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Integrative Single-Cell Epigenomic Atlas Annotates the Regulatory Genome of the Adult Mouse Brain
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Integrative Single-Cell Epigenomic Atlas Annotates the Regulatory Genome of the Adult Mouse Brain

Zhaoning Wang, Songpeng Zu, Ethan J. Armand +24 more
February 2026
 ·
bioRxiv
 ·
DOI 
10.64898/2026.02.07.704075
94
%
Reproducible
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This paper passed independent validation.
QED's automated review checked the evidence supporting each claim, the statistical methods, and whether the results are reproducible from the data provided.

It ranks in the top 1% of preprints assessed in Genomics this quarter.
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Why this is interesting

This atlas of four histone modifications across 2.5 million brain nuclei overturns the sufficiency of open chromatin for enhancer identification, annotates 81% of the brain regulatory genome, and enables sequence-to-function prediction across 100+ neural cell types.

Author perspective

What is the most important insight, discovery, or finding from your paper that you would like other scientists to know?
“

We created detailed molecular maps of individual brain cells that reveal how the genome is turned on and off to produce the remarkable diversity of cell types in the mouse and human brains. Our work shows that gene silencing is an active and informative process, not simply the absence of gene activity, and helps preserve the developmental history and identity of brain cells. These maps also identify the DNA switches and cell types linked to neurological and psychiatric diseases. Finally, we trained artificial intelligence models to predict how DNA sequences control brain function, providing a powerful framework for understanding disease-causing genetic variants and designing future therapies.

”
Bing Ren

QED claims analysis

Summary

Joint profiling of transcription and four histone modifications in 2.5 million mouse brain nuclei, integrated with chromatin accessibility, DNA methylation, and 3D genome organization, functionally annotates 81% of the genome across over 100 brain cell subclasses, revealing that combinatorial active histone marks more precisely identify functional enhancers than chromatin accessibility alone, while Polycomb- and H3K9me3-mediated repression programs contribute prominently to cell-type-specific gene regulation, together establishing a comprehensive regulatory framework that enables accurate sequence-based prediction of epigenomic features and gene expression.

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Main Claim 1 –

Paired-Tag profiles RNA and histone marks in 2.5M nuclei

Supporting evidence

  • Brain cell types show subtle sex-biased epigenomic and transcriptomic patterns
Main Claim 2 –

Integrated multi-modal epigenome atlas resolves cell-type gene regulation

Supporting evidence

  • Polycomb H3K27me3 and H3K9me3 repression shape cell-type regulation
  • Transposable elements act as cell-type-specific enhancer-like regulators
Main Claim 3 –

ChromHMM chromatin states functionally annotate 81% of brain genome

Supporting evidence

  • Oligodendrocyte differentiation shows coordinated chromatin-state and expression shifts
Main Claim 4 –

Combinatorial histone marks outperform ATAC in enhancer identification

Abstract

Histone modifications underpin the cell-type-specific gene regulatory networks that drive the remarkable cellular heterogeneity of the adult mammalian brain. Here, we profiled four histone modifications jointly with transcriptome in 2.5 million nuclei across multiple adult mouse brain regions. By integrating these data with existing maps of chromatin accessibility, DNA methylation, and 3D genome organization, we established a unified regulatory framework for over 100 brain cell subclasses. This integrative epigenomic atlas annotates 81% of the genome, defining distinct active, primed, and repressive states. Notably, active chromatin states marked by combinatorial histone modifications more precisely identify functional enhancers than chromatin accessibility alone, while Polycomb- and H3K9me3-mediated repression contributes prominently to cell-type-specific regulation. Finally, this multi-modal resource enables deep learning models to predict epigenomic features and gene expression from DNA sequences. This work provides a comprehensive annotation of the mouse brain regulatory genome and a framework for interpreting non-coding variation in complex tissues.

HIGHLIGHTS

-A single-cell epigenome atlas of transcription and four histone modifications across 2.5M mouse brain cells.

-Multi-modal integration functionally annotates ∼81% of the adult mouse brain regulatory genome

-Cell-type-resolved chromatin landscapes reveal regulatory programs mediated by enhancers, Polycomb and H3K9me3

-Deep learning models predict cell-type-specific epigenomic features and gene expression from DNA sequence

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