Cited by 2,705Single-cell and spatial transcriptomicsNeurogenesis and neuroplasticity mechanismsNeuroscience and Neuropharmacology Research

The DOI matches its Crossref record; 66 of the 66 references it cites were found in a registry or an index; 23 of the 45 sources its claims cite were checked for support.

Molecular Architecture of the Mouse Nervous System

Open access

Published version of a preprint

Abstract

The mammalian nervous system executes complex behaviors controlled by specialized, precisely positioned, and interacting cell types. Here, we used RNA sequencing of half a million single cells to create a detailed census of cell types in the mouse nervous system. We mapped cell types spatially and derived a hierarchical, data-driven taxonomy. Neurons were the most diverse and were grouped by developmental anatomical units and by the expression of neurotransmitters and neuropeptides. Neuronal diversity was driven by genes encoding cell identity, synaptic connectivity, neurotransmission, and membrane conductance. We discovered seven distinct, regionally restricted astrocyte types that obeyed developmental boundaries and correlated with the spatial distribution of key glutamate and glycine neurotransmitters. In contrast, oligodendrocytes showed a loss of regional identity followed by a secondary diversification. The resource presented here lays a solid foundation for understanding the molecular architecture of the mammalian nervous system and enables genetic manipulation of specific cell types.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

The paper uses single-cell RNA sequencing of ~half a million cells across 19 regions of the mouse nervous system to create a molecular census and data-driven taxonomy of cell types. It reports that nervous system organization reflects major cell class, developmental origin, and neurotransmitter type, with regionally specified astrocytes and a loss of regional patterning in the oligodendrocyte lineage.

Key findings

  • The survey analyzed 509,876 cells and retained a final curated compendium of 265 clusters represented by 160,796 high-quality single-cell transcriptomes; 248 (93%) clusters were uniquely identifiable with just two genes, 17 required three genes, and none required more than three. A random forest classifier on held-out data achieved average precision and recall of 82%, and 98% of 139 previously published clusters were perfect or near-perfect matches.
  • Neurons were the most diverse class: PNS neurons segregated into sensory, sympathetic, and enteric subdivisions, while CNS neurons generally split first by anteroposterior domain and then by excitatory versus inhibitory neurotransmitter. The paper identified seven molecularly distinct astrocyte types with regionally restricted distributions, including telencephalon-specific ACTE1/ACTE2 and non-telencephalon ACNT1/ACNT2 separated by a sharp Mfge8/Agt border.
  • Oligodendrocyte lineage stages OPC, COP, and NFOL presented as single brain-wide common cell types regardless of tissue, indicating that mature oligodendrocyte diversity arises by secondary diversification rather than developmental patterning. Spinal cord and hindbrain oligodendrocytes retained Hox gene expression, but forebrain and midbrain patterning transcription factors were detected only at very low levels (<1% of cells) if at all.

Methods

  • Dissected 19 regions from adolescent mice (postnatal ages P12–30, plus 6- and 8-week-old mice), including brain, spinal cord, dorsal root ganglia, sympathetic ganglion, and enteric nervous system; used 133 samples and 10X Genomics Chromium droplet microfluidics, with FACS for enteric neural-crest-derived cells and some inhibitory neurons.
  • Developed and applied “cytograph,” a multistage pipeline including quality filtering, major-class SVM classification, multiscale KNN manifold learning, graph t-SNE, Polished Louvain clustering, gene enrichment, Bayesian trinarization, marker gene set discovery, and dendrogram construction.
  • Validated clusters by random forest classification, comparison with six published scRNA-seq datasets, RNAscope in situ hybridization, and spatial correlation of cluster expression profiles with Allen Mouse Brain Atlas ISH voxel data.

Limitations

  • Stated limitations: technical/experimental issues including doublets, sex-specific gene expression, and low-quality cells; sampling only a little more than half a million cells with relatively shallow sequencing likely misses additional structure and subtypes; differential survival or size selection biases may have lost cell types (e.g., Purkinje cells likely undersampled); clustering was conservative and did not analyze substantial remaining heterogeneity within clusters; and the work describes only molecular cell types without linking them to functional, anatomical, morphological, or electrophysiological properties.
  • Evident from the text: the survey omitted at least the retina, olfactory epithelium, vomeronasal organ, inner ear, and parasympathetic ganglia; enteric analysis covered only the myenteric plexus of the small intestine; and the authors note that interneurons were undersampled by scRNA-seq while astrocytes were undersampled by osmFISH.

