EXCEED THE SPACE PROVIDED. In the post-genomic era,the genetic dissection of common diseases (e.g., diabetes, atherosclerosis, obesity, hypertension, depression, alcoholism, osteoporosis, cancer etc.) will be one of the most critically important areas of biomedical science. The specific genes that are involved in the biological pathways of these diseases and their individual effects on the general population are still largely unknown. Genomic localization and identification of these quantitative trait loci (QTLs) and the characterization of the causal functional polymorphisms will require new advanced statistical genetic tools. In this project's first 2.5 years, we have been successful in developing the necessary theoretical and empirical foundationfor variance component-based quantitative trait linkage methods. During this short funding period, we published 37 papers and have an additional 17 in press. We also have incorporated many of our statistical genetic developments into SOLAR, a freely available computer package that is now used by approximately 700 researchers around the world. In this competing renewal application, we propose to continue/expand support for SOLAR and to extend our work on variance-component methods to provide a complete unified framework from initial localization, to fine mapping, to the identification of functional variants in positional candidate genes. The proposed research will address five specific aims: 1) We will continue to examine the statistical features ofvariance component linkageprocedures, such as power and robustness under various study designs, using both analytical methods and extensive computer simulation; 2) We will continue to develop and extend the variance component linkage procedures to include more complex models, such as the incorporation of X-linkage, genotypexenvironment interaction, and multivariate/longitudinal phenotypes; 3) Methods for fine mapping QTLs in extended pedigrees, including extensions of our joint linkage/disequilibrium analysis method and our gamete competition model, will be developed and evaluated; 4) We will develop and evaluate a novel method for quantitative trait nucleotide (QTN) analysis using Bayesian model averaging that allows for the statistical assessment of the functionality of a polymorphism and the prioritization of expensive molecular assays; and 5) All of the above methods will be incorporated into the software package (SOLAR) for statistical genetic analysis of complex traits in extended pedigrees. PERFORMANCE SITE ========================================Section End===========================================
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