Spatial epigenome–transcriptome co-profiling of mammalian tissues

Di Zhang, Yanxiang Deng (), Petra Kukanja, Eneritz Agirre, Marek Bartosovic, Mingze Dong, Cong Ma, Sai Ma, Graham Su, Shuozhen Bao, Yang Liu, Yang Xiao, Gorazd B. Rosoklija, Andrew J. Dwork, J. John Mann, Kam W. Leong, Maura Boldrini, Liya Wang, Maximilian Haeussler, Benjamin J. Raphael, Yuval Kluger, Gonçalo Castelo-Branco () and Rong Fan ()
Additional contact information
Di Zhang: Yale University
Yanxiang Deng: Yale University
Petra Kukanja: Karolinska Institutet
Eneritz Agirre: Karolinska Institutet
Marek Bartosovic: Karolinska Institutet
Mingze Dong: Yale University School of Medicine
Cong Ma: Princeton University
Sai Ma: Broad Institute of MIT and Harvard
Graham Su: Yale University
Shuozhen Bao: Yale University
Yang Liu: Yale University
Yang Xiao: Columbia University
Gorazd B. Rosoklija: Columbia University
Andrew J. Dwork: Columbia University
J. John Mann: Columbia University
Kam W. Leong: Columbia University
Maura Boldrini: Columbia University
Liya Wang: AtlasXomics, Inc.
Maximilian Haeussler: University of California Santa Cruz
Benjamin J. Raphael: Princeton University
Yuval Kluger: Yale University School of Medicine
Gonçalo Castelo-Branco: Karolinska Institutet
Rong Fan: Yale University

Nature, 2023, vol. 616, issue 7955, 113-122

Abstract: Abstract Emerging spatial technologies, including spatial transcriptomics and spatial epigenomics, are becoming powerful tools for profiling of cellular states in the tissue context1–5. However, current methods capture only one layer of omics information at a time, precluding the possibility of examining the mechanistic relationship across the central dogma of molecular biology. Here, we present two technologies for spatially resolved, genome-wide, joint profiling of the epigenome and transcriptome by cosequencing chromatin accessibility and gene expression, or histone modifications (H3K27me3, H3K27ac or H3K4me3) and gene expression on the same tissue section at near-single-cell resolution. These were applied to embryonic and juvenile mouse brain, as well as adult human brain, to map how epigenetic mechanisms control transcriptional phenotype and cell dynamics in tissue. Although highly concordant tissue features were identified by either spatial epigenome or spatial transcriptome we also observed distinct patterns, suggesting their differential roles in defining cell states. Linking epigenome to transcriptome pixel by pixel allows the uncovering of new insights in spatial epigenetic priming, differentiation and gene regulation within the tissue architecture. These technologies are of great interest in life science and biomedical research.

Date: 2023
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DOI: 10.1038/s41586-023-05795-1

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