Functional promoter modules can be defected by formal models independent of overall nucleoside sequence similarity
Functional promoter modules can be defected by formal models independent of overall nucleoside sequence similarity
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DOI：
10.1093/bioinformatics/15.3.180
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发表时间：
1999-03-01
期刊：
影响因子：
5.8
通讯作者：
Werner, T
中科院分区：
文献类型：
--
作者：
Klingenhoff, A;Frech, K;Werner, T
动机：基因调控通常依赖于功能模块，这些功能模块具有可检测的内部组织。这些模块的整体序列相似性通常不足以通过一般搜索方法如FASTA或甚至Gapped BLAST进行检测。然而，评估通常从单个序列的实验分析中已知的模块是否存在于其他调控序列中是有意义的。我们开发了一种新的方法（FastM），它结合了单个转录因子结合位点的搜索算法（MatInspector）与距离相关函数。FastM允许快速定义相关的结合位点模型，这些结合位点来源于少至单个启动子或增强子。ModelInspector结果适用于评估模型的显著性。我们使用FastM来定义一个模型，用于实验验证的NF κ B B/IRF 1调节模块从主要组织相容性复合体（MHC）I类HLA-B基因启动子。分析一组测试序列以及使用该模型进行的数据库搜索显示，该模型与模块的生物学功能具有良好的相关性。这些结果不能通过使用基于序列相似性的FASTA或Gapped BLAST的检索获得。我们还能够证明一个假设的GRE-GRE模块与病毒序列的分析的基础上，与此模块的几个基因库部分的关联。
Motivation: Gene regulation often depends on functional modules which feature a detectable internal organization. Overall sequence similarity of these modules is often insufficient for detection by general search methods like FASTA or even Gapped BLAST However; it is of interest to evaluate whether modules, often known from experimental analysis of single sequences, are present in other regulatory sequences.Results: We developed a new method (FastM) which combines a search algorithm for individual transcription factor binding sites (MatInspector) with a distance correlation function. FastM allows fast definition of a model of correlated binding sires derived from as little as a single promoter or enhancer ModelInspector results are suitable for evaluation of the significance of the model. We used FastM to define a model for the experimentally verified NF kappa B/IRF1 regulatory module from the major histocompatibility complex (MHC) class I HLA-B gene promoter Analysis of a test set of sequences as Ir ell as database searches with this model showed excellent correlation of the model with the biological function of the module. These results could not be obtained by searches using FASTA or Gapped BLAST, which are based on sequence similarity. We were also able to demonstrate association of a hypothetical GRE-GRE module with viral sequences based on analysis of several GenBank sections with this module.