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Research ArticleMethods/New Tools, Novel Tools and Methods

Cross-Laboratory Analysis of Brain Cell Type Transcriptomes with Applications to Interpretation of Bulk Tissue Data

B. Ogan Mancarci, Lilah Toker, Shreejoy J. Tripathy, Brenna Li, Brad Rocco, Etienne Sibille and Paul Pavlidis
eNeuro 20 November 2017, 4 (6) ENEURO.0212-17.2017; DOI: https://doi.org/10.1523/ENEURO.0212-17.2017
B. Ogan Mancarci
1Graduate Program in Bioinformatics, University of British Columbia, Vancouver V6T 1Z4, Canada
2Department of Psychiatry, University of British Columbia, Vancouver V6T 2A1, Canada
3Michael Smith Laboratories, University of British Columbia, Vancouver V6T 1Z4, Canada
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Lilah Toker
2Department of Psychiatry, University of British Columbia, Vancouver V6T 2A1, Canada
3Michael Smith Laboratories, University of British Columbia, Vancouver V6T 1Z4, Canada
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Shreejoy J. Tripathy
2Department of Psychiatry, University of British Columbia, Vancouver V6T 2A1, Canada
3Michael Smith Laboratories, University of British Columbia, Vancouver V6T 1Z4, Canada
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Brenna Li
2Department of Psychiatry, University of British Columbia, Vancouver V6T 2A1, Canada
3Michael Smith Laboratories, University of British Columbia, Vancouver V6T 1Z4, Canada
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Brad Rocco
4Campbell Family Mental Health Research Institute of CAMH
5Department of Psychiatry and the Department of Pharmacology and Toxicology, University of Toronto, Vancouver M5S 1A8, Canada
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Etienne Sibille
4Campbell Family Mental Health Research Institute of CAMH
5Department of Psychiatry and the Department of Pharmacology and Toxicology, University of Toronto, Vancouver M5S 1A8, Canada
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Paul Pavlidis
2Department of Psychiatry, University of British Columbia, Vancouver V6T 2A1, Canada
3Michael Smith Laboratories, University of British Columbia, Vancouver V6T 1Z4, Canada
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Article Figures & Data

Figures

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  • Figure1
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  • Figure 1.
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    Figure 1.

    Mouse brain cell type-specific expression database compiled from publicly available datasets. A, Workflow of the study. Cell type-specific expression profiles are collected from publicly available datasets and personal communications. Acquired samples are grouped based on cell type and brain region. Marker genes are selected per brain region for all cell types. Marker genes are biologically and computationally validated and used in estimation of cell type proportions. B, Brain region hierarchy used in the study. Samples included in a brain region based on the region they were extracted from. For instance, dopaminergic cells isolated from the midbrain were included when selecting marker genes in the context of brainstem and whole brain, and microglia extracted from whole brain isolates were added to all brain regions.

  • Figure 2.
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    Figure 2.

    The NeuroExpresso.org web application. The application allows easy visualization of gene expression across cell types in brain regions. Depicted is the expression of cell types from neocortex region. Alternatively, cell types can be grouped based on their primary neurotransmitter or the purification type. The application can be reached at www.neuroexpresso.org.

  • Figure 3.
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    Figure 3.

    Marker genes are selected for mouse brain cell types and used to estimate cell type profiles. A, Expression of top marker genes selected for cell cortical cell types in cell types represented by RNA-seq (left) and microarray (right) data in NeuroExpresso. Expression levels were normalized per gene to be between 0 and 1 for each dataset. B, Expression of Fam114a1 in neocortex in microarray (top) and RNA-seq (bottom) datasets. Fam114a1 is a proposed fast spiking basket cell marker. It was not selected as a marker in this study due to its high expression in oligodendrocytes and S100a10 expressing pyramidal cells that were both absent from the original study.

  • Figure 4.
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    Figure 4.

    Validation of candidate markers using the ABA. A, ISH images from the ABA. Rightmost panels show the location of the image in the brain according to the Allen Brain mouse reference atlas. Panels on the left show the ISH image and normalized expression level of known and novel dentate gyrus granule cell (upper panels) and Purkinje cell (lower panels) markers. B, Validation status of marker genes detected for Purkinje and dentate gyrus granule cells. Figures used for validation and validation statuses of individual marker genes can be found in Extended Data (Extended Data Fig. 4-1,2,3,4).

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    Figure 5.

    Single-plane image of mouse sensorimotor cortex labeled for Pvalb, Slc32a1, and Cox6a2 mRNAs and counterstained with NeuroTrace. Arrows indicate Cox6a2+ neurons. Scale bar: 10 µm.

  • Figure 6.
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    Figure 6.

