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accession-icon SRP112900
A novel addressable 9600-microwell array single cell RNA-seq method applied on fresh mouse cortical cells and frozen human cortical nuclei
  • organism-icon Mus musculus
  • sample-icon 647 Downloadable Samples
  • Technology Badge Icon

Description

We adopted the STRT-seq [Islam et al., Nat Methods 11, 163-166 (2013)] RNA-seq technology to a 9600-well array and applied it to analyze single cells from mouse and human cortex single cells. Overall design: 2192 single cells from mouse somatosensory cortex and 2028 single nuclei from human post-mortem middle temporal gyrus cortex.

Publication Title

STRT-seq-2i: dual-index 5' single cell and nucleus RNA-seq on an addressable microwell array.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP095855
A protective function of IL-22BP in acute liver injury
  • organism-icon Mus musculus
  • sample-icon 18 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Acute liver injury is a critical life-threatening event. Common causes are infections, intoxication, and ischemic conditions. The cytokine Interleukin 22 (IL-22) has been implicated in this process. However, the role of IL-22 during acute liver damage is controversial, since both protective and pathogenic properties have been reported. IL-22 binding protein (IL-22BP, IL-22Ra2), a soluble endogenous inhibitor of IL-22, is able to regulate IL-22 activity, and thus might explain some of the controversial findings. Since the role of IL-22BP in liver injury is unknown, we used Il22bp deficient mice and mouse models for acute liver damage to address this point. We found that Il22bp deficient mice were more susceptible to ischemia- and acetaminophen- induced liver damage. Deficiency of Il22bp caused increased hepatic damage and delayed liver regeneration. Using an unbiased approach, we found that IL-22, if uncontrolled in Il22bp deficient mice, induced Cxcl10 expression by hepatocytes, thereby recruiting inflammatory CD11b+Ly6C+ monocytes into the liver upon liver damage. Accordingly, neutralization of Cxcl10 reversed the increased disease susceptibility of Il22bp deficient mice. In conclusion, our data suggest dual functions of IL-22 in acute liver damage, and highlight the need to control IL-22 activity via IL-22BP. Overall design: RNA sequencing of RNA isolated from liver tissue from mice that underwent liver reperfusion treatment (IR) or sham surgery, in triplicate for three genotypes (Wt, Il22-/- and Il22bp-/-).

Publication Title

A Protective Function of IL-22BP in Ischemia Reperfusion and Acetaminophen-Induced Liver Injury.

Sample Metadata Fields

Specimen part, Treatment, Subject

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accession-icon SRP028333
RNA sequencing of pheromone stimulated and unstimulated MATa and MATa Saccharomyces cerevisiae
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Haploid budding yeast has two mating types, defined by the alleles of the MAT locus, MATa and MATa. Mating occurs when two haploid cells of opposite mating types signal to each other using reciprocal pheromones and receptors, polarize and grow towards each other, and eventually fuse to form a single diploid cell. The pheromones and receptors are necessary and sufficient to define a mating type, but other mating type-specific proteins make mating more efficient. We examined the role of these proteins by genetically engineering “transvestite” cells that swap the pheromone, pheromone receptor, and pheromone processing factors of one mating type for another. These cells can mate with each other, but their mating is inefficient. By characterizing their mating defects and examining their transcriptomes, we found Afb1 (a-factor barrier), a novel MATa-specific protein that interferes with a-factor, the pheromone secreted by MATa cells. We show that strong pheromone secretion is essential for efficient mating and that the weak mating of transvestites can be improved by boosting their pheromone production. Using synthetic biology, it is possible to characterize the factors that control efficiency in biological processes. In the case of budding yeast mating, selection for increased mating efficiency is likely to have continually boosted pheromone levels and the ability to discriminate between partners who make more (potentially fitter) and less (potentially less fit) pheromones. This sensitivity to which partner makes more pheromone comes at a cost: it means mating is not robust in situations where all potential partners make less pheromone. Overall design: 4 conditions were analysed, each with 3 biological replicates. The conditions were unstimulated MATa cells in YPD. Stimulated MATa cells in YPD+10nM a-factor. Unstimulated MATa cells in YPD. Stimulated MATa cells in YPD+10nM a-factor.

Publication Title

Genetically engineered transvestites reveal novel mating genes in budding yeast.

Sample Metadata Fields

Cell line, Subject

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accession-icon GSE63362
Identification of sexually dimorphically expressed genes in rat tissues
  • organism-icon Rattus norvegicus
  • sample-icon 256 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

The sexually dimorphic expression of genes across 26 somatic rat tissues was using Affymetrix RAE-230 genechips. We considered probesets to be sexually dimorphically expressed (SDE) if they were measurably expressed above background in at least one sex, there was at least a two-fold difference in expression (dimorphism) between the sexes, and the differences were statistically significant after correcting for false discovery. 14.5% of expressed probesets were SDE in at least one tissue, with higher expression nearly twice as prevalent in males compared to females. Most were SDE in a single tissue. Surprisingly, nearly half of the probesets that were (SDE) in multiple tissues were oppositely sex biased in different tissues, and most SDE probesets were also expressed without sex bias in other tissues. Two genes were widely SDE: Xist (female-only) and Eif2s3y (male-only). The frequency of SDE probesets varied widely between tissues, and was highest in the duodenum (6.2%), whilst less than 0.05% in over half of the surveyed tissues. The occurrence of SDE probesets was not strongly correlated between tissues. Within individual tissues, however, relational networks of SDE genes were identified. In the liver, networks relating to differential metabolism between the sexes were seen. The estrogen receptor was implicated in differential gene expression in the duodenum. To conclude, sexually dimorphic gene expression is common, but highly tissue-dependent. Sexually dimorphic gene expression may provide insights into mechanisms underlying phenotypic sex differences.

