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accession-icon GSE12845
B cell subsets from human tonsil and blood
  • organism-icon Homo sapiens
  • sample-icon 14 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

B cells from human tonsil and blood were sorted using flow cytometry. The human samples were processed immediately ex-vivo using markers for known B cell subsets.

Publication Title

Analysis of somatic hypermutation in X-linked hyper-IgM syndrome shows specific deficiencies in mutational targeting.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE12366
B cell subsets
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Sorted B cells using flow cytometry

Publication Title

Analysis of somatic hypermutation in X-linked hyper-IgM syndrome shows specific deficiencies in mutational targeting.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE138016
A circular RNA from the MDM2 locus regulates proliferation by suppressing basal p53 levels
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

Circular RNAs (circRNAs) are a class of noncoding RNAs produced by a non-canonical form of alternative splicing called back-splicing. To investigate a potential role of circRNAs in the p53 pathway, we analyzed RNA-seq data from colorectal cancer cell lines (HCT116, RKO and SW48) in the presence or absence of DNA damage. Surprisingly, unlike the strong p53-dependent induction of hundreds of p53-induced mRNAs, only a few circRNAs were induced from the p53-induced genes. Circ-MDM2, an annotated circRNA from the MDM2 locus, was one of the handful of circRNAs that originated from a p53-induced gene. Given the central role of MDM2 in suppressing p53 protein levels and p53 activity, we investigated the function of circ-MDM2. Knocking down circ-MDM2 with siRNAs that targeted the circ-MDM2 junction and had no effect on linear MDM2 mRNA, resulted in increased basal p53 levels and growth defects in vitro and in vivo. Consistent with these results, transcriptome profiling showed increased expression of several direct p53 targets, reduced Rb phosphorylation and defects in G1-S progression upon silencing circ-MDM2. Our results reveal the role of a novel circRNA by which the MDM2 locus suppresses p53 levels and cell cycle progression.

Publication Title

A Circular RNA from the <i>MDM2</i> Locus Controls Cell Cycle Progression by Suppressing p53 Levels.

Sample Metadata Fields

Treatment

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accession-icon GSE38312
autologous pairs of cutaneous melanocyte and melanoma cell cultures
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Early-passage (<10 passages) cultures of melanoma cells from metastatic lymph node lesions and normal adult melanocytes explanted in parallel from the adjacent, non-involved skin of 5 patients were compared by cDNA arrays. Differences between normal and neoplastic counterparts were then assessed upon adjustment for individual factors.

Publication Title

A melanoma immune response signature including Human Leukocyte Antigen-E.

Sample Metadata Fields

Sex, Specimen part

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accession-icon E-MTAB-2508
Transcriptional profiling of chronic myelogenous leukemia (CML) and normal, quiescent and dividing haematopoietic cells
  • organism-icon Homo sapiens
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Quiescent and dividing hemopoietic stem cells (HSC) display marked differences in their ability to move between the peripheral circulation and the bone marrow. Specifically, long-term engraftment potential predominantly resides in the quiescent HSC subfraction, and G-CSF mobilization results in the preferential accumulation of quiescent HSC in the periphery. In contrast, stem cells from chronic myeloid leukemia (CML) patients display a constitutive presence in the circulation. To understand the molecular basis for this, we have used microarray technology to analyze the transcriptional differences between dividing and quiescent, normal, and CML-derived CD34+ cells.

Publication Title

Transcriptional analysis of quiescent and proliferating CD34+ human hemopoietic cells from normal and chronic myeloid leukemia sources.

Sample Metadata Fields

Specimen part, Disease, Subject

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accession-icon SRP033498
Integrative AUF1 PAR-CLIP analysis uncovers AUF1 roles in translation and genome integrity (RNA-Seq 1)
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerII

Description

We report that AUF1 modulates global mRNA stability and translation, in turn promoting the maintenance of DNA integrity. Overall design: Please see individual series. For AUF1 PAR-CLIP, the four isoforms of AUF1 (p37, p40, p42, and p45) tagged with a Flag epitope were expressed in HEK293 cells. For total RNA-Seq HEK293 cells were transfected with Control siRNA, AUF1 siRNA, Empty Vector, Flag-AUF1 p37, p40, p42, or p45 as well as WI-38 cells were collected at PDL 15 and 55 and also transfected with Control siRNA, AUF1 siRNA, HuR siRNA. For Ribo-Seq HeLa cells were transfected with Control siRNA, AUF1 siRNA, or HuR siRNA.

