High resolution genetic dissection of complex and quantitative traits in yeast

项目摘要/摘要 复杂和数量性状的遗传解剖在基础和生物医学中仍然是一个巨大的挑战 研究。尽管酵母酿酒酵母是一个潜在的强大的模型系统来解决 关于基因结构的基本问题，它的承诺还没有完全实现。更具体地说，有 需要开发新的工具来揭示基因结构的基本特征。至 为此，在目标1中，我们将在酵母中建立一个强大的作图群体，用于高分辨率遗传 复杂和数量性状的剖析。具体地说，我们将从漏斗十字中创建10,000个子代 在八个智能选择的亲本菌株中，捕捉到了相当大比例的遗传变异 酿酒酵母自然分离株的分离。初步分析证明了绘制变种图谱的能力 弱效应和上下文依赖效应，如基因与基因的相互作用，将是非常高的。重要的是 大量的减数分裂将允许极高的作图分辨率，通常是在单个基因的规模上。 或者更小。所有10,000个子代都将进行密集的基因分型，从而使整个基因组序列数据准确 归罪于。在目标2中，我们将开发新的统计方法，以利用这项实验的内在力量 克罗斯。更具体地说，我们将开发新的方法来检测基因-基因相互作用和预测病因 来自不同数据源的变体。最后，在目标3中，我们将使用实验杂交来 全面描绘了一套具有生物医学重要性的表型的遗传结构，如 抗真菌耐药性和生物被膜的形成。总体而言，我们开发的测绘人口和统计工具 将使人们能够对复杂和数量性状的遗传结构进行强大而全面的洞察， 补充了其他模式生物复杂杂交的发展，为研究提供了新的方法 解释全基因组序列数据，并对相关的潜在治疗靶点产生新的见解 真菌致病机制。

PROJECT SUMMARY/ ABSTRACT The genetic dissection of complex and quantitative traits remains a formidable challenge in basic and biomedical research. Although the yeast Saccharomyces cerevisiae is a potentially powerful model system to address fundamental questions about genetic architecture, its promise has not been fully realized. More specifically, there is a need to develop new tools to reveal insights into the fundamental characteristics of genetic architecture. To this end, in Aim 1, we will develop a powerful mapping population in yeast for the high- resolution genetic dissection of complex and quantitative traits. Specifically, we will create 10,000 progeny from a funnel cross among eight intelligently selected parental strains that captures a substantial proportion of genetic variation segregating in natural isolates of S. cerevisiae. Preliminary analyses demonstrate the power to map variants of weak effect and context dependent effects, such as gene-gene interactions, will be extremely high. Importantly, the large number of meioses will allow extraordinarily high mapping resolution, often at the scale of a single gene or smaller. All 10,000 progeny will be densely genotyped, allowing whole genome sequence data to be accurately imputed. In Aim 2, we will develop new statistical methods for leveraging the inherent power of this experimental cross. More specifically, we will develop new methods for detecting gene-gene interactions and predicting causal variants from heterogeneous sources of data. Finally, in Aim 3 we will use the experimental cross to comprehensively delineate the genetic architecture of a suite of biomedically important phenotypes such as antifungal resistance and biofilm formation. Overall, the mapping population and statistical tools that we develop will enable powerful and comprehensive insights into the genetic architecture of complex and quantitative traits, complement the development of complex crosses in other model organisms, provide new methods for the interpretation of whole-genome sequence data, and yield novel insights into potential therapeutic targets relevant to fungal pathogenesis.