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GSE69849
Homo sapiens
363 Downloadable Samples
Affymetrix Human Genome U219 Array (hgu219)
Description
This study provides an evaluation of changes in gene expression associated with treating human Ishikawa cells with 34 different chemical compounds.
Publication Title
Grouping 34 Chemicals Based on Mode of Action Using Connectivity Mapping.
Sample Metadata Fields
Sex, Cell line
View Samples- Homo sapiens
- 360 Downloadable Samples
- Affymetrix Human Genome U219 Array (hgu219)
Description
This study provides an evaluation of changes in gene expression associated with treating human MCF7 cells with 34 different chemical compounds.
Publication Title
Grouping 34 Chemicals Based on Mode of Action Using Connectivity Mapping.
Sample Metadata Fields
Sex, Cell line
View Samples- Homo sapiens
- 348 Downloadable Samples
- Affymetrix Human Genome U219 Array (hgu219)
Description
This study provides an evaluation of changes in gene expression associated with treating human HEPG2 cells with 34 different chemical compounds.
Publication Title
Grouping 34 Chemicals Based on Mode of Action Using Connectivity Mapping.
Sample Metadata Fields
Sex, Cell line
View Samples- Homo sapiens
- 331 Downloadable Samples
- Affymetrix Human Genome U219 Array (hgu219)
Description
This study provides an evaluation of changes in gene expression associated with treating human HepaRG cells with 34 different chemical compounds.
Publication Title
Grouping 34 Chemicals Based on Mode of Action Using Connectivity Mapping.
Sample Metadata Fields
Sex, Cell line
View Samples- Homo sapiens
- 97 Downloadable Samples
Affymetrix Human Genome U219 Array (hgu219)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Grouping 34 Chemicals Based on Mode of Action Using Connectivity Mapping.
Sample Metadata Fields
Sex, Cell line
View Samples- Mus musculus
- 9 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
Oocyte maturation, fertilization, and early embryonic development occur in the absence of gene transcription. Therefore, it is critical to understand at a global level the post-transcriptional events that are driving these transitions. Here, we have used a systems approach by combining polysome mRNA profiling and bioinformatics to identify RNA binding motifs in mRNAs that either enter or exit the polysome pool during mouse oocyte maturation. Association of mRNA with the polysomes correlates with active translation.
Publication Title
Genome-wide analysis of translation reveals a critical role for deleted in azoospermia-like (Dazl) at the oocyte-to-zygote transition.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 8 Downloadable Samples
Illumina HiSeq 2000
Description
Male germ cells express the widest repertoire of transcript variants in mammalian tissues. Nevertheless, factors and mechanisms underlying such pronounced diversity are largely unknown. The splicing regulator Sam68 is highly expressed in meiotic cells and its ablation results in defective spermatogenesis. Herein, we uncover an extensive splicing program operated by Sam68 across meiosis, primarily characterized by alternative last exon (ALE) regulation in genes of functional relevance for spermatogenesis. Lack of Sam68 preferentially causes premature transcript termination at internal polyadenylation sites. Overall design: RNA-Seq data for purified spermatocytes and spermatids isolated from Sam68+/+ and Sam68-/- mice.
Publication Title
Functional Interaction between U1snRNP and Sam68 Insures Proper 3' End Pre-mRNA Processing during Germ Cell Differentiation.
Sample Metadata Fields
Specimen part, Cell line, Subject
View Samples- Homo sapiens
- 24 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Burkitt lymphoma (BL) is a highly aggressive B cell non-Hodgkin lymphoma (B-NHL), which originates from germinal center (GC) B cells and harbors translocations deregulating the MYC oncogene. A comparative analysis of microRNAs (miRNAs) expressed in normal and malignant GC B cells identified miR-28 as significantly down-regulated in BL, as well as in other GC-derived B-NHL. We show that re-expression of miR-28 impairs cell growth and clonogenic properties of BL cells by modulating several targets including MAD2L1, a component of the spindle checkpoint whose down-regulation is essential in mediating miR-28-induced growth-arrest, and BAG1, an activator of the ERK pathway.
Publication Title
MicroRNA 28 controls cell proliferation and is down-regulated in B-cell lymphomas.
Sample Metadata Fields
Cell line, Treatment, Time
View Samples- Homo sapiens
- 18 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Large-scale cancer genomics projects are profiling hundreds of tumors at multiple molecular layers, including copy number, mRNA and miRNA expression, but the mechanistic relationships between these layers are often excluded from computational models. We developed a supervised learning framework for integrating molecular profiles with regulatory sequence information to reveal regulatory programs in cancer, including miRNA-mediated regulation. We applied our approach to 320 glioblastoma profiles and identified key miRNAs and transcription factors as common or subtype-specific drivers of expression changes. We confirmed that predicted gene expression signatures for proneural subtype regulators were consistent with in vivo expression changes in a PDGF-driven mouse model. We tested two predicted proneural drivers, miR-124 and miR-132, both underexpressed in proneural tumors, by overexpression in neurospheres and observed a partial reversal of corresponding tumor expression changes. Computationally dissecting the role of miRNAs in cancer may ultimately lead to small RNA therapeutics tailored to subtype or individual.
Publication Title
Inferring transcriptional and microRNA-mediated regulatory programs in glioblastoma.
Sample Metadata Fields
Cell line
View Samples- Homo sapiens
- 160 Downloadable Samples
- Illumina HiSeq 2500
Description
Allergic asthma and rhinitis are two common chronic allergic diseases that affect the lungs and nose, respectively. Both diseases share clinical and pathological features characteristic of excessive allergen-induced type 2 inflammation, orchestrated by memory CD4+ T cells that produce type 2 cytokines (TH2 cells). However, a large majority of subjects with allergic rhinitis do not develop asthma, suggesting divergence in disease mechanisms. Since TH2 cells play a pathogenic role in both these diseases and are also present in healthy non-allergic subjects, we performed global transcriptional profiling to determine whether there are qualitative differences in TH2 cells from subjects with allergic asthma, rhinitis and healthy controls. TH2 cells from asthmatic subjects expressed higher levels of several genes that promote their survival as well as alter their metabolic pathways to favor persistence at sites of allergic inflammation. In addition, genes that enhanced TH2 polarization and TH2 cytokine production were also upregulated in asthma. Several genes that oppose T cell activation were downregulated in asthma, suggesting enhanced activation potential of TH2 cells from asthmatic subjects. Many novel genes with poorly defined functions were also differentially expressed in asthma. Thus, our transcriptomic analysis of circulating TH2 cells has identified several molecules that are likely to confer pathogenic features to TH2 cells that are either unique or common to both asthma and rhinitis. Overall design: RNA-sequencing of circulating TH2 cells isolated from a cohort of patients with allergic rhinitis (25), asthma (40) patients and healthy non allergic subjects (15). Cells were directly isolated from blood by flow cytometry. Total RNA was extracted, messenger RNA was selected and cDNA was amplified linearly with a PCR based method (Picelli et al. 2014). Libraries were prepared using the NexteraXT Illumina sequencing platform.
Publication Title
Transcriptional Profiling of Th2 Cells Identifies Pathogenic Features Associated with Asthma.
Sample Metadata Fields
No sample metadata fields
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