High resolution genetic dissection of complex and quantitative traits in yeast

酵母复杂和数量性状的高分辨率遗传解析

• 批准号: 9005198
• 负责人: Joshua Michael Akey
• 金额: $ 54.08万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-01 至 2017-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9005198
• 关键词: Address; Alleles; Animal Model; Antifungal Agents; Architecture; Basic Science; Bioinformatics; Biological Models; Biomedical Research; Characteristics; Chromosome Mapping; Communities; Complement; Complex; Computing Methodologies; Data; Data Set; Data Sources; Development; Disease; Dissection; Fungal Drug Resistance; Genes; Genetic; Genetic Determinism; Genetic Variation; Genomic Segment; Genomics; Genotype; Goals; Haplotypes; Human; Learning; Maps; Meiosis; Methods; Microbial Biofilms; Mus; Nucleotides; Organism; Pathogenesis; Phenotype; Plants; Population; Population Genetics; Prevalence; Resistance; Resolution; Resources; Saccharomyces; Saccharomyces cerevisiae; Saccharomycetales; Statistical Methods; Variant; Yeasts; base; design; fly; gene environment interaction; gene interaction; genome sequencing; insight; interest; novel; offspring; pre-clinical; public health relevance; rare variant; response; therapeutic target; tool; trait; whole genome

 DESCRIPTION (provided by applicant): 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. In particular, 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. In particular, 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.

 描述（由申请人提供）： 复杂和数量性状的遗传解析仍然是基础和生物医学研究中的巨大挑战。尽管酿酒酵母是解决遗传结构基本问题的潜在强大模型系统，但其前景尚未完全实现。特别是，需要开发新的工具来揭示对遗传结构基本特征的见解。为此，在目标 1 中，我们将开发强大的酵母图谱群体，用于复杂和数量性状的高分辨率遗传解析。具体来说，我们将通过八个智能选择的亲本菌株之间的漏斗杂交产生 10,000 个后代，这些亲本菌株捕获了酿酒酵母天然分离株中分离的大部分遗传变异。初步分析表明，绘制弱效应和背景相关效应（例如基因间相互作用）变体的能力将非常高。重要的是，大量的减数分裂将允许极高的作图分辨率，通常在单个基因或更小的规模上。所有 10,000 个后代都将进行密集基因分型，从而可以准确估算全基因组序列数据。在目标 2 中，我们将开发新的统计方法来利用这种实验杂交的内在力量。特别是，我们将开发新方法来检测基因间相互作用并从异质数据源预测因果变异。最后，在目标 3 中，我们将利用实验杂交来全面描述一系列生物医学上重要的表型（例如抗真菌耐药性和生物膜形成）的遗传结构。总体而言，我们开发的群体图谱和统计工具将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，补充其他模式生物中复杂杂交的发展，为解释全基因组序列数据提供新方法，并对与真菌发病机制相关的潜在治疗靶点产生新的见解。