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accession-icon SRP131203
Effects of Hif1a mutation and maternal diabetes on the offspring heart
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

We analysed the combined effects of exposure to maternal diabetes and disrupted HIF-1 signaling on the transcriptom in cardiac left ventricles of 12 weeks old male mice. This approach provides the information about the long term changes originating in utero due to maternal diabetes and inefficient response to hypoxia which develops as a result of hyperglycemia. The majority of changes were detected in Hif1a insufficient mice exposed to maternal diabetes. Overall design: Streptozotocin induced diabetic FVB females were mated with non-diabetic males with global heterozygous deletion of Hif1a (Hif1a+/-). Total RNA was extracted from the LV of the hearts of 12-week-old male offspring in biological triplicates per each group (wt, non-diabetic pregnancy; wt, diabetic pregnancy; Hif1a+/-, non-diabetic pregnancy; Hif1a+/-, diabetic pregnancy). RNA profiles were generated by deep sequencing using Illumina NextSeq.

Publication Title

Adverse effects of Hif1a mutation and maternal diabetes on the offspring heart.

Sample Metadata Fields

Sex, Age, Specimen part, Subject

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accession-icon GSE44781
Expression data for plant compensatory responses
  • organism-icon Arabidopsis thaliana
  • sample-icon 5 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

Plant compensatory responses depends on transcriptional reprogramming. We used microarray analysis to understand the differential gene expression pattern between clipped (herbivore browsed)

Publication Title

Overcompensation in response to herbivory in Arabidopsis thaliana: the role of glucose-6-phosphate dehydrogenase and the oxidative pentose-phosphate pathway.

Sample Metadata Fields

Specimen part

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accession-icon GSE87382
Dietary medium-chain saturated fatty acids induce gene expression of energy metabolism-related pathways in adipose tissue of abdominally obese subjects
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.1 ST Array (hugene11st)

Description

High MC-SFA intake resulted in a downregulation of gene expression of pathways related to complement system and inflammation, and an upregulation of gene expression of pathways related to citric acid cycle, electron transport chain and lipid metabolism in adipose tissue. Based on our results, we hypothesize that the beneficial effects of MC-SFAs on prevention of fat accumulation may be mediated by increases in gene expression related to energy metabolism in the adipose tissue. Additionally, decreases in inflammation-related gene expression in the adipose may potentially have beneficial effects in relation to cardiometabolic diseases.

Publication Title

Dietary medium-chain saturated fatty acids induce gene expression of energy metabolism-related pathways in adipose tissue of abdominally obese subjects.

Sample Metadata Fields

Sex, Age, Specimen part, Subject

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accession-icon GSE108649
Transcriptomic Predictors of Paradoxical Cryptococcosis-Associated Immune Reconstitution Inflammatory Syndrome
  • organism-icon Homo sapiens
  • sample-icon 162 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

Paradoxical cryptococcosis-associated immune reconstitution inflammatory syndrome

Publication Title

Transcriptomic Predictors of Paradoxical Cryptococcosis-Associated Immune Reconstitution Inflammatory Syndrome.

Sample Metadata Fields

Specimen part

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accession-icon GSE45194
Oncogenic Nras has a bimodal effect on hematopoietic stem cells promoting proliferation and self-renewal
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Pre-leukemic mutations are thought to promote clonal expansion of hematopoietic stem cells (HSCs) by increasing self-renewal and competitiveness. However, mutations that increase HSC proliferation tend to reduce competitiveness and self-renewal potential, raising the question of how a mutant HSC can sustainably outcompete wild-type HSCs. Activating mutations in NRAS are prevalent in human myeloproliferative disease and leukemia. Here we show that a single allele of oncogenic NrasG12D increases HSC proliferation but also increases reconstituting and self-renewal potential upon serial transplantation in irradiated mice, all without immortalizing HSCs or causing leukemia in our experiments. NrasG12D also confers long-term self-renewal potential upon multipotent progenitors. To explore the mechanism by which NrasG12D promotes HSC proliferation and self-renewal we assessed HSC cell cycle kinetics using H2B-GFP label retention. We found that NrasG12D had a bimodal effect on HSCs, increasing the proliferation of some HSCs while increasing the quiescence and competitiveness of other HSCs. One signal can therefore increase HSC proliferation, competitiveness, and self-renewal through a bimodal effect that promotes proliferation in some HSCs and quiescence in others.

