BIOINFORMATICS OF A GENE INTERACTION MAP

基因相互作用图谱的生物信息学

• 批准号: 6693150
• 负责人: DANIEL SHIH-EN YUAN
• 金额: $ 7.44万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-01-01 至 2005-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6693150
• 关键词: biotechnology; functional /structural genomics; fungal genetics; gene interaction; genetic mapping; informatics; lethal genes; microarray technology; molecular biology information system; phenotype; postdoctoral investigator; technology /technique development; yeasts

DESCRIPTION (provided by applicant): Gene function is often obscured or modified by other genes. The most dramatic examples of such "gene interactions" are those that result in cell death ("synthetic lethality"), since these often signal the existence of parallel or redundant pathways in the architecture of a vital physiological system. Our goal is to construct a comprehensive map of synthetic lethal gene interactions in yeast, the organism for which genetic screens for synthetic lethality are most highly developed. Populations of cells carrying defined deletion mutations are being systematically mutated at a second defined locus, and the viability of the resulting double mutants is being assessed in parallel using microarrays. This proposal describes (1) the testing of a novel microarray design for sharpening the precision of our experimental results, and (2) the development of an object database for facilitating access to our functional genomic data across multiple levels of abstraction. The classification of gene interactions that will eventually emerge from this project is fundamental to the study of all polygenic traits and will provide an improved basis for characterizing the roles of common genetic variants in human disease.

描述（由申请人提供）：基因功能经常被其他基因掩盖或修饰。这种“基因相互作用”最引人注目的例子是那些导致细胞死亡的例子（“合成致死”），因为这些通常表明在重要生理系统的结构中存在平行或冗余的途径。我们的目标是构建酵母中合成致死基因相互作用的综合图谱，酵母是合成致死基因筛选最发达的生物体。携带确定缺失突变的细胞群在第二个确定的位点被系统地突变，并且由此产生的双突变体的生存能力正在使用微阵列并行评估。本提案描述了(1)测试一种新型微阵列设计，以提高实验结果的精度，以及(2)开发一个对象数据库，以促进跨多个抽象层次访问我们的功能基因组数据。该项目最终产生的基因相互作用分类是研究所有多基因特征的基础，并将为描述常见遗传变异在人类疾病中的作用提供改进的基础。