Osman Noha M, Kitapci Tevfik Hamdi, Vlaho Srna, Wunderlich Zeba, Nuzhdin Sergey V
University of Southern California, Los Angeles, CA.
National Research Centre, Dokki, Giza, Egypt.
Biophysics (Oxf). 2018 Jan;63(1):43-51. doi: 10.1134/S0006350918010128. Epub 2018 Apr 23.
Gene regulatory networks control the complex programs that drive development. Deciphering the connections between transcription factors (TFs) and target genes is challenging, in part because TFs bind to thousands of places in the genome but control expression through a subset of these binding events. We hypothesize that we can combine natural variation of expression levels and predictions of TF binding sites to identify TF targets. We gather RNA-seq data from 71 genetically distinct F1 embryos and calculate the correlations between TF and potential target genes' expression levels, which we call "regulatory strength." To separate direct and indirect TF targets, we hypothesize that direct TF targets will have a preponderance of binding sites in their upstream regions. Using 14 TFs active during embryogenesis, we find that 12 TFs showed a significant correlation between their binding strength and regulatory strength on downstream targets, and 10 TFs showed a significant correlation between the number of binding sites and the regulatory effect on target genes. The general roles, e.g. 's role as an activator, and the particular interactions we observed between our TFs, e.g. role as a repressor of and , generally coincide with the literature.
基因调控网络控制着驱动发育的复杂程序。解读转录因子（TFs）与靶基因之间的联系具有挑战性，部分原因是TFs与基因组中的数千个位点结合，但通过这些结合事件的一个子集来控制基因表达。我们假设可以结合表达水平的自然变异和TF结合位点的预测来识别TF靶标。我们收集了来自71个基因不同的F1胚胎的RNA测序数据，并计算TF与潜在靶基因表达水平之间的相关性，我们将其称为“调控强度”。为了区分直接和间接的TF靶标，我们假设直接的TF靶标在其上游区域会有大量的结合位点。使用在胚胎发生过程中活跃的14个TFs，我们发现12个TFs在其与下游靶标的结合强度和调控强度之间显示出显著相关性，并且10个TFs在结合位点数量与对靶基因的调控作用之间显示出显著相关性。这些TFs的一般作用，例如 作为激活剂的作用，以及我们观察到的TFs之间的特定相互作用，例如 作为 和 的抑制剂的作用，总体上与文献一致。
