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accession-icon GSE8240
EMT initiation in MCF10A cells subjected to ionizing radiation and treatment with transforming growth factor beta-1.
  • organism-icon Homo sapiens
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix HT Human Genome U133A Array (hthgu133a)

Description

Transforming growth factor beta-1 (TGFbeta) is a tumor suppressor during the initial stage of tumorigenesis, but it can switch to a tumor promoter during neoplastic progression. Ionizing radiation (IR), both a carcinogen and a therapeutic agent, induces TGFbeta activation in vivo. We now show that IR sensitizes human mammary epithelial cells (HMEC) to undergo TGFbeta-mediated epithelial to mesenchymal transition (EMT). Non-malignant HMEC (MCF10A, HMT3522 S1 and 184v) were irradiated with 2 Gy shortly after attachment in monolayer culture, or treated with a low concentration of TGFbeta (0.4 ng/ml), or double-treated. All double-treated (IR+TGFbeta) HMEC underwent a morphological shift from cuboidal to spindle-shaped. This phenotype was accompanied by decreased expression of epithelial markers E-cadherin, beta-catenin and ZO-1, remodeling of the actin cytoskeleton, and increased expression of mesenchymal markers N-cadherin, fibronectin and vimentin. Furthermore, double-treatment increased cell motility, promoted invasion and disrupted acinar morphogenesis of cells subsequently plated in Matrigel. Neither radiation nor TGFbeta alone elicited EMT, even though IR increased chronic TGFbeta signaling and activity. Gene expression profiling revealed that double treated cells exhibit a specific 10-gene signature associated with Erk/MAPK signaling. We hypothesized that IR-induced MAPK activation primes non-malignant HMEC to undergo TGFbeta-mediated EMT. Consistent with this, Erk phosphorylation were transiently induced by irradiation, persisted in irradiated cells treated with TGFbeta, and treatment with U0126, a Mek inhibitor, blocked the EMT phenotype. Together, these data demonstrate that the interactions between radiation-induced signaling pathways elicit heritable phenotypes that could contribute to neoplastic progression.

Publication Title

Ionizing radiation predisposes nonmalignant human mammary epithelial cells to undergo transforming growth factor beta induced epithelial to mesenchymal transition.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP035359
Competence for reprogramming sex
  • organism-icon Caenorhabditis elegans
  • sample-icon 77 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer IIx

Description

We used RNA-Seq to compare transcriptomes of chemical reprogramming competent worms versus worms not competent for chemical reprogramming. We also performed RNA-seq during a time course of chemical reprogramming. Overall design: Three replicates of each of two reprogramming non-competent strains and three replicates of each of two reprogramming competent strains were collected. For the time course, five time points were analyzed (1, 2, 4, 6, and 18 hours) in either DMSO or DMSO + U0126 in three genotypes (non-reprogramming competent worms, reprogramming competent, and wildtype worms).

Publication Title

Competence for chemical reprogramming of sexual fate correlates with an intersexual molecular signature in Caenorhabditis elegans.

Sample Metadata Fields

Subject

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accession-icon GSE19246
A novel method of amplification of FFPET derived-RNA enables accurate disease classification with microarrays
  • organism-icon Homo sapiens
  • sample-icon 171 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

A new method for amplification and labeling of RNA is assessed that permits gene expression microarray analysis of formalin-fixed paraffin embedded tissue (i.e. FFPET) samples.

Publication Title

A novel method of amplification of FFPET-derived RNA enables accurate disease classification with microarrays.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon SRP047289
Dosage compensation can buffer copy-number variation in wild yeast
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 59 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000, Illumina HiSeq 2500

Description

We show that aneuploidy is common in wild isolates of yeast, which are inherently tolerant to chromosome amplification and down-regulate expression at 40% of amplified genes.  To dissect the mechanism of this dosage response, we generated isogenic strain panels in which diploid cells carried either two, three, or four copies of the affected chromosomes.  Using a mixture of linear regression (MLR) model to classify genes, we find that expression is actively down regulated in proportion to increased gene copy at up to 30% of genes. Genes subject to dosage control are under higher expression constraint – but show elevated rates of gene amplification – in wild populations, suggesting that dosage compensation buffers copy number variation (CNV) at toxic genes Overall design: RNA-seq and transcriptome analysis of S. cerevisiae natural isolates having aneuploidy. Technical triplicate was performed for isogenic diploid strains having 2, 3 and 4 copies of a given chromosome (strain panels), while technical duplicate or singulate was performed on all other aneuploids.

Publication Title

Dosage compensation can buffer copy-number variation in wild yeast.