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Integrity signals

Registry

Crossref · 10.1016/j.cell.2018.06.021

Cites

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Statistics

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Figures

Graphical abstract
Graphical abstract CC BY · PubMed Central
Figure 1 Molecular Survey of the Mouse Nervous System Using Single-Cell RNA Sequencing (A) Schematic illustration of the sampling strategy. The brain was divided into coarse anatomical units, and in addition, we sampled from the spinal cord, dorsal root ganglia, sympathetic ganglion, and enteric nervous system. (B) Visualization of the single-cell data using gt-SNE embedding (see STAR Methods). Cells are colored by rank 3 taxonomy units indicated in the legend. (C) Dendrogram describing the taxonomy of all identified cell types. Main branches, corresponding to the taxonomy, are annotated with labels and colored background. The neurotransmitter used by each cell type is indicated below the leaves as colored circles. The lower panel indicates the developmental compartment of origin for each cell types. See also Figure S1 and Tables S1, S2, S3, S4, and S5.
Figure 1 Molecular Survey of the Mouse Nervous System Using Single-Cell RNA Sequencing (A) Schematic illustration of the sampling strategy. The brain was divided into coarse anatomical units, and in addition, we sampled from the spinal cord, dorsal root ganglia, sympathetic ganglion, and enteric nervous system. (B) Visualization of the single-cell data using gt-SNE embedding (see STAR Methods). Cells are colored by rank 3 taxonomy units indicated in the legend. (C) Dendrogram describing the taxonomy of all identified cell types. Main branches, corresponding to the taxonomy, are annotated with labels and colored background. The neurotransmitter used by each cell type is indicated below the leaves as colored circles. The lower panel indicates the developmental compartment of origin for each cell types. See also Figure S1 and Tables S1, S2, S3, S4, and S5.CC BY · PubMed Central
Figure S1 Data Quality, Related to Figure 1 (A) Number of cells retained in analysis for each level of the pipeline. (B) Circle plots showing number of cells from each main class and each dissection region. (C) Cluster robustness and relatedness. The heatmap illustrates the performance of a random forest classifier, showing the average probability assigned to every cell type (rows) for each test cell of given type (columns). When the correct cell type (diagonal) has high probability, almost every test cell will be correctly classified. (D,E) Magnified view of heatmap as indicated in (C). (F) Distribution of Gene and UMI counts for individual Chromium samples (gray) and major cell classes (colored), shown for each of a representative selection of tissues. (G) Comparison of cell type fractions observed by osmFISH (single-molecule fluorescent in situ hybridization) and scRNA-seq. (H) Comparison of oligodendrocyte lineage clustering in the present paper and those previously published in Marques et al., 2016.
Figure S1 Data Quality, Related to Figure 1 (A) Number of cells retained in analysis for each level of the pipeline. (B) Circle plots showing number of cells from each main class and each dissection region. (C) Cluster robustness and relatedness. The heatmap illustrates the performance of a random forest classifier, showing the average probability assigned to every cell type (rows) for each test cell of given type (columns). When the correct cell type (diagonal) has high probability, almost every test cell will be correctly classified. (D,E) Magnified view of heatmap as indicated in (C). (F) Distribution of Gene and UMI counts for individual Chromium samples (gray) and major cell classes (colored), shown for each of a representative selection of tissues. (G) Comparison of cell type fractions observed by osmFISH (single-molecule fluorescent in situ hybridization) and scRNA-seq. (H) Comparison of oligodendrocyte lineage clustering in the present paper and those previously published in Marques et al., 2016.CC BY · PubMed Central
Figure 2 A Map of Neurogenesis in the Juvenile Mouse Brain (A) A cut-out from dendrogram of relevant cell types, including neuroblasts, radial glia-like cells, astrocytes, OPCs, and ependymal cells. (B) Sketch illustrating the locations where we found neurogenic activity. (C) gt-SNE embedding of all cells from the relevant cell types shown in (A). The dashed line suggests the border between glia-like cells and neuroblasts. (D) Expression distribution of individual key genes projected onto the gt-SNE embedding. See also Figure S2.
Figure 2 A Map of Neurogenesis in the Juvenile Mouse Brain (A) A cut-out from dendrogram of relevant cell types, including neuroblasts, radial glia-like cells, astrocytes, OPCs, and ependymal cells. (B) Sketch illustrating the locations where we found neurogenic activity. (C) gt-SNE embedding of all cells from the relevant cell types shown in (A). The dashed line suggests the border between glia-like cells and neuroblasts. (D) Expression distribution of individual key genes projected onto the gt-SNE embedding. See also Figure S2.CC BY · PubMed Central
