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accession-icon GSE17939
MEK5D-transfected HUVEC
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We expressed a constitutively active mutant of MEK5 (MEK5D) in human primary endothelial cells (EC) to study the transcriptional and functional responses to Erk5 activation under static conditions.

Publication Title

Erk5 activation elicits a vasoprotective endothelial phenotype via induction of Kruppel-like factor 4 (KLF4).

Sample Metadata Fields

Cell line

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accession-icon GSE35011
PPARg agonists induce a white-to-brown fat conversion through stabilization of PRDM16 protein
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

Brown adipose tissue dissipates energy through heat and functions as a defense against cold and obesity. PPAR ligands have been shown to induce the browning of white adipocytes; however, the underlying mechanisms remain unclear. Here we show that PPAR ligands require full agonism to induce a brown fat gene program preferentially in subcutaneous white adipose. These effects require expression of PRDM16, a factor that controls the development of classical brown fat. Depletion of PRDM16 blunts the effects of the PPAR agonist rosiglitazone on the induced brown fat gene program. Conversely, PRDM16 and rosiglitazone synergistically activate the brown fat gene program in vivo. This synergy is tightly associated with an increased accumulation of PRDM16 protein, due in large measure to an increase in the half-life of the protein in agonist treated cells. Identifying compounds that stabilize PRDM16 protein may represent a novel therapeutic pathway for the treatment of obesity and diabetes.

Publication Title

PPARγ agonists induce a white-to-brown fat conversion through stabilization of PRDM16 protein.

Sample Metadata Fields

Sex

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accession-icon GSE103941
Expression data from mice liver drinking Hydrogen water
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Liver RNA samples from C57BL6 mice drinking Hydrogen water for 4 weeks

Publication Title

Molecular hydrogen upregulates heat shock response and collagen biosynthesis, and downregulates cell cycles: meta-analyses of gene expression profiles.

Sample Metadata Fields

Specimen part

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accession-icon GSE18474
A novel metabolic monitoring system identified nutrition-mediated microbial interactions
  • organism-icon Escherichia coli, Bifidobacterium longum
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix E. coli Genome 2.0 Array (ecoli2)

Description

"Omics" technologies have been developed to understand the whole complex microbial systems; however, most omics studies reported so far were utilized to analyze the living matters of single-species. To understand the cell-cell interaction in the gut microbial complex, we selected to examine the interaction of Escherichia coli O157:H7 (O157) and Bifidobacterium longum (BL), known as a pathogenic and a commensal bacteria, as a first step for understanding the whole gut microbial complex. We have developed a novel time-lapse 2D-NMR metabolic profiling system in order to measure the extracellular metabolites, which are considered a key factor to understand the bacterial crosstalk. Furthermore, in combination with transcriptome and proteome analysis, we found that the relationship between BL and O157 could be partially regarded as the producer and the consumer of nutrients, especially in the case of serine and aspartate metabolism. These findings suggest that our novel profiling systems could be a powerful tool toward understanding crosstalk of the whole microbial complex such as the gut, industrial bioreactors or environmental microbial communities.

Publication Title

Dynamic omics approach identifies nutrition-mediated microbial interactions.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE16081
Gallus gallus bursal FAE and IFE
  • organism-icon Gallus gallus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Chicken Genome Array (chicken)

Description

A minor population of M cells within the follicle-associated epithelium (FAE) of intestinal Peyers patches (PP) serves as a major portal for entry of exogenous antigens. Characterization of the mammalian M cells, including identification of M-cell surface molecules used for bacterial uptake, has been hampered by their relative rarity. In contrast, M cells constitute virtually all of the FAE cells in the avian bursa of Fabricius. We therefore performed comparative gene expression profiling of chicken and murine FAE to identify commonly expressed genes by M cells in both species. The comprehensive transcriptome analysis revealed that 28 genes were commonly up-regulated in FAE from both species. In situ hybridization (ISH) revealed that annexin A10 (Anxa10) mRNA was scattered in FAE, and co-localized with Ulex europaeus agglutinin-1(UEA-1) that binds to M cells. Whole-mount immunostaining also revealed that cellular prion protein (PrPC) was expressed on the luminal side of the apical plasma membrane of M cells, and co-localized with grycoprotein2 (GP2) that recognizes only M cells in murine PP. Taken together, we found new M-cell-specific molecules by using comprehensive transcriptome analysis. These molecules conserved in M cells from both species might play critical roles in M-cell function and/or differentiation.

Publication Title

New approach for m-cell-specific molecules screening by comprehensive transcriptome analysis.

