Reconstructing the Global Epistasis Network for Aging

项目摘要 自从分子遗传学被引入到生物学领域以来， 领域在过去的几十年里，对模式生物的遗传分析已经导致发现了许多 基因/调节寿命的途径，导致对衰老机制的重要见解。然而 调节寿命的基因网络的全球图景仍然难以捉摸。对长寿突变体进行分类 它们的作用机制，将影响寿命的基因置于通路中，并描绘出 对于长寿突变体的寿命延长的下游效应子，有必要系统地 分析寿命表型基因间的上位关系。到目前为止， 由于需要分析的双突变体的绝对数量和低的 传统寿命测定的通量性质。 在这里，我们建议系统地重建全球上位网络老化使用芽殖酵母作为 模式生物和复制寿命作为表型。我们将开发一种高通量方法， 产生所有可能的单突变体和双突变体，并同时测量它们的寿命（目标1）。我们 这种方法将基于一些新技术：1）一种新的基因工程菌株， 可以基于液体培养中的细胞计数来测量寿命; 2）基于CRISPR/dCas 9的技术， 产生单突变体和双突变体的合并文库，每个突变体携带独特的DNA序列标识符; 3） 高通量测序以同时计数合并的突变体的细胞数。我们将使用 综合寿命数据，通过计算分析重建全局上位性图。我们将 还测试了一些在酵母和蠕虫中发现的上位关系（目的2）。 我们希望这个项目将产生前所未有的关于上位网络的全面数据， 控制着典型模式生物的寿命对这些数据的分析将导致对 衰老背景下基因的功能组织和长寿人群寿命延长的机制 变种人这样的见解可能可以转移到高等真核生物，其中系统地重建了 衰老的上位性网络是不可行的。

Project Summary Research in the biology of aging has seen rapid advance since the introduction of molecular genetics to the field. In the past few decades, genetic analyses of model organisms have led to the discovery of a number of genes/pathways that regulate lifespan, leading to important insight into the mechanisms of aging. However a global picture of the gene network that regulates lifespan is still elusive. To classify longevity mutants based on their mechanisms of action, to place genes influencing lifespan into pathways, and to delineate the downstream effectors of the lifespan extension for the longevity mutants, it is necessary to systematically analyze the epistatic relations between genes for the lifespan phenotype. So far this has not been possible in any model organism due to the sheer number of double mutants that need to be analyzed and the low throughput nature of the traditional lifespan assays. Here we propose to systematically reconstruct the global epistasis network for aging using budding yeast as the model organism and replicative lifespan as the phenotype. We will develop a high throughput approach to generate all possible single and double mutants and measure their lifespan simultaneously (Aim 1). Our approach will be based on a number of new technologies: 1) a novel genetically engineered strain that makes it possible to measure lifespan based on cell counting in liquid culture; 2) CRISPR/dCas9 based technology to generate a pooled library of single and double mutants, each carrying a unique DNA sequence identifier; 3) high throughput sequencing to count the number of cells of the pooled mutants simultaneously. We will use the comprehensive lifespan data to reconstruct the global epistasis map through computational analysis. We will also test some of the discovered epistatic relations both in yeast and in worms (Aim 2). We expect that this project will produce unprecedented and comprehensive data on the epistasis network that controls lifespan in a canonical model organism. The analysis of this data will lead to important insights into the functional organization of genes in the context of aging and mechanisms for the lifespan extension in long-lived mutants. Such insights might be transferrable to higher eukaryotes, in which a systematic reconstruction of the epistasis network for aging is not feasible.