Search

Recent advances in single-cell technologies have led to the discovery of thousands of brain cell types; however, our understanding of the gene regulatory programs in these cell types is far from complete1-4. Here we report a comprehensive atlas of candidate cis-regulatory DNA elements (cCREs) in the adult mouse brain, generated by analysing chromatin accessibility in 2.3 million individual brain cells from 117 anatomical dissections. The atlas includes approximately 1 million cCREs and their chromatin accessibility across 1,482 distinct brain cell populations, adding over 446,000 cCREs to the most recent such annotation in the mouse genome. The mouse brain cCREs are moderately conserved in the human brain. The mouse-specific cCREs-specifically, those identified from a subset of cortical excitatory neurons-are strongly enriched for transposable elements, suggesting a potential role for transposable elements in the emergence of new regulatory programs and neuronal diversity. Finally, we infer the gene regulatory networks in over 260 subclasses of mouse brain cells and develop deep-learning models to predict the activities of gene regulatory elements in different brain cell types from the DNA sequence alone. Our results provide a resource for the analysis of cell-type-specific gene regulation programs in both mouse and 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)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.

Single-cell analyses parse the brains 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.

Determining which features of the neural code drive behavior requires the ability to simultaneously read out and write in neural activity patterns with high precision across many neurons. All-optical systems that combine two-photon calcium imaging and targeted photostimulation enable the activation of specific, functionally defined groups of neurons. However, these techniques are unable to test how patterns of activity across a population contribute to computation because of an inability to both read and write cell-specific firing rates. To overcome this challenge, we make two advances: first, we introduce a genetic line of mice for Cre-dependent co-expression of a calcium indicator and a potent soma-targeted microbial opsin. Second, using this line, we develop a method for read-out and write-in of precise population vectors of neural activity by calibrating the photostimulation to each cell. These advances offer a powerful and convenient platform for investigating the neural codes of computation and behavior.

Characterizing cellular diversity at different levels of biological organization and across data modalities is a prerequisite to understanding the function of cell types in the brain. Classification of neurons is also essential to manipulate cell types in controlled ways and to understand their variation and vulnerability in brain disorders. The BRAIN Initiative Cell Census Network (BICCN) is an integrated network of data-generating centers, data archives, and data standards developers, with the goal of systematic multimodal brain cell type profiling and characterization. Emphasis of the BICCN is on the whole mouse brain with demonstration of prototype feasibility for human and nonhuman primate (NHP) brains. Here, we provide a guide to the cellular and spatial approaches employed by the BICCN, and to accessing and using these data and extensive resources, including the BRAIN Cell Data Center (BCDC), which serves to manage and integrate data across the ecosystem. We illustrate the power of the BICCN data ecosystem through vignettes highlighting several BICCN analysis and visualization tools. Finally, we present emerging standards that have been developed or adopted toward Findable, Accessible, Interoperable, and Reusable (FAIR) neuroscience. The combined BICCN ecosystem provides a comprehensive resource for the exploration and analysis of cell types in the brain.

Enhancers integrate transcription factor signaling pathways that drive cell fate specification in the developing brain. We paired enhancer labeling and single-cell RNA-sequencing (scRNA-seq) to delineate and distinguish specification of neuronal lineages in mouse medial, lateral, and caudal ganglionic eminences (MGE, LGE, and CGE) at embryonic day (E)11.5. We show that scRNA-seq clustering using transcription factors improves resolution of regional and developmental populations, and that enhancer activities identify specific and overlapping GE-derived neuronal populations. First, we mapped the activities of seven evolutionarily conserved brain enhancers at single-cell resolution in vivo, finding that the selected enhancers had diverse activities in specific progenitor and neuronal populations across the GEs. We then applied enhancer-based labeling, scRNA-seq, and analysis of in situ hybridization data to distinguish transcriptionally distinct and spatially defined subtypes of MGE-derived GABAergic and cholinergic projection neurons and interneurons. Our results map developmental origins and specification paths underlying neurogenesis in the embryonic basal ganglia and showcase the power of scRNA-seq combined with enhancer-based labeling to resolve the complex paths of neuronal specification underlying mouse brain development.

