Comprehensive bioinformatics analysis reveals the hub genes and pathways in a mouse model of Pierpont Syndrome
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE246719 | GEO | 2025/10/31
REPOSITORIES: GEO
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Project description:Unravelling molecular defects resulting from the missense mutation in TBL1XR1 using targeted mutant mice bearing the Tbl1xr1 Y446C/Y446C mutation. These mice used as an animal model of Pierpont syndrome have disturbed hearing and subtle changes in fat metabolism. RNA seq of white adipose tissue has been performed to establish the transcriptome.
2022-09-14 | GSE198787 | GEO
Project description:Osteoarthritis (OA) is a progressive cartilage degradation disease, concomitant with synovitis, osteophyte formation, and subchondral bone sclerosis. Over 37% of the elderly population is affected by OA, and the number of cases is increasing as the global population ages. Therefore, the objective of this study was to identify and analyze the hub genes of OA combining with comprehensive bioinformatics analysis tools to provide theoretical basis in further OA effective therapies. Two sample sets of GSE46750 contained 12 pairs OA synovial membrane and normal samples harvested from patients as well as GSE98918 including 12 OA and non-OA patients were downloaded from the Gene Expression Omnibus database (GEO) database. Differentially expressed genes (DEGs) were identified using Gene Expression Omnibus 2R (GEO2R), followed by functional enrichment analysis, protein-protein interaction networks construction. The hub genes were identified and evaluated. An OA rat model was constructed, hematoxylin and eosin staining, safranin O/fast green staining, cytokines concentrations of serum were used to verify the model. The hub genes expression level in the knee OA samples were verified using RT-qPCR. The top 20 significantly up-regulated and down-regulated DEGs were screened out from the two datasets, respectively. The top 18 GO terms and 10 KEGG pathways were enriched. Eight hub genes were identified, namely MS4A6A, C1QB, C1QC, CD74, CSF1R, HLA-DPA1, HLA-DRA and ITGB2. Among them, the hub genes were all up-regulated in in vivo OA rat model, compared with healthy controls. The eight hub genes identified (MS4A6A, C1QB, C1QC, CD74, CSF1R, HLA-DPA1, HLA-DRA and ITGB2) were shown to be associated with OA. These genes can serve as disease markers to discriminate OA patients from healthy controls.
| S-EPMC10739719 | biostudies-literature
Project description:Background Osteoarthritis (OA) is the most common type of arthritis. OA can cause joint pain, stiffness, and loss of function. The pathogenesis of OA is not completely clear. Moreover, there is no effective treatment, and clinical management is limited to symptomatic relief or joint surgery. This study utilized bioinformatics to analyze normal and OA articular cartilage samples to find biomarkers and therapeutic targets for OA. Methods The GSE169077 gene chip dataset was downloaded from the public gene chip data platform of the National Biotechnology Information Center. The dataset included 6 samples of OA tissues and 5 samples of healthy cartilage tissues. Differentially expressed genes (DEGs) were screened using the R language “limma” function package under the threshold of log2[fold change (FC)] ≥2 and a P value <0.05. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) signal pathways of the target genes were enriched and analyzed using the database for annotation, visualization, and integrated discovery (DAVID), and a protein-protein interaction (PPI) network was further constructed using the search tool for the retrieval of interacting genes/proteins (STRING) database. The coexpression relationship of the genes in the module was visualized and screened with Cytoscape. Results A total of 27 DEGs were identified, including 9 downregulated genes and 18 upregulated genes. GO signal pathway enrichment analysis showed involvement in hypoxic response, fibrous collagen trimer, and extracellular matrix structural components. KEGG analysis demonstrated associations with protein digestion and absorption, extracellular matrix receptor interaction, and the peroxisome proliferator-activated receptor signal pathway, among several other pathways. A PPI network was obtained through STRING analysis, and the results were imported into Cytoscape software. The 27 DEGs were sequenced by the cytoHubba plug-in by various calculation methods, and 5 hub genes (COL1A1, COL1A2, POSTN, BMP1, and MMP13) were finally selected. These genes were analyzed by PPI again and annotated with GO and KEGG in different colors. Conclusions Bioinformatics technology effectively identified differential genes in the knee cartilage tissue of healthy controls and patients with OA, providing opportunities to further explore the mechanism and treatment of OA on a transcriptional level.
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Project description:Our spatiotemporal data confirmed activation of Tbl1xr1 in hepatocytes after 2/3 hepatectomy. TBL1XR1 is a transcriptional cofactor inducing ubiquitination and degradation of NCoR/SMRT co-repressors and NCoR is a negative regulator of hepatocyte proliferation acting through histone deacetylases (HDACs). We have examined the role of TBL1XR1 in liver regeneration through in vivo shRNA knockdown using adeno-associated viruses (shNC and shTbl1xr1) specifically targeting hepatocytes. The knockdown of Tbl1xr1 results in impair hepatocyte proliferation.To investigate the downstream targets of TBL1XR1 during liver regenration, we here perform the bulk RNA-seq for shNC and shTbl1xr1 at D2 after hepatectomy. Our data show demonstrated that Tbl1xr1 knockdown not only led to reduced cell cycle genes but also to impaired fatty acid β-oxidation as the most obviously affected liver function.
