Dataset Information

Identification of Genes Associated with Smad3-dependent Renal Injury by RNA-seq-based Transcriptome Analysis.

ABSTRACT: Transforming growth factor-?/Smad3 signaling plays a critical role in the process of chronic kidney disease (CKD), but targeting Smad3 systematically may cause autoimmune disease by impairing immunity. In this study, we used whole-transcriptome RNA-sequencing to identify the differential gene expression profile, gene ontology, pathways, and alternative splicing related to TGF-?/Smad3 in CKD. To explore common dysregulation of genes associated with Smad3-dependent renal injury, kidney tissues of Smad3 wild-type and knockout mice with immune (anti-glomerular basement membrane glomerulonephritis) and non-immune (obstructive nephropathy)-mediated CKD were used for RNA-sequencing analysis. Totally 1922 differentially expressed genes (DEGs) were commonly found in these CKD models. The up-regulated genes are inflammatory and immune response associated, while decreased genes are material or electron transportation and metabolism related. Only 9 common DEGs were found to be Smad3-dependent in two models, including 6 immunoglobulin genes (Ighg1, Ighg2c, Igkv12-41, Ighv14-3, Ighv5-6 and Ighg2b) and 3 metabolic genes (Ugt2b37, Slc22a19, and Mfsd2a). Our results identify transcriptomes associated with renal injury may represent a common mechanism for the pathogenesis of CKD and reveal novel Smad3 associated transcriptomes in the development of CKD.

SUBMITTER: Zhou Q

PROVIDER: S-EPMC4673424 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of Genes Associated with Smad3-dependent Renal Injury by RNA-seq-based Transcriptome Analysis.

Zhou Qin Q Xiong Yuanyan Y Huang Xiao R XR Tang Patrick P Yu Xueqing X Lan Hui Y HY

Scientific reports 20151209

Transforming growth factor-β/Smad3 signaling plays a critical role in the process of chronic kidney disease (CKD), but targeting Smad3 systematically may cause autoimmune disease by impairing immunity. In this study, we used whole-transcriptome RNA-sequencing to identify the differential gene expression profile, gene ontology, pathways, and alternative splicing related to TGF-β/Smad3 in CKD. To explore common dysregulation of genes associated with Smad3-dependent renal injury, kidney tissues of ...[more]

PMID: 26648110

Similar Datasets

Project description:BACKGROUND:Fluralaner is a novel isoxazoline insecticide with a unique action site on the γ-aminobutyric acid receptor (GABAR), shows excellent activity on agricultural pests including the common cutworm Spodoptera litura, and significantly influences the development and fecundity of S. litura at either lethal or sublethal doses. Herein, Illumina HiSeq Xten (IHX) platform was used to explore the transcriptome of S. litura and to identify genes responding to fluralaner exposure. RESULTS:A total of 16,572 genes, including 451 newly identified genes, were observed in the S. litura transcriptome and annotated according to the COG, GO, KEGG and NR databases. These genes included 156 detoxification enzyme genes [107 cytochrome P450 enzymes (P450s), 30 glutathione S-transferases (GSTs) and 19 carboxylesterases (CarEs)] and 24 insecticide-targeted genes [5 ionotropic GABARs, 1 glutamate-gated chloride channel (GluCl), 2 voltage-gated sodium channels (VGSCs), 13 nicotinic acetylcholine receptors (nAChRs), 2 acetylcholinesterases (AChEs) and 1 ryanodine receptor (RyR)]. There were 3275 and 2491 differentially expressed genes (DEGs) in S. litura treated with LC30 or LC50 concentrations of fluralaner, respectively. Among the DEGs, 20 related to detoxification [16 P450s, 1 GST and 3 CarEs] and 5 were growth-related genes (1 chitin and 4 juvenile hormone synthesis genes). For 26 randomly selected DEGs, real-time quantitative PCR (RT-qPCR) results showed that the relative expression levels of genes encoding several P450s, GSTs, heat shock protein (HSP) 68, vacuolar protein sorting-associated protein 13 (VPSAP13), sodium-coupled monocarboxylate transporter 1 (SCMT1), pupal cuticle protein (PCP), protein takeout (PT) and low density lipoprotein receptor adapter protein 1-B (LDLRAP1-B) were significantly up-regulated. Conversely, genes encoding esterase, sulfotransferase 1C4, proton-coupled folate transporter, chitinase 10, gelsolin-related protein of 125 kDa (GRP), fibroin heavy chain (FHC), fatty acid synthase and some P450s were significantly down-regulated in response to fluralaner. CONCLUSIONS:The transcriptome in this study provides more effective resources for the further study of S. litura whilst the DEGs identified sheds further light on the molecular response to fluralaner.

