Non-insulin dependant diabetes mellitus (NIDDM) is one of the most significant chronic human diseases, affecting over 20 million people in the United States (7% of the population). Twin and family studies have demonstrated a strong genetic component to NIDDM, but despite recent advances in molecular genetics susceptibility genes for the most common forms of the disease have yet to be identified. A large number of genome-wide scans have been published resulting in the identification of multiple genomic regions in humans showing significant linkage to the disease, and many more regions in mouse and rat animal models as well. Work is ongoing in many laboratories and multiple populations to map additional regions. The long-range goal of the proposed effort is to utilize modern methods of comparative genomics together with previously published genomic research to facilitate the discovery of genetic susceptibility components for NIDDM. Quantitative trait locus (QTL) and single nucleotide polymorphism (SNiP) information from human, mouse and rat studies will be compiled, compared and analyzed. Comparative genomics tools will be used and developed as necessary to narrow the QTL intervals and to identify consensus regions among the species. These regions may then be further localized using SNiP mapping techniques. Comprehensive lists of candidate genes and SNiPs from the consensus regions will be made available for focused study in future projects. The lists of candidate genes, as well as the developed tools and maps used to identify them, will be made publicly available in an online database. The specific objectives of this project are: 1. Identify genetic susceptibility components for NIDDM. 2. Build an online database to house information and tools. 3. Promote and enhance bioinformatics training at Virginia State University. Relevance of research to public health: This research will use comparative genomics to enhance previously published genomic research on non-insulin dependant diabetes mellitus (NIDDM). The ultimate goal is to construct a comprehensive list of genes that are most likely to be involved in susceptibility to the disease.
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