Conventional Hi-C, first described more than a decade and a half ago, revolutionized genomics by revealing that chromosomes fold into compartments, topologically associating domains, and loops that bring distant regulatory elements into physical proximity. But the technique has always carried a fundamental trade-off. To generate enough material for sequencing, researchers typically dissociate tissues into cell suspensions or grind them into homogenates, destroying the spatial context that makes a brain a brain. Single-cell Hi-C and imaging-based chromatin tracing recovered some of that information, but at the cost of throughput, resolution, or genomic coverage. Spatial transcriptomics, meanwhile, maps gene expression across tissue but says nothing about the physical folding of the DNA that produces that expression. Spatial Hi-C was designed to close precisely this gap.

The technical core of the method is a microfluidic device that performs the Hi-C chemistry in situ on thin tissue sections. The chip contains arrays of parallel channels, with widths of 10, 20, or 50 micrometers depending on the desired resolution, through which barcoded reagents are delivered to spatially defined strips of the section. By running the barcoding in two perpendicular passes, each microscopic spot on the tissue acquires a unique combination of two barcodes, effectively assigning a spatial address to every chromatin contact captured there. The researchers verified that the channels do not leak or diffuse into one another using fluorescent dyes, and demonstrated that valid contact counts concentrate within expected barcode combinations rather than spreading across the chip. The result is a contact map, the raw currency of Hi-C analysis, attached to a coordinate on the tissue.

To validate the approach, the team applied spatial Hi-C to sections of mouse embryos at embryonic day 13. Pseudobulk contact matrices, generated by pooling data across an entire section, showed the expected high-quality features of Hi-C data, including clear compartmentalization and domain structure at resolutions down to 10 kilobases. Unsupervised clustering of the spatial data reproduced the anatomy of the embryo, separating the central nervous system from surrounding mesenchyme and other tissues without any anatomical annotation being provided. When the researchers compared their spatial Hi-C clusters with bulk Hi-C data generated from manually dissected embryonic organs, principal component analysis showed tight agreement, and aggregate compartment and TAD signals were highly consistent. Correlations between replicate sections exceeded 0.95, indicating that the method is both faithful and reproducible.

Integrating spatial Hi-C with spatial transcriptomics on adjacent sections proved particularly powerful. In the E13 embryo, the team identified differential chromatin interactions between the central nervous system and mesenchymal regions, including changes in A/B compartment scores, reorganized TAD boundaries, and distinct chromatin loops. Genes such as Nova1, a neuronal splicing regulator, and Tbx3, a transcription factor involved in developmental patterning, showed spatial expression patterns that aligned with spatially resolved changes in their local chromatin contact landscapes. Differential loop anchors were enriched for genes involved in neural and developmental functions, and examples such as Dner in the nervous system and Gja1 in mesenchyme illustrated how enhancer-promoter wiring differs across tissue regions. The compartment scores derived from spatial Hi-C tracked the expression of marker genes for neural progenitor cells, premature neurons, heart, and liver clusters identified by the transcriptomic data.

The adult mouse cerebellum provided the most striking demonstration of the method’s spatial resolving power. At 20-micrometer resolution, spatial Hi-C distinguished the molecular layer, Purkinje layer, granular layer, and white matter by their 3D genome architectures. Within the granular layer, the analysis revealed subclusters with distinct 3D genomes that aligned with the anatomical lobules of the cerebellum, the repeating folds that organize cerebellar function. Genes such as Dpp6, Gprin3, and Galntl6 showed promoter-region compartment scores that varied systematically across these granule cell subclusters, and the corresponding spatial expression patterns in the transcriptomic data mirrored the chromatin differences. The researchers also documented B-compartment fusion events and differential TAD reorganization between the granular and Purkinje layers, including loops at the Etv1 locus, a regulator of granule cell maturation, whose associated enhancer was validated in an independent in vivo reporter assay.

Pushing resolution further, the team achieved single-spot 3D chromatin reconstruction in the adult cortex at 10 micrometers, a scale comparable to single-cell data. Using the Tensor-FLAMINGO algorithm, they reconstructed distance matrices and 3D structures for individual nuclear spots that closely matched those derived from Dip-C single-cell datasets of the same brain regions. Spatial Hi-C clusters in the cortex corresponded to cortical layers and to cell types identified by single-nucleus transcriptomic references, and spots overlapping segmented nuclei by more than 90 percent provided near-single-cell chromatin contact information. In the hippocampus, the method resolved clusters corresponding to the dentate gyrus, CA1 pyramidal layer, and even the ependymal cell layer lining the ventricles, with compartment scores at loci such as Npas3 and Vit1a varying across these microdomains.

Perhaps the most conceptually significant finding came from the developing brain. Across embryonic days 14.5, 16.5, and 18.5, the researchers measured the ratio of short-range to long-range chromatin interactions on coronal sections and found an increasing radial gradient of this ratio from the germinal zone toward the cortical plate. This gradient tracked neuronal maturity: when compared with CytoTRACE2 developmental potency scores computed from spatial transcriptomic data, the short-versus-long interaction ratio correlated significantly across clusters at 10-micrometer resolution. In other words, the physical compactness of local chromatin packing, readable directly from tissue, serves as a marker of how far a neuron has progressed along its developmental trajectory. Genes such as Sox2 and Notch2, markers of progenitors, and Celf2 and Ank3, associated with maturing neurons, showed spatial expression patterns consistent with the chromatin gradient.

The implications extend well beyond neurobiology. Disease-associated non-coding variants often act through long-range enhancer-promoter contacts that are specific to cell type and tissue context, and a method that preserves both the contact information and the anatomical address could pinpoint where in a tissue a regulatory variant exerts its effect. The data and code from the study have been deposited in public repositories, including the Genome Sequence Archive and Zenodo, with BEDPE contact files ready for standard Hi-C visualization tools, lowering the barrier for other laboratories to adopt the framework. The protocol itself is available through protocols.io, and the underlying microfluidic chip design is included with the supplementary materials.

Spatial Hi-C establishes what its developers call a paradigm for investigating spatially resolved chromatin structures within complex tissue microenvironments. By fusing the contact-mapping power of Hi-C with the positional awareness of spatial omics, it transforms the 3D genome from an abstraction studied in dissociated cells into an anatomical object that can be read layer by layer, lobule by lobule, and spot by spot. As the technology matures and resolution improves further, researchers anticipate applying it to human tissue, pathological specimens, and models of neurological disease, where the folding of the genome in its native spatial context may hold keys to understanding how regulatory architecture goes awry.

Subject of Research: Spatially resolved 3D chromatin architecture mapping in mammalian brain tissue using spatial Hi-C

Article Title: Spatially resolved chromatin architectures in mammalian brain tissues

Article References: Chen, Z., Guo, M., Zhang, L., Yu, H., Wang, X., Yu, X., Chen, M., Lv, J., Chen, Z., Peng, C., Gong, Q., Zhang, Q., Guo, R., Huang, Y., Gao, L., Jiang, S., Wang, J., Zhang, Z., Qian, J., … Chen, X. (2026). Spatially resolved chromatin architectures in mammalian brain tissues. Nature Methods. https://doi.org/10.1038/s41592-026-03218-3

Image Credits: AI Generated

DOI: 10.1038/s41592-026-03218-3

Keywords: spatial Hi-C, 3D genome, chromatin architecture, mouse brain, cerebellum, cortex, spatial transcriptomics, topologically associating domains, A/B compartments, neuronal development, microfluidics, Nature Methods