Cell-type-specific transposon demethylation and TAD remodeling in aging mouse brain

Qiurui Zeng; Wenliang Wang; Wei Tian; Amit Klein; Anna Bartlett; Hanqing Liu; Joseph R Nery; Rosa G Castanon; Julia Osteen; Nicholas D Johnson; Wubin Ding; Huaming Chen; Jordan Altshul; Mia Kenworthy; Cynthia Valadon; William Owens; Zhanghao Wu; Maria Luisa Amaral; Nathan R Zemke; Yuru Song; Cindy Tatiana Báez-Becerra; Silvia Cho; Chumo Chen; Jackson Willier; Stella Cao; Jonathan Rink; Jasper Lee; Ariana Barcoma; Jessica Arzavala; Nora Emerson; Yuancheng Ryan Lu; Bing Ren; M Margarita Behrens; Joseph R Ecker

doi:10.1016/j.cell.2026.02.015

Cell-type-specific transposon demethylation and TAD remodeling in aging mouse brain

Cell. 2026 Apr 2;189(7):2148-2166.e27. doi: 10.1016/j.cell.2026.02.015. Epub 2026 Mar 11.

Authors

Qiurui Zeng¹, Wenliang Wang², Wei Tian², Amit Klein³, Anna Bartlett², Hanqing Liu⁴, Joseph R Nery², Rosa G Castanon², Julia Osteen⁵, Nicholas D Johnson⁵, Wubin Ding², Huaming Chen², Jordan Altshul², Mia Kenworthy², Cynthia Valadon², William Owens², Zhanghao Wu⁶, Maria Luisa Amaral⁷, Nathan R Zemke⁸, Yuru Song⁹, Cindy Tatiana Báez-Becerra⁵, Silvia Cho⁵, Chumo Chen², Jackson Willier⁵, Stella Cao⁵, Jonathan Rink⁵, Jasper Lee⁵, Ariana Barcoma⁵, Jessica Arzavala⁵, Nora Emerson⁵, Yuancheng Ryan Lu¹⁰, Bing Ren¹¹, M Margarita Behrens¹², Joseph R Ecker¹³

Affiliations

¹ Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA; Division of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA.
² Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA.
³ Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA; Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA 92093, USA.
⁴ Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA; Junior Fellow, Faculty of Arts and Sciences, Harvard University, Cambridge, MA 02138, USA.
⁵ Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA.
⁶ Sky Computing Lab, University of California, Berkeley, Berkeley, CA 94709, USA.
⁷ Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA 92093, USA; Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA 92093, USA.
⁸ Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA 92093, USA; Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA 92093, USA.
⁹ Neurosciences Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA.
¹⁰ Whitehead Institute for Biomedical Research, Cambridge, MA 02138, USA.
¹¹ Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA 92093, USA; New York Genome Center, 101 Avenue of the Americas, New York, NY 10013, USA; Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, 701 W 168th Street, New York, NY 10032, USA.
¹² Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA. Electronic address: mbehrens@salk.edu.
¹³ Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA; Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA. Electronic address: ecker@salk.edu.

Abstract

Aging is a major risk factor for neurodegenerative diseases, yet the underlying epigenetic mechanisms remain unclear. Here, we generated a comprehensive single-nucleus cell atlas of brain aging across multiple brain regions, comprising 132,551 single-cell methylomes and 72,666 joint chromatin conformation-methylome nuclei. Integration with companion transcriptomic and chromatin accessibility data yielded a cross-modality taxonomy of 36 major cell types. We observed that transposable element (TE) methylation alone distinguished age groups, showing cell-type-specific genome-wide demethylation. Chromatin conformation analysis demonstrated age-related increases in topologically associated domain (TAD) boundary strength with enhanced accessibility at CCCTC-binding factor (CTCF) binding sites. Spatial transcriptomics across 895,296 cells revealed regional heterogeneity during aging within identical cell types. Finally, we developed deep-learning models that reliably predict age-related gene expression changes using multi-modal epigenetic features, providing mechanistic insights into gene regulation. Age-related comparisons use a 2-month baseline reflecting the late-adolescent/early-young adult stage. This dataset advances our understanding of brain aging and offers potential translational applications.

Keywords: 3D genome; DNA methylation; brain aging; deep learning; multi-omic; neurons and glias; single-cell; spatial transcriptome; topologically associating domains; transposable elements.

MeSH terms

Aging* / genetics
Animals
Brain* / metabolism
Chromatin / metabolism
Chromatin Assembly and Disassembly*
DNA Methylation / genetics
DNA Transposable Elements* / genetics
Demethylation
Epigenesis, Genetic
Female
Male
Mice
Mice, Inbred C57BL
Single-Cell Analysis
Transcriptome / genetics

Substances

DNA Transposable Elements
Chromatin

Grants and funding

R01 AG066018/AG/NIA NIH HHS/United States