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ECHOS enables spatial epigenome profiling at subcellular resolution

Cao, Q.; Xu, Q.; Ueda, Y.; Rajachandran, S.; Sharma, M.; Zhang, X.; Mahendroo, M.; Grow, E. J.; Chen, H.

2026-03-27 genetics
10.64898/2026.03.26.714421 bioRxiv
Show abstract

Biological structures and the epigenome are intertwined. For example, complex tissues are often the combined products of various groups of spatially patterned cell types with distinct epigenetic states. Furthermore, chromatin at various subnuclear locations within a cell often differ in their epigenetic properties. Thus, a systematic understanding of the relationship between the epigenome and its spatial distribution across biological scales would inform tissue and cellular functions as well as gene regulatory mechanisms. Yet, spatially resolved epigenome profiling--particularly at subcellular resolution--remains technically challenging. Here, we present Epigenetic CUT&Tag via High-resolution Optical Selection (ECHOS), a platform that combines high-resolution imaging and high-throughput sequencing to enable precise, spatially targeted epigenetic profiling across biological scales. At the cellular scale, ECHOS generates high-quality DNA-binding protein and histone modification datasets that show strong concordances with datasets from ChIP-seq and CUT&Tag experiments. Further optimization of ECHOS (ECHOS+) enables the characterization of the histone modification landscape of chromatin at the sub-micron resolution. Using ECHOS+, we revealed distinct gene regulatory logics at different layers of human ectocervical epithelium. We also showed that micronuclei--small nucleus-like structures formed by mitotic errors--exhibited a different epigenetic state from the same chromosome regions on the intact nuclei. Finally, we found that human aging altered the epigenetic state of the inactive X chromosome located in a subcellular nuclear structure called the Barr body, which may contribute to genes escaping X chromosome inactivation during female aging. Together, ECHOS and ECHOS+ represent a scalable and generalizable framework for spatial epigenomic analyses, with broad potential applications in various domains of biology.

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