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accession-icon SRP095021
Requirements for different Tcf1 isoforms in T cell development
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Comparison of transcriptome between control, Tcf1 long isoform (p45)-deficient, complete Tcf1-deficient DN3 thymoctyes Overall design: lineage-negative, CD4-, CD8-, CD44 low and CD25 high (DN3) thymocytes were sorted from control mice or those are deficient for either Tcf1 long isoforms (p45) or all Tcf1 proteins. Lck-Cre was used to ablate all Tcf1 proteins

Publication Title

Cutting Edge: β-Catenin-Interacting Tcf1 Isoforms Are Essential for Thymocyte Survival but Dispensable for Thymic Maturation Transitions.

Sample Metadata Fields

Specimen part, Subject

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accession-icon SRP105428
Differential requirements for Tcf1 long isoforms in CD8+ and CD4+ T cell responses to acute viral infection
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Comparison of the transcriptome between control Tfh and Tcf1 long isoform-deficient Tfh cells Overall design: SMARTA CD4+ T cells (control or Tcf1 long isoform deficient) were adoptively transferred into B6.SJL recipient mice and then infected with LCMV-Arm. On day 8 after infection, the splenocytes were isolated, and CD45.2+CD4+CXCR5+PD-1 negative cells were sorted as Tfh cells and used in RNAseq analysis.

Publication Title

Differential Requirements for Tcf1 Long Isoforms in CD8<sup>+</sup> and CD4<sup>+</sup> T Cell Responses to Acute Viral Infection.

Sample Metadata Fields

Specimen part, Subject

View Samples
accession-icon SRP056606
Impact of Lef1 overexpression on follicular helper T (Tfh) differentiation
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Comparison of transcriptome between GFP-RV+ Th1 cells and Lef1-RV+ Th1 cells Overall design: B6 mice received GFP-RV+ or Lef1-RV+ LCMV gp specific TCRtg Smarta cells and were infected with LCMV. On four days after infection, splenocytes were collected to sort CXCR5- Th1 cells per genotype. Contributor: LIAI RNAi Center (LIAI)

Publication Title

LEF-1 and TCF-1 orchestrate T(FH) differentiation by regulating differentiation circuits upstream of the transcriptional repressor Bcl6.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP056078
Impact of Tcf1 and Lef1 deficiency on follicular helper T (Tfh) cells
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Comparison of transcriptome between control and Tcf1/Lef1-deficient germinal center Tfh (GC-Tfh) cells Overall design: Control mice or those are deficient for Tcf1 and Lef1 transcription factors were infected with vaccinia virus. On day 8 after infection, the splenocytes were isolated and surface stained to identify CD44-high, CD62L-low, GFP+, CD4+ T cells. From these cells, PD-1+, CXCR5+ GC-Tfh cells were sorted for RNAseq analysis

Publication Title

LEF-1 and TCF-1 orchestrate T(FH) differentiation by regulating differentiation circuits upstream of the transcriptional repressor Bcl6.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP067404
Dynamic organization and activation of enhancers and super-enhancers dictate effector and memory CD8+ T cell responses (RNA-Seq)
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Our experiments aimed to investigate the landscape of enhancers and super-enhancers in naïve, effector and memory CD8+ T cells. Here we mapped four histone modification marks and gene expression in naive, effector, and memory cells after viral infection. Our results suggest that the chromatin environment at regulatory DNA sequences in TCM is more permissive than in TN and TE. We further predicted the enhancers and their targets, and constructed transcriptional regulatory networks (TRNs) in three T cell stages. We have identified a highly dynamic repertoire of the enhancers and their targets during CD8 T cell responses, as 77% of the enhancers and 82% of the enhancer-promoter interactions are stage-specific. Our results suggest the dynamic change of enhancer activity during cell stage transition leads to TRN rewiring, which explains the expression change of the key factors of T cell function. Overall design: We performed ChIP-Seq for 4 histone modification markers and RNA-Seq experiments in three CD8+ T cell differentiation stages.

Publication Title

CD8<sup>+</sup> T Cells Utilize Highly Dynamic Enhancer Repertoires and Regulatory Circuitry in Response to Infections.

