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accession-icon GSE28144
The Apple Flavonoid Phloretin Inhibits Escherichia coli O157:H7 Biofilm Formation and Ameliorates Colon Inflammation in Rat
  • organism-icon Escherichia coli
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix E. coli Genome 2.0 Array (ecoli2)

Description

Pathogenic biofilms have been associated with persistent infections due to high resistance to antimicrobial agents while commensal biofilms often fortify host immune system. Hence, controlling biofilm formation of both pathogenic bacteria and commensal bacteria is important in bacteria-related diseases. We investigated the effect of plant flavonoids on biofilm formation of both enterohemorrhagic Escherichia coli O157:H7 and three commensal E. coli K-12 strains. Phloretin abundant in apples markedly reduced E. coli O157:H7 biofilm formation without affecting the growth of planktonic cells while phloretin did not harm commensal E. coli K-12 biofilms. Also, phloretin reduced E. coli O157:H7 attachment to human colon epithelial cells. Global transcriptome analyses revealed that phloretin repressed toxin genes (hlyE and stx2), autoinducer-2 importer genes (lsrACDBF), a curli gene (csgA), and a dozens of prophage genes in E. coli O157:H7 cells. Electron microscopy confirmed that phroretin reduced the curli production in E. coli O157:H7. In addition, phloretin suppressed TNF--induced inflammatory response in vitro using human colonic epithelial cells. Moreover, in the trinitrobenzene sulfonic acid (TNBS)-induced rat colitis model, phloretin significantly ameliorated colon inflammation and body weight loss. Taken together, our results suggest that phloretin may act as an inhibitor of E. coli O157:H7 biofilm formation as well as anti-inflammatory agent on inflammatory bowel diseases while leaving beneficial commensal E. coli biofilm intact.

Publication Title

Apple flavonoid phloretin inhibits Escherichia coli O157:H7 biofilm formation and ameliorates colon inflammation in rats.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE7696
Glioblastoma from a homogenous cohort of patients treated within clinical trial
  • organism-icon Homo sapiens
  • sample-icon 79 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Analysis of 80 glioblastoma specimen of patients treated within clinical trials and 4 samples of "normal" brain tissue (non-tumoral). The data was used to identify factors of resistance to a chemoradiation therapy protocol of radiotherapy and concomitant and adjuvant temozolomide (alkylating agent).

Publication Title

Stem cell-related "self-renewal" signature and high epidermal growth factor receptor expression associated with resistance to concomitant chemoradiotherapy in glioblastoma.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Treatment, Subject

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accession-icon SRP054971
Ribosome profiling and RNA sequencing of MCF10A-ER-Src and fibroblast cell transformation
  • organism-icon Homo sapiens
  • sample-icon 7 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

We applied ribosome profiling and RNA sequencing to examine gene expression regulation during oncogenic cell transformation. One model involves normal mammary epithelial cells (MCF10A) containing ER-Src. Treatment of such cells with tamoxifen rapidly induces Src, thereby making it possible to kinetically follow the transition between normal and transformed cells. The other model consists of three isogenic cell lines derived from primary fibroblasts in a serial manner (Hahn et al., 1999). EH cell is immortalized by overexpression of telomerase (hTERT), and exhibits normal fibroblast morphology. EL cell expresses hTERT along with both large and small T antigens of Simian virus 40, and it displays an altered morphology but is not transformed. ELR cell expresses hTERT, T antigens, and an oncogenic derivative of Ras (H-RasV12). Overall design: Ribosome profiling and RNA sequencing in two cancer cell models

Publication Title

Many lncRNAs, 5'UTRs, and pseudogenes are translated and some are likely to express functional proteins.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP129440
Smart-seq2 analysis of larval zebrafish habenula from the gng8-GFP transgenic line
  • organism-icon Danio rerio
  • sample-icon 1138 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

The identification of cell types and marker genes is critical for dissecting neural development and function, but the size and complexity of the brain has hindered the comprehensive discovery of cell types. We combined single-cell RNA-seq with anatomical brain registration to create a comprehensive map of the zebrafish habenula, a conserved forebrain hub involved in pain processing and learning. Single-cell transcriptomes of ~13000 habenular cells (>4x coverage) identified 18 neuronal types and dozens of marker genes. Registration of marker genes onto a common reference atlas created a rich resource for anatomical and functional studies and enabled the mapping of active neurons onto neuronal types following aversive stimuli. Strikingly, despite brain growth and functional maturation, cell types were retained between the larval and adult habenula. This study provides a gene expression atlas to dissect habenular development and function and offers a general framework for the comprehensive characterization of other brain regions. Overall design: gng8-GFP zebrafish heads were dissected, dissociated and FAC sorted into 96 well plates. Single cell libraries were generated in batches of 384 cells using Smart-seq2. A total of 22 gng8-GFP fish were dissected in 3 batches and 384 cells were processed from each using Smart-seq2.

Publication Title

Comprehensive Identification and Spatial Mapping of Habenular Neuronal Types Using Single-Cell RNA-Seq.