We uncovered a transcription factor (TF) network that regulates cortical regional patterning in radial glial stem cells. Screening the expression of hundreds of TFs in the developing mouse cortex identified 38 TFs that are expressed in gradients in the ventricular zone (VZ). We tested whether their cortical expression was altered in mutant mice with known patterning defects (Emx2, Nr2f1, and Pax6), which enabled us to define a cortical regionalization TF network (CRTFN). To identify genomic programming underlying this network, we performed TF ChIP-seq and chromatin-looping conformation to identify enhancer-gene interactions. To map enhancers involved in regional patterning of cortical progenitors, we performed assays for epigenomic marks and DNA accessibility in VZ cells purified from wild-type and patterning mutant mice. This integrated approach has identified a CRTFN and VZ enhancers involved in cortical regional patterning in the mouse.

Cortical neurons exhibit extreme diversity in gene expression as well as in morphological and electrophysiological properties1,2. Most existing neural taxonomies are based on either transcriptomic3,4 or morpho-electric5,6 criteria, as it has been technically challenging to study both aspects of neuronal diversity in the same set of cells7. Here we used Patch-seq8 to combine patch-clamp recording, biocytin staining, and single-cell RNA sequencing of more than 1,300 neurons in adult mouse primary motor cortex, providing a morpho-electric annotation of almost all transcriptomically defined neural cell types. We found that, although broad families of transcriptomic types (those expressing Vip, Pvalb, Sst and so on) had distinct and essentially non-overlapping morpho-electric phenotypes, individual transcriptomic types within the same family were not well separated in the morpho-electric space. Instead, there was a continuum of variability in morphology and electrophysiology, with neighbouring transcriptomic cell types showing similar morpho-electric features, often without clear boundaries between them. Our results suggest that neuronal types in the neocortex do not always form discrete entities. Instead, neurons form a hierarchy that consists of distinct non-overlapping branches at the level of families, but can form continuous and correlated transcriptomic and morpho-electrical landscapes within families.

Single-cell transcriptomics can provide quantitative molecular signatures for large, unbiased samples of the diverse cell types in the brain1-3. With the proliferation of multi-omics datasets, a major challenge is to validate and integrate results into a biological understanding of cell-type organization. Here we generated transcriptomes and epigenomes from more than 500,000 individual cells in the mouse primary motor cortex, a structure that has an evolutionarily conserved role in locomotion. We developed computational and statistical methods to integrate multimodal data and quantitatively validate cell-type reproducibility. The resulting reference atlas-containing over 56 neuronal cell types that are highly replicable across analysis methods, sequencing technologies and modalities-is a comprehensive molecular and genomic account of the diverse neuronal and non-neuronal cell types in the mouse primary motor cortex. The atlas includes a population of excitatory neurons that resemble pyramidal cells in layer 4 in other cortical regions4. We further discovered thousands of concordant marker genes and gene regulatory elements for these cell types. Our results highlight the complex molecular regulation of cell types in the brain and will directly enable the design of reagents to target specific cell types in the mouse primary motor cortex for functional analysis.

Here we report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Our results advance the collective knowledge and understanding of brain cell-type organization1-5. First, our study reveals a unified molecular genetic landscape of cortical cell types that integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a consensus taxonomy of transcriptomic types and their hierarchical organization that is conserved from mouse to marmoset and human. Third, in situ single-cell transcriptomics provides a spatially resolved cell-type atlas of the motor cortex. Fourth, cross-modal analysis provides compelling evidence for the transcriptomic, epigenomic and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types. We further present an extensive genetic toolset for targeting glutamatergic neuron types towards linking their molecular and developmental identity to their circuit function. Together, our results establish a unifying and mechanistic framework of neuronal cell-type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties.

To understand the function of cortical circuits, it is necessary to catalog their cellular diversity. Past attempts to do so using anatomical, physiological or molecular features of cortical cells have not resulted in a unified taxonomy of neuronal or glial cell types, partly due to limited data. Single-cell transcriptomics is enabling, for the first time, systematic high-throughput measurements of cortical cells and generation of datasets that hold the promise of being complete, accurate and permanent. Statistical analyses of these data reveal clusters that often correspond to cell types previously defined by morphological or physiological criteria and that appear conserved across cortical areas and species. To capitalize on these new methods, we propose the adoption of a transcriptome-based taxonomy of cell types for mammalian neocortex. This classification should be hierarchical and use a standardized nomenclature. It should be based on a probabilistic definition of a cell type and incorporate data from different approaches, developmental stages and species. A community-based classification and data aggregation model, such as a knowledge graph, could provide a common foundation for the study of cortical circuits. This community-based classification, nomenclature and data aggregation could serve as an example for cell type atlases in other parts of the body.

