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accession-icon SRP148477
Single cell RNA sequencing of B cells from allergic individuals
  • organism-icon Homo sapiens
  • sample-icon 973 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

IgE antibodies mediate the symptoms of allergic reactions, yet these antibodies and the cells that produce them remain enigmatic due to their scarcity in humans. To address this, we have isolated single B cells of all isotypes, including rare IgE producing B cells, from the peripheral blood of food allergic individuals. Using single cell RNA sequencing (scRNA-seq) we have characterized the gene expression, splicing, and heavy and light chain antibody sequences of these cells.

Publication Title

High-affinity allergen-specific human antibodies cloned from single IgE B cell transcriptomes.

Sample Metadata Fields

Sex, Age, Specimen part, Disease

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accession-icon SRP150461
Transcriptome analysis of Casz1 conditional mutant progenitors at postnatal day 2
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Transcriptome analysis of Casz1 was performed using litters of postnatal day 2 retinas from crosses between Casz1Flox/Flox; R26-Stop-EYFP and Casz1Flox/Flox; IKCre-A; R26-Stop-EYFP. The IK-A Cre driver is described in Tarchini et al., Dev Dyn 241(12):1973-85. EYFP marks Cre expressing (and therefore cKO) cells. Cells were incubated for 30 min in RGM serum-free medium described in Cayouette et al., Neuron 40(5):897, supplemented with Hoechst 33342 (Invitrogen), and 4N cells were sorted using a MOFLO cytometer (Beckman) based on Hoechst, GFP expression, and propidium iodide exclusion. Overall design: Cells were sorted directly into lysis buffer on ice and RNA was immediately extracted using RNeasy mini columns (Qiagen). Two independent experiments were performed, and the RNA samples were processed in parallel. RNA amplification was performed using Truseq PE Cluster kit v3 PE50 (Illumina). Deep sequencing was performed using Truseq stranded mRNA (Illumina) with mRNA enrichment and strand-specific parameters, using a Hiseq 2000 instrument (Illumina).

Publication Title

Casz1 controls higher-order nuclear organization in rod photoreceptors.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE29912
The effect of GW3965 and dexamethasone on gene expression of rat livers
  • organism-icon Rattus norvegicus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

GLUCOCORTICOIDS are steroid hormones that strongly influence intermediary carbohydrate metabolism by increasing the transcription rate of glucose-6-phosphatase (G6Pase) a key enzyme of gluconeogenesis, and suppress the immune system which makes them one of the most important therapeutic agents in the treatment of allergic, autoimmune and inflammatory diseases. The biologic actions of circulating glucocorticoids are transmitted to the cells nucleus by the glucocorticoid receptor (GR). The nuclear liver X receptors (LXRs) bind to cholesterol metabolites, heterodimerize with the retinoid X receptor (RXR), and regulate the cholesterol turnover, the hepatic glucose metabolism by decreasing the expression of G6Pase, and repress a set of inflammatory genes in immune cells. The aim of this study is to evaluate the crosstalk between the GR- and LXR-mediated signaling systems. Transient transfection-based reporter assays and gene silencing methods using siRNAs for LXRs showed that overexpression/ligand (GW3965) activation of LXRs/RXRs repressed GR-stimulated transactivation of certain glucocorticoid response element (GRE)-driven promoters in a gene-specific fashion. Activation of LXRs by GW3965 attenuated dexamethasone-stimulated elevation of circulating glucose in rats and suppressed dexamethasone-induced mRNA expression of hepatic glucose-6-phosphatase (G6Pase) in rats, mice and human hepatoma HepG2 cells. In microarray transcriptomic analysis of rat liver, GW3965 differentially regulated glucocorticoid-induced transcriptional activity of about 15% of endogenous glucocorticoid-responsive genes. Mechanistically, and in vitro chromatin immunoprecipitation assay, we found that LXR/RXR bound GREs and inhibited GR binding to these DNA sequences in a gene-specific fashion. These novel results were further confirmed in in vivo binding assays, and in gel mobility shift assays, where recombinant LXR/RXR proteins were used to examine their interaction with classic or G6Pase GREs. We propose that administration of LXR agonists may be beneficial in glucocorticoid treatment- or stress-associated dysmetabolic states by directly attenuating the transcriptional activity of the GR on glucose and/or lipid metabolism.