Sample Metadata Fields

Cell line, Subject

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accession-icon SRP081301
Genome structure and organization in mouse CD8 T cells [RNA-seq]
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Our experiments aimed to investigate the landscape of enhancers and super-enhancers in naïve, effector and memory CD8+ T cells. Here we mapped four histone modification marks and gene expression in naive, effector, and memory cells after viral infection. Our results suggest that the chromatin environment at regulatory DNA sequences in TCM is more permissive than in TN and TE. We further predicted the enhancers and their targets, and constructed transcriptional regulatory networks (TRNs) in three T cell stages. We have identified a highly dynamic repertoire of the enhancers and their targets during CD8 T cell responses, as 77% of the enhancers and 82% of the enhancer-promoter interactions are stage-specific. Our results suggest the dynamic change of enhancer activity during cell stage transition leads to TRN rewiring, which explains the expression change of the key factors of T cell function. Overall design: We performed RNA-Seq experiments in WT and Tcf1/Lef1 difficient CD8 cells, and performed Hi-C experiments in WT cells.

Publication Title

CD8<sup>+</sup> T Cells Utilize Highly Dynamic Enhancer Repertoires and Regulatory Circuitry in Response to Infections.

Sample Metadata Fields

Cell line, Subject

View Samples
accession-icon GSE51540
Effects of TNF-alpha blocking in sorted Th17 cells from co-cultures of human CD4-positive and CD14-positive cells
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Human CD4+ T cells and CD14+ monocytes from healthy donors were co-cultured with anti-CD3 for three days in the presence or absence of TNF-alpha mAb (Adalimumab). Classical Th17 cells (Th17) or those generated in the presence of the inhibitor (iTh17) were then sorted and analyzed by full transcriptome microarray analysis.

Publication Title

TNF-α blockade induces IL-10 expression in human CD4+ T cells.

Sample Metadata Fields

Specimen part, Treatment, Subject

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accession-icon GSE51080
Expression data from exposure of BAT and WAT at 6 and 28 degrees C
  • organism-icon Mus musculus
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

We run microarrays from three per group Sv129 female mice, ten weeks old, which were maintained at 28C (warm conditions) or 6 C (cold stimulated) for ten days, while standard animal house temperature is 22 C.

Publication Title

Brown and white adipose tissues: intrinsic differences in gene expression and response to cold exposure in mice.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon SRP073245
RNA-seq analysis reveals profound changes in transcript profiles between siCon- and siH19-transfected EVT cells
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

We used high throughput sequencing to analyze the transcriptional profiling of EVT. By comparing the transcriptional profiling of EVT with or without H19 knockdown, numerous genes showed significantly altered expression as a result of H19 repression. Overall design: HTR cells were transfected with either control siRNA or siH19. 48h later after transfection, total RNA was extracted for library preparation and RNA-seq analysis to compare trancript profiles between siCon and siH19 cells.

Publication Title

H19 long noncoding RNA alters trophoblast cell migration and invasion by regulating TβR3 in placentae with fetal growth restriction.

Sample Metadata Fields

Cell line, Subject, Time

View Samples
accession-icon GSE22132
Expression data from purified human platelets
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Patients with systemic lupus erythematosus (SLE) have a markedly increased risk to develop cardiovascular disease, and traditional cardiovascular risk factors fail to account for this increased risk. We used microarray to probe the platelet transcriptome in individuals with SLE and healthy controls, and the gene and protein expression of a subset of differentially expressed genes was further investigated and correlated to platelet activation status. Real-time PCR was used to confirm a type I interferon (IFN) gene signature in patients with SLE, and the IFN-regulated proteins PRKRA, IFITM1 and CD69 (p<0.0001) were found to be up-regulated in platelets from SLE patients as compared to healthy volunteers. Notably, patients with a history of vascular disease had increased expression of type I IFN-regulated proteins as well as more activated platelets as compared with patients without vascular disease. We suggest that interferogenic immune complexes stimulate production of IFN which up-regulates the megakaryocytic type I IFN-regulated genes and proteins. This could affect platelet activation and contribute to development of vascular disease in SLE. In addition, platelets with type I IFN signature could be a novel marker for vascular disease in SLE.

Publication Title

Platelet transcriptional profile and protein expression in patients with systemic lupus erythematosus: up-regulation of the type I interferon system is strongly associated with vascular disease.

Sample Metadata Fields

Sex, Age, 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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