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

这项研究在遗传网络的背景下探索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相结合的方法来表征遗传变异对调控途径的影响，这些调控途径决定了酿酒酵母(芽殖酵母)对氮饥饿的反应。缺氮的酵母细胞可以经历两个相互排斥的发育过程之一--产孢子或假菌丝生长。这两种反应背后的调控和信号通路是相互交织的。这项研究将描述遗传变异对这些重叠遗传途径的影响，并探索遗传多态如何影响基因表达的不同模式，最终导致不同的产孢量和假菌丝生长表型。研究人员将使用基因中断和表型分析来验证一组影响两种感兴趣表型的潜在突变靶点。这组有效的基因靶点将形成进一步研究的“候选网络”。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。这些多态的功能后果将通过基于RT-PCR的分析来评估，以确定所识别的遗传差异是否会导致基因表达中的等位基因偏向。这些数据将与以前研究中的生化、遗传和基因组信息相结合，建立调控网络的数学模型，用于探索基因表达变化与细胞表型之间的机械假说。这项研究将通过提供一个大型遗传网络中的遗传变异的详细图景，为我们理解复杂性状的遗传基础提供重大进展。将要进行的实验和建模工作将提供关于调节网络功能的这种变异的功能后果的见解。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水平上的变异与表型变异(如生理、形态、行为)之间的关系。要彻底了解这种关系，就需要研究单基因的突变效应，以及重点研究相互作用的基因和基因产物的网络。在这笔赠款的赞助下进行的研究将有助于更好地理解遗传变异如何影响基因网络，以及这种网络的行为如何导致不同的细胞表型。利用实验和数学相结合的方法，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萌芽酵母(酿酒酵母)对简单的环境线索(氮饥饿)的反应。酵母是目前研究最多的真核生物模型系统之一，也是一种重要的农业和工业微生物。对基因型-表型关系的深入了解将推动酵母遗传学的发展，并将有助于为在农业上重要的动植物进行类似的研究铺平道路。这项研究的更广泛的社会影响是促进博士后和本科生一级的培训和指导，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团体的成员。

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.