Bhogale Shounak, Sinha Saurabh
Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
iScience. 2022 Mar 24;25(5):104152. doi: 10.1016/j.isci.2022.104152. eCollection 2022 May 20.
Transcription factors (TFs) influence gene expression by binding to DNA, yet experimental data suggests that they also frequently bind regulatory DNA indirectly by interacting with other DNA-bound proteins. Here, we used a data modeling approach to test if such indirect binding by TFs plays a significant role in gene regulation. We first incorporated regulatory function of indirectly bound TFs into a thermodynamics-based model for predicting enhancer-driven expression from its sequence. We then fit the new model to a rich data set comprising hundreds of enhancers and their regulatory activities during mesoderm specification in Drosophila embryogenesis and showed that the newly incorporated mechanism results in significantly better agreement with data. In the process, we derived the first sequence-level model of this extensively characterized regulatory program. We further showed that allowing indirect binding of a TF explains its localization at enhancers more accurately than with direct binding only. Our model also provided a simple explanation of how a TF may switch between activating and repressive roles depending on context.
转录因子（TFs）通过与DNA结合来影响基因表达，但实验数据表明，它们也经常通过与其他DNA结合蛋白相互作用而间接结合调控DNA。在这里，我们使用数据建模方法来测试TFs的这种间接结合是否在基因调控中起重要作用。我们首先将间接结合的TFs的调控功能纳入基于热力学的模型，以从其序列预测增强子驱动的表达。然后，我们将新模型与一个丰富的数据集进行拟合，该数据集包含果蝇胚胎发育中胚层特化过程中的数百个增强子及其调控活性，并表明新纳入的机制与数据的一致性显著提高。在此过程中，我们推导了这个广泛表征的调控程序的第一个序列水平模型。我们进一步表明，允许TF间接结合比仅考虑直接结合更准确地解释了其在增强子处的定位。我们的模型还提供了一个简单的解释，说明TF如何根据上下文在激活和抑制作用之间切换。
