Disorders of the cardiovascular (CV) system are frequently due to temporal or quantitative changes in the expression of a large, but finite set of genes. Noncoding cis regulatory sequences play a central role in controlling gene expression and inter-species (i.e., human/mouse) genomic sequence comparisons serve as a rapid and accurate means for identifying such noncoding regulatory elements. The central goal of this PGA will be to use a comparative genomic approach first to identify, and them to determine the function of elements regulating the expression of genes affecting the CV system. The activities of this PGA are not centered on the discovery of new genes, but rather upon using comparative genomics to understand the role of cis regulating elements in the expression of genes already being studied by CV researchers. In this integrated program to """"""""genomically"""""""" explore the regulation of CV genes, 200 human genomic intervals (=~200 BACs), each containing a CV gene(s), will be comparatively characterized. The components of this program will include: (1) The acquisition of orthologous human/mouse and other mammalian genomic sequence for a set of prioritized CV genes. Sequences will either be accessed from publicly funded databases or generated by the sequencing component of this PGA. (2) The creation of a cardiovascular comparative genomic database that will contain extensively annotated human and mouse sequences including the localization of conserved noncoding elements in proximity to well studied CV genes. (3) Genome-wide expression profiling to discover genes co-regulated with CV genes and identify shared noncoding regulatory elements, through intra-species analysis. (4) The identification of SNPs within conserved non- coding sequences, and analysis of their effect on CV gene expression in humans. (5) Analysis in genetically engineered mice of a prioritized set of the conserved noncoding elements for their role in CV gene expression. (6) The establishment of an educational program for cardiovascular researchers in the use of genomic databases and tools.
| Mar, Rebecca; Pajukanta, Paivi; Allayee, Hooman et al. (2004) Association of the APOLIPOPROTEIN A1/C3/A4/A5 gene cluster with triglyceride levels and LDL particle size in familial combined hyperlipidemia. Circ Res 94:993-9 |
| Banerjee, Poulabi; Bahlo, Melanie; Schwartz, Jody R et al. (2002) SNPs in putative regulatory regions identified by human mouse comparative sequencing and transcription factor binding site data. Mamm Genome 13:554-7 |
