Characterizing the complex underpinnings of genetic background effects

项目摘要 这项研究计划的长期目标是确定基因和分子 导致自发突变和诱发突变的机制在 基因上截然不同的个体。这些“背景效应”对人类健康很重要。 因为它们会使预测、预防和治疗疾病的努力复杂化 个性化的基因组数据。尽管已知背景效应是由遗传因素引起的 突变和标准多态之间的相互作用及其潜在的遗传 对其结构和分子机制的研究才刚刚开始。我们最近的工作 表明背景效应通常是由多个基因座引起的，这些基因座 不仅与突变相互作用，而且彼此之间也相互作用。这一发现可能具有重要的 对绘制疾病和其他常见特征的遗传基础图的影响 受突变的影响，因此其普遍性和潜在的机制需要更深层次的 调查。在这里，我们将扩展我们在酵母中使用Emerging的背景效应的工作 高通量表型和基因组编辑技术，以及统计 强大的连锁图谱。我们的工作将解决三个主要问题：(1)什么是 背景效应的流行和形式？(2)什么遗传复杂性和类型 上位性是背景效果的基础？以及，(3)基因和基因的特性是什么 会产生背景效果的变种？这项工作将产生对 背景效应应促进理解和预测关系的努力 在人类和模式生物中的基因和表型之间的差异。

Project Summary The long-term goal of this research program is to determine the genetic and molecular mechanisms that cause spontaneous and induced mutations to show different effects across genetically distinct individuals. These `background effects' are important to human health because they can complicate efforts to predict, prevent, and treat disease based on personalized genomic data. Although background effects are known to result from genetic interactions between mutations and standing polymorphisms, their underlying genetic architectures and molecular mechanisms have only begun to be characterized. Our recent work in budding yeast suggests that background effects are typically caused by multiple loci that interact not only with a mutation, but also each other. This finding could have important implications for efforts to map the genetic basis of diseases and other traits that are commonly influenced by mutations, and thus its generality and underlying mechanisms require deeper investigation. Here, we will extend our work on background effects in yeast using emerging technologies for high-throughput phenotyping and genome editing, as well as statistically powerful linkage mapping. Our work will address three main questions: (1) What are the prevalence and forms of background effects? (2) What genetic complexities and types of epistasis underlie background effects? And, (3) what are the properties of genes and genetic variants that cause background effects? This work will produce detailed insights into background effects that should advance efforts to understand and predict the relationship between genotype and phenotype in humans and model organisms.