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accession-icon GSE51498
Regulation of HSF1-mediated transcriptional programs by PGC-1alpha
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

We examined global gene expression patterns in response to PGC-1 expression in cells derived from liver or muscle.

Publication Title

Direct link between metabolic regulation and the heat-shock response through the transcriptional regulator PGC-1α.

Sample Metadata Fields

Specimen part

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accession-icon GSE81171
Inhibition of adhesion molecule gene expression and cell adhesion by the metabolic regulator PGC-1alpha
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Cell adhesion plays an important role in determining cell shape and function in a variety of physiological and pathophysiological conditions. While links between metabolism and cell adhesion were previously suggested, the exact context and molecular details of such a cross-talk remain incompletely understood.

Publication Title

Inhibition of Adhesion Molecule Gene Expression and Cell Adhesion by the Metabolic Regulator PGC-1α.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE87100
Control of secreted protein gene expression and the mammalian secretome by the metabolic regulator PGC-1a
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Secreted proteins serve pivotal roles in the development of multicellular organisms, acting as structural matrix, extracellular enzymes and signal molecules. In this study we demonstrate, unexpectedly, that PGC-1, a critical transcriptional co-activator of metabolic gene expression, functions to down-regulate expression of diverse genes encoding secreted molecules and extracellular matrix (ECM) components to modulate the secretome. We show that both endogenous and exogenous PGC-1 down-regulate expression of numerous genes encoding secreted molecules. Mechanistically, results obtained using mRNA stability measurements as well as intronic RNA expression analysis are consistent with a transcriptional effect of PGC-1 on expression of genes encoding secreted proteins. Interestingly, PGC-1 requires the central heat shock response regulator HSF1 to affect some of its targets, and both factors co-reside on several target genes encoding secreted molecules in cells. Finally, using a mass spectrometric analysis of secreted proteins, we demonstrate that PGC-1 modulates the secretome of mouse embryonic fibroblasts (MEFs).

Publication Title

Control of Secreted Protein Gene Expression and the Mammalian Secretome by the Metabolic Regulator PGC-1α.

Sample Metadata Fields

Specimen part

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accession-icon GSE30694
Comparison of the effects of early pregnancy with human interferon, alpha 2 (IFNA2) on gene expression in bovine endometrium
  • organism-icon Bos taurus
  • sample-icon 33 Downloadable Samples
  • Technology Badge Icon Affymetrix Bovine Genome Array (bovine)

Description

Interferon tau (IFNT), a Type I IFN similar to alpha IFNs (IFNA), is the pregnancy recognition signal, produced by the ruminant conceptus. To elucidate specific effects of bovine IFNT and of other conceptus-derived factors, endometrial gene expression changes during early pregnancy were compared to gene expression changes after intrauterine application of human IFNA2. In study one, endometrial tissue samples were obtained on days (D) 12, 15, and 18 post-mating from nonpregnant or pregnant heifers. In study two, heifers were treated from D14 to D16 of the estrous cycle with an intrauterine device releasing IFNA2 or placebo lipid extrudates or PBS only as controls. Endometrial biopsies were collected after flushing the uterus. All samples from both experiments were analyzed with an Affymetrix Bovine Genome Array. Study one revealed differential gene expression between pregnant and nonpregnant endometria on D15 and D18. In study two, IFNA2 treatment resulted in differential gene expression in the bovine endometrium. Comparison of the datasets from both studies identified genes that were differentially expressed in response to IFNA2 but not in response to pregnancy on D15 or D18. Vice versa, genes were found as differentially expressed during pregnancy but not after IFNA2 treatment. In study three, spatiotemporal alterations in expression of selected genes were determined in uteri from nonpregnant and early pregnant heifers using in situ hybridization. The findings of this study suggest differential effects of bovine IFNT compared to human IFNA2 and that some pregnancy-specific changes in the endometrium are elicited by conceptus-derived factors other than IFNT.

Publication Title

Comparison of the effects of early pregnancy with human interferon, alpha 2 (IFNA2), on gene expression in bovine endometrium.

Sample Metadata Fields

Sex, Treatment

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accession-icon SRP046242
TRIM24 suppresses development of spontaneous hepatic lipid accumulation and hepatocellular carcinoma in mice
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Purpose: berrantly high expression of TRIM24 occurs in human cancers, including hepatocellular carcinoma. In contrast, TRIM24 in the mouse is reportedly a liver-specific tumor suppressor. To address this dichotomy and uncover direct regulatory functions of TRIM24 in vivo, we developed a new mouse model that lacks expression of all Trim24 isoforms, as the previous model expresses normal levels of Trim24 lacking only exon 4. Methods: To produce germline-deleted Trim24dlE1 mice, deletion of the promoter and exon 1 of Trim24 was induced in Trim24LoxP mice by crossing with a zona pellucida 3-Cre line for global deletion. Liver-specific deletion (Trim24hep) was achieved by crossing with an Albumin-Cre line. Phenotypic analyses were complemented by protein, gene-specific and global RNA expression analyses and quantitative chromatin immunoprecipitation. Results:Global loss of Trim24 disrupted hepatic homeostasis in 100% of mice with highly significant, decreased expression of oxidation/reduction, steroid, fatty acid and lipid metabolism genes, as well as increased expression of genes in unfolded protein, endoplasmic reticulum stress and cell cycle pathways. Trim24dlE1/dlE1 mice have markedly depleted visceral fat and, like Trim24hep/hep mice, spontaneously develop hepatic lipid-filled lesions, steatosis, hepatic injury, fibrosis and hepatocellular carcinoma. Conclusions: TRIM24, an epigenetic co-regulator of transcription, directly and indirectly represses hepatic lipid accumulation, inflammation, fibrosis and damage in the murine liver. Complete loss of Trim24 offers a model of human nonalcoholic fatty liver disease, steatosis, fibrosis and development of hepatocellular carcinoma in the absence of high-fat diet or obesity. Overall design: mRNA profiles of 8 weeks wild type (WT) and Trim24-/- mice were generated by deep sequencing, in triplicate, using Illumina HiSeq 2000

