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accession-icon GSE13138
A New Oxidative Sensing and Regulation Pathway Mediated by the MgrA Homologue SarZ in Staphylococcus aureus
  • organism-icon Staphylococcus aureus
  • sample-icon 11 Downloadable Samples
  • Technology Badge Icon Affymetrix S. aureus Genome Array (saureus)

Description

The S. aureus transcriptome was assessed for strains Newman (wild type) and Newman (sarZ) during both exponential (2hr) and early stationary (5hr) cell growth.

Publication Title

A new oxidative sensing and regulation pathway mediated by the MgrA homologue SarZ in Staphylococcus aureus.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE61484
Gamma radiation and HZE treatment of seedlings in Arabidopsis
  • organism-icon Arabidopsis thaliana
  • sample-icon 44 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

Plants exhibit a robust transcriptional response to gamma radiation which includes the induction of transcripts required for homologous recombination and the suppression of transcripts that promote cell cycle progression. Various DNA damaging agents induce different spectra of DNA damage as well as collateral damage to other cellular components and therefore are not expected to provoke identical responses by the cell.

Publication Title

High atomic weight, high-energy radiation (HZE) induces transcriptional responses shared with conventional stresses in addition to a core "DSB" response specific to clastogenic treatments.

Sample Metadata Fields

Age, Time

View Samples
accession-icon GSE8840
Effect of genomic imbalances on gene expression in rhabdomyosarcoma
  • organism-icon Homo sapiens
  • sample-icon 13 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Rhabdomyosarcoma (RMS) is the most common paediatric soft-tissue

Publication Title

Genomic imbalances in rhabdomyosarcoma cell lines affect expression of genes frequently altered in primary tumors: an approach to identify candidate genes involved in tumor development.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE10565
Identification of targets of transcription factor Trp63: primary keratinocytes
  • organism-icon Mus musculus
  • sample-icon 28 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Direct targets of the TRP63 transcription factor revealed by a combination of gene expression profiling and reverse engineering.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE10562
Induction of ERDNp63a via Tamoxifen in primary keratinocytes
  • organism-icon Mus musculus
  • sample-icon 13 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

Genome-wide identification of bona fide targets of transcription factors in mammalian cells is still a challenge. We present a novel integrated computational and experimental approach to identify direct targets of a transcription factor. This consists in measuring time-course (dynamic) gene expression profiles upon perturbation of the transcription factor under study, and in applying a novel reverse-engineering algorithm (TSNI) to rank genes according to their probability of being direct targets. Using primary keratinocytes as a model system, we identified novel transcriptional target genes of Trp63, a crucial regulator of skin development. TSNI-predicted Trp63 target genes were validated by Trp63 knockdown and by ChIP-chip to identify Trp63-bound regions in vivo. Our study revealed that short sampling times, in the order of minutes, are needed to capture the dynamics of gene expression in mammalian cells. We show that Trp63 transiently regulates a subset of its direct targets, thus highlighting the importance of considering temporal dynamics when identifying transcriptional targets. Using this approach, we uncovered a previously unsuspected transient regulation of the AP-1 complex by Trp63, through direct regulation of a subset of AP-1 components. The integrated experimental and computational approach described here is readily applicable to other transcription factors in mammalian systems and is complementary to genome-wide identification of transcription factor binding sites.

Publication Title

Direct targets of the TRP63 transcription factor revealed by a combination of gene expression profiling and reverse engineering.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE47065
Gene expression profiling of IR-/-, IGF-1R-/- (dKO) newborn epidermis.
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Analysis of newborn mouse epidermis lacking the expression of Insulin receptor (IR) and Insulin like growth factor 1 receptor (IGF-1R). Results show that IR/IGF-1R signalling control epidermal morphogenesis.

Publication Title

Insulin/IGF-1 controls epidermal morphogenesis via regulation of FoxO-mediated p63 inhibition.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE10563
Primary keratinocytes treated with Tamoxifen
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

Genome-wide identification of bona fide targets of transcription factors in mammalian cells is still a challenge. We present a novel integrated computational and experimental approach to identify direct targets of a transcription factor. This consists in measuring time-course (dynamic) gene expression profiles upon perturbation of the transcription factor under study, and in applying a novel reverse-engineering algorithm (TSNI) to rank genes according to their probability of being direct targets. Using primary keratinocytes as a model system, we identified novel transcriptional target genes of Trp63, a crucial regulator of skin development. TSNI-predicted Trp63 target genes were validated by Trp63 knockdown and by ChIP-chip to identify Trp63-bound regions in vivo. Our study revealed that short sampling times, in the order of minutes, are needed to capture the dynamics of gene expression in mammalian cells. We show that Trp63 transiently regulates a subset of its direct targets, thus highlighting the importance of considering temporal dynamics when identifying transcriptional targets. Using this approach, we uncovered a previously unsuspected transient regulation of the AP-1 complex by Trp63, through direct regulation of a subset of AP-1 components. The integrated experimental and computational approach described here is readily applicable to other transcription factors in mammalian systems and is complementary to genome-wide identification of transcription factor binding sites.

Publication Title

Direct targets of the TRP63 transcription factor revealed by a combination of gene expression profiling and reverse engineering.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE10564
Silencing of p63 (trp63) in primary keratinocytes via siRNA oligo transfection.
  • organism-icon Mus musculus
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

Genome-wide identification of bona fide targets of transcription factors in mammalian cells is still a challenge. We present a novel integrated computational and experimental approach to identify direct targets of a transcription factor. This consists in measuring time-course (dynamic) gene expression profiles upon perturbation of the transcription factor under study, and in applying a novel reverse-engineering algorithm (TSNI) to rank genes according to their probability of being direct targets. Using primary keratinocytes as a model system, we identified novel transcriptional target genes of Trp63, a crucial regulator of skin development. TSNI-predicted Trp63 target genes were validated by Trp63 knockdown and by ChIP-chip to identify Trp63-bound regions in vivo. Our study revealed that short sampling times, in the order of minutes, are needed to capture the dynamics of gene expression in mammalian cells. We show that Trp63 transiently regulates a subset of its direct targets, thus highlighting the importance of considering temporal dynamics when identifying transcriptional targets. Using this approach, we uncovered a previously unsuspected transient regulation of the AP-1 complex by Trp63, through direct regulation of a subset of AP-1 components. The integrated experimental and computational approach described here is readily applicable to other transcription factors in mammalian systems and is complementary to genome-wide identification of transcription factor binding sites.

Publication Title

Direct targets of the TRP63 transcription factor revealed by a combination of gene expression profiling and reverse engineering.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP093996
Zebrafish heart regeneration
  • organism-icon Danio rerio
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

The study compares gene expression profile at 20 days post amputation of the zebrafish ventricular heart between dusp6 mutant and WT siblings. Overall design: Ventricular resection was performed and 20 dpa, hearts were extracted.

Publication Title

Dusp6 attenuates Ras/MAPK signaling to limit zebrafish heart regeneration.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE75317
BRAF V600E mutant colorectal cancer subtypes based on gene expression
  • organism-icon Homo sapiens
  • sample-icon 112 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

BRAF V600E Mutant Colorectal Cancer Subtypes Based on Gene Expression.

Sample Metadata Fields

Sex, Age, Subject

View Samples
...

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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Developed by the Childhood Cancer Data Lab

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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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