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首页> 外文会议>2007 summer computer simulation conference (SCSC'07) >Dissecting network motifs by identifying promoter features that govern differential gene expression
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Dissecting network motifs by identifying promoter features that govern differential gene expression

机译：通过识别控制差异基因表达的启动子特征来解剖网络基序

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摘要

One of the biggest challenges in genomics is thernelucidation of the design principles controlling genernexpression. Current approaches examine promoterrnsequences for particular features, such as the presence ofrnbinding sites for a transcriptional regulator, and identifyrnrecurrent relationships among these features termed networkrnmotifs. To define the expression dynamics of a group ofrngenes, the strength of the connections in a network must bernspecified, and these are determined by the cis-promoterrnfeatures participating in the regulation. Approaches thatrnhomogenize features among promoters (e.g., relying onrnconsensuses to describe the various promoter features) andrneven across species hamper the discovery of the keyrndifferences that distinguish promoters that are co-regulatedrnby the same transcriptional regulator. Thus, we haverndeveloped a an approach based on fuzzy logic expressionsrnto analyze proteobacterial genomes for promoter featuresrnthat is specifically designed to account for the variability inrnsequence, location and topology intrinsic to differential genernexpression. We applied our method to characterize networkrnmotifs controlled by the PhoP/PhoQ regulatory system ofrnEscherichia coli and Salmonella enterica serovarrnTyphimurium. We identify key features that that enable thernPhoP protein to produce differential regulation in targetrngenes, reflecting distinct kinetic patterns even for the samerntype of network motif. These findings could not have beenrnuncovered just by inspecting network architecture. We showrnthat the same approach can be generalized to model otherrnregulatory systems.
机译：基因组学的最大挑战之一是对控制基因表达的设计原则的阐明。当前的方法检查特定特征的启动子序列，例如转录调节子的结合位点的存在，并鉴定这些被称为网络基序的特征之间的递归关系。要定义一组基因的表达动力学，必须指定网络中连接的强度，这些强度由参与调控的顺式启动子功能决定。使启动子之间的特征同质化的方法（例如，依靠共识来描述各种启动子特征）以及跨物种的方法阻碍了关键区别的发现，这些区别区别了由同一转录调节子共同调节的启动子。因此，我们已经开发出了一种基于模糊逻辑表达式来分析蛋白细菌基因组的启动子特征的方法，该方法专门用于解决差异基因表达固有的变异性序列，位置和拓扑。我们应用我们的方法来表征由大肠杆菌和肠炎沙门氏菌鼠伤寒沙门氏菌的PhoP / PhoQ调节系统控制的网络基序。我们确定了关键的功能，这些功能使rnPhoP蛋白能够在targetrngenes中产生差异调节，甚至针对相同类型的网络主题也能反映出不同的动力学模式。仅通过检查网络体系结构就无法发现这些发现。我们证明，可以将相同的方法推广到其他调节系统的模型中。

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  • 来源
  • 会议地点 San Diego CA(US);San Diego CA(US)
  • 作者

    Oscar Harari; Igor Zwir;

  • 作者单位

    Department of Computer Science, University of Buenos Aires, Buenos Aires, Argentina Department Computer Science and Artificial Intelligence, University of Granada, Granada, Spain;

    rnDepartment Computer Science and Artificial Intelligence, University of Granada, Granada, Spain Howard Hughes Medical Institute, Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, Missouri, USA, E-mail: zwir@borcim.wustl.edu;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 计算机仿真;
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