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accession-icon GSE69317
Nos3-/- iPSCs model concordant signatures of in utero cardiac pathogenesis
  • organism-icon Mus musculus
  • sample-icon 42 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Nos3-/- iPSCs model concordant signatures of in utero cardiac pathogenesis.

Sample Metadata Fields

Specimen part, Time

View Samples
accession-icon GSE69316
Nos3-/- iPSCs model concordant signatures of in utero cardiac pathogenesis [iPSCs]
  • organism-icon Mus musculus
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Through genome-wide transcriptional comparisons, this study interrogates the capacity of iPSCs to accurately model pathogenic signatures of structural cardiac defects. Herein, we studied the molecular etiology of structural cardiac defects in Nos3-/- mice via transcriptional analysis of stage-matched embryonic and iPSC-derived tissues. In vitro comparisons of differentiated embryoid bodies were calibrated to in utero benchmarks of health and disease. Integrated systems biology analysis of WT and Nos3-/- transcriptional profiles revealed 50% concordant expression patterns between in utero embryonic and ex vivo iPSC-derived tissue. In particular, up-regulation of glucose metabolism (p-value = 3.95x10-12) and down-regulation of fatty acid metabolism (p-value = 6.71x10-12) highlight a bioenergetic signature of early Nos3 deficiency during cardiogenesis that can be recapitulated in iPSC-derived tissues. The in vitro concordance of early Nos3-/- disease signatures supports the utility of iPSCs as a cell-autonomous model of structural heart defects. Moreover, this study supports the use of iPSCs as a platform to pinpoint initial stages of cardiac pathogenesis.

Publication Title

Nos3-/- iPSCs model concordant signatures of in utero cardiac pathogenesis.

Sample Metadata Fields

Specimen part, Time

View Samples
accession-icon GSE69315
Nos3-/- iPSCs model concordant signatures of in utero cardiac pathogenesis [tissue]
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Through genome-wide transcriptional comparisons, this study interrogates the capacity of iPSCs to accurately model pathogenic signatures of structural cardiac defects. Herein, we studied the molecular etiology of structural cardiac defects in Nos3-/- mice via transcriptional analysis of stage-matched embryonic and iPSC-derived tissues. In vitro comparisons of differentiated embryoid bodies were calibrated to in utero benchmarks of health and disease. Integrated systems biology analysis of WT and Nos3-/- transcriptional profiles revealed 50% concordant expression patterns between in utero embryonic and ex vivo iPSC-derived tissue. In particular, up-regulation of glucose metabolism (p-value = 3.95x10-12) and down-regulation of fatty acid metabolism (p-value = 6.71x10-12) highlight a bioenergetic signature of early Nos3 deficiency during cardiogenesis that can be recapitulated in iPSC-derived tissues. The in vitro concordance of early Nos3-/- disease signatures supports the utility of iPSCs as a cell-autonomous model of structural heart defects. Moreover, this study supports the use of iPSCs as a platform to pinpoint initial stages of cardiac pathogenesis.

Publication Title

Nos3-/- iPSCs model concordant signatures of in utero cardiac pathogenesis.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE28084
Genome-wide Localization of SREBP-2 in Hepatic Chromatin Predicts a Novel Role in Autophagy
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Genome-wide localization of SREBP-2 in hepatic chromatin predicts a role in autophagy.

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon GSE28083
Expression data from CH/LE Mice
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

We are using genome-wide ChIP-seq with isoform-specific antibodies and chromatin from select tissues of mice challenged with different dietary conditions that enrich for specific SREBPs.

Publication Title

Genome-wide localization of SREBP-2 in hepatic chromatin predicts a role in autophagy.

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon E-MEXP-1344
Transcription profiling of Arabidopsis plants grown under diurnal conditions and transferred to cold conditions at different times of day to identify factors influencing cold-responsive genes
  • organism-icon Arabidopsis thaliana
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

Arabidopsis plants growing under diurnal conditions were transferred to cold of approximately one day duration, starting at different times of the day. All comparisons are of unreplicated pairs and are thus not designed to identify cold-responsive gens in isolation but are rather to supplement existing publicly available data. The overall aim was to use a diverse set of experiments to see which factors have the greatest influence on the identity of cold-responsive genes.

Publication Title

Disruption of the Arabidopsis circadian clock is responsible for extensive variation in the cold-responsive transcriptome.

Sample Metadata Fields

Age, Specimen part, Time

View Samples
accession-icon E-MEXP-1345
Transcription profiling of Arabdiposis plants before and after cold treatment using spike-in controls to allow measurement of absolute mRNA expression at the global level
  • organism-icon Arabidopsis thaliana
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

To address the neglected possibility for global mRNA changes in microarray experiments we developed a simple method to generate external controls for Affymetrix microarrays to allow these platforms to measure absolute mRNA expression at the global level. We used publicly available data to select probesets that never detect endogenous transcripts, and used PCR and IVT to generate synthetic mRNAs corresponding to them. After quality control and testing, these control transcripts were spiked into total RNA samples from plants before and after 24 h of cold treatment. Due to changes in the proportion of mRNA, these data reveal intensity-dependent bias in expression estimates based on standard all-gene normalizations. When not accounted for, this leads to false classification of the differential expression for thousands of genes.

Publication Title

Disruption of the Arabidopsis circadian clock is responsible for extensive variation in the cold-responsive transcriptome.

Sample Metadata Fields

Age, Specimen part

View Samples
accession-icon GSE15258
Whole blood transcript profiling of rheumatoid arthritis patients
  • organism-icon Homo sapiens
  • sample-icon 83 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The whole blood was collected pre-treatment from rheumatoid arthritis patients starting the anti_TNF therapy. All patients were nave to anti_TNFs. The disease activity was measured using the DAS28 score at the pre-treatment visit1 (DAS28_v1) and 14 weeks after treatment visit3 (DAS28_v3). The response to the therapy was evaluated using the EULAR [European League Against Rheumatism] definition of the response. The objective of the data analysis was to identify gene expression coorelating with response as well as to identify genes that differentiate responders versus non-responders pre-treatment. The results of this investigation identified 8 trainscripts that predict responders vs. non-responders with 89% accuracy.

Publication Title

Convergent Random Forest predictor: methodology for predicting drug response from genome-scale data applied to anti-TNF response.

Sample Metadata Fields

Specimen part, Disease, Disease stage

View Samples
accession-icon GSE104634
Analysis of microarray data reliability and pathway networks using experimental formalin-fixed paraffin-embedded tissue
  • organism-icon Mus musculus
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.1 ST Array (mogene21st)

Description

We assessed the usability of microarrays, which base on formalin-fixed paraffin-embedded (FFPE) tissue.

Publication Title

Systematic evaluation of RNA quality, microarray data reliability and pathway analysis in fresh, fresh frozen and formalin-fixed paraffin-embedded tissue samples.

Sample Metadata Fields

Specimen part, Treatment

View Samples
accession-icon GSE104568
Systematic evaluation of RNA quality and microarray data reliability in formalin-fixed paraffin-embedded and fresh frozen tissue samples
  • organism-icon Homo sapiens, Rattus norvegicus
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Systematic evaluation of RNA quality, microarray data reliability and pathway analysis in fresh, fresh frozen and formalin-fixed paraffin-embedded tissue samples.

Sample Metadata Fields

Specimen part, Disease

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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