Figure S2 Markers and Validation of Neurogenesis and Astroependymal Cells, Related to Figure 2 (A) Additional marker genes for neurogenesis-related clusters, relevant clusters are indicated on the g-tSNE embedding. (B) Additional marker genes for various astroependymal cell types. The most enriched cluster is indicated. (C) Additional close-ups from validation using RNAscope. Genes and location indicated around the image. Scale bars: 500μm (CB, SVZ); 100μm (OB). (D) Composite image with colored dots representing cells, reconstructed from Allen Brain Atlas images, similar to Figure 3F but showing in situ hybridization. (E,F) Position of reference points used for alignment of multiple sagittal sections of RNAscope (E) and Allen Brain in situ hybridization (F) images. (G) In situ hybridization (Allen Brain Atlas) showing the extent of expression of Slc17a6 and Slc17a7, for comparison with astrocyte cell types.
Figure S2 Markers and Validation of Neurogenesis and Astroependymal Cells, Related to Figure 2 (A) Additional marker genes for neurogenesis-related clusters, relevant clusters are indicated on the g-tSNE embedding. (B) Additional marker genes for various astroependymal cell types. The most enriched cluster is indicated. (C) Additional close-ups from validation using RNAscope. Genes and location indicated around the image. Scale bars: 500μm (CB, SVZ); 100μm (OB). (D) Composite image with colored dots representing cells, reconstructed from Allen Brain Atlas images, similar to Figure 3F but showing in situ hybridization. (E,F) Position of reference points used for alignment of multiple sagittal sections of RNAscope (E) and Allen Brain in situ hybridization (F) images. (G) In situ hybridization (Allen Brain Atlas) showing the extent of expression of Slc17a6 and Slc17a7, for comparison with astrocyte cell types.CC BY · PubMed Central
Figure 3 Molecular and Spatial Diversity of the Astroependymal Cells in the CNS (A) Subtree describing the hierarchy of astroependymal cell types. (B) Schematic sagittal section showing the location of astroependymal cells. (C–E) gt-SNE embedding of all cells from the relevant clusters colored by cluster identity (C), tissue of origin (D), and patterning transcription factors (E). (F) Validation of spatial distribution of astrocytes cell types using multiplex ISH (RNAscope). Images from three consecutive sections were aligned and overlaid (see STAR Methods) to generate a composite with dots representing cells (upper panel). Below, high-magnification images show details of spatial location. Scale bars: top and bottom left, 500 μm; right, 1000 μm (cerebellum overview) and 100μm (olfactory bulb and cerebellum zoom-ins). (G) Gene expression of selected markers shown on the gt-SNE layout.
Figure 3 Molecular and Spatial Diversity of the Astroependymal Cells in the CNS (A) Subtree describing the hierarchy of astroependymal cell types. (B) Schematic sagittal section showing the location of astroependymal cells. (C–E) gt-SNE embedding of all cells from the relevant clusters colored by cluster identity (C), tissue of origin (D), and patterning transcription factors (E). (F) Validation of spatial distribution of astrocytes cell types using multiplex ISH (RNAscope). Images from three consecutive sections were aligned and overlaid (see STAR Methods) to generate a composite with dots representing cells (upper panel). Below, high-magnification images show details of spatial location. Scale bars: top and bottom left, 500 μm; right, 1000 μm (cerebellum overview) and 100μm (olfactory bulb and cerebellum zoom-ins). (G) Gene expression of selected markers shown on the gt-SNE layout.CC BY · PubMed Central
Figure 4 Convergence to a Common State at the Early Stages of Oligodendrocytes Lineage (A and B) gt-SNE embedding of the three first stages of the oligodendrocytes lineage OPC, COP, and NFOL colored by cluster identity (A) and tissue of origin (B). Edges in (A) connect nodes between mutual neighbors (k = 150), but only if they are from different clusters. (C) Gene expression of selected markers overlaid on gt-SNE embedding. (D) Patterning transcription factor analysis. Circles represent fraction of positive cells in each cluster and brain region. (E) Illustration of the proposed model of primary patterning, loss of regional identity and secondary diversification.
Figure 4 Convergence to a Common State at the Early Stages of Oligodendrocytes Lineage (A and B) gt-SNE embedding of the three first stages of the oligodendrocytes lineage OPC, COP, and NFOL colored by cluster identity (A) and tissue of origin (B). Edges in (A) connect nodes between mutual neighbors (k = 150), but only if they are from different clusters. (C) Gene expression of selected markers overlaid on gt-SNE embedding. (D) Patterning transcription factor analysis. Circles represent fraction of positive cells in each cluster and brain region. (E) Illustration of the proposed model of primary patterning, loss of regional identity and secondary diversification.CC BY · PubMed Central
