The landscape of regulatory genes in brain-wide neuronal phenotypes of a vertebrate brain
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, China
- University of Chinese Academy of Sciences, China
- Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, China
- School of Future Technology, University of Chinese Academy of Sciences, China
Figures
Figure 1 with 2 supplements
Molecular classification of whole-brain cells in larval zebrafish.
(A) The t-distributed stochastic neighbor embedding (t-SNE) plot of 45,746 single-cell transcriptomes pooled from whole brains (n = 4) and four different individual brain regions (n = 2 each). The …
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Figure 1—source data 1
Bioinformatics processing of raw reads of single-cell samples.
- https://cdn.elifesciences.org/articles/68224/elife-68224-fig1-data1-v3.xlsx
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Figure 1—source data 2
The annotation of 68 clusters of whole-brain sample.
- https://cdn.elifesciences.org/articles/68224/elife-68224-fig1-data2-v3.xlsx
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Figure 1—source data 3
The regional origins and neurotransmitter-type annotation of each whole-brain cluster with well-known markers.
- https://cdn.elifesciences.org/articles/68224/elife-68224-fig1-data3-v3.xlsx
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Figure 1—source data 4
Top 20 marker genes of whole-brain larval zebrafish 68 clusters.
- https://cdn.elifesciences.org/articles/68224/elife-68224-fig1-data4-v3.xlsx
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Figure 1—source data 5
Marker genes of major six cell type in whole brain.
- https://cdn.elifesciences.org/articles/68224/elife-68224-fig1-data5-v3.xlsx
Figure 1—figure supplement 1
Molecular classification of whole-brain cells in larval zebrafish brain.
(A) The schematic showing each samples of whole brain and different brain regions. (B) t-Distributed stochastic neighbor embedding (t-SNE) plot of pooled single-cell transcriptome data from …
Figure 1—figure supplement 2
Molecular classification of whole-brain cells in larval zebrafish brain.
(A) t-Distributed stochastic neighbor embedding (t-SNE) plots showing the expression (in red) of specific markers (eomesa, foxg1a, dlx5a, pitx2 as markers for the forebrain; tal1, en2a as markers …
Figure 2 with 1 supplement
Molecular classification of neuromodulator-type neurons.
(A) The schematic showing the procedure of collecting single-cell transcriptomes of neuromodulator neurons with fluorescence-activated cell sorting (FACS). Using Tg (ETvmat2:GFP) fishline, we could …
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Figure 2—source data 1
The annotation of neuromodulator-type neuronal types with well-known markers.
- https://cdn.elifesciences.org/articles/68224/elife-68224-fig2-data1-v3.xlsx
Figure 2—figure supplement 1
Molecular classification of neuromodulator neurons.
(A) The JaccardRainCloundPlot showing the stability of vmat2+ neuromodulator clusters in Figure 2B. Red line indicated the 0.6 cutoff of Jaccard index to evaluate the cluster stability. Red …
Figure 3 with 4 supplements
The transcription factor (TF) regulatory landscape in whole-brain neuronal clusters.
(A) Schematic showing the strategies to assess the cluster similarity based on effector gene and TF profiles. We focused on clusters of whole-brain glutamatergic/GABAergic neurons and neuromodulator …
Figure 3—figure supplement 1
Hierarchical clustering analysis of whole-brain glutamatergic/GABAegric neurotransmitter-type neurons based on effector gene and transcription factor (TF) profiles.
(A) Hierarchical clustering of 39 glutamatergic/GABAegric neurotransmitter-type neurons based on 1099 effector gene profiles in highly variable genes. Red boxes were highlighted to indicate the …
Figure 3—figure supplement 2
The transcription factor (TF) regulatory landscape in whole-brain glutamatergic/GABAergic neuronal clusters.
(A) Schematic showing the sister clusters identification based on hierarchical clustering of 39 whole-brain glutamatergic/GABAergic neurotransmitter neuronal clusters (IIa: glutamatergic neurons and …
Figure 3—figure supplement 3
Similar pair clusters of neuromodulator-type neurons.
(A-B) Hierarchical clustering of neuromodulator-type neurons based on 1783 effector genes or 319 transcription factors (TFs) in highly variable genes. The tree plots visualizing the matching nodes …
Figure 3—figure supplement 4
Divergent pattern of glutamatergic/GABAergic neurotransmitter-type neuronal clusters.
(A) A schematic for divergent pattern (left) and a summary table (right) showing that neuronal clusters as sister cluster pairs within transcription factor (TF)-based hierarchy were divergent at …
Figure 4 with 1 supplement
Combinatorial transcription factors (TFs) in marking tectal morphological subclasses.
(A) Left: the schematic showing the procedure of collecting single-cell transcriptomes of tectal glutamatergic neurons with fluorescence-activated cell sorting (FACS) using Tg (vglut2a:loxp-DsRed-lox…
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Figure 4—source data 1
The annotation of transcription factors (TFs) expression in each tectal glutamatergic clusters.
- https://cdn.elifesciences.org/articles/68224/elife-68224-fig4-data1-v3.xlsx
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Figure 4—source data 2
Gene labeled morphological analysis of tectal glutamatergic neurons.
