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Synaptic transmission constitutes the primary mode of communication between neurons. It is extensively studied in rodent but not human neocortex. We characterized synaptic transmission between pyramidal neurons in layers 2 and 3 using neurosurgically resected human middle temporal gyrus (MTG, Brodmann area 21), which is part of the distributed language circuitry. We find that local connectivity is comparable with mouse layer 2/3 connections in the anatomical homologue (temporal association area), but synaptic connections in human are 3-fold stronger and more reliable (0% vs 25% failure rates, respectively). We developed a theoretical approach to quantify properties of spinous synapses showing that synaptic conductance and voltage change in human dendritic spines are 3–4-folds larger compared with mouse, leading to significant NMDA receptor activation in human unitary connections. This model prediction was validated experimentally by showing that NMDA receptor activation increases the amplitude and prolongs decay of unitary excitatory postsynaptic potentials in human but not in mouse connections. Since NMDA-dependent recurrent excitation facilitates persistent activity (supporting working memory), our data uncovers cortical microcircuit properties in human that may contribute to language processing in MTG.

Delivering genes to and across the brain vasculature efficiently and specifically across species remains a critical challenge for addressing neurological diseases. We have evolved adeno-associated virus (AAV9) capsids into vectors that transduce brain endothelial cells specifically and efficiently following systemic administration in wild-type mice with diverse genetic backgrounds, and in rats. These AAVs also exhibit superior transduction of the CNS across non-human primates (marmosets and rhesus macaques), and in ex vivo human brain slices, although the endothelial tropism is not conserved across species. The capsid modifications translate from AAV9 to other serotypes such as AAV1 and AAV-DJ, enabling serotype switching for sequential AAV administration in mice. We demonstrate that the endothelial-specific mouse capsids can be used to genetically engineer the blood-brain barrier by transforming the mouse brain vasculature into a functional biofactory. We apply this approach to Hevin knockout mice, where AAV-X1-mediated ectopic expression of the synaptogenic protein Sparcl1/Hevin in brain endothelial cells rescued synaptic deficits.

Alzheimer’s disease (AD) is the most common cause of dementia in older adults. Neuropathological and imaging studies have demonstrated a progressive and stereotyped accumulation of protein aggregates, but the underlying molecular and cellular mechanisms driving AD progression and vulnerable cell populations affected by disease remain coarsely understood. The current study harnesses single cell and spatial genomics tools and knowledge from the BRAIN Initiative Cell Census Network to understand the impact of disease progression on middle temporal gyrus cell types. We used image-based quantitative neuropathology to place 84 donors spanning the spectrum of AD pathology along a continuous disease pseudoprogression score and multiomic technologies to profile single nuclei from each donor, mapping their transcriptomes, epigenomes, and spatial coordinates to a common cell type reference with unprecedented resolution. Temporal analysis of cell-type proportions indicated an early reduction of Somatostatin-expressing neuronal subtypes and a late decrease of supragranular intratelencephalic-projecting excitatory and Parvalbumin-expressing neurons, with increases in disease-associated microglial and astrocytic states. We found complex gene expression differences, ranging from global to cell type-specific effects. These effects showed different temporal patterns indicating diverse cellular perturbations as a function of disease progression. A subset of donors showed a particularly severe cellular and molecular phenotype, which correlated with steeper cognitive decline. We have created a freely available public resource to explore these data and to accelerate progress in AD research atSEA-AD.org.

Massive single-cell profiling efforts have accelerated our discovery of the cellular composition of the human body while at the same time raising the need to formalize this new knowledge. Here, we discuss current efforts to harmonize and integrate different sources of annotations of cell types and states into a reference cell ontology. We illustrate with examples how a unified ontology can consolidate and advance our understanding of cell types across scientific communities and biological domains.

Neurons in the developing brain undergo extensive structural refinement as nascent circuits adopt their mature form. This physical transformation of neurons is facilitated by the engulfment and degradation of axonal branches and synapses by surrounding glial cells, including microglia and astrocytes. However, the small size of phagocytic organelles and the complex, highly ramified morphology of glia have made it difficult to define the contribution of these and other glial cell types to this crucial process. Here, we used large-scale, serial section transmission electron microscopy (TEM) with computational volume segmentation to reconstruct the complete 3D morphologies of distinct glial types in the mouse visual cortex, providing unprecedented resolution of their morphology and composition. Unexpectedly, we discovered that the fine processes of oligodendrocyte precursor cells (OPCs), a population of abundant, highly dynamic glial progenitors, frequently surrounded small branches of axons. Numerous phagosomes and phagolysosomes (PLs) containing fragments of axons and vesicular structures were present inside their processes, suggesting that OPCs engage in axon pruning. Single-nucleus RNA sequencing from the developing mouse cortex revealed that OPCs express key phagocytic genes at this stage, as well as neuronal transcripts, consistent with active axon engulfment. Although microglia are thought to be responsible for the majority of synaptic pruning and structural refinement, PLs were ten times more abundant in OPCs than in microglia at this stage, and these structures were markedly less abundant in newly generated oligodendrocytes, suggesting that OPCs contribute substantially to the refinement of neuronal circuits during cortical development.