Publication Title

TRIM24 suppresses development of spontaneous hepatic lipid accumulation and hepatocellular carcinoma in mice.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE6904
Expression data from mouse SCN after 30-min light pulse
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

The transmission of information about the photic environment to the circadian clock involves a complex array of neurotransmitters, receptors, and second messenger systems. Using laser capture microscopy and microarray analysis, a population of genes rapidly induced by light in the suprachiasmatic nucleus is identified.

Publication Title

Identification of novel light-induced genes in the suprachiasmatic nucleus.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE66649
Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology
  • organism-icon Homo sapiens
  • sample-icon 28 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Transcriptome Array 2.0 (hta20), Agilent-014850 Whole Human Genome Microarray 4x44K G4112F (Feature Number version), Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology.

Sample Metadata Fields

Specimen part, Disease

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accession-icon GSE66628
Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology (Affymetrix_Gene1.0) (exon analysis)
  • organism-icon Homo sapiens
  • sample-icon 19 Downloadable Samples
  • Technology Badge IconAgilent-014850 Whole Human Genome Microarray 4x44K G4112F (Feature Number version), Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

We present a more extensive and yet precise assessment to elucidate differences and similarities in performance at numerous aspects including signal range, sensitivity to fold-change, and fidelity with TaqMan qRT-PCR. There were three levels of data examined: entire data sets, data derived from gene name annotation oriented subset of 15442 RefSeq genes, and data derived from transcript pattern defined subset of 7034 RefSeq genes. Our results showed a fair degree of overall correlation between all 6 platforms evaluated; but, to varying degrees, two RNA-seq protocols outperformed three of the microarray platforms in most categories. Notably, a fourth microarray platform, Agilent, was comparable, or marginally superior, to the RNA-seq protocols within these same assessments. Furthermore, 3 platforms (Agilent and two RNA-seq methods) demonstrated over 80% concordance with the gold standard TaqMan assay in terms of fold-change accuracy. Our study suggests that the use of transcript patterns can enhance a number of the observed cross-platform correlations, indicating a potential usefulness for similar evaluations.

Publication Title

Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology.

Sample Metadata Fields

Disease

View Samples
accession-icon GSE66648
Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology (Affymetrix_HTA2.0)
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge IconAgilent-014850 Whole Human Genome Microarray 4x44K G4112F (Feature Number version), Affymetrix Human Transcriptome Array 2.0 (hta20)

Description

We present a more extensive and yet precise assessment to elucidate differences and similarities in performance at numerous aspects including signal range, sensitivity to fold-change, and fidelity with TaqMan qRT-PCR. There were three levels of data examined: entire data sets, data derived from gene name annotation oriented subset of 15442 RefSeq genes, and data derived from transcript pattern defined subset of 7034 RefSeq genes. Our results showed a fair degree of overall correlation between all 6 platforms evaluated; but, to varying degrees, two RNA-seq protocols outperformed three of the microarray platforms in most categories. Notably, a fourth microarray platform, Agilent, was comparable, or marginally superior, to the RNA-seq protocols within these same assessments. Furthermore, 3 platforms (Agilent and two RNA-seq methods) demonstrated over 80% concordance with the gold standard TaqMan assay in terms of fold-change accuracy. Our study suggests that the use of transcript patterns can enhance a number of the observed cross-platform correlations, indicating a potential usefulness for similar evaluations.

Publication Title

Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology.

Sample Metadata Fields

Disease

View Samples
accession-icon SRP055917
Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology (RNA-seq_ClonTech)
  • organism-icon Homo sapiens
  • sample-icon 5 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

We present a more extensive and yet precise assessment to elucidate differences and similarities in performance at numerous aspects including signal range, sensitivity to fold-change, and fidelity with TaqMan qRT-PCR. There were three levels of data examined: entire data sets, data derived from gene name annotation oriented subset of 15442 RefSeq genes, and data derived from transcript pattern defined subset of 7034 RefSeq genes. Our results showed a fair degree of overall correlation between all 6 platforms evaluated; but, to varying degrees, two RNA-seq protocols outperformed three of the microarray platforms in most categories. Notably, a fourth microarray platform, Agilent, was comparable, or marginally superior, to the RNA-seq protocols within these same assessments. Furthermore, 3 platforms (Agilent and two RNA-seq methods) demonstrated over 80% concordance with the gold standard TaqMan assay in terms of fold-change accuracy. Our study suggests that the use of transcript patterns can enhance a number of the observed cross-platform correlations, indicating a potential usefulness for similar evaluations. Overall design: The study assessed differences and similarities in performance at numerous aspects including signal range, sensitivity to fold-change, and fidelity with TaqMan qRT-PCR. There were three levels of data examined: entire data sets, data derived from gene name annotation oriented subset of 15442 RefSeq genes, and data derived from transcript pattern defined subset of 7034 RefSeq genes.

Publication Title

Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology.

Sample Metadata Fields

No sample metadata fields

View Samples
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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)

fund-icon Fund the CCDL

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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