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Dissecting network motifs by identifying promoter features that govern differential gene expression

机译:通过鉴定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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One of the biggest challenges in genomics is the elucidation of the design principles controlling gene expression. Current approaches examine promoter sequences for particular features, such as the presence of binding sites for a transcriptional regulator, and identify recurrent relationships among these features termed network motifs. To define the expression dynamics of a group of genes, the strength of the connections in a network must be specified, and these are determined by the cis-promoter features participating in the regulation. Approaches that homogenize features among promoters (e.g., relying on consensuses to describe the various promoter features) and even across species hamper the discovery of the key differences that distinguish promoters that are co-regulated by the same transcriptional regulator. Thus, we have developed a an approach based on fuzzy logic expressions to analyze proteobacterial genomes for promoter features that is specifically designed to account for the variability in sequence, location and topology intrinsic to differential gene expression. We applied our method to characterize network motifs controlled by the PhoP/PhoQ regulatory system of Escherichia coli and Salmonella enterica serovar Typhimurium. We identify key features that that enable the PhoP protein to produce differential regulation in target genes, reflecting distinct kinetic patterns even for the same type of network motif. These findings could not have been uncovered just by inspecting network architecture. We show that the same approach can be generalized to model other regulatory systems.
机译:基因组学中最大的挑战之一是阐明控制基因表达的设计原理。电流方法检查特定特征的启动子序列,例如对转录调节剂的结合位点的存在,并识别这些特征所谓的网络图案中的复发关系。为了定义一组基因的表达动态,必须指定网络中的连接中的连接强度,并通过参与调节的顺式启动子特征来确定。致促进剂中特征的方法(例如,依赖于描述各种启动子特征的共识),甚至跨种类妨碍了发现由相同转录调节剂共同调节的启动子的关键差异的发现。因此,我们已经开发了一种基于模糊逻辑表达的一种方法,以分析用于促进剂特征的植物基因组,所述促进剂特征专门设计用于考虑序列,位置和拓扑的变异性,差异基因表达。我们应用了我们的方法来表征由大肠杆菌和牛蒡子肠道塞洛维尔毒蕈类动物和沙门氏菌的Phop / Phoq监管系统控制的网络图案。我们识别能够使PHOP蛋白能够在靶基因中产生差异调节的关键特征,即使对于相同类型的网络图案,也反映了不同的动力学模式。只需检查网络架构就无法发现这些发现。我们表明,相同的方法可以推广到建模其他监管系统。

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