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accession-icon GSE116660
Human NK cells under normoxic and hypoxic conditions
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Hypoxia, which characterizes most tumor tissues, can alter the function of different immune cell types, favoring tumor escape mechanisms. In this study, we show that hypoxia profoundly acts on NK cells by influencing their transcriptome, affecting their immunoregulatory functions, and changing the chemiotactic responses of different NK cell subsets.

Publication Title

Hypoxia Modifies the Transcriptome of Human NK Cells, Modulates Their Immunoregulatory Profile, and Influences NK Cell Subset Migration.

Sample Metadata Fields

Specimen part

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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 SRP153358
Next Generation Sequencing Facilitates Quantitative Analysis of ischemic postconditioning (IPO) to attenuate hepatic ischemia-reperfusion injury in mice
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 4000

Description

This is the first study to investigate mRNA expression profiling in regard to hepatic I/R and IPO by next-generation RNA-Seq. Our results may provide an experimental basis for elucidating the underlying mechanism of IPO and reveal candidate biomarkers with which to assess hepatic I/R injury Overall design: liver mRNA profiles of sham, I/R and IPO mice were generated by next-generation sequencing, in triplicate, using Illumina HiSeq 4000.

Publication Title

Gene Expression Profiling in Ischemic Postconditioning to Alleviate Mouse Liver Ischemia/Reperfusion Injury.

Sample Metadata Fields

Specimen part, Cell line, Treatment, Subject

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accession-icon GSE34936
NOD genetic variation influences ab/gd lineage decisions when TCRa is prematurely expressed, but not the process of negative selection.
  • organism-icon Mus musculus
  • sample-icon 59 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Thymic negative selection is functional in NOD mice.

Sample Metadata Fields

Sex, Age

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accession-icon GSE34934
Expression data from BDC2.5 TCR Tg, preselected Rag-/-.B6 and Rag-/-.NOD.H2b thymocytes upon antigenic stimulation
  • organism-icon Mus musculus
  • sample-icon 43 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The aim of this study was to quantify the impact of NOD genetic vatiation on thymic negative selection transcriptional programs.

Publication Title

Thymic negative selection is functional in NOD mice.

Sample Metadata Fields

Sex, Age

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accession-icon GSE34935
Expression data from BDC2.5 TCR Tg thymocytes on B6g7 and NOD background
  • organism-icon Mus musculus
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The aim of this study was to quantify the impact of NOD genetic vatiation on the transcriptional programs induced by the alpha beta-TCR at the DN to DP transition in the BDC2.5 TCR Tg model

Publication Title

Thymic negative selection is functional in NOD mice.

Sample Metadata Fields

Sex, Age

View Samples
accession-icon SRP063523
Next Generation Sequencing Facilitates Quantitative Analysis of mesoderm posterior bHLH transcription factor 1(MESP1)+ and MESP1- cells' Transcriptomes
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500, Illumina HiSeq 2000

Description

Purpose: To compare the transcriptome of MESP1-mTomato reporter cells at undifferentiated state, cardiac differentiation day 3 and day 5. Methods: total RNA from sorted MESP1+, MESP1- and HESCs (in biological duplicates) was extracted using RNeasy Plus Mini Kit (Qiagen) and treated with RNase free DNase. RNA library was prepared following the instruction of TruSeqâ„¢ RNA Sample Preparation kit (Illumina) and sequenced on Illumina HiSeq 2000. Results: genes differentially expressed in MESP1-mTomato+ and mTomato- cells were identified. Conclusions: the gene expression profile of MESP1-mTomato cells indicates that they are cardiovascular progenitor cells. Overall design: Through RNA-seq of MESP1+, MESP1- and undifferentiated cells, perform bioinformatics analysis to identify differentially expressed genes, then perform functional study.

Publication Title

Homozygous MESP1 knock-in reporter hESCs facilitated cardiovascular cell differentiation and myocardial infarction repair.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE33807
Eosinophil specific transcriptome in homeostatic intestine and lung
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Objective: To study the physiological role of eosinophils in the GI tract and lung under homeostatic conditions,

Publication Title

The pan-B cell marker CD22 is expressed on gastrointestinal eosinophils and negatively regulates tissue eosinophilia.

Sample Metadata Fields

Specimen part

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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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