Delineating the gene-regulatory programs underlying complex cell types is fundamental for understanding brain function in health and disease. Here, we comprehensively examined human brain cell epigenomes by probing DNA methylation and chromatin conformation at single-cell resolution in 517 thousand cells (399 thousand neurons and 118 thousand non-neurons) from 46 regions of three adult male brains. We identified 188 cell types and characterized their molecular signatures. Integrative analyses revealed concordant changes in DNA methylation, chromatin accessibility, chromatin organization, and gene expression across cell types, cortical areas, and basal ganglia structures. We further developed single-cell methylation barcodes that reliably predict brain cell types using the methylation status of select genomic sites. This multimodal epigenomic brain cell atlas provides new insights into the complexity of cell-type–specific gene regulation in adult human brains.

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)¹technologies 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-seq²dataset. 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.

Single-cell analyses parse the brain’s billions of neurons into thousands of ‘cell-type’ clusters residing in different brain structures¹. Many cell types mediate their functions through targeted long-distance projections allowing interactions between specific cell types. Here we used epi-retro-seq² to link single-cell epigenomes and cell types to long-distance projections for 33,034 neurons dissected from 32 different regions projecting to 24 different targets (225 source-to-target combinations) across the whole mouse brain. We highlight uses of these data for interrogating principles relating projection types to transcriptomics and epigenomics, and for addressing hypotheses about cell types and connections related to genetics. We provide an overall synthesis with 926 statistical comparisons of discriminability of neurons projecting to each target for every source. We integrate this dataset into the larger BRAIN Initiative Cell Census Network atlas, composed of millions of neurons, to link projection cell types to consensus clusters. Integration with spatial transcriptomics further assigns projection-enriched clusters to smaller source regions than the original dissections. We exemplify this by presenting in-depth analyses of projection neurons from the hypothalamus, thalamus, hindbrain, amygdala and midbrain to provide insights into properties of those cell types, including differentially expressed genes, their associated cis-regulatory elements and transcription-factor-binding motifs, and neurotransmitter use.

Cytosine DNA methylation is essential in brain development and has been implicated in various neurological disorders. A comprehensive understanding of DNA methylation diversity across the entire brain in the context of the brain’s 3D spatial organization is essential for building a complete molecular atlas of brain cell types and understanding their gene regulatory landscapes. To this end, we employed optimized single-nucleus methylome (snmC-seq3) and multi-omic (snm3C-seq ¹ ) sequencing 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 type taxonomy that contains 4,673 cell groups and 261 cross-modality-annotated subclasses. We identified millions of differentially methylated regions (DMRs) across the genome, representing 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 multiplexed error-robust fluorescence in situ hybridization (MERFISH ² ) data validated the association of this spatial epigenetic diversity with transcription and allowed the mapping of the DNA methylation and topology information into anatomical structures more precisely than our dissections. Furthermore, multi-scale chromatin conformation diversities occur in important neuronal genes, highly associated with DNA methylation and transcription changes. Brain-wide cell type comparison allowed us to build a regulatory model for each gene, linking transcription factors, DMRs, chromatin contacts, and downstream genes to establish regulatory networks. Finally, intragenic DNA methylation and chromatin conformation patterns predicted alternative gene isoform expression observed in a companion whole-brain SMART-seq ³ dataset. Our study establishes the first brain-wide, single-cell resolution DNA methylome and 3D multi-omic atlas, providing an unparalleled resource for comprehending the mouse brain’s cellular-spatial and regulatory genome diversity.

This study applied a molecular-based method to detect parainfluenza virus 5 (PIV5) collected from 2016 to 2018 in nine provinces of Republic of Korea. We demonstrated that PIV5 was detectable in both serum and pooled organs at an average positive rate of 1.78% (99/5566). Among these, the complete genome sequence of 15,246 nucleotides was obtained for 12 field strains. Three out of the 12 strains had the lowest genetic identity (96.20–96.68%) among the 21 porcine PIV5 genomes collected in Germany, China, India, and Republic of Korea from 1998 to 2017. By analyzing a large collection of complete genome sequences of the structural protein-coding F and HN genes, this study proposed a classification of PIV5 into two lineages, 1 and 2, and identified that group 2.2.2 within sub-lineage 2.2 was substantially divergent. The evolution of two structural protein-coding genes was largely under purifying selection. A few codons (6/9 for the F gene, 7/8 for the HN gene) had elevated dN/dS values, which were loaded on internal branches and were predicted to be related to beneficial trait(s) of the virus.

An investigation into retrovirus was conducted in six species of bats ( Myotis aurascens , Myotis petax , Myotis macrodactylus , Miniopterus fuliginosus , Rhinolophus ferrumequinum , and Pipistrellus abramus ) inhabiting South Korea. Exogenous retroviruses (XRVs) were detected in the tissue samples of R. ferrumequinum individuals by PCR assay. Proviruses were identified in all tissue samples through viral quantification using a digital PCR assay per organ (lung, intestine, heart, brain, wing, kidney, and liver), with viral loads varying greatly between each organ. In phylogenetic analysis based on the whole genome, the Korean bat retroviruses and the R. ferrumequinum retrovirus (RfRV) strain formed a new clade distinct from the Gammaretrovirus clade. The phylogenetic results determined these viruses to be RfRV-like viruses. In the Simplot comparison, Korean RfRV-like viruses exhibited relatively strong fluctuated patterns in the latter part of the envelope gene area compared to other gene areas. Several point mutations within this region (6,878–7,774 bp) of these viruses were observed compared to the RfRV sequence. One Korean RfRV-like virus (named Y4b strain) was successfully recovered in the Raw 264.7 cell line, and virus particles replicated in the cells were confirmed by transmission electron microscopy. RfRVs (or RfRV-like viruses) have been spreading since their first discovery in 2012, and the Korean RfRV-like viruses were assumed to be XRVs that evolved from RfRV. IMPORTANCE: R. ferrumequinum retrovirus (RfRV)-like viruses were identified in greater horseshoe bats in South Korea. These RfRV-like viruses were considered exogenous retroviruses (XRVs) that emerged from RfRV. Varying amounts of provirus detected in different organs suggest ongoing viral activity, replication, and de novo integration in certain organs. Additionally, the successful recovery of the virus in the Raw 264.7 cell line provides strong evidence supporting their status as XRVs. These viruses have now been identified in South Korea and, more recently, in Kenya since RfRV was discovered in China in 2012, indicating that RfRVs (or RfRV-like viruses) have spread worldwide.