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accession-icon GSE51378
Expression data from wild type (WT) and TREM2 null alveolar macrophages (AM)
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

TREM-2 has been described to be a phagocytic receptor. We assessed the influence of TREM-2 on gene expression in alveolar macrophages (AM)

Publication Title

The triggering receptor expressed on myeloid cells 2 inhibits complement component 1q effector mechanisms and exerts detrimental effects during pneumococcal pneumonia.

Sample Metadata Fields

Specimen part

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accession-icon GSE61562
Murine Norovirus Effect on Cells
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Changes in gene expression on MNV infection of RAW264.7 cells

Publication Title

Murine norovirus replication induces G0/G1 cell cycle arrest in asynchronously growing cells.

Sample Metadata Fields

Cell line

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accession-icon GSE25306
Gene expression profiling of skeletal muscles treated with a soluble activin type IIB receptor
  • organism-icon Mus musculus
  • sample-icon 35 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Inhibition of the myostatin signaling pathway is emerging as a promising therapeutic means to treat muscle wasting disorders. Activin type IIB receptor is the putative myostatin receptor, and a soluble activin receptor (ActRIIB-Fc) has been demonstrated to potently inhibit a subset of TGF- family members including myostatin. In order to determine reliable and valid biomarkers for myostatin pathway inhibition, we assessed gene expression profiles for quadriceps muscles from mice treated with ActRIIB-Fc compared to mice genetically lacking myostatin and control mice.

Publication Title

Gene expression profiling of skeletal muscles treated with a soluble activin type IIB receptor.

Sample Metadata Fields

Sex, Age, Specimen part, Treatment

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accession-icon GSE102259
Combined analysis of oligonucleotide microarray data from transgenic and knockout mice identifies direct SREBP target genes
  • organism-icon Mus musculus
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Murine Genome U74A Version 2 Array (mgu74av2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Combined analysis of oligonucleotide microarray data from transgenic and knockout mice identifies direct SREBP target genes.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE102256
Combined analysis of oligonucleotide microarray data from transgenic and knockout mice identifies directSREBP target genes [MG_U74Av2]
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Murine Genome U74A Version 2 Array (mgu74av2)

Description

The synthesis of fatty acids and cholesterol is regulated by three membrane-bound transcription factors: sterol regulatory element-binding proteins (SREBP)-1a, -1c, and -2. Their function in liver has been characterized in transgenic mice that overexpress each SREBP isoform and in mice that lack all three nuclear SREBPs because of gene knockout of SREBP cleavage-activating protein (SCAP) required for nuclear localization of SREBPs. Here, we use oligonucleotide arrays hybridized with RNA from livers of three lines of mice (transgenic for SREBP-1a, transgenic for SREBP-2, and knockout for SCAP) to identify genes that are likely to be direct targets of SREBPs in liver. Application of stringent combinatorial criteria to the transgenic/knockout approach allows identification of genes whose activities are likely controlled directly by the SREBPs.

Publication Title

Combined analysis of oligonucleotide microarray data from transgenic and knockout mice identifies direct SREBP target genes.

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon GSE102257
Combined analysis of oligonucleotide microarray data from transgenic and knockout mice identifies directSREBPtarget genes [MG_U74Bv2]
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Murine Genome U74A Version 2 Array (mgu74av2)

Description

The synthesis of fatty acids and cholesterol is regulated by three membrane-bound transcription factors: sterol regulatory element-binding proteins (SREBP)-1a, -1c, and -2. Their function in liver has been characterized in transgenic mice that overexpress each SREBP isoform and in mice that lack all three nuclear SREBPs because of gene knockout of SREBP cleavage-activating protein (SCAP) required for nuclear localization of SREBPs. Here, we use oligonucleotide arrays hybridized with RNA from livers of three lines of mice (transgenic for SREBP-1a, transgenic for SREBP-2, and knockout for SCAP) to identify genes that are likely to be direct targets of SREBPs in liver. Application of stringent combinatorial criteria to the transgenic/knockout approach allows identification of genes whose activities are likely controlled directly by the SREBPs.