Publication Title

Liver x receptors regulate the transcriptional activity of the glucocorticoid receptor: implications for the carbohydrate metabolism.

Sample Metadata Fields

Specimen part

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accession-icon GSE70840
Transcriptomic response of rice leaves to 30% CO2 concentration
  • organism-icon Oryza sativa
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Rice Genome Array (rice)

Description

Analysis of rice leaves (V2 stage) in response to a short treatment with very high CO2 concentration in the dark, using standard atmosphere as control.

Publication Title

High CO2 concentration as an inductor agent to drive production of recombinant phytotoxic antimicrobial peptides in plant biofactories.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE46449
Expression data from Patients with Bipolar (BP) Disorder and Matched Control Subjects
  • organism-icon Homo sapiens
  • sample-icon 84 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

There are currently no biological tests that differentiate patients with bipolar disorder (BPD) from healthy controls. While there is evidence that peripheral gene expression differences between patients and controls can be utilized as biomarkers for psychiatric illness, it is unclear whether current use or residual effects of antipsychotic and mood stabilizer medication drives much of the differential transcription. We therefore tested whether expression changes in first-episode, never-medicated bipolar patients, can contribute to a biological classifier that is less influenced by medication and could potentially form a practicable biomarker assay for BPD.

Publication Title

Utilization of never-medicated bipolar disorder patients towards development and validation of a peripheral biomarker profile.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon E-MEXP-750
Transcription profiling of human CD4 T cell subsets isolated from peripheral blood and palatine tonsils
  • organism-icon Homo sapiens
  • sample-icon 42 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133B Array (hgu133b), Affymetrix Human Genome U133A Array (hgu133a)

Description

Comparatative gene expression analysis for CD4 T cell subsets isolated from peripheral blood and palatine tonsils

Publication Title

A methodology for global validation of microarray experiments.

Sample Metadata Fields

Specimen part

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accession-icon GSE467
Response of rat muscle to acute resistance exercise
  • organism-icon Rattus norvegicus
  • sample-icon 36 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome U34 Array (rgu34a)

Description

To further understand molecular mechanisms underlying skeletal muscle hypertrophy, expression profiles of translationally and transcriptionally regulated genes were characterized following an acute bout of maximally activated eccentric contractions. Experiments demonstrated that translational mechanisms contribute to acute gene expression changes following high resistance contractions with two candidate mRNAs, basic fibroblast growth factor (bFGF) and elongation factor-1 alpha (EF1alpha), targeted to the heavier polysomal fractions after a bout of contractions. Gene profiling was performed using Affymetrix Rat U34A GeneChips with either total RNA or polysomal RNA at one and six hours following contractions. There were 18 genes that changed expression at one hour and 70 genes that were different (60 genes increased:10 genes decreased)at six hours after contractions. The model from this profiling suggests that following high resistance contractions skeletal muscle shares a common growth profile with proliferating cells exposed to serum. This cluster of genes can be classified as "growth" genes and is commonly associated with progression of the cell cycle. However, a unique aspect was that there was induction of a cluster of tumour suppressor or antigrowth genes. We propose that this cluster of "antigrowth" genes is induced by the stress of contractile activity and may act to maintain skeletal muscle in the differentiated state. From the profiling results, further experiments determined that p53 levels increased in skeletal muscle at 6 h following contractions. This novel finding of p53 induction following exercise also demonstrates the power of expression profiling for identification of novel pathways involved in the response to muscle contraction.

Publication Title

Response of rat muscle to acute resistance exercise defined by transcriptional and translational profiling.

