Human Brain Cell Types Research Articles

A brain cell atlas integrating single-cell transcriptomes across human brain regions

While single-cell technologies have greatly advanced our comprehension of human brain cell types and functions, studies including large numbers of donors and multiple brain regions are needed to extend our understanding of brain cell heterogeneity. Integrating atlas-level single-cell data presents a chance to reveal rare cell types and cellular heterogeneity across brain regions. Here we present the Brain Cell Atlas, a comprehensive reference atlas of brain cells, by assembling single-cell data from 70 human and 103 mouse studies of the brain throughout major developmental stages across brain regions, covering over 26.3 million cells or nuclei from both healthy and diseased tissues. Using machine-learning based algorithms, the Brain Cell Atlas provides a consensus cell type annotation, and it showcases the identification of putative neural progenitor cells and a cell subpopulation of PCDH9high microglia in the human brain. We demonstrate the gene regulatory difference of PCDH9high microglia between hippocampus and prefrontal cortex and elucidate the cell–cell communication network. The Brain Cell Atlas presents an atlas-level integrative resource for comparing brain cells in different environments and conditions within the Human Cell Atlas.

Signature morphoelectric properties of diverse GABAergic interneurons in the human neocortex.

Human cortex transcriptomic studies have revealed a hierarchical organization of γ-aminobutyric acid-producing (GABAergic) neurons from subclasses to a high diversity of more granular types. Rapid GABAergic neuron viral genetic labeling plus Patch-seq (patch-clamp electrophysiology plus single-cell RNA sequencing) sampling in human brain slices was used to reliably target and analyze GABAergic neuron subclasses and individual transcriptomic types. This characterization elucidated transitions between PVALB and SST subclasses, revealed morphological heterogeneity within an abundant transcriptomic type, identified multiple spatially distinct types of the primate-specialized double bouquet cells (DBCs), and shed light on cellular differences between homologous mouse and human neocortical GABAergic neuron types. These results highlight the importance of multimodal phenotypic characterization for refinement of emerging transcriptomic cell type taxonomies and for understanding conserved and specialized cellular properties of human brain cell types.

Fingerprinting heterocellular β-adrenoceptor functional expression in the brain using agonist activity profiles.

Noradrenergic projections from the brainstem locus coeruleus drive arousal, attentiveness, mood, and memory, but specific adrenoceptor (AR) function across the varied brain cell types has not been extensively characterized, especially with agonists. This study reports a pharmacological analysis of brain AR function, offering insights for innovative therapeutic interventions that might serve to compensate for locus coeruleus decline, known to develop in the earliest phases of neurodegenerative diseases. First, β-AR agonist activities were measured in recombinant cell systems and compared with those of isoprenaline to generate Δlog(Emax/EC50) values, system-independent metrics of agonist activity, that, in turn, provide receptor subtype fingerprints. These fingerprints were then used to assess receptor subtype expression across human brain cell systems and compared with Δlog(Emax/EC50) values arising from β-arrestin activation or measurements of cAMP response desensitization to assess the possibility of ligand bias among β-AR agonists. Agonist activity profiles were confirmed to be system-independent and, in particular, revealed β2-AR functional expression across several human brain cell types. Broad β2-AR function observed is consistent with noradrenergic tone arising from the locus coeruleus exerting heterocellular neuroexcitatory and homeostatic influence. Notably, Δlog(Emax/EC50) measurements suggest that tested β-AR agonists do not show ligand bias as it pertains to homologous receptor desensitization in the system examined. Δlog(Emax/EC50) agonist fingerprinting is a powerful means of assessing receptor subtype expression regardless of receptor expression levels or assay readout, and the method may be applicable to future use for novel ligands and tissues expressing any receptor with available reference agonists.