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Project description:In order to investigate whether carriers of BRCA1 heterozygous mutation show altered miRNA expression profiles, we established a panel of lymphoblastoid cell lines (LCLs) harboring either mutated or WT BRCA1 (control) and investigated their miRNA expression profiles. We were especially interested whether we find differences in miRNA expression between carriers of missense versus truncating mutation in BRCA1 gene. We evaluated the miRNA expression in a panel of 21 non-treated lymphoblastoid cell lines (LCLs). Among them, 6 LCLs with WT BRCA1, 5 LCLs carrying missense mutation in BRCA1, and 10 LCLs harboring truncating mutation in BRCA1 were included in this study.
2015-12-31 | E-GEOD-60444 | biostudies-arrayexpress
Project description:In order to investigate whether carriers of BRCA1 heterozygous mutation show altered gene expression profiles, we used a whole genome microarray expression profiling of a panel of lymphoblastoid cell lines (LCLs) harboring either mutated or WT BRCA1 (control). We were especially interested whether we find differences in gene expression between carriers of missense versus truncating mutation in BRCA1 gene. We evaluated gene expression of a panel of 21 non-treated lymphoblastoid cell lines (LCLs). Among them, 6 LCLs with WT BRCA1, 5 LCLs carrying missense mutation in BRCA1, and 10 LCLs harboring truncating mutation in BRCA1 were included in this study.
2015-12-31 | E-GEOD-60396 | biostudies-arrayexpress
Project description:Enlarged vestibular aqueducts (EVA) is one of the most commonly identified inner ear malformations in hearing loss patients including Pendred syndrome. While biallelic mutations of the SLC26A4 gene, encoding pendrin, causes non-syndromic hearing loss with EVA or Pendred syndrome, a considerable number of patients appear to carry mono-allelic mutation. This suggests faulty pendrin regulatory machinery results in hearing loss. Here we identify EPHA2 as another causative gene of Pendred syndrome with SLC26A4. EphA2 forms a protein complex with pendrin controlling pendrin localization, which is disrupted in some pathogenic forms of pendrin. Moreover, point mutations leading to amino acid substitution in the EPHA2 gene are identified from patients bearing mono-allelic mutation of SLC26A4. Ephrin-B2 binds to EphA2 triggering internalization with pendrin inducing EphA2 autophosphorylation weakly. The identified EphA2 mutants attenuate ephrin-B2- but not ephrin-A1-induced EphA2 internalization with pendrin. Our results uncover an unexpected role of the Eph/ephrin system in epithelial function.
2020-04-22 | PXD017011 | Pride
Project description:An improved understanding of the molecular mechanism of colorectal adenocarcinoma is necessary to predict the prognosis and develop new target gene therapy strategies. This study aims to identify hub genes associated with colorectal adenocarcinoma and further analyze their prognostic significance. In this study, The Cancer Genome Atlas (TCGA) COAD-READ database and the gene expression profiles of GSE25070 from the Gene Expression Omnibus were collected to explore the differentially expressed genes between colorectal adenocarcinoma and normal tissues. The weighted gene co-expression network analysis (WGCNA) and differential expression analysis identified 82 differentially co-expressed genes in the collected datasets. Enrichment analysis was applied to explore the regulated signaling pathway in colorectal adenocarcinoma. In addition, 10 hub genes were identified in the protein-protein interaction (PPI) network by using the cytoHubba plug-in of Cytoscape, where five genes were further proven to be significantly related to the survival rate. Compared with normal tissues, the expressions of the five genes were both downregulated in the GSE110224 dataset. Subsequently, the expression of the five hub genes was confirmed by the Human Protein Atlas database. Finally, we used Cox regression analysis to identify genes associated with prognosis, and a 3-gene signature (CLCA1-CLCA4-GUCA2A) was constructed to predict the prognosis of patients with colorectal cancer. In conclusion, our study revealed that the five hub genes and CLCA1-CLCA4-GUCA2A signature are highly correlated with the development of colorectal adenocarcinoma and can serve as promising prognosis factors to predict the overall survival rate of patients.
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Project description:Spermatogenesis is a complex process related to male infertility. Till now, the critical genes and specific mechanisms have not been elucidated clearly. Our objective was to determine the hub genes that play a crucial role in spermatogenesis by analyzing the differentially expressed genes (DEGs) present in non-obstructive azoospermia (NOA) compared to OA and normal samples using bioinformatics analysis. Four datasets, namely GSE45885, GSE45887, GSE9210 and GSE145467 were used. Functional enrichment analyses were performed on the DEGs. Hub genes were identified based on protein-protein interactions between DEGs. The expression of the hub genes was further examined in the testicular germ cell tumors from the TCGA by the GEPIA and validated by qRT-PCR in the testes of lipopolysaccharide-induced acute orchitis mice with impaired spermatogenesis. A total of 203 DEGs including 34 up-regulated and 169 down-regulated were identified. Functional enrichment analysis showed DEGs were mainly involved in microtubule motility, the process of cell growth and protein transport. PRM2, TEKT2, FSCN3, UBQLN3, SPATS1 and GTSF1L were identified and validated as hub genes for spermatogenesis. Three of them (PRM2, FSCN3 and TEKT2) were significantly down-regulated in the testicular germ cell tumors and their methylation levels were associated with the pathogenesis. In summary, the hub genes identified may be related to spermatogenesis and may act as potential therapeutic targets for NOA and testicular germ cell tumors.
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