Publication Title

Oncogenic Nras has bimodal effects on stem cells that sustainably increase competitiveness.

Sample Metadata Fields

Specimen part

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accession-icon GSE119061
Reovirus infection induces stabilization and up-regulation of cellular transcripts that encode regulators of TGF-beta signaling
  • organism-icon Mus musculus
  • sample-icon 46 Downloadable Samples
  • Technology Badge Icon Affymetrix Murine Genome U74A Version 2 Array (mgu74av2)

Description

We utilized oligonucleotide microarrays to measure cellular mRNA decay rates in mock- or reovirus-infected murine L929 cells to determine if changes in host mRNA expression are a consequence of reovirus-induced alterations in cellular mRNA stability.

Publication Title

Reovirus infection induces stabilization and up-regulation of cellular transcripts that encode regulators of TGF-β signaling.

Sample Metadata Fields

Cell line, Time

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accession-icon GSE15930
Gene expression signature of nave and in vitro activated CD8 T cells in response to IL-12 and Type I IFN
  • organism-icon Mus musculus
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Murine Genome U74A Version 2 Array (mgu74av2)

Description

Differentiation of naive CD8 T cells into cytotoxic effector cells requires three distinct signals- antigen (signal 1), costimulation -B7-1 (signal 2) and cytokine, either interleukin-12 or interferon-a/b (signal 3). Interaction of naive CD8 T cells with antigen and B7-1 programs cell division and proliferation whereas the presence of cytokines- IL-12 or IFNa/b promote survival, differentiation and memory establishment. In the absence of signal 3, the cells interacting with antigen/B7-1 undergo tolerance induction. The objective of this study was to elucidate the mechanisms how the provision of signal 3 promotes differentiation and averts tolerance induction in CD8 T cells. Trichostatin A is a pharmacological agent that inhibits histone deacetylase activity, hence regulating chromatin structure and gene expression and differentiation in many cell types. Gene signature profiles of IL-12, IFNa/b and trichostatin A stimulated cells were compared to elucidate the molecular mechanisms of gene regulation.

Publication Title

Gene regulation and chromatin remodeling by IL-12 and type I IFN in programming for CD8 T cell effector function and memory.

Sample Metadata Fields

Age, Specimen part, Time

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accession-icon GSE21031
Time-series of IL-6 stimulated primary mouse hepatocytes
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

External stimulations of cells by hormones, growth factors or cytokines activate signal transduction pathways that subsequently induce a rearrangement of cellular gene expression. The representation and analysis of changes in the gene response is complicated, and essentially consists of multiple layered temporal responses. In such situations, matrix factorization techniques may provide efficient tools for the detailed temporal analysis. Related methods applied in bioinformatics intentionally do not take prior knowledge into account. In signal processing, factorization techniques incorporating data properties like second-order spatial and temporal structures have shown a robust performance. However, large-scale biological data rarely imply a natural order that allows the definition of an autocorrelation function. We therefore develop the concept of graph-autocorrelation. We encode prior knowledge like transcriptional regulation, protein interactions or metabolic pathways as a weighted directed graph. By linking features along this underlying graph, we introduce a partial ordering of the samples to define an autocorrelation function. Using this framework as constraint to the matrix factorization task allows us to set up the fast and robust graph decorrelation (GraDe) algorithm. To analyze the alterations in the gene response in IL-6 stimulated primary mouse hepatocytes by GraDe, a time-course microarray experiment was performed. Extracted gene expression profiles show that IL-6 activates genes involved in cell cycle progression and cell division in a time-resolved manner. On the contrary, genes linked to metabolic and apoptotic processes are down-regulated indicating that IL-6 mediated priming rendered hepatocytes more responsive towards cell proliferation and reduces expenses for the energy household.

Publication Title

Knowledge-based matrix factorization temporally resolves the cellular responses to IL-6 stimulation.