Figure 5 Diversity of the Vasculature and Neural-Crest-like Glia (A) Subtree describing the vasculature and neural-crest-like glia. (B) Expression dot plots for marker genes on log scale and jittered vertically in a uniform interval. Dots are colored only if the trinarization score is positive (posterior probability greater than 0.95), and colors represent the taxonomy rank 4 taxa. (C) The tissue contribution to each cluster represented by the circle size (enteric glia not shown). (D) Schematic illustration of the approximate position of vascular cell types and the meninges. See also Figure S3.
Figure 5 Diversity of the Vasculature and Neural-Crest-like Glia (A) Subtree describing the vasculature and neural-crest-like glia. (B) Expression dot plots for marker genes on log scale and jittered vertically in a uniform interval. Dots are colored only if the trinarization score is positive (posterior probability greater than 0.95), and colors represent the taxonomy rank 4 taxa. (C) The tissue contribution to each cluster represented by the circle size (enteric glia not shown). (D) Schematic illustration of the approximate position of vascular cell types and the meninges. See also Figure S3.CC BY · PubMed Central
Figure S3 Markers of Neural-Crest-like Glia and Vascular Cell Types, Related to Figure 5 (A) Additional marker genes for the neural crest-like glia taxonomy unit, related to Figure 5. First panel on the left show the different clusters. Other panels show the expression (red high) distribution of marker genes. Black arrows indicate small clusters. (B) Similar to (A) but for the vasculature taxon. (C) Scatterplot showing differences between Schwann cells and mature oligodendrocytes (MOL) clusters. Values shown are log2(x+1) transformed average molecule counts. The top 10 differentially expressed genes are shown in red and labeled.
Figure S3 Markers of Neural-Crest-like Glia and Vascular Cell Types, Related to Figure 5 (A) Additional marker genes for the neural crest-like glia taxonomy unit, related to Figure 5. First panel on the left show the different clusters. Other panels show the expression (red high) distribution of marker genes. Black arrows indicate small clusters. (B) Similar to (A) but for the vasculature taxon. (C) Scatterplot showing differences between Schwann cells and mature oligodendrocytes (MOL) clusters. Values shown are log2(x+1) transformed average molecule counts. The top 10 differentially expressed genes are shown in red and labeled.CC BY · PubMed Central
Figure S4 Neurons of the Peripheral Nervous System, Related to Figure 7 (A) Hierarchical structure of the peripheral nervous system neuronal cell types. Neurotransmitters used by each cell types are indicated by the colored dots next to each leaf. (B) gt-SNE embedding of all related cells demonstrate the diversity and abundance of the different clusters. (C) Dot plots for marker genes along the PNS neurons. Dots show gene expression on log scale, and jittered vertically for clarity. Colors are shown only if the trinarization score is positive (posterior probability greater than 0.95 with f = 0.2).
Figure S4 Neurons of the Peripheral Nervous System, Related to Figure 7 (A) Hierarchical structure of the peripheral nervous system neuronal cell types. Neurotransmitters used by each cell types are indicated by the colored dots next to each leaf. (B) gt-SNE embedding of all related cells demonstrate the diversity and abundance of the different clusters. (C) Dot plots for marker genes along the PNS neurons. Dots show gene expression on log scale, and jittered vertically for clarity. Colors are shown only if the trinarization score is positive (posterior probability greater than 0.95 with f = 0.2).CC BY · PubMed Central
Figure S5 Spatial Distribution of All Telencephalon Excitatory Projecting Neurons, Related to Figure 6 Dendrogram above shows the hierarchical structure as in Figure 1C. Left, reference atlas annotation (Allen Brain Atlas). Each column shows the expression map of an individual cluster, where dark brown is high and white is low correlation.
Figure S5 Spatial Distribution of All Telencephalon Excitatory Projecting Neurons, Related to Figure 6 Dendrogram above shows the hierarchical structure as in Figure 1C. Left, reference atlas annotation (Allen Brain Atlas). Each column shows the expression map of an individual cluster, where dark brown is high and white is low correlation.CC BY · PubMed Central
Figure 6 Neuronal Cell Types Are Spatially Restricted Examples of inferred spatial distributions for cell types across the brain. The left column shows reference images from the Allen Brain Atlas. Each row shows one coronal section, ordered rostrocaudally, and each column shows one cluster as indicated at the top. For every cluster and every voxel, the correlation coefficient is depicted by the colormap (dark high, white low). Labels indicate the top-scoring anatomical unit for each cluster. See also Figure S5.
Figure 6 Neuronal Cell Types Are Spatially Restricted Examples of inferred spatial distributions for cell types across the brain. The left column shows reference images from the Allen Brain Atlas. Each row shows one coronal section, ordered rostrocaudally, and each column shows one cluster as indicated at the top. For every cluster and every voxel, the correlation coefficient is depicted by the colormap (dark high, white low). Labels indicate the top-scoring anatomical unit for each cluster. See also Figure S5.CC BY · PubMed Central
Figure S6 Neurotransmitter Modularity, Related to Figure 7 (A) Co-expression of neurotransmitters. Rows and columns represent neurotransmitters. Circle size represents the number of cells in clusters with the indicated combination. Each circle shows (as a pie chart) the brain compartment in which we found the relevant clusters. (B) Analysis of pan-markers along the different ranks of the taxonomy. The heatmap represents the percentage of clusters with trinarization score greater than 90% within the taxonomy unit. Rows represent taxonomy units and columns genes. (C) Similar co-expression analysis as in (A) but with individual genes encoding neurotransmitters and neuropeptides. Upper half of the matrix shows pie charts representing only the compartment distribution. Lower part of the matrix represent the frequency each combination was found. (D) Summary diagram of the biosynthesis components and transporters used to define neurotransmitter phenotypes. Asterisks indicate the genes used separately (glutamatergic neurons) or jointly (all other) to identify each class of neurotransmitter.
Figure S6 Neurotransmitter Modularity, Related to Figure 7 (A) Co-expression of neurotransmitters. Rows and columns represent neurotransmitters. Circle size represents the number of cells in clusters with the indicated combination. Each circle shows (as a pie chart) the brain compartment in which we found the relevant clusters. (B) Analysis of pan-markers along the different ranks of the taxonomy. The heatmap represents the percentage of clusters with trinarization score greater than 90% within the taxonomy unit. Rows represent taxonomy units and columns genes. (C) Similar co-expression analysis as in (A) but with individual genes encoding neurotransmitters and neuropeptides. Upper half of the matrix shows pie charts representing only the compartment distribution. Lower part of the matrix represent the frequency each combination was found. (D) Summary diagram of the biosynthesis components and transporters used to define neurotransmitter phenotypes. Asterisks indicate the genes used separately (glutamatergic neurons) or jointly (all other) to identify each class of neurotransmitter.CC BY · PubMed Central
Figure 7 Drivers of Cellular Diversity (A) Gene ontology analysis of the most highly enriched genes in CNS neuronal clusters. Each panel shows the significantly (false discovery rate [FDR] < 10%) enriched terms ranked by FDR. Bars show the percentage of all genes (belonging to each term) that were enriched and the FDR. Colors indicate major categories of terms, as indicated below the figure. (B) Gene expression of developmental patterning transcription factors is shown along the cell-type taxonomy. Each row represents one transcription factor, and columns represent clusters. Circles represent mean expression values proportional to area. Genes are sorted according to their expression pattern, with Hox genes sorted rostrocaudally. Labels on the right indicate the approximate anatomical extent of the expression of corresponding Hox genes. See also Figures S4, S6, and S7.
Figure 7 Drivers of Cellular Diversity (A) Gene ontology analysis of the most highly enriched genes in CNS neuronal clusters. Each panel shows the significantly (false discovery rate [FDR] < 10%) enriched terms ranked by FDR. Bars show the percentage of all genes (belonging to each term) that were enriched and the FDR. Colors indicate major categories of terms, as indicated below the figure. (B) Gene expression of developmental patterning transcription factors is shown along the cell-type taxonomy. Each row represents one transcription factor, and columns represent clusters. Circles represent mean expression values proportional to area. Genes are sorted according to their expression pattern, with Hox genes sorted rostrocaudally. Labels on the right indicate the approximate anatomical extent of the expression of corresponding Hox genes. See also Figures S4, S6, and S7.CC BY · PubMed Central
Figure S7 Expression Patterns of Transcription Factors, Related to Figure 7 Each section shows the expression of the indicated family of transcription factors, omitting genes that showed uniform or no expression. Circle areas are shown proportional to average gene expression in each cluster, normalized by row.
Figure S7 Expression Patterns of Transcription Factors, Related to Figure 7 Each section shows the expression of the indicated family of transcription factors, omitting genes that showed uniform or no expression. Circle areas are shown proportional to average gene expression in each cluster, normalized by row.CC BY · PubMed Central

