Institute of Computer Science, Martin Luther University Halle-Wittenberg, Halle 06120, Germany.
Goethe-University Frankfurt, Institute for Cardiovascular Regeneration, Theodor-Stern-Kai 7, 60590 Frankfurt, Germany.
Nucleic Acids Res. 2023 Oct 13;51(18):e95. doi: 10.1093/nar/gkad693.
Several studies suggested that transcription factor (TF) binding to DNA may be impaired or enhanced by DNA methylation. We present MeDeMo, a toolbox for TF motif analysis that combines information about DNA methylation with models capturing intra-motif dependencies. In a large-scale study using ChIP-seq data for 335 TFs, we identify novel TFs that show a binding behaviour associated with DNA methylation. Overall, we find that the presence of CpG methylation decreases the likelihood of binding for the majority of methylation-associated TFs. For a considerable subset of TFs, we show that intra-motif dependencies are pivotal for accurately modelling the impact of DNA methylation on TF binding. We illustrate that the novel methylation-aware TF binding models allow to predict differential ChIP-seq peaks and improve the genome-wide analysis of TF binding. Our work indicates that simplistic models that neglect the effect of DNA methylation on DNA binding may lead to systematic underperformance for methylation-associated TFs.
几项研究表明,转录因子(TF)与 DNA 的结合可能会受到 DNA 甲基化的损害或增强。我们提出了 MeDeMo,这是一个用于 TF 基序分析的工具包,它将 DNA 甲基化的信息与捕获基序内依赖性的模型相结合。在一项使用 335 个 TF 的 ChIP-seq 数据的大规模研究中,我们确定了显示与 DNA 甲基化相关的结合行为的新型 TF。总体而言,我们发现 CpG 甲基化的存在降低了大多数与甲基化相关的 TF 结合的可能性。对于相当一部分 TF,我们表明基序内的依赖性对于准确建模 DNA 甲基化对 TF 结合的影响至关重要。我们表明,新型的甲基化感知 TF 结合模型可以预测差异 ChIP-seq 峰,并改进 TF 结合的全基因组分析。我们的工作表明,忽略 DNA 甲基化对 DNA 结合影响的简单模型可能会导致与甲基化相关的 TF 出现系统性能下降。