Xie Zhiyuan, Sokolov Ilya, Osmala Maria, Yue Xue, Bower Grace, Pett J Patrick, Chen Yinan, Wang Kai, Cavga Ayse Derya, Popov Alexander, Teichmann Sarah A, Morgunova Ekaterina, Kvon Evgeny Z, Yin Yimeng, Taipale Jussi
State Key Laboratory of Cardiovascular Diseases and Medical Innovation Center, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China.
Department of Biochemistry, University of Cambridge, Cambridge, UK.
Nature. 2025 Apr 9. doi: 10.1038/s41586-025-08844-z.
In the same way that the mRNA-binding specificities of transfer RNAs define the genetic code, the DNA-binding specificities of transcription factors (TFs) form the molecular basis of the gene regulatory code. The human gene regulatory code is much more complex than the genetic code, in particular because there are more than 1,600 TFs that commonly interact with each other. TF-TF interactions are required for specifying cell fate and executing cell-type-specific transcriptional programs. Despite this, the landscape of interactions between DNA-bound TFs is poorly defined. Here we map the biochemical interactions between DNA-bound TFs using CAP-SELEX, a method that can simultaneously identify individual TF binding preferences, TF-TF interactions and the DNA sequences that are bound by the interacting complexes. A screen of more than 58,000 TF-TF pairs identified 2,198 interacting TF pairs, 1,329 of which preferentially bound to their motifs arranged in a distinct spacing and/or orientation. We also discovered 1,131 TF-TF composite motifs that were markedly different from the motifs of the individual TFs. In total, we estimate that the screen identified between 18% and 47% of all human TF-TF motifs. The novel composite motifs we found were enriched in cell-type-specific elements, active in vivo and more likely to be formed between developmentally co-expressed TFs. Furthermore, TFs that define embryonic axes commonly interacted with different TFs and bound to distinct motifs, explaining how TFs with a similar specificity can define distinct cell types along developmental axes.
正如转运RNA的mRNA结合特异性定义了遗传密码一样,转录因子(TFs)的DNA结合特异性构成了基因调控密码的分子基础。人类基因调控密码比遗传密码复杂得多,特别是因为有1600多种TFs通常相互作用。TF-TF相互作用对于确定细胞命运和执行细胞类型特异性转录程序是必需的。尽管如此,DNA结合TFs之间的相互作用情况仍不清楚。在这里,我们使用CAP-SELEX绘制DNA结合TFs之间的生化相互作用图谱,这是一种可以同时识别单个TF结合偏好、TF-TF相互作用以及相互作用复合物结合的DNA序列的方法。对超过58,000个TF-TF对的筛选确定了2198个相互作用的TF对,其中1329个优先结合以不同间距和/或方向排列的基序。我们还发现了1131个TF-TF复合基序,它们与单个TF的基序明显不同。我们估计,该筛选总共识别出了所有人类TF-TF基序的18%至47%。我们发现的新型复合基序在细胞类型特异性元件中富集,在体内具有活性,并且更有可能在发育中共表达的TFs之间形成。此外,定义胚胎轴的TFs通常与不同的TFs相互作用并结合到不同的基序上,这解释了具有相似特异性的TFs如何沿着发育轴定义不同的细胞类型。