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accession-icon GSE34936
NOD genetic variation influences ab/gd lineage decisions when TCRa is prematurely expressed, but not the process of negative selection.
  • organism-icon Mus musculus
  • sample-icon 59 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

Thymic negative selection is functional in NOD mice.

Sample Metadata Fields

Sex, Age

View Samples
accession-icon GSE34934
Expression data from BDC2.5 TCR Tg, preselected Rag-/-.B6 and Rag-/-.NOD.H2b thymocytes upon antigenic stimulation
  • organism-icon Mus musculus
  • sample-icon 43 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The aim of this study was to quantify the impact of NOD genetic vatiation on thymic negative selection transcriptional programs.

Publication Title

Thymic negative selection is functional in NOD mice.

Sample Metadata Fields

Sex, Age

View Samples
accession-icon GSE34935
Expression data from BDC2.5 TCR Tg thymocytes on B6g7 and NOD background
  • organism-icon Mus musculus
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The aim of this study was to quantify the impact of NOD genetic vatiation on the transcriptional programs induced by the alpha beta-TCR at the DN to DP transition in the BDC2.5 TCR Tg model

Publication Title

Thymic negative selection is functional in NOD mice.

Sample Metadata Fields

Sex, Age

View Samples
accession-icon GSE37535
PPAR is a major driver of the accumulation and phenotype of adipose-tissue Treg cells
  • organism-icon Mus musculus
  • sample-icon 27 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

PPAR-γ is a major driver of the accumulation and phenotype of adipose tissue Treg cells.

Sample Metadata Fields

Sex, Age, Specimen part, Treatment

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accession-icon GSE37532
Gene expression profile of regulatory T cells (Tregs) isolated from visceral adipose tissue and lymph nodes of mice sufficient and deficient of Pparg expression in Tregs
  • organism-icon Mus musculus
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

We identified Pparg as a major orchestrator of the phenotype of adipose-tissue resident regulatory T cells (VAT Tregs). To establish the role of Pparg in shaping the VAT Tregs gene profile and cell dynamics, Tregs from lymph nodes and visceral adipose tissue of mice sufficient and deficient of Pparg expression in Tregs were double sorted for microarray analysis.

Publication Title

PPAR-γ is a major driver of the accumulation and phenotype of adipose tissue Treg cells.

Sample Metadata Fields

Sex, Age, Specimen part

View Samples
accession-icon GSE37533
Expression data of Pioglitazone- or vehicle-treated CD4+FoxP3- T cells transduced with Foxp3+/- Pparg1 (or Pparg2)
  • organism-icon Mus musculus
  • sample-icon 3 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

We identified Pparg as a major orchestrator of the phenotype of adipose-tissue resident regulatory T cells (VAT Tregs). To explore the contribution of Pparg1 and 2 in the generation of the VAT Tregs-specific gene signatures, CD4+FoxP3- T cells were transduced with Foxp3+/- Pparg1 (or Pparg2), treated with Pioglitazone or vehicle, and double sorted for microarray analysis.

Publication Title

PPAR-γ is a major driver of the accumulation and phenotype of adipose tissue Treg cells.

Sample Metadata Fields

Sex, Age, Specimen part, Treatment

View Samples
accession-icon GSE6813
Gene expression profiles of CD4+CD25+ Tregs from NOD and B6.H2g7 mice
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The NOD (nonobese diabetic) mouse strain develops a characteristic autoimmune syndrome that closely resembles human type I diabetes. It has been suggested that NOD mice exhibit both numerical deficiency in CD4+CD25+ regulatory T cells (Treg) and reduced suppressive activity. We compared sorted CD4+CD25+ Tregs from the spleens of 6-7 week-old female NOD and nondiabetic B6.H2g7 mice. Tregs were 932% and 951% Foxp3+ in NOD and B6.H2g7 cells, respectively, on post-sort reanalysis. "Conventional" CD4+CD25- T cells (Tconv) are included as reference populations. Surprisingly, Treg "signature" is similar between the two strains, with only a few probesets that subtly deviate.

Publication Title

The defect in T-cell regulation in NOD mice is an effect on the T-cell effectors.

Sample Metadata Fields

Age, Specimen part

View Samples
accession-icon GSE7460
Contribution of Foxp3 to the Treg signature
  • organism-icon Mus musculus
  • sample-icon 52 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The transcription factor Foxp3 is usually considered the master regulator for the CD4+CD25+ "Treg" lineage, which plays a key role in controlling immune and autoimmune responses, and is characterized by a unique transcriptional signature. We have performed a meta-analysis of this signature in Treg cells in several conditions to delineate the elements that can be ascribed to T cell activation, TGFbeta signaling, or Foxp3 itself. We find that these influences synergize to activate many of the signatures components. Foxp3 and TGFbeta signaling have interconnected relationships, as Foxp3 is induced by TGFbeta while enhancing TGFbetas positive feedback loop. Much of the Treg signature cannot be ascribed to Foxp3, as it contains gene clusters that are co-regulated, but cannot be transactivated, by Foxp3. This suggests that the Treg lineage is specified at a higher level of regulation, upstream of Foxp3, which does control some of the lineages essential immunoregulatory attributes.

Publication Title

Foxp3 transcription-factor-dependent and -independent regulation of the regulatory T cell transcriptional signature.

Sample Metadata Fields

Age, Specimen part

View Samples
accession-icon GSE62157
A role of regulatory T cells in brown adipose tissue physiology
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

The presence of different types of immune cells in adipose tissue has been demonstrated in numerous studies. Whereas cells of the immune system in white adipose tissue contribute to the low-grade chronic inflammation under obese conditions, their function in brown adipose tissue (BAT) remains largely elusive. Here we report a role of regulatory T (Treg) cells in BAT physiology.Ablation of Treg cells resulted in massive invasion of macrophages into BAT concordant with rearrangement of BAT morphology. Treg ablated animals displayed reduced energy expenditure. Our results for the first time demonstrate a functional role of Treg cells in the regulation of energy homeostasis.

Publication Title

Brown adipose tissue harbors a distinct sub-population of regulatory T cells.

Sample Metadata Fields

Treatment

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accession-icon GSE7852
Fat Treg cells
  • organism-icon Mus musculus
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Comparisons of global gene-expression profiles revealed a greater distinction between CD4+ Treg cells and CD4+ conventional (Tconv) T cells residing in abdominal (epidydimal) fat versus in more standard locations such as the spleen, thymus and LN.

Publication Title

Lean, but not obese, fat is enriched for a unique population of regulatory T cells that affect metabolic parameters.

Sample Metadata Fields

Specimen part

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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