refine.bio
  • Search
      • Normalized Compendia
      • RNA-seq Sample Compendia
  • Docs
  • About
  • My Dataset
github link
Showing
of 41 results
Sort by

Filters

Technology

Platform

accession-icon GSE36923
Microarray Gene Expression for Undifferentiated Mesenchymal Stem Cells, Adipogenically Differentiated and Dedifferentiation cells
  • organism-icon Homo sapiens
  • sample-icon 11 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Bone marrow mesenchymal stem cells (MSC) were adipogenically differentiated followed by dedifferentiation. We are interested to know the new fat markers, adipogenic signaling pathways and dedifferentiation signaling pathways.Furthermore we are also intrested to know that how differentiated cells convert into dedifferentiated progenitor cells. To address these questions, MSC were adipogenically differentiated, followed by dedifferentiation. Finally these dedifferentiated cells were used for adipogenesis, osteogenesis and chondrogenesis. Histology, FACS, qPCR and GeneChip analyses of undifferentiated, adipogenically differentiated and dedifferentiated cells were performed. Regarding the conversion of adipogenically differentiated cells into dedifferentiated cells, gene profiling and bioinformatics demonstrated that upregulation (DHCR24, G0S2, MAP2K6, SESN3) and downregulation (DST, KAT2, MLL5, RB1, SMAD3, ZAK) of distinct genes play a curcial role in cell cycle to drive the adipogenically differentiated cells towards an arrested state to narrow down the lineage potency. However, the upregulation (CCND1, CHEK, HGF, HMGA2, SMAD3) and downregulation (CCPG1, RASSF4, RGS2) of these cell cycle genes motivates dedifferentiation of adipogenically differentiated cells to reverse the arrested state. We also found new fat markers along with signaling pathways for adipogenically differentiated and dedifferentiated cells, and also observed the influencing role of proliferation associated genes in cell cycle arrest and progression.

Publication Title

Transdifferentiation of adipogenically differentiated cells into osteogenically or chondrogenically differentiated cells: phenotype switching via dedifferentiation.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE71646
Identification of global regulators of T-helper cell lineage specification
  • organism-icon Homo sapiens
  • sample-icon 12 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

Identification of global regulators of T-helper cell lineage specification.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE71566
Identification of global regulators of T-helper cell lineage specification (microarray)
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The aim of the dataset was to identify genome-wide regulators of gene expression in early differentiation of human cord blood derived CD4+ T cells cultured under Th1 (Act+IL12) and Th2 (Act+IL4) polarizing conditions.

Publication Title

Identification of global regulators of T-helper cell lineage specification.

Sample Metadata Fields

Specimen part

View Samples
accession-icon SRP061932
Identification of global regulators of T-helper cell lineage specification (RNA-Seq)
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

The aim of the dataset was to identify genome-wide regulators of gene expression in early differentiation of human cord blood derived CD4+ T cells cultured under Th1 (Act+IL12) and Th2 (Act+IL4) polarizing conditions. Overall design: Total RNA from naive CD4+ T cells was compared to total RNA from cells cultured in the following three conditions: activating (antiCD3+antiCD28)+antiIL4+antiIFNG; activating (antiCD3+antiCD28)+IL12+antiIL4; activating (antiCD3+antiCD28) +IL4+antiIFNG. Samples from 3 biological replicates were analysed.

Publication Title

Identification of global regulators of T-helper cell lineage specification.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP115320
DOCK8 enforces immunological tolerance by promoting IL-2 signaling and immune synapse formation in Treg cells
  • organism-icon Mus musculus
  • sample-icon 15 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Patients deficient in the guanine nucleotide exchange factor DOCK8 have decreased numbers and impaired in vitro function of T regulatory (Treg) cells and make autoantibodies, but seldom develop autoimmunity. We show that similarly, Dock8-/- mice have decreased numbers and impaired in vitrofunction of Treg cells, but do not develop autoimmunity. In contrast, mice with selective DOCK8 deficiency in Treg cells develop lymphoproliferation, autoantibodies, and gastrointestinal inflammation, despite normal percentage and in vitro function of Treg cells, suggesting that deficient T effector cell function might protect DOCK8 deficient patients from autoimmunity. We demonstrate that DOCK8 associates with STAT5 and is important for IL-2 driven STAT5 phosphorylation in Treg cells. DOCK8 localizes within the lamellar actin ring of the Treg cell immune synapse (IS). Dock8-/- Treg cells have abnormal TCR-driven actin dynamics, decreased adhesiveness, altered gene expression profile, an unstable IS with decreased recruitment of signaling molecules, and impaired transendocytosis of the co-stimulatory molecule CD86. These data suggest that DOCK8 enforces immunological tolerance by promoting IL-2 signaling, TCR-driven actin dynamics, and the IS in Treg cells.   Overall design:  CD4+CD25+CD39+YFP+ and CD4+CD25+CD39+YFP- Treg cells were isolated from the spleen and lymph nodes of Foxp3YFP-Cre/+/Dock8flox/flox mice.  Treg cells were then cultured overnight in complete media alone or in the presence of media + anti-CD3+CD28 beads (1 bead per cell). After 16 hours, cells were harvested and the RNA was isolated. For unstimulated samples, there were 4 independent YFP- samples and 6 independent YFP+ samples.  For bead stimulated samples, there were 3 independent YFP- samples and 2 YFP+ samples.

