The primary motor cortex (M1) is essential for voluntary fine-motor control and is functionally conserved across mammals1. Here, using high-throughput transcriptomic and epigenomic profiling of more than 450,000 single nuclei in humans, marmoset monkeys and mice, we demonstrate a broadly conserved cellular makeup of this region, with similarities that mirror evolutionary distance and are consistent between the transcriptome and epigenome. The core conserved molecular identities of neuronal and non-neuronal cell types allow us to generate a cross-species consensus classification of cell types, and to infer conserved properties of cell types across species. Despite the overall conservation, however, many species-dependent specializations are apparent, including differences in cell-type proportions, gene expression, DNA methylation and chromatin state. Few cell-type marker genes are conserved across species, revealing a short list of candidate genes and regulatory mechanisms that are responsible for conserved features of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic classification allows us to use patch–seq (a combination of whole-cell patch-clamp recordings, RNA sequencing and morphological characterization) to identify corticospinal Betz cells from layer 5 in non-human primates and humans, and to characterize their highly specialized physiology and anatomy. These findings highlight the robust molecular underpinnings of cell-type diversity in M1 across mammals, and point to the genes and regulatory pathways responsible for the functional identity of cell types and their species-specific adaptations.

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.

Highlights d BARseq uses in situ sequencing to map neuronal projections with high throughput d BARseq correlates neuronal projections to gene expression and Cre-labeling d BARseq recapitulates known organization of projections in auditory cortex d BARseq reveals distinct projections of transcriptionally defined IT subtypes

Single cell transcriptomics has transformed the characterization of brain cell identity by providing quantitative molecular signatures for large, unbiased samples of brain cell populations. With the proliferation of taxonomies based on individual datasets, a major challenge is to integrate and validate results toward defining biologically meaningful cell types. We used a battery of single-cell transcriptome and epigenome measurements generated by the BRAIN Initiative Cell Census Network (BICCN) to comprehensively assess the molecular signatures of cell types in the mouse primary motor cortex (MOp). We further developed computational and statistical methods to integrate these multimodal data and quantitatively validate the reproducibility of the cell types. The reference atlas, based on more than 600,000 high quality single-cell or -nucleus samples assayed by six molecular modalities, is a comprehensive molecular account of the diverse neuronal and non-neuronal cell types in MOp.Collectively, our study indicates that the mouse primary motor cortex contains over 55 neuronal cell types that are highly replicable across analysis methods, sequencing technologies, and modalities. We find many concordant multimodal markers for each cell type, as well as thousands of genes and gene regulatory elements with discrepant transcriptomic and epigenomic signatures. These data highlight the complex molecular regulation of brain cell types and will directly enable design of reagents to target specific MOp cell types for functional analysis. IntroductionNeural circuits are characterized by extraordinary diversity of their cellular components 1,2 . Single-cell molecular assays, especially transcriptomic measurements by RNA-Seq, have accelerated the discovery and characterization of cell types across brain regions and in diverse species. Recent advances include single-cell transcriptome datasets with >10 5 individual cells, identifying hundreds of neuronal and non-neuronal cell types across the mouse nervous system 3-5 . As the number of profiled cells grows into the millions, a key question is whether these data will converge toward a comprehensive and coherent taxonomy of cell types with broad utility for organizing knowledge of brain cells and their function. Data from different modalities, including transcriptomic and epigenomic data, must be cross-referenced and integrated to establish robust and consistent cell type classifications.Although a comprehensive atlas should incorporate anatomical and physiological information, the high throughput of single cell sequencing assays makes integration of molecular data a particularly urgent challenge. A rigorous and reproducible consensus molecular atlas of brain cell types would drive progress across modalities, including obtaining functional information.Single cell sequencing technologies can measure multiple molecular signatures of cell identity. The core molecular identity of a cell is largely established during development and maintained by a combination of gene regulatory proteins...

An essential step toward understanding brain function is to establish a structural framework with cellular resolution on which multi-scale datasets spanning molecules, cells, circuits and systems can be integrated and interpreted1. Here, as part of the collaborative Brain Initiative Cell Census Network (BICCN), we derive a comprehensive cell type-based anatomical description of one exemplar brain structure, the mouse primary motor cortex, upper limb area (MOp-ul). Using genetic and viral labelling, barcoded anatomy resolved by sequencing, single-neuron reconstruction, whole-brain imaging and cloud-based neuroinformatics tools, we delineated the MOp-ul in 3D and refined its sublaminar organization. We defined around two dozen projection neuron types in the MOp-ul and derived an input–output wiring diagram, which will facilitate future analyses of motor control circuitry across molecular, cellular and system levels. This work provides a roadmap towards a comprehensive cellular-resolution description of mammalian brain architecture.

