refine.bio
  • Search
      • Normalized Compendia
      • RNA-seq Sample Compendia
  • Docs
  • About
  • My Dataset
github link
Showing
of 462 results
Sort by

Filters

Technology

Platform

accession-icon SRP079982
Zac1 is a regulator of the imprinted gene network (RNA-seq)
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

In order to determine the imprinted transcription factor Zac1 targets, we overexpressed Zac1 in a mouse insulinoma cell line and measured the regulated expressed genes by RNA-seq. We have shown that Zac1 regulates many genes belonging to the Imprinted Gene Network, including genes coding for the extra-cellular matrix. Overall design: Determination of Zac1 target genes in transfected Min6 cells (4 biological replicates) using RNA-seq, .

Publication Title

Identification of Plagl1/Zac1 binding sites and target genes establishes its role in the regulation of extracellular matrix genes and the imprinted gene network.

Sample Metadata Fields

Specimen part, Subject

View Samples
accession-icon SRP043271
Embryonic stem cell-derived cerebral cortex largely reproduces the in vivo epigenetic control of imprinted gene expression [RNA-seq]
  • organism-icon Mus musculus
  • sample-icon 31 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

In vitro differentiation of embryonic stem cells (ESC) provides models that reproduce in vivo development and cells for therapy. Whether the epigenetic signatures that are crucial for brain development and function and that are sensitive to in vitro culture are similar between native brain tissues and their artificial counterpart generated from ESC is largely unknown. Here, using RNA-seq we have compared the parental origin-dependent expression of imprinted genes (IGs), a model of epigenetic regulation, in cerebral cortex generated either in vivo, or from ESCs using in vitro corticogenesis, a model that reproduces the landmarks of in vivo corticogenesis. For a majority of IGs, the expressed parental alleles were the same for in vivo and in vitro cortex. In most cases, this choice was already set in ESCs and faithfully maintained during the 3 weeks of in vitro corticogenesis. Confirming these findings, methylation, which selects the parental allele to be transcribed, was also largely equivalent between the 2 types of cortex and ESCs. Our results thus indicate that the allele specific expression of imprinted transcripts, a model of epigenetic regulation resulting from a differential methylation of parental genomes, is mostly mimicked in cortical cells derived from ESC. Overall design: We have crossed two strains of mice (B6 and JF1) that display more than 12 million of SNPs (Takada et al., Genome Res. 2013 Aug;23(8):1329-38. doi: 10.1101/gr.156497.113). We have then analyzed allele specific expression transcriptome-wide using RNA-seq on hybrid F1 cortex generated either in vivo or in vitro from ESCs. In addition, we have used 2 different developmental stages of in vivo cortex (E13.5, P0) and three stages in vitro (undiffererentiated ESC, and differentiated into cortex for 12 and 21 days) to measure the dynamics of parental expression. Please note that [1] the same raw data files were used to generate the ''*allele-specific_sense_read_bases_by_gene_withoutContamination.txt'' processed data files. [2] The samples associated with each file are indicated in the file column header (as their GSM accession numbers). [3] The readme.txt file contains the data processing steps, file description.

Publication Title

In Vitro Corticogenesis from Embryonic Stem Cells Recapitulates the In Vivo Epigenetic Control of Imprinted Gene Expression.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE146814
Gene expression profiling of Splenic Marginal Zone Lymphoma
  • organism-icon Homo sapiens
  • sample-icon 65 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Splenic marginal zone lymphoma (SMZL) is a rare, indolent non-Hodgkin’s lymphoma that affects 0.13 per 100,000 persons annually. Overall survival of SMZL is estimated to reach 8 to 11 years in most cases, but up to 30% of SMZL cases develop aggressive presentations resulting in greatly diminished time of survival. SMZL presents with a very heterogeneous molecular profile, making diagnosis problematic and accurate prognosis even less likely. The study herein has utilized this data to assist in identifying a potential diagnostic gene expression signature with highly specific predictive utility for further evaluation among control and SMZL patient samples. Delineation of a unique SMZL signature that could provide diagnostic utility for a malignancy that has historically been difficult to identify. These results should be further investigated and validated in subsequent molecular investigations of SMZL so it may be potentially incorporated into standard oncology practice for improving the understanding and outlook for SMZL patients.

Publication Title

Identification of a Splenic Marginal Zone Lymphoma Signature: Preliminary Findings With Diagnostic Potential.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP012062
RNA-sequencing analysis of NB4 cells overexpressing miR-125b
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer

Description

To better understand the mechanisms of blockage of myeloid differentiation and apoptosis and induction of proliferation by miR-125b, we proceeded to identify miR-125b target genes involved in these pathways. We analyzed the total cellular gene expression pattern by RNA-sequencing of the parental NB4 myeloid cell line and that transiently transfected with miR-125b. We generated four cDNA libraries corresponding to duplicates of miR-125b and control cells. Overall design: Compare the gene expression levels in miR control transfected cells with that in miR-125b transfected NB4 cells. 

