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Mus musculus
181 Downloadable Samples
Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
Gene-expression microarray datasets generated as part of the Immunological Genome Project (ImmGen) for samples that use a different set of amplification reagents (Ambion WT Expression Kit, not the Affymetrix GeneChip WT cDNA Synthesis and Amplification Kits).
Publication Title
The tumor microenvironment shapes lineage, transcriptional, and functional diversity of infiltrating myeloid cells.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Homo sapiens
- 19 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
Viral infections of the CNS are of increasing concern, especially among immunocompromised populations. Rodent models are often inappropriate for studies of CNS infection, as many viruses, including JC Virus (JCV) and HIV, cannot replicate in rodent cells. Consequently, human fetal brain-derived multipotential CNS progenitor cells (NPCs) that can be differentiated into neurons, oligodendrocytes, or astrocytes, have served as a model for CNS studies. NPCs can be non-productively infected by JCV, while infection of progenitor-derived astrocytes (PDAs) is robust. We profiled cellular gene expression at multiple times during differentiation of NPCs to PDAs. Several activated transcription factors show commonality between cells of the brain in which JCV replicates and lymphocytes in which JCV is likely latent. Bioinformatic analysis determined transcription factors that may influence the favorable transcriptional environment for JCV in PDAs. This study attempts to provide a framework for understanding the functional transcriptional profile necessary for productive JCV infection.
Publication Title
Differentiation of human fetal multipotential neural progenitor cells to astrocytes reveals susceptibility factors for JC virus.
Sample Metadata Fields
Specimen part, Time
View Samples- Homo sapiens
- 13 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
JC virus (JCV) is a ubiquitous human polyomavirus that causes the demyelinating disease Progressive Multifocal Leukoencephalopathy (PML). JCV replicates in limited cell types in culture, predominantly in human glial cells. Thus, productive JCV infection is an indicator of the host cell transcription environment. Following introduction of a replication defective SV40 mutant that expressed large T protein into a heterogeneous culture of human fetal brain cells, multiple phenotypes became immortalized (SVG cells). A subset of SVG cells could support JCV replication. This mixed culture was called SVG cells. In the current study, clonal cell lines were selected from the original SVG cell culture. The SVG-5F4 clone showed low levels of viral growth. The SVG-10B1 clone was highly permissive for JCV DNA replication and gene expression. Microarray analysis revealed that viral infection did not significantly change gene expression in these cells. More resistant 5F4 cells expressed high levels of transcription factors known to inhibit JCV transcription. Interestingly, 5F4 cells highly expressed RNA of markers of Bergman or radial glia and 10B1 cells had high expression of markers of immature glial cells and activation of transcription regulators important for stem/progenitor cell self-renewal. These SVG-derived clonal cell lines provide a biologically relevant model to investigate cell type differences in JCV host range and pathogenesis, as well as neural development.
Publication Title
Clonal immortalized human glial cell lines support varying levels of JC virus infection due to differences in cellular gene expression.
Sample Metadata Fields
Specimen part, Time
View Samples- Homo sapiens
- 6 Downloadable Samples
- Affymetrix Human Genome U133A 2.0 Array (hgu133a2)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Reactivation of ERK signaling causes resistance to EGFR kinase inhibitors.
Sample Metadata Fields
Cell line
View Samples- Homo sapiens
- 6 Downloadable Samples
- Affymetrix Human Genome U133A 2.0 Array (hgu133a2)
Description
The clinical efficacy of EGFR kinase inhibitors is limited by the development of drug resistance. The irreversible EGFR kinase inhibitor WZ4002 is effective against the most common mechanism of drug resistance mediated by the EGFR T790M mutation. Here we show that in multiple complementary models harboring EGFR T790M, resistance to WZ4002 develops through aberrant activation of ERK signaling caused by either an amplification of MAPK1 or by downregulation of negative regulators of ERK signaling. Inhibition of MEK or ERK restores sensitivity to WZ4002, and the combination of WZ4002 and a MEK inhibitor prevents the emergence of drug resistance. The WZ4002 resistant MAPK1 amplified cells also demonstrate an increase both in EGFR internalization and a decrease in sensitivity to cytotoxic chemotherapy compared to the parental counterparts. Our findings provide insights into mechanisms of drug resistance to EGFR kinase inhibitors and highlight rational combination therapies that should be evaluated in clinical trials.
Publication Title
Reactivation of ERK signaling causes resistance to EGFR kinase inhibitors.
Sample Metadata Fields
Cell line
View Samples- Homo sapiens
- 130 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Background: Septic shock is a heterogeneous syndrome within which probably exist several biological subclasses. Discovery and identification of septic shock subclasses could provide the foundation for the design of more specifically targeted therapies. Herein we tested the hypothesis that pediatric septic shock subclasses can be discovered through genome-wide expression profiling. Methods: Genome-wide expression profiling was conducted using whole blood-derived RNA from 98 children with septic shock, followed by a series of bioinformatic approaches targeted at subclass discovery and characterization. Results: Three putative subclasses (subclasses A, B, and C) were initially identified based on an empiric, discovery-oriented expression filter and unsupervised hierarchical clustering. Statistical comparison of the 3 putative subclasses (ANOVA, Bonferonni correction, p < 0.05) identified 6,934 differentially regulated genes. K means clustering of these 6,934 genes generated 10 coordinately regulated gene clusters corresponding to multiple signaling and metabolic pathways, all of which were differentially regulated across the 3 subclasses. Leave one out cross validation procedures indentified 100 genes having the strongest predictive values for subclass identification. Forty-four of these 100 genes corresponded to signaling pathways relevant to the adaptive immune system and glucocorticoid receptor signaling, the majority of which were repressed in subclass A patients. Subclass A patients were also characterized by repression of genes corresponding to zinc-related biology. Phenotypic analyses revealed that subclass A patients were younger, had a higher illness severity, and a higher mortality rate than patients in subclasses B and C. Conclusions: Genome-wide expression profiling can identify pediatric septic shock subclasses having clinically relevant phenotypes.
