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accession-icon GSE12711
Differential gene expression profiles are dependent upon method of peripheral blood RNA isolation
  • organism-icon Homo sapiens
  • sample-icon 45 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

Differential gene expression profiles are dependent upon method of peripheral blood collection and RNA isolation.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE12709
Differential gene expression profiles are dependent upon method of peripheral blood RNA isolation (PHA)
  • organism-icon Homo sapiens
  • sample-icon 25 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

RNA isolation and purification steps greatly influence the results of gene expression profiling. There are two commercially available products for whole blood RNA collection, PAXgene and Tempus blood collection tubes, and each comes with their own RNA purification method. We examined the impact of RNA isolation methods on gene expression profiles.

Publication Title

Differential gene expression profiles are dependent upon method of peripheral blood collection and RNA isolation.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE12710
Differential gene expression profiles are dependent upon method of peripheral blood RNA isolation (direct, heparin)
  • organism-icon Homo sapiens
  • sample-icon 13 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

RNA isolation and purification steps greatly influence the results of gene expression profiling. There are two commercially available products for whole blood RNA collection, PAXgene and Tempus blood collection tubes, and each comes with their own RNA purification method. We examined the impact of RNA isolation methods on gene expression profiles.

Publication Title

Differential gene expression profiles are dependent upon method of peripheral blood collection and RNA isolation.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP159271
Innate mesenchymal TLR4/MyD88 signals promote spontaneous intestinal tumorigenesis
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIon Torrent Proton

Description

This study shows that the TLR4/MyD88 pathway in intestinal mesenchymal cells promotes intestinal carcinogenesis in the APCmin mouse model. Overall design: 3' RNA-Seq (QuantSeq) profiling of ColVIcre+ wt and MyD88 knockout primary mouse intestinal mesenchymal cells before and after treatment with LPS for 6 hours. 3 replicates per group.

Publication Title

Innate Sensing through Mesenchymal TLR4/MyD88 Signals Promotes Spontaneous Intestinal Tumorigenesis.

Sample Metadata Fields

Specimen part, Cell line, Treatment, Subject

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accession-icon GSE9915
Transcript profiling of Lr1- and Lr34-mediated leaf rust resistance in wheat
  • organism-icon Triticum aestivum
  • sample-icon 35 Downloadable Samples
  • Technology Badge Icon Affymetrix Wheat Genome Array (wheat)

Description

The wheat gene Lr34 confers partial resistance to all races of Puccinia triticina, the causal agent of wheat leaf rust. However, the biological basis for the exceptional durability of Lr34 is unclear. The Affymetrix wheat genome array was used to identify wheat genes differentially expressed in a compatible interaction (Tc), an R-gene mediated incompatible interaction (Tc-Lr1), and a race non-specific resistance interaction (Tc-Lr34) in response to infection challenge by P. triticina race 1 at anthesis. Transcriptome interrogation was conducted by comparing mock- and P. triticina-inoculated leaves harvested at 3 and 7 days post inoculation (dpi).

Publication Title

Lr34-mediated leaf rust resistance in wheat: transcript profiling reveals a high energetic demand supported by transient recruitment of multiple metabolic pathways.

Sample Metadata Fields

No sample metadata fields

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accession-icon E-MEXP-958
Transcription profiling of human wild type and deltaTOR-containing hepatocyte-like cells to compare total RNA and polysome-bound RNA populations upon hepatocytic differentiation
  • organism-icon Homo sapiens
  • sample-icon 22 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Comparison of Total RNA and Polysome-bound RNA populations in deltaTOR containing cells and control cells upon hepatocyitc differentiation.

Publication Title

Mammalian target of rapamycin activation impairs hepatocytic differentiation and targets genes moderating lipid homeostasis and hepatocellular growth.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon GSE26525
Expression data analyzed with LPIA in A549 lung carcinoma cells treated with geldanamycin.
  • organism-icon Homo sapiens
  • sample-icon 13 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The statsitcal model, latent pathway identification analysis (LPIA), was implemented for the analysis of A549 lung carcinoma cells treated with geldanamycin. Control and treated samples were assayed with Affymetrix HG_U133_plus_2 arrays and analyzed using LPIA. LPIA looks for statistically signcant evidence of dysregulation in a network of pathways constructed in a manner that explicitly links pathways through their common function in the cell. Geldanamycin (geld) is known to inhibit the molecular chaperone protein, Hsp90, and plays a role in preventing the malignant transformation and proliferation of healthy cells during oncogenesis. LPIA successfully identified pathways specific to geldanamycin effects at the gene transcription level.

Publication Title

Network-based prediction for sources of transcriptional dysregulation using latent pathway identification analysis.