Single-nucleus gene and gene set expression-based similarity network fusion identifies autism molecular subtypes

BackgroundAutism spectrum disorder (ASD) is a complex neurodevelopmental disorder that is highly phenotypically and genetically heterogeneous. With the accumulation of biological sequencing data, more and more studies shift to molecular subtype-first approach, from identifying molecular subtypes based on genetic and molecular data to linking molecular subtypes with clinical manifestation, which can reduce heterogeneity before phenotypic profiling.ResultsIn this study, we perform similarity network fusion to integrate gene and gene set expression data of multiple human brain cell types for ASD molecular subtype identification. Then we apply subtype-specific differential gene and gene set expression analyses to study expression patterns specific to molecular subtypes in each cell type. To demonstrate the biological and practical significance, we analyze the molecular subtypes, investigate their correlation with ASD clinical phenotype, and construct ASD molecular subtype prediction models.ConclusionsThe identified molecular subtype-specific gene and gene set expression may be used to differentiate ASD molecular subtypes, facilitating the diagnosis and treatment of ASD. Our method provides an analytical pipeline for the identification of molecular subtypes and even disease subtypes of complex disorders.

A multimodal deep learning model to infer cell-type-specific functional gene networks

BackgroundFunctional gene networks (FGNs) capture functional relationships among genes that vary across tissues and cell types. Construction of cell-type-specific FGNs enables the understanding of cell-type-specific functional gene relationships and insights into genetic mechanisms of human diseases in disease-relevant cell types. However, most existing FGNs were developed without consideration of specific cell types within tissues.ResultsIn this study, we created a multimodal deep learning model (MDLCN) to predict cell-type-specific FGNs in the human brain by integrating single-nuclei gene expression data with global protein interaction networks. We systematically evaluated the prediction performance of the MDLCN and showed its superior performance compared to two baseline models (boosting tree and convolutional neural network). Based on the predicted cell-type-specific FGNs, we observed that cell-type marker genes had a higher level of hubness than non-marker genes in their corresponding cell type. Furthermore, we showed that risk genes underlying autism and Alzheimer’s disease were more strongly connected in disease-relevant cell types, supporting the cellular context of predicted cell-type-specific FGNs.ConclusionsOur study proposes a powerful deep learning approach (MDLCN) to predict FGNs underlying a diverse set of cell types in human brain. The MDLCN model enhances prediction accuracy of cell-type-specific FGNs compared to single modality convolutional neural network (CNN) and boosting tree models, as shown by higher areas under both receiver operating characteristic (ROC) and precision-recall curves for different levels of independent test datasets. The predicted FGNs also show evidence for the cellular context and distinct topological features (i.e. higher hubness and topological score) of cell-type marker genes. Moreover, we observed stronger modularity among disease-associated risk genes in FGNs of disease-relevant cell types. For example, the strength of connectivity among autism risk genes was stronger in neurons, but risk genes underlying Alzheimer’s disease were more connected in microglia.

Vast diversity of human brain cell types revealed in trove of new datasets

Vast diversity of human brain cell types revealed in trove of new datasets

Cell-type-specific cis-eQTLs in eight human brain cell types identify novel risk genes for psychiatric and neurological disorders.

To date, most expression quantitative trait loci (eQTL) studies, which investigate how genetic variants contribute to gene expression, have been performed in heterogeneous brain tissues rather than specific cell types. In this study, we performed an eQTL analysis using single-nuclei RNA sequencing from 192 individuals in eight brain cell types derived from the prefrontal cortex, temporal cortex and white matter. We identified 7,607 eGenes, a substantial fraction (46%, 3,537/7,607) of which show cell-type-specific effects, with strongest effects in microglia. Cell-type-level eQTLs affected more constrained genes and had larger effect sizes than tissue-level eQTLs. Integration of brain cell type eQTLs with genome-wide association studies (GWAS) revealed novel relationships between expression and disease risk for neuropsychiatric and neurodegenerative diseases. For most GWAS loci, a single gene co-localized in a single cell type, providing new clues into disease etiology. Our findings demonstrate substantial contrast in genetic regulation of gene expression among brain cell types and reveal potential mechanisms by which disease risk genes influence brain disorders.

Cellular and genetic drivers of RNA editing variation in the human brain

Posttranscriptional adenosine-to-inosine modifications amplify the functionality of RNA molecules in the brain, yet the cellular and genetic regulation of RNA editing is poorly described. We quantify base-specific RNA editing across three major cell populations from the human prefrontal cortex: glutamatergic neurons, medial ganglionic eminence-derived GABAergic neurons, and oligodendrocytes. We identify more selective editing and hyper-editing in neurons relative to oligodendrocytes. RNA editing patterns are highly cell type-specific, with 189,229 cell type-associated sites. The cellular specificity for thousands of sites is confirmed by single nucleus RNA-sequencing. Importantly, cell type-associated sites are enriched in GTEx RNA-sequencing data, edited ~twentyfold higher than all other sites, and variation in RNA editing is largely explained by neuronal proportions in bulk brain tissue. Finally, we uncover 661,791 cis-editing quantitative trait loci across thirteen brain regions, including hundreds with cell type-associated features. These data reveal an expansive repertoire of highly regulated RNA editing sites across human brain cell types and provide a resolved atlas linking cell types to editing variation and genetic regulatory effects.

