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The neocortex is disproportionately expanded in human compared with mouse1,2, both in its total volume relative to subcortical structures and in the proportion occupied by supragranular layers composed of neurons that selectively make connections within the neocortex and with other telencephalic structures. Single-cell transcriptomic analyses of human and mouse neocortex show an increased diversity of glutamatergic neuron types in supragranular layers in human neocortex and pronounced gradients as a function of cortical depth3. Here, to probe the functional and anatomical correlates of this transcriptomic diversity, we developed a robust platform combining patch clamp recording, biocytin staining and single-cell RNA-sequencing (Patch-seq) to examine neurosurgically resected human tissues. We demonstrate a strong correspondence between morphological, physiological and transcriptomic phenotypes of five human glutamatergic supragranular neuron types. These were enriched in but not restricted to layers, with one type varying continuously in all phenotypes across layers 2 and 3. The deep portion of layer 3 contained highly distinctive cell types, two of which express a neurofilament protein that labels long-range projection neurons in primates that are selectively depleted in Alzheimer’s disease4,5. Together, these results demonstrate the explanatory power of transcriptomic cell-type classification, provide a structural underpinning for increased complexity of cortical function in humans, and implicate discrete transcriptomic neuron types as selectively vulnerable in disease., Combined patch clamp recording, biocytin staining and single-cell RNA-sequencing of human neurocortical neurons shows an expansion of glutamatergic neuron types relative to mouse that characterizes the greater complexity of the human neocortex.

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., An examination of motor cortex in humans, marmosets and mice reveals a generally conserved cellular makeup that is likely to extend to many mammalian species, but also differences in gene expression, DNA methylation and chromatin state that lead to species-dependent specializations.

Understanding the diversity of cell types in the brain has been an enduring challenge and requires detailed characterization of individual neurons in multiple dimensions. To systematically profile morpho-electric properties of mammalian neurons, we established a single-cell characterization pipeline using standardized patch-clamp recordings in brain slices and biocytin-based neuronal reconstructions. We built a publicly accessible online database, the Allen Cell Types Database, to display these datasets. Intrinsic physiological properties were measured from 1,938 neurons from the adult laboratory mouse visual cortex, morphological properties were measured from 461 reconstructed neurons, and 452 neurons had both measurements available. Quantitative features were used to classify neurons into distinct types using unsupervised methods. We established a taxonomy of morphologically and electrophysiologically defined cell types for this region of the cortex, with 17 electrophysiological types, 38 morphological types and 46 morpho-electric types. There was good correspondence with previously defined transcriptomic cell types and subclasses using the same transgenic mouse lines.

To elucidate cortical microcircuit structure and synaptic properties we present a unique, extensive, and public synaptic physiology dataset and analysis platform. Through its application, we reveal principles that relate cell type to synapse properties and intralaminar circuit organization in the mouse and human cortex. The dynamics of excitatory synapses align with the postsynaptic cell subclass, whereas inhibitory synapse dynamics partly align with presynaptic cell subclass but with considerable overlap. Despite these associations, synaptic properties are heterogeneous in most subclass to subclass connections. The two main axes of heterogeneity are strength and variability. Cell subclasses divide along the variability axis, while the strength axis accounts for significant heterogeneity within the subclass. In human cortex, excitatory to excitatory synapse dynamics are distinct from those in mouse and short-term plasticity varies with depth across layers 2 and 3. With a novel connectivity analysis that enables fair comparisons between circuit elements, we find that intralaminar connection probability among cell subclasses exhibits a strong layer dependence.These and other findings combined with the analysis platform create new opportunities for the neuroscience community to advance our understanding of cortical microcircuits.

In the neocortex, subcerebral axonal projections originate largely from layer 5 (L5) extratelencephalic-projecting (ET) neurons. The highly distinctive morpho-electric properties of these neurons have mainly been described in rodents, where ET neurons can be labeled by retrograde tracers or transgenic lines. Similar labeling strategies are not possible in the human neocortex, rendering the translational relevance of findings in rodents unclear. We leveraged the recent discovery of a transcriptomically-defined L5 ET neuron type to study the properties of human L5 ET neurons in neocortical brain slices derived from neurosurgeries. Patch-seq recordings, where transcriptome, physiology and morphology are assayed from the same cell, revealed many conserved morpho-electric properties of human and rodent L5 ET neurons. Divergent properties were also apparent but were often smaller than differences between cell types within these two species. These data suggest a conserved function of L5 ET neurons in the neocortical hierarchy, but also highlight marked phenotypic divergence possibly related to functional specialization of human neocortex.

