Genetic and Nongenetic Variation in Complex Traits

复杂性状的遗传和非遗传变异

• 批准号: 9923669
• 负责人: Mark L Siegal
• 金额: $ 33.3万
• 依托单位: NEW YORK UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-05-03 至 2022-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9923669
• 关键词: Biological; Biomedical Research; Cells; Complex; Disease; Eukaryota; Experimental Designs; Genetic; Genetic Epistasis; Genetic Variation; Genotype; Goals; Growth; Health; Heterogeneity; Human; Individual; Infection; Knowledge; Lead; Malignant Neoplasms; Maps; Measurement; Methods; Microbe; Microscopy; Modeling; Molecular; Mutation; Nature; Pathway interactions; Pharmaceutical Preparations; Phenotype; Population; Predisposition; Research; Resistance; Saccharomyces cerevisiae; Saccharomycetales; Shapes; Source; Stress; System; Uncertainty; Variant; Work; acute stress; base; disorder risk; microbial; non-genetic; personalized medicine; pressure; programs; public health relevance; single cell analysis; tool; trait; tumor

 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.

 描述（由申请人提供）：该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，目前的重点是抑制或促进变异的机制。对芽殖酵母（酿酒酵母）的单细胞性状进行大规模分析，其中一项工作与其他工作一起表明，神秘的遗传变异一直受到抑制，直到扰动揭示其表型。这一观察结果表明，遗传相互作用（上位性）可能是复杂性状变异的主要决定因素，第二项工作与其他研究一起表明，一些克隆群体会产生异质性，以对冲环境不确定性的赌注。该研究计划将遵循这两条工作线，旨在了解上位性如何促进复杂性状的自然变异，这是生物医学研究的一个主要目标，因为这种知识直接影响到复杂性状的自然变异。前景个性化医疗，例如根据个体基因型预测疾病风险，如果不考虑上位性，上位性也很重要，因为它可以限制进化适应遵循特定的路径，使适应更加可预测。尽管已经使用实验室衍生的突变对上位性进行了深入研究，但它在自然界中尚未得到充分研究，因为大多数实验设计没有足够的能力来治疗具有强大进化成分的疾病，例如微生物感染和癌症。检测相互作用的位点。该研究计划的一个关键目标是对大量独立表型的相互作用进行显着增强的检测能力，以获得对复杂性状差异的根本原因的更丰富的了解。这些研究将利用最近的进展。开发高通量、基于显微镜的方法来量化许多独立的表型，他们将创建和使用酿酒酵母菌株，使寻找上位性变得更加强大。另一组项目旨在了解新发现的分子机制。赌注对冲现象，即酿酒酵母克隆群体包含对急性应激敏感的快速生长的细胞和能够耐受急性应激的缓慢生长的细胞。人们对这种适应性异质性的分子机制知之甚少，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模型真核生物中研究这样的系统的机会可能会导致控制生长和抗逆性异质性的候选途径的研究。此外，还将绘制酿酒酵母菌株之间生长率分布的自然变化图，以努力了解生态压力如何塑造赌注对冲机制。这两条工作线在此交汇，因为上位相互作用似乎主导了差异的遗传基础。增长率方差。