Publication Title

DOCK8 enforces immunological tolerance by promoting IL-2 signaling and immune synapse formation in Tregs.

Sample Metadata Fields

Specimen part, Cell line, Treatment, Subject

View Samples
accession-icon SRP048971
Expression profiles of long non-coding RNAs located in autoimmune disease-associated regions reveal immune cell type specificity
  • organism-icon Homo sapiens
  • sample-icon 7 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Background: Although genome-wide association studies (GWAS) have identified hundreds of variants associated with risk of autoimmune and immune-related disorders (AID), our understanding of the diseases mechanisms is limited. In particular, more than 90% of the risk variants lie in non-coding regions, and almost 10% of these map to long non-coding RNA transcripts (lncRNAs). LncRNAs are known to show more cell-type specificity than protein-coding genes. Methods: In this study, we aimed to characterize lncRNAs and protein-coding genes located in loci associated with nine AID which have been well-defined by Immunochip analysis, by transcriptome analysis across seven peripheral blood leukocyte populations (granulocytes, monocytes, NK cells, B-cells, memory-T cells, naive CD4+ and naive CD8+ T-cells) and four cord blood derived T-helper cell populations (precursor, primary, polarized (Th1, Th2) T-helper cells). Results: We show that lncRNAs mapping to loci shared between AIDs are significantly enriched in immune cell types when compared to lncRNAs from the whole genome (a<0.005). We were not able to prioritize single cell types relevant for specific diseases, but we observed five cell types enriched (a<0.005) in five AID (NK cells for inflammatory bowel disease, juvenile idiopathic arthritis, primary biliary cirrhosis, psoriasis; memory-T and CD8+ T-cells in juvenile idiopathic arthritis, primary biliary cirrhosis, psoriasis, rheumatoid arthritis; Th0 and Th2 cells for inflammatory bowel disease, juvenile idiopathic arthritis, primary biliary cirrhosis, psoriasis, rheumatoid arthritis). Furthermore we show that co-expression analyses of lncRNAs and protein-coding genes can predict the signaling pathways in which these AID-associated lncRNAs are involved. Conclusions: The observed enrichment of lncRNA transcripts in AID loci implies an important role for lncRNAs in AID etiology and suggests that lncRNA genes should be studied in more detail to correctly interpret GWAS findings. The co-expression results strongly support a model in which the lncRNA and protein-coding genes function together in the same pathways. Overall design: 7 immune cell types

Publication Title

Expression profiles of long non-coding RNAs located in autoimmune disease-associated regions reveal immune cell-type specificity.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE108595
Expression data from sorted humanized TREM2 murine microglia
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The R47H variant of TREM2 is associated with higher risk of Alzheimer's disease. We generated mice expressing the common variant or R47H variant of human TREM2

Publication Title

Humanized TREM2 mice reveal microglia-intrinsic and -extrinsic effects of R47H polymorphism.

Sample Metadata Fields

Sex, Age, Specimen part

View Samples
accession-icon GSE92693
IL-15 sustains IL-7R independent ILC2 and ILC3 development
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

ILC3 contain 3 well-defined subsets, CCR6+ ILC3, NKp46+ ILC3, and CCR6NKp46 DN ILC3. These subsets had not previously been transcriptionally compared and the extent to which they had shared or unique transcriptional profiles remained unclear.

Publication Title

IL-15 sustains IL-7R-independent ILC2 and ILC3 development.

Sample Metadata Fields

Specimen part

View Samples
accession-icon SRP093990
Retinoic Acid Induced Transcriptional Repressor HIC1 is Required for Suppressive Function of Human Induced Regulatory T cells [RNA-Seq 2]
  • organism-icon Homo sapiens
  • sample-icon 57 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Human CD4 positive T cells were isolated from cord blood using CD4 positive isolation kit from Dynal. Cells were activated with plate bound anti-CD3 and soluble anti-CD28 in presence (iTreg) or absence (Th0) of IL2, TGF beta and ATRA. The cells were harvested at 0, 0.5, 1, 2, 4, 6, 12, 24, 48, and 72 hours. Overall design: Comparing the gene expression in activated CD4+ cells and iTreg differentiated cells in human. 9 time points, 3 replicates for each time point.

Publication Title

Transcriptional Repressor HIC1 Contributes to Suppressive Function of Human Induced Regulatory T Cells.

Sample Metadata Fields

Specimen part, Subject

View Samples
accession-icon GSE100248
SMAD4 impedes conversion of NK cells into ILC1-like cells by curtailing non-canonical TGFb signaling
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

SMAD4 impedes the conversion of NK cells into ILC1-like cells by curtailing non-canonical TGF-β signaling.

Sample Metadata Fields

Specimen part

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)

fund-icon Fund the CCDL

Developed by the Childhood Cancer Data Lab

Powered by Alex's Lemonade Stand Foundation

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.

BSD 3-Clause LicensePrivacyTerms of UseContact