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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.

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.

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.

To provide a temporal framework for the genoarchitecture of brain development, we generated in situ hybridization data for embryonic and postnatal mouse brain at seven developmental stages for ∼2,100 genes, which were processed with an automated informatics pipeline and manually annotated. This resource comprises 434,946 images, seven reference atlases, an ontogenetic ontology, and tools to explore coexpression of genes across neurodevelopment. Gene sets coinciding with developmental phenomena were identified. A temporal shift in the principles governing the molecular organization of the brain was detected, with transient neuromeric, plate-based organization of the brain present at E11.5 and E13.5. Finally, these data provided a transcription factor code that discriminates brain structures and identifies the developmental age of a tissue, providing a foundation for eventual genetic manipulation or tracking of specific brain structures over development. The resource is available as the Allen Developing Mouse Brain Atlas (http://developingmouse.brain-map.org).

The neocortex contains a multitude of cell types that are segregated into layers and functionally distinct areas. To investigate the diversity of cell types across the mouse neocortex, here we analysed 23,822 cells from two areas at distant poles of the mouse neocortex: the primary visual cortex and the anterior lateral motor cortex. We define 133 transcriptomic cell types by deep, single-cell RNA sequencing. Nearly all types of GABA ([gamma]-aminobutyric acid)-containing neurons are shared across both areas, whereas most types of glutamatergic neurons were found in one of the two areas. By combining single-cell RNA sequencing and retrograde labelling, we match transcriptomic types of glutamatergic neurons to their long-range projection specificity. Our study establishes a combined transcriptomic and projectional taxonomy of cortical cell types from functionally distinct areas of the adult mouse cortex. Single-cell transcriptomics of more than 20,000 cells from two functionally distinct areas of the mouse neocortex identifies 133 transcriptomic types, and provides a foundation for understanding the diversity of cortical cell types., Author(s): Bosiljka Tasic [sup.1] , Zizhen Yao [sup.1] , Lucas T. Graybuck [sup.1] , Kimberly A. Smith [sup.1] , Thuc Nghi Nguyen [sup.1] , Darren Bertagnolli [sup.1] , Jeff Goldy [...]

Comprehensive knowledge of the brain's wiring diagram is fundamental for understanding how the nervous system processes information at both local and global scales. However, with the singular exception of the C. elegans microscale connectome, there are no complete connectivity data sets in other species. Here we report a brain-wide, cellular-level, mesoscale connectome for the mouse. The Allen Mouse Brain Connectivity Atlas uses enhanced green fluorescent protein (EGFP)-expressing adeno-associated viral vectors to trace axonal projections from defined regions and cell types, and high-throughput serial two-photon tomography to image the EGFP-labelled axons throughout the brain. This systematic and standardized approach allows spatial registration of individual experiments into a common three dimensional (3D) reference space, resulting in a whole-brain connectivity matrix. A computational model yields insights into connectional strength distribution, symmetry and other network properties. Virtual tractography illustrates 3D topography among interconnected regions. Cortico-thalamic pathway analysis demonstrates segregation and integration of parallel pathways. The Allen Mouse Brain Connectivity Atlas is a freely available, foundational resource for structural and functional investigations into the neural circuits that support behavioural and cognitive processes in health and disease., A central principle of neuroscience is that the nervous system is a network of diverse types of neurons and supporting cells communicating with each other mainly through synaptic connections. This [...]

Transcriptomic profiling of complex tissues by single-nucleus RNA-sequencing (snRNA-seq) affords some advantages over single-cell RNA-sequencing (scRNA-seq). snRNA-seq provides less biased cellular coverage, does not appear to suffer cell isolation-based transcriptional artifacts, and can be applied to archived frozen specimens. We used well-matched snRNA-seq and scRNA-seq datasets from mouse visual cortex to compare cell type detection. Although more transcripts are detected in individual whole cells (~11,000 genes) than nuclei (~7,000 genes), we demonstrate that closely related neuronal cell types can be similarly discriminated with both methods if intronic sequences are included in snRNA-seq analysis. We estimate that the nuclear proportion of total cellular mRNA varies from 20% to over 50% for large and small pyramidal neurons, respectively. Together, these results illustrate the high information content of nuclear RNA for characterization of cellular diversity in brain tissues. [ABSTRACT FROM AUTHOR]

The isocortex and hippocampal formation (HPF) in the mammalian brain play critical roles in perception, cognition, emotion, and learning. We profiled ∼1.3 million cells covering the entire adult mouse isocortex and HPF and derived a transcriptomic cell-type taxonomy revealing a comprehensive repertoire of glutamatergic and GABAergic neuron types. Contrary to the traditional view of HPF as having a simpler cellular organization, we discover a complete set of glutamatergic types in HPF homologous to all major subclasses found in the six-layered isocortex, suggesting that HPF and the isocortex share a common circuit organization. We also identify large-scale continuous and graded variations of cell types along isocortical depth, across the isocortical sheet, and in multiple dimensions in hippocampus and subiculum. Overall, our study establishes a molecular architecture of the mammalian isocortex and hippocampal formation and begins to shed light on its underlying relationship with the development, evolution, connectivity, and function of these two brain structures. [Display omitted] • Single-cell transcriptomics from >1.3 million cells in the mouse cortex and hippocampus • Many neuron types specific to associational cortex and hippocampal regions are identified • Parallel cell-type and laminar organization between isocortex and hippocampal formation • Large-scale continuous neuron-type variation in isocortex and hippocampus/subiculum Single-cell transcriptomics of the entire mouse isocortex and hippocampal formation shows shared cellular and circuit organization and large-scale continuous gradients of neuron-type variation that illuminates the underlying relationship between these two critical brain structures. [ABSTRACT FROM AUTHOR]

