High resolution genetic dissection of complex and quantitative traits in yeast

项目概要/摘要 复杂数量性状的遗传解剖在基础和生物医学领域仍然是一个巨大的挑战。 research.虽然酵母酿酒酵母是一个潜在的强大的模型系统，以解决 关于遗传结构的基本问题，它的承诺还没有完全实现。更具体地说， 需要开发新的工具来揭示遗传结构的基本特征。到 为此，在目标1中，我们将在酵母中开发一个强大的作图群体，用于高分辨率遗传分析。 复杂和数量性状的解剖。具体来说，我们将从一个漏斗杂交中产生10,000个后代， 在八个精心挑选的亲本菌株中， 在S.啤酒。初步分析表明，绘制 弱效应和背景依赖效应，如基因-基因相互作用，将非常高。重要的是， 大量的减数分裂将允许非常高的作图分辨率，通常在单个基因的尺度上 或者更小。所有10，000个后代都将进行密集的基因分型，使全基因组序列数据能够准确地 归咎于在目标2中，我们将开发新的统计方法，以利用这种实验的内在力量。 十字架更具体地说，我们将开发检测基因-基因相互作用和预测因果关系的新方法。 来自异构数据源的变体。最后，在目标3中，我们将使用实验交叉来 全面描绘了一套生物医学重要表型的遗传结构，如 抗真菌抗性和生物膜形成。总体而言，我们开发的人口绘图和统计工具 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了解， 补充了其他模式生物中复杂杂交的发展，提供了新的方法， 全基因组序列数据的解释，并产生新的见解，潜在的治疗靶点相关 真菌的致病机理

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.