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Non-disruptive 3D Profiling of Combinations of Epigenetic Marks in Single Cells

GSE274718 Mus musculus Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing 6 samples Submitted 2025/07/30 Platform GPL24247
Summary
Recent advancements in single-cell sequencing and spatial omics technologies have enhanced our understanding of diverse cellular identities, compositions, and functions. However, the single-cell three-dimensional (3D) organization of the epigenome is still not well understood, due to an absence of spatial single-cell methods that allow high-resolution, locus-specific detection of combinations of epigenetic marks while maintaining the 3D organization of the genome. Here, we develop Epigenetic Proximity Hybridization Reaction (Epi-PHR), an image-based single-cell spatial epigenetic profiling technique. Epi-PHR enables high-sensitivity and high-resolution in situ detection of combinations of epigenetic marks at hundreds of single gene targets within the same individual cells, while retaining the 3D organization of the genome, a clear advantage over previous technologies. Phased Epi-PHR combined with chromatin tracing simultaneously detects allele-specific epigenetic states and chromatin conformations of an imprinting gene cluster in single cells, revealing associations between specific epigenetic mark enrichment and chromatin folding features for the distinct alleles from different parental origins. We expect Epi-PHR to be broadly applicable in research requiring single-cell spatial epigenetic information, and to help understand the combinatorial code of epigenetic marks and its relationship with chromatin folding in diverse biological and medical contexts.
Published in
Non-disruptive 3D profiling of combinations of epigenetic marks in single cells
Chen Y, Radda JSD, Alderman MH 3rd et al. · bioRxiv : the preprint server for biology 2025 · PMID 40666962 · doi:10.1101/2025.06.13.659535
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Also filed as BioProject PRJNA1147705 and SRA study SRP526131. Searching any of these in the dataset finder brings you back here.

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