Research Initiation Grant: The Effects of Genetic Variation on Gene Networks in Yeast

研究启动资助：遗传变异对酵母基因网络的影响

• 批准号: 0614959
• 负责人: Paul Magwene
• 金额: $ 17.49万
• 依托单位: Duke University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-10-01 至 2009-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0614959&HistoricalAwards=false
• 关键词: Research; Initiation; Grant; Effects; Genetic

This research explores the relationship between genotype and phenotype in the context of genetic networks. The investigator will use a combination of experimental and mathematical approaches to characterize the effects of genetic variation on the regulatory pathways that determine responses to nitrogen starvation in Saccharomyces cerevisiae (budding yeast). Yeast cells that are starved for nitrogen can undergo one of two mutually exclusive developmental processes - sporulation or pseudohyphal growth. The regulatory and signaling pathways that underlie these two responses are intertwined. This study will characterize the impact of genetic variation on these overlapping genetic pathways and explore how genetic polymorphism contributes to variable patterns of gene expression and ultimately to distinct sporulation and pseudohyphal growth phenotypes. The investigator will employ gene disruptions and phenotypic assays to validate a set of potential mutational targets that affect both phenotypes of interest. This set of validated gene targets will form a 'candidate network' for further study. DNA sequencing will be carried out to identify polymorphisms in the protein coding and regulatory sequences for genes in this candidate network. The functional consequences of these polymorphisms will be assessed using RT-PCR based assays to determine if the genetic differences identified confer allelic biases in gene expression. These data will be combined with biochemical, genetic, and genomic information from previous studies to build a mathematical model of the regulatory networks that will be used to explore mechanistic hypotheses relating gene expression variation to cellular phenotypes. This research will provide significant advances towards our understanding of the genetic basis of variation for complex traits by providing a detailed picture of genetic variation across a large genetic network. The experiments and modeling efforts to be carried out will provide insights into the functional consequences of this variation with respect to regulatory network function. Furthermore, this project will lead to the development of a novel experimental system for exploring important genetic phenomena such as pleiotropy and epistasis. A key issue in biology is to understand how variation at the level of DNA relates to phenotypic variation (e.g. physiology, morphology, behavior). A thorough understanding of such relationships requires the study of mutational effects on single genes as well as investigations focused on networks of interacting genes and gene products. The research to be conducted under the auspices of this grant will contribute to a greater understanding of how genetic variation impacts gene networks and how the behavior of such networks leads to distinct cellular phenotypes. Using a combination of experimental and mathematical approaches the investigator will study the affects of genetic variation on signaling pathways and gene networks that determine how budding yeast (Saccharomyces cerevisiae) respond to a simple environmental cue (nitrogen starvation). Yeast is one of the best studied eukaryotic model systems as well as an important agricultural and industrial microorganism. A deeper understanding of genotype-phenotype relationships will advance yeast genetics and will help to pave the way for similar studies in agriculturally important animals and plants. The broader societal impacts of this research are to promote training and mentoring at the postdoctoral and undergraduate levels and to foster the development of scientists from underrepresented groups. The principal investigator is a member of a group under-represented in science.

本研究在遗传网络的背景下探讨了基因型和表型之间的关系。研究人员将使用实验和数学方法的组合来表征遗传变异对调控途径的影响，这些调控途径决定酿酒酵母（芽殖酵母）对氮饥饿的反应。缺乏氮的酵母细胞可以经历两个相互排斥的发育过程之一-孢子形成或假菌丝生长。这两种反应背后的调节和信号通路是相互交织的。本研究将描述遗传变异对这些重叠遗传途径的影响，并探讨遗传多态性如何有助于基因表达的可变模式，并最终导致不同的孢子形成和假菌丝生长表型。 研究者将采用基因破坏和表型测定来验证一组影响两种感兴趣表型的潜在突变靶点。这组经过验证的基因靶点将形成一个“候选网络”，供进一步研究。 将进行DNA测序，以确定该候选网络中基因的蛋白质编码和调控序列的多态性。将使用基于RT-PCR的测定法评估这些多态性的功能后果，以确定所鉴定的遗传差异是否赋予基因表达中的等位基因偏倚。 这些数据将与以前研究的生化，遗传和基因组信息相结合，以建立一个调控网络的数学模型，该模型将用于探索基因表达变异与细胞表型相关的机制假说。 这项研究将通过提供一个大型遗传网络中遗传变异的详细情况，为我们理解复杂性状变异的遗传基础提供重大进展。要进行的实验和建模工作将提供洞察这种变化的功能后果相对于监管网络功能。 此外，该项目将导致开发一种新的实验系统，用于探索重要的遗传现象，如多效性和上位性。 生物学中的一个关键问题是了解DNA水平的变异如何与表型变异（例如生理学，形态学，行为）相关。 要彻底了解这种关系，需要研究突变对单个基因的影响，以及研究相互作用的基因和基因产物的网络。 这项研究将有助于更好地了解遗传变异如何影响基因网络，以及这些网络的行为如何导致不同的细胞表型。使用实验和数学方法的结合，研究人员将研究遗传变异对信号通路和基因网络的影响，这些信号通路和基因网络决定了芽殖酵母（酿酒酵母）如何响应简单的环境提示（氮饥饿）。 酵母是研究最多的真核生物模式系统之一，也是重要的农业和工业微生物。 对基因型-表型关系的深入理解将促进酵母遗传学的发展，并有助于为农业上重要的动物和植物的类似研究铺平道路。这项研究的更广泛的社会影响是促进博士后和本科层次的培训和指导，并促进来自代表性不足群体的科学家的发展。首席研究员是一个在科学界代表性不足的群体的成员。