Human intelligence is a highly heritable trait, and GWAS have yielded numerous associated genes. These genes overlap with human accelerated regions (HARs) implicated in human brain evolution and might act on the same biological processes. Here, we investigated whether genes associated with human cognition and HAR genes are similarly expressed in adult human cortical neurons and brain areas of cognition, and how their expression relates to neuronal function and structure. We find that these gene sets are preferentially expressed in L3 excitatory neurons in middle temporal gyrus (MTG). Furthermore, neurons with higher expression had larger dendrites and faster action potential kinetics, properties previously linked to intelligence. Finally, we identify a subset of genes associated with dendritic length, with predominantly synaptic functions and high abundance of HARs. Our results indicate that mechanisms underlying human brain evolution and interindividual differences in intelligence might share genetic origin and manifest in specific neuronal types.

The human brain contains an extraordinarily diverse set of neuronal and glial cell types. Recent advances in single cell transcriptomics have begun to delineate the cellular heterogeneity in different brain regions, but the transcriptional regulatory programs responsible for the identity and function of each brain cell type remain to be defined. Here, we carried out single nucleus ATAC-seq analysis to probe the open chromatin landscape from over 1.1 million cells in 42 brain regions of three neurotypical adult donors. Integrative analysis of the resulting data identified 107 distinct cell types and revealed the cell-type-specific usage of 544,735 candidate cis-regulatory DNA elements (cCREs) in the human genome. Nearly 1/3 of them displayed sequence conservation as well as chromatin accessibility in the mouse brain. On the other hand, nearly 40% cCREs were human specific, with chromatin accessibility associated with species-restricted gene expression. Interestingly, these human specific cCREs were enriched for distinct families of retrotransposable elements, which displayed cell-type-specific chromatin accessibility. We uncovered strong associations between specific brain cell types and neuropsychiatric disorders. We futher developed deep learning models to predict regulatory function of non-coding disease risk variants.

Human cortical interneurons have been challenging to study due to high diversity and lack of mature brain tissue platforms and genetic targeting tools. We employed rapid GABAergic neuron viral labeling plus unbiased Patch-seq sampling in brain slices to define the signature morpho-electric properties of GABAergic neurons in the human neocortex. Viral targeting greatly facilitated sampling of the SST subclass, including primate specialized double bouquet cells which mapped to two SST transcriptomic types. Multimodal analysis uncovered an SST neuron type with properties inconsistent with original subclass assignment; we instead propose reclassification into PVALB subclass. Our findings provide novel insights about functional properties of human cortical GABAergic neuron subclasses and types and highlight the essential role of multimodal annotation for refinement of emerging transcriptomic cell type taxonomies.One Sentence SummaryViral genetic labeling of GABAergic neurons in humanex vivobrain slices paired with Patch-seq recording yields an in-depth functional annotation of human cortical interneuron subclasses and types and highlights the essential role of multimodal functional annotation for refinement of emerging transcriptomic cell type taxonomies.

Variation in cortical cytoarchitecture is the basis for histology-based definition of cortical areas, such as Brodmann areas. Single cell transcriptomics enables higher-resolution characterization of cell types in human cortex, which we used to revisit the idea of the canonical cortical microcircuit and to understand functional areal specialization. Deeply sampled single nucleus RNA-sequencing of eight cortical areas spanning cortical structural variation showed highly consistent cellular makeup for 24 coarse cell subclasses. However, proportions of excitatory neuron subclasses varied strikingly, reflecting differences in intra- and extracortical connectivity across primary sensorimotor and association cortices. Astrocytes and oligodendrocytes also showed differences in laminar organization across areas. Primary visual cortex showed dramatically different organization, including major differences in the ratios of excitatory to inhibitory neurons, expansion of layer 4 excitatory neuron types and specialized inhibitory neurons. Finally, gene expression variation in conserved neuron subclasses predicts differences in synaptic function across areas. Together these results provide a refined cellular and molecular characterization of human cortical cytoarchitecture that reflects functional connectivity and predicts areal specialization.

Neocortical layer 1 (L1) is a site of convergence between pyramidal neuron dendrites and feedback axons where local inhibitory signaling can profoundly shape cortical processing. Evolutionary expansion of human neocortex is marked by distinctive pyramidal neuron types with extensive branching in L1, but whether L1 interneurons are similarly diverse is underexplored. Using patch-seq recordings from human neurosurgically resected tissues, we identified four transcriptomically defined subclasses, unique subtypes within those subclasses and additional types with no mouse L1 homologue. Compared with mouse, human subclasses were more strongly distinct from each other across all modalities. Accompanied by higher neuron density and more variable cell sizes compared with mouse, these findings suggest L1 is an evolutionary hotspot, reflecting the increasing demands of regulating the expanding human neocortical circuit.One Sentence SummaryUsing transcriptomics and morpho-electric analyses, we describe innovations in human neocortical layer 1 interneurons.