Publication Title
Identification of pediatric septic shock subclasses based on genome-wide expression profiling.
Sample Metadata Fields
Age, Specimen part, Disease, Disease stage
View Samples- Homo sapiens
- 122 Downloadable Samples
Illumina HiSeq 2000
Description
We performed RNA-Seq transcriptome profiling on 29 immune cell types consituting peripheral blood mononuclear cells (PBMCs) sorted from 4 Singaporean-Chinese individuals (S4 cohort). We also performed RNA-Seq and microarray transcriptome profiling of PBMCs from an extended cohort of 13 individuals (S13 cohort). The data was used first to characterize the transcriptomic signatures and relationships among the 29 immune cell types. Then we explored the difference in mRNA composition in terms of transcripts proportions and abundance. Lastly, we performed deep deconvolution for both microarray and RNA-Seq technologies. Overall design: Total RNA of 29 immune cell types (from 4 individuals) and peripheral blood mononuclear cells (PBMCs, from 13 individuals) was extracted for gene expression profiling. The 13 PBMCs samples were processed with both microarray and RNA-Seq platforms.
Publication Title
RNA-Seq Signatures Normalized by mRNA Abundance Allow Absolute Deconvolution of Human Immune Cell Types.
Sample Metadata Fields
Sex, Specimen part, Disease, Subject
View Samples- Homo sapiens
- 13 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
Gene expression from cord blood stem cells and respective derived neuronal cells at different times point of differentiation:CD133+ cells;
Publication Title
Cord blood-derived neuronal cells by ectopic expression of Sox2 and c-Myc.
Sample Metadata Fields
Specimen part, Time
View Samples- Mus musculus
- 9 Downloadable Samples
- Illumina HiSeq 2000
Description
Transcriptome analysis of somatic stem cells and their progeny is fundamental to identify new factors controlling proliferation versus differentiation during tissue formation. Here we generated a combinatorial, fluorescent reporter mouse line to isolate proliferating neural stem cells, differentiating progenitors and newborn neurons that coexist as intermingled cell populations during brain development. Transcriptome sequencing revealed numerous novel long non-coding (lnc)RNAs and uncharacterized protein-coding transcripts identifying the signature of neurogenic commitment. Importantly, most lncRNAs overlapped neurogenic genes and shared with them a nearly identical expression pattern suggesting that lncRNAs control corticogenesis by tuning the expression of nearby cell fate determinants. We assessed the power of our approach by manipulating lncRNAs and protein-coding transcripts with no function in corticogenesis reported to date. This led to several evident phenotypes in neurogenic commitment and neuronal survival indicating that our study provides a remarkably high number of uncharacterized transcripts with hitherto unsuspected roles in brain development. Finally, we focussed on one lncRNA, Miat, whose manipulation was found to trigger pleiotropic effects on brain development and aberrant splicing of Wnt7b. Hence, our study suggests that lncRNA-mediated alternative splicing of cell fate determinants controls stem cell commitment during neurogenesis. “LncRNAs control neurogenesis” Aprea, Prenninger, Dori, Monasor, Wessendof, Zocher, Massalini, Ghosh, Alexopoulou, Lesche, Dahl, Groszer, Hiller, Calegari, The EMBO Journal (In Press) Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.
Publication Title
Transcriptome sequencing during mouse brain development identifies long non-coding RNAs functionally involved in neurogenic commitment.
Sample Metadata Fields
No sample metadata fields
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GSE8121- Homo sapiens
- 66 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
In an ongoing translational research program involving microarray-based expression profiles in pediatric septic shock, we have now conducted longitudinal studies focused on the temporal expression profiles of canonical signaling pathways and gene networks. Genome-level expression profiles were generated from whole blood-derived RNA samples of children with septic shock (n = 30 individual patients) corresponding to days 1 and 3 of admission to the pediatric intensive care unit. Based on sequential statistical and expression filters, day 1 and day 3 of septic shock were characterized by differential regulation of 2,142 and 2,504 gene probes, respectively, relative to normal control patients. Venn analysis demonstrated 239 unique genes in the day 1 data set, 598 unique genes in the day 3 data set, and 1,906 genes common to both data sets. Analyses targeted toward derivation of biological function from these data sets demonstrated time-dependent, differential regulation of genes involved in multiple canonical signaling pathways and gene networks primarily related to immunity and inflammation. Notably, multiple and distinct gene networks involving T cell- and MHC antigen-related biological processes were persistently downregulated from day 1 to day 3. Further analyses demonstrated large scale and persistent downregulation of genes corresponding to functional annotations related to zinc homeostasis. These data represent the largest reported cohort of patients with septic shock, which has undergone longitudinal genome-level expression profiling. The data further advance our genome-level understanding of pediatric septic shock and support novel hypotheses that can be readily tested at both the experimental and translational levels.
Publication Title
Genome-level longitudinal expression of signaling pathways and gene networks in pediatric septic shock.
Sample Metadata Fields
No sample metadata fields
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