Robust and Highly Reproducible Generation of Cortical Brain Organoids for Modelling Brain Neuronal Senescence In Vitro.

Brain organoids are three-dimensional models of the developing human brain and provide a compelling, cutting-edge platform for disease modeling and large-scale genomic and drug screening. Due to the self-organizing nature of cells in brain organoids and the growing range of available protocols for their generation, issues with heterogeneity and variability between organoids have been identified. In this protocol paper, we describe a robust and replicable protocol that largely overcomes these issues and generates cortical organoids from neuroectodermal progenitors within 1 month, and that can be maintained for more than 1 year. This highly reproducible protocol can be easily carried out in a standard tissue culture room and results in organoids with a rich diversity of cell types typically found in the developing human cortex. Despite their early developmental make-up, neurons and other human brain cell types will start to exhibit the typical signs of senescence in neuronal cells after prolonged in vitro culture, making them a valuable and useful platform for studying aging-related neuronal processes. This protocol also outlines a method for detecting such senescent cells in cortical brain organoids using senescence-associated beta-galactosidase staining.

Robust and Highly Reproducible Generation of Cortical Brain Organoids for Modelling Brain Neuronal Senescence <em>In Vitro</em>

Brain organoids are three-dimensional models of the developing human brain and provide a compelling, cutting-edge platform for disease modeling and large-scale genomic and drug screening. Due to the self-organizing nature of cells in brain organoids and the growing range of available protocols for their generation, issues with heterogeneity and variability between organoids have been identified. In this protocol paper, we describe a robust and replicable protocol that largely overcomes these issues and generates cortical organoids from neuroectodermal progenitors within 1 month, and that can be maintained for more than 1 year. This highly reproducible protocol can be easily carried out in a standard tissue culture room and results in organoids with a rich diversity of cell types typically found in the developing human cortex. Despite their early developmental make-up, neurons and other human brain cell types will start to exhibit the typical signs of senescence in neuronal cells after prolonged in vitro culture, making them a valuable and useful platform for studying aging-related neuronal processes. This protocol also outlines a method for detecting such senescent cells in cortical brain organoids using senescence-associated beta-galactosidase staining.

HPRep: Quantifying Reproducibility in HiChIP and PLAC-Seq Datasets

HiChIP and PLAC-Seq are emerging technologies for studying genome-wide long-range chromatin interactions mediated by the protein of interest, enabling more sensitive and cost-efficient interrogation of protein-centric chromatin conformation. However, due to the unbalanced read distribution introduced by protein immunoprecipitation, existing reproducibility measures developed for Hi-C data are not appropriate for the analysis of HiChIP and PLAC-Seq data. Here, we present HPRep, a stratified and weighted correlation metric derived from normalized contact counts, to quantify reproducibility in HiChIP and PLAC-Seq data. We applied HPRep to multiple real datasets and demonstrate that HPRep outperforms existing reproducibility measures developed for Hi-C data. Specifically, we applied HPRep to H3K4me3 PLAC-Seq data from mouse embryonic stem cells and mouse brain tissues as well as H3K27ac HiChIP data from human lymphoblastoid cell line GM12878 and leukemia cell line K562, showing that HPRep can more clearly separate among pseudo-replicates, real replicates, and non-replicates. Furthermore, in an H3K4me3 PLAC-Seq dataset consisting of 11 samples from four human brain cell types, HPRep demonstrated the expected clustering of data that could not be achieved by existing methods developed for Hi-C data, highlighting the need for a reproducibility metric tailored to HiChIP and PLAC-Seq data.