Single cell transcriptomic studies have identified a conserved set of neocortical cell types from small post-mortem cohorts. We extend these efforts by assessing cell type variation across 75 adult individuals undergoing epilepsy and tumor surgeries. Nearly all nuclei map to one of 125 robust cell types identified in middle temporal gyrus, but with varied abundances and gene expression signatures across donors, particularly in deep layer glutamatergic neurons. A minority of variance is explainable by known factors including donor identity and small contributions from age, sex, ancestry, and disease state. Genomic variation was significantly associated with variable expression of 150-250 genes for most cell types. Thus, human individuals display a highly consistent cellular makeup, but with significant variation reflecting donor characteristics, disease condition, and genetic regulation.One-Sentence SummaryInter-individual variation in human cortex is greatest for deep layer excitatory neurons and largely unexplainable by known factors.

Humans have unique cognitive abilities among primates, including language, but their molecular, cellular, and circuit substrates are poorly understood. We used comparative single nucleus transcriptomics in adult humans, chimpanzees, gorillas, rhesus macaques, and common marmosets from the middle temporal gyrus (MTG) to understand human-specific features of cellular and molecular organization. Human, chimpanzee, and gorilla MTG showed highly similar cell type composition and laminar organization, and a large shift in proportions of deep layer intratelencephalic-projecting neurons compared to macaque and marmoset. Species differences in gene expression generally mirrored evolutionary distance and were seen in all cell types, although chimpanzees were more similar to gorillas than humans, consistent with faster divergence along the human lineage. Microglia, astrocytes, and oligodendrocytes showed accelerated gene expression changes compared to neurons or oligodendrocyte precursor cells, indicating either relaxed evolutionary constraints or positive selection in these cell types. Only a few hundred genes showed human-specific patterning in all or specific cell types, and were significantly enriched near human accelerated regions (HARs) and conserved deletions (hCONDELS) and in cell adhesion and intercellular signaling pathways. These results suggest that relatively few cellular and molecular changes uniquely define adult human cortical structure, particularly by affecting circuit connectivity and glial cell function.

Serial-section electron microscopy (ssEM) is the method of choice for studying macroscopic biological samples at extremely high resolution in three dimensions. In the nervous system, nanometer-scale images are necessary to reconstruct dense neural wiring diagrams in the brain, so calledconnectomes. In order to use this data, consisting of up to 108individual EM images, it must be assembled into a volume, requiring seamless 2D stitching from each physical section followed by 3D alignment of the stitched sections. The high throughput of ssEM necessitates 2D stitching to be done at the pace of imaging, which currently produces tens of terabytes per day. To achieve this, we present a modular volume assembly software pipelineASAP(Assembly Stitching and Alignment Pipeline) that is scalable to datasets containing petabytes of data and parallelized to work in a distributed computational environment. The pipeline is built on top of theRender[18] services used in the volume assembly of the brain of adultDrosophila melanogaster[2]. It achieves high throughput by operating on the meta-data and transformations of each image stored in a database, thus eliminating the need to render intermediate output. ASAP is modular, allowing for easy incorporation of new algorithms without significant changes in the workflow. The entire software pipeline includes a complete set of tools for stitching, automated quality control, 3D section alignment, and final rendering of the assembled volume to disk. ASAP has been deployed for continuous processing of several large-scale datasets of the mouse visual cortex and human brain samples including one cubic millimeter of mouse visual cortex [1, 25] at speeds that exceed imaging. The pipeline also has multi-channel processing capabilities and can be applied to fluorescence and multi-modal datasets like array tomography.

The human cerebral cortex has tremendous cellular diversity. How different cell types are organized in the human cortex and how cellular organization varies across species remain unclear. In this study, we performed spatially resolved single-cell profiling of 4000 genes using multiplexed error-robust fluorescence in situ hybridization (MERFISH), identified more than 100 transcriptionally distinct cell populations, and generated a molecularly defined and spatially resolved cell atlas of the human middle and superior temporal gyrus. We further explored cell-cell interactions arising from soma contact or proximity in a cell type–specific manner. Comparison of the human and mouse cortices showed conservation in the laminar organization of cells and differences in somatic interactions across species. Our data revealed human-specific cell-cell proximity patterns and a markedly increased enrichment for interactions between neurons and non-neuronal cells in the human cortex.

