Author
Listed:
- Di Zhang
(Yale University)
- Yanxiang Deng
(Yale University
Yale School of Medicine
University of Pennsylvania)
- Petra Kukanja
(Karolinska Institutet)
- Eneritz Agirre
(Karolinska Institutet)
- Marek Bartosovic
(Karolinska Institutet)
- Mingze Dong
(Yale University School of Medicine
Yale University)
- Cong Ma
(Princeton University)
- Sai Ma
(Broad Institute of MIT and Harvard)
- Graham Su
(Yale University
Yale School of Medicine)
- Shuozhen Bao
(Yale University)
- Yang Liu
(Yale University
Yale School of Medicine)
- Yang Xiao
(Columbia University)
- Gorazd B. Rosoklija
(Columbia University
New York State Psychiatric Institute
Macedonian Academy of Sciences & Arts)
- Andrew J. Dwork
(Columbia University
New York State Psychiatric Institute
Macedonian Academy of Sciences & Arts
Columbia University)
- J. John Mann
(Columbia University
New York State Psychiatric Institute
Columbia University)
- Kam W. Leong
(Columbia University
Columbia University Irving Medical Center)
- Maura Boldrini
(Columbia University
New York State Psychiatric Institute)
- Liya Wang
(AtlasXomics, Inc.)
- Maximilian Haeussler
(University of California Santa Cruz)
- Benjamin J. Raphael
(Princeton University)
- Yuval Kluger
(Yale University School of Medicine
Yale University
Yale University)
- Gonçalo Castelo-Branco
(Karolinska Institutet
Karolinska Institutet)
- Rong Fan
(Yale University
Yale School of Medicine
Yale University School of Medicine
Yale School of Medicine)
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.
Suggested Citation
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 , 2023.
"Spatial epigenome–transcriptome co-profiling of mammalian tissues,"
Nature, Nature, vol. 616(7955), pages 113-122, April.
Handle:
RePEc:nat:nature:v:616:y:2023:i:7955:d:10.1038_s41586-023-05795-1
DOI: 10.1038/s41586-023-05795-1
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