refine.bio
  • Search
      • Normalized Compendia
      • RNA-seq Sample Compendia
  • Docs
  • About
  • My Dataset
github link
Showing
of 126 results
Sort by

Filters

Technology

Platform

accession-icon GSE62252
Expression data from kidney of Grhl1wt and Grhl1 ko mice.
  • organism-icon Mus musculus
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

The aim of our study was to investigate the functions of Grhl transcription factor in the kidney.

Publication Title

Consequences of the loss of the Grainyhead-like 1 gene for renal gene expression, regulation of blood pressure and heart rate in a mouse model.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE78501
Gene expression profiling of genes differentially expressed by oral carcinoma Ca9-22 and SLPI-deficient Ca9-22 (SLPI) cells
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We used the myoma model in conjunction with gene expression profiling with microarray data as an efficient tool for high throughput analysis and to screen for differentially expressed genes. Our aim was to identify candidates playing an important role in SLPI and/or MMP-promoted tumor invasion by comparing oral carcinoma Ca9-22 cells, which highly express secretory leukocyte protease inhibitor (SLPI) gene, with SLPI-deficient Ca9-22 cells.

Publication Title

Human uterus myoma and gene expression profiling: A novel in vitro model for studying secretory leukocyte protease inhibitor-mediated tumor invasion.

Sample Metadata Fields

Cell line

View Samples
accession-icon GSE137998
Expression profiling of cervical cancer cells with IGF2R knock down
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

From comprehensive expression analysis of RNAseq data, IGF2R was found to correlate with poor prognosis in cervical cancer. Gene knockdown of IGF2R lead to cell death in cervical cancer. To reveal its biological function, we performed microarray analysis using IGF2R knockdown cervical cancer cells.

Publication Title

Upregulation of IGF2R evades lysosomal dysfunction-induced apoptosis of cervical cancer cells via transport of cathepsins.

Sample Metadata Fields

Cell line

View Samples
accession-icon GSE69925
Gene expression profiling of esophageal squamous cell carcinomas
  • organism-icon Homo sapiens
  • sample-icon 256 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

To identify the specific genes for subtyping.

Publication Title

Discovery of a Good Responder Subtype of Esophageal Squamous Cell Carcinoma with Cytotoxic T-Lymphocyte Signatures Activated by Chemoradiotherapy.

Sample Metadata Fields

Specimen part, Disease, Disease stage

View Samples
accession-icon GSE8761
Transcriptional profiling of ribosomal protein knockouts
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome S98 Array (ygs98)

Description

Duplicated genes escape gene loss by conferring a dosage benefit or evolving diverged functions. The yeast Saccharomyces cerevisiae contains many duplicated genes encoding ribosomal proteins. Prior studies have suggested that these duplicated proteins are functionally redundant and affect cellular processes in proportion to their expression. In contrast, through studies of ASH1 mRNA in yeast, we demonstrate paralog-specific requirements for the translation of localized mRNAs. Intriguingly, these paralog-specific effects are limited to a distinct subset of duplicated ribosomal proteins. Moreover, transcriptional and phenotypic profiling of cells lacking specific ribosomal proteins reveals differences between the functional roles of ribosomal protein paralogs that extend beyond effects on mRNA localization. Finally, we show that ribosomal protein paralogs exhibit differential requirements for assembly and localization. Together, our data indicate complex specialization of ribosomal proteins for specific cellular processes, and support the existence of a ribosomal code.

Publication Title

Functional specificity among ribosomal proteins regulates gene expression.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE4006
Estrogen effects on MCF-7 breast cancer cells co-expressing ERa and ERb
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Two subtypes of the estrogen receptor, ERalpha and ERbeta, mediate the actions of estrogens, and the majority of human breast tumors contain both ERalpha and ERbeta. To examine the possible interactions and modulatory effects of ERbeta on ERalpha activity, we have used adenoviral gene delivery to produce human breast cancer (MCF-7) cells expressing ERbeta, along with their endogenous ERalpha. We have examined the effects of ER expression on genome-wide gene expression by Affymetrix GeneChip microarrays. We find that ERbeta modulated estrogen gene expression on nearly 24% of E2-stimulated genes but only 8% of E2-inhibited genes. We find that ERbeta modulation is gene-specific, enhancing or counteracting ERalpha regulation for distinct subsets of estrogen target genes. Introduction of ERbeta into ERalpha-containing cells induced up/down-regulation of many estrogen target in the absence of any added ligand. In addition, ERbeta presence elicited the expression of a unique set of genes that were not regulated by ERalpha alone. ERbeta modulated the expression of genes in many functional categories, but the greatest numbers were associated with transcription factor and signal transduction pathways. Regulation of multiple components in the TGF beta, SDF1, and semaphorin pathways, may contribute to the suppression of proliferation observed with ERbeta both in the presence and absence of estrogen. Hence, ERbeta modulates ERalpha gene regulation in diverse ways that may contribute to its growth-inhibiting beneficial effects in breast cancer