Publication Title

PAR-CLIP analysis uncovers AUF1 impact on target RNA fate and genome integrity.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP033502
Integrative AUF1 PAR-CLIP analysis uncovers AUF1 roles in translation and genome integrity (RNA-Seq 2)
  • organism-icon Homo sapiens
  • sample-icon 5 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerII

Description

We report that AUF1 modulates global mRNA stability and translation, in turn promoting the maintenance of DNA integrity. Overall design: Please see individual series. In short, for AUF1 PAR-CLIP, the four isoforms of AUF1 (p37, p40, p42, and p45) tagged with a Flag epitope were expressed in HEK293 cells. For total RNA-Seq HEK293 cells were transfected with Control siRNA, AUF1 siRNA, Empty Vector, Flag-AUF1 p37, p40, p42, or p45 as well as WI-38 cells were collected at PDL 15 and 55 and also transfected with Control siRNA, AUF1 siRNA, HuR siRNA. For Ribo-Seq HeLa cells were transfected with Control siRNA, AUF1 siRNA, or HuR siRNA.

Publication Title

PAR-CLIP analysis uncovers AUF1 impact on target RNA fate and genome integrity.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE9037
response to LPS of WT and IRAK4 kinase dead mouse bone marrow macrophages
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

IRAK-4 is an essential component of the signal transduction complex downstream of the IL-1- and Toll-like receptors. Though regarded as the first kinase in the signaling cascade, the role of IRAK-4 kinase activity versus its scaffold function is still controversial. In order to investigate the role of IRAK-4 kinase function in vivo, knock-in mice were generated by replacing the wild type IRAK-4 gene with a mutant gene encoding kinase deficient IRAK-4 protein (IRAK-4 KD). Analysis of bone marrow macrophages obtained from WT and IRAK-4 KD mice with a number of experimental techniques demonstrated that the IRAK-4 KD cells greatly lack responsiveness to stimulation with the Toll-like receptor 4 (TLR4) agonist LPS. One of the techniques used, microarray analysis, identified IRAK-4 kinase-dependent LPS response genes and revealed that the induction of LPS-responsive mRNAs was largely ablated in IRAK-4 KD cells. In summary, our results suggest that IRAK-4 kinase activity plays a critical role in TLR4-mediated induction of inflammatory responses.

Publication Title

IRAK-4 kinase activity-dependent and -independent regulation of lipopolysaccharide-inducible genes.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE6246
Gene expression profiling: breast cancer formation in WAP-SVT/t transgenic animals
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Expression 430A Array (moe430a)

Description

Microarray studies revealed that as a first hit, SV40 T/t-antigen causes deregulation of 462 genes in mammary gland cells (ME-cells) of WAP-SVT/t transgenic animals. The majority of deregulated genes are cell-proliferation specific and Rb-E2F dependent, causing ME-cell proliferation and gland hyperplasia but not breast cancer formation. In the breast tumor cells, a further 207 genes are differentially expressed, most of them belonging to the cell communication category. In tissue culture, breast tumor cells frequently switch off WAP-SVT/t transgene expression and regain the morphology and growth characteristics of normal-ME-cells, although the tumor-revertant cells are aneuploid and only 114 genes regain the expression level of normal-ME-cells. The profile of retransformants shows that only 38 deregulated genes appear to be tumor-relevant and that none of them is considered to be a typical breast cancer gene.

Publication Title

Gene expression profiling: cell cycle deregulation and aneuploidy do not cause breast cancer formation in WAP-SVT/t transgenic animals.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE107039
Epigenetic and transcriptomic signature of aging in human liver
  • organism-icon Homo sapiens
  • sample-icon 33 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

Molecular Aging of Human Liver: An Epigenetic/Transcriptomic Signature.

Sample Metadata Fields

Sex, Age, Specimen part, Disease

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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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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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