Sample Metadata Fields

Age, Specimen part, Disease, Disease stage

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accession-icon GSE27583
mRNA decay analysis in the mouse myoblast cell line, C2C12 cells treated with conrtol-, Cugbp1- or Mbnl1-siRNA
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

CUGBP1 and MBNL1 are developmentally regulated RNA-binding proteins that are causally associated with myotonic dystrophy type 1. Using HITS-CLIP anlysis, we found CUGBP1 and MBNL1 preferentially bind to alternatively spliced introns and exons, as well as to the 3' UTRs.

Publication Title

CUGBP1 and MBNL1 preferentially bind to 3' UTRs and facilitate mRNA decay.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon SRP200067
Constitutive CD8 expression drives innate CD8+ T cell differentiation via induction of iNKT2 subset
  • organism-icon Mus musculus
  • sample-icon 2 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 1500

Description

Constitutive CD8 expression drives innate CD8+ T cell differentiation via induction of iNKT2 subset. Overall design: Analysis of RNA from Cd8ab transgenic mice by RNA-seq.

Publication Title

Constitutive CD8 expression drives innate CD8<sup>+</sup> T-cell differentiation via induction of iNKT2 cells.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE6313
Comparison of Hybridization-based and Sequencing-based Gene Expression Technologies on Biological Replicates
  • organism-icon Mus musculus
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Murine Genome U74A Version 2 Array (mgu74av2)

Description

High-throughput systems for gene expression profiling have been developed and matured rapidly through the past decade. Broadly, these can be divided into two categories: hybridization-based and sequencing-based approaches. With data from different technologies being accumulated, concerns and challenges are raised regarding data comparability and agreement across technologies. Within an ongoing large-scale cross-platform data comparison framework, we report here a comparison based on identical samples between one-dye DNA microarray platforms and MPSS (Massively Parallel Signature Sequencing). The DNA microarray platforms generally provided highly correlated data, while moderate correlations between microarrays and MPSS were obtained. Disagreements between the two types of technologies can be attributed to limitations inherent to both technologies. The variation found between pooled biological replicates underlines the importance of exercising caution in identification of differential expression, especially for the purposes of biomarker discovery. Based on different principles, hybridization-based and sequencing-based technologies should be considered complementary to each other, rather than competitive, and currently, both provide indispensable tools for transcriptome profiling.

Publication Title

Comparison of hybridization-based and sequencing-based gene expression technologies on biological replicates.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE29364
Identification of WUSCHEL direct targets.
  • organism-icon Arabidopsis thaliana
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

Cell-cell communication is critical for stem cell maintenance. Shoot apical meristem (SAM) located at the shoot tip harbors stem cells within the central zone (CZ). Their progeny differentiate in the adjacent peripheral zone (PZ). WUSCHEL (WUS) is a homeodomain transcription factor produced in a few cells of the organizing center (OC), located beneath the CZ. It has been shown to specify stem cell fate and also activate CLAVATA3 (CLV3) expression in cells of the CZ. CLV3 is a secreted peptide that activates a membrane bound receptor kinase-CLAVATA1 to restrict WUS transcription to the OC. It has been hypothesized that WUS activates CLV3 expression and stem cell fate in adjacent cells of the CZ by activating a non-cell autonomous signal. Contrary to this hypothesis, here we show that the WUS protein after being synthesized in cells of the OC, migrates into the superficial cell layers of the CZ where it activates CLV3 transcription by binding to its promoter elements. WUS also migrates laterally into the PZ to repress the expression of differentiation promoting transcription factors by binding to their regulatory regions. Migration of a stem cell inducing transcription factor into adjacent cells to activate a negative regulator, whereby restricting its own accumulation is unique to plant stem cell niches. While stem cell promoting transcription factor directly repressing differentiation promoting transcription factors to prevent premature differentiation of stem cell progenitors is conserved among diverse stem cell niches.

Publication Title

Plant stem cell maintenance involves direct transcriptional repression of differentiation program.

Sample Metadata Fields

Treatment

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accession-icon GSE12939
Global gene expression changes including drug metabolism and disposition induced by three-dimensional culture of HepG2
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

We found constitutive upregulation and higher degree induction of drug metabolism and disposition-related genes in a three-dimensional HepG2 culture. The upregulated genes are those believed to be regulated by different regulatory factors. The global gene expression analysis by Affymetrix GeneChip indicated that altered expressions of microtubule-related genes may change expressed levels of drug metabolism and disposition genes. Stabilization of the microtubule molecules with docetaxel, a tubulin stabilizing agent, in the two-dimensional culture showed gene expression patterns similar to those in the three-dimensional culture, indicating that culture environment affects drug metabolism functions in HepG2 cells.

Publication Title

Global gene expression changes including drug metabolism and disposition induced by three-dimensional culture of HepG2 cells-Involvement of microtubules.

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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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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