Cell Type–Specific Nuclei Markers: The Need for Human Brain Research to Go Nuclear

Identifying and interrogating cell type–specific populations within the heterogeneous milieu of the human brain is paramount to resolving the processes of normal brain homeostasis and the pathogenesis of neurological disorders. While brain cell type–specific markers are well established, most are localized on cellular membranes or within the cytoplasm, with limited literature describing those found in the nucleus. Due to the complex cytoarchitecture of the human brain, immunohistochemical studies require well-defined cell-specific nuclear markers for more precise and efficient quantification of the cellular populations. Furthermore, efficient nuclear markers are required for cell type–specific purification and transcriptomic interrogation of archived human brain tissue through nuclei isolation–based RNA sequencing. To sate the growing demand for robust cell type–specific nuclear markers, we thought it prudent to comprehensively review the current literature to identify and consolidate a novel series of robust cell type–specific nuclear markers that can assist researchers across a range of neuroscientific disciplines. The following review article collates and discusses several key and prospective cell type–specific nuclei markers for each of the major human brain cell types; it then concludes by discussing the potential applications of cell type–specific nuclear workflows and the power of nuclear-based neuroscientific research.

Chitinase 3-like 1 and neurofilament light chain in CSF and CNS atrophy in MS.

ObjectiveTo investigate cross-sectional associations of CSF levels of neurofilament light chain (NfL) and of the newly emerging marker chitinase 3–like protein 1 (CHI3L1) with brain and spinal cord atrophy, which are established MRI markers of disease activity in MS, to study CHI3L1 and NfL in relapsing (RMS) and progressive MS (PMS), and to assess the expression of CHI3L1 in different cell types.MethodsIn a single-center study, 131 patients with MS (42 RMS and 89 PMS) were assessed for NfL and CHI3L1 concentrations in CSF, MRI-based spinal cord and brain volumetry, MS subtype, age, disease duration, and disability. We included 42 matched healthy controls receiving MRI. CHI3L1 expression of human brain cell types was examined in 2 published single-cell RNA sequencing data sets.ResultsCHI3L1 was associated with spinal cord volume (B = −1.07, 95% CI −2.04 to −0.11, p = 0.029) but not with brain volumes. NfL was associated with brain gray matter (B = −7.3, 95% CI −12.0 to −2.7, p = 0.003) but not with spinal cord volume. CHI3L1 was suitable to differentiate between progressive or relapsing MS (p = 0.015, OR 1.0103, CI for OR 1.002–1.0187), and its gene expression was found in MS-associated microglia and macrophages and in astrocytes of MS brains.ConclusionsNfL and CHI3L1 in CSF were differentially related to brain and spinal cord atrophy. CSF CHI3L1 was associated with spinal cord volume loss and was less affected than NfL by disease duration and age, whereas CSF NfL was associated with brain gray matter atrophy. CSF NfL and CHI3L1 measurement provides complementary information regarding brain and spinal cord volumes.Classification of evidenceThis study provides Class II evidence that CSF CHI3L1 is associated with spinal cord volume loss and that CSF NfL is associated with gray matter atrophy.

Abstract IA29: Developmental and oncogenic programs in pediatric brain tumors dissected by single-cell RNA-sequencing

Abstract During development, the multiple cell types of human brain arise from pluripotent stem cells via progressively more committed progenitor cells. Emerging data suggest that pediatric brain tumors arise from progenitors that have become developmentally stalled. In preliminary studies, our lab used single-cell RNA-seq to display the expression profiles of individual cells within pediatric midline and hemispheric high-grade gliomas. Our data show that these tumors are composed of (i) replicating cells that resemble glial and neural progenitors and (ii) maturing cells resembling astrocytes, oligodendrocytes, or mesenchymal cells. In this presentation I will address how single-cell RNA-sequencing has revolutionized our understanding of the developmental hierarchy and oncogenic programs in pediatric brain tumors. Our recent findings pointing towards potential cells of origin of midline and hemispheric pediatric high-grade gliomas as well as plasticity of different cancer cell states will be discussed. Citation Format: Mariella G. Filbin. Developmental and oncogenic programs in pediatric brain tumors dissected by single-cell RNA-sequencing [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr IA29.

Neurodegeneration in a dish: advancing human stem-cell-based models of Alzheimer's disease.

