Project description: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-seq1) 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 (MERFISH2) 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-seq3 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.
Project description:Cataloging the diverse cellular architecture of the primate brain is crucial for understanding cognition, behavior, and disease in humans. Here, we generated a brain-wide single-cell multimodal molecular atlas of the rhesus macaque brain. Together, we profiled 2.58 M transcriptomes and 1.59 M epigenomes from single nuclei sampled from 30 regions across the adult brain. Cell composition differed extensively across the brain, revealing cellular signatures of region-specific functions. We also identified 1.19 M candidate regulatory elements, many previously unidentified, allowing us to explore the landscape of cis-regulatory grammar and neurological disease risk in a cell type-specific manner. Altogether, this multi-omic atlas provides an open resource for investigating the evolution of the human brain and identifying novel targets for disease interventions.
Project description:Human subcutaneous adipose tissue (SAT) contains a diverse array of cell-types; however, the epigenomic landscape among the SAT cell-types has remained elusive. Our integrative analysis of single-cell resolution DNA methylation and chromatin conformation profiles (snm3C-seq), coupled with matching RNA expression (snRNA-seq), systematically cataloged the epigenomic, 3D topology, and transcriptomic dynamics across the SAT cell-types. We discovered that the SAT CG methylation (mCG) landscape is characterized by pronounced hyper-methylation in myeloid cells and hypo-methylation in adipocytes and adipose stem and progenitor cells (ASPCs), driving nearly half of the 705,063 detected differentially methylated regions (DMRs). In addition to the enriched cell-type-specific transcription factor binding motifs, we identified TET1 and DNMT3A as plausible candidates for regulating cell-type level mCG profiles. Furthermore, we observed that global mCG profiles closely correspond to SAT lineage, which is also reflected in cell-type-specific chromosome compartmentalization. Adipocytes, in particular, display significantly more short-range chromosomal interactions, facilitating the formation of complex local 3D genomic structures that regulate downstream transcriptomic activity, including those associated with adipogenesis. Finally, we discovered that variants in cell-type level DMRs and A compartments significantly predict and are enriched for variance explained in abdominal obesity. Together, our multimodal study characterizes human SAT epigenomic landscape at the cell-type resolution and links partitioned polygenic risk of abdominal obesity to SAT epigenome.
Project description:Aging is the primary risk factor for many neurodegenerative diseases, primarily attributed to progressive changes in cellular epigenomes. Despite this known association, the complexity of the mammalian brain complicates the identification of brain regions and cell types that are most susceptible to aging effects. While alterations in gene expression have been observed in aging neural cells, comprehension of the epigenetic regulatory mechanisms underlying the transcriptomic changes remains largely elusive. To unveil these complexities in a comprehensive manner, we utilized single-nucleus methylome sequencing (snmC-seq3) and multi-omic sequencing (snm3C-seq) to produce extensive datasets comprising 132,551 methylomes and 72,666 chromatin conformation-methylome joint profiles from eight distinct brain regions of C57BL/6J mice aged 2, 9, and 18 months. These regions include the anterior hippocampus (AHC), posterior hippocampus (PHC), frontal cortex (FC), amygdala (AMY), nucleus accumbens (NACB), PAG/PCG, entorhinal cortex (ENT), and caudate putamen (CP). We utilized this dataset to investigate age-related changes in DNA methylomes and transcription factor motifs potentially affected by methylation alterations. We also examined methylation changes in transposable elements, observing locus-specific retrotransposon activation. At the chromatin conformation level, we analyzed aging-related changes in compartmentalization, topologically associating domains (TADs), and chromatin loops. Furthermore, we explored regional heterogeneity during aging within identical cell types and validated our findings using the MERFISH dataset.
