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GSE11018
Mus musculus
6 Downloadable Samples
Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
Familial pulmonary arterial hypertension (fPAH) is associated with mutations in BMPR2. Many of these mutations occur in the BMPR2 tail domain, leaving the SMAD functions intact. In order to determine the in vivo consequences of BMPR2 tail domain mutation, we created a smooth-muscle specific doxycycline inducible BMPR2 mutation with an arginine to termination mutation at amino acid 899. When these SM22-rtTA x TetO7-BMPR2R899X mice had transgene induced for 9 weeks, starting at 4 weeks of age, they universally developed pulmonary vascular pruning as assessed by fluorescent microangiography. Approximately half the time the induced animals developed elevated right ventricular systolic pressures (RVSP), associated with extensive pruning, muscularization of small pulmonary vessels, and development of large structural pulmonary vascular changes. These lesions included large numbers of macrophages and T-cells in their adventitial compartment, as well as CD133 positive cells in the lumen. Small vessels filled with CD45 positive and sometimes CD3 positive cells were a common feature in all SM22-rtTA x TetO7-BMPR2R899X mice. Gene array experiments show changes in stress response, muscle organization and function, proliferation and apoptosis, and developmental pathways before RVSP increases. Our results show that the primary phenotypic result of BMPR2 tail domain mutation in smooth muscle is pulmonary vascular pruning leading to elevated RVSP, associated with early dysregulation in multiple pathways with clear relevance to PAH. This model should be useful to the research community in examining early molecular and physical events in the development of PAH, and as a platform to validate potential treatments.
Publication Title
Mice expressing BMPR2R899X transgene in smooth muscle develop pulmonary vascular lesions.
Sample Metadata Fields
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View Samples- Mus musculus
- 6 Downloadable Samples
- Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
Histone modifications are a key epigenetic mechanism to activate or repress the expression of genes. Data sets of matched microarray expression data and histone modification data measured by ChIP-seq exist, but methods for integrative analysis of both data types are still rare. Here, we present a novel bioinformatic approach to detect genes that are differentially expressed between two conditions putatively caused by alterations in histone modification. We introduce a correlation measure for integrative analysis of ChIP-seq and gene expression data and demonstrate that a proper normalization of the ChIP-seq data is crucial. We suggest applying Bayesian mixture models of different distributions to further study the distribution of the correlation measure. The implicit classification of the mixture models is used to detect genes with differences between two conditions in both gene expression and histone modification. The method is applied to different data sets and its superiority to a naive separate analysis of both data types is demonstrated. This GEO series contains the expression data of the Cebpa example data set.
Publication Title
Integrative analysis of histone ChIP-seq and transcription data using Bayesian mixture models.
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