Publication Title

The incidence of sexually dimorphic gene expression varies greatly between tissues in the rat.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE20030
Expression Data from BALB/c and Stat6-deficient bone marrow derived macrophages (BMDM)
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

We used microarrays to find Stat6 dependent genes in control and IL-4 exposed bone marrow derived macrophages.

Publication Title

Alternatively activated macrophages inhibit T-cell proliferation by Stat6-dependent expression of PD-L2.

Sample Metadata Fields

Specimen part

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accession-icon GSE29815
Drosophila Staged follicles
  • organism-icon Drosophila melanogaster
  • sample-icon 22 Downloadable Samples
  • Technology Badge Icon Affymetrix Drosophila Genome 2.0 Array (drosophila2)

Description

Gene expression analysis of yw follicles at S9/10a, S10B, S12, and S14; Gene expression analysis of pxt mutant follicles (f01000 and EY03052) at S10B, S12, S14

Publication Title

Drosophila eggshell production: identification of new genes and coordination by Pxt.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE92428
Expression data from mRNA in complex with EGFR from irradiated human A549 (ATCC CCL185) cells
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.1 ST Array (hugene21st)

Description

Immunoprecipitation of EGFR from irradiated A549 (ATCC CCL185) cells was performed in order to characterize bound mRNA species with the help of microarray analysis

Publication Title

New roles for nuclear EGFR in regulating the stability and translation of mRNAs associated with VEGF signaling.

Sample Metadata Fields

Cell line, Treatment

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accession-icon E-MEXP-549
Transcription profiling by array of irradiated human MOLT4 cells
  • organism-icon Homo sapiens
  • sample-icon 21 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

The purpose of the experiment was to generate a time course of gene expression following irradiation. The goal was then to model this data to extract hidden variables - chiefly, the activity profiles of the p53 transcription factor. Using this information the aim was to predict which transcripts changed by IR were targets of p53. Cells in log phase (1 x 106 ml-1) were ?-irradiated with 5 Gy at room temperature (RT) at a dose rate of 2.45 Gy per minute with a 137Cs ?-irradiator. Cells were harvested at 0, 2, 4, 6, 8, 10 and 12 hours, and RNA and protein were extracted (Trizol, Invitrogen). Affymetrix U133A arrays were hybridized as standard (www.affymetrix.co.uk). Array quality was determined using R and GCOS .rpt file values. The time course was replicated three times from independent cell preparations.

Publication Title

Ranked prediction of p53 targets using hidden variable dynamic modeling.

Sample Metadata Fields

Specimen part, Disease, Cell line, Time

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accession-icon GSE35478
Characterization of colon cancer cells: a functional approach characterizing CD133 as a potential stem cell marker
  • organism-icon Homo sapiens
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Background: Isolation and characterization of tumourigenic colon cancer initiating cells may help to develop novel diagnostic and therapeutic procedures. Methods: We characterized a panel of fourteen human colon carcinoma cell lines and their corresponding xenografts for the surface expression of different potential stem cell markers: CD133, CD24, CD44, CDCP1 and CXCR4. In five cell lines and nine xenografts mRNA expression of the investigated markers was determined. Tumour growth behaviour of CD133+, CD133- and unsorted SW620 cells was evaluated in vivo. Results: All surface markers showed distinct expression patterns in the examined tumours. Analyses of the corresponding xenografts revealed a significant reduction of cell numbers expressing the investigated markers. CD44 and CXCR4 mRNA expression correlated within the cell line panel and CD44 and CDCP1 within the xenograft panel, respectively. Small subpopulations of double and triple positive cells could be described. SW620 showed significantly higher take rates and shorter doubling times in vivo when sorted for CD133 positivity. Conclusion: Our data support the hypothesis of a small subset of cells with stem cell-like properties characterized by a distinct surface marker profile. In vivo growth kinetics give strong relevance for an important role of CD133 within the mentioned surface marker profile.

Publication Title

Characterization of colon cancer cells: a functional approach characterizing CD133 as a potential stem cell marker.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE22772
Expression data from U373 cells expressing EGFP, MAML1-dn and DTX1-myc
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Glioblastoma multiforme (GBM) is the most malignant and most common tumor of the central nervous system characterized by rapid growth and extensive tissue infiltration. GBM results in more years of life lost than any other cancer type. Notch signaling has been implicated in GBM pathogenesis through several modes of action. Inhibition of Notch leads to a reduction of cancer-initiating cells in gliomas and reduces proliferation and migration. Deltex1 (DTX1) is part of an alternative Notch signaling pathway distinct from the canonical MAML1/RBPJ-mediated cascade. In this study, we show that DTX1 activates both the RTK/PI3K/PKB as well as the MAPK/ERK pathway. Moreover, we found the anti-apoptotic factor Mcl-1 to be induced by DTX1. In accordance with this, the clonogenic potential and proliferation rates of glioma cell lines correlated with DTX1 levels. DTX1 knock down mitigated the tumorigenic potential in vivo, and overexpression of DTX1 increased cell migration and invasion of tumor cells accompanied by an elevation of the pro-migratory factors PKB and Snail1. Microarray gene expression analysis identified a DTX1-specific transcriptional program - including microRNA-21 - which is distinct from the canonical Notch signaling. We propose the alternative Notch pathway via DTX1 as oncogenic factor in malignant glioma and found low DTX1 expression levels to correlate with prolonged survival of GBM and early breast cancer patients in open source databases.

Publication Title

Deltex-1 activates mitotic signaling and proliferation and increases the clonogenic and invasive potential of U373 and LN18 glioblastoma cells and correlates with patient survival.

Sample Metadata Fields

Specimen part, Cell line

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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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