Beknazarov Nazar, Konovalov Dmitry, Herbert Alan, Poptsova Maria
Laboratory of Bioinformatics, Faculty of Computer Science, National Research University Higher School of Economics, Moscow, Russia.
InsideOutBio, Charlestown, MA, USA.
Sci Rep. 2024 Aug 1;14(1):17786. doi: 10.1038/s41598-024-68439-y.
A long-standing question concerns the role of Z-DNA in transcription. Here we use a deep learning approach DeepZ that predicts Z-flipons based on DNA sequence, structural properties of nucleotides and omics data. We examined Z-flipons that are conserved between human and mouse genomes after generating whole-genome Z-flipon maps and then validated them by orthogonal approaches based on high resolution chemical mapping of Z-DNA and the transformer algorithm Z-DNABERT. For human and mouse, we revealed similar pattern of transcription factors, chromatin remodelers, and histone marks associated with conserved Z-flipons. We found significant enrichment of Z-flipons in alternative and bidirectional promoters associated with neurogenesis genes. We show that conserved Z-flipons are associated with increased experimentally determined transcription reinitiation rates compared to promoters without Z-flipons, but without affecting elongation or pausing. Our findings support a model where Z-flipons engage Transcription Factor E and impact phenotype by enabling the reset of preinitiation complexes when active, and the suppression of gene expression when engaged by repressive chromatin complexes.
一个长期存在的问题涉及Z-DNA在转录中的作用。在这里，我们使用一种深度学习方法DeepZ，它基于DNA序列、核苷酸的结构特性和组学数据预测Z-翻转子。在生成全基因组Z-翻转子图谱后，我们检查了人类和小鼠基因组之间保守的Z-翻转子，然后通过基于Z-DNA高分辨率化学图谱和Transformer算法Z-DNABERT的正交方法对它们进行验证。对于人类和小鼠，我们揭示了与保守Z-翻转子相关的转录因子、染色质重塑因子和组蛋白标记的相似模式。我们发现与神经发生基因相关的可变启动子和双向启动子中Z-翻转子显著富集。我们表明，与没有Z-翻转子的启动子相比，保守的Z-翻转子与实验确定的转录重新起始率增加相关，但不影响延伸或暂停。我们的研究结果支持一种模型，即Z-翻转子与转录因子E结合，并通过在激活时使预起始复合物重置，以及在与抑制性染色质复合物结合时抑制基因表达来影响表型。