Dendritic and axonal morphology reflects the input and output of neurons and is a defining feature of neuronal types1,2, yet our knowledge of its diversity remains limited. Here, to systematically examine complete single-neuron morphologies on a brain-wide scale, we established a pipeline encompassing sparse labelling, whole-brain imaging, reconstruction, registration and analysis. We fully reconstructed 1,741 neurons from cortex, claustrum, thalamus, striatum and other brain regions in mice. We identified 11 major projection neuron types with distinct morphological features and corresponding transcriptomic identities. Extensive projectional diversity was found within each of these major types, on the basis of which some types were clustered into more refined subtypes. This diversity follows a set of generalizable principles that govern long-range axonal projections at different levels, including molecular correspondence, divergent or convergent projection, axon termination pattern, regional specificity, topography, and individual cell variability. Although clear concordance with transcriptomic profiles is evident at the level of major projection type, fine-grained morphological diversity often does not readily correlate with transcriptomic subtypes derived from unsupervised clustering, highlighting the need for single-cell cross-modality studies. Overall, our study demonstrates the crucial need for quantitative description of complete single-cell anatomy in cell-type classification, as single-cell morphological diversity reveals a plethora of ways in which different cell types and their individual members may contribute to the configuration and function of their respective circuits., Sparse labelling and whole-brain imaging are used to reconstruct and classify brain-wide complete morphologies of 1,741 individual neurons in the mouse brain, revealing a dependence on both brain region and transcriptomic profile.

The neocortex is disproportionately expanded in human compared to mouse, both in its total volume relative to subcortical structures and in the proportion occupied by supragranular layers that selectively make connections within the cortex and other telencephalic structures. Single-cell transcriptomic analyses of human and mouse cortex show an increased diversity of glutamatergic neuron types in supragranular cortex in human and pronounced gradients as a function of cortical depth. To probe the functional and anatomical correlates of this transcriptomic diversity, we describe a robust Patch-seq platform using neurosurgically-resected human tissues. We characterize the morphological and physiological properties of five transcriptomically defined human glutamatergic supragranular neuron types. Three of these types have properties that are specialized compared to the more homogeneous properties of transcriptomically defined homologous mouse neuron types. The two remaining supragranular neuron types, located exclusively in deep layer 3, do not have clear mouse homologues in supragranular cortex but are transcriptionally most similar to deep layer mouse intratelencephalic-projecting neuron types. Furthermore, we reveal the transcriptomic types in deep layer 3 that express high levels of non-phosphorylated heavy chain neurofilament protein that label long-range neurons known to be selectively depleted in Alzheimer’s disease. Together, these results demonstrate the power of transcriptomic cell type classification, provide a mechanistic underpinning for increased complexity of cortical function in human cortical evolution, and implicate discrete transcriptomic cell types as selectively vulnerable in disease.

Neurons are frequently classified into distinct groups or cell types on the basis of structural, physiological, or genetic attributes. To better constrain the definition of neuronal cell types, we characterized the transcriptomes and intrinsic physiological properties of over 3,700 GABAergic mouse visual cortical neurons and reconstructed the local morphologies of 350 of those neurons. We found that most transcriptomic types (t-types) occupy specific laminar positions within mouse visual cortex, and many of those t-types exhibit consistent electrophysiological and morphological features. We observed that these properties could vary continuously between t-types, which limited the ability to predict specific t-types from other data modalities. Despite that, the data support the presence of at least 20 interneuron met-types that have congruent morphological, electrophysiological, and transcriptomic properties.HighlightsPatch-seq data obtained from >3,700 GABAergic cortical interneuronsComprehensive characterization of morpho-electric features of transcriptomic types20 interneuron met-types that have congruent properties across data modalitiesDifferent Sst met-types preferentially innervate different cortical layers