Project description:Endothelial dysfunction caused by endothelial cell injuries is the initiating factor for atherosclerosis (AS), and lipid peroxidative injury is one of a dominant factor for AS pathogenesis. Using RNA-seq, we compared changes in transcriptome expression before and after endothelial cell injury, and found 311 differentially expressed genes (DEGs), of which 258 genes were upregulated and 53 genes were downregulated. The protein-protein interactions (PPIs) between the genes were analysed using the STRING database, and a PPI network of DEGs was constructed. The relationship distributions among these PPIs were analysed by performing network node statistics. We found that in the top 20 DEGs with high connected protein nodes in the PPI network, 16 were upregulated and 4 were downregulated. Gene ontology (GO) functional enrichment analysis and KEGG pathway enrichment analysis on the DEGs were also performed. By comparing the upregulated expressed genes with high connected protein nodes in the PPI network to those related to endothelial cell lipid damage and repair in the GO analysis, we identified seven genes (NOX4, PPARA, CCL2, PDGFB, IL8, VWF, CD36) and verified their expression levels by real-time polymerase chain reaction. The protein interactions between the seven genes were then analysed using the STRING database. The results predicted that CCL2 interacts with NOX4, PPARα, PDGFβ and VWF individually. Thus, we examined the protein expression levels of CCL2, NOX4, PPARα, PDGFβ and VWF, and found that the expression levels of all proteins were significantly upregulated after the lipid peroxidative injury, with CCL2 and PPARα exhibiting the highest expression levels. Therefore, we investigated the interregulatory relationship between CCL2 and PPARα and their roles in the repair of endothelial cell injury. With the help of gene overexpression and knockdown techniques, we discovered that PPARα promotes the repair of endothelial cell injury by upregulating CCL2 expression in human umbilical vein endothelial cells but that CCL2 cannot regulate PPARα expression. Therefore, we believe that PPARα participates in the repair of endothelial cell lipid peroxidative injury through regulating the expression of CCL2.

Project description:BackgroundFormalin-fixed paraffin-embedded (FFPE) tissue samples are routinely archived in the course of patient care and can be linked to clinical outcomes with long-term follow-up. However, FFPE tissues have degraded RNA which poses challenges for analyzing gene expression. Next-generation sequencing (NGS) is rapidly becoming accepted as an effective tool for measuring gene expressions for research and clinical use. However, the feasibility of NGS has not been firmly established when using FFPE tissue.ResultsWe optimized strategies for whole transcriptome sequencing (RNA-seq) using FFPE tissue. Ribosomal RNA (rRNA) was successfully depleted by competitive hybridization using the Ribo-zero™ Kit (Epicentre Biotechnologies), and rRNA sequence content was less than one percent for each library. Gene expression measured by FFPE RNA-seq was compared to two different standards: RNA-seq from fresh frozen (FF) tissue and quantitative PCR (qPCR). Both FF and FFPE tumors were sequenced on an Illumina Genome Analyzer IIX with an average of 10 million reads. The distribution of FPKMs (fragments per kilobase of exon per million fragments mapped) and number of detected genes were similar between FFPE and FF. RNA-seq expressions from FF and FFPE samples from the same renal cell carcinoma (RCC) correlated highly (r = 0.919 for tumor 1 and r = 0.954 for tumor 2). On hierarchical cluster analysis, samples clustered by patient identity rather than method of preservation. TaqMan qPCR of 424 RCC-related genes correlated highly with FFPE RNA-seq expressions (r = 0.775 for FFPE tumor 1, r = 0.803 for FFPE tumor 2). Expression fold changes were considered, to assess biologic relevance of gene expressions. Expression fold changes between FFPE tumors (tumor 1/tumor 2) correlated well when comparing qPCR and RNA-seq (r = 0.890). Expression fold changes between tumors from different risk groups (our high risk RCC/The Cancer Genome Atlas, TCGA, low risk RCC) also correlated well when comparing RNA-seq from FF and FFPE tumors (r = 0.887).ConclusionsFFPE RNA-seq provides reliable genes expression data, comparable to that obtained from fresh frozen tissue. It represents a useful tool for discovery and validation of biomarkers.

Dataset Information

Identification of Genes Associated with Smad3-dependent Renal Injury by RNA-seq-based Transcriptome Analysis.

Publications

Identification of Genes Associated with Smad3-dependent Renal Injury by RNA-seq-based Transcriptome Analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets