bioRxivGenomicsPreprint
An Integrative Single-Cell Epigenomic Atlas Annotates the Regulatory Genome of the Adult Mouse Brain
Zhaoning WangiD, Songpeng ZuiD, Ethan J. ArmandiD, Timothy H. Loe, Jonathan A. RinkiD, Wanying WuiD, Yang XieiD, Lei ChangiD, Chenxu ZhuiD, Nicholas D. JohnsoniD, Jasper LeeiD, Jackson K. Willier, Silvia ChoiD, Stella Maris Cao, Ariana S. BarcomaiD, Nora EmersoniD, Hanqing LiuiD, Kangli WangiD, Bharath SaravananiD, Zane A. GibbsiD, Xiaomeng GaoiD, Sunan XuiD, David GuoiD, Zhuowen TuiD, Yang Eric LiiD, , Bing ReniD
Abstract
Histone modifications underpin the cell-type-specific gene regulatory programs that drive the remarkable cellular diversity of the mammalian brain. Here, we jointly profiled four histone modifications and the transcriptome in 2.5 million nuclei from the adult mouse brain. By integrating these data with chromatin accessibility, DNA methylation, and three-dimensional genome organization, we constructed a unified epigenomic atlas spanning over 100 brain cell subclasses, and assigned active, primed, and repressive chromatin states across 81% of the genome. Active chromatin states marked by combinatorial histone modifications better nominate candidate enhancers with functional support than chromatin accessibility alone, while H3K27me3- and H3K9me3-marked chromatin states delineate distinct modes of cell-type-specific gene repression. Finally, this multimodal resource enables deep learning models that predict cell-type-specific epigenomic features and gene expression from DNA sequence, providing a comprehensive framework for annotating the brain regulatory genome and interpreting non-coding disease risk variants. HIGHLIGHTS- A single-cell epigenome atlas of transcription and four histone modifications across 2.5M mouse brain cells - Multimodal integration maps chromatin states across [~]81% of the adult mouse brain 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
- organism: mouse
- assay: scATAC-seq
- assay: scRNA-seq
- assay: DNA methylation
- assay: Hi-C
- research focus: cell type annotation
- research focus: gene regulatory network inference
- research focus: benchmarking
- research focus: database / resource
- approach: deep learning
- approach: statistical model
- approach: matrix factorization
- Citations
- 0
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Single-Cell Atlas of Transcription and Chromatin States Reveals Regulatory Programs in the Human Brain
- DNA Methylation Atlas of the Mouse Brain at Single-Cell Resolution
Hanqing Liu, Jingtian Zhou, … Joseph R. Ecker·NaturePeer-reviewed·Oct 6, 2021
- Epigenomic complexity of the human brain revealed by single-cell DNA methylomes and 3D genome structures
Wei Tian, Jingtian Zhou, … Joseph R. Ecker·bioRxiv·Nov 30, 2022
- Single-cell DNA Methylome and 3D Multi-omic Atlas of the Adult Mouse Brain
Hanqing Liu, Qiurui Zeng, … Joseph R. Ecker·NaturePeer-reviewed·Dec 13, 2023
- Single-cell profiling of histone modifications in the mouse brain
Marek Bartošovič, Mukund Kabbe, Gonçalo Castelo‐Branco·bioRxiv·Sep 2, 2020
- Systematic mapping of chromatin state landscapes during mouse development
David U. Gorkin, Iros Barozzi, … Bing Ren·NaturePeer-reviewed·Jul 29, 2020