Verification

Claims the paper makes

132 Own result · 63 Own interpretation · 14 Own method · 11 Partly supported · 10 No full text of the sources · 9 Supported · 6 No basis given · 3 Sources not found · 3 Not checked yet · 1 Couldn’t confirm · accuracy not yet measured

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  • Probably not a substantial claim. 27
  • It may state two separate claims as one. 96
  • The quote only partly states this claim. 1
116 of 116
  • The paper relies on this without support.

    The mouse nervous system is representative of the mammalian nervous system.

    “The resource presented here lays a solid foundation for understanding the molecular architecture of the mammalian nervous system”
  • The paper relies on this without support.

    The sampled regions and cell numbers are sufficient to capture the full diversity of cell types in the mouse nervous system.

    “In total, we analyzed 19 regions (Figure 1A) but omitted at least the retina, the olfactory epithelium, the vomeronasal organ, the inner ear, and the parasympathetic ganglia.”
  • The paper relies on this without support.

    The adolescent age (postnatal days 20–30) is appropriate for identifying mature cell types and the overall architecture of the mouse nervous system.

    “Although most neuronal types were already mature at the age investigated (postnatal days 20–30)”
  • The paper relies on this without support.

    The developmental origin assigned to each cluster (e.g., telencephalon, diencephalon, midbrain, hindbrain) is correct.

    “We assigned each cluster a unique mnemonic identifier (e.g., MBDOP1), descriptive name (“midbrain dopaminergic neuron”), major class (e.g., “neuron”), neurotransmitter identity, putative developmental origin, anatomical location, and region (Table S3).”
  • The paper relies on this without support.

    OPCs are the progenitors of the entire oligodendrocyte lineage.

    “Since OPCs are the progenitors of the entire oligodendrocyte lineage”
  • The paper relies on this without support.

    Hox genes 6–10 are responsible for patterning the thoracic spinal cord.

    “Hox genes 6–10 (that is, Hoxa6, Hoxb6, …, Hoxd10), which are responsible for patterning the thoracic spinal cord.”
  • The paper relies on this without support.

    Glycine is a widely used inhibitory neurotransmitter only in the caudal parts of the brain and in the spinal cord.

    “Glycine is a widely used inhibitory neurotransmitter only in the caudal parts of the brain and in the spinal cord.”
  • The paper relies on this without support.

    The dendrogram based on gene expression distance reflects true cell type relationships.

    “we calculated a robust dendrogram of cell types (Figure 1C and STAR Methods), showing relationships between cell types based on gene expression distance.”
  • The paper relies on this without support.

    The technical artifacts can be sufficiently mitigated by the cytograph pipeline so that the resulting clusters reflect biological cell types.

    “we developed a multistage analysis pipeline called “cytograph,” which progressively discovers cell types or states while mitigating the impact of technical artifacts”
  • The authors state this as an assumption.

    OPCs are produced by the same progenitors as astrocytes and neurons.

