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High-throughput precision genome editing to characterize natural genetic variants

高通量精确基因组编辑来表征自然遗传变异

基本信息

批准号：
10405429
负责人：
Hunter B Fraser
金额：
$ 45.44万
依托单位：
STANFORD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-08-01 至 2023-05-31
项目状态：
已结题

项目摘要

Project summary A major goal of genetics and evolutionary biology is to understand how changes in genotype affect phenotype. Genetic variants affecting fitness are especially informative for investigating evolution, since natural selection acts exclusively on these variants. By identifying specific variants that influence fitness, we can begin to understand the molecular mechanisms driving the incredible adaptations of all organisms to their respective environments. We recently developed an approach that allows us to edit genomes with unprecedented efficiency (~100%) and throughput. In our initial screen, we measured the fitness effects of 16,000 natural genetic variants differing between two strains of Saccharomyces cerevisiae. In this pilot experiment, we measured the effects of each variant in isolation, in a single condition. We found that nearly all strong fitness effects were from promoter variants, rather than protein-coding regions, and these were especially enriched at transcription factor binding sites. Here we propose to utilize this powerful system to investigate two types of interactions of fundamental importance: gene-by-environment (GxE) in Aim 1, and gene-by-gene (GxG, or epistasis) in Aim 2. Understanding the context-dependence of fitness effects will reveal key insights into the evolutionary process that would be unapproachable without our high-throughput precision genome editing technology. !

项目总结遗传学和进化生物学的一个主要目标是了解基因的变化如何影响表型。影响适合度的遗传变异对于研究进化特别有用，因为选择只作用于这些变种。通过识别影响适合度的特定变量，我们可以开始了解推动所有有机体对其各自的环境。我们最近开发了一种方法，使我们能够以前所未有的效率编辑基因组 (~100%)和吞吐量。在我们最初的筛选中，我们测量了16,000种天然基因的健康效果两株酿酒酵母的变异体不同。在这个试点实验中，我们测量了在一个单独的条件下，每个变种的单独影响。我们发现，几乎所有强烈的健身效果都是来自启动子变体，而不是蛋白质编码区，这些区域在转录时尤其丰富因子结合位点。在这里，我们建议利用这个强大的系统来研究两种类型的基本相互作用重要性：在目标1中由环境决定基因(GxE)，在目标2中按基因决定(GXG或上位性)。理解适应度效应的上下文依赖性将揭示进化过程的关键见解如果没有我们的高通量精确基因组编辑技术，这将是无法企及的。好了！