With the advent of multiplex fluorescence in situ hybridization (FISH) and in situ RNA sequencing technologies, spatial transcriptomics analysis is advancing rapidly. Spatial transcriptomics provides spatial location and pattern information about cells in tissue sections at single cell resolution. Cell type classification of spatially-resolved cells can also be inferred by matching the spatial transcriptomics data to reference single cell RNA-sequencing (scRNA-seq) data with cell types determined by their gene expression profiles. However, robust cell type matching of the spatial cells is challenging due to the intrinsic differences in resolution between the spatial and scRNA-seq data. In this study, we systematically evaluated six computational algorithms for cell type matching across four spatial transcriptomics experimental protocols (MERFISH, smFISH, BaristaSeq, and ExSeq) conducted on the same mouse primary visual cortex (VISp) brain region. We find that while matching results of individual algorithms vary to some degree, they also show agreement to some extent. We present two ensembl meta-analysis strategies to combine the individual matching results and share the consensus matching results in the Cytosplore Viewer (https://viewer.cytosplore.org) for interactive visualization and data exploration. The consensus matching can also guide spot-based spatial data analysis using SSAM, allowing segmentation-free cell type assignment.

Methods to spatially profile the transcriptome are dominated by a trade-off between resolution and throughput. Here, we developed a method named EEL FISH that can rapidly process large tissue samples without compromising spatial resolution. By electrophoretically transferring RNA from a tissue section onto a capture surface, EEL speeds up data acquisition by reducing the amount of imaging needed, while ensuring that RNA molecules move straight down towards the surface, preserving single-cell resolution. We applied EEL on eight entire sagittal sections of the mouse brain and measured the expression patterns of up to 440 genes to reveal complex tissue organisation. Moreover, EEL enabled the study of challenging human samples by removing autofluorescent lipofuscin, so that we could study the spatial transcriptome of the human visual cortex. We provide full hardware specification, all protocols and complete software for instrument control, image processing, data analysis and visualization.

Methods to spatially profile the transcriptome are dominated by a trade-off between resolution and throughput. Here we develop a method named Enhanced ELectric Fluorescence in situ Hybridization (EEL FISH) that can rapidly process large tissue samples without compromising spatial resolution. By electrophoretically transferring RNA from a tissue section onto a capture surface, EEL speeds up data acquisition by reducing the amount of imaging needed, while ensuring that RNA molecules move straight down toward the surface, preserving single-cell resolution. We apply EEL on eight entire sagittal sections of the mouse brain and measure the expression patterns of up to 440 genes to reveal complex tissue organization. Moreover, EEL can be used to study challenging human samples by removing autofluorescent lipofuscin, enabling the spatial transcriptome of the human visual cortex to be visualized. We provide full hardware specifications, all protocols and complete software for instrument control, image processing, data analysis and visualization.

The human cerebral cortex has tremendous cellular diversity and complex cellular organization that are essential for brain function. How different types of cells are organized and interact with each other in the human cortex, and how cellular organizations and interaction patterns vary across species are, however, unclear. Here, we performed spatially resolved single-cell expression profiling of 4,000 genes in human middle and superior temporal gyrus using multiplexed error-robust fluorescence in situ hybridization (MERFISH). We identified >100 neuronal and non-neuronal cell populations with distinct transcriptional signatures, generated a molecularly defined and spatially resolved cell atlas of these brain regions, and analyzed cell-cell interactions in a cell-type-specific manner. Comparison with the mouse cortex showed conservation in the laminar organization of cells and substantial divergence in cell-cell interactions between human and mouse. Notably, our data revealed a drastic increase in interactions between neurons and non-neuronal cells in the human cortex, uncovered human-specific cell-cell interaction patterns, and identified potential ligand-receptor basis of microglia-neuron interactions.

Increasing interest in studies of prenatal human brain development, particularly using new single-cell genomics and anatomical technologies to create cell atlases, creates a strong need for accurate and detailed anatomical reference atlases. In this study, we present two cellular-resolution digital anatomical atlases for prenatal human brain at post-conceptional weeks (PCW) 15 and 21. Both atlases were annotated on sequential Nissl-stained sections covering brain-wide structures on the basis of combined analysis of cytoarchitecture, acetylcholinesterase staining and an extensive marker gene expression dataset. This high information content dataset allowed reliable and accurate demarcation of developing cortical and subcortical structures and their subdivisions. Furthermore, using the anatomical atlases as a guide, spatial expression of 37 and 5 genes from the brains respectively at PCW 15 and 21 was annotated, illustrating reliable marker genes for many developing brain structures. Finally, the present study uncovered several novel developmental features, such as the lack of an outer subventricular zone in the hippocampal formation and entorhinal cortex, and the apparent extension of both cortical (excitatory) and subcortical (inhibitory) progenitors into the prenatal olfactory bulb. These comprehensive atlases provide useful tools for visualization, segmentation, targeting, imaging and interpretation of brain structures of prenatal human brain, and for guiding and interpreting the next generation of cell census and connectome studies. This article is protected by copyright. All rights reserved.

