Spatial multi-omics reveals cell-type-specific nuclear compartments
Creators
Abstract
The mammalian nucleus is compartmentalized by diverse subnuclear structures. These subnuclear structures, marked by nuclear bodies and histone modifications, are often cell-type specific and affect gene regulation and 3D genome organization¹, ², ³. Understanding their relationships rests on identifying the molecular constituents of subnuclear structures and mapping their associations with specific genomic loci and transcriptional levels in individual cells, all in complex tissues. Here, we introduce two-layer DNA seqFISH+, which enables simultaneous mapping of 100,049 genomic loci, together with the nascent transcriptome for 17,856 genes and subnuclear structures in single cells. These data enable imaging-based chromatin profiling of diverse subnuclear markers and can capture their changes at genomic scales ranging from 100–200 kilobases to approximately 1 megabase, depending on the marker and DNA locus. By using multi-omics datasets in the adult mouse cerebellum, we showed that repressive chromatin regions are more variable by cell type than are active regions across the genome. We also discovered that RNA polymerase II-enriched foci were locally associated with long, cell-type-specific genes (bigger than 200 kilobases) in a manner distinct from that of nuclear speckles. Furthermore, our analysis revealed that cell-type-specific regions of heterochromatin marked by histone H3 trimethylated at lysine 27 (H3K27me3) and histone H4 trimethylated at lysine 20 (H4K20me3) are enriched at specific genes and gene clusters, respectively, and shape radial chromosomal positioning and inter-chromosomal interactions in neurons and glial cells. Together, our results provide a single-cell high-resolution multi-omics view of subnuclear structures, associated genomic loci and their effects on gene regulation, directly within complex tissues.
Copyright and License (English)
© 2025, The Author(s), under exclusive licence to Springer Nature Limited.
Acknowledgement (English)
We thank I. Strazhnik for help with the figures; I. Carmi and M. Elowitz for help with the manuscript; C. H. Tischbirek, S. Shah and C.-H. L. Eng for discussion; C. Karp, C. Cronin and A. Cronin for help with the automated imaging set-up; F. Gao for processing published sequencing data; I. A. Antoshechkin for the sequencing run; S. Peiró and M. A. Marti-Renom for sharing processed Hi-C data on NMuMG cells; P. Kaufman for sharing processed NAD-seq data on mESCs; and N. J. Rezaee and A. Cunha for help with cell segmentation. Y.T. was supported by the JST Presto grant, JPMJPR22E7, and the Riva Foundation Fellowship. This project was funded by NIH U01DK127420 and the Allen Discovery Center.
Data Availability
Data from this study are available at Zenodo at https://doi.org/10.5281/zenodo.7693825 (ref. 135) and NCBI GEO (accession GSE248631). More processed data and experimental resources (for example, probe sequences) from this study are available at GitHub (https://github.com/CaiGroup/dna-seqfish-plus-multi-omics). The raw microscopy data have not been uploaded owing to their large size (6.8 Tb) but are available from the corresponding authors upon reasonable request. Publicly available datasets used in this study (GSE98674, GSE96033, GSE48895, GSE166210, GSE181693, GSE17051, GSE165371, GSE151515, GSE71585, 4DNESL2AY9CM and https://doi.org/10.5281/zenodo.4708112 (ref. 136)) are detailed in the Methods. The chromosomal DNA binding probe sequences were obtained from mm10 newBalance DNA FISH probes at PaintSHOP resources (https://github.com/beliveau-lab/PaintSHOP_resources).
Code Availability
The custom scripts used in this study are available at GitHub (https://github.com/CaiGroup/dna-seqfish-plus-multi-omics).
Conflict of Interest
L.C. is a co-founder of Spatial Genomics. Y.T. and L.C. have filed a patent on the two-layer seqFISH+ barcoding.
Additional details
Related works
- Describes
- Journal Article: https://rdcu.be/ewmTf (ReadCube)
Funding
- Japan Science and Technology Agency
- PRESTO JPMJPR22E7
- National Institutes of Health
- U01DK127420
Dates
- Available
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2025-04-09Published online