Publication Title

MicroRNA-125b transforms myeloid cell lines by repressing multiple mRNA.

Sample Metadata Fields

Specimen part, Cell line, Subject

View Samples
accession-icon SRP012041
RNA-sequencing analysis of 32Dclone3 cells overexpressing miR-125b
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer

Description

To better understand the mechanisms of blockage of myeloid differentiation and apoptosis and induction of proliferation by miR-125b, we preceded to identify miR-125b target genes involved in these pathways. We analyzed the total cellular gene expression pattern by RNA-sequencing of the parental 32Dclone3 myeloid cell line and that ectopically expressing miR-125b. We generated four cDNA libraries corresponding to duplicates of miR-125b and control cells. Overall design: Compare the gene expression level in vector transduced 32Dclone3 cells with that in miR-125b transduced 32Dclone3 cells. 

Publication Title

MicroRNA-125b transforms myeloid cell lines by repressing multiple mRNA.

Sample Metadata Fields

Specimen part, Cell line, Subject

View Samples
accession-icon GSE99777
Expression data of adult quiescent and activated mouse neural stem cells
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Neural stem cells were sorted according to their activated or quiescent state by flow cytometry using a set of 3 markers (LeX, CD24 and EGFR)

Publication Title

Distinct Molecular Signatures of Quiescent and Activated Adult Neural Stem Cells Reveal Specific Interactions with Their Microenvironment.

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon GSE7491
Expression data from rat lung alveolar development
  • organism-icon Rattus norvegicus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

Lung alveolarization is a complex process that involves interactions between several cell types and leads to considerable increase in gas-exchange surface area. The step designated secondary septation includes elastogenesis from interstitial fibroblasts.

Publication Title

Gene expression profiling in lung fibroblasts reveals new players in alveolarization.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE70421
SMARCB1-deficient rhaboid tumors of the kidney and renal medullary carcinomas.
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We used microarrays to compared gene expression profilings in various tumors of the kidney.

Publication Title

Balanced Translocations Disrupting SMARCB1 Are Hallmark Recurrent Genetic Alterations in Renal Medullary Carcinomas.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE102067
An RNAi screen reveals an essential role for HIPK4 in human skin epithelial differentiation from iPSCs
  • organism-icon Homo sapiens
  • sample-icon 21 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

Molecular mechanisms that are responsible for the development of human skin epithelial cells are not completely understood so far. As a consequence, the efficiency to establish a pure skin epithelial cell population from human induced pluripotent stem cells (hiPSC) remains poor. Using an approach including RNA interference and high-throughput imaging of early epithelial cells, we could identify candidate kinases which are involved in skin epithelial differentiation. Among them, we found HIPK4 to be an important inhibitor of this process. Indeed, its silencing increased the amount of generated skin epithelial precursors, increased the amount of generated keratinocytes and improved growth and differentiation of organotypic cultures, allowing for the formation of a denser basal layer and stratification with the expression of several keratins. Our data bring substantial input in the regulation of human skin epithelial differentiation and for improving differentiation protocols from pluripotent stem cells.

Publication Title

An RNAi Screen Reveals an Essential Role for HIPK4 in Human Skin Epithelial Differentiation from iPSCs.

Sample Metadata Fields

Specimen part, Time

View Samples
accession-icon SRP078987
Tissue-specific Emergence of Regulatory and Intraepithelial T Cells from a Clonal T-cell Precursor
  • organism-icon Mus musculus
  • sample-icon 18 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

We used RNA sequencing to characterize gene expression of CD4+ CD8a+ double positive (DP), Foxp3+ Treg (TR) and CD4+ single positive (SP) cells in the lamina propria (LP) and intraepithelial compartment (IEL) that had differentiante from the same clonal transnuclear (TN) precursor. Overall design: We adoptively transferred CD4+ CD8a- Foxp3-GFP- isolated from pTregTN/RKO/Foxp3-GFP mice into TCRaßKO hosts. After 6 weeks, we sorted transferred CD4+ CD8a+, Foxp3+ pTreg as well as unconverted CD4+ CD8a- Foxp3-GFP- from the small intestine LP and IEL compartments for whole transcriptome analysis by mRNA sequencing.

Publication Title

Tissue-specific emergence of regulatory and intraepithelial T cells from a clonal T cell precursor.

Sample Metadata Fields

Specimen part, Subject

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