Department of Life Sciences, Pohang University of Science and Technology, Pohang, Republic of Korea.
PLoS One. 2009 Sep 4;4(9):e6911. doi: 10.1371/journal.pone.0006911.
The comprehensive identification of functional transcription factor binding sites (TFBSs) is an important step in understanding complex transcriptional regulatory networks. This study presents a motif-based comparative approach, STAT-Finder, for identifying functional DNA binding sites of STAT3 transcription factor. STAT-Finder combines STAT-Scanner, which was designed to predict functional STAT TFBSs with improved sensitivity, and a motif-based alignment to minimize false positive prediction rates. Using two reference sets containing promoter sequences of known STAT3 target genes, STAT-Finder identified functional STAT3 TFBSs with enhanced prediction efficiency and sensitivity relative to other conventional TFBS prediction tools. In addition, STAT-Finder identified novel STAT3 target genes among a group of genes that are over-expressed in human cancer cells. The binding of STAT3 to the predicted TFBSs was also experimentally confirmed through chromatin immunoprecipitation. Our proposed method provides a systematic approach to the prediction of functional TFBSs that can be applied to other TFs.
综合识别功能转录因子结合位点（TFBS）是理解复杂转录调控网络的重要步骤。本研究提出了一种基于基序的比较方法 STAT-Finder，用于鉴定 STAT3 转录因子的功能 DNA 结合位点。STAT-Finder 结合了 STAT-Scanner，它旨在提高灵敏度预测功能 STAT TFBS，以及基于基序的对齐以最小化假阳性预测率。使用包含已知 STAT3 靶基因启动子序列的两个参考集，与其他常规 TFBS 预测工具相比，STAT-Finder 提高了预测效率和灵敏度，确定了功能 STAT3 TFBS。此外，STAT-Finder 在一组在人类癌细胞中过度表达的基因中鉴定了新的 STAT3 靶基因。通过染色质免疫沉淀实验也证实了 STAT3 与预测的 TFBS 的结合。我们提出的方法为预测功能 TFBS 提供了一种系统的方法，可应用于其他 TF。