Sample Metadata Fields

Specimen part, Treatment, Time

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accession-icon GSE53971
Wnt/beta-catenin-signaling in immortalized mouse adrenocortical cell line ATCL7
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.1 ST Array (mogene11st)

Description

In order to investigate genes regulated by Wnt/Beta-catenin-signaling in immortalized mouse adrenocortical cells, we treated a pair of ATCL7 cell cultures, one with BIO, a small molecule mimicking Wnt/Beta-catenin-signaling, the other with a control treatment. We repeated this 3 additional times resulting in 4 pairs of samples. The Wnt/beta-catenin pathway is not basally active in ATCL7 cells, nor do these cells appear to contain any mutations in the Wnt/Beta-catenin pathway. ATCL7 cells were grown under standard conditions at 37C in a humidified incubator containing 5% CO2. 250,000 ATCL7 cells per sample were treated with 0.5uM BIO (6-Bromoindirubin-3'-oxime) or 0.01% DMSO (v/v) for 24 hours, in DMEM:F12 growth media containing 100U/mL pencillin/streptomycin, 1X insulin-transferrin-selenium-X, 0.025% fetal bovine serum and 0.025% horse serum. Cells were harvested and RNA was extracted using an RNeasy Plus Mini Kit (Qiagen). Biotinylated cDNA were prepared according to the Ambion WT kit protocol from 250 ng total RNA (GeneAtlas WT Expression Kit User Manual P/N 702935 Rev. 3). We assayed the targets with Affymetrix Mouse Gene ST 1.1 strip arrays. We modeled the data using paired T-tests for each probe-set. We also supply a supplementary file holding the data and some statistical analysis, as well as probe-set annotation that we used at that time (users may wish to obtain new annotation though). We analyzed only 28944 probe-sets with category "main", "---", and "flmrna->unmapped" according to Affymetrix annotation.

Publication Title

Wnt signaling inhibits adrenal steroidogenesis by cell-autonomous and non-cell-autonomous mechanisms.

Sample Metadata Fields

Sex, Specimen part, Cell line, Treatment

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accession-icon GSE53981
Sf1+ mouse adrenocortical cells vs. Wnt-responsive mouse adrenocortical cells
  • organism-icon Mus musculus
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.1 ST Array (mogene11st)

Description

We sought to determine which gene transcripts are enriched in Wnt-responsive adrenocortical mouse cells compared to the entire adrenocortical mouse cell population in vivo. To this end, we employed transgenic reporter mice that label Wnt-responsive cells with GFP expression (TCF/Lef:H2B-GFP mice) or label all adrenocortical cells with GFP expression (Sf1:eGFP mice). GFP-positive adrenocortical cells were obtained from 6-week-old male TCF/Lef:H2B-GFP mice and Sf1:eGFP mice independently. 10 adrenals per genotype per sort were minced and digested by incubation in DMEM:F12 containing 0.1% collagenase/ 0.01% DNaseI solution for 1 h at 37C. A single cell suspension was obtained following mechanical dispersion, filtration through a 40 micron nylon cell strainer, centrifugation at 1500rpm for 5 min followed by re-suspension in sterile 1X PBS containing 10% cosmic calf serum and 10g/mL Propidium iodide. 10,000-50,000 viable GFP-positive cells were isolated via FACS using a BD FACSAria III cell sorter. RNA was extracted using an RNeasy Micro Kit (Qiagen) from 4 independent sorts per genotype. cDNA were prepared according to the NuGen WT-Pico V2 kit protocol from 5 ng total RNA (Ovation PicoSL WTA System V2 P/N 3312). Biotinylated single-stranded cDNA were prepared from 3ug of cDNA (Encore Biotin Module P/N 4200-12, 4200-60, 4200-A01). Targets were assayed on the Mouse Gene ST 1.1 strip arrays using the Affymetrix Gene Atlas system (software version 1.0.4.267). One TCF/Lef:H2B-GFP array was deemed low-quality and discarded. Two-sample T-tests were used to compare the two groups of samples. We also supply a supplementary file holding the data and some statistical analysis, as well as probe-set annotation that we used at that time (users may wish to obtain new annotation though). We analyzed only 28944 probe-sets with category "main", "---", and "flmrna->unmapped" according to Affymetrix annotation.

Publication Title

Wnt signaling inhibits adrenal steroidogenesis by cell-autonomous and non-cell-autonomous mechanisms.

Sample Metadata Fields

Sex, Age, 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)

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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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