DESCRIPTION (adapted from the application) Chronic renal failure frequently progresses to end stage renal disease (ESRD), resulting in significant morbidity, mortality and economic burden to the health care delivery system. The lack of effective therapies for chronic renal failure is partly a testament to the complex nature of the disease. Accumulating evidence suggests that genetic predisposition plays important role in the progression of chronic renal failure to ESRD. To date, no nephropathy susceptibility gene(s) have yet been identified in humans, despite the efforts of multiple laboratories using classical genetic methods, including gene mapping and loci scanning. We propose to utilize an animal model for ESRD (the oligosyndactyly mouse) to try to identify genes that might be involved in the pathogenesis and/or affect the progression of chronic renal failure to ESRD. We adopted an empiric approach utilizing a novel powerful technique called serial analysis of gene expression (SAGE) that will allow systematic analysis and comparison of gene expression libraries in diseased animals and their wild type controls. Our Specific Aims are: 1) To generate SAGE expression libraries from kidneys of ROP-Os/+, C57BL/6-Os/+, ROP-+/+, and C57BL/6-+/+ mice, and 2) To analyze the expression libraries using Monte Carlo simulation analysis and hierarchical clustering to identify candidate genes and pathways involved in renal disease pathogenesis. An algorithm is proposed to prioritize candidate genes identified by these analyses of the libraries. Functional analysis of these genes will be performed in future studies using standard molecular and genetic techniques, which will allow us to learn more about pathways critical for renal disease pathogenesis. Ultimately, this might pave the way to the development of new therapeutic and/or diagnostic modalities.