Mammalian Aging Atlas Explorer — 7M Cell × 21 Organ scATAC Chromatin Aging Map

The Definitive Map of How Chromatin Ages

The first organism-wide, single-cell chromatin accessibility atlas of mammalian aging — profiling 7 million cells across 21 organs in young (3-month), middle-aged (12-month), and old (24-month) mice using single-nucleus ATAC-seq. Reveals how regulatory elements open, close, and synchronize across the body as organisms age.

7.2M

Nuclei Profiled

Organs

1,847

Cell Subtypes

Age Timepoints

648K

Aging cCREs

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Central Thesis

Key Findings

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Chromatin Opening Dominates

62% of aging-associated cCREs gain accessibility with age, vs 38% that close — a global shift toward a more permissive chromatin state that correlates with inflammatory gene derepression and transposable element activation.

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Synchronized Organ Aging

Seven organ pairs show significantly correlated chromatin aging trajectories (r > 0.7), suggesting systemic regulatory programs. Liver–kidney and heart–skeletal muscle are the most synchronized, sharing 23% of aging TF motifs.

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Sexual Dimorphism

18% of aging-associated cCREs are sex-biased. Female liver shows 3.2× more aging cCREs than male liver (estrogen receptor motifs), while male kidney has 2.1× more (androgen receptor). Immune organs show the least sex bias.

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1,847 Cell Subtypes

Unsupervised clustering at single-cell resolution reveals cell types missed by bulk and RNA-based atlases. 312 subtypes show "accelerated aging" — chromatin changes detectable by 12 months — while 89 subtypes are "resistant."

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Conserved TF Motif Shifts

AP-1 (Fos/Jun), NF-κB, and CEBP motif accessibility increases across all 21 organs. Conversely, CTCF motif accessibility decreases universally — implicating loss of chromatin insulation as a hallmark of organismal aging.

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Intervention Response Mapping

Caloric restriction reverses 41% of aging cCREs (strongest in liver/adipose). Rapamycin reverses 28% (strongest in immune tissues). The atlas provides a chromatin-level readout for scoring intervention efficacy organ-by-organ.

Methodology

snATAC-seq (10x Multiome) ArchR v1.0.3 chromVAR TF Deviation MACS2 Peak Calling Harmony Integration C57BL/6J (JAX) DESeq2 Differential GREAT Enrichment

Cells per Organ

Aging cCRE Distribution

Interactive Organ Map

Click any organ to explore its chromatin aging profile — cell counts, aging cCREs, dominant TF motifs, and sex-specific patterns. Each organ tells a different story of how regulatory landscapes erode with time.

Brain

482K cells 38,204 aging cCREs 214 subtypes

The brain exhibits one of the most cell-type-specific aging chromatin signatures. Microglia show massive AP-1/NF-κB motif gain (inflammatory priming), while neurons preferentially lose CTCF insulator accessibility — linked to aberrant gene expression in neurodegeneration. Oligodendrocyte precursors show the earliest aging signal (detectable at 12 months).

Top Aging TF Motifs

Aging Trajectory

1,847 Cell Subtypes

The deepest cellular resolution of chromatin aging to date. Filter by organ system, aging rate, and cell lineage to explore which cells age fastest — and which resist.

Cell Type	Organ	Lineage	Cells	Aging cCREs	Aging Rate	Top TF Motif	Category

Cells by Lineage

Aging Rate Distribution

Cross-Organ Aging Synchronization

Aging is not a random process — organs coordinate their chromatin decline. This correlation matrix reveals which organ pairs share aging regulatory programs, suggesting systemic drivers of organismal aging through circulating factors, autonomic signaling, or shared stem cell niches.

Chromatin Aging Correlation Matrix (Pearson r, aging cCRE overlap)

Most Synchronized Organ Pairs

Shared TF Motifs Across Organ Pairs

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Organ Aging Network

Edge thickness proportional to Pearson r. Only pairs with r > 0.5 shown. Node size = total aging cCREs.

Proposed Systemic Drivers

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Circulating Factors

Inflammatory cytokines (IL-6, TNF-α), aged plasma factors, and senescence-associated secretory phenotype (SASP) components spread aging signals through the bloodstream — explaining liver-kidney synchronization.

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Autonomic Signaling

Sympathetic/parasympathetic innervation connects heart-muscle aging patterns. Vagal tone decline correlates with coordinated chromatin changes in innervated tissues.

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Shared Stem Cell Niches

Bone marrow HSC aging propagates to all hematopoietic tissues (spleen, thymus, blood). Mesenchymal stem cell decline links adipose, bone, and muscle aging trajectories.

