Toward comprehensive genetic dissection of complex traits in yeast

描述（由申请人提供）： 项目概述拟议研究的广泛目标是实现酵母S.酿酒酵母，可以说是最强大的真核生物模型系统，由于其小的基因组，易于遗传操作，并能够产生非常大的样本量。进化保守也确保了许多酵母性状与生物医学上重要的人类表型有直接的相似之处。我们试图回答许多关于复杂性状的遗传结构的基本问题，包括性状基础的基因座数量，等位基因效应大小的分布，遗传相互作用的普遍性，以及群体中等位基因频率的分布。成功回答这些问题将为人类和其他具有医学、生物学和农业意义的生物体的基因型-表型研究的设计提供重要指导。我们的建议侧重于生物医学相关的特征，因此将使我们能够利用酵母遗传学的力量来更好地了解人类生物学和疾病。具体而言，将为充分研究的BYxRM杂交产生4000个单独分离子的作图组，以及为其他20个杂交产生1000个分离子的作图组，所述其他20个杂交使用改良的循环设计选择，其中20个菌株中的每一个将与两个其他菌株杂交。我们将通过高度多重低覆盖全基因组测序对这些样本组进行基因分型。然后，我们将使用集落生长测定法对面板进行表型分析，以探索细胞生理学的广泛空间。我们开发了高通量自动化表型分析，使我们能够在拟议的项目期间在数百种条件下测量数万种菌株的生长。我们建议测试的生长条件包括抗真菌剂，化疗药物，营养消耗，靶向特定细胞过程的小分子，以及已被证明是疾病相关人类表型的酵母“phenologs”的治疗。我们将使用这些数据来估计每个性状的广义和狭义遗传力，进行连锁分析以检测具有加性和上位性效应的位点，测量效应大小的分布，并计算由检测到的位点解释的遗传力的分数。我们将尝试确定候选基因和变异的潜在检测位点，并验证这些与分子遗传学技术，如等位基因置换的子集。我们将选择10个高度可遗传的性状与实质性的“缺失遗传力”，并使用X-QTL检测基因座与其他方法相比，可能具有较小的影响，并提高已确定的基因座的定位分辨率。我们将检验X-QTL检测到的新位点的加性效应和互作效应大小，建立多QTL模型，并评估可由效应较小的位点解释的遗传力比例。 表型变异的0.1%。我们确定的数量性状基因和核苷酸也将在大量不同的酵母菌株中进行重新测序，以确定常见和罕见多态性对酵母中复杂性状变异的相对贡献，以及研究这些基因中功能变异的等位基因复杂性。我们的研究将为许多复杂性状的遗传结构提供广泛的视角，并对性状的子集有非常深入的了解。

DESCRIPTION (provided by applicant): PROJECT SUMMARY The broad objective of the proposed research is to achieve comprehensive dissection of the genetic basis of many complex phenotypes in the yeast S. cerevisiae, arguably the most powerful eukaryotic model system due to its small genome, ease of genetic manipulation, and the ability to generate very large sample sizes. Evolutionary conservation has also ensured that many yeast traits have direct parallels to biomedically important human phenotypes. We seek to answer many of the basic questions about the genetic architecture of complex traits, including the number of loci underlying a trait, the distribution of allelic effect sizes, the prevalence of genetic interactions, and the distribution f allele frequencies in a population. Success in answering these questions will provide critical guidance for the design of genotype-phenotype studies in humans and other organisms of medical, biological, and agricultural interest. Our proposal focuses on biomedically relevant traits, and will therefore allow us to leverage the power of yeast genetics to better understand human biology and disease. Specifically, will generate a mapping panel of 4000 individual segregants for the well-studied BYxRM cross, as well as panels of 1000 segregants for 20 other crosses, chosen with a modified round-robin design in which each of 20 strains will be crossed to two other strains. We will genotype these panels by very highly multiplexed low-coverage whole-genome sequencing. We will then phenotype the panels using colony growth assays probing an extensive space of cell physiology. We have developed high-throughput automated phenotyping assays that will enable us to measure growth of tens of thousands of strains in hundreds of conditions over the proposed project period. The growth conditions we propose to test include antifungals, chemotherapeutics, nutrient depletion, small molecules that target specific cellular processes, and treatments that have been shown to be yeast "phenologs" of disease-related human phenotypes. We will use these data to estimate broad-sense and narrow-sense heritability of each trait, carry out linkage analysis to detect loci with additive an epistatic effects, measure the distribution of effect sizes, and compute the fraction of heritabiliy explained by the detected loci. We will attempt to identify candidate genes and variants underlying the detected loci, and validate a subset of these with molecular genetics techniques such as allele replacements. We will select 10 highly heritable traits with substantial "missing heritability", and use X-QTL to detect loci with smaller effects than possible with other approaches, and to improve the mapping resolution of already identified loci. We will examine the additive and interaction effect sizes of the new loci detected by X-QTL, build multiple-QTL models, and assess the fraction of heritability that can be explained by loci with effects as small as 0.1% of phenotypic variance. Quantitative trait genes and nucleotides we identify will also be resequenced across a large panel of diverse yeast strains in order to determine the relative contributions of common and rare polymorphisms to complex trait variation in yeast, as well as to examine the allelic complexity of functional variation in these genes. Our studies will provide a broad view of genetic architectures of many complex traits and a very deep understanding of a subset of traits.