Department of Ecology & Evolutionary Biology, University of Michigan, Ann Arbor, Michigan, United States of America.
PLoS One. 2013;8(1):e53778. doi: 10.1371/journal.pone.0053778. Epub 2013 Jan 8.
The short length and high degeneracy of sites recognized by DNA-binding transcription factors limit the amount of information they can carry, and individual sites are rarely sufficient to mediate the regulation of specific targets. Computational analysis of microbial genomes has suggested that many factors function optimally when in a particular orientation and position with respect to their target promoters. To investigate this further, we developed and trained spatial models of binding site positioning and applied them to the genome of the yeast Saccharomyces cerevisiae. We found evidence of non-random organization of sites within promoters, differences in binding site density, or both for thirty-eight transcription factors. We show that these signatures allow transcription factors with substantial differences in binding site specificity to share similar promoter specificities. We illustrate how spatial information dictating the positioning and density of binding sites can in principle increase the information available to the organism for differentiating a transcription factor's true targets, and we indicate how this information could potentially be leveraged for the same purpose in bioinformatic analyses.
DNA 结合转录因子识别的短序列和高简并性限制了它们所能携带的信息量，而且单个结合位点通常不足以介导对特定靶标的调控。对微生物基因组的计算分析表明，许多因子在相对于其靶启动子的特定方向和位置上能够最佳地发挥作用。为了进一步研究这一点，我们开发并训练了结合位点定位的空间模型，并将其应用于酵母酿酒酵母的基因组。我们发现，三十八个转录因子的启动子内的结合位点存在非随机组织，或者结合位点密度存在差异，或者两者兼而有之。我们表明，这些特征允许具有显著不同结合位点特异性的转录因子具有相似的启动子特异性。我们说明了空间信息如何决定结合位点的定位和密度，从而可以增加生物区分转录因子真实靶标的信息量，并且我们指出了如何在生物信息学分析中出于相同目的利用该信息。
