Temporal and spatial effects on expression and function

描述（由申请人提供）：尽管它们在几乎所有的生物过程中都很重要，但空间和时间效应对基因表达、蛋白质丰度和蛋白质修饰的影响在全基因组分析中被大大低估了。该提案旨在开发和实施能够测量和建模时空生物学数据的新实验和计算工具，重点关注模式生物S.cerevisiae中细胞周期与线粒体功能之间的关系。该研究计划的重点是用于突变表型和遗传连锁的大规模测量的实验系统，使用RNA丰度系统的全基因组RNA表达分析，绝对规模的定量，以及基于质谱的亚细胞细胞器中蛋白质和蛋白质修饰状态的鉴定。这些数据的计算分析将包括这些条件下的转录调控网络，酵母代谢模型，以及进化与细胞器功能之间的关系。本研究中开发的所有技术和方法都是全基因组、高通量、高成本效益和易于转移到其他系统的。除了开发急需的技术和计算工具外，该项目还将提供重要的生物学结果，这些结果将进一步加深我们对可能与人类疾病相关的先前表征的基因和途径的理解。

DESCRIPTION (provided by applicant): Despite their importance in nearly all biological processes, the impacts of spatial and temporal effects on gene expression, protein abundance, and protein modification are greatly underrepresented in genome-wide analyses. This proposal is aimed at the development and implementation of new experimental and computational tools capable of measuring and modeling spatial and temporal biological data, focusing on the poorly studied relationship between the cell cycle and mitochondrial function in the model organism, S.cerevisiae. The research plan focuses on experimental systems for the large-scale measurement of mutant phenotype and genetic linkage, whole-genome RNA expression analysis using a system of RNA abundance, quantitation on an absolute scale, and mass spectrometry-based identification of proteins and protein modification states present in subcellular organelles. The computational analysis of this data will include the transcriptional regulatory network under these conditions, a model of yeast metabolism, and the relationship between evolution and organelle function. All of the techniques and methodologies developed in this study are designed to be genome-wide, high-throughput, cost-effective, and readily transferable to other systems. In addition to developing much needed technologies and computational tools, this project will also contribute important biological results that will further our understanding of previously characterized genes and pathways that are likely to be relevant to human disease. The candidate's long-term career goal is the establishment of an academic research laboratory focusing on the analysis of biological problems using a combination of functional genomics and computational modeling of biological processes. The Genome Scholar phase of the award will be used to improve computational skills and to acquire experience in the use of protein mass spectrometry. The Faculty Transition phase of the award will be used to establish a multidisciplinary environment for the conduct of genomics research.