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.

Neuronal cell types are classically defined by their molecular properties, anatomy and functions. Although recent advances in single-cell genomics have led to high-resolution molecular characterization of cell type diversity in the brain1, neuronal cell types are often studied out of the context of their anatomical properties. To improve our understanding of the relationship between molecular and anatomical features that define cortical neurons, here we combined retrograde labelling with single-nucleus DNA methylation sequencing to link neural epigenomic properties to projections. We examined 11,827 single neocortical neurons from 63 cortico-cortical and cortico-subcortical long-distance projections. Our results showed unique epigenetic signatures of projection neurons that correspond to their laminar and regional location and projection patterns. On the basis of their epigenomes, intra-telencephalic cells that project to different cortical targets could be further distinguished, and some layer 5 neurons that project to extra-telencephalic targets (L5 ET) formed separate clusters that aligned with their axonal projections. Such separation varied between cortical areas, which suggests that there are area-specific differences in L5 ET subtypes, which were further validated by anatomical studies. Notably, a population of cortico-cortical projection neurons clustered with L5 ET rather than intra-telencephalic neurons, which suggests that a population of L5 ET cortical neurons projects to both targets. We verified the existence of these neurons by dual retrograde labelling and anterograde tracing of cortico-cortical projection neurons, which revealed axon terminals in extra-telencephalic targets including the thalamus, superior colliculus and pons. These findings highlight the power of single-cell epigenomic approaches to connect the molecular properties of neurons with their anatomical and projection properties.

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25Neuronal cell types are classically defined by their molecular properties, anatomy, and functions. 26 While recent advances in single-cell genomics have led to high-resolution molecular 27 characterization of cell type diversity in the brain, neuronal cell types are often studied out of the 28 context of their anatomical properties. To better understand the relationship between molecular 29 and anatomical features defining cortical neurons, we combined retrograde labeling with single-30 nucleus DNA methylation sequencing to link epigenomic properties of cell types to neuronal 31 projections. We examined 11,827 single neocortical neurons from 63 cortico-cortical (CC) and 32 cortico-subcortical long-distance projections. Our results revealed unique epigenetic signatures of 33 projection neurons that correspond to their laminar and regional location and projection patterns. 34 Based on their epigenomes, intra-telencephalic (IT) cells projecting to different cortical targets 35 could be further distinguished, and some layer 5 neurons projecting to extra-telencephalic targets 36 (L5-ET) formed separate subclusters that aligned with their axonal projections. Such separation 37 varied between cortical areas, suggesting area-specific differences in L5-ET subtypes, which were 38 further validated by anatomical studies. Interestingly, a population of CC projection neurons 39 clustered with L5-ET rather than IT neurons, suggesting a population of L5-ET cortical neurons 40 projecting to both targets (L5-ET+CC). We verified the existence of these neurons by labeling the 41 axon terminals of CC projection neurons and observed clear labeling in ET targets including 42 thalamus, superior colliculus, and pons. These findings highlight the power of single-cell 43 epigenomic approaches to connect the molecular properties of neurons with their anatomical and 44 projection properties. 45Main Text 46 The mammalian brain is a complex system consisting of multiple types of neurons with diverse 47 morphology, physiology, connections, gene expression, and epigenetic modifications. Identifying 48 brain cell types and how they interact is critical to understanding the neural mechanisms that 49 underlie brain function. During the last decade, these efforts have been facilitated by the advent of 50 molecular, genetic and viral tools for allowing genetic access and manipulation of specific cell 51 types 1,2 . Available evidence suggests, however, that there are far more cell types than can presently 52 be accessed genetically. Moreover, the correspondence between molecular cell types and neuronal 53 populations defined by connectivity are largely unknown. 55Single-cell technologies deconvolve mammalian brains into molecularly defined cell clusters 56 corresponding to putative neuron types 3 . Among these technologies, single nucleus methylation 57 sequencing (snmC-Seq) applied to neurons has the unique ability to allow identification of 58 potential regulatory elements and a prediction of gene expression in the same cells. This i...