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Danio rerio
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Description
Investigation of expression differences between skin and melanomas from a transgenic BRAFV600E zebrafish model of melanoma The embryos described in this study are further analyzed in a manuscript submitted for publication by White, et al. A 15 chip study using RNA extracted from either WT zebrafish skin, mitf-BRAFV600E;p53-/- skin or mitf-BRAFV600E;p53-/- melanoma
Publication Title
DHODH modulates transcriptional elongation in the neural crest and melanoma.
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Specimen part, Subject
View Samples- Mus musculus
- 19 Downloadable Samples
Description
3 subtypes of cortical projection neurons were purified by fluorescence-activated cell sorting (FACS) at 4 different stages of development from mouse cortex. A detailed description of the data set is described in Arlotta, P et al (2005) and Molyneaux, BJ et al (2009). The hybridization cocktails used here were originally applied to the Affymetrix mouse 430A arrays and submitted as GEO accession number GSE2039. The same hybridization cocktails were then applied to the Affymetrix mouse 430 2.0 arrays, and those data are contained in this series.
Publication Title
Novel subtype-specific genes identify distinct subpopulations of callosal projection neurons.
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Specimen part
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GSE24061- Mus musculus
- 4 Downloadable Samples
Description
The Hamner data set (endpoint A) was provided by The Hamner Institutes for Health Sciences (Research Triangle Park, NC, USA). The study objective was to apply microarray gene expression data from the lung of female B6C3F1 mice exposed to a 13-week treatment of chemicals to predict increased lung tumor incidence in the 2-year rodent cancer bioassays of the National Toxicology Program. If successful, the results may form the basis of a more efficient and economical approach for evaluating the carcinogenic activity of chemicals. Microarray analysis was performed using Affymetrix Mouse Genome 430 2.0 arrays on three to four mice per treatment group, and a total of 70 mice were analyzed and used as the MAQC-II's training set (GEO Series GSE6116). Additional data from another set of 88 mice were collected later and provided as the MAQC-II's external validation set (this Series). The training dataset had already been deposited in GEO by its provider and its accession number is GSE6116.
Publication Title
Effect of training-sample size and classification difficulty on the accuracy of genomic predictors.
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Specimen part, Compound
View Samples- Mus musculus
- 6 Downloadable Samples
Description
The objective of this set of samples is to identify genes that are differentially expressed following the introduction of DNA double strand breaks (DSBs) by ionizing radiation in wild-type murine pre-B cells. The data generated in this project will be compared to the data generated in GSE9024, in which genes that are differentially expressed following the introduction of DNA double strand breaks (DSBs) by the Rag proteins in murine pre-B cells were examined. In order to understand the differences between the physiologic and genotoxic responses to DSB DNA damage, we need to compare cells that are all in the same compartment of the cell cycle. We are therefore examining the response to IR-induced damage in cells that are arrested in G1, which would correspond to our previous study of G1 arrested cells with Rag-induced breaks. This will illuminate the difference directly, allowing us to better understand the signaling responses to the different types of DNA damage.
Publication Title
DNA damage activates a complex transcriptional response in murine lymphocytes that includes both physiological and cancer-predisposition programs.
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Specimen part
View Samples- Mus musculus
- 34 Downloadable Samples
Description
Aim of present study was to describe the changes induced deletion of the Wfs1 gene in the temporal lobe of mice. Mutant mice were backcrossed to two different genomic backgrounds in order to exclude confounding foreign genomic background influence. Samples from temporal lobes were analyzed by using Affymetrix Genechips, expression profiles were functionally annotated by using GSEA and Ingenuity Pathway Analysis. We found that Wfs1 mutant mice are significantly smaller (20.9 1.6 g) than their wild-type counterparts (31.0 0.6g, p < 0.0001). Interestingly, genechip analysis identified growth hormone transcripts up-regulated and functional analysis found appropriate pathways activated. Moreover, we found significant increase in the level of IGF1 in the plasma of wfs1 mutant mice. Taken together, wfs1 mutation induces growth retardation whereas the growth hormone pathway is activated. Further studies are needed to describe biochemical and molecular details of the growth hormone axis in the wfs1 mutant mice.
Publication Title
Wfs1 gene deletion causes growth retardation in mice and interferes with the growth hormone pathway.
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Specimen part
View Samples- Mus musculus
- 12 Downloadable Samples
Description
Microarray expression profiling has become a valuable tool in the evaluation of the genetic consequences of metabolic disease. Although 3-biased gene expression microarray platforms were the first generation to have widespread availability, newer platforms are gradually emerging that have more up-to-date content and/or higher cost efficiency. Deciphering the relative strengths and weaknesses of these various platforms for metabolic pathway level analyses can be daunting. We sought to determine the practical strengths and weaknesses of four leading commercially-available expression array platforms relative to biologic investigations, as well as assess the feasibility of cross-platform data integration for purposes of biochemical pathway analyses. METHODS: Liver RNA from B6.Alb/cre,Pdss2loxP/loxP mice having primary Coenzyme Q deficiency was extracted either at baseline or following treatment with an antioxidant/antihyperlipidemic agent, probucol. Target RNA samples were prepared and hybridized to Affymetrix 430 2.0, Affymetrix Gene 1.0 ST, Affymetrix Exon 1.0 ST, and Illumina Mouse WG-6 expression arrays. Probes on all platforms were re-mapped to coding sequences in the current version of the mouse genome. Data processing and statistical analysis were performed by R/Bioconductor functions, and pathway analyses were carried out by KEGG Atlas and GSEA. RESULTS: Expression measurements were generally consistent across platforms. However, intensive probe-level comparison suggested that differences in probe locations were a major source of inter-platform variance. In addition, genes expressed at low or intermediate levels had lower inter-platform reproducibility than highly expressed genes. All platforms showed similar patterns of differential expression between sample groups, with steroid biosynthesis consistently identified as the most down-regulated metabolic pathway by probucol treatment. CONCLUSIONS: This work offers a timely guide for metabolic disease investigators to enable informed end-user decisions regarding choice of expression microarray platform best-suited to specific research project goals. Successful cross-platform integration of biochemical pathway expression data is also demonstrated, especially for well-annotated and highly-expressed genes. However, integration of gene-level expression data is limited by individual platform probe design and the expression level of target genes. Cross-platform analyses of biochemical pathway data will require additional data processing and novel computational bioinformatics tools to address unique statistical challenges.
Publication Title
Cross-platform expression microarray performance in a mouse model of mitochondrial disease therapy.
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Sample Metadata Fields
Sex, Age, Specimen part, Treatment
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