Induced pluripotent stem-cell-based models enable investigation of pathomechanisms in disease-relevant human brain cell types and therefore offer great potential for mechanistic and translational studies on neurodegenerative disorders, such as Alzheimer's disease (AD). While current AD models allow analysis of early disease phenotypes including Aβ accumulation and Tau hyperphosphorylation, they still fail to fully recapitulate later hallmarks such as protein aggregation and neurodegeneration. This impedes the identification of pathomechanisms and novel therapeutic targets. We discuss strategies to overcome these drawbacks and optimize physiological properties and translational potential of iPSC-based models by improving culture formats, increasing cellular diversity, applying genome editing, and implementing maturation and ageing paradigms.

Abstract 1896: Blockade of laminin-411-notch crosstalk as an effective therapy for glioblastoma treatment

Abstract Purpose: The extracellular matrix (ECM) in tumor microenvironment including laminins is important for tumor development, and we aimed to develop an effective glioblastoma therapy via blocking the communication between tumor and their microenvironment mediated by laminin-411-Notch axis. Methods: The glioma vascular protein, laminin-411(α4β1γ1) expression was examined in >200 glioma patient specimens by immunohistochemistry. In glioblastoma bearing mice, laminin-411 expression in tumor cells was disrupted by CRISPR/Ca9 system, and its impact on two glioblastoma cell lines was studied in intracranial xenografts. Laminin-411-Notch crosstalk was further dissected in vitro using cell cultures. Finally, a nanobioconjugate was developed to block laminin-411 expression in vivo. The effects of blocking laminin-411-Notch axis via systemic administration of this nanodrug were investigated in vivo using MRI, immunohistochemistry, western blot and survival analysis. Results: Laminin-411 (α4β1γ1) expression in a panel of 226 patient brain glioma samples was correlated with higher tumor grade, and expression of cancer stem cell (CSC) markers including Notch pathway, CD133, Nestin, and c-Myc. Laminin-411 overexpression was also correlated with higher recurrence rate and shorter survival of glioma patients. Depletion of laminin-411 α4 and β1 chains with CRISPR/Cas9 in human glioblastoma cells led to slower growth of resultant intracranial tumors compared to wild type tumors as revealed by MRI. Concomitantly, survival of host animals carrying the laminin-411 knockout tumors was significantly increased. Mechanistic studies in vitro and in vivo showed that laminin-411 inhibition suppressed Notch pathway in both normal and malignant human brain cell types. A nanobioconjugate potentially suitable for clinical use and capable of crossing blood-brain barrier was designed to block laminin-411 expression. Nanobioconjugate treatment of mice carrying intracranial glioblastoma significantly increased animal survival and inhibited multiple CSC markers including Notch axis. Conclusion: The depletion of “malignant” laminin-411 α4 and β1 chains with CRISPR/Cas9 led to slower growth of resultant intracranial tumors compared to wild type tumors, and a systemic nanodrug treatment to inhibit laminin-411-Notch crosstalk provides a new strategy for glioblastoma treatment. This study demonstrates a new strategy of glioblastoma treatment through targeting a critical component of tumor microenvironment, largely independent of heterogeneous genetic mutations in the tumor. Citation Format: Dmytro Klymyshyn, Anna Galstyan, Rameshwar Patil, Hui Ding, Ekaterina Shatalova, Shawn Wagner, Keith Black, Alexander Ljubimov, Eggehard Holler, Julia Ljubimova, Tao Sun. Blockade of laminin-411-notch crosstalk as an effective therapy for glioblastoma treatment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1896.

Blockade of a Laminin-411-Notch Axis with CRISPR/Cas9 or a Nanobioconjugate Inhibits Glioblastoma Growth through Tumor-Microenvironment Cross-talk.