    “OPCs are derived from the neural tube and assumed to be produced by the same progenitors as astrocytes and neurons.”
  • The paper relies on this without support.

    The enteric nervous system has not been previously studied in molecular detail using single-cell methods.

    “The enteric nervous system has not been previously studied in molecular detail using single-cell methods.”
  • The paper relies on this without support.

    The diversity and function of enteric glia are not known in detail.

    “The diversity and function of enteric glia are not known in detail.”
  • The paper relies on this without support.

    Synaptic connectivity, neurotransmission, and membrane conductance are uniquely neuronal properties.

    “But synaptic connectivity, neurotransmission, and membrane conductance are uniquely neuronal properties”
  • The paper relies on this without support.

    Some resolution limit-free algorithms can be tuned to detect smaller clusters, but at the expense of breaking up large clusters.

    “Some variants (so called resolution limit-free algorithms) can be tuned to detect smaller clusters, but at the expense of breaking up large clusters.”
  • The paper relies on this without support.

    Granule cells of the dentate gyrus and the cerebellum are not related.

    “Note: we pooled granule cells of the dentate gyrus and the cerebellum not because we think they are related (they are not), but because they are both extremely abundant and tended to skew manifold learning when included with other cells.”
  • The paper relies on this without support.

    Many, even most, of the cell types described in this paper were not previously associated with known markers.

    “Many, even most, of the cell types described in this paper were not previously associated with known makers.”
  • The authors state this as an assumption.

    The trinarization model applies to a cluster of cells representing a putatively homogeneous population.

    “The model applies to a cluster of cells representing a putatively homogeneous population.”
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Metadata

Authors
Zeisel, A., Hochgerner, H., Lönnerberg, P., Johnsson, A., Memic, F., van der Zwan, J., Häring, M., Braun, E., Borm, L. E., La Manno, G., Codeluppi, S., Furlan, A., Lee, K., Skene, N., Harris, K. D., Hjerling-Leffler, J., Arenas, E., Ernfors, P., Marklund, U., & Linnarsson, S.
Affiliations
  • Karolinska Institutet (SE)
  • UCL Queen Square Institute of Neurology (GB)
Corresponding author
Linnarsson, Sten
Venue
Cell
Publisher
Elsevier BV
Published
2018-08
Volume
174
Issue
4
Pages
999-1014.e22
ISSN
0092-8674 (ISSN-L)
OpenAlex
W2949693884
Cited by
2,552
References
53
Citations by year
2026: 232 · 2025: 317 · 2024: 315 · 2023: 321 · 2022: 361 · 2021: 412 · 2020: 348 · 2019: 200 · 2018: 41
FWCI
78.44
Type
journal article
Language
en
Open access
Locations
  • Cell (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (submittedVersion, cc-by-nd)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Cold Spring Harbor Laboratory Institutional Repository (Cold Spring Harbor Laboratory) (acceptedVersion)
  • UCL Discovery (University College London) (submittedVersion)
  • Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
  • Spiral (Imperial College London) (submittedVersion, cc-by)
Funders
  • Knut and Alice Wallenberg Foundation (2015.0041)
  • Swedish Foundation for Strategic Research (SSF (RIF 14-0057, SB16-0065)
  • Wellcome Trust (108726/Z/15/Z)
  • Swedish Research Council (2016-01526, 2016-03130)
  • SSF (SRL, SB16-0065)
  • Cancerfonden (CAN 2016/572)
  • EU
  • Hjärnfonden (FO2017-0059)
  • SFO Strat Regen (SG-2018)
  • European Research Council (740491)
  • Ollie and Elof Ericssons Foundation
  • Åke Wiberg Foundation (M16-0197)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
  • Life Sciences › Neuroscience › Developmental Neuroscience › Neurogenesis and neuroplasticity mechanisms
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
Keywords
single-cell transcriptomics, neuronal heterogeneity, astrocyte heterogeneity, neurotransmitters, neuropeptides, glutamate, glycine, synaptic connectivity, cell identity genes, membrane conductance
MeSH terms
Animals, Female, Male, Mice, Inbred C57BL, Nervous System, Gene Expression Regulation, Developmental, Gene Expression Profiling, Mice, Gene Regulatory Networks, Single-Cell Analysis, High-Throughput Nucleotide Sequencing, Transcriptome

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