Transcription Factor Map Alignment of Promoter Regions

We address the problem of comparing and characterizing the promoter regions of genes with similar expression patterns. This remains a challenging problem in sequence analysis, because often the promoter regions of co-expressed genes do not show discernible sequence conservation. In our approach, thus, we have not directly compared the nucleotide sequence of promoters. Instead, we have obtained predictions of transcription factor binding sites, annotated the predicted sites with the labels of the corresponding binding factors, and aligned the resulting sequences of labels��to which we refer here as transcription factor maps (TF-maps). To obtain the global pairwise alignment of two TF-maps, we have adapted an algorithm initially developed to align restriction enzyme maps. We have optimized the parameters of the algorithm in a small, but well-curated, collection of human�Cmouse orthologous gene pairs. Results in this dataset, as well as in an independent much larger dataset from the CISRED database, indicate that TF-map alignments are able to uncover conserved regulatory elements, which cannot be detected by the typical sequence alignments.本研究旨在解决具有相似表达模式的基因的启动子区域的比较与特征分析问题。该问题在序列分析领域仍极具挑战性，因为共表达基因的启动子区域往往不具备可辨识的序列保守性。因此，本研究并未直接对启动子的核苷酸序列进行比对。取而代之的是，我们首先预测得到转录因子结合位点（transcription factor binding sites），为每个预测得到的结合位点标注对应转录因子的标识，并将所得的标识序列进行比对——本文中将此类标识序列称为转录因子图谱（transcription factor maps，TF-maps）。为实现两个TF-maps的全局两两比对，我们对最初用于限制性酶切图谱比对的算法进行了适配改造。我们在一组规模有限但经过精心整理的人-小鼠同源基因对集合中，对该算法的参数进行了优化。本数据集以及来自CISRED数据库的另一组规模更大的独立数据集的实验结果均表明，TF-map比对能够发掘出经典序列比对无法检测到的保守调控元件。