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accession-icon GSE31369
Expression profiling of rpb1-12XWTCTD and rpb1-12XS2ACTD fission yeast strains.
  • organism-icon Schizosaccharomyces pombe
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome 2.0 Array (yeast2)

Description

In fission yeast, the nuclear-localized Lsk1p-Lsc1p-Lsg1p cyclin dependent kinase complex is required for the reliable execution of cytokinesis and is also required for Ser-2 phosphorylation RNA pol II carboxy terminal domain.

Publication Title

Global gene expression analysis of fission yeast mutants impaired in Ser-2 phosphorylation of the RNA pol II carboxy terminal domain.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE33228
Expression profiling of wild-type and set3D fission yeast strains
  • organism-icon Schizosaccharomyces pombe
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome 2.0 Array (yeast2)

Description

In fission yeast the SET domain protein, Set3p is required for the reliable execution of cytokinesis.

Publication Title

The SET domain protein, Set3p, promotes the reliable execution of cytokinesis in Schizosaccharomyces pombe.

Sample Metadata Fields

Treatment

View Samples
accession-icon GSE67458
The MEF2B Regulatory Network
  • organism-icon Homo sapiens
  • sample-icon 21 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

MEF2B mutations in non-Hodgkin lymphoma dysregulate cell migration by decreasing MEF2B target gene activation.

Sample Metadata Fields

Cell line, Treatment

View Samples
accession-icon GSE67417
The MEF2B Regulatory Network - Expression microarray data
  • organism-icon Homo sapiens
  • sample-icon 21 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

Myocyte enhancer factor 2B (MEF2B) is a transcription factor with somatic mutation hotspots at K4, Y69 and D83 in diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL). The recurrence of these mutations indicates that they may drive lymphoma development. However, inferring the mechanisms by which they may drive lymphoma development was complicated by our limited understanding of MEF2Bs normal functions. To expand our understanding of the cellular activities of wildtype (WT) and mutant MEF2B, I developed and addressed two hypotheses: (1) identifying genes regulated by WT MEF2B will allow identification of cellular phenotypes affected by MEF2B activity and (2) contrasting the DNA binding sites, effects on gene expression and effects on cellular phenotypes of mutant and WT MEF2B will help refine hypotheses about how MEF2B mutations may contribute to lymphoma development. To address these hypotheses, I first identified genome-wide WT MEF2B binding sites and transcriptome-wide gene expression changes mediated by WT MEF2B. Using these data I identified and validated novel MEF2B target genes. I found that target genes of MEF2B included the cancer genes MYC, TGFB1, CARD11, NDRG1, RHOB, BCL2 and JUN. Identification of target genes led to findings that WT MEF2B promotes expression of mesenchymal markers, promotes HEK293A cell migration, and inhibits DLBCL cell chemotaxis. I then investigated how K4E, Y69H and D83V mutations change MEF2Bs activity. I found that K4E, Y69H and D83V mutations decreased MEF2B DNA binding and decreased MEF2Bs capacity to promote gene expression in both HEK293A and DLBCL cells. These mutations also reduced MEF2Bs capacity to alter HEK293A and DLBCL cell movement. From these data, I hypothesize that MEF2B mutations may promote DLBCL and FL development by reducing expression of MEF2B target genes that would otherwise function to help confine germinal centre B-cells to germinal centres. Overall, my research demonstrates how observations from genome-scale data can be used to identify cellular effects of candidate driver mutations. Moreover, my work provides a unique resource for exploring the role of MEF2B in cell biology: I map for the first time the MEF2B regulome, demonstrating connections between a relatively understudied transcription factor and genes significant to oncogenesis.

Publication Title

MEF2B mutations in non-Hodgkin lymphoma dysregulate cell migration by decreasing MEF2B target gene activation.

