Determining the source of missing heritability

项目摘要 大多数人类特征是复杂的/定量的。同样，许多常见的人类疾病 复杂;它们通常不是由少数基因引起的，而是受到基因的影响。 由成百上千个基因组成关于数量性状知之甚少， 概念、实验和分析局限性。该提案旨在解决几个关键问题 问题：1）什么是可以驱动数量性状的基因，它们是如何相互关联的， 2)在自然群体中，驱动数量性状变异的基因是什么？ 每个数量基因的表型是如何联合收割机决定整体的 性状的表型，即基因-基因相互作用重要。半乳糖的诱导， 芽殖酵母Saccharomycescerevisiae中的磷酸盐代谢基因是经典的 用于探测信号的真核模型系统。本提案中描述的初步结果 表明这些反应也是复杂的特质。我们的实验室已经开发出高- 通量流式细胞术方法，其对于准确确定 基因对数量性状的影响。充分发挥两国 实验强度，我们将结合联合收割机荧光报告菌株与一系列缺失或 剂量扰动文库。我们将生成最全面的定量列表， 基因还在这些性状中的每一个，并评估这些定量基因的相互作用， 在特质之间。利用等位基因交换结合群体分离分析和经典连锁 我们将确定数量基因的等位基因在性质上的变化程度。通过组合 在零到四个等位基因之间或缺失定量基因时，我们将能够直接测试 基因间相互作用的重要性。这种方法的结合将大大提高 我们对复杂性状的理解与人类疾病有直接关系。

Project Summary Most human traits are complex/quantitative. Similarly, many common human diseases are complex; they typically are not caused by a small number of genes, but instead are influenced by hundreds if not thousands of genes. Little is known about quantitative traits due to conceptual, experimental, and analytical limitations. This proposal aims to address several key questions: 1) what are the genes that can drive a quantitative trait and how are they interrelated, 2) what are the genes that drive variation in a quantitative trait in natural populations, and 3) how do the phenotypes of each individual quantitative gene combine to determine the overall phenotype of the trait, i.e. are gene-gene interactions important. The induction of galactose and phosphate metabolic genes in the budding yeast Saccharomyces cerevisiae are classical Eukaryotic model systems for probing signaling. Preliminary results described in this proposal show that these responses are also complex traits. Our laboratory has developed high- throughput flow cytometry methods that are essential for accurately determining the effects of genes on quantitative traits both among natural variants and mutant strains. Building on our experimental strengths, we will combine fluorescence reporter strains with a series of deletion or dosage perturbation libraries. We will generate the most comprehensive list of quantitative genes yet in each of these traits, and assess the interplay of these quantitative genes within and between traits. Using allele swaps combined with bulk segregant analysis and classical linkage we will determine the extent to which alleles of quantitative genes vary in nature. By combining between zero to four alleles or deletion of quantitative genes, we will be able to directly test the importance of gene-gene interactions. This combination of approaches should greatly enhance our understanding of complex traits and have direct relevance for human disease.