There is an unmet need for the treatment of glioblastoma multiforme (GBM). The extracellular matrix, including laminins, in the tumor microenvironment is important for tumor invasion and progression. In a panel of 226 patient brain glioma samples, we found a clinical correlation between the expression of tumor vascular laminin-411 (α4β1γ1) with higher tumor grade and with expression of cancer stem cell (CSC) markers, including Notch pathway members, CD133, Nestin, and c-Myc. Laminin-411 overexpression also correlated with higher recurrence rate and shorter survival of GBM patients. We also showed that depletion of laminin-411 α4 and β1 chains with CRISPR/Cas9 in human GBM cells led to reduced growth of resultant intracranial tumors in mice and significantly increased survival of host animals compared with mice with untreated cells. Inhibition of laminin-411 suppressed Notch pathway in normal and malignant human brain cell types. A nanobioconjugate potentially suitable for clinical use and capable of crossing blood-brain barrier was designed to block laminin-411 expression. Nanobioconjugate treatment of mice carrying intracranial GBM significantly increased animal survival and inhibited multiple CSC markers, including the Notch axis. This study describes an efficient strategy for GBM treatment via targeting a critical component of the tumor microenvironment largely independent of heterogeneous genetic mutations in glioblastoma.Significance: Laminin-411 expression in the glioma microenvironment correlates with Notch and other cancer stem cell markers and can be targeted by a novel, clinically translatable nanobioconjugate to inhibit glioma growth.

APOE4 Causes Widespread Molecular and Cellular Alterations Associated with Alzheimer’s Disease Phenotypes in Human iPSC-Derived Brain Cell Types

The apolipoprotein E4 (APOE4) variant is the single greatest genetic risk factor for sporadic Alzheimer's disease (sAD). However, the cell-type-specific functions of APOE4 in relation to AD pathology remain understudied. Here, we utilize CRISPR/Cas9 and induced pluripotent stem cells (iPSCs) to examine APOE4 effects on human brain cell types. Transcriptional profiling identified hundreds of differentially expressed genes in each cell type, with the most affected involving synaptic function (neurons), lipid metabolism (astrocytes), and immune response (microglia-like cells). APOE4 neurons exhibited increased synapse number and elevated Aβ42 secretion relative to isogenic APOE3 cells while APOE4 astrocytes displayed impaired Aβ uptake and cholesterol accumulation. Notably, APOE4 microglia-like cells exhibited altered morphologies, which correlated with reduced Aβ phagocytosis. Consistently, converting APOE4 to APOE3 in brain cell types from sAD iPSCs was sufficient to attenuate multiple AD-related pathologies. Our study establishes a reference for human cell-type-specific changes associated with the APOE4 variant. VIDEO ABSTRACT.

Localization of migraine susceptibility genes in human brain by single-cell RNA sequencing.

Migraine is a debilitating disorder characterized by severe headaches and associated neurological symptoms. A key challenge to understanding migraine has been the cellular complexity of the human brain and the multiple cell types implicated in its pathophysiology. The present study leverages recent advances in single-cell transcriptomics to localize the specific human brain cell types in which putative migraine susceptibility genes are expressed. The cell-type specific expression of both familial and common migraine-associated genes was determined bioinformatically using data from 2,039 individual human brain cells across two published single-cell RNA sequencing datasets. Enrichment of migraine-associated genes was determined for each brain cell type. Analysis of single-brain cell RNA sequencing data from five major subtypes of cells in the human cortex (neurons, oligodendrocytes, astrocytes, microglia, and endothelial cells) indicates that over 40% of known migraine-associated genes are enriched in the expression profiles of a specific brain cell type. Further analysis of neuronal migraine-associated genes demonstrated that approximately 70% were significantly enriched in inhibitory neurons and 30% in excitatory neurons. This study takes the next step in understanding the human brain cell types in which putative migraine susceptibility genes are expressed. Both familial and common migraine may arise from dysfunction of discrete cell types within the neurovascular unit, and localization of the affected cell type(s) in an individual patient may provide insight into to their susceptibility to migraine.

MAPPING NEURONAL CELL TYPES USING INTEGRATIVE MULTI-SPECIES MODELING OF HUMAN AND MOUSE SINGLE CELL RNA SEQUENCING.

Mouse brain transcriptomic studies are important in the understanding of the structural heterogeneity in the brain. However, it is not well understood how cell types in the mouse brain relate to human brain cell types on a cellular level. We propose that it is possible with single cell granularity to find concordant genes between mouse and human and that these genes can be used to separate cell types across species. We show that a set of concordant genes can be algorithmically derived from a combination of human and mouse single cell sequencing data. Using this gene set, we show that similar cell types shared between mouse and human cluster together. Furthermore we find that previously unclassified human cells can be mapped to the glial/vascular cell type by integrating mouse cell type expression profiles.