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Genome-Wide In Silico Identification of Transcriptional Regulators Controlling the Cell Cycle in Human Cells

机译:全基因组计算机控制转录调节剂在人类细胞中的周期调控。

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摘要

Dissection of regulatory networks that control gene transcription is one of the greatest challenges of functional genomics. Using human genomic sequences, models for binding sites of known transcription factors, and gene expression data, we demonstrate that the reverse engineering approach, which infers regulatory mechanisms from gene expression patterns, can reveal transcriptional networks in human cells. To date, such methodologies were successfully demonstrated only in prokaryotes and low eukaryotes. We developed computational methods for identifying putative binding sites of transcription factors and for evaluating the statistical significance of their prevalence in a given set of promoters. Focusing on transcriptional mechanisms that control cell cycle progression, our computational analyses revealed eight transcription factors whose binding sites are significantly overrepresented in promoters of genes whose expression is cell-cycle-dependent. The enrichment of some of these factors is specific to certain phases of the cell cycle. In addition, several pairs of these transcription factors show a significant co-occurrence rate in cell-cycle-regulated promoters. Each such pair indicates functional cooperation between its members in regulating the transcriptional program associated with cell cycle progression. The methods presented here are general and can be applied to the analysis of transcriptional networks controlling any biological process.[Supplemental material is available online at , including full lists of genes whose promoters were found to contain high scoring sites for any of the enriched transcription factors reported in Tables and .]>Table 1.Enriched TF PWMs in Promoters of E2F Target Genes
机译:控制基因转录的调节网络的解剖是功能基因组学的最大挑战之一。使用人类基因组序列,已知转录因子结合位点的模型和基因表达数据,我们证明了逆向工程方法可从基因表达模式中推断调控机制,可揭示人类细胞中的转录网络。迄今为止,仅在原核生物和低等真核生物中成功地证明了这种方法。我们开发了计算方法,用于鉴定假定的转录因子结合位点,并评估其在给定启动子集中的流行程度的统计学意义。着眼于控制细胞周期进程的转录机制,我们的计算分析揭示了八种转录因子,其结合位点在其表达是细胞周期依赖性基因的启动子中明显过量表达。其中某些因子的富集特定于细胞周期的某些阶段。此外,几对这些转录因子在细胞周期调控的启动子中显示出显着的共现率。每个这样的对指示其成员之间在调节与细胞周期进程相关的转录程序中的功能合作。这里介绍的方法是一般性的,可用于控制任何生物过程的转录网络的分析。[补充材料可在以下网站在线获得,包括发现其启动子包含任何富集转录因子高得分位点的基因的完整列表。在表和表中报告。] <!-表ft1-> <!-table-wrap mode =“ anchored” t5-> >表1。<!-标题a7->丰富的TF PWM E2F目标基因的启动子

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