The Patch-seq approach is a powerful variation of the patch-clamp technique that allows for the combined electrophysiological, morphological, and transcriptomic characterization of individual neurons. To generate Patch-seq datasets at scale, we identified and refined key factors that contribute to the efficient collection of high-quality data. We developed patch-clamp electrophysiology software with analysis functions specifically designed to automate acquisition with online quality control. We recognized the importance of extracting the nucleus for transcriptomic success and maximizing membrane integrity during nucleus extraction for morphology success. The protocol is generalizable to different species and brain regions, as demonstrated by capturing multimodal data from human and macaque brain slices. The protocol, analysis and acquisition software are compiled at https://githubcom/AllenInstitute/patchseqtools. This resource can be used by individual labs to generate data across diverse mammalian species and that is compatible with large publicly available Patch-seq datasets.

Single cell/nucleus RNA sequencing (scRNAseq) is emerging as an essential tool to unravel the phenotypic heterogeneity of cells in complex biological systems. While computational methods for scRNAseq cell type clustering have advanced, the ability to integrate datasets to identify common and novel cell types across experiments remains a challenge. Here, we introduce a cluster-to-cluster cell type matching method—FR-Match—that utilizes supervised feature selection for dimensionality reduction and incorporates shared information among cells to determine whether two cell type clusters share the same underlying multivariate gene expression distribution. FR-Match is benchmarked with existing cell-to-cell and cell-to-cluster cell type matching methods using both simulated and real scRNAseq data. FR-Match proved to be a stringent method that produced fewer erroneous matches of distinct cell subtypes and had the unique ability to identify novel cell phenotypes in new datasets. In silico validation demonstrated that the proposed workflow is the only self-contained algorithm that was robust to increasing numbers of true negatives (i.e. non-represented cell types). FR-Match was applied to two human brain scRNAseq datasets sampled from cortical layer 1 and full thickness middle temporal gyrus. When mapping cell types identified in specimens isolated from these overlapping human brain regions, FR-Match precisely recapitulated the laminar characteristics of matched cell type clusters, reflecting their distinct neuroanatomical distributions. An R package and Shiny application are provided at https://github.com/JCVenterInstitute/FRmatch for users to interactively explore and match scRNAseq cell type clusters with complementary visualization tools.

Neurons in the developing brain undergo extensive structural refinement as nascent circuits adopt their mature form1. This transformation is facilitated by the engulfment and degradation of excess axonal branches and inappropriate synapses by surrounding glial cells, including microglia and astrocytes2,3. However, the small size of phagocytic organelles and the complex, highly ramified morphology of glia has made it difficult to determine the contribution of these and other glial cell types to this process. Here, we used large scale, serial electron microscopy (ssEM) with computational volume segmentation to reconstruct the complete 3D morphologies of distinct glial types in the mouse visual cortex. Unexpectedly, we discovered that the fine processes of oligodendrocyte precursor cells (OPCs), a population of abundant, highly dynamic glial progenitors4, frequently surrounded terminal axon branches and included numerous phagolysosomes (PLs) containing fragments of axons and presynaptic terminals. Single- nucleus RNA sequencing indicated that cortical OPCs express key phagocytic genes, as well as neuronal transcripts, consistent with active axonal engulfment. PLs were ten times more abundant in OPCs than in microglia in P36 mice, and declined with age and lineage progression, suggesting that OPCs contribute very substantially to refinement of neuronal circuits during later phases of cortical development.

Neurons in the developing brain undergo extensive structural refinement as nascent circuits adopt their mature form1. This transformation is facilitated by the engulfment and degradation of excess axonal branches and inappropriate synapses by surrounding glial cells, including microglia and astrocytes2,3. However, the small size of phagocytic organelles and the complex, highly ramified morphology of glia has made it difficult to determine the contribution of these and other glial cell types to this process. Here, we used large scale, serial electron microscopy (ssEM) with computational volume segmentation to reconstruct the complete 3D morphologies of distinct glial types in the mouse visual cortex. Unexpectedly, we discovered that the fine processes of oligodendrocyte precursor cells (OPCs), a population of abundant, highly dynamic glial progenitors4, frequently surrounded terminal axon branches and included numerous phagolysosomes (PLs) containing fragments of axons and presynaptic terminals. Single- nucleus RNA sequencing indicated that cortical OPCs express key phagocytic genes, as well as neuronal transcripts, consistent with active axonal engulfment. PLs were ten times more abundant in OPCs than in microglia in P36 mice, and declined with age and lineage progression, suggesting that OPCs contribute very substantially to refinement of neuronal circuits during later phases of cortical development.

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.

The expansion of supragranular cortical layers is thought to have enabled evolutionary development of human cognition and language. However, whether increased volume of supragranular cortical layers can actually support greater cognitive and language abilities in humans has not been demonstrated. Here, we find that subjects with higher general and verbal intelligence test (VIQ) scores have selectively expanded layers 2 and 3 only in the left temporal cortex, an area associated with language and IQ-test performance. This expansion is accompanied by lower neuron densities and larger cell-body size. Furthermore, individuals with higher VIQ scores had neurons with larger dendritic trees in left temporal cortex, potentially impacting their function. Indeed, neurons of subjects with higher VIQ scores had faster action potential upstroke kinetics, which improves information processing. These data show that expansion of supragranular layer volume, cortical and cellular micro-architecture and function are associated with improved verbal mental ability in human subjects.