Regulation of gut function depends on the detection and response to luminal contents. Luminal l-amino acids (l-AA) are detected by several receptors including metabotropic glutamate receptors 1 and 4 (mGluR1 and mGluR4), calcium-sensing receptor (CaSR), GPRC family C group 6 subtype A receptor (GPRC6A) and umami taste receptor heterodimer T1R1/T1R3. Here, we show that murine mucosal homogenates and STC-1 cells, a murine enteroendocrine cell line, express mRNA for all l-AA receptors. Immunohistochemical analysis demonstrated the presence of all l-AA receptors on STC-1 with CaSR being most commonly expressed and T1R1 least expressed (35% versus 15% of cells); mGluRs and GPRC6a were intermediate (~ 20% of cells). Regarding coexpression of l-AA receptors, the mGluRs and T1R1 were similarly coexpressed with CaSR (10–12% of cells) whereas GPRC6a was coexpressed least (7% of cells). mGluR1 was coexpressed with GPRC6a in 11% of cells whereas coexpression between other receptors was less (2–8% of cells). CaSR and mGluR1 were coexpressed with glucagon-like peptide-1 (GLP-1) and peptide YY (PYY) in 20–25% of cells whereas T1R1 and GPRC6a were coexpressed with GLP-1 and PYY less (8–12% of cells). Only mGluR4 showed differential coexpression with GLP-1 (13%) and PYY (21%). l-Phenylalanine (10 mM) caused a 3-fold increase in GLP-1 release, which was strongly inhibited by siRNA to CaSR indicating functional coupling of CaSR to GLP-1 release. The results suggest that not all STC-1 cells express (and coexpress) l-AA receptors to the same extent and that the pattern of response likely depends on the pattern of expression of l-AA receptors. [ABSTRACT FROM AUTHOR]

Summary An increasingly powerful approach for studying brain circuits relies on targeting genetically encoded sensors and effectors to specific cell types. However, current approaches for this are still limited in functionality and specificity. Here we utilize several intersectional strategies to generate multiple transgenic mouse lines expressing high levels of novel genetic tools with high specificity. We developed driver and double reporter mouse lines and viral vectors using the Cre/Flp and Cre/Dre double recombinase systems and established a new, retargetable genomic locus, TIGRE, which allowed the generation of a large set of Cre/tTA-dependent reporter lines expressing fluorescent proteins, genetically encoded calcium, voltage, or glutamate indicators, and optogenetic effectors, all at substantially higher levels than before. High functionality was shown in example mouse lines for GCaMP6, YCX2.60, VSFP Butterfly 1.2, and Jaws. These novel transgenic lines greatly expand the ability to monitor and manipulate neuronal activities with increased specificity. Video Abstract [ABSTRACT FROM AUTHOR]

Rapid cell type identification by new genomic single-cell analysis methods has not been met with efficient experimental access to these cell types. To facilitate access to specific neural populations in mouse cortex, we collected chromatin accessibility data from individual cells and identified enhancers specific for cell subclasses and types. When cloned into recombinant adeno-associated viruses (AAVs) and delivered to the brain, these enhancers drive transgene expression in specific cortical cell subclasses. We extensively characterized several enhancer AAVs to show that they label different projection neuron subclasses as well as a homologous neuron subclass in human cortical slices. We also show how coupling enhancer viruses expressing recombinases to a newly generated transgenic mouse, Ai213 , enables strong labeling of three different neuronal classes/subclasses in the brain of a single transgenic animal. This approach combines unprecedented flexibility with specificity for investigation of cell types in the mouse brain and beyond. [Display omitted] • High-quality single-cell ATAC-seq dataset for adult mouse visual cortex • Enhancer AAVs targeting distinct subclasses of excitatory projection neurons • New TIGRE-based transgenic reporter line with three-color readout • Combined enhancer AAVs label up to three distinct cell populations in one brain Graybuck et al. generated a single-cell chromatin accessibility dataset for adult mouse cortex and identified functional enhancer elements. They created a suite of enhancer-containing adeno-associated viruses to label genetically defined cell populations in the mouse brain. [ABSTRACT FROM AUTHOR]

The evolutionarily conserved default mode network (DMN) is a distributed set of brain regions coactivated during resting states that is vulnerable to brain disorders. How disease affects the DMN is unknown, but detailed anatomical descriptions could provide clues. Mice offer an opportunity to investigate structural connectivity of the DMN across spatial scales with cell-type resolution. We co-registered maps from functional magnetic resonance imaging and axonal tracing experiments into the 3D Allen mouse brain reference atlas. We find that the mouse DMN consists of preferentially interconnected cortical regions. As a population, DMN layer 2/3 (L2/3) neurons project almost exclusively to other DMN regions, whereas L5 neurons project in and out of the DMN. In the retrosplenial cortex, a core DMN region, we identify two L5 projection types differentiated by in- or out-DMN targets, laminar position, and gene expression. These results provide a multi-scale description of the anatomical correlates of the mouse DMN. • Mouse resting-state default mode network anatomy described at high resolution in 3D • Systematic axon tracing shows cortical DMN regions are preferentially interconnected • Layer 2/3 DMN neurons project mostly in the DMN; layer 5 neurons project in and out • Retrosplenial cortex contains distinct types of in- and out-DMN projection neurons The default mode network is vulnerable to brain disorders, but details of its anatomy and connectivity are coarse. Whitesell et al. use modern neuroanatomical tools in the mouse, including whole-brain imaging and viral tracing, to provide high-resolution anatomical descriptions and identify cell type correlates of this conserved brain network. [ABSTRACT FROM AUTHOR]