Longitudinal bone growth depends upon the execution of an intricate series of cellular activities by epiphyseal growth plate chondrocytes. In order to better understand these coordinated events, microarray analysis was used to compare gene expression in chondrocytes isolated from the proliferative and hypertrophic zones of the avian growth plate.
Use of microarray analysis to study gene expression in the avian epiphyseal growth plate.
Age, Specimen part
View SamplesThe goal of this experiment was to determine gene expression changes during influenza A virus infection as the result of expression influenza virus inducible miRNAs in A549 cells.
Small RNA profiling of influenza A virus-infected cells identifies miR-449b as a regulator of histone deacetylase 1 and interferon beta.
Cell line
View SamplesAn understanding of the mechanisms regulating white adipose tissue (WAT) formation is key for developing of new tools to treat obesity and its related diseases. Here, we identify DEPTOR as a positive regulator of adipogenesis whose expression is associated with obesity. In a polygenic mouse model of obesity/leanness, Deptor is part of the Fob3a QTL linked to obesity and we fine that Deptor is the highest priority candidate gene regulating WAT accumulation in this model. Using a doxycycline-inducible mouse model for Deptor overexpression, we confirmed that Deptor promotes WAT expansion in vivo. DEPTOR expression is elevated in WAT of obese humans and strongly correlates with the degree of obesity. We show that DEPTOR is induced during adipogenesis and that its overexpression cell-autonomously promotes, while its suppression blocks, adipogenesis. DEPTOR positively regulates adipogenesis by promoting the activity of the pro-adipogenic factors Akt/PKB and PPAR-gamma. These results establish DEPTOR as a physiological regulator of adipogenesis and provide new insights into the molecular mechanisms controlling WAT formation.
DEPTOR cell-autonomously promotes adipogenesis, and its expression is associated with obesity.
Sex, Specimen part
View SamplesDiffuse 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.
Gene expression profiling of gliomas strongly predicts survival.
Sex, Age, Specimen part, Disease stage
View SamplesMigrated 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.
Gene expression profiling of gliomas strongly predicts survival.
Sex, Age, Specimen part, Disease, Disease stage
View SamplesAssessment of mRNA expression levels in fat biopsies from subcutaneous adipose tissue from unrelated individuals.
A systems genetics approach implicates USF1, FADS3, and other causal candidate genes for familial combined hyperlipidemia.
Specimen part
View SamplesInduced pluripotent stem (iPS) cells can be obtained from fibroblasts by expression of Oct4, Sox2, Klf4, and c-Myc. To determine how these factors induce this change in cell identity, we carried out genomewide promoter analysis of their binding in iPS and partially reprogrammed cells. Most targets in iPS cells are shared with ES cells and the factors cooperate to activate the ES-like expression program. In partially reprogrammed cells, genes bound by c-Myc have achieved a more ES-like binding and expression pattern. In contrast, genes that are co-bound by Oct4, Sox2, and Klf4 in ES cells and that encode pluripotency regulators show severe lack of both binding and transcriptional activation. Among the factors, c-Myc has a pivotal effect on the initiation of the ES transcription program, including the repression of fibroblast-specific genes. Our analysis begins to unravel how the four factors function together and suggests a temporal and separable order of their effects during reprogramming.
Role of the murine reprogramming factors in the induction of pluripotency.
No sample metadata fields
View SamplesTissue-resident mononuclear phagocytes (MNPs) in metabolic organs contribute to the regulation of whole body metabolism. CD301b+ MNPs are a subset of MNPs that are found in most peripheral organs including metabolic organs. In a mouse model in which CD301b+ MNPs can be selectively and transiently depleted, we examined the impact of the depletion on gene expression in the white adipose tissue and the liver.
CD301b(+) Mononuclear Phagocytes Maintain Positive Energy Balance through Secretion of Resistin-like Molecule Alpha.
Specimen part
View SamplesSymptomatic glycerol kinase deficiency (GKD) is associated with episodic metabolic and central nervous system deterioration. We report here the first application of Weighted Gene Co-Expression Network Analysis (WGCNA) to investigate a knockout (KO) murine model of a human genetic disease. WGCNA identified networks and key hub transcripts from liver mRNA of glycerol kinase (Gyk) KO and wild type (WT) mice. Day of life 1 (dol1) samples from KO mice contained a network module enriched for organic acid metabolism before Gyk KO mice develop organic acidemia and die on dol3-4 and the module containing Gyk was enriched with apoptotic genes. Roles for the highly connected Acot, Psat and Plk3 transcripts were confirmed in cell cultures and subsequently validated by causality testing. We provide evidence that GK may have an apoptotic moonlighting role that is lost in GKD. This systems biology strategy has improved our understanding of GKD pathogenesis and suggests possible treatments.
Weighted gene co-expression network analysis identifies biomarkers in glycerol kinase deficient mice.
Sex, Specimen part
View SamplesOverexpression of USF1 in HEK293T cells in vitro to ascertain the genes downstream of USF1. Will identify direct targets as well as indirect targets of USF1.
A systems genetics approach implicates USF1, FADS3, and other causal candidate genes for familial combined hyperlipidemia.
Cell line
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