Abundant evidence supports the presence of at least three distinct types of thalamocortical (TC) neurons in the primate dorsal lateral geniculate nucleus (dLGN) of the thalamus, the brain region that conveys visual information from the retina to the primary visual cortex (V1). Different types of TC neurons in mice, humans, and macaques have distinct morphologies, distinct connectivity patterns, and convey different aspects of visual information to the cortex. To investigate the molecular underpinnings of these cell types, and how these relate to differences in dLGN between human, macaque, and mice, we profiled gene expression in single nuclei and cells using RNA-sequencing. These efforts identified four distinct types of TC neurons in the primate dLGN: magnocellular (M) neurons, parvocellular (P) neurons, and two types of koniocellular (K) neurons. Despite extensively documented morphological and physiological differences between M and P neurons, we identified few genes with significant differential expression between transcriptomic cell types corresponding to these two neuronal populations. Likewise, the dominant feature of TC neurons of the adult mouse dLGN is high transcriptomic similarity, with an axis of heterogeneity that aligns with core vs. shell portions of mouse dLGN. Together, these data show that transcriptomic differences between principal cell types in the mature mammalian dLGN are subtle relative to the observed differences in morphology and cortical projection targets. Finally, alignment of transcriptome profiles across species highlights expanded diversity of GABAergic neurons in primate versus mouse dLGN and homologous types of TC neurons in primates that are distinct from TC neurons in mouse.

The Patch-seq approach is a powerful variation of the standard patch clamp technique that allows for the combined electrophysiological, morphological, and transcriptomic characterization of individual neurons. To generate Patch-seq datasets at a scale and quality that can be integrated with high-throughput dissociated cell transcriptomic data, we have optimized the technique by identifying and refining key factors that contribute to the efficient collection of high-quality data. To rapidly generate high-quality electrophysiology data, we developed patch clamp electrophysiology software with analysis functions specifically designed to automate acquisition with online quality control. We recognized a substantial improvement in transcriptomic data quality when the nucleus was extracted following the recording. For morphology success, the importance of maximizing the neuron’s membrane integrity during the extraction of the nucleus was much more critical to success than varying the duration of the electrophysiology recording. We compiled the lab protocol with the analysis and acquisition software athttps://github.com/AllenInstitute/patchseqtools. This resource can be used by individual labs to generate Patch-seq data across diverse mammalian species and that is compatible with recent large-scale publicly available Allen Institute Patch-seq datasets.

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.

Rodent studies have demonstrated that synaptic dynamics from excitatory to inhibitory neuron types are often dependent on the target cell type. However, these target cell-specific properties have not been well investigated in human cortex, where there are major technical challenges in reliably identifying cell types. Here, we take advantage of newly developed methods for human neurosurgical tissue analysis with multiple patch-clamp recordings, post-hoc fluorescent in situ hybridization (FISH), and prospective GABAergic AAV-based labeling to investigate synaptic properties between pyramidal neurons and PVALB- vs. SST- positive interneurons. We find that there are robust molecular differences in synapse-associated genes between these neuron types, and that individual presynaptic pyramidal neurons evoke postsynaptic responses with heterogeneous synaptic dynamics in different postsynaptic cell types. Using molecular identification with FISH and classifiers based on transcriptomically identified PVALB neurons analyzed with Patch-seq methods, we find that PVALB neurons typically show depressing synaptic characteristics, whereas other interneuron types including SST-positive neurons show facilitating characteristics. Together, these data support the existence of target cell-specific synaptic properties in human cortex that are similar to rodent, thereby indicating evolutionary conservation of local circuit connectivity motifs from excitatory to inhibitory neurons and their synaptic dynamics.

Single cell genomics is rapidly advancing our knowledge of cell phenotypic types and states. Driven by single cell/nucleus RNA sequencing (scRNA-seq) data, comprehensive atlas projects covering a wide range of organisms and tissues are currently underway. As a result, it is critical that the cell transcriptional phenotypes discovered are defined and disseminated in a consistent and concise manner. Molecular biomarkers have historically played an important role in biological research, from defining immune cell-types by surface protein expression to defining diseases by molecular drivers. Here we describe a machine learning-based marker gene selection algorithm, NS-Forest version 2.0, which leverages the non-linear attributes of random forest feature selection and a binary expression scoring approach to discover the minimal marker gene expression combinations that precisely captures the cell type identity represented in the complete scRNA-seq transcriptional profiles. The marker genes selected provide a barcode of the necessary and sufficient characteristics for semantic cell type definition and serve as useful tools for downstream biological investigation. The use of NS-Forest to identify marker genes for human brain middle temporal gyrus cell types reveals the importance of cell signaling and non-coding RNAs in neuronal cell type identity.