Project description:The mammalian stomach is structurally highly diverse and its organ functionality critically depends on a normal embryonic development. Although there have been several studies on the morphological changes during stomach development, a system-wide analysis of the underlying molecular changes is lacking. Here, we present a comprehensive, temporal proteome and transcriptome atlas of the mouse stomach at multiple developmental stages. Quantitative analysis of 12,108 gene products allows identifying three distinct phases based on changes in proteins and RNAs and the gain of stomach functions on a longitudinal time scale. The transcriptome indicates functionally important isoforms relevant to development and identifies several functionally unannotated novel splicing junction transcripts that we validate at the peptide level. Importantly, many proteins differentially expressed in stomach development are also significantly overexpressed in diffuse-type gastric cancer. Overall, our study provides a resource to understand stomach development and its connection to gastric cancer tumorigenesis.
Project description:Liver organogenesis and development are composed of a series of complex, well-orchestrated events. Identifying key factors and pathways governing liver development will help elucidate the physiological and pathological processes including those of cancer. We conducted multidimensional omics measurements including protein, mRNA, and transcription factor (TF) DNA-binding activity for mouse liver tissues collected from embryonic day 12.5 (E12.5) to postnatal week 8 (W8), encompassing major developmental stages. These data sets reveal dynamic changes of core liver functions and canonical signaling pathways governing development at both mRNA and protein levels. The TF DNA-binding activity data set highlights the importance of TF activity in early embryonic development. A comparison between mouse liver development and human hepatocellular carcinoma (HCC) proteomic profiles reveal that more aggressive tumors are characterized with the activation of early embryonic development pathways, whereas less aggressive ones maintain liver function-related pathways that are elevated in the mature liver. This work offers a panoramic view of mouse liver development and provides a rich resource to explore in-depth functional characterization.
Project description: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.
Project description:B cells are capable of a wide range of effector functions including antibody secretion, antigen presentation, cytokine production, and generation of immunological memory. A consistent strategy for classifying human B cells by using surface molecules is essential to harness this functional diversity for clinical translation. We developed a highly multiplexed screen to quantify the co-expression of 351 surface molecules on millions of human B cells. We identified differentially expressed molecules and aligned their variance with isotype usage, VDJ sequence, metabolic profile, biosynthesis activity, and signaling response. Based on these analyses, we propose a classification scheme to segregate B cells from four lymphoid tissues into twelve unique subsets, including a CD45RB+CD27- early memory population, a class-switched CD39+ tonsil-resident population, and a CD19hiCD11c+ memory population that potently responds to immune activation. This classification framework and underlying datasets provide a resource for further investigations of human B cell identity and function.
Project description:Brain maps are essential for integrating information and interpreting the structure-function relationship of circuits and behavior. We aimed to generate a systematic classification of the adult mouse brain based purely on the unbiased identification of spatially defining features by employing whole-brain spatial transcriptomics. We found that the molecular information was sufficient to deduce the complex and detailed neuroanatomical organization of the brain. The unsupervised (non-expert, data-driven) classification revealed new area- and layer-specific subregions, for example in isocortex and hippocampus, and new subdivisions of striatum. The molecular atlas further supports the characterization of the spatial identity of neurons from their single-cell RNA profile, and provides a resource for annotating the brain using a minimal gene set-a brain palette. In summary, we have established a molecular atlas to formally define the spatial organization of brain regions, including the molecular code for mapping and targeting of discrete neuroanatomical domains.
Project description:The blood-brain barrier (BBB) is primarily manifested by a variety of physiological properties of brain endothelial cells (ECs), but the molecular foundation for these properties remains incompletely clear. Here, we generate a comprehensive molecular atlas of adult brain ECs using acutely purified mouse ECs and integrated multi-omics. Using RNA sequencing (RNA-seq) and proteomics, we identify the transcripts and proteins selectively enriched in brain ECs and demonstrate that they are partially correlated. Using single-cell RNA-seq, we dissect the molecular basis of functional heterogeneity of brain ECs. Using integrative epigenomics and transcriptomics, we determine that TCF/LEF, SOX, and ETS families are top-ranked transcription factors regulating the BBB. We then validate the identified brain-EC-enriched proteins and transcription factors in normal mouse and human brain tissue and assess their expression changes in mice with Alzheimer's disease. Overall, we present a valuable resource with broad implications for regulation of the BBB and treatment of neurological disorders.