Cajal recognized that the elaborate shape of neurons is fundamental to their function in the brain. However, there are no simple and generalizable genetic methods to study neuronal or glial cell morphology in the mammalian brain. Here, we describe four mouse lines conferring Cre-dependent sparse cell labeling based on mononucleotide repeat frameshift (MORF) as a stochastic translational switch. Notably, the optimized MORF3 mice, with a membrane-bound multivalent immunoreporter, confer Cre-dependent sparse and bright labeling of thousands of neurons, astrocytes, or microglia in each brain, revealing their intricate morphologies. MORF3 mice are compatible with imaging in tissue-cleared thick brain sections and with immuno-EM. An analysis of 151 MORF3-labeled developing retinal horizontal cells reveals novel morphological cell clusters and axonal maturation patterns. Our study demonstrates a conceptually novel, simple, generalizable, and scalable mouse genetic solution to sparsely label and illuminate the morphology of genetically defined neurons and glia in the mammalian brain.

Energy homeostasis requires precise measurement of the quantity and quality of ingested food. The vagus nerve innervates the gut and can detect diverse interoceptive cues, but the identity of the key sensory neurons and corresponding signals that regulate food intake remains unknown. Here, we use an approach for target-specific, single-cell RNA sequencing to generate a map of the vagal cell types that innervate the gastrointestinal tract. We show that unique molecular markers identify vagal neurons with distinct innervation patterns, sensory endings, and function. Surprisingly, we find that food intake is most sensitive to stimulation of mechanoreceptors in the intestine, whereas nutrient-activated mucosal afferents have no effect. Peripheral manipulations combined with central recordings reveal that intestinal mechanoreceptors, but not other cell types, potently and durably inhibit hunger-promoting AgRP neurons in the hypothalamus. These findings identify a key role for intestinal mechanoreceptors in the regulation of feeding.

Elucidating the cellular architecture of the human cerebral cortex is central to understanding our cognitive abilities and susceptibility to disease. Here we used single-nucleus RNA-sequencing analysis to perform a comprehensive study of cell types in the middle temporal gyrus of human cortex. We identified a highly diverse set of excitatory and inhibitory neuron types that are mostly sparse, with excitatory types being less layer-restricted than expected. Comparison to similar mouse cortex single-cell RNA-sequencing datasets revealed a surprisingly well-conserved cellular architecture that enables matching of homologous types and predictions of properties of human cell types. Despite this general conservation, we also found extensive differences between homologous human and mouse cell types, including marked alterations in proportions, laminar distributions, gene expression and morphology. These species-specific features emphasize the importance of directly studying human brain.

Satiation is the process by which eating and drinking reduce appetite. For thirst, oropharyngeal cues have a critical role in driving satiation by reporting to the brain the volume of fluid that has been ingested1-12. By contrast, the mechanisms that relay the osmolarity of ingested fluids remain poorly understood. Here we show that the water and salt content of the gastrointestinal tract are precisely measured and then rapidly communicated to the brain to control drinking behaviour in mice. We demonstrate that this osmosensory signal is necessary and sufficient for satiation during normal drinking, involves the vagus nerve and is transmitted to key forebrain neurons that control thirst and vasopressin secretion. Using microendoscopic imaging, we show that individual neurons compute homeostatic need by integrating this gastrointestinal osmosensory information with oropharyngeal and blood-borne signals. These findings reveal how the fluid homeostasis system monitors the osmolarity of ingested fluids to dynamically control drinking behaviour.

A comprehensive characterization of neuronal cell types, their distributions, and patterns of connectivity is critical for understanding the properties of neural circuits and how they generate behaviors. Here we review the experiences of the BRAIN Initiative Cell Census Consortium, ten pilot projects funded by the U.S. BRAIN Initiative, in developing, validating, and scaling up emerging genomic and anatomical mapping technologies for creating a complete inventory of neuronal cell types and their connections in multiple species and during development. These projects lay the foundation for a larger and longer-term effort to generate whole-brain cell atlases in species including mice and humans.

