Single-cell analysis of chromatin accessibility in the adult mouse brain

Zu, Songpeng; Li, Yang Eric; Wang, Kangli; Armand, Ethan J.; Mamde, Sainath; Amaral, Maria Luisa; Wang, Yuelai; Chu, Andre; Xie, Yang; Miller, Michael; Xu, Jie; Wang, Zhaoning; Zhang, Kai; Jia, Bojing; Hou, Xiaomeng; Lin, Lin; Yang, Qian; Lee, Seoyeon; Li, Bin; Kuan, Samantha; Liu, Hanqing; Zhou, Jingtian; Pinto-Duarte, Antonio; Lucero, Jacinta; Osteen, Julia; Nunn, Michael; Smith, Kimberly A.; Tasic, Bosiljka; Yao, Zizhen; Zeng, Hongkui; Wang, Zihan; Shang, Jingbo; Behrens, M. Margarita; Ecker, Joseph R.; Wang, Allen; Preissl, Sebastian; Ren, Bing

doi:10.1038/s41586-023-06824-9

Cited by 16 publications

(12 citation statements)

References 104 publications

(217 reference statements)

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“…We collected 301,626 methylomes and 176,003 m3C joint profiles from the entire mouse brain to produce a dataset comprising 786 billion methylation reads (snmC-seq3 plus snm3C-seq) and 33 billion cis-long-range chromatin contacts (snm3C-seq). This rich dataset identifies 4,673 cell groups, which aligned well with other BRAIN Initiative Cell Census Network (BICCN) data 6,11 . The methylome clusters were annotated using the nomenclature from companion transcriptomic studies 6 , thereby offering a comprehensive multi-omic resource.…”

supporting

confidence: 72%

“…At the highest level of granularity, we obtained a total of 4,673 cell groups. To validate and annotate the dataset, we integrated the methylome data with other brain-wide chromatin accessibility 11 and transcriptome datasets 6 , which resulted in cluster-level mapping across modalities and annotations of these clusters into 30 class labels and 274 subclass labels shared with a companion transcriptome study 6 (Supplementary Table 4 and see below).…”

Section: Articlementioning

confidence: 99%

“…Our study establishes a brain-wide, single-cell DNA methylome and 3D multi-omic atlas and provides a valuable resource for comprehending the cellularspatial and regulatory genome diversity of the mouse brain.The mouse brain is a complex organ comprising millions of cells that form diverse anatomical structures and cell types [3][4][5][6][7][8] . Advances in single-cell transcriptome and epigenome technologies are revealing the intricate molecular diversity of the mammalian brain, which in turn are offering insights into epigenetic mechanisms central to orchestrating this biological diversity [9][10][11][12][13] .Cytosine DNA methylation (5mC), a covalent genome modification in post-mitotic cells throughout their lifespan 14 , is associated with neuronal function, behaviour and various diseases 15 . Although 5mC predominantly occurs at CpG sites (mCG) in mammalian genomes, non-CpG cytosine methylation (mCH, where H can be A, C or T) is also prevalent in neurons 14,16 .…”

mentioning

confidence: 99%

“…The mouse brain is a complex organ comprising millions of cells that form diverse anatomical structures and cell types [3][4][5][6][7][8] . Advances in single-cell transcriptome and epigenome technologies are revealing the intricate molecular diversity of the mammalian brain, which in turn are offering insights into epigenetic mechanisms central to orchestrating this biological diversity [9][10][11][12][13] .…”

mentioning

confidence: 99%

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Single-cell DNA methylome and 3D multi-omic atlas of the adult mouse brain

