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Gallus gallus
12 Downloadable Samples
Affymetrix Chicken Genome Array (chicken)
Description
The proneural NEUROG2 is essential for neuronal commitment, cell cycle exit and neuronal differentiation. Characterizing genes networks regulated downstream of NEUROG2 is therefore of prime importance. To identify NEUROG2 early response genes, we combined gain of function in the neural tube with a global detection of modified transcripts using microarrays. We included in our study a mutant form of NEUROG2 (NEUROG2AQ) that cannot bind DNA and cannot trigger neurogenesis. Using this approach, we identified 942 genes modified at the onset of NEUROG2 activation. The global analysis of functions regulated by NEUROG2 allowed unmasking its rapid impact on cell cycle control. We found that NEUROG2 specifically represses a subset of cyclins acting at the G1 and S phases of the cell cycle, thereby impeding S phase re-entry. This repression occurs before modification of p27kip1, indicating that the decision to leave the cell cycle precedes the activation of this Cyclin-dependant Kinase Inhibitor. Moreover, NEUROG2 down-regulates only one of the D-type cyclins, cyclinD1, and maintaining cyclinD1 blocks the ability of the proneural to trigger cell cycle exit, without altering its capacity to trigger neuronal differentiation. The fact that NEUROG2 represses a subset but not all cell cycle regulators indicates that cell cycle exit is not an indirect consequence of neuronal differentiation but is precisely controlled by NEUROG2. Altogether our findings indicate that NEUROG2, by specifically repressing G1 and S cyclins, allows committed neuronal precursors to perform their last mitosis but blocks their re-entry in the cell cycle, thus favouring cell cycle exit.
Publication Title
NEUROG2 drives cell cycle exit of neuronal precursors by specifically repressing a subset of cyclins acting at the G1 and S phases of the cell cycle.
Sample Metadata Fields
Specimen part, Treatment
View Samples- Bos taurus, Ovis aries
- 10 Downloadable Samples
- Affymetrix Bovine Genome Array (bovine)
Description
Background Correct achievement of early ovarian folliculogenesis is a crucial phase for further ovarian function. This process is closely regulated by cell-cell interactions and coordinated expression of genes from oocyte and granulosa cells. But, despite of the large number of studies, little is known about the precise gene expression patterns driving early folliculogenesis. The experimental limitations concerned the very small size of these follicles and the mixture of the different developmental stages within an ovary that make the study of isolated follicular components much more difficult. The recently developed laser capture microdissection (LCM) technique coupled with microarrays experiments is promising in addressing the molecular specificity of each follicular compartment. Nevertheless, the isolation of unique cells or group of cells is still challenging to maintain RNA quality during this process and to obtain sufficient amount of RNA. In this study, we described a method allowing the analysis of oocyte and granulosa cells gene expression during the first stages of sheep early folliculogenesis. Results First we developed a new fixation protocol using a frizzed 70% ethanol fixation solution that ensures correct single cell capture and RNA integrity during microdissection time. After LCM capture of the compartments and follicular stages, RNA extraction and amplification, the expression of 6 oocyte-specific genes (SOHLH2, MAEL, MATER, VASA, GDF9, BMP15) and 3 granulosa cell-specific genes (KITLG, GATA4, AMH) confirmed the purity of the samples and documented their ovine expression profiles. Then, using bovine Affymetrix chip, we identified for the first time, a global gene expression for each follicular compartment during early developmental stages. Particularly the granulosa cell data set is quite unique. 1050 granulosa cell specific transcripts compared to oocyte and 759 oocyte specific transcripts were detected. The analysis of the expression of 2 genes (SIRT7, FST) confirmed this specificity of expression. Finally, the integration of the data stated the 3 main physiological events involved in early folliculogenesis and provided descriptive elements that confirmed the relevance and the potential of the LCM-derived RNAs. Conclusions This method should contribute through an additional genome wide expression profiling to give insights on molecular mechanisms involved in stage transitions and cell type interplays.
Publication Title
Transcriptome profiling of sheep granulosa cells and oocytes during early follicular development obtained by laser capture microdissection.