Sample Metadata Fields

Specimen part, Subject

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accession-icon SRP186866
Progressive dosage compensation during Drosophila embryogenesis is reflected by gene arrangement on the X chromosome [RNA-seq]
  • organism-icon Drosophila melanogaster
  • sample-icon 52 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 1500

Description

In D. melanogaster males, X chromosome monosomy is compensated by chromosome-wide transcription activation. We found that complete dosage compensation during embryogenesis takes surprisingly long. Although the activating Dosage Compensation Complex (DCC) associates with the chromosome and acetylates histone H4 early, many genes are not compensated. Acetylation levels on gene bodies continue to increase for several hours after gastrulation in parallel with progressive compensation. Constitutive genes are compensated earlier than developmental genes. Remarkably, later compensation correlates with longer distances to DCC binding sites. This time-space relationship suggests that DCC action on target genes requires maturation of the active chromosome compartment. Overall design: RNA-seq in 8 embryonic stages in total 54 single embryos.

Publication Title

Progressive dosage compensation during Drosophila embryogenesis is reflected by gene arrangement.

Sample Metadata Fields

Specimen part, Subject

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accession-icon SRP042091
Genome-wide expression profiles in young and old mouse liver [RNA-seq]
  • organism-icon Mus musculus
  • sample-icon 7 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Aging is accompanied by physiological impairments, which, in insulin-responsive tissues, including the liver, predispose individuals to metabolic disease. However, the molecular mechanisms underlying these changes remain largely unknown. Here, we analyze genome-wide profiles of RNA and chromatin organization in the liver of young (3 months) and old (21 months) mice. Transcriptional changes suggest that de-repression of the nuclear receptors PPARa, PPAR?, and LXRa in aged mouse liver leads to activation of targets regulating lipid synthesis and storage, whereas age-dependent changes in nucleosome occupancy are associated with binding sites for both known regulators (forkhead factors and nuclear receptors) and for novel candidates associated with nuclear lamina (Hdac3 and Srf) implicated to govern metabolic function of aging liver. Winged-helix factor Foxa2 and nuclear receptor co-repressor Hdac3 exhibit reciprocal binding pattern at PPARa targets contributing to gene expression changes that lead to steatosis in aged liver. Overall design: Genome-wide expression profiles (RNA-Seq) from young (3 months) and old (21 months) mouse livers

Publication Title

Changes in nucleosome occupancy associated with metabolic alterations in aged mammalian liver.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP055996
Spatial reconstruction of single-cell gene expression
  • organism-icon Danio rerio
  • sample-icon 1138 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Spatial localization is a key determinant of cellular fate and behavior, but spatial RNA assays traditionally rely on staining for a limited number of RNA species. In contrast, single-cell RNA-seq allows for deep profiling of cellular gene expression, but established methods separate cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos, inferring a transcriptome-wide map of spatial patterning. We confirmed Seurat’s accuracy using several experimental approaches, and used it to identify a set of archetypal expression patterns and spatial markers. Additionally, Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems. Overall design: We generated single-cell RNA-seq profiles from dissociated cells from developing zebrafish embryos (late blastula stage - 50% epiboly)

Publication Title

Spatial reconstruction of single-cell gene expression data.

Sample Metadata Fields

Subject

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accession-icon GSE23211
Expression data from PSARK::IPT and wildtype rice plants
  • organism-icon Oryza sativa
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Rice Genome Array (rice)

Description

Transgenic rice plants expressing isopentenyltransferase (IPT), an enzyme that catalyzes the rate-limiting step in CK synthesis under the control of SARK, a maturation- and stress-inducible promoter. Increased CK production resulted in sink source alteration and enhanced drought tolerance of the transgenic plants.

Publication Title

Cytokinin-mediated source/sink modifications improve drought tolerance and increase grain yield in rice under water-stress.

Sample Metadata Fields

Age, Specimen part

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accession-icon SRP109817
RNA-seq during MCF10A-ER-Src cell transformation and upon factor knockdowns
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

We performed RNA-seq to examine RNA expression profiles during MCF10A-ER-Src cell transformation and upon knockdowns of transcription factors Overall design: RNA-seq before and after MCF10A-ER-Src cell transformation, and RNA-seq upon factor knockdowns after inducing cell transformation

Publication Title

Genome-scale identification of transcription factors that mediate an inflammatory network during breast cellular transformation.

Sample Metadata Fields

Specimen part, Subject

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accession-icon E-MEXP-729
Transcription profiling of barley in response to nitrate, ammonium or both
  • organism-icon Hordeum vulgare
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Barley Genome Array (barley1)

Description

Comparative genomic analysis of nutrient response to NO3-, NH4+ or NH4+: NO3- in barley

Publication Title

Global transcriptional and physiological responses of Saccharomyces cerevisiae to ammonium, L-alanine, or L-glutamine limitation.

Sample Metadata Fields

Age, Specimen part, Subject, Compound

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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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