Accurate Prediction of Inducible Transcription Factor Binding Intensities In Vivo

DNA sequence and local chromatin landscape act jointly to determine transcription factor (TF) binding intensity profiles. To disentangle these influences, we developed an experimental approach, called protein/DNA binding followed by high-throughput sequencing (PB–seq), that allows the binding energy landscape to be characterized genome-wide in the absence of chromatin. We applied our methods to the Drosophila Heat Shock Factor (HSF), which inducibly binds a target DNA sequence element (HSE) following heat shock stress. PB–seq involves incubating sheared naked genomic DNA with recombinant HSF, partitioning the HSF–bound and HSF–free DNA, and then detecting HSF–bound DNA by high-throughput sequencing. We compared PB–seq binding profiles with ones observed in vivo by ChIP–seq and developed statistical models to predict the observed departures from idealized binding patterns based on covariates describing the local chromatin environment. We found that DNase I hypersensitivity and tetra-acetylation of H4 were the most influential covariates in predicting changes in HSF binding affinity. We also investigated the extent to which DNA accessibility, as measured by digital DNase I footprinting data, could be predicted from MNase–seq data and the ChIP–chip profiles for many histone modifications and TFs, and found GAGA element associated factor (GAF), tetra-acetylation of H4, and H4K16 acetylation to be the most predictive covariates. Lastly, we generated an unbiased model of HSF binding sequences, which revealed distinct biophysical properties of the HSF/HSE interaction and a previously unrecognized substructure within the HSE. These findings provide new insights into the interplay between the genomic sequence and the chromatin landscape in determining transcription factor binding intensity.

DNA序列与局部染色质景观共同决定转录因子（transcription factor, TF）的结合强度谱。为厘清这些影响因素，我们开发了一种名为蛋白/DNA结合后高通量测序（protein/DNA binding followed by high-throughput sequencing, PB–seq）的实验方法，可在无染色质的全基因组范围内表征结合能景观。我们将该方法应用于果蝇热休克因子（Drosophila Heat Shock Factor, HSF）——该因子可在热休克应激后诱导结合靶DNA序列元件（Heat Shock Element, HSE）。PB–seq的实验流程为：将剪切后的裸露基因组DNA与重组HSF共孵育，分离结合HSF与未结合HSF的DNA，随后通过高通量测序检测结合HSF的DNA片段。我们将PB–seq得到的结合谱与体内染色质免疫共沉淀测序（ChIP–seq）获得的结合谱进行对比，并基于描述局部染色质环境的协变量开发了统计模型，以预测观测到的与理想结合模式的偏差。研究发现，DNase I超敏性与组蛋白H4四乙酰化是预测HSF结合亲和力变化的最具影响力的协变量。我们还探究了通过微球菌核酸酶测序（MNase–seq）数据以及多种组蛋白修饰与转录因子的染色质免疫共沉淀芯片（ChIP-chip）谱，能否预测数字DNase I足迹实验数据所表征的DNA可及性，并发现GAGA元件结合因子（GAGA element associated factor, GAF）、组蛋白H4四乙酰化以及组蛋白H4K16乙酰化是最具预测性的协变量。最后，我们构建了HSF结合序列的无偏模型，该模型揭示了HSF与HSE相互作用的独特生物物理特性，以及HSE内部此前未被发现的亚结构。本研究结果为理解基因组序列与染色质景观在决定转录因子结合强度中的相互作用提供了新视角。