We measured transcriptional changes resulting from overexpression or downregulation of the GTPase Obg.
Obg and Membrane Depolarization Are Part of a Microbial Bet-Hedging Strategy that Leads to Antibiotic Tolerance.
No sample metadata fields
View SamplesAn important but largely unmet challenge in understanding the mechanisms that govern formation of specific organs is to decipher the complex and dynamic genetic programs exhibited by the diversity of cell types within the tissue of interest. Here, we use an integrated genetic, genomic and computational strategy to comprehensively determine the molecular identities of distinct myoblast subpopulations within the Drosophila embryonic mesoderm at the time that cell fates are initially specified. A compendium of gene expression profiles was generated for primary mesodermal cells purified by flow cytometry from appropriately staged wild-type embryos and from twelve genotypes in which myogenesis was selectively and predictably perturbed. A statistical meta-analysis of these pooled datasetsbased on expected trends in gene expression and on the relative contribution of each genotype to the detection of known muscle genesprovisionally assigned hundreds of differentially expressed genes to particular myoblast subtypes. Whole embryo in situ hybridizations were then used to validate the majority of these predictions, thereby enabling true positive detection rates to be estimated for the microarray data. This combined analysis reveals that myoblasts exhibit much greater gene expression heterogeneity and overall complexity than was previously appreciated. Moreover, it implicates the involvement of large numbers of uncharacterized, differentially expressed genes in myogenic specification and subsequent morphogenesis. These findings also underscore a requirement for considerable regulatory specificity for generating diverse myoblast identities. Finally, to illustrate how the developmental functions of newly identified myoblast genes can be efficiently surveyed, a rapid RNA interference assay that can be scored in living embryos was developed and applied to selected genes. This integrated strategy for examining embryonic gene expression and function provides a substantially expanded framework for further studies of this model developmental system.
An integrated strategy for analyzing the unique developmental programs of different myoblast subtypes.
No sample metadata fields
View SamplesThe forkhead O transcription factors (FOXO) integrate a range of extracellular signals including growth factor signaling, inflammation, oxidative stress and nutrient availability, to substantially alter the program of gene expression and modulate cell survival, cell cycle progression, and many cell-type specific responses yet to be unraveled. Naive antigen-specific CD8+ T cells undergo a rapid expansion and arming of effector function within days of pathogen exposure, but in addition, by the peak of expansion, they form precursors to memory T cells capable of self-renewal and indefinite survival.
Differentiation of CD8 memory T cells depends on Foxo1.
Specimen part
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Transcriptomic signature of fasting in human adipose tissue.
Age, Specimen part, Subject
View SamplesLittle is known about the impact of fasting on gene regulation in human adipose tissue. Accordingly, the objective of this study was to investigate the effects of fasting on adipose tissue gene expression in humans. To that end, subcutaneous adipose tissue biopsies were collected from volunteers 2h and 26h after consumption of a standardized meal. For comparison, epididymal adipose tissue was collected from C57Bl/6J mice after a 16h fast and in the ab-libitum fed state. Transcriptome analysis was carried out using Affymetrix microarrays. We found that, 1) fasting downregulated numerous metabolic pathways in human adipose tissue, including triglyceride and fatty acid synthesis, glycolysis and glycogen synthesis, TCA cycle, oxidative phosphorylation, mitochondrial translation, and insulin signaling; 2) fasting downregulated genes involved in proteasomal degradation in human adipose tissue; 3) fasting had much less pronounced effects on the adipose tissue transcriptome in humans than mi ce; 4) although major overlap in fasting-induced gene regulation was observed between human and mouse adipose tissue, many genes were differentially regulated in the two species, including genes involved in insulin signaling (PRKAG2, PFKFB3), PPAR signaling (PPARG, ACSL1, HMGCS2, SLC22A5, ACOT1), glycogen metabolism (PCK1, PYGB), and lipid droplets (PLIN1, PNPLA2, CIDEA, CIDEC). In conclusion, although numerous genes and pathways are regulated similarly by fasting in human and mouse adipose tissue, many genes show very distinct responses to fasting in humans and mice. Our data provide a useful resource to study adipose tissue function during fasting.
Transcriptomic signature of fasting in human adipose tissue.
Specimen part
View SamplesMicroarray expression profilling of mouse primary mixed cortical/hippocampal neurons, primary fibroblasts and L929 cells to compare ISGs signature in disctinct cell types
Inefficient type I interferon-mediated antiviral protection of primary mouse neurons is associated with the lack of apolipoprotein l9 expression.
Specimen part, Cell line
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Feasibility of developing reliable gene expression modules from FFPE derived RNA profiled on Affymetrix arrays.