Methods for highly multiplexed RNA imaging are limited in spatial resolution, and thus in their ability to localize transcripts to nanoscale and subcellular compartments. We adapt expansion microscopy, which physically expands biological specimens, for long-read untargeted and targeted in situ RNA sequencing. We applied untargeted expansion sequencing (ExSeq) to mouse brain, yielding readout of thousands of genes, including splice variants and novel transcripts. Targeted ExSeq yielded nanoscale-resolution maps of RNAs throughout dendrites and spines in neurons of the mouse hippocampus, revealing patterns across multiple cell types; layer-specific cell types across mouse visual cortex; and the organization and position-dependent states of tumor and immune cells in a human metastatic breast cancer biopsy. Thus ExSeq enables highly multiplexed mapping of RNAs, from nanoscale to system scale.One Sentence SummaryIn situ sequencing of physically expanded specimens enables multiplexed mapping of RNAs at nanoscale, subcellular resolution.

Single cell/nucleus RNA sequencing (scRNAseq) is emerging as an essential tool to unravel the phenotypic heterogeneity of cells in complex biological systems. While computational methods for scRNAseq cell type clustering have advanced, the ability to integrate datasets to identify common and novel cell types across experiments remains a challenge. Here, we introduce a cluster-to-cluster cell type matching method – FR-Match – that utilizes supervised feature selection for dimensionality reduction and incorporates shared information among cells to determine whether two cell type clusters share the same underlying multivariate gene expression distribution. FR-Match is benchmarked with existing cell-to-cell and cell-to-cluster cell type matching methods using both simulated and real scRNAseq data. FR-Match proved to be a stringent method that produced fewer erroneous matches of distinct cell subtypes and had the unique ability to identify novel cell phenotypes in new datasets. In silico validation demonstrated that the proposed workflow is the only self-contained algorithm that was robust to increasing numbers of true negatives (i.e. non-represented cell types). FR-Match was applied to two human brain scRNAseq datasets sampled from cortical layer 1 and full thickness middle temporal gyrus. When mapping cell types identified in specimens isolated from these overlapping human brain regions, FR-Match precisely recapitulated the laminar characteristics of matched cell type clusters, reflecting their distinct neuroanatomical distributions. An R package and Shiny application are provided at https://github.com/JCVenterInstitute/FRmatch for users to interactively explore and match scRNAseq cell type clusters with complementary visualization tools.

Visualization of the transcriptome in situ has proven to be a valuable tool in exploring single-cell RNA-sequencing data, providing an additional dimension to investigate spatial cell typing and cell atlases, disease architecture or even data driven discoveries. The field of spatially resolved transcriptomic technologies is emerging as a vital tool to profile gene-expression, continuously pushing current methods to accommodate larger gene panels and larger areas without compromising throughput efficiency. Here, we describe a new version of the in situ sequencing (ISS) method based on padlock probes and rolling circle amplification. Modifications in probe design allows for a new barcoding system via sequence-by-hybridization chemistry for improved spatial detection of RNA transcripts. Due to the amplification of probes, amplicons can be visualized with standard epifluorescence microscopes with high-throughput efficiency and the new sequencing chemistry removes limitations bound by sequence-by-ligation chemistry of ISS. Here we present hybridization-based in situ sequencing (HybISS) that allows for increased flexibility and multiplexing, increased signal-to-noise, all without compromising throughput efficiency of imaging large fields of view. Moreover, the current protocol is demonstrated to work on human brain tissue samples, a source that has proven to be difficult to work with image-based spatial analysis techniques. Overall, HybISS technology works as a target amplification detection method for improved spatial transcriptomic visualization, and importantly, with an ease of implementation.

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.

To better understand the molecular and cellular differences in brain organization between human and nonhuman primates, we performed transcriptome sequencing of 16 regions of adult human, chimpanzee, and macaque brains. Integration with human single-cell transcriptomic data revealed global, regional, and cell-type–specific species expression differences in genes representing distinct functional categories. We validated and further characterized the human specificity of genes enriched in distinct cell types through histological and functional analyses, including rare subpallial-derived interneurons expressing dopamine biosynthesis genes enriched in the human striatum and absent in the nonhuman African ape neocortex. Our integrated analysis of the generated data revealed diverse molecular and cellular features of the phylogenetic reorganization of the human brain across multiple levels, with relevance for brain function and disease., Data was generated as part of the PsychENCODE Consortium, supported by MH103339, MH106934, and MH110926. Additional support was provided by NIH grants MH109904, MH106874, AG048918, DK111178, and NS092988 (National Chimpanzee Brain Resource), the Kavli Foundation, the James S. McDonnell Foundation, NSF grant BCS-1316829, MINECO BFU2014-55090-P (FEDER), Howard Hughes International Early Career, and Secretaria d’Universitats i Recerca del Departament d’Economia i Coneixement de la Generalitat de Catalunya.

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.

