Abstract
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.
Highlights
The ability of any biological system to properly respond to stimuli heavily depends on biochemical cascades of signaling pathways that culminate in the activation of transcription factors (TFs) and the subsequent alteration of gene expression patterns [1]
Overview of STAT-Finder To identify direct Signal transducer and activator of transcription 3 (STAT3) target genes, we developed a computational framework that predicts functional transcription factor binding sites (TFBSs) of STAT3 with increased sensitivity and low false positive rate
We presented a computational framework for identifying functional STAT3 TFBSs in mammalian promoters
Summary
The ability of any biological system to properly respond to stimuli heavily depends on biochemical cascades of signaling pathways that culminate in the activation of transcription factors (TFs) and the subsequent alteration of gene expression patterns [1]. Information about which genes need to be expressed in a specific cell type at any given time is believed to be encoded in the genome. The molecular machinery used to interpret such genetic information has evolved to ensure the accuracy and specificity of gene regulation. Transcriptional activators and repressors bind in a sequence-specific manner to promoters or enhancers of target genes. They govern the recruitment of transactivators, chromatin modifiers, and general transcription factors, including RNA polymerase II, to regulate gene expression [2,3]
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