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 Show more
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. Show less
DNA structure has many potential places where endogenous compounds and xenobiotics can bind. Therefore, xenobiotics bind along the sites of the nucleic acid with the aim of changing its structure, its Show more
DNA structure has many potential places where endogenous compounds and xenobiotics can bind. Therefore, xenobiotics bind along the sites of the nucleic acid with the aim of changing its structure, its genetic message, and, implicitly, its functions. Currently, there are several mechanisms known to be involved in DNA binding. These mechanisms are covalent and non-covalent interactions. The covalent interaction or metal base coordination is an irreversible binding and it is represented by an intra-/interstrand cross-link. The non-covalent interaction is generally a reversible binding and it is represented by intercalation between DNA base pairs, insertion, major and/or minor groove binding, and electrostatic interactions with the sugar phosphate DNA backbone. In the present review, we focus on the types of DNAâmetal complex interactions (including some representative examples) and on presenting the methods currently used to study them. Show less
Computational methods to predict Z-DNA regions are in high demand to understand the functional role of Z-DNA. The previous state-of-the-art method Z-Hunt is based on statistical mechanical and energy Show more
Computational methods to predict Z-DNA regions are in high demand to understand the functional role of Z-DNA. The previous state-of-the-art method Z-Hunt is based on statistical mechanical and energy considerations about B- to Z-DNA transition using sequence information. Z-DNA CHiP-seq experiment results showed little overlap with Z-Hunt predictions implying that sequence information only is not sufficient to explain emergence of Z-DNA at different genomic locations. Adding epigenetic and other functional genomic mark-ups to DNA sequence level can help revealing the functional Z-DNA sites. Here we take advantage of the deep learning approach that can analyze and extract information from large volumes of molecular biology data. We developed a machine learning approach DeepZ that aggregates information from genome-wide maps of epigenetic markers, transcription factor and RNA polymerase binding sites, and chromosome accessibility maps. With the developed model we not only verify the experimental Z-DNA predictions, but also generate the whole-genome annotation, introducing new possible Z-DNA regions, which have not yet been found in experiments and can be of interest to the researchers from various fields. Show less