In humans and other mammalian species, lesions in the preoptic area of the hypothalamus cause profound sleep impairment, indicating a crucial role of the preoptic area in sleep generation. However, the underlying circuit mechanism remains poorly understood. Electrophysiological recordings and c-Fos immunohistochemistry have shown the existence of sleep-active neurons in the preoptic area, especially in the ventrolateral preoptic area and median preoptic nucleus. Pharmacogenetic activation of c-Fos-labelled sleep-active neurons has been shown to induce sleep. However, the sleep-active neurons are spatially intermingled with wake-active neurons, making it difficult to target the sleep neurons specifically for circuit analysis. Here we identify a population of preoptic area sleep neurons on the basis of their projection target and discover their molecular markers. Using a lentivirus expressing channelrhodopsin-2 or a light-activated chloride channel for retrograde labelling, bidirectional optogenetic manipulation, and optrode recording, we show that the preoptic area GABAergic neurons projecting to the tuberomammillary nucleus are both sleep active and sleep promoting. Furthermore, translating ribosome affinity purification and single-cell RNA sequencing identify candidate markers for these neurons, and optogenetic and pharmacogenetic manipulations demonstrate that several peptide markers (cholecystokinin, corticotropin-releasing hormone, and tachykinin 1) label sleep-promoting neurons. Together, these findings provide easy genetic access to sleep-promoting preoptic area neurons and a valuable entry point for dissecting the sleep control circuit.

Elucidating the transcriptional circuitry controlling forebrain development requires an understanding of enhancer activity and regulation. We generated stable transgenic mouse lines that express CreERT2 and GFP from ten different enhancer elements with activity in distinct domains within the embryonic basal ganglia. We used these unique tools to generate a comprehensive regional fate map of the mouse subpallium, including sources for specific subtypes of amygdala neurons. We then focused on deciphering transcriptional mechanisms that control enhancer activity. Using machine-learning computations, in vivo chromosomal occupancy of 13 transcription factors that regulate subpallial patterning and differentiation and analysis of enhancer activity in Dlx1/2 and Lhx6 mutants, we elucidated novel molecular mechanisms that regulate region-specific enhancer activity in the developing brain. Thus, these subpallial enhancer transgenic lines are data and tool resources to study transcriptional regulation of GABAergic cell fate.

Intracellular Ca(2+) signaling is considered to be important for multiple astrocyte functions in neural circuits. However, mice devoid of inositol triphosphate type 2 receptors (IP3R2) reportedly lack all astrocyte Ca(2+) signaling, but display no neuronal or neurovascular deficits, implying that astrocyte Ca(2+) fluctuations are not involved in these functions. An assumption has been that the loss of somatic Ca(2+) fluctuations also reflects a similar loss in astrocyte processes. We tested this assumption and found diverse types of Ca(2+) fluctuations in astrocytes, with most occurring in processes rather than in somata. These fluctuations were preserved in Ip3r2(-/-) (also known as Itpr2(-/-)) mice in brain slices and in vivo, occurred in end feet, and were increased by G protein-coupled receptor activation and by startle-induced neuromodulatory responses. Our data reveal previously unknown Ca(2+) fluctuations in astrocytes and highlight limitations of studies that used Ip3r2(-/-) mice to evaluate astrocyte contributions to neural circuit function and mouse behavior.

Elucidating the genetic control of cerebral cortical (pallial) development is essential for understanding function, evolution, and disorders of the brain. Transcription factors (TFs) that embryonically regulate pallial regionalization are expressed in gradients, raising the question of how discrete domains are generated. We provide evidence that small enhancer elements active in protodomains integrate broad transcriptional information. CreER(T2) and GFP expression from 14 different enhancer elements in stable transgenic mice allowed us to define a comprehensive regional fate map of the pallium. We explored transcriptional mechanisms that control the activity of the enhancers using informatics, in vivo occupancy by TFs that regulate cortical patterning (CoupTFI, Pax6, and Pbx1), and analysis of enhancer activity in Pax6 mutants. Overall, the results provide insights into how broadly expressed patterning TFs regulate the activity of small enhancer elements that drive gene expression in pallial protodomains that fate map to distinct cortical regions.

The dentate gyrus (DG), in addition to its role in learning and memory, is increasingly implicated in the pathophysiology of anxiety disorders. Here, we show that, dependent on their position along the dorsoventral axis of the hippocampus, DG granule cells (GCs) control specific features of anxiety and contextual learning. Using optogenetic techniques to either elevate or decrease GC activity, we demonstrate that GCs in the dorsal DG control exploratory drive and encoding, not retrieval, of contextual fear memories. In contrast, elevating the activity of GCs in the ventral DG has no effect on contextual learning but powerfully suppresses innate anxiety. These results suggest that strategies aimed at modulating the excitability of the ventral DG may be beneficial for the treatment of anxiety disorders.