Neurons are frequently classified into distinct groups or cell types on the basis of structural, physiological, or genetic attributes. To better constrain the definition of neuronal cell types, we characterized the transcriptomes and intrinsic physiological properties of over 3,700 GABAergic mouse visual cortical neurons and reconstructed the local morphologies of 350 of those neurons. We found that most transcriptomic types (t-types) occupy specific laminar positions within mouse visual cortex, and many of those t-types exhibit consistent electrophysiological and morphological features. We observed that these properties could vary continuously between t- types, which limited the ability to predict specific t-types from other data modalities. Despite that, the data support the presence of at least 20 interneuron met-types that have congruent morphological, electrophysiological, and transcriptomic properties.

In the neocortex, subcerebral axonal projections originate largely from layer 5 (L5) extratelencephalic-projecting (ET) neurons. The unique morpho-electric properties of these neurons have been mainly described in rodents, where retrograde tracers or transgenic lines can label them. Similar labeling strategies are infeasible in the human neocortex, rendering the translational relevance of findings in rodents unclear. We leveraged the recent discovery of a transcriptomically defined L5 ET neuron type to study the properties of human L5 ET neurons in neocortical brain slices derived from neurosurgeries. Patch-seq recordings, where transcriptome, physiology, and morphology were assayed from the same cell, revealed many conserved morpho-electric properties of human and rodent L5 ET neurons. Divergent properties were often subtler than differences between L5 cell types within these two species. These data suggest a conserved function of L5 ET neurons in the neocortical hierarchy but also highlight phenotypic divergence possibly related to functional specialization of human neocortex.

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.

Neurons are frequently classified into distinct types on the basis of structural, physiological, or genetic attributes. To better constrain the definition of neuronal cell types, we characterized the transcriptomes and intrinsic physiological properties of over 4,200 mouse visual cortical GABAergic interneurons and reconstructed the local morphologies of 517 of those neurons. We find that most transcriptomic types (t-types) occupy specific laminar positions within visual cortex, and, for most types, the cells mapping to a t-type exhibit consistent electrophysiological and morphological properties. These properties display both discrete and continuous variation among t-types. Through multimodal integrated analysis, we define 28 met-types that have congruent morphological, electrophysiological, and transcriptomic properties and robust mutual predictability. We identify layer-specific axon innervation pattern as a defining feature distinguishing different met-types. These met-types represent a unified definition of cortical GABAergic interneuron types, providing a systematic framework to capture existing knowledge and bridge future analyses across different modalities.

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

Understanding the diversity of cell types in the brain has been an enduring challenge and requires detailed characterization of individual neurons in multiple dimensions. To profile morpho-electric properties of mammalian neurons systematically, we established a single cell characterization pipeline using standardized patch clamp recordings in brain slices and biocytin-based neuronal reconstructions. We built a publicly-accessible online database, the Allen Cell Types Database, to display these data sets. Intrinsic physiological and morphological properties were measured from over 1,800 neurons from the adult laboratory mouse visual cortex. Quantitative features were used to classify neurons into distinct types using unsupervised methods. We establish a taxonomy of morphologically- and electrophysiologically-defined cell types for this region of cortex with 17 e-types and 35 m-types, as well as an initial correspondence with previously-defined transcriptomic cell types using the same transgenic mouse lines.

The neurogenic potential of the subgranular zone (SGZ) of the hippocampal dentate gyrus is likely to be regulated by molecular cues arising from its complex heterogeneous cellular environment. Through transcriptome analysis using laser microdissection coupled with DNA microarrays, in combination with analysis of genome-wide in situ hybridization data, we identified 363 genes selectively enriched in adult mouse SGZ. These genes reflect expression in the different constituent cell types, including progenitor and dividing cells, immature granule cells, astrocytes, oligodendrocytes and GABAergic interneurons. Similar transcriptional profiling in the rhesus monkey dentate gyrus across postnatal development identified a highly overlapping set of SGZ-enriched genes, which can be divided based on temporal profiles to reflect maturation of glia versus granule neurons. Furthermore, we identified a neurogenesis-related gene network with decreasing postnatal expression that is highly correlated with the declining number of proliferating cells in dentate gyrus over postnatal development. Many of the genes in this network showed similar postnatal downregulation in mouse, suggesting a conservation of molecular mechanisms underlying developmental and adult neurogenesis in rodents and primates. Conditional deletion of Sox4 and Sox11, encoding two neurogenesis-related transcription factors central in this network, produces a mouse with no hippocampus, confirming the crucial role for these genes in regulating hippocampal neurogenesis.

