Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Gene expression and phenotypic characterization of mouse heart after chronic constant or intermittent hypoxia

ABSTRACT: Chronic constant hypoxia (CCH), such as in pulmonary diseases or high altitude, and chronic intermittent hypoxia (CIH), such as in sleep apnea, can lead to major changes in the heart. The molecular mechanisms underlying these cardiac alterations are not well understood. We hypothesized that analysis on the changes in gene expression could help to delineate such mechanisms. In addition, the differences that can be anticipated between CCH and CIH could be potentially dissected. Current study used CCH and CIH mouse models combined with cDNA microarrays to determine the changes of gene expression in CCH or CIH mice heart. Keywords = heart Keywords = hypoxia Keywords = mouse Keywords = microarray Keywords: time-course

ORGANISM(S): Mus musculus

SUBMITTER: Chenghao Fan

PROVIDER: E-GEOD-2271 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Integrated transcriptomic response to cardiac chronic hypoxia: translation regulators and response to stress in cell survival.

Iacobas Dumitru A DA Fan Chenhao C Iacobas Sanda S Haddad Gabriel G GG

Functional & integrative genomics 20080501 3

Complementary deoxyribonucleic acid microarray data from 36 mice subjected for 1, 2, or 4 weeks of their early life to normal atmospheric conditions (normoxia) or chronic intermittent (CIH) or constant (CCH) hypoxia were analyzed to extract organizational principles of the developing heart transcriptome and determine the integrated response to oxygen deprivation. Although both CCH and CIH regulated numerous genes involved in a wide diversity of processes, the changes in maturational profile, exp ...[more]

PMID: 18446526

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Project description:cDNA microarrays have been shown to be useful for monitoring global gene expression patterns in normal and disease states and in response to various environmental stimuli. In this study we have used a cattle cDNA microarray containing 7653 elements to analyze expression profiles in 19 different cattle tissues. Signal intensities from all tissue sample RNAs were compared to a reference standard RNA created from different tissues and cell lines. Data analysis identified a subset of genes significantly differentially expressed between tissues and the reference standard that were further subdivided according to fold change. Log transformed ratios were normalized using the intensity-based regional Lowess algorithm. A global error model, to account for the dependence of variation on signal intensities, was used to identify lists of genes for effect of tissue on gene expression taking into account an experiment-wise significance of 0.05, using either a Bonferroni correction (663 genes) or Benjamini and Hochbergâ??s False Discovery Rate (3350 genes). Non-supervised cluster analysis revealed groups of genes common to nerve, muscle, immune or digestive tissues. Discriminant analysis was used to support physiological functional categories and embryonic origin of tissues. Unique profiles were constructed with genes preferentially expressed in specific tissues or tissue groups in order to define gene expression for individual tissues. Global expression along a large collection of tissues revealed tissue specific expression of enzyme isomers and utilization in specific metabolic pathways. A comprehensive matrix of all possible pair-wise comparisons for individual genes among tissues was constructed to further identify genes with tissue-specific behavior and possibly unique function. A reference design was used to compare 19 cattle tissues. All tissues were compared to a universal control consisting of a mix of cattle cell lines. All samples were duplicated with a dye swap.

Project description:We used cDNA microarray technology to compare the genome-wide expression profiles of a wild type strain (BY4700) (E02, E04, E06) or the isogenic strain deleted of GLN3 and GAT1 genes (E01, E03, E05) grown in YNB medium with glutamine as nitrogen source (M.Gln) against the wild type strain grown in M.Gln after addition of rapamacyn (20 min) (E01, E02), or M.proline (M.Pro) (E03, E04) or after a two hours shift from M.Gln to M.Pro (E05, E06), all growth conditions known to modify the expression of genes involved in nitrogen utilization. These microarrays allowed to identify the set of genes that were up or down-regulated in response to the quality of the nitrogen source. To evaluate whether the majority of genes responding to the nitrogen source were dependent on Gln3 and Gat1, we compared the expression profiles of the wild type strain and of the isogenic strain deleted of GLN3 and GAT1 genes (03167b: ura3, gln3â, gat1â), when both strains were grown on M.Gln + rapamycin (E07), or M.Pro (E08) or after a shift from M.Gln to M.Pro (E09). We also used an independent means of identifying Gln3-Gat1 regulated genes by comparing the expression profiles in wild type and ure2â (4709âURE2) strains on M.Gln medium (E10). The hybridization signal was measured using a GSM418 laser scanner. Image analysis for each array was processed using the GenePix Pro 4.0 (Axon Instruments, Inc.) software package, which measures fluorescence intensity pairs for each gene. Following image acquisition, a visual inspection of the individual spots on each microarray (size, signal-to-noise ratio, background level, and spot uniformity) completed the flagging (present/not present, good/bad) of the data. To maximize sensitivity two scans were made, one at high laser power and high PMT (Photo Multiplier Tube) gain to detect the faintest spots, and a second one using low laser power and a PMT gain avoiding saturation. The values for spots presenting â¥ 5% saturation in the first scan were calculated based on an extrapolation after linear regression analysis of the intensities from both scans. These data were then imported in the GeneSpring 7.1 (Silicon Genetics) software package, applying a per spot per chip intensity-dependent (Lowess) normalization for further analysis.

Dataset Information

Gene expression and phenotypic characterization of mouse heart after chronic constant or intermittent hypoxia

Publications

Integrated transcriptomic response to cardiac chronic hypoxia: translation regulators and response to stress in cell survival.

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