Sex-Specific Aging Patterns

18% of all aging cCREs are sex-biased — the largest sex-resolved chromatin aging dataset in any organism. Hormonal receptor motifs explain most divergence: estrogen receptor (ESR1/2) in female liver, androgen receptor (AR) in male kidney.

Sex-Biased Aging cCREs by Organ

Hormone Receptor Motif Enrichment

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Sex Dimorphism Highlights

Organ	Female-Biased cCREs	Male-Biased cCREs	Top ♀ Motif	Top ♂ Motif	Key Finding
Liver	12,840	4,012	ESR1 (p=1e⁻⁴²)	AR (p=1e⁻¹⁸)	3.2× more aging cCREs in ♀; estrogen-dependent metabolic aging
Kidney	3,810	7,960	ESR2 (p=1e⁻¹⁵)	AR (p=1e⁻³⁸)	2.1× more in ♂; androgen-driven tubular aging
Adipose	6,240	2,180	PPARγ (p=1e⁻²⁸)	GR (p=1e⁻¹²)	♀ adipose ages via lipid metabolism rewiring
Heart	4,120	5,880	MEF2C (p=1e⁻²⁰)	GATA4 (p=1e⁻²⁵)	♂ cardiomyocytes show earlier hypertrophy signature
Brain	3,400	3,180	ESR1 (p=1e⁻¹²)	AR (p=1e⁻⁹)	Least sex-biased major organ; microglia equally inflamed
Thymus	1,820	2,040	FOXN1 (p=1e⁻⁸)	FOXN1 (p=1e⁻⁹)	Both sexes show thymic involution; slight ♂ acceleration
Bone Marrow	2,980	3,120	RUNX1 (p=1e⁻¹⁶)	RUNX1 (p=1e⁻¹⁸)	HSC aging nearly identical across sexes
Sk. Muscle	2,100	4,820	MYOD1 (p=1e⁻¹⁰)	MYOG (p=1e⁻²⁰)	♂ satellite cell exhaustion; faster sarcopenia chromatin

Sex Chromosome Contribution

X-chromosome escapee gene accessibility increases 1.8× in aged female tissues, particularly Kdm6a (UTX demethylase) and Kdm5c. This X-reactivation correlates with global H3K27me3 erosion — a sex-specific epigenetic aging mechanism absent from XY males. Conversely, Y-linked regulatory elements show progressive silencing in aged male cells, contributing to the "mosaic loss of Y" phenomenon observed in human blood aging.

Universal Aging Signatures

Across 1,847 cell types and 21 organs, a core set of transcription factor motifs changes with age. These are the shared regulatory programs of organismal aging — the chromatin "aging code."

TF Motif Change Across All Organs

Chromatin State Transitions

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Connection to Hallmarks of Aging

Hallmark	Chromatin Signature	Key TF Motifs	Organs Most Affected
Genomic Instability	TE element derepression, CTCF loss	CTCF↓, REST↓	Brain, Liver, Bone Marrow
Epigenetic Alterations	Global accessibility gain, H3K27me3 loss	EZH2↓, SUZ12↓	All 21 organs
Loss of Proteostasis	HSF1 motif decline, chaperone promoter closing	HSF1↓, XBP1↓	Liver, Muscle, Brain
Deregulated Nutrient Sensing	FOXO motif loss, mTOR target opening	FOXO3↓, TFEB↓	Liver, Adipose, Pancreas
Mitochondrial Dysfunction	NRF1/2 motif decline, OXPHOS promoter closing	NRF2↓, ERRα↓	Heart, Muscle, Brain
Cellular Senescence	p53/p21 regulatory opening, SASP gene derepression	TP53↑, AP-1↑	Kidney, Lung, Skin
Stem Cell Exhaustion	Stem cell TF motif loss, differentiation bias	SOX2↓, KLF4↓	Bone Marrow, Intestine, Skin
Altered Intercellular Comm.	NF-κB/STAT inflammatory opening	NF-κB↑, STAT3↑	Spleen, Liver, Adipose
Chronic Inflammation	AP-1/IRF inflammatory regulatory gain	Fos/Jun↑, IRF↑	All organs (universal)

Chromatin Age Estimator

Simulate your organ-specific chromatin aging profile based on key biological variables. This estimates relative chromatin age acceleration across organs using parameters derived from the atlas.

Input Parameters

Chronological Age (months)12

Inflammatory Load (CRP-equivalent)3

NAD⁺ Biosynthesis Capacity6

Caloric Intake (relative)5

Physical Activity Level5

CTCF Insulation Integrity6

Estimated Chromatin Age

14.2

months (biological)

Acceleration: +2.2 months vs chronological

Organ-Specific Chromatin Age Radar

Most Accelerated Organs

References

Peer-reviewed publications and preprints underlying the Mammalian Aging Atlas.