Sample Metadata Fields
Age, Specimen part
View Samples- Mus musculus
- 6 Downloadable Samples
- Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
The expansion, trafficking and functional effectiveness of adoptively transferred CD8+ T-cells play a critical role in mediating effective anti-tumor immunity. However, the mechanisms which program the highly proliferative and functional state of CD8+ T-cells are not completely understood. We hypothesized that IL-12, a cytokine commonly induced by TLR activation, could enhance T-cell priming by altering responsiveness to antigen and cytokines. Priming of tumor specific CD8+ T-cells in the presence of IL-12 induced the acquisition of a 'polyfunctional' effector response and increased the generation of memory cells. Moreover, IL-12 priming also promoted high levels of the IL-2 receptor alpha-chain (CD25) and robust IL-2 mediated activation of STAT5. This sensitivity to IL-2 translated into enhanced in vivo proliferation of adoptively transferred CD8+ T-cells. Furthermore, real-time, in vivo imaging of T-cell trafficking confirmed the ability of IL-12 priming to drive in vivo proliferation. IL-12 priming enhanced the anti-tumor function of adoptively transferred cells by reducing established subcutaneous tumor burden, and significantly increasing survival in an established intracranial tumor model. Finally, IL-12 priming of human PBMCs generates tumor specific T-cells phenotypically and functionally similar to IL-12 primed Pmel-1 T-cells. These results highlight IL-12 as an important mediator of CD8+ T-cell effector function and anti-tumor immunity.
Publication Title
Enhanced sensitivity to IL-2 signaling regulates the clinical responsiveness of IL-12-primed CD8(+) T cells in a melanoma model.
Sample Metadata Fields
Sex, Specimen part, Treatment
View Samples- Mus musculus
- 6 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
Unraveling the mechanisms underlying early neural differentiation of ESCs is crucial to the cell-based therapies of neurodegenerate diseases. Neural fate acquisition is proposed to be controlled by a default mechanism, for which the molecular regulation is not well understood. In this study, we investigated the functional roles of Mediator Med23 in pluripotency and lineage commitment of embryonic stem cells (ESCs). Unexpectedly we found that, despite the largely unchanged pluripotency and self-renewal of ESCs, Med23-depletion rendered the cells prone to neural differentiation in different differentiation assays. Knockdown of other Mediator subunit, Med1 or Med15, did not alter the neural differentiation of ESCs; and Med15 knockdown selectively inhibited endoderm differentiation, suggesting the specificity of cell fate control by distinctive Mediator subunits. Gene profiling revealed that Med23-depletion attenuated the BMP signaling in ESCs. Mechanistically, MED23 modulated Bmp4 expression by controlling the activity of ETS1 that is involved in the Bmp4 promoter-enhancer communication. Interestingly, Med23 knockdown in zebrafish embryos also enhanced the neural development at early embryogenesis, which could be reversible by coinjection of bmp4 mRNA. Taken together, our study reveals an intrinsic, restrictive role of MED23 in early neural development, thus providing new molecular insights for neural fate determination.
Publication Title
Mediator Med23 deficiency enhances neural differentiation of murine embryonic stem cells through modulating BMP signaling.
Sample Metadata Fields
No sample metadata fields
View Samples- Arabidopsis thaliana
- 3 Downloadable Samples
Illumina HiSeq 4000
Description
DNA methylation on N6-adenine (6mA) has recently been found as a potentially new epigenetic mark in several unicellular and multicellular eukaryotes. However, its distribution patterns and potential functions in land plants, which are primary producers for most ecosystems, remain completely unknown. Here we report global profiling of 6mA sites at single-nucleotide resolution in the genome of Arabidopsis thaliana using single-molecule real-time sequencing. 6mA sites are widely distributed across the Arabidopsis genome and enriched over the pericentromeric heterochromatin regions. Nearly 30% of 6mA sites are present in gene bodies. Further analysis of 6mA methylome and RNA-sequencing data demonstrates that 6mA frequency positively correlates with the gene expression level in Arabidopsis. Consistently, histone variants associated with actively expressed genes interact with 6mA DNA. Our results uncover 6mA as a DNA mark associated with actively expressed genes in Arabidopsis, suggesting that 6mA serves as a novel epigenetic mark in land plants. Overall design: RNA-seq in 3-week-old Arabidopsis thaliana (Col-0) wild-type with three replicates.