Sample Metadata Fields

Cell line, Treatment

View Samples
accession-icon SRP056742
The MEF2B Regulatory Network - RNA-seq data
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Myocyte enhancer factor 2B (MEF2B) is a transcription factor with somatic mutation hotspots at K4, Y69 and D83 in diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL). The recurrence of these mutations indicates that they may drive lymphoma development. However, inferring the mechanisms by which they may drive lymphoma development was complicated by our limited understanding of MEF2B’s normal functions. To expand our understanding of the cellular activities of wildtype (WT) and mutant MEF2B, I developed and addressed two hypotheses: (1) identifying genes regulated by WT MEF2B will allow identification of cellular phenotypes affected by MEF2B activity and (2) contrasting the DNA binding sites, effects on gene expression and effects on cellular phenotypes of mutant and WT MEF2B will help refine hypotheses about how MEF2B mutations may contribute to lymphoma development. To address these hypotheses, I first identified genome-wide WT MEF2B binding sites and transcriptome-wide gene expression changes mediated by WT MEF2B. Using these data I identified and validated novel MEF2B target genes. I found that target genes of MEF2B included the cancer genes MYC, TGFB1, CARD11, NDRG1, RHOB, BCL2 and JUN. Identification of target genes led to findings that WT MEF2B promotes expression of mesenchymal markers, promotes HEK293A cell migration, and inhibits DLBCL cell chemotaxis. I then investigated how K4E, Y69H and D83V mutations change MEF2B’s activity. I found that K4E, Y69H and D83V mutations decreased MEF2B DNA binding and decreased MEF2B’s capacity to promote gene expression in both HEK293A and DLBCL cells. These mutations also reduced MEF2B’s capacity to alter HEK293A and DLBCL cell movement. From these data, I hypothesize that MEF2B mutations may promote DLBCL and FL development by reducing expression of MEF2B target genes that would otherwise function to help confine germinal centre B-cells to germinal centres. Overall, my research demonstrates how observations from genome-scale data can be used to identify cellular effects of candidate driver mutations. Moreover, my work provides a unique resource for exploring the role of MEF2B in cell biology: I map for the first time the MEF2B ‘regulome’, demonstrating connections between a relatively understudied transcription factor and genes significant to oncogenesis. Overall design: RNA-seq was performed on cells expressing V5 tagged WT or mutant MEF2B and on empty vector control cells. One biological replicates was performed on cell treated with either ionomycin or a solvent-only control.

Publication Title

MEF2B mutations in non-Hodgkin lymphoma dysregulate cell migration by decreasing MEF2B target gene activation.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE14363
Expression data from adipocytes and white adipose tissue of mice maintained on normal chow or high fat diet
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

We studied the role of the cAMP responsive factor CREB in promoting insulin resistance following its activation in adipose under obese conditions

Publication Title

Adipocyte CREB promotes insulin resistance in obesity.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE1639
Rpd3 and histone H3 and H4 deletions/mutations
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome S98 Array (ygs98)

Description

Signal intensity data for rpd3 delete, H3delta(1-28), H3(K4,9,14,18,23,27Q), H4delta(2-26), H4(K5,8,12,16Q), rpd3 delete H3delta(1-28), and rpd3 delete H4(K5,8,12,16Q) yeast grown in rich (YPD) media

Publication Title

Genome-wide analysis of the relationship between transcriptional regulation by Rpd3p and the histone H3 and H4 amino termini in budding yeast.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE21360
Whole-genome microarray analysis of primary, secondary, tertiary and quaternary memory CD8 T cells
  • organism-icon Mus musculus
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The transcriptome of naive OT-I T cells was compared to memory CD8 T cells after 1, 2, 3, or 4 infection with ovalbumin expressing Listeria monocytogenes (LM-OVA).

Publication Title

Repetitive antigen stimulation induces stepwise transcriptome diversification but preserves a core signature of memory CD8(+) T cell differentiation.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE43685
Early growth response protein-1 coordinates lipotoxicity-associated placental inflammation: Role in Maternal Obesity
  • organism-icon Homo sapiens
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Maternal obesity during pregnancy leads to a pro-inflammatory milieu in the placenta. We conducted a global transcriptomic profiling in BeWo cells following palmitic acid (PA, 500 uM) and/or TNF-alpha (10 ng/ml) treatment for 24 h. Microarray analysis revealed that placental cytotrophoblasts increased expression of genes related to inflammation, stress response and immediate-early factors in response to plamitic acid, TNF-alpha or a combination of both. Our results suggest that fatty acids and inflammatory cytokines induce inflammation in placental cells via activation of JNK-Egr-1 signaling.

Publication Title

Early growth response protein-1 mediates lipotoxicity-associated placental inflammation: role in maternal obesity.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon SRP059956
Identification of promoters and enhancers induced by carbon nanotube exposure
  • organism-icon Mus musculus
  • sample-icon 11 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Cap Analysis of Gene Expression (CAGE) applied on carbon nanotubes exposed lung tissue to identify alternative promoter and enhancer usage after 24 hr of exposure in order to investigate the nature of the response observed in these mice. Overall design: C57BL/6 mice was exposed to vehicle or multi walled carbon nanotubes (MWCNT) by intratracheal installation. 5 mice was exposed to 162 ug of MWCNTs ( XNRI-7; lot05072001K28, Hadoga Chemical industry (formerly known as Mitsui) disolved in 0.9% NaCl and 10% v/v cellfree cellular broncho alveolar lavage (BAL) fluid collected from C57BL/6 mice. 6 mice was exposed to the previously decribed saline/BAL solution but without carbon nanotubes.

Publication Title

Identification of Gene Transcription Start Sites and Enhancers Responding to Pulmonary Carbon Nanotube Exposure in Vivo.

Sample Metadata Fields

No sample metadata fields

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)

fund-icon Fund the CCDL

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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