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accession-icon GSE22324
Mapping of disease-associated expression polymorphisms in primary peripheral blood CD4+ lymphocytes
  • organism-icon Homo sapiens
  • sample-icon 200 Downloadable Samples
  • Technology Badge IconIllumina humanRef-8 v2.0 expression beadchip

Description

Analysis of expression quantitative trait loci (eQTLs) using RNA derived from freshly harvested peripheral blood CD4+ lymphocytes from 200 asthmatics collected in clinical settings.

Publication Title

Mapping of numerous disease-associated expression polymorphisms in primary peripheral blood CD4+ lymphocytes.

Sample Metadata Fields

Sex, Specimen part, Disease, Disease stage, Subject

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accession-icon SRP058313
RNA sequencing of ILK-deficient hair follicle bulge stem cells
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

We sequenced mRNA from FACS purified hair follicle bulge stem cells from 21 d old control and ILK-deficient mice, 3 biological replicates each Overall design: Examination of mRNA levels in control and ILK-deficient hair follicle bulge stem cells

Publication Title

Integrin-linked kinase regulates the niche of quiescent epidermal stem cells.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE7793
Vancomycin nephrotoxicity assessed by DNA microarray
  • organism-icon Mus musculus
  • sample-icon 48 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The glycopeptide antibiotic vancomycin (VCM) represents one of the last lines of defense against methicillin-resistant Staphylococcus aureus infections. However, vancomycin is nephrotoxic, but the mechanism of toxicity is still unclear.

Publication Title

Gene expression analysis reveals new possible mechanisms of vancomycin-induced nephrotoxicity and identifies gene markers candidates.

Sample Metadata Fields

Specimen part

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accession-icon GSE11812
Gene expression profile of cancer cell lines of different origin
  • organism-icon Homo sapiens
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Gene expression profile of cancer cell lines of breast, lung, pancreatic, gasctric, ovarian, hepatocellular, prostate carcinomas and melanomas.

Publication Title

Gene expression profiling of 30 cancer cell lines predicts resistance towards 11 anticancer drugs at clinically achieved concentrations.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE100788
Gata4 and LMO3 balance angiocrine signaling and autocrine inflammatory activation by BMP2 in liver sinusoidal endothelial cells
  • organism-icon Homo sapiens
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st), Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

GATA4 and LMO3 balance angiocrine signaling and autocrine inflammatory activation by BMP2 in liver sinusoidal endothelial cells.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE100712
Gata4 and LMO3 balance angiocrine signaling and autocrine inflammatory activation by BMP2 in liver sinusoidal endothelial cells [HUVEC]
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st), Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

Liver sinusoidal endothelial cells (LSEC) represent a unique, organ-specific type of discontinuous endothelial cells. LSEC instruct the hepatic vascular niche by paracrine-acting angiocrine factors. Recently, we have shown that LSEC-specific transcriptional regulator GATA4 induces expression of BMP2 in cultured endothelial cells (EC) in vitro. Furthermore, angiocrine Bmp2 signaling in the liver in vivo was demonstrated to control iron homeostasis. Here, we investigated GATA4-dependent autocrine BMP2 signaling in endothelial cells by gene expression profiling. GATA4 induced a large cluster of inflammatory endothelial response genes in cultured EC, which is similar to previously identified virus-induced and interferon-associated responses. Treating the cells with the BMP2 inhibitor Noggin counter-regulated the GATA4-dependent inflammatory phenotype of EC, indicating that BMP2 is indeed the major driver. In contrast to continuous EC, LSEC were less prone to activation by BMP2. Notably, GATA4-dependent induction of the inflammatory EC response gene cluster was attenuated by over-expression of the LSEC-specific transcriptional modifier LMO3 while hepatocyte activation was fully preserved, indicating conserved BMP2 synthesis. In summary, our data suggest that transcriptional counter-regulation by GATA4 and LMO3 in LSEC prevents autocrine induction of an inflammatory phenotype, while maintaining angiocrine BMP2-mediated cell communication in the liver vascular niche.

Publication Title

GATA4 and LMO3 balance angiocrine signaling and autocrine inflammatory activation by BMP2 in liver sinusoidal endothelial cells.

Sample Metadata Fields

Specimen part, Treatment

View Samples
accession-icon GSE100711
Gata4 and LMO3 balance angiocrine signaling and autocrine inflammatory activation by BMP2 in liver sinusoidal endothelial cells [HLSEC]
  • organism-icon Homo sapiens
  • sample-icon 3 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

Liver sinusoidal endothelial cells (LSEC) represent a unique, organ-specific type of discontinuous endothelial cells. LSEC instruct the hepatic vascular niche by paracrine-acting angiocrine factors. Recently, we have shown that LSEC-specific transcriptional regulator GATA4 induces expression of BMP2 in cultured endothelial cells (EC) in vitro. Furthermore, angiocrine Bmp2 signaling in the liver in vivo was demonstrated to control iron homeostasis. Here, we investigated GATA4-dependent autocrine BMP2 signaling in endothelial cells by gene expression profiling. GATA4 induced a large cluster of inflammatory endothelial response genes in cultured EC, which is similar to previously identified virus-induced and interferon-associated responses. Treating the cells with the BMP2 inhibitor Noggin counter-regulated the GATA4-dependent inflammatory phenotype of EC, indicating that BMP2 is indeed the major driver. In contrast to continuous EC, LSEC were less prone to activation by BMP2. Notably, GATA4-dependent induction of the inflammatory EC response gene cluster was attenuated by over-expression of the LSEC-specific transcriptional modifier LMO3 while hepatocyte activation was fully preserved, indicating conserved BMP2 synthesis. In summary, our data suggest that transcriptional counter-regulation by GATA4 and LMO3 in LSEC prevents autocrine induction of an inflammatory phenotype, while maintaining angiocrine BMP2-mediated cell communication in the liver vascular niche.

