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FOG-2 is a multi-zinc finger protein that binds the transcriptional activator GATA4 and modulates GATA4-mediated regulation of target genes during heart development. Our previous work has demonstrated that the Nucleosome Remodeling and Deacetylase (NuRD) complex physically interacts with FOG-2 and is necessary for FOG-2 mediated repression of GATA4 activity in vitro. However, the relevance of this interaction for FOG-2 function in vivo has remained unclear. In this report, we demonstrate the importance of FOG-2/NuRD interaction through the generation and characterization of mice homozygous for a mutation in FOG-2 that disrupts NuRD binding (FOG-2(R3K5A)). These mice exhibit a perinatal lethality and have multiple cardiac malformations, including ventricular and atrial septal defects and a thin ventricular myocardium. To investigate the etiology of the thin myocardium, we measured the rate of cardiomyocyte proliferation in wild-type and FOG-2(R3K5A) developing hearts. We found cardiomyocyte proliferation was reduced by 31±8% in FOG-2(R3K5A) mice. Gene expression analysis indicated that the cell cycle inhibitor Cdkn1a (p21(cip1)) is up-regulated 2.0±0.2-fold in FOG-2(R3K5A) hearts. In addition, we demonstrate that FOG-2 can directly repress the activity of the Cdkn1a gene promoter, suggesting a model by which FOG-2/NuRD promotes ventricular wall thickening by repression of this cell cycle inhibitor. Consistent with this notion, the genetic ablation of Cdkn1a in FOG-2(R3K5A) mice leads to an improvement in left ventricular function and a partial rescue of left ventricular wall thickness. Taken together, our results define a novel mechanism in which FOG-2/NuRD interaction is required for cardiomyocyte proliferation by directly down-regulating the cell cycle inhibitor Cdkn1a during heart development.
Pubmed ID: 25196150
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A web-based software application that enables users to analyze, integrate, and understand data derived from gene expression, microRNA, and SNP microarrays, metabolomics, proteomics, and RNA-Seq experiments, and small-scale experiments that generate gene and chemical lists. Users can search for targeted information on genes, proteins, chemicals, and drugs, and build interactive models of experimental systems. IPA allows exploration of molecular, chemical, gene, protein and miRNA interactions, creation of custom molecular pathways, and the ability to view and modify metabolic, signaling, and toxicological canonical pathways. In addition to the networks and pathways that can be created, IPA can provide multiple layering of additional information, such as drugs, disease genes, expression data, cellular functions and processes, or a researchers own genes or chemicals of interest.
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