Sample Metadata Fields

No sample metadata fields

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accession-icon E-MEXP-774
Transcription profiling by array of mouse preadipocytes after treatment with dexamethasone
  • organism-icon Mus musculus
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Murine Genome U74A Version 2 Array (mgu74av2)

Description

DNA microarrays are popular tools for measuring gene expression of biological samples. This ever increasing popularity is ensuring that a large number of microarray studies are conducted, many of which with data publicly available for mining by other investigators. Under most circumstances, validation of differential expression of genes is performed on a gene to gene basis. Thus, it is not possible to generalize validation results to the remaining majority of non-validated genes or to evaluate the overall quality of these studies. <br></br> We have devised an approach for the global validation of DNA microarray experiments that will allow researchers to evaluate the general quality of their experiment and to extrapolate validation results of a subset of genes to the remaining non-validated genes. We applied this method to a microarray experiment validated with quantitative real time polymerase chain reaction. The experiment consists of three biological replicate treatments of mouse 3T3-L1 preadipocytes with the steroid hormone dexamethasone for 3 hours. Total RNA was extracted from each of our three treatment and three control samples, and we labeled and hybridized five aliquots of each sample to Affymetrix MGU74Av2 microarrays, for a total of 30 microarrays.<br></br> We illustrate why the popular strategy of selecting only the most differentially expressed genes for validation generally fails as a global validation strategy and propose random-stratified sampling as a better gene selection method. We also illustrate shortcomings of often-used validation indices such as overlap of significant effects and the correlation coefficient and recommend the concordance correlation coefficient (CCC) as an alternative.

Publication Title

A methodology for global validation of microarray experiments.

Sample Metadata Fields

Cell line, Subject, Compound

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accession-icon GSE2952
Adipose tissue gene expression profiles of lean, insulin resistant, obese, and diabetic mice.
  • organism-icon Mus musculus
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Murine 11K SubA Array (mu11ksuba)

Description

The expression of adipogenic genes is decreased in obesity and diabetes mellitus

Publication Title

The expression of adipogenic genes is decreased in obesity and diabetes mellitus.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE22647
Adenosine 5 monophosphate-activated protein kinase regulates metabolic actions of glucocorticoids by phosphorylating the glucocorticoid receptor through p38 mitogen-activated protein kinase.
  • organism-icon Rattus norvegicus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

Glucocorticoids play central roles in the regulation of energy metabolism by shifting it toward catabolism, while AMPK is the master regulator of energy homeostasis, sensing energy depletion and stimulating pathways of increasing fuel uptake and saving on peripheral supplies. We showed here that AMPK regulates glucocorticoid actions on carbohydrate metabolism by targeting the glucocorticoid receptor (GR) and modifying transcription of glucocorticoid-responsive genes in a tissue- and promoter-specific fashion. Activation of AMPK in rats reversed glucocorticoid-induced hepatic steatosis and suppressed glucocorticoid-mediated stimulation of glucose metabolism. Transcriptomic analysis in the liver suggested marked overlaps between the AMPK and glucocorticoid signaling pathways directed mostly from AMPK to glucocorticoid actions. AMPK accomplishes this by phosphorylating serine 211 of the human GR indirectly through phosphorylation and consequent activation of p38 MAPK and by altering attraction of transcriptional coregulators to DNA-bound GR. In human peripheral mononuclear cells, AMPK mRNA expression positively correlated with that of glucocorticoid-responsive GILZ, which correlated also positively with the body mass index of subjects. These results indicate that the AMPK-mediated energy control system modulates glucocorticoid action at target tissues. Since increased action of glucocorticoids is associated with development of metabolic disorders, activation of AMPK could be a promising target for developing pharmacologic interventions to these pathologies.

Publication Title

AMPK regulates metabolic actions of glucocorticoids by phosphorylating the glucocorticoid receptor through p38 MAPK.

Sample Metadata Fields

Sex

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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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