    NeuroExpresso reveals novel gene expression patterns. A, Expression of cholinergic, GABAergic, and glutamatergic markers in cholinergic cells from forebrain and thalamus. Forebrain cholinergic neurons express GABAergic markers while thalamus (hubenular) cholinergic neurons express glutamatergic markers. B, left, Expression of Ddc in oligodendrocyte samples from Cahoy et al. (2008), Doyle et al. (2008), and Fomchenko et al. (2011) datasets and in comparison to dopaminergic cells and other (nonoligodendrocyte) cell types from the neocortex in the microarray dataset. In all three datasets, expression of Ddc in oligodendrocytes is comparable to expression in dopaminergic cells and is higher than in any of the other cortical cells. Oligodendrocyte samples show higher than background levels of expression across datasets. Right, Ddc expression in oligodendrocytes, OPCs, and other cell types from Tasic et al. (2016) single-cell dataset. C, Bimodal gene expression in two dopaminergic cell isolates by different labs. Genes shown are labeled as marker genes in the context of midbrain if the two cell isolates are labeled as different cell types.

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    Figure 7.

    MGPs reveal cell type-specific changes in whole tissue data. A, Estimation of cell type profiles for cortical cells in frontal cortex and white matter. Values are normalized to be between 0 and 1. (***p < 0.001). B, left, Oligodendrocyte MGPs in Stanley C cohort. Right, Morphology-based oligodendrocyte counts of Stanley C cohort. Figure adapted from Uranova et al. (2004). C, Estimations of dopaminergic cell MGPs in substantia nigra of controls and PD patients. Values are relative and are normalized to be between 0 and 1 and are not reflective of absolute proportions (**p < 0.01, ***p < 0.001).

Tables

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    Table 1.

    Cell types in NeuroExpresso database

    Cell typeSample countMarker gene countGEO accession and reference
    Whole brain
    Astrocyte9/1*94**GSE9566 (Cahoy et al., 2008), GSE35338 (Zamanian et al., 2012), GSE71585 (Tasic et al., 2016)
    Oligodendrocyte25/1*22**GSE48369, (Bellesi et al., 2013), GSE9566 (Cahoy et al., 2008), GSE13379 (Doyle et al., 2008), GSE30016 (Fomchenko et al., 2011), GSE71585 (Tasic et al., 2016)
    Microglia3/1*131**GSE29949 (Anandasabapathy et al., 2011), GSE71585 (Tasic et al., 2016)
    Cortex
    FS Basket (G42)13/5*18GSE17806 (Okaty et al., 2009), GSE8720 (Sugino et al., 2014), GSE2882 (Sugino et al., 2006), GSE71585 (Tasic et al., 2016)
    Martinotti (GIN)3/1*15GSE2882 (Sugino et al., 2006), GSE71585 (Tasic et al., 2016)
    VIPReln (G30)6/1*33GSE2882 (Sugino et al., 2006), GSE71585 (Tasic et al., 2016)
    Pan-pyramidal***9/17 *35See below
    Pyramidal cortico-thalamic3/2*2GSE2882 (Schmidt et al., 2012), GSE71585 (Tasic et al., 2016)
    Pyramidal Glt25d23/2*3GSE35758 (Schmidt et al., 2012), GSE71585 (Tasic et al., 2016)
    Pyramidal S100a103/4*2GSE35751 (Schmidt et al., 2012), GSE71585 (Tasic et al., 2016)
    Layer 2 3 Pyra2*3GSE71585 (Tasic et al., 2016)
    Layer 4 Pyra3*5GSE71585 (Tasic et al., 2016)
    Layer 6a Pyra2*6GSE71585 (Tasic et al., 2016)
    Layer 6b Pyra2*9GSE71585 (Tasic et al., 2016)
    OPs1*184GSE71585 (Tasic et al., 2016)
    Endothelial2*178GSE71585 (Tasic et al., 2016)
    Basal forebrain
    Forebrain cholinergic390GSE13379 (Doyle et al., 2008)
    Striatum
    Forebrain cholinergic345GSE13379 (Doyle et al., 2008)
    Medium spiny neurons3974GSE13379 (Doyle et al., 2008), GSE55096 (Heiman et al., 2014), GSE54656 (Maze et al., 2014), GSE48813 (Tan et al., 2013a)
    Amygdala
    Glutamatergic310GSE2882 (Sugino et al., 2006)
    Pyramidal Thy1 Amyg1221GSE2882 (Sugino et al., 2006)
    Hippocampus
    DentateGranule317GSE11147 (Perrone-Bizzozero et al., 2011)
    GabaSSTReln354GSE2882 (Sugino et al., 2006)
    Pyramidal Thy1 Hipp1217GSE2882 (Sugino et al., 2006)
    Subependymal
    Ependymal250GSE18765 (Beckervordersandforth et al., 2010)
    Thalamus
    GabaReln353GSE2882 (Sugino et al., 2006)
    Hypocretinergic435GSE38668 (Dalal et al., 2013)
    Thalamus cholinergic340GSE43164 (Görlich et al., 2013)
    Midbrain
    Midbrain cholinergic334GSE13379 (Doyle et al., 2008)
    Serotonergic318GSE36068 (Dougherty et al., 2013)
    Substantia nigra
    Dopaminergic3058**No accession **** (Chung et al., 2005), GSE17542 (Phani et al., 2010)
    Locus coeruleus
    Noradrenergic9133GSE8720 (Sugino et al., 2014), No accession**** (Sugino et al., unpublished observations)
    Cerebellum
    Basket166GSE13379 (Doyle et al., 2008), GSE37055 (Paul et al., 2012)
    Bergmann352GSE13379 (Doyle et al., 2008)
    Cerebellar granule cells311GSE13379 (Doyle et al., 2008)
    Golgi326GSE13379 (Doyle et al., 2008)
    Purkinje4443GSE13379 (Doyle et al., 2008), GSE57034 (Galloway et al., 2014), GSE37055 (Paul et al., 2012), no accession**** (Rossner et al., 2006), GSE8720 (Sugino et al., 2014), no accession**** Sugino et al. (unpublished observations)
    Spinal cord
    Spinal cord cholinergic3124GSE13379 (Doyle et al., 2008)
    • Sample count, number of samples that representing the cell type; gene count, number of marker genes detected for cell type; *, the number of clusters from RNA-seq data; **, marker genes for these cell types are identified in multiple regions displayed yet only the number of the genes that are found in the region specified on the table is shown for the sake of conservation of space. Astrocytes, microglia, and oligodendrocyte markers are identified in the context of all other brain regions (except cerebellum for astrocytes) and dopaminergic markers are also identified for midbrain; ***, pan-pyramidal is a merged cell type composed of all pyramidal samples; ****, data obtained directly from authors.

