Reconstructing the Global Epistasis Network for Aging

项目摘要 自从将分子遗传学引入人体后，衰老生物学的研究取得了迅速的进展。 菲尔德。在过去的几十年里，对模式生物的遗传分析导致了一些 调节寿命的基因/途径，导致对衰老机制的重要洞察。然而，一个 调节寿命的基因网络的全球图景仍然难以捉摸。根据以下指标对长寿突变体进行分类 它们的作用机制，将影响寿命的基因放入途径中，并描绘 下游效应者的寿命延长对于长寿突变体来说，有必要系统地 分析寿命表型基因间的上位性关系。到目前为止，这是不可能的 任何模式生物，因为需要分析的双突变体数量很多，而且 传统寿命分析的吞吐量性质。 在这里，我们建议系统地重建全球上位性衰老网络，使用萌芽酵母作为 以模式生物和复制寿命为表型。我们将开发一种高吞吐量方法来 产生所有可能的单突变和双突变，并同时测量它们的寿命(目标1)。我们的 这一方法将基于许多新技术：1)一种新的基因工程菌株，它可以产生 可以基于液体培养中的细胞计数来测量寿命；2)基于CRISPR/dCas9的技术 生成单个和双突变体库，每个库携带唯一的DNA序列识别符；3) 高通量测序，以同时计数池中突变的细胞数量。我们将使用 综合寿命数据，通过计算分析重建全球上位图。我们会 也测试在酵母和蠕虫中发现的一些上位关系(目标2)。 我们预计，该项目将产生史无前例的、全面的上位网络数据， 控制规范模型生物体中的寿命。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。这种洞察力可能可以转移到高等真核生物中，在这种情况下，系统地重建 上位式老龄化网络是不可行的。

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.