We propose to conduct comprehensive genome-wide mapping and a novel method named reciprocal hemizygosity analysis to fully identify all major-effect genes underlying the quantitative trait of high-temperature growth in yeast. Because quantitative traits are poorly understood, we have developed S. cerevisiae as a model for the study of quantitative traits and have chosen high temperature growth because it is readily quantifiable and as previously described for pathogenic fungi, the ability to grow at high temperature is important for pathogenicity. Our combination of technologies designed, developed and tested in our laboratory and applied to dissect a high-temperature growth quantitative trait locus (QTL) in yeast is now ready for large-scale application. Our first study revealed an unexpectedly complex genetic architecture with three quantitative trait genes in a single 32-kb mapped interval. Now we are ready to expand that study and try to understand the genetic architecture at other QTLs and for other traits. We wiU identify new QTLs by genome-wide mapping of F2 backcross progeny using direct allelic variation scanning, our high-throughput array-based genotyping assay that reduces the time for a genome scan to 1 day. Denaturing HPLC fine-structure mapping, sequence analysis, mRNA expression analysis, and reciprocal hemizygosity analysis will be applied to identify and evaluate the responsible genes in each mapped QTL. In conjunction a new application named reciprocal hemizygosity scanning will be tested and applied to identify quantitative trait genes directly on a genome-scale. Reciprocal hemizygosity scanning is a tool for comparing two genomes and identifying all phenotypically relevant allelic differences in a single step using a hybrid strain. With this technology throughput may be increased to one trait per overnight experiment. We expect that this combination of approaches will yield the most comprehensive list to date of genetic factors underlying quantitative traits. Since we project that the next major hurdle lies in functional studies of interactions among loci, we propose to generate allele replacement yeast strains containing different combinations of quantitative trait genes. The establishment of tools for identifying quantitative trait genes and results on their functional reconstitution and genetic engineering will provide the best data for approaching complex traits for medical studies.
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