Chromatin-dependent motif syntax defines differentiation trajectories [ChIP-seq]

Transcription factors (TFs) recognizing DNA motifs within regulatory regions drive cell identity. Despite recent advances, their specificity remains incompletely understood. Here, we address this by contrasting two TFs, Neurogenin-2 (NGN2) and MyoD1, which recognize ubiquitous E-box motifs yet drive distinct cell fates toward neurons and muscles, respectively. Upon induction in mouse embryonic stem cells, we monitor binding across differentiation, employing an interpretable machine learning approach that integrates preexisting DNA accessibility. This reveals a chromatin-dependent motif syntax, delineating both common and factor-specific binding, validated by cellular and in vitro assays. Shared binding sites reside in open chromatin, locally influenced by nucleosomes. In contrast, factor-specific binding in closed chromatin involves NGN2 and MyoD1 acting as pioneer factors, influenced by motif variant frequencies, motif spacing, and interaction partners, which together account for subsequent lineage divergence. Transferring our methodology to other models demonstrates how a combination of opportunistic binding and context-specific chromatin-opening underpin TF specificity, driving differentiation trajectories. ChIP-seq of NGN2, MyoD1 with mutant and GFP IP controls upon expression induction in mESCs together with H3K27ac and Pol2 ChIP-seq to monitor downstream effect

识别调控区域内DNA基序的转录因子（Transcription Factors, TFs）决定细胞身份。尽管近年研究取得诸多进展，但其结合特异性仍未被完全阐明。本研究通过对比两种转录因子——神经生成素2（Neurogenin-2, NGN2）与肌分化因子1（MyoD1）——来解决这一问题：二者均识别广泛存在的E盒基序（E-box motifs），却分别驱动神经元与肌肉细胞的独特细胞命运。在小鼠胚胎干细胞（mouse embryonic stem cells, mESCs）中诱导表达后，我们监测其在分化过程中的结合情况，并采用整合了预先存在的DNA可及性信息的可解释机器学习方法。该分析揭示了依赖于染色质状态的基序语法，勾勒出共有的转录因子结合位点与因子特异性结合位点，并通过细胞实验与体外实验验证了这一结论。共有结合位点位于开放染色质区域，其局部状态受核小体影响。与之相反，封闭染色质中的因子特异性结合位点则依赖于作为先驱因子（pioneer factors）的NGN2与MyoD1，其结合过程受基序变体频率、基序间距与互作蛋白的共同调控，这些因素共同解释了后续的细胞谱系分化差异。将本研究方法推广至其他模型后，我们证明机遇性结合与情境特异性染色质开放的协同作用如何支撑转录因子的结合特异性，并驱动细胞分化轨迹。本研究获取了在mESCs中诱导表达后的NGN2、MyoD1及其突变体与GFP免疫沉淀（GFP IP）对照的染色质免疫共沉淀测序（ChIP-seq）数据，同时获取了组蛋白H3赖氨酸27乙酰化（H3K27ac）与RNA聚合酶II（Pol2）的ChIP-seq数据以监测下游生物学效应。