Publication Title
DNA N<sup>6</sup>-Adenine Methylation in Arabidopsis thaliana.
Sample Metadata Fields
Subject
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GSE4412- Homo sapiens
- 169 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Diffuse infiltrating gliomas are the most common primary brain malignancy found in adults, and Glioblastoma multiforme, the highest grade glioma, is associated with a median survival of 7 months. Transcriptional profiling has been applied to 85 gliomas from 74 patients to elucidate glioma biology, prognosticate survival, and define tumor sub-classes. These studies reveal that transcriptional profiling of gliomas is more accurate at predicting survival than traditional pathologic grading, and that gliomas characteristically express coordinately regulated genes of one of four molecular signatures: neurogenesis, synaptic transmission, mitotic, or extra-cellular matrix. Elucidation of these survival associated molecular signatures will aid in tumor prognostication and define targets for future directed therapy.
Publication Title
Gene expression profiling of gliomas strongly predicts survival.
Sample Metadata Fields
Sex, Age, Specimen part, Disease stage
View Samples- Homo sapiens
- 167 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Migrated from 1.6 id: 1015897590491013 GEDP id: 760 In current clinical practice, histology-based grading of diffuse infiltrative gliomas is the best predictor of patient survival time. Yet histology provides little insight into the underlying biology of gliomas and is limited in its ability to identify and guide new molecularly targeted therapies. We have performed large-scale gene expression analysis using the Affymetrix HG U133 oligonucleotide arrays on 85 diffuse infiltrating gliomas of all histologic types to assess whether a gene expression-based, histology-independent classifier is predictive of survival and to determine whether gene expression signatures provide insight into the biology of gliomas. We found that gene expression-based grouping of tumors is a more powerful survival predictor than histologic grade or age. The poor prognosis samples could be grouped into three different poor prognosis groups, each with distinct molecular signatures. We further describe a list of 44 genes whose expression patterns reliably classify gliomas into previously unrecognized biological and prognostic groups: these genes are outstanding candidates for use in histology-independent classification of high-grade gliomas. The ability of the large scale and 44 gene set expression signatures to group tumors into strong survival groups was validated with an additional external and independent data set from another institution composed of 50 additional gliomas. This demonstrates that large-scale gene expression analysis and subset analysis of gliomas reveals unrecognized heterogeneity of tumors and is efficient at selecting prognosis-related gene expression differences which are able to be applied across institutions.
Publication Title
Gene expression profiling of gliomas strongly predicts survival.
Sample Metadata Fields
Sex, Age, Specimen part, Disease, Disease stage
View Samples- Homo sapiens
- 267 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Background: Glioblastomas are the most common primary brain tumour in adults. While the prognosis for patients is poor, gene expression profiling has detected signatures that can sub-classify GBMs relative to histopathology and clinical variables. One category of GBM defined by a gene expression signature is termed ProNeural (PN), and has substantially longer patient survival relative to other gene expression-based subtypes of GBMs. Age of onset is a major predictor of the length of patient survival where younger patients survive longer than older patients. The reason for this survival advantage has not been clear.
Publication Title
Gene expression analysis of glioblastomas identifies the major molecular basis for the prognostic benefit of younger age.
Sample Metadata Fields
Sex, Age
View Samples- Mus musculus
- 12 Downloadable Samples
- Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
MicroRNA-188 regulates age-related switch between osteoblast and adipocyte differentiation.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 6 Downloadable Samples
- Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
We identified microRNA-188 differentially expressed in the BMSCs of aged and young mice and influenced on BMSCs differentiation with ageing.
Publication Title
MicroRNA-188 regulates age-related switch between osteoblast and adipocyte differentiation.
Sample Metadata Fields
Specimen part
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