Phasing single-molecule nano-NOMe-seq reveals chromatin state heterogeneity in the context of transcription and long-range interactions

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The study develops a cluster-based phasing approach using long-read single-molecule nano-NOMe-seq to connect chromatin accessibility and CTCF binding states in individual cells to promoter transcriptional activity and long-range enhancer–promoter loop configurations. By stitching partially overlapping reads and clustering them on shared GpC accessibility patterns, the authors stratify CTCF into graded single-molecule binding states, classify RNA polymerase states at Sox2, Hoxa, and Klf1 regions, and infer whether spatially separated loci are coordinately activated while occupying loop-competent configurations. A key caveat is that the paper is a technology/methods-focused demonstration, centered on specific genomic regions examined rather than a genome-wide census. This paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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ABSTRACT A central challenge in molecular biology is determining how 3D chromatin architecture, particularly enhancer-promoter looping and insulating CTCF-mediated interactions, influences gene transcription in individual cells, which has significant implications for healthy and diseased states. To overcome current limitations in imaging and genomic technologies, we developed a cluster-based phasing strategy using long read nano-NOMe-seq to link distinct CTCF binding states— captured at the single molecule level—to the transcriptional status of genes. By stitching partially overlapping long reads and clustering them by shared GpC-accessibility patterns, we stratify CTCF into graded binding states on individual molecules, classify RNA polymerase states at promoters/gene bodies, and infer when spatially separated loci are coordinately activated and occupy loop-competent configurations on the same molecules. When applied to Sox2, Hoxa, and Klf1 regions, cluster-based nano-NOMe-seq phasing reveals how specific topologies bias polymerase behavior and multi-locus activity in ways that bulk assays or locus-engineered imaging cannot fully capture. Competing Interest Statement The authors have declared no competing interest. Footnotes Fixes in Figure 1 (one profile in B and PI formula in C) Figure 5 and 6 (color of anchor validated by ORCA in legend box) Correction in Figure 7 legend (region length)

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last seen: 2026-05-20T01:45:00.602351+00:00