltration. A reduction in ASF1B could markedly inhibit the expression of CD86, CD8, STAT1, STAT4, CD68, and PD1 in HCC cells. Flow cytometry showed that SNHG3 promoted the PD-1 expression by regulating ASF1B. Meanwhile, elevated ASF1B predicted poor prognosis of HCC patients in subgroups with decreased B cells, CD8+ T cells, or neutrophils, and those with enriched CD4+ T cells. In conclusion, we found that a novel lncRNA SNHG3/miR-214-3p/ASF1B axis could promote the recurrence of HCC by regulating immune infiltration.
| S-EPMC8320021 | biostudies-literature
Project description:Progenitor differentiation requires remodeling of genomic expression; however, in many tissues, such as epidermis, the spectrum of remodeled genes and the transcription factors (TFs) that control them are not fully defined. We performed kinetic transcriptome analysis during regeneration of differentiated epidermis and identified gene sets enriched in progenitors (594 genes), in early (159 genes), and in late differentiation (387 genes). Module mapping of 1,046 TFs identified MAF and MAFB as necessary and sufficient for progenitor differentiation. MAF:MAFB regulated 393 genes altered in this setting. Integrative analysis identified ANCR and TINCR lncRNAs as essential upstream MAF:MAFB regulators. ChIP-seq analysis demonstrated MAF:MAFB binding to known epidermal differentiation TF genes whose expression they controlled, including GRHL3, ZNF750, KLF4, and PRDM1. Each of these TFs rescued expression of specific MAF:MAFB target gene subsets in the setting of MAF:MAFB loss, indicating they act downstream of MAF:MAFB. A lncRNA-TF network is thus essential for epidermal differentiation.
| S-EPMC4456036 | biostudies-literature