Mapping the reference genetic network of a eukaryotic cell

绘制真核细胞的参考遗传网络

• 批准号: 8147861
• 负责人: Brenda Jean ANDREWS
• 金额: $ 66.5万
• 依托单位: UNIVERSITY OF TORONTO
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-26 至 2013-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8147861
• 关键词: Address; Amaze; Animal Model; Atlases; Cataloging; Catalogs; Cell Cycle; Cell physiology; Cells; Communities; Complex; Data; Data Set; Databases; Development; Disease; Distant; Drug Delivery Systems; Eukaryota; Eukaryotic Cell; Evolution; Fission Yeast; Foundations; Future; Genes; Genetic; Genetic Variation; Genome; Genomics; Genotype; Goals; Grouping; Health; Human; Link; Mammalian Cell; Mammalian Genetics; Maps; Methods; Modeling; Nobel Prize; Organism; Pathway interactions; Phenotype; Research; Resources; Saccharomyces cerevisiae; Saccharomycetales; Sequence Analysis; Surveys; Testing; To specify; Work; Yeasts; base; bioprocess; comparative; computerized tools; functional genomics; gene function; genetic analysis; genome sequencing; human disease; insight; man; meetings; mutant; programs; public health relevance; tool; web-accessible; yeast genetics

DESCRIPTION (provided by applicant): The importance of genetic interactions in disease has been emphasized by genome sequencing projects which have revealed the astounding genetic diversity in a variety of organisms, from yeast to man. We are now faced with the significant challenge of assigning functions to the thousands of uncharacterized genes, and how to use this information to understand how genes interact to determine cell function in health and disease. Despite amazing technical advances, our understanding of genetic interactions relevant to human disease remains rudimentary, and discovering relevant interactions demands an integrated, systematic approach. The proposed work aims to address this challenge by identifying genetic interactions in a model eukaryote, the budding yeast, Saccharomyces cerevisiae. We developed the Synthetic Genetic Array (SGA) method which automates yeast genetics and enables systematic analysis of genetic interactions. 'The emerging principles of genetic networks suggest that systematic identification of genetic interactions offers the potential to organize genomes into hierarchical maps, grouping genes into coherent pathways. This project will complete a reference genetic interaction map for the eukaryotic cell and will explore the conservation of genetic networks over millions of years of evolution. A complete atlas of genetic interactions will reveal how genes act in concert to specify the cellular programs that control development, differentiation, and disease states. AIM 1: Mapping the reference genetic interaction network. The SGA approach will be used to complete the genetic interaction network map for the budding yeast, a fundamental eukaryotic cell that shares thousands of genes and the basic cellular functions of its human counterparts. The complete genetic interaction "altas" in yeast will guide development of the first mammalian genetic interaction maps. AIM 2: Surveying genetic interactions in fission yeast. Fission yeast is a model organism that is separated from budding yeast by hundreds of millions of years of evolution. Comparison of genetic interactions between these two unicellular organisms will provide a foundation for understanding genetic networks in human cells. AIM 3: Database and Computational Tools for Cross-Species Analysis of Genetic Interactions. We will develop a web-accessible data warehouse for storage and cross-species analysis of genetic interaction networks. A cross-species database will enable analysis of the general rules governing conservation or rewiring of interactions and prediction of conserved interactions. PUBLIC HEALTH RELEVANCE: This project will produce unique datasets and tools that will reveal how genes interact in normal and diseased cells. Genetic interaction reference maps produced by the project will provide valuable insights into gene function, drug target analysis and the link between genotype and phenotype, including the genetic basis of human disease.

描述（由申请人提供）：基因组测序项目揭示了从酵母菌到人类的各种生物体中惊人的遗传多样性，强调了疾病中基因相互作用的重要性。我们现在面临的重大挑战是为数千个未表征的基因分配功能，以及如何利用这些信息来了解基因如何相互作用以确定健康和疾病中的细胞功能。尽管技术取得了惊人的进步，但我们对与人类疾病相关的基因相互作用的理解仍然很初级，发现相关的相互作用需要一种综合的、系统的方法。提出的工作旨在通过识别一种模式真核生物，出芽酵母，酿酒酵母的遗传相互作用来解决这一挑战。我们开发了合成遗传阵列（SGA）方法，使酵母遗传自动化，使遗传相互作用的系统分析成为可能。“基因网络的新兴原理表明，对基因相互作用的系统识别提供了将基因组组织成分层图、将基因分组成连贯通路的潜力。”该项目将完成真核细胞的参考遗传相互作用图，并将探索遗传网络在数百万年进化中的保护。一个完整的基因相互作用图谱将揭示基因如何协同作用，以指定控制发育、分化和疾病状态的细胞程序。目标1：绘制参考遗传相互作用网络。SGA方法将用于完成芽殖酵母的遗传相互作用网络图谱，芽殖酵母是一种基本的真核细胞，与人类细胞具有数千种基因和基本的细胞功能。酵母中完整的遗传相互作用“altas”将指导第一个哺乳动物遗传相互作用图谱的开发。目的2：研究裂变酵母的遗传相互作用。裂变酵母是一种模式生物，经过数亿年的进化，它与出芽酵母分离开来。比较这两种单细胞生物之间的遗传相互作用将为理解人类细胞中的遗传网络提供基础。目标3：跨物种遗传相互作用分析的数据库和计算工具。我们将开发一个可访问网络的数据仓库，用于存储和跨物种遗传相互作用网络的分析。跨物种数据库将能够分析控制相互作用的保护或重新布线的一般规则，并预测保守的相互作用。