    • View popup
    Table 2.

    Matching single-cell RNA sequencing data from tasic to well-defined cell types

    Microarray cell type Tasic et al. (2016) cell clusterMatching methodNeuroExpresso cell type name
    AstrocyteAstro Gja1Direct matchAstrocyte
    MicrogliaMicro CtssDirect matchMicroglia
    OligodendrocyteOligo OpalinDirect matchOligodendrocyte
    FS Basket (G42)Pvalb Gpx3, Pvalb Rspo2, Pvalb Wt1, Pvalb Obox3, Pvalb Cpne5Definition: fast spiking pval positive interneuronsFS Basket (G42)
    Martinotti (GIN)Sst Cbln4Direct matchMartinotti (GIN)
    VIPReln (G30)Vip SncgUnique Vip and Sncg expression, high Sncg expression in microarray cell typeVIPReln (G30)
    Pyramidal Glt25d2L5b Tph2, L5b Cdh13Definition: Glt25d2 positive Fam84b positivePyramidal Glt25d2
    Pyramidal S100a10L5a Hsd11b1, L5a Batf3, L5a Tcerg1l, L5a Pde1cDefinition: S100a10 expressing cells from layer 5aPyramidal S100a10
    Pyramidal CrtThalamicL6a Car12, L6a Syt17Direct matchPyramidal CrtThalamic
    —Endo Myl9, Endo Tbc1d4New cell typeEndothelial
    —OPC PdgfraNew cell typeOPCs
    —L4 Ctxn3, L4 Scnn1a, L4 Arf5New cell typeLayer 4 Pyra
    —L2 Ngb, L2/3 Ptgs2New cell typeLayer 2 3 Pyra
    —L6a Mgp, L6a SlaNew cell typeLayer 6a Pyra
    —L6b Serpinb11, L6b Rgs12New cell typeLayer 6b Pyra
    • List of molecular cell types identified by Tasic et al. (2016) and their corresponding cell types in NeuroExpresso. Matching method column defines how the matching was performed. Direct matches are one to one matching between the definition provided by Tasic et al. (2016) for the molecular cell types and definition provided by microarray samples. For “definition” matches, description of the cell type in the original source is used to find molecular cell types that fit the definition. VIPReln, Vip Sncg matching was done based on unique Sncg expression in VIPReln cells in the microarray data. New cell types are well defined cell types that have no counterpart in microarray data.

    • View popup
    Table 3.

