Abstract
Mammalian brain cells show remarkable diversity in gene expression, anatomy and function, yet the regulatory DNA landscape underlying this extensive heterogeneity is poorly understood. Here we carry out a comprehensive assessment of the epigenomes of mouse brain cell types by applying single-nucleus DNA methylation sequencing1,2 to profile 103,982 nuclei (including 95,815 neurons and 8,167 non-neuronal cells) from 45 regions of the mouse cortex, hippocampus, striatum, pallidum and olfactory areas. We identified 161 cell clusters with distinct spatial locations and projection targets. We constructed taxonomies of these epigenetic types, annotated with signature genes, regulatory elements and transcription factors. These features indicate the potential regulatory landscape supporting the assignment of putative cell types and reveal repetitive usage of regulators in excitatory and inhibitory cells for determining subtypes. The DNA methylation landscape of excitatory neurons in the cortex and hippocampus varied continuously along spatial gradients. Using this deep dataset, we constructed an artificial neural network model that precisely predicts single neuron cell-type identity and brain area spatial location. Integration of high-resolution DNA methylomes with single-nucleus chromatin accessibility data3 enabled prediction of high-confidence enhancer–gene interactions for all identified cell types, which were subsequently validated by cell-type-specific chromatin conformation capture experiments4. By combining multi-omic datasets (DNA methylation, chromatin contacts, and open chromatin) from single nuclei and annotating the regulatory genome of hundreds of cell types in the mouse brain, our DNA methylation atlas establishes the epigenetic basis for neuronal diversity and spatial organization throughout the mouse cerebrum.
Highlights
Epigenomic dynamics are associated with cell differentiation and maturation in the mammalian brain and have an essential role in regulating neuronal functions and animal behaviour5,6
A deeper understanding of epigenomic diversity in the mouse brain provides a complementary approach to transcriptome-based profiling methods for identifying brain cell types and allows genome-wide prediction of the regulatory elements and transcriptional networks
Previous studies have demonstrated the utility of studying brain cell types and regulatory diversity using single-nucleus methylome sequencing1
Summary
To further study cis-regulatory elements and their potential target genes across the genome, we applied single-nucleus methylation and chromosome conformation capture sequencing (sn-m3C-seq) to profile the methylome and chromatin conformation in the same cells These epigenomic datasets provide a detailed and comprehensive census of the diversity of cell types across mouse brain regions, allowing identification of cell-type-specific regulatory elements and their candidate target genes and upstream transcription factors. We show that differentially methylated transcription factor genes and binding motifs can be associated with subtype taxonomy branches, allowing the prediction of cell-type gene regulatory programs specific for each developmental lineage Integration of these data with cell clusters identified on the basis of chromatin accessibility validates most methylome-derived subtypes, enabling the prediction of 1.6 million enhancer-like genomic regions. Branch detail Branch Speci c CH-DMG Subtype taxonomy a Subtype characteristics in methylome
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