Publication Title

GATA4 and LMO3 balance angiocrine signaling and autocrine inflammatory activation by BMP2 in liver sinusoidal endothelial cells.

Sample Metadata Fields

Specimen part, Treatment

View Samples
accession-icon SRP028887
Differential Protein Occupancy Profiling of the mRNA Transcriptome
  • organism-icon Homo sapiens
  • sample-icon 25 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500, IlluminaHiSeq2000

Description

Protein-RNA interactions are fundamental to core biological processes, such as mRNA splicing, localization, degradation and translation. We have developed a photoreactive nucleotide-enhanced UV crosslinking and oligo(dT) purification approach to identify the mRNA-bound proteome using quantitative proteomics and to display the protein occupancy on mRNA transcripts by next-generation sequencing (Baltz and Munschauer et al. 2012). Our current work focuses on streamlining and extending protein occupancy profiling on poly(A)-RNA. Our objectives are to identify previously unknown protein-bound transcripts and, more importantly, to assess global and local differences in protein occupancy across different biological conditions. To this end, we have implemented poppi, the first pipeline for differential analysis of protein occupancy profiles. We have applied our analysis pipeline to pinpoint changes in occupancy profiles of MCF7 cells against already published HEK293 cells [GSE38157]. Overall design: We generated protein occupancy cDNA libraries for two biological replicates. Briefly, we crosslinked 4SU-labeled MCF7 cells and purified protein-mRNA complexes using oligo(dT)-beads. The precipitate was treated with RNAse I to reduce the protein-crosslinked RNA fragments to a length of about 30-60 nt. To remove non-crosslinked RNA, protein-RNA complexes were precipitated with ammonium sulfate and blotted onto nitrocellulose. The RNA was recovered by Proteinase K treatment, ligated to cloning adapters, and reverse transcribed. The resulting cDNA libraries were PCR-amplified and next-generation sequenced.

Publication Title

Differential protein occupancy profiling of the mRNA transcriptome.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP041130
MOV10 Is a 5'' to 3'' RNA Helicase Contributing to UPF1 mRNA Target Degradation by Translocation along 3''UTRs (expression)
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

RNA helicases are important regulators of gene expression that act by remodeling RNA secondary structures and as RNA-protein interactions. Here, we demonstrate that MOV10 has an ATP-dependent 5'' to 3'' in vitro RNA unwinding activity and determine the RNA-binding sites of MOV10 and its helicase mutants using PAR-CLIP. We find that MOV10 predominantly binds to 3'' UTRs upstream of regions predicted to form local secondary structures and provide evidence that MOV10 helicase mutants are impaired in their ability to translocate 5'' to 3'' on their mRNA targets. MOV10 interacts with UPF1, the key component of the nonsense-mediated mRNA decay pathway. PAR-CLIP of UPF1 reveals that MOV10 and UPF1 bind to RNA in close proximity. Knockdown of MOV10 resulted in increased mRNA half-lives of MOV10-bound as well as UPF1-regulated transcripts, suggesting that MOV10 functions in UPF1-mediated mRNA degradation as an RNA clearance factor to resolve structures and displace proteins from 3'' UTRs. Overall design: Flp-In T-REx HEK293 cells expressing FLAG/HA-tagged MOV10 WT, MOV10 K530A, MOV10 D645N and UPF1 were used to determine the protein-RNA interaction sites of RNA helicases MOV10 and UPF1 as well as MOV10 inactive variants using PAR-CLIP in combination with next generation sequencing. mRNA half-life changes of MOV10-targeted mRNA were determined by measuring mRNA half-lives by mRNA sequencing of mock and MOV10-depleted HEK293 cells.

Publication Title

MOV10 Is a 5' to 3' RNA helicase contributing to UPF1 mRNA target degradation by translocation along 3' UTRs.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE111184
Transcriptional effects of Deoxynivalenol on intestinal porcine epithelial cells (IPEC-J2)
  • organism-icon Sus scrofa
  • sample-icon 23 Downloadable Samples
  • Technology Badge Icon Affymetrix Porcine Genome Array (porcine)

Description

in vitro microarray study of transcriptional changes of jejunal cells

Publication Title

Deoxynivalenol Affects Cell Metabolism and Increases Protein Biosynthesis in Intestinal Porcine Epithelial Cells (IPEC-J2): DON Increases Protein Biosynthesis.

Sample Metadata Fields

No sample metadata fields

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Developed by the Childhood Cancer Data Lab

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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