## 4 Conclusions  
In conclusion, an integrative computational and population-based bioinformatics approach was applied to systematically investigate the genome-wide distribution of Z-DNA-forming sequences within typical enhancers and super-enhancers. The findings highlight the significant non-random enrichment of Z-DNA-forming sequences within enhancer elements, particularly typical enhancers and super-enhancers, underscoring their potential functional roles in chromatin dynamics and transcription regulation. The identified mutations at these loci, notably concentrated within regions enriched for transcription factor binding motifs linked to the SP/KLF family, reveal possibly functional consequences relevant to gene regulation and human genetic variation. In particular, the clustering of novel variants in a single super-enhancer locus and their association with known pathogenic copy number variants emphasize the potential clinical relevance of these regions. Super-enhancers are known to regulate genes important during embryogenesis, ontogenesis, and disease development [3, 65, 66], likely via aforementioned mechanisms based on torsional stress-enhanced TF binding and phase separation. Revealed SP and KLF motifs, along with pathogenic variant overlaps, support the theory of narrow functional specialization of Z-DNA-enriched SE loci. In order to disclose this very intriguing question and fulfill scientific knowledge, future works should be conducted with the aim of dissecting these roles across various cell types using perturbation assays. These computational insights enhance our understanding of how Z-DNA might influence transcriptional regulation and genetic diversity, providing a robust foundation for subsequent experimental and clinical investigations. Future investigations could extend these analyses to larger population datasets, integrating CRISPR-based functional assays and high-resolution chromatin conformation techniques to confirm how non-B DNA conformations, such as Z-DNA, influence transcriptional output and contribute to disease etiologies. The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/app15095113/s1](https://www.mdpi.com/article/10.3390/app15095113/s1)]([https://www.mdpi.com/article/10.3390/app15095113/s1](https://www.mdpi.com/article/10.3390/app15095113/s1)). Table S1: Download Links for 100 individuals from the 1000 Genomes Project used in the study; Table S2: Fold-Change in Z-DNA Enrichment Across Enhancer Categories and Background Regions Across Cell Lines; Table S3: Disease-Associated Variants Identified Within Z-DNA-Forming Super-Enhancer Regions; Table S4: Per-individual information on mutation status, reference and alternative alleles, affected motifs, transcription factor binding changes, and intersections with pathogenic variants; Figure S1: Heat maps of Z-DNA distribution across enhancer elements in five cancer cell lines (HeLa, MDA-MB-231, MCFF, BT-549, LNCaPCap). Conceptualization, Y.V.M., G.A.A., A.V.O. and N.N.O. ; Data curation, Y.V.M., G.A.A., A.V.O., P.I.N., Z.G.Z. and N.N.O. ; Formal analysis, Y.V.M., G.A.A., A.V.O., P.I.N., Z.G.Z. and N.N.O. ; Funding acquisition, N.N.O. ; Investigation, Y.V.M., G.A.A., A.V.O., P.I.N., Z.G.Z. and N.N.O. ; Methodology, Y.V.M., G.A.A., A.V.O., P.I.N., Z.G.Z. and N.N.O. ; Project administration, G.A.A., A.V.O. and N.N.O. ; Resources, P.I.N. and N.N.O. ; Supervision, G.A.A., A.V.O. and N.N.O. ; Visualization, Y.V.M., G.A.A., A.V.O., P.I.N., Z.G.Z. and N.N.N.O. ; Writing--original draft, Y.V.M., G.A.A., A.V.O., P.I.N., Z.G.Z. and N.N.N.O. ; Writing--review and editing, Y.V.M., G.A.A., A.V.O., P.I.N., Z.G.Z. and N.N.O. All authors have read and agreed to the published version of the manuscript. This research was funded by the Russian Science Foundation, grant number 22-74-10053, [[https://rscf.ru/en/project/22-74-10053/](https://rscf.ru/en/project/22-74-10053/)]([https://rscf.ru/en/project/22-74-10053/](https://rscf.ru/en/project/22-74-10053/)) (accessed on 25 March 2025). Not applicable.