23The primary motor cortex (M1) is essential for voluntary fine motor control and is functionally conserved 24 across mammals. Using high-throughput transcriptomic and epigenomic profiling of over 450,000 single 25 nuclei in human, marmoset monkey, and mouse, we demonstrate a broadly conserved cellular makeup 26 of this region, whose similarity mirrors evolutionary distance and is consistent between the 27 transcriptome and epigenome. The core conserved molecular identity of neuronal and non-neuronal 28 types allowed the generation of a cross-species consensus cell type classification and inference of 29 conserved cell type properties across species. Despite overall conservation, many species 30 specializations were apparent, including differences in cell type proportions, gene expression, DNA 31 methylation, and chromatin state. Few cell type marker genes were conserved across species, 32 providing a short list of candidate genes and regulatory mechanisms responsible for conserved features 33 of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic 34 classification allowed the Patch-seq identification of layer 5 (L5) corticospinal Betz cells in non-human 35 primate and human and characterization of their highly specialized physiology and anatomy. These 36 findings highlight the robust molecular underpinnings of cell type diversity in M1 across mammals and 37 point to the genes and regulatory pathways responsible for the functional identity of cell types and their 38 species-specific adaptations. 39 40 distinguished on the basis of regions of open chromatin or DNA methylation 5,9,10 . Furthermore, several 48 recent studies have shown that transcriptomically-defined cell types can be aligned across species 2,11-49 13 , indicating that these methods provide a path to quantitatively study evolutionary conservation and 50 divergence at the level of cell types. However, application of these methods has been highly 51 fragmented to date. Human and mouse comparisons have been performed in different cortical regions, 52 using single-cell (with biases in cell proportions) versus single-nucleus (with biases in transcript 53 makeup) analysis, and most single-cell transcriptomic and epigenomic studies have been performed 54 independently. 55 56The primary motor cortex (MOp in mouse, M1 in human and non-human primates, all referred to as M1 57 herein) provides an ideal cortical region to address questions about cellular evolution in rodents and 58 primates by integrating these approaches. Unlike the primary visual cortex (V1), which is highly 59 specialized in primates, or frontal and temporal association areas, whose homologues in rodents 60 remain poorly defined, M1 is essential for fine motor control and is functionally conserved across 61 placental mammals. M1 is an agranular cortex, lacking a defined L4, although neurons with L4-like 62properties have been described 14 . L5 of carnivore and primate M1 contains exceptionally large 63 "giganto-cellular" corticospinal neurons (Betz c...

SummaryUnderstanding neural circuits requires deciphering the interactions of myriad cell types defined by anatomy, spatial organization, gene expression, and functional properties. Resolving these cell types requires both single neuron resolution and high-throughput, a combination that is challenging to achieve with conventional anatomical methods. Here we introduce BARseq, a method for mapping the projections of thousands of spatially resolved neurons by combining the high throughput of DNA sequencing with the high spatial resolution of microscopy. We used BARseq to determine the projections of 1309 neurons in mouse auditory cortex to 11 targets. We observed 264 distinct projection patterns. Hierarchical clustering confirmed the major classical classes of projection neurons, segregated across cortical laminae. Further analysis revealed 25 subclasses, largely intermingled across laminae. Unlike cell types defined by gene expression, projection subclasses beyond the major classes were rarely enriched in specific laminae, raising the possibility that the organization of projection patterns in mature neurons is orthogonal to that of gene expression. In this way, downstream brain areas could receive information from multiple cell types through parallel pathways. By sequencing in situ, BARseq has the potential to bridge anatomical, transcriptomic, functional, and other approaches at single neuron resolution with high throughput, and thereby offer unprecedented insight of the structure and function of a neural circuit.. CC-BY-NC 4.0 International license It is made available under a was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint (which . http://dx.doi.org/10.1101/294637 doi: bioRxiv preprint first posted online Apr. 3, 2018; 2 An important challenge in neuroscience is to relate diverse characteristics of single neurons, in a co-registered fashion, within single brains 1 . Even simultaneous co-registration of two characteristics can be challenging, and has led to insights about the functional organization of neural circuits 2,3 . A high-throughput method capable of such multimodal co-registration would yield a "Rosetta Brain"-an integrative dataset that could constrain theoretical efforts to bridge across levels of structure and function in the nervous system 1 .As a first step toward this goal we began with MAPseq 4,5 (Fig. 1A, left), a sequencing-based method capable of mapping long-range projections of thousands of single neurons in a single brain. MAPseq achieves multiplexing by uniquely labeling individual neurons with random RNA sequences, or "barcodes". Because MAPseq, like most other sequencing methods, relies on tissue homogenization, it cannot resolve the spatial organization of the neuronal somata. This spatial organization, however, potentially allows the registration of distinct neuronal characteristics. We therefore sought to develop a method that would preserve the spatial organization of barc...