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Homo sapiens
21 Downloadable Samples
Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
We isolated hematopoietic stem and progenitor cells from AML patients by FACS.
Publication Title
Cellular origin of prognostic chromosomal aberrations in AML patients.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 33 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
We used microarray to create a normal cell landscape for the myeloid arm of the hematopoietic system.
Publication Title
Comparing cancer vs normal gene expression profiles identifies new disease entities and common transcriptional programs in AML patients.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 12 Downloadable Samples
- Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
To investigate the role of the transcription factor ERG in hematopoiesis we generated Erg heterozygous knockout and conditional Erg knockout mice. We found that several hematopoietic cell types were decreased in these mice. To define Erg downstream target genes in hematopoietic stem cells, we sorted Lineage-, Sca-1+, c-kit+, CD150+, CD48- cells from Erg +/- mice for gene expression analysis. To define Erg downstream target genes in hematopoietic progenitors, we sorted multipotent progenitors (Lineage-, Sca-1+, c-kit+, CD150-) from Erg -/- mice for gene expression analysis.
Publication Title
ERG promotes the maintenance of hematopoietic stem cells by restricting their differentiation.
Sample Metadata Fields
Sex, Specimen part
View Samples- Saccharomyces cerevisiae
- 25 Downloadable Samples
- Affymetrix Yeast Genome S98 Array (ygs98)
Description
These Affymetrix data were used to determine the role of each non-essential subunit of the conserved Ccr4-Not complex in the control of gene expression in the yeast S. cerevisiae. The study was performed with cells growing exponentially in high glucose and with cells grown to glucose depletion. Specific patterns of gene de-regulation were observed upon deletion of any given subunit, revealing the specificity of each subunits function. Consistently, the purification of the Ccr4-Not complex through Caf40p by tandem affinity purification from wild-type cells or cells lacking individual subunits of the Ccr4-Not complex revealed that each subunit had a particular impact on complex integrity. Furthermore, the micro-arrays revealed that the role of each subunit was specific to the growth conditions. From the study of only two different growth conditions, revealing an impact of the Ccr4-Not complex on more than 85% of all studied genes, we can infer that the Ccr4-Not complex is important for expression of most of the yeast genome.
Publication Title
Specific roles for the Ccr4-Not complex subunits in expression of the genome.
Sample Metadata Fields
No sample metadata fields
View Samples
GSE1428- Homo sapiens
- 22 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
This series includes the global gene expression profile of the vastus lateralis muscle for 10 young (19-25 years old) and 12 older (70-80 years old) male subjects.
Publication Title
Identification of a molecular signature of sarcopenia.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 12 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
This dataset was created to study M-CSF dependent in vitro differentiation of human monocytes to macrophages as a model process to demonstrate that independent component analysis (ICA) is a useful tool to support and extend knowledge-based strategies and to identify complex regulatory networks or novel regulatory candidate genes.
Publication Title
Analyzing M-CSF dependent monocyte/macrophage differentiation: expression modes and meta-modes derived from an independent component analysis.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 12 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
External stimulations of cells by hormones, growth factors or cytokines activate signal transduction pathways that subsequently induce a rearrangement of cellular gene expression. The representation and analysis of changes in the gene response is complicated, and essentially consists of multiple layered temporal responses. In such situations, matrix factorization techniques may provide efficient tools for the detailed temporal analysis. Related methods applied in bioinformatics intentionally do not take prior knowledge into account. In signal processing, factorization techniques incorporating data properties like second-order spatial and temporal structures have shown a robust performance. However, large-scale biological data rarely imply a natural order that allows the definition of an autocorrelation function. We therefore develop the concept of graph-autocorrelation. We encode prior knowledge like transcriptional regulation, protein interactions or metabolic pathways as a weighted directed graph. By linking features along this underlying graph, we introduce a partial ordering of the samples to define an autocorrelation function. Using this framework as constraint to the matrix factorization task allows us to set up the fast and robust graph decorrelation (GraDe) algorithm. To analyze the alterations in the gene response in IL-6 stimulated primary mouse hepatocytes by GraDe, a time-course microarray experiment was performed. Extracted gene expression profiles show that IL-6 activates genes involved in cell cycle progression and cell division in a time-resolved manner. On the contrary, genes linked to metabolic and apoptotic processes are down-regulated indicating that IL-6 mediated priming rendered hepatocytes more responsive towards cell proliferation and reduces expenses for the energy household.