Publication Title

Combined analysis of oligonucleotide microarray data from transgenic and knockout mice identifies direct SREBP target genes.

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon GSE102258
Combined analysis of oligonucleotide microarray data from transgenic and knockout mice identifies directSREBPtarget genes [MG_U74Cv2]
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Murine Genome U74A Version 2 Array (mgu74av2)

Description

The synthesis of fatty acids and cholesterol is regulated by three membrane-bound transcription factors: sterol regulatory element-binding proteins (SREBP)-1a, -1c, and -2. Their function in liver has been characterized in transgenic mice that overexpress each SREBP isoform and in mice that lack all three nuclear SREBPs because of gene knockout of SREBP cleavage-activating protein (SCAP) required for nuclear localization of SREBPs. Here, we use oligonucleotide arrays hybridized with RNA from livers of three lines of mice (transgenic for SREBP-1a, transgenic for SREBP-2, and knockout for SCAP) to identify genes that are likely to be direct targets of SREBPs in liver. Application of stringent combinatorial criteria to the transgenic/knockout approach allows identification of genes whose activities are likely controlled directly by the SREBPs.

Publication Title

Combined analysis of oligonucleotide microarray data from transgenic and knockout mice identifies direct SREBP target genes.

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon GSE51581
Gene expression profile of E. coli MG1655 cells grown at different growth rates in mixed substrates culture
  • organism-icon Escherichia coli
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix E. coli Genome 2.0 Array (ecoli2)

Description

E. coli MG155 cells were grown at different grwoth rates in mixed substrate culture. To facilitate different metaoblic status, cells adjust substrate consumption behavior which must be reflected in the gene expression profiles of metablism network. The metabolism network including the substrate transporter systems is our study focus.

Publication Title

Carbon catabolite repression correlates with the maintenance of near invariant molecular crowding in proliferating E. coli cells.

Sample Metadata Fields

Treatment

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accession-icon GSE99340
Transcriptome-based network analysis reveals renal cell type-specific dysregulation of hypoxia-associated transcripts
  • organism-icon Homo sapiens
  • sample-icon 402 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Transcriptome-based network analysis reveals renal cell type-specific dysregulation of hypoxia-associated transcripts.

Sample Metadata Fields

Specimen part

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accession-icon GSE99339
Transcriptome-based network analysis reveals renal cell type-specific dysregulation of hypoxia-associated transcripts [glomeruli]
  • organism-icon Homo sapiens
  • sample-icon 187 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Accumulating evidence suggests that dysregulation of hypoxia-regulated transcriptional mechanisms is involved in development of chronic kidney diseases (CKD). However, it remains unclear how hypoxia-induced transcription factors (HIFs) and subsequent biological processes contribute to CKD development and progression. In our study, genome-wide expression profiles of more than 200 renal biopsies from patients with different CKD stages revealed significant correlation of HIF-target genes with eGFR in glomeruli and tubulointerstitium. These correlations were positive and negative and in part compartment-specific. Microarrays of proximal tubular cells and podocytes with stable HIF1 and/or HIF2 suppression displayed cell type-specific HIF1/HIF2-dependencies as well as dysregulation of several pathways. WGCNA analysis identified gene sets that were highly coregulated within modules. Characterization of the modules revealed common as well as cell group- and condition-specific pathways, GO-Terms and transcription factors. Gene expression analysis of the hypoxia-interconnected pathways in patients with different CKD stages revealed an increased dysregulation with loss of renal function. In conclusion, our data clearly point to a compartment- and cell type-specific dysregulation of hypoxia-associated gene transcripts and might help to improve the understanding of hypoxia, HIF dysregulation, and transcriptional program response in CKD.

Publication Title

Transcriptome-based network analysis reveals renal cell type-specific dysregulation of hypoxia-associated transcripts.

Sample Metadata Fields

Specimen part

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)

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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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