Publication Title

Impact of estrogen receptor beta on gene networks regulated by estrogen receptor alpha in breast cancer cells.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE59860
Defining CD4 T Cell Memory by the Epigenetic Landscape of CpG DNA Methylation
  • organism-icon Homo sapiens
  • sample-icon 17 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.1 ST Array (hugene11st), Illumina Genome Analyzer IIx

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Defining CD4 T cell memory by the epigenetic landscape of CpG DNA methylation.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE58684
Defining CD4 T Cell Memory by the Epigenetic Landscape of CpG DNA Methylation [Affymetrix]
  • organism-icon Homo sapiens
  • sample-icon 17 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.1 ST Array (hugene11st), Illumina Genome Analyzer IIx

Description

Memory T cells are primed for rapid responses to antigen; however, the molecular mechanisms responsible for priming remain incompletely defined. CpG methylation in promoters is an epigenetic modification, which regulates gene transcription. Using targeted bisulfite sequencing, we examined methylation of 2100 genes (56,000 CpG) mapped by deep sequencing to T cell activation in human nave and memory CD4 T cells. 466 CpGs (132 genes) displayed differential methylation between nave and memory cells. 21 genes exhibited both differential methylation and gene expression before activation, linking promoter DNA methylation states to gene regulation; 6 genes encode proteins closely studied in T cells while 15 genes represent novel targets for further study. 39 genes exhibited reduced methylation in memory cells coupled with increased gene expression with activation compared to nave cells, revealing specific genes more rapidly expressed in memory compared to nave cells and potentially regulated by DNA methylation. These findings define a DNA methylation signature unique to memory CD4 T cells and correlated with activation-induced gene expression.

Publication Title

Defining CD4 T cell memory by the epigenetic landscape of CpG DNA methylation.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP045052
Defining CD4 T Cell Memory by the Epigenetic Landscape of CpG DNA Methylation [RNA-Seq]
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerIIx

Description

Memory T cells are primed for rapid responses to antigen; however, the molecular mechanisms responsible for priming remain incompletely defined. CpG methylation in promoters is an epigenetic modification, which regulates gene transcription. Using targeted bisulfite sequencing, we examined methylation of 2100 genes (56,000 CpG) mapped by deep sequencing to T cell activation in human naïve and memory CD4 T cells. 466 CpGs (132 genes) displayed differential methylation between naïve and memory cells. 21 genes exhibited both differential methylation and gene expression before activation, linking promoter DNA methylation states to gene regulation; 6 genes encode proteins closely studied in T cells while 15 genes represent novel targets for further study. 39 genes exhibited reduced methylation in memory cells coupled with increased gene expression with activation compared to naïve cells, revealing specific genes more rapidly expressed in memory compared to naïve cells and potentially regulated by DNA methylation. These findings define a DNA methylation signature unique to memory CD4 T cells and correlated with activation-induced gene expression. Overall design: RNA sequencing of primary human naïve and memory CD4 T cells at rest and 48 hours post-activation.

Publication Title

Defining CD4 T cell memory by the epigenetic landscape of CpG DNA methylation.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE4616
Time series of diabetes and exercise training induced expression changes in cardiac muscle of mice
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Murine Genome U74A Version 2 Array (mgu74av2)

Description

We investigated the effects of diabetes, physical training, and their combination on the gene expression of cardiac muscle. Mice were divided to control (C), training (T), streptozotocin-induced diabetic (D), and diabetic training (DT) groups. Training groups performed 1, 3, or 5 weeks of endurance training on a motor-driven treadmill. Muscle samples from T and DT groups together with respective controls were collected 24 hours after the last training session. Gene expression of cardiac muscles were analyzed using Affymetrix Gene chip MG U74Av2 (Affymetrix , Inc., Santa Clara, CA).

Publication Title

Effects of streptozotocin-induced diabetes and physical training on gene expression of titin-based stretch-sensing complexes in mouse striated muscle.

Sample Metadata Fields

No sample metadata fields

View Samples
...

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

Powered by Alex's Lemonade Stand Foundation

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.

BSD 3-Clause LicensePrivacyTerms of UseContact