Genetic and Nongenetic Variation in Complex Traits

 描述(申请人提供)：本研究计划的长期目标是了解复杂性状变异的机制和进化原因。目前的焦点是抑制或促进变异的机制。主要的实验方法是对萌芽酵母--酿酒酵母--的单细胞特性进行大规模分析。一项工作与其他工作一起表明，隐秘的遗传变异是普遍存在的，这种变异一直被抑制，直到一种扰动揭示其表型效应。这一观察表明，遗传交互作用(上位性)可能是复杂性状变异的主要决定因素。第二项工作加入了其他工作的行列，提出一些克隆种群产生异质性，以对冲它们对环境不确定性的押注。研究计划将遵循这两条工作路线。其中一组项目旨在了解上位性如何影响复杂性状的自然变异。了解复杂性状变异的来源是生物医学研究的一个主要目标，因为这一知识直接影响到个性化医学的前景，例如从个人的基因型别预测疾病风险。如果不考虑上位性，上位性可能会混淆这样的预测。上位性也很重要，因为它可以约束进化适应遵循特定的路径，使适应更具可预测性。这种可预测性在微生物感染和癌症等具有强烈进化成分的疾病的治疗中可能是有价值的。虽然上位性利用实验室衍生的突变得到了很好的研究，但在自然界中还没有得到很好的研究，因为大多数实验设计没有足够的能力来检测相互作用的基因座。这项研究计划的一个关键目标是以显著提高的能力进行研究，以检测大量独立表型的相互作用，以获得对复杂性状差异的根本原因的更丰富的看法。这些研究将利用高通量、基于显微镜的方法来量化许多独立表型的最新进展，并将创造和使用使上位性搜索更加强大的酿酒酵母菌株。另一组项目旨在了解新发现的一种更好的对冲现象背后的分子机制，即酿酒酵母的克隆群体包含对急性压力敏感的快速生长细胞和耐受急性压力的缓慢生长细胞。这种适应性异质性的分子机制还知之甚少，特别是在真核生物中，因此利用强大的遗传、分子和细胞生物学工具在真核生物模型中研究这种系统可能会带来重大进展。将研究控制生长和抗逆性异质性的候选途径。此外，还将绘制酿酒酵母菌株之间生长速度分布的自然变异图，以努力了解生态压力如何形成更好的对冲机制。这两条工作在这里汇聚在一起，因为上位性交互似乎主导了增长速度差异的遗传基础。

 DESCRIPTION (provided by applicant): The long-term goal of this research program is to understand the mechanistic and evolutionary causes of variation in complex traits. The current focus is on mechanisms that appear to either suppress or promote variation. The primary experimental approach is to perform large-scale analyses of single-cell traits of the budding yeast, Saccharomyces cerevisiae. One line of work joins others in showing that cryptic genetic variation, kept suppressed until a perturbation reveals its phenotypic effects, is pervasive. This observation suggests that genetic interactions (epistasis) might be a major determinant of complex-trait variation. A second line of work joins others in suggesting that some clonal populations generate heterogeneity in order to hedge their bets against environmental uncertainty. The research program will follow these two lines of work. One set of projects aims to understand how epistasis contributes to natural variation in complex traits. Understanding the sources of variation in complex traits is a major goal in biomedical research because this knowledge impinges directly on the prospect of personalized medicine, for example the prediction of disease risk from an individual's genotype. If not taken into account, epistasis can confound such predictions. Epistasis is also important because it can constrain evolutionary adaptation to follow particular paths, making adaptation more predictable. This predictability could be valuable in the treatment of diseases that have a strong evolutionary component, such as microbial infections and cancer. Although epistasis has been well studied using lab- derived mutations, it has not been well studied in nature because most experimental designs have insufficient power to detect interacting loci. A key aim of this research program is to perform studies with dramatically increased power to detect interactions, for a large number of independent phenotypes, to gain a far richer view of the underlying causes of differences in complex traits. These studies will leverage recent progress in developing high-throughput, microscopy-based methods of quantifying many independent phenotypes, and they will create and use strains of S. cerevisiae that make searching for epistasis much more powerful. The other set of projects aims to understand the molecular mechanisms underlying a newly discovered bet-hedging phenomenon whereby clonal populations of S. cerevisiae contain fast-growing cells that are sensitive to acute stress and slow-growing cells that are tolerant of acute stress. Molecular mechanisms of this kind of adaptive heterogeneity are poorly understood, especially in eukaryotes, so the opportunity to study such a system in a model eukaryote with powerful genetic, molecular and cell-biological tools could lead to major advances. A candidate pathway for controlling the heterogeneity in growth and stress resistance will be studied. In addition, natural variation in growth-rate distributions between S. cerevisiae strains will be mapped, in an effort to understand how ecological pressures shape bet-hedging mechanisms. The two lines of work converge here because epistatic interactions appear to dominate the genetic basis of differences in growth-rate variance.