Sample Metadata Fields

Subject

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accession-icon SRP082529
Single cell RNA-seq data of human hESCs to evaluate SCnorm: robust normalization of single-cell rna-seq data
  • organism-icon Homo sapiens
  • sample-icon 414 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Normalization of RNA-sequencing data is essential for accurate downstream inference, but the assumptions upon which most methods are based do not hold in the single-cell setting. Consequently, applying existing normalization methods to single-cell RNA-seq data introduces artifacts that bias downstream analyses. To address this, we introduce SCnorm for accurate and efficient normalization of scRNA-seq data. Overall design: Total 183 single cells (92 H1 cells, 91 H9 cells), sequenced twice, were used to evaluate SCnorm in normalizing single cell RNA-seq experiments. Total 48 bulk H1 samples were used to compare bulk and single cell properties. For single-cell RNA-seq, the identical single-cell indexed and fragmented cDNA were pooled at 96 cells per lane or at 24 cells per lane to test the effects of sequencing depth, resulting in approximately 1 million and 4 million mapped reads per cell in the two pooling groups, respectively.

Publication Title

SCnorm: robust normalization of single-cell RNA-seq data.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon SRP095642
Transcriptomic analysis of strains evolved for anaerobic xylose utilization [Y223_Y127_Y128]
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 27 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Engineering microbes with novel metabolic properties is a critical step for production of biofuels and biochemicals. Synthetic biology enables identification and engineering of metabolic pathways into microbes; however, knowledge of how to reroute cellular regulatory signals and metabolic flux remains lacking. Here we used network analysis of multi-omic data to dissect the mechanism of anaerobic xylose fermentation, a trait important for biochemical production from plant lignocellulose. We compared transcriptomic, proteomic, and phosphoproteomic differences across a series of strains evolved to ferment xylose under various conditions. Overall design: RNA-seq and transcriptome analysis of three evolved S. cerevisiae strains (Y22-3, Y127, Y128) grown aerobically or anaerobically in rich lab media with glucose, xylose, galactose, or sorbitol. Duplicates were collected on different days.

Publication Title

Rewired cellular signaling coordinates sugar and hypoxic responses for anaerobic xylose fermentation in yeast.

Sample Metadata Fields

Subject

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accession-icon SRP095641
Transcriptomic analysis of strains evolved for anaerobic xylose utilization [Azf1]
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 16 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Engineering microbes with novel metabolic properties is a critical step for production of biofuels and biochemicals. Synthetic biology enables identification and engineering of metabolic pathways into microbes; however, knowledge of how to reroute cellular regulatory signals and metabolic flux remains lacking. Here we used network analysis of multi-omic data to dissect the mechanism of anaerobic xylose fermentation, a trait important for biochemical production from plant lignocellulose. We compared transcriptomic, proteomic, and phosphoproteomic differences across a series of strains evolved to ferment xylose under various conditions. Overall design: RNA-seq and transcriptome analysis of Azf1 deletion and over-expression (via MoBY 2.0 plasmid) in YPX -O2. Duplicate samples were collected on different days.

Publication Title

Rewired cellular signaling coordinates sugar and hypoxic responses for anaerobic xylose fermentation in yeast.

Sample Metadata Fields

Subject

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accession-icon GSE23501
DNA methylation signatures define molecular subtypes of Diffuse Large B Cell Lymphoma
  • organism-icon Homo sapiens
  • sample-icon 67 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We performed DNA methylation (HELP array) and gene expression profiling in 69 samples of diffuse large B cell lymphoma (DLBCL). First, by gene expression, two molecular subtypes of DLBCL termed as "germinal center B cell-like" (GCB) and "activated B cell-like" (ABC) DLBCL were assigned to the 69 DLBCL cases. Then, the supervised analysis using HELP data revealed strikingly different DNA promoter methylation patterns in the two molecular DLBCL subtypes. These data provide epigenetic evidence that the DLBCL subtypes are distinct diseases that utilize different oncogenic pathways.

Publication Title

DNA methylation signatures define molecular subtypes of diffuse large B-cell lymphoma.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE33455
Expression data from docetaxel-resistant prostate cancer cell lines
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Docetaxel-based chemotherapy is the standard first-line therapy in metastatic castration-resistant prostate cancer. However, most patients eventually develop resistance to this treatment.

Publication Title

Identification of docetaxel resistance genes in castration-resistant prostate cancer.

Sample Metadata Fields

Disease, Disease stage, Cell line, Treatment

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accession-icon GSE10626
MuRF1-dependent regulation of systemic carbohydrate metabolism as revealed from transgenic mouse studies
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Under various pathophysiological muscle-wasting conditions like diabetes and starvation, a family of ubiquitin ligases, including MuRF1 (Muscle specific RING-Finger protein 1), are induced to target muscle proteins for degradation via ubiquitination. In an attempt to identify the in vivo targets of MuRF1 we have generated transgenic mouse lines overexpressing MuRF1 in a skeletal muscle specific fashion. MuRF1-TG lines were viable and had normal fertility. Characterization of their skeletal muscles did not reveal evidence for muscle wasting at 10 weeks of age. In this experiment we compared the skeletal muscle transcriptome of transgenic mice with wildtypes.

Publication Title

MuRF1-dependent regulation of systemic carbohydrate metabolism as revealed from transgenic mouse studies.

Sample Metadata Fields

Sex, Age, Specimen part

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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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