Sample Metadata Fields

Specimen part, Cell line, Time

View Samples
accession-icon GSE42771
Microarray gene expression profiling of kinase-dependent and kinase-independent effects of GRK2
  • organism-icon Homo sapiens
  • sample-icon 11 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The ubiquitously expressed G-protein-coupled receptor kinase 2 (GRK2, ADRBK1) is an indispensable kinase involved in growth, differentiation and development. Exaggerated GRK2 activity plays a major pathophysiological role in the development of cardiovascular diseases such as heart failure and hypertension. GRK2 exerts its functions by kinase-dependent and kinase-independent effects. To assess the differential impact of GRK2 on cellular signalling we established HEK cell clones with over-expression of comparable protein levels of GRK2 or the kinase-deficient GRK2-K220R mutant, respectively. HEK cells were either cultured in vitro or expanded in vivo, in immunodeficient NOD.Scid mice to discriminate between in vitro and in vivo effects of GRK2. Whole genome microarray gene expression profiling was performed of cultured HEK cells and of NOD.Scid mouse-expanded HEK clones. As an additional control, cells were re-cultured in vitro after expansion in NOD.Scid mice.

Publication Title

Inhibition of G-protein-coupled receptor kinase 2 (GRK2) triggers the growth-promoting mitogen-activated protein kinase (MAPK) pathway.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE37127
Positive and Negative Spatial Gradients of High Wall Shear Stress Have Different Effects on Endothelial Gene Expression
  • organism-icon Bos taurus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Bovine Genome Array (bovine)

Description

Intracranial aneurysms tend to form at bifurcation apices, where flow impingement causes high frictional force (or wall shear stress, WSS) and flow acceleration and deceleration that create positive and negative streamwise gradients in WSS (WSSG), respectively. In vivo, intracranial aneurysms initiate under high WSS and positive WSSG. Little is known about the responses of endothelial cells (ECs) to either positive or negative WSSG under high WSS conditions. We used cDNA microarrays to profile EC gene expression exposed to positive WSSG vs. negative WSSG for 24 hours in a flow chamber with converging and diverging channels, respectively. WSS varied between 3.5 and 28.4 Pa in each gradient channel. GO and biological pathway analysis indicated that positive WSSG favored proliferation, apoptosis, and extracellular matrix processing while decreasing expression of pro-inflammatory genes. A subset of characteristic genes was validated using qPCR: Genes for ADAMTS1, CKAP2 and NCEH1 had higher expression under positive WSSG compared to negative WSSG while TAGLN, THBS1, VCAM1, CCL2, and CSF2 had lower expression. To determine if these patterns of expression are also exhibited in vivo, we tested whether the extracellular matrix related protein ADAMTS1 and proliferation were modulated by positive WSSG during intracranial aneurysm initiation. An aneurysm was induced at the basiliar terminus in rabbits by bilateral carotid ligation. WSSG at the bifurcation was determined by computational fluid dynamic simulations from 3D angiography and mapped on immunofluorescence staining for ADAMTS1 and the proliferation marker, Ki-67. Endothelial ADAMTS1 protein and Ki-67 were significantly higher in regions with positive WSSG compared to adjacent sites where WSSG was negative. Our results indicate that WSSG can elicit distinct gene expression profiles in ECs. Increased matrix processing and high levels of proliferation under positive WSSG could contribute to intracranial aneurysm initiation by causing transient gaps in the endothelium or disrupting EC signals to smooth muscle cells.

Publication Title

Differential gene expression by endothelial cells under positive and negative streamwise gradients of high wall shear stress.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE27859
Inflammation switches the differentiation program of Ly6Chi monocytes from anti-inflammatory macrophages to inflammatory dendritic cells in the colon
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Dendritic cells (DCs) and macrophages (MPs) are important for immunological homeostasis in the colon. We found that F4/80hi CX3CR1hi (CD11b+CD103-) cells account for 80% of mouse colonic lamina propria (cLP) MHC-IIhi cells. Both CD11c+ and CD11c- cells within this population were identified as MPs based on multiple criteria, including a MP transcriptome revealed by microarray analysis. These MPs constitutively released high levels of IL-10 at least partially in response to the microbiota via an MyD88-independent mechanism. In contrast, cells expressing low to intermediate levels of F4/80 and CX3CR1 were identified as DCs, based on phenotypic and functional analysis and comprise three separate CD11chi cell populations: CD103+CX3CR1-CD11b- DCs, CD103+CX3CR1-CD11b+ DCs and CD103-CX3CR1intCD11b+ DCs. In non-inflammatory conditions, Ly6Chi monocytes differentiated primarily into CD11c+, but not CD11c- MPs. In contrast, during colitis, Ly6Chi monocytes massively invaded the colon and differentiated into pro-inflammatory CD103-CX3CR1intCD11b+ DCs, which produced high levels of IL-12, IL-23, iNOS and TNF. These findings demonstrate the dual capacity of Ly6Chi blood monocytes to differentiate into either regulatory MPs or inflammatory DCs in the colon, and that the balance of these immunologically antagonistic cell types is dictated by microenvironmental conditions.

Publication Title

Inflammation switches the differentiation program of Ly6Chi monocytes from antiinflammatory macrophages to inflammatory dendritic cells in the colon.

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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