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全面剖析酵母中许多复杂表型的遗传基础，酿酒酵母是最强大的真核模型系统，因为它的基因组很小，易于遗传操作，并且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遗传结构的基本问题，包括性状潜在的基因座数量、等位基因效应大小的分布、遗传互作的流行程度以及等位基因频率在群体中的分布。成功地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-表型研究的设计提供重要的指导。我们的建议侧重于与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。具体地说，将为经过充分研究的BYxRM杂交组合生成一个由4000个单独分离物组成的图谱小组，以及为其他20个杂交组合生成由1000个分离物组成的小组，这些小组采用改进的循环法设计，其中20个菌株中的每一个都将与另外两个菌株杂交。我们将通过高度多元化、低覆盖率的全基因组测序对这些面板进行基因分型。然后，我们将使用集落生长试验对面板进行表型分析，探索广泛的细胞生理学空间。我们已经开发了高通量的自动化表型分析，这将使我们能够测量在拟议的项目期内数百种条件下数万种菌株的生长。我们建议测试的生长条件包括抗真菌药物、化疗药物、营养耗竭、针对特定细胞过程的小分子，以及已被证明是与疾病相关的人类表型的酵母“物候素”的治疗。我们将利用这些数据来估计每个性状的广义遗传力和狭义遗传力，进行连锁分析以检测具有加性和上位性效应的基因座，测量效应大小的分布，并计算被检测基因座解释的遗传力百分比。我们将尝试识别候选基因和检测到的基因座下的变异，并用等位基因替换等分子遗传学技术验证其中的子集。我们将选择10个高度可遗传的“缺失遗传力”性状，并使用X-QTL来检测影响比其他方法更小的基因座，并提高已识别基因座的作图分辨率。我们将检验X-QTL检测到的新基因座的加性效应和互作效应大小，建立多个QTL模型，并评估效应很小的基因座可以解释的遗传力的比例 为表型变异的0.1%。我们确定的数量性状基因和核苷酸也将在一大批不同的酵母菌株中重新测序，以确定常见和罕见多态对酵母复杂性状变异的相对贡献，以及检验这些基因功能变异的等位基因复杂性。我们的研究将提供对许多复杂性状的遗传结构的广泛看法，并对某些性状的子集有非常深刻的理解。

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.