Liu,

Zeng,

Zhou

et al. 2023

Nature

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Cytosine DNA methylation is essential in brain development and is implicated in various neurological disorders. Understanding DNA methylation diversity across the entire brain in a spatial context is fundamental for a complete molecular atlas of brain cell types and their gene regulatory landscapes. Here we used single-nucleus methylome sequencing (snmC-seq3) and multi-omic sequencing (snm3C-seq)1 technologies to generate 301,626 methylomes and 176,003 chromatin conformation–methylome joint profiles from 117 dissected regions throughout the adult mouse brain. Using iterative clustering and integrating with companion whole-brain transcriptome and chromatin accessibility datasets, we constructed a methylation-based cell taxonomy with 4,673 cell groups and 274 cross-modality-annotated subclasses. We identified 2.6 million differentially methylated regions across the genome that represent potential gene regulation elements. Notably, we observed spatial cytosine methylation patterns on both genes and regulatory elements in cell types within and across brain regions. Brain-wide spatial transcriptomics data validated the association of spatial epigenetic diversity with transcription and improved the anatomical mapping of our epigenetic datasets. Furthermore, chromatin conformation diversities occurred in important neuronal genes and were highly associated with DNA methylation and transcription changes. Brain-wide cell-type comparisons enabled the construction of regulatory networks that incorporate transcription factors, regulatory elements and their potential downstream gene targets. Finally, intragenic DNA methylation and chromatin conformation patterns predicted alternative gene isoform expression observed in a whole-brain SMART-seq2 dataset. Our study establishes a brain-wide, single-cell DNA methylome and 3D multi-omic atlas and provides a valuable resource for comprehending the cellular–spatial and regulatory genome diversity of the mouse brain.

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supporting

confidence: 72%

Section: Articlementioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Single-cell DNA methylome and 3D multi-omic atlas of the adult mouse brain

Liu,

Zeng,

Zhou

et al. 2023

Nature

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“…Neuroscience spans scales from live animal studies (e.g., electrophysiologists and preclinical MRI @ 0.1 mm 3 to the cellular level e.g The Brain Initiative Cell Census Network (BICCN) at 1 μm 3 35–38 . Regional volume estimates are crucial for preclinical MRI and microPET studies of aging and neurodegeneration.…”

Section: Discussionmentioning

confidence: 99%

An Open Resource: MR and light sheet microscopy stereotaxic atlas of the mouse brain

Mansour,

Azrak,

Cook

et al. 2024

Preprint

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We have combined MR histology and light sheet microscopy (LSM) of five postmortem C57BL/6J mouse brains in a stereotaxic space based on micro-CT yielding a multimodal 3D atlas with the highest spatial and contrast resolution yet reported. Brains were imaged in situ with multi gradient echo (mGRE) and diffusion tensor imaging (DTI) at 15 um resolution (~ 2.4 million times that of clinical MRI). Scalar images derived from the average DTI and mGRE provide unprecedented contrast in 14 complementary 3D volumes, each highlighting distinct histologic features. The same tissues scanned with LSM and registered into the stereotaxic space provide 17 different molecular cell type stains. The common coordinate framework labels (CCFv3) complete the multimodal atlas. The atlas has been used to correct distortions in the Allen Brain Atlas and harmonize it with Franklin Paxinos. It provides a unique resource for stereotaxic labeling of mouse brain images from many sources.

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Deciphering brain cellular and behavioral mechanisms: Insights from single‐cell and spatial RNA sequencing

Chen,

Nie,

Wang

et al. 2024

WIREs RNA

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The brain is a complex computing system composed of a multitude of interacting neurons. The computational outputs of this system determine the behavior and perception of every individual. Each brain cell expresses thousands of genes that dictate the cell's function and physiological properties. Therefore, deciphering the molecular expression of each cell is of great significance for understanding its characteristics and role in brain function. Additionally, the positional information of each cell can provide crucial insights into their involvement in local brain circuits. In this review, we briefly overview the principles of single‐cell RNA sequencing and spatial transcriptomics, the potential issues and challenges in their data processing, and their applications in brain research. We further outline several promising directions in neuroscience that could be integrated with single‐cell RNA sequencing, including neurodevelopment, the identification of novel brain microstructures, cognition and behavior, neuronal cell positioning, molecules and cells related to advanced brain functions, sleep–wake cycles/circadian rhythms, and computational modeling of brain function. We believe that the deep integration of these directions with single‐cell and spatial RNA sequencing can contribute significantly to understanding the roles of individual cells or cell types in these specific functions, thereby making important contributions to addressing critical questions in those fields.This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA in Disease and Development > RNA in Development RNA in Disease and Development > RNA in Disease

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Single-cell analysis of chromatin accessibility in the adult mouse brain

Cited by 16 publications

References 104 publications

Single-cell DNA methylome and 3D multi-omic atlas of the adult mouse brain

Single-cell DNA methylome and 3D multi-omic atlas of the adult mouse brain

An Open Resource: MR and light sheet microscopy stereotaxic atlas of the mouse brain

Deciphering brain cellular and behavioral mechanisms: Insights from single‐cell and spatial RNA sequencing

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