Comparative Analysis of Genetic and Physical Interaction Networks in Yeasts

酵母遗传和物理相互作用网络的比较分析

• 批准号: 7652501
• 负责人: Trey Ideker
• 金额: $ 49.39万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-08-01 至 2012-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7652501
• 关键词: Address; Affinity Chromatography; Amino Acid Sequence; Animal Model; Architecture; Area; Binding; Bioinformatics; Biological Assay; Biology; California; Cell physiology; Commit; Communities; Companions; Complex; Computer software; DNA Binding; DNA Microarray Chip; DNA-Protein Interaction; Data; Eukaryota; Event; Evolution; Exons; Fission Yeast; Follow-Up Studies; Funding; Gene Deletion; Generations; Genes; Genetic; Genetic Databases; Genetic Screening; Genome; Genomics; Goals; Grant; Housing; In Vitro; Institutes; Introns; Laboratories; Libraries; Mammals; Maps; Measures; Methodology; Methods; Mitogen-Activated Protein Kinases; Modeling; Mutation; Neighborhoods; Pathway interactions; Peptide Sequence Determination; Phenotype; Phosphorylation; Phosphotransferases; Physiology; Principal Investigator; Protein Databases; Proteins; Quantitative Genetics; RNA Interference; RNA Splicing; Relative (related person); Research; Resources; Role; Saccharomyces cerevisiae; Saccharomycetales; San Francisco; Set protein; Signal Pathway; Technology; Time; Translating; Universities; Ursidae Family; Validation; Variant; Work; Yeasts; base; chromatin immunoprecipitation; comparative; data integration; density; genetic analysis; genome-wide; human EML2 protein; insight; knockout gene; mutant; promoter; protein complex; protein protein interaction; scaffold; tandem mass spectrometry; tool; transcription factor

DESCRIPTION (provided by applicant): Comparative interaction mapping resolves protein complexes and signaling pathways on the basis of their conservation across different species or types of interaction network. It is an emerging methodology which, like comparative genomics, provides a powerful tool for understanding cellular function. Network comparison has been used to identify the functional roles of many proteins, and it offers insight into how mutations in the genome contribute to the evolution of new functions and phenotypes. A current hurdle towards these goals is the lack of high-coverage interaction maps at the appropriate evolutionary distances to enable network comparison. To address this shortcoming, the major goal of this project is to obtain matching sets of highdensity physical and genetic interaction maps across the model organisms Schizosaccharomyces pombe and Saccharomyces cerevisiae. Use of these data will ultimately help resolve the following questions: How closely do the architectures of the physical, genetic, and transcriptional interaction networks reflect variation in the underlying genomic sequence?; What relative contributions do changes in the physical interactome, genetic pathways, transcriptional networks, and mutations at the protein sequence level make to the evolution of new cellular functions? Specific hypotheses directly related to the physiologies of S. pombe and S. cerevisiae can also be addressed. Many aspects of S. pombe physiology bear more in common with mammals than does S. cerevisiae, including intron/exon splicing, chromosomal architecture, and RNA interference machinery. In fact, the last common ancestor of S. pombe and S. cerevisiae is quite ancient (420 mya), making the conserved interaction map generalizable to large parts of the eukaryotic lineage. To focus our initial interaction mapping efforts on the regulatory machinery most likely to form the basis for the similarities and differences between S. pombe and S. cerevisiae physiology, we will screen interactions among a targeted set of ~400 kinases and transcriptional regulators. This set will limit our scope sufficiently such that high coverage maps can be obtained at reasonable funding levels within a five-year time frame. Pair-wise genetic interactions will be measured using epistatic phenotyping, protein-protein interactions using affinity purification followed by tandem mass spectrometry, and transcription factor / promoter binding interactions using genome-wide chromatin immunoprecipitation assays. In parallel, we will develop a companion suite of bioinformatic methods to perform integrative and comparative analysis of the yeast interaction networks. Bioinformatic research will address: [1] Models of interplay between quantitative genetic and physical interactions; [2] Alignment of the integrated networks across species; and [3] Prediction and transfer of interactions within and across species, at varying degrees of data integration. Assembling the network of transcriptional regulators and kinases will serve as a pilot for establishing basic principles of network integration and comparison prior to embarking on larger-scale efforts to comprehensively map fission yeast as well as higher eukaryotes. It will involve close coordination among the two principal investigators Krogan and Ideker. It will join two University of California campuses as well as two California institutes, Cal-IT2 and QB3, which are committing space to house the proposed project in the San Diego and San Francisco areas.

描述（由申请人提供）：基于蛋白质复合物和信号通路在不同物种或相互作用网络类型中的保护，比较相互作用制图解决了蛋白质复合物和信号通路。这是一种新兴的方法，像比较基因组学一样，为理解细胞功能提供了强有力的工具。网络比较已被用于识别许多蛋白质的功能作用，它提供了对基因组突变如何促进新功能和表型进化的见解。目前实现这些目标的一个障碍是，在适当的进化距离上缺乏高覆盖率的交互图，无法进行网络比较。