Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Gene expression profiles of the diabetic glomerular endothelial cell

ABSTRACT: The objective of this study is to create an encyclopedia of all genes expressed in the glomerular endothelial cell under normal and diabetic conditions. We utilized Tie2-GFP transgenic mice to mark cells of the glomerular endothelium. To induce diabetic nephropathy (DB), a genetic model of DB, BKS.Cg-m +/+ Leprdb/J from Jax laboratories was used. We utilized fluorescent activated cell sorting (FACS) to isolate glomerular endothelial cells from normal and diabetic mice. The RNAs from these samples were isolated and utilized to hybridize to microarrays, which offers a powerful, efficient and effective method for the creation of a gene expression atlas. Microarrays were used to identify the transciptional differences that occur in the glomular endothelium of a diabetic mouse. Diabetic and control mice carrying the Tie2-GFP transgenic were utilized to isolate the endothelial cells from the adult glomerulus. The endothelial cells were isolated from the glomerulus using FACS. RNA was isolated and the gene expression profiles were determined by microarrays.

ORGANISM(S): Mus musculus

SUBMITTER: Eric Brunskill

PROVIDER: E-GEOD-21324 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Gene expression programs of mouse endothelial cells in kidney development and disease.

Brunskill Eric W EW Potter S Steven SS

PloS one 20100810 8

Endothelial cells are remarkably heterogeneous in both morphology and function, and they play critical roles in the formation of multiple organ systems. In addition endothelial cell dysfunction can contribute to disease processes, including diabetic nephropathy, which is a leading cause of end stage renal disease. In this report we define the comprehensive gene expression programs of multiple types of kidney endothelial cells, and analyze the differences that distinguish them. Endothelial cells ...[more]

PMID: 20706631

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Project description:Glomerular diseases account for the majority of cases with chronic renal failure. Several genes have been identified with key relevance for glomerular function. Quite a few of these genes show a specific or preferential mRNA expression in the renal glomerulus. To identify additional candidate genes involved in glomerular function in humans we generated a human renal glomerulus-specific transcript dataset (GTD) by comparing gene expression profiles from human glomeruli and tubulointerstitium obtained from six transplant living donors using Affymetrix HG-U133A arrays. This analysis resulted in 677 genes with prominent overrepresentation in the glomerulus. Genes with ‘a prior’i established known prominent glomerular expression served for validation and were all found in the novel expression library (e.g. CDKN1, DAG1, DDN, EHD3, MYH9, NES, NPHS1, NPHS2, PDPN, PLA2R1, PLCE1, PODXL, PTPRO, SYNPO, TCF21, TJP1, WT1). The mRNA expression for several novel glomerulus-enriched genes identified in REGGEL was validated by qRT-PCR. Gene ontology and pathway analysis identified biological processes previously not reported to be of relevance in glomeruli including among others axon guidance. This finding was further validated by assessing the expression of the axon guidance molecules neuritin (NRN1) and roundabout receptor ROBO1 and -2. Glomerular disease associated differential mRNA regulation of ROBO2 was found in diabetic nephropathy. In summary, using a comparative strategy on microdissected nephrons novel transcripts with predominant expression in the human glomerulus could be identified. A systematic analysis of this glomerulus-specifc gene expression library allows the detection of target molecules and biological processes involved in glomerular biology and renal disease. Sample from kidney biopsies of 6 transplant Living Donors (LD) were microdissected into tubular and glomerular compartment and separately hybridized an Affymetrix HG-U133A microarrays. Background correction and quantile normalization was ferformed using RMAexpress Version 0.3 as part of a dataset of 88 samples for glomeruli and 84 samples for tubuli. All data are reported in log2 scale. A background filter cut-off was defined to lower the count of false positive calls using the highest signal value obtained from non-human Affymetrix control oligonucleotides multiplied by a factor of 1.2, following previous studies: Schmid H, Boucherot A, Yasuda Y, et al.: Modular activation of nuclear factor-kappaB transcriptional programs in human diabetic nephropathy. Diabetes 55:2993-3003, 2006 A linear model was fit to compensate differences in expression due to separate sample processing of the compartments. Subsequently, genes were selected based on foldchange.

Dataset Information

Gene expression profiles of the diabetic glomerular endothelial cell

Publications

Gene expression programs of mouse endothelial cells in kidney development and disease.

Similar Datasets

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