Spatial epigenome-transcriptome co-profiling of mammalian tissues

  • Nature. 2023 Apr;616(7955):113-122. doi: 10.1038/s41586-023-05795-1.
Di Zhang  #  1 ,  Yanxiang Deng  #  2  3  4 ,  Petra Kukanja  5 ,  Eneritz Agirre  5 ,  Marek Bartosovic  5 ,  Mingze Dong  6  7 ,  Cong Ma  8 ,  Sai Ma  9 ,  Graham Su  1  10 ,  Shuozhen Bao  1 ,  Yang Liu  1  10 ,  Yang Xiao  11 ,  Gorazd B Rosoklija  12  13  14 ,  Andrew J Dwork  12  13  14  15 ,  J John Mann  12  13  16 ,  Kam W Leong  11  17 ,  Maura Boldrini  12  13 ,  Liya Wang  18 ,  Maximilian Haeussler  19 ,  Benjamin J Raphael  8 ,  Yuval Kluger  6  7  20 ,  Gonçalo Castelo-Branco  21  22 ,  Rong Fan  23  24  25  26
Affiliations
  • 1. Department of Biomedical Engineering, Yale University, New Haven, CT, USA.
  • 2. Department of Biomedical Engineering, Yale University, New Haven, CT, USA. [email protected].
  • 3. Yale Stem Cell Center and Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA. [email protected].
  • 4. Department of Pathology and Laboratory Medicine, Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. [email protected].
  • 5. Laboratory of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden.
  • 6. Department of Pathology, Yale University School of Medicine, New Haven, CT, USA.
  • 7. Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA.
  • 8. Department of Computer Science, Princeton University, Princeton, NJ, USA.
  • 9. Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • 10. Yale Stem Cell Center and Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA.
  • 11. Department of Biomedical Engineering, Columbia University, New York, NY, USA.
  • 12. Department of Psychiatry, Columbia University, New York, NY, USA.
  • 13. Division of Molecular Imaging and Neuropathology, New York State Psychiatric Institute, New York, NY, USA.
  • 14. Macedonian Academy of Sciences & Arts, Skopje, Republic of Macedonia.
  • 15. Department of Pathology and Cell Biology, Columbia University, New York, NY, USA.
  • 16. Department of Radiology, Columbia University, New York, NY, USA.
  • 17. Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA.
  • 18. AtlasXomics, Inc., New Haven, CT, USA.
  • 19. Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA.
  • 20. Applied Mathematics Program, Yale University, New Haven, CT, USA.
  • 21. Laboratory of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden. [email protected].
  • 22. Ming Wai Lau Centre for Reparative Medicine, Stockholm Node, Karolinska Institutet, Stockholm, Sweden. [email protected].
  • 23. Department of Biomedical Engineering, Yale University, New Haven, CT, USA. [email protected].
  • 24. Yale Stem Cell Center and Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA. [email protected].
  • 25. Department of Pathology, Yale University School of Medicine, New Haven, CT, USA. [email protected].
  • 26. Human and Translational Immunology Program, Yale School of Medicine, New Haven, CT, USA. [email protected].
  • # Contributed equally.
PMID: 36922587 DOI: 10.1038/s41586-023-05795-1
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.