Motor, sensory, and integrative activities of the brain are coordinated by a series of midline-bridging neuronal commissures whose development is tightly regulated. Here we report a new human syndrome in which these commissures are widely disrupted, thus causing clinical manifestations of horizontal gaze palsy, scoliosis, and intellectual disability. Affected individuals were found to possess biallelic loss-of-function mutations in the gene encoding the axon-guidance receptor 'deleted in colorectal carcinoma' (DCC), which has been implicated in congenital mirror movements when it is mutated in the heterozygous state but whose biallelic loss-of-function human phenotype has not been reported. Structural MRI and diffusion tractography demonstrated broad disorganization of white-matter tracts throughout the human central nervous system (CNS), including loss of all commissural tracts at multiple levels of the neuraxis. Combined with data from animal models, these findings show that DCC is a master regulator of midline crossing and development of white-matter projections throughout the human CNS.

SummaryViral genetic tools to target specific brain cell types in humans and non-genetic model organisms will transform basic neuroscience and targeted gene therapy. Here we used comparative epigenetics to identify thousands of human neuronal subclass-specific putative enhancers to regulate viral tools, and 34% of these were conserved in mouse. We established an AAV platform to evaluate cellular specificity of functional enhancers by multiplexed fluorescent in situ hybridization (FISH) and single cell RNA sequencing. Initial testing in mouse neocortex yields a functional enhancer discovery success rate of over 30%. We identify enhancers with specificity for excitatory and inhibitory classes and subclasses including PVALB, LAMP5, and VIP/LAMP5 cells, some of which maintain specificityin vivoorex vivoin monkey and human neocortex. Finally, functional enhancers can be proximal or distal to cellular marker genes, conserved or divergent across species, and could yield brain-wide specificity greater than the most selective marker genes.

Defining a complete set of cell types within the cortex requires reconciling disparate results achieved through diverging methodologies. To address this correspondence problem, multiple methodologies must be applied to the same cells across multiple single-cell experiments. Here we present a new approach applying spatial transcriptomics using multiplexed fluorescencein situhybridization, (mFISH) to brain tissue previously interrogated through two photon optogenetic mapping of synaptic connectivity. This approach can resolve the anatomical, transcriptomic, connectomic, electrophysiological, and morphological characteristics of single cells within the mouse cortex.

We combined de novo mutation (DNM) data from 10,927 individuals with developmental delay and autism to identify 253 candidate neurodevelopmental disease genes with an excess of missense and/or likely gene-disruptive (LGD) mutations. Of these genes, 124 reach exome-wide significance (P

INTRODUCTION The brain is responsible for cognition, behavior, and much of what makes us uniquely human. The development of the brain is a highly complex process, and this process is reliant on precise regulation of molecular and cellular events grounded in the spatiotemporal regulation of the transcriptome. Disruption of this regulation can lead to neuropsychiatric disorders. RATIONALE The regulatory, epigenomic, and transcriptomic features of the human brain have not been comprehensively compiled across time, regions, or cell types. Understanding the etiology of neuropsychiatric disorders requires knowledge not just of endpoint differences between healthy and diseased brains but also of the developmental and cellular contexts in which these differences arise. Moreover, an emerging body of research indicates that many aspects of the development and physiology of the human brain are not well recapitulated in model organisms, and therefore it is necessary that neuropsychiatric disorders be understood in the broader context of the developing and adult human brain. RESULTS Here we describe the generation and analysis of a variety of genomic data modalities at the tissue and single-cell levels, including transcriptome, DNA methylation, and histone modifications across multiple brain regions ranging in age from embryonic development through adulthood. We observed a widespread transcriptomic transition beginning during late fetal development and consisting of sharply decreased regional differences. This reduction coincided with increases in the transcriptional signatures of mature neurons and the expression of genes associated with dendrite development, synapse development, and neuronal activity, all of which were temporally synchronous across neocortical areas, as well as myelination and oligodendrocytes, which were asynchronous. Moreover, genes including MEF2C , SATB2 , and TCF4 , with genetic associations to multiple brain-related traits and disorders, converged in a small number of modules exhibiting spatial or spatiotemporal specificity. CONCLUSION We generated and applied our dataset to document transcriptomic and epigenetic changes across human development and then related those changes to major neuropsychiatric disorders. These data allowed us to identify genes, cell types, gene coexpression modules, and spatiotemporal loci where disease risk might converge, demonstrating the utility of the dataset and providing new insights into human development and disease. Spatiotemporal dynamics of human brain development and neuropsychiatric risks. Human brain development begins during embryonic development and continues through adulthood (top). Integrating data modalities (bottom left) revealed age- and cell type–specific properties and global patterns of transcriptional dynamics, including a late fetal transition (bottom middle). We related the variation in gene expression (brown, high; purple, low) to regulatory elements in the fetal and adult brains, cell type–specific signatures, and genetic loci associated with neuropsychiatric disorders (bottom right; gray circles indicate enrichment for corresponding features among module genes). Relationships depicted in this panel do not correspond to specific observations. CBC, cerebellar cortex; STR, striatum; HIP, hippocampus; MD, mediodorsal nucleus of thalamus; AMY, amygdala.