Publication Title
Knowledge-based matrix factorization temporally resolves the cellular responses to IL-6 stimulation.
Sample Metadata Fields
Specimen part, Treatment, Time
View Samples- Mus musculus
- 129 Downloadable Samples
Illumina HiSeq 2000
Description
We performed single-cell RNA sequencing (RNA-seq) during the in vitro transition of mouse ESCs (mESCs) from a naïve pluripotent state into epiblast-like cells (EpiLCs), a primed pluripotent state. We derived pseudotime expression trajectories to investigate transcript dynamics of key metabolic regulators, with the aim to identify metabolic pathways that potentially impact on early embryonic cell state transitions. Overall design: Single-cell RNA-seq during the in vitro differentiation of mouse embryonic stem cells (ESCs) in 2i culture conditions (time point t=0h) into epiblast-like cells (EpiLCs) at time points t=24h and t=48h.
Publication Title
Metabolic regulation of pluripotency and germ cell fate through α-ketoglutarate.
Sample Metadata Fields
Specimen part, Cell line, Subject
View Samples- Mus musculus
- 9 Downloadable Samples
- Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
Cross-presentation of cell-associated antigens is carried out by classical DCs (cDCs) and monocyte-derived DCs (Mo-DCs), but whether a similar or distinct program exists for this process is unknown. In examining this issue, we discovered that only Ly-6ChiTremL4 monocytes, but not Ly-6ChiTremL4+ monocytes, can differentiate into Zbtb46+ Mo-DCs in response to GM-CSF and IL-4. However, Ly-6ChiTremL4+ monocytes were committed to Nur77-dependent development of Ly-6CloTremL4+ monocytes. Further, differentiation of monocytes with GM-CSF required addition of IL-4 to generate Zbtb46+ Mo-DCs that cross-presented as efficiently as CD24+ cDCs, which was accompanied by increased Batf3 and Irf4 expression. Unlike cDCs, Mo-DCs required only IRF4, and not Batf3, for cross-presentation. Further, Irf4/ monocytes failed to develop into Zbtb46+ Mo-DCs, and instead developed into macrophages. Thus, cDCs and Mo-DCs use distinct transcriptional programs for cross-presentation that may drive different antigen-processing pathways. These differences may influence development of therapeutic DC vaccines based on Mo-DCs.
Publication Title
Distinct Transcriptional Programs Control Cross-Priming in Classical and Monocyte-Derived Dendritic Cells.
Sample Metadata Fields
Sex, Specimen part, Treatment
View Samples- Mus musculus
- 4 Downloadable Samples
- Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
Cross-presentation of cell-associated antigens is carried out by classical DCs (cDCs) and monocyte-derived DCs (Mo-DCs), but whether a similar or distinct program exists for this process is unknown. In examining this issue, we discovered that only Ly-6ChiTremL4 monocytes, but not Ly-6ChiTremL4+ monocytes, can differentiate into Zbtb46+ Mo-DCs in response to GM-CSF and IL-4. However, Ly-6ChiTremL4+ monocytes were committed to Nur77-dependent development of Ly-6CloTremL4+ monocytes. Further, differentiation of monocytes with GM-CSF required addition of IL-4 to generate Zbtb46+ Mo-DCs that cross-presented as efficiently as CD24+ cDCs, which was accompanied by increased Batf3 and Irf4 expression. Unlike cDCs, Mo-DCs required only IRF4, and not Batf3, for cross-presentation. Further, Irf4/ monocytes failed to develop into Zbtb46+ Mo-DCs, and instead developed into macrophages. Thus, cDCs and Mo-DCs use distinct transcriptional programs for cross-presentation that may drive different antigen-processing pathways. These differences may influence development of therapeutic DC vaccines based on Mo-DCs.
Publication Title
Distinct Transcriptional Programs Control Cross-Priming in Classical and Monocyte-Derived Dendritic Cells.
Sample Metadata Fields
Sex, Specimen part, Treatment
View Samples