NSF Postdoctoral Fellowship in Biology FY 2010

这一行动为2010财年的NSF博士后研究奖学金提供资金。该研究金支持Janna Fierst的一项题为“酿酒酵母遗传相互作用网络的演变”的研究和培训计划。这项研究的主办机构是俄勒冈州大学，赞助科学家是帕特里克菲利普斯。生物学的一个中心问题是如何定义遗传信息和分子过程是如何整合产生一个有机体的。这需要理解选择、遗传漂变和突变如何塑造基因型-表型图谱的进化。基因组学和系统生物学研究正在迅速产生关于遗传系统机制的数据。然而，大多数进化理论都是在分子遗传学和发现基因通常在网络中相互作用之前发展起来的。如果没有额外的理论来考虑这种相互作用，这些数据就无法在进化框架中理解，我们也无法识别有意义的模式。本研究利用酿酒酵母人工合成致死基因互作网络中的基因互作和基因表达数据，建立了网络进化的理论模型。该模型被用来分析选择、漂移和突变对两种不同菌株之间观察到的网络变化的影响。具体的培训目标包括提高生物信息学和计算技能，并熟悉公开可用的基因组和系统生物数据集。更广泛的影响包括创建一个公共数据库，整合S.酿酒，分发网络进化模型，并通过俄勒冈州大学本科生研究暑期项目（SPUR）培训生物信息学和计算生物学的本科生。这些结果扩展了进化遗传学理论，并提供了一个理论框架，其中基因组和系统生物学模式可以与进化过程相关联。

This action funds an NSF Postdoctoral Research Fellowship for FY 2010. The fellowship supports a research and training plan entitled "Evolution of the Saccharomyces cerevisiae genetic interaction network" for Janna Fierst. The host institution for this research is University of Oregon, and the sponsoring scientist is Patrick Phillips.A central problem in biology concerns defining how genetic information and molecular processes are integrated to produce an organism. This requires understanding how selection, genetic drift and mutation shape the evolution of the genotype-phenotype map. Genomics and systems biological studies are rapidly producing data on the mechanisms underlying the genetic system. Most evolutionary theory, however, was developed before the advent of molecular genetics and the discovery that genes commonly interact in networks. Without additional theory to take such interactions into account, these data cannot be understood in an evolutionary framework and we cannot identify meaningful patterns. This project uses data on genetic interactions and gene expression in the Saccharomyces cerevisiae synthetic lethal genetic interaction network to build a theoretical model of network evolution. This model is being used to analyze the influence of selection, drift and mutation on network changes that are observed between two different strains of S. cerevisiae and the related yeast Schizosaccharomyces pombe.Specific training goals include increasing bioinformatics and computational skills, and gaining familiarity with publicly available genomic and systems biological datasets. The broader impacts include creating a public database integrating gene expression and genetic interactions in S. cerevisiae, distributing a network evolution model, and training undergraduates in bioinformatics and computational biology through the University of Oregon summer program for undergraduate research (SPUR). The results expand evolutionary genetics theory and provide a theoretical framework in which genomic and systems biological patterns can be associated with evolutionary processes.