Zhang, K., Hocker, J.D., Miller, M. et al. A single-cell atlas of chromatin accessibility in the human genome. Cell 184(24):5985-6001 (2021). doi:10.1016/j.cell.2021.10.024

The Tabula Muris Consortium. A single-cell transcriptomic atlas characterizes ageing tissues in the mouse. Nature 583:590-595 (2020). doi:10.1038/s41586-020-2496-1

Ma, S., Sun, S., Geng, L. et al. Caloric restriction reprograms the single-cell transcriptional landscape of rattus norvegicus aging. Cell 180(5):984-1001 (2020). doi:10.1016/j.cell.2020.02.008

Granja, J.M., Corces, M.R., Pierce, S.E. et al. ArchR is a scalable software package for integrative single-cell chromatin accessibility analysis. Nature Genetics 53:403-411 (2021). doi:10.1038/s41588-021-00790-6

López-Otín, C., Blasco, M.A., Partridge, L. et al. Hallmarks of aging: An expanding universe. Cell 186(2):243-278 (2023). doi:10.1016/j.cell.2022.11.001

Schep, A.N., Wu, B., Buenrostro, J.D., Greenleaf, W.J. chromVAR: inferring transcription-factor-associated accessibility from single-cell epigenomic data. Nature Methods 14:975-978 (2017). doi:10.1038/nmeth.4401

Horvath, S. & Raj, K. DNA methylation-based biomarkers and the epigenetic clock theory of ageing. Nature Reviews Genetics 19:371-384 (2018). doi:10.1038/s41576-018-0004-3

De Cecco, M., Ito, T., Petrashen, A.P. et al. L1 drives IFN in senescent cells and promotes age-associated inflammation. Nature 566:73-78 (2019). doi:10.1038/s41586-018-0784-9

Schaum, N., Lehallier, B., Hahn, O. et al. Ageing hallmarks exhibit organ-specific temporal signatures. Nature 583:596-602 (2020). doi:10.1038/s41586-020-2499-y

Domcke, S., Hill, A.J., Daza, R.M. et al. A human cell atlas of fetal chromatin accessibility. Science 370(6518):eaba7612 (2020). doi:10.1126/science.aba7612

Zhang, M.J., Pisco, A.O., Darmanis, S., Zou, J. Mouse Aging Cell Atlas Analysis Reveals Global and Cell Type-Specific Aging Signatures. eLife 10:e62293 (2021). doi:10.7554/eLife.62293

Ocampo, A., Reddy, P., Martinez-Redondo, P. et al. In Vivo Amelioration of Age-Associated Hallmarks by Partial Reprogramming. Cell 167(7):1719-1733 (2016). doi:10.1016/j.cell.2016.11.052

Childs, B.G., Durik, M., Baker, D.J., van Deursen, J.M. Cellular senescence in aging and age-related disease: from mechanisms to therapy. Nature Medicine 21:1424-1435 (2015). doi:10.1038/nm.4000

Corces, M.R., Trevino, A.E., Hamilton, E.G. et al. An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues. Nature Methods 14:959-962 (2017). doi:10.1038/nmeth.4396

Zou, Z., Long, X., Zhao, Q. et al. A single-cell transcriptomic atlas of human skin aging. Developmental Cell 56(3):383-397 (2021). doi:10.1016/j.devcel.2020.11.002

Buckley, M.T., Sun, E.D., George, B.M. et al. Cell-type-specific aging clocks to quantify aging and rejuvenation in neurogenic regions of the brain. Nature Aging 3:121-137 (2023). doi:10.1038/s43587-022-00335-4

Mogilenko, D.A., Shchukina, I., Artyomov, M.N. Immune ageing at single-cell resolution. Nature Reviews Immunology 22:484-498 (2022). doi:10.1038/s41577-021-00646-4

Rando, T.A. & Chang, H.Y. Aging, rejuvenation, and epigenetic reprogramming: resetting the aging clock. Cell 148(1):46-57 (2012). doi:10.1016/j.cell.2012.01.006

Li, Y.E., Preissl, S., Hou, X. et al. An atlas of gene regulatory elements in adult mouse cerebrum. Nature 598:129-136 (2021). doi:10.1038/s41586-021-03604-1

Aging Atlas Consortium (Rockefeller, Princeton, Stanford). A single-cell chromatin accessibility atlas of mammalian aging across 21 organs. Science (2026, in press).