Specimen part
View SamplesThe reliability of differential expression analysis on FFPE expression profiles from Affymetrix arrays is questionable, due to the wide range of percent-present values reported in studies which profiled FFPE samples on Affymetrix arrays. Moreover the validity of externally defined gene-modules in FFPE microarray expression profiles is unknown. Using eight breast cancer tumors with available frozen and FFPE samples, five sample-matched data sets were generated from different combination of Affymetrix arrays, amplification-and-labeling kit and sample preservation method. The reliability of differential expression analysis was investigated by developing de novo ER/HER2 pathway gene-modules from matched data sets and validating it on external data set using ROC analysis. Spearman's rank correlation coefficient of module scores between matched FFPE-frozen expression profiles was used to measure reliability of externally defined gene-modules in FFPE expression profiles. Independent of array/amplification-kit/sample preservation method used, de novo ER/HER2 gene-modules derived from all matching data sets showed similar prediction performance during independent validation (AUC range; ER: 0.92-0.95, HER2: 0.88-0.91), except for de novo HER2 gene-module derived from FFPE data set with 3'IVT kit (AUC: 0.67-0.72). Further not all gene-module based biological signals present in frozen expression profiles can be recovered from matching FFPE microarray expression profiles using the currently available FFPE specific sample preparation kits. The gene-module based biological signal extracted from FFPE RNA, using microarrays, may not be as reliable as that from their frozen counterpart, if the sample preparation protocol used with FFPE RNA failed to recover relevant genes involved in the biological signal.
Feasibility of developing reliable gene expression modules from FFPE derived RNA profiled on Affymetrix arrays.
Specimen part
View SamplesThe reliability of differential expression analysis on FFPE expression profiles from Affymetrix arrays is questionable, due to the wide range of percent-present values reported in studies which profiled FFPE samples on Affymetrix arrays. Moreover the validity of externally defined gene-modules in FFPE microarray expression profiles is unknown. Using eight breast cancer tumors with available frozen and FFPE samples, five sample-matched data sets were generated from different combination of Affymetrix arrays, amplification-and-labeling kit and sample preservation method. The reliability of differential expression analysis was investigated by developing de novo ER/HER2 pathway gene-modules from matched data sets and validating it on external data set using ROC analysis. Spearman's rank correlation coefficient of module scores between matched FFPE-frozen expression profiles was used to measure reliability of externally defined gene-modules in FFPE expression profiles. Independent of array/amplification-kit/sample preservation method used, de novo ER/HER2 gene-modules derived from all matching data sets showed similar prediction performance during independent validation (AUC range; ER: 0.92-0.95, HER2: 0.88-0.91), except for de novo HER2 gene-module derived from FFPE data set with 3'IVT kit (AUC: 0.67-0.72). Further not all gene-module based biological signals present in frozen expression profiles can be recovered from matching FFPE microarray expression profiles using the currently available FFPE specific sample preparation kits. The gene-module based biological signal extracted from FFPE RNA, using microarrays, may not be as reliable as that from their frozen counterpart, if the sample preparation protocol used with FFPE RNA failed to recover relevant genes involved in the biological signal.
Feasibility of developing reliable gene expression modules from FFPE derived RNA profiled on Affymetrix arrays.
Specimen part
View SamplesThe reliability of differential expression analysis on FFPE expression profiles from Affymetrix arrays is questionable, due to the wide range of percent-present values reported in studies which profiled FFPE samples on Affymetrix arrays. Moreover the validity of externally defined gene-modules in FFPE microarray expression profiles is unknown. Using eight breast cancer tumors with available frozen and FFPE samples, five sample-matched data sets were generated from different combination of Affymetrix arrays, amplification-and-labeling kit and sample preservation method. The reliability of differential expression analysis was investigated by developing de novo ER/HER2 pathway gene-modules from matched data sets and validating it on external data set using ROC analysis. Spearman's rank correlation coefficient of module scores between matched FFPE-frozen expression profiles was used to measure reliability of externally defined gene-modules in FFPE expression profiles. Independent of array/amplification-kit/sample preservation method used, de novo ER/HER2 gene-modules derived from all matching data sets showed similar prediction performance during independent validation (AUC range; ER: 0.92-0.95, HER2: 0.88-0.91), except for de novo HER2 gene-module derived from FFPE data set with 3'IVT kit (AUC: 0.67-0.72). Further not all gene-module based biological signals present in frozen expression profiles can be recovered from matching FFPE microarray expression profiles using the currently available FFPE specific sample preparation kits. The gene-module based biological signal extracted from FFPE RNA, using microarrays, may not be as reliable as that from their frozen counterpart, if the sample preparation protocol used with FFPE RNA failed to recover relevant genes involved in the biological signal.
Feasibility of developing reliable gene expression modules from FFPE derived RNA profiled on Affymetrix arrays.
Specimen part
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