The underlying pathology of schizophrenia (SZ) is likely as heterogeneous as its symptomatology. A variety of cortical and subcortical regions, including the prefrontal cortex, have been implicated in its pathology, and a number of genes have been identified as risk factors for disease development. We used in situ hybridization (ISH) to examine the expression of 58 genes in the dorsolateral prefrontal cortex (DLPFC, comprised of Brodmann areas 9 and 46) from 19 individuals with a premorbid diagnosis of SZ and 33 control individuals. Genes were selected based on: (1) previous identification as risk factors for SZ; (2) cell type markers or (3) laminar markers. Cell density and staining intensity were compared in the DLPFC, as well as separately in Brodmann areas 9 and 46. The expression patterns of a variety of genes, many of which are associated with the GABAergic system, were altered in SZ when compared with controls. Additional genes, including C8orf79 and NR4A2, showed alterations in cell density or staining intensity between the groups, highlighting the need for additional studies. Alterations were, with only a few exceptions, limited to Brodmann area 9, suggesting regional specificity of pathology in the DLPFC. Our results agree with previous studies on the GABAergic involvement in SZ, and suggest that areas 9 and 46 may be differentially affected in the disease. This study also highlights additional genes that may be altered in SZ, and indicates that these potentially interesting genes can be identified by ISH and high-throughput image analysis techniques.

Neuroanatomically precise, genome-wide maps of transcript distributions are critical resources to complement genomic sequence data and to correlate functional and genetic brain architecture. Here we describe the generation and analysis of a transcriptional atlas of the adult human brain, comprising extensive histological analysis and comprehensive microarray profiling of ~900 neuroanatomically precise subdivisions in two individuals. Transcriptional regulation varies enormously by anatomical location, with different regions and their constituent cell types displaying robust molecular signatures that are highly conserved between individuals. Analysis of differential gene expression and gene co-expression relationships demonstrates that brain-wide variation strongly reflects the distributions of major cell classes such as neurons, oligodendrocytes, astrocytes and microglia. Local neighbourhood relationships between fine anatomical subdivisions are associated with discrete neuronal subtypes and genes involved with synaptic transmission. The neocortex displays a relatively homogeneous transcriptional pattern, but with distinct features associated selectively with primary sensorimotor cortices and with enriched frontal lobe expression. Notably, the spatial topography of the neocortex is strongly reflected in its molecular topography— the closer two cortical regions, the more similar their transcriptomes. This freely accessible online data resource forms a high-resolution transcriptional baseline for neurogenetic studies of normal and abnormal human brain function.

The molecular and cellular landscape of glioblastoma is highly complex and its relationship to histologic features routinely used for diagnosis is unclear. To investigate this relationship, we generated an anatomic transcriptional atlas of human glioblastoma, adopting a highly-systematized, large-scale, histology-driven approach to the characterization of anatomic features and cancer stem cell populations. The atlas of 42 tumors consists of several data modalities, including 270 transcriptomes, ∼11,500 semi-annotated pathology images registered to ∼23,000 in situ hybridization gene expression images, ∼400 MRI scans, tumor-derived cell lines and xenografts, and supporting longitudinal clinical information. We show that gene expression varies considerably by anatomic feature and cancer stem cell population, exhibiting molecular signatures that are more highly conserved within tumors than between tumors, and reflecting the cell types and microenvironment of each feature and population. These freely-accessible online data resources of the Ivy Glioblastoma Atlas Project (Ivy GAP), one for the fully-annotated anatomic transcriptional atlas (http://glioblastoma.alleninstitute.org/), and one for the detailed clinical and genomic data (http://ivygap.org/), constitute a unique platform for exploring the anatomic and genetic basis of glioblastoma at the cellular and molecular levels. This project was supported by grants from the Ben and Catherine Ivy Foundation to the Allen Institute (PI, RBP) and Swedish Neuroscience Institute (PIs, GDF and NS).