    Coexpression of cortical MGSs in single-cell RNA-seq data

    Zeisel et al. (2015; mouse)Darmanis et al. (2015; human)
    Cell typesp valueGene countp valueGene count
    Endothelialp < 0.001180p < 0.001157
    Astrocytep < 0.001282p < 0.001239
    Microgliap < 0.001248p < 0.001201
    Oligodendrocytep < 0.001156p < 0.001201
    OPCs0.8311930.999203
    FS Basket (G42)p < 0.00126p < 0.00126
    Martinotti (GIN)p < 0.00121p < 0.00120
    VIPReln (G30)p < 0.00143p < 0.00136
    Pyramidalp < 0.00134p < 0.00127
    • Statistics were calculated by Wilcoxon rank-sum test.

    • View popup
    Table 4.

    Summaries of statistical analyses

    Figure 7A
    Frontal cortex (n = 91)White matter (n = 88)Group comparison
    MeanSDMeanSDWp value
    Endothelial0.2650.1170.640.11242p < 0.001
    Astrocyte0.4010.1350.7570.101136p < 0.001
    Microglia0.1790.0920.7080.1354p < 0.001
    Oligodendrocyte0.2260.1070.8150.0872p < 0.001
    Olig. precursors0.2150.1230.8170.0780p < 0.001
    FS Basket (G42)0.8650.0810.270.1157744p < 0.001
    VIPReln (G30)0.7920.1020.2880.1427718p < 0.001
    Pyramidal0.8770.0620.2120.1127744p < 0.001
    Figure 7B, left
    MeanSDW (vs control)p value (vs control)
    Schizophrenia (n = 10)0.5980.129750.013
    Bipolar (n = 11)0.3340.242102p < 0.001
    Depression (n = 9)0.3860.1389p < 0.001
    Control (n = 11)0.780.146NANA
    Figure 7B, right
    Uranova et al. (2004)
    Figure 7C
    PDControlGroup comparison
    MeanSDNMeanSDnWp value
    Lesnick0.260.179160.5780.26391190.007
    Moran lateral0.1740.13590.6650.2467600.001
    Moran medial0.3050.191150.7990.1918115p < 0.001
    Zhang0.2010.101100.4890.287181480.004
    • All statistics were calculated by Wilcoxon rank-sum test.

Extended Data

  • Figures
  • Tables
  • Extended Data 1

    R package to perform MGP estimations on whole tissue expression data and to select marker genes from cell type-specific expression data. Download Extended Data 1, ZIP file.

  • Extended Data 2

    R package to find gene homologues across species. Download Extended Data 2, ZIP file.

  • Extended Data 3

    Code for data acquisition, analysis, and generation of all figures. Download Extended Data 3, ZIP file.

  • Figure 4-1,2,3,4

    Figure 4-1. Expression of DG cell markers discovered in the study in ABA mouse brain ISH database. The first gene is Prox1, a known marker of DG cells. The intensity is color coded to range from blue (low expression intensity), through green (medium intensity) to red (high intensity). All images except Ogn is taken from the sagittal view. Ogn is taken from the coronal view.

    Figure 4-2. Expression of Purkinje markers discovered in the study in ABA mouse brain ISH database. The first gene is Pcp2, a known marker of Purkinje cells. The intensity is color coded to range from blue (low expression intensity), through green (medium intensity) to red (high intensity). All images are taken from the sagittal view.

    Figure 4-3. Validation status of DG cell markers.

    Figure 4-4. Validation status of Purkinje cell markers. Download Figure 4-1,2,3,4, PDF file.

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Cross-Laboratory Analysis of Brain Cell Type Transcriptomes with Applications to Interpretation of Bulk Tissue Data
B. Ogan Mancarci, Lilah Toker, Shreejoy J. Tripathy, Brenna Li, Brad Rocco, Etienne Sibille, Paul Pavlidis
eNeuro 20 November 2017, 4 (6) ENEURO.0212-17.2017; DOI: 10.1523/ENEURO.0212-17.2017

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Cross-Laboratory Analysis of Brain Cell Type Transcriptomes with Applications to Interpretation of Bulk Tissue Data
B. Ogan Mancarci, Lilah Toker, Shreejoy J. Tripathy, Brenna Li, Brad Rocco, Etienne Sibille, Paul Pavlidis
eNeuro 20 November 2017, 4 (6) ENEURO.0212-17.2017; DOI: 10.1523/ENEURO.0212-17.2017
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  • Article
    • Visual Abstract
    • Abstract
    • Significance Statement
    • Introduction
    • Materials and Methods
    • Allen Brain Atlas (ABA) ISH data
    • Validation of marker genes using external single-cell data
    • Preprocessing of microarray data
    • Estimation of MGPs
    • Code accessibility
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Keywords

  • Cell Type
  • gene expression
  • Marker Gene
  • Microarray
  • RNA sequencing

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