- https://cdn.elifesciences.org/articles/68224/elife-68224-fig4-data2-v3.xlsx
Figure 4—figure supplement 1
Combinatorial transcription factors (TFs) in marking tectal morphological subclasses.
(A) Canonical correlation analysis (CCA) of cells from two independent experiments of Tg (vglut2a:loxp-DsRed-loxp-gfp), two rounds overlapping indicated data reproducibility. Two rounds of data were …
Figure 5 with 1 supplement
The post-transcriptional regulatory landscape in neurons with different terminal features but similar transcription factor (TF) profiles.
(A) Dot plot showing Gene Ontology (GO) analysis of differentially expressed genes between each pair clusters with divergent pattern. Red highlighted the category of post-transcriptional regulators. …
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Figure 5—source data 1
Differentially gene expression between sister pair clusters with matched, convergent, and divergent patterns.
- https://cdn.elifesciences.org/articles/68224/elife-68224-fig5-data1-v3.xlsx
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Figure 5—source data 2
The p-value of differential gene expression between sister pair clusters.
- https://cdn.elifesciences.org/articles/68224/elife-68224-fig5-data2-v3.xlsx
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Figure 5—source data 3
Annotation the function of RNA-binding proteins (RBPs).
- https://cdn.elifesciences.org/articles/68224/elife-68224-fig5-data3-v3.xlsx
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Figure 5—source data 4
The binding sites of pattern specific RNA-binding proteins (RBPs).
- https://cdn.elifesciences.org/articles/68224/elife-68224-fig5-data4-v3.xlsx
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Figure 5—source data 5
The combinatorial usage of RNA-binding proteins (RBPs).
- https://cdn.elifesciences.org/articles/68224/elife-68224-fig5-data5-v3.xlsx
Figure 5—figure supplement 1
The post-transcriptional regulatory landscape in neurons with different terminal features but similar transcription factor (TF) profiles.
(A) Dot graph showing the Gene Ontology (GO) analysis of differentially expressed genes between neuronal clusters with convergent pattern. Red highlighted the category of post-transcriptional …
Figure 6
Organization of transcriptional and post-transcriptional regulators in the specification of brain-wide neuronal clusters.
(A) Graphic summary describes the general organization of transcription factors (TFs) and post-transcriptional regulators in the specification of neuronal clusters at the whole-brain level. Effector …
Tables
Key resources table
| Reagent type (species) or resource | Designation | Source or reference | Identifiers | Additional information |
|---|---|---|---|---|
| Strain, strain background (Danio rerio) | Wild type | Dr William | AB | |
| Strain, strain background (Danio rerio) | gad1b:EGFP | Wang et al., 2020 | ZDB-TGCONSTRCT-210507–9 | Tg (gad1b:EGFP) |
| Strain, strain background (Danio rerio) | vglut2a:loxp-DsRed:loxp-GFP | Satou et al., 2012 | ZDB-FISH-150901–9050 | Tg (vglut2a:loxp-DsRed:loxp-GFP) |
| Strain, strain background (Danio rerio) | glyT2:GFP | McLean et al., 2007 | ZDB-ALT-070514–1 | Tg (glyT2:GFP) |
| Strain, strain background (Danio rerio) | vmat2:GFP | Wen et al., 2008 | ZDB-PUB-080102–11 | Tg (ETvmat2:GFP) |
| Strain, strain background (Danio rerio) | elavl3: H2B-GCaMP6s | Freeman et al., 2014 | ZDB-TGCONSTRCT-190827–1 | Tg (elavl3: H2B-GCaMP6s) |
| Recombinant DNA reagent | pTol2-10xUAS:loxp-stop-loxp-tdtomato | This paper | We made this plasmid by ligated three PCR fragments: loxp-stop-loxp, tdTomatocaax and 10× uas backbone | |
| Recombinant DNA reagent | vglut2a:cre | This paper | BAC plasmid use BAC (CH211-111D5) | |
| Recombinant DNA reagent | zic1:gal4FF | This paper | BAC plasmid use BAC (CH211-95F4) | |
| Recombinant DNA reagent | bhlhe22:gal4FF | This paper | BAC plasmid use BAC (CH211-277b21) | |
| Recombinant DNA reagent | en2b:gal4FF | This paper | BAC plasmid use BAC (DKEY-265A7) | |
| Recombinant DNA reagent | foxb1a:gal4FF | This paper | BAC plasmid use BAC (CH211-2C17R) | |
| Recombinant DNA reagent | zbtb18:gal4FF | This paper | BAC plasmid use BAC (CH211-221N23) | |
| Recombinant DNA reagent | irx1a:gal4FF | This paper | BAC plasmid use BAC (CH73-211K12) | |
| Commercial assay or kit | Single Cell 3' Library and Gel Bead kit v2 Chip kit | 10× Genomics | 120237 | scRNA-seq |
| Commercial assay or kit | dsDNA High Sensitivity Assay Kit | AATI | DNF-474–0500 | scRNA-seq |
| Commercial assay or kit | ClonExpressMultiS One Step Cloning Kit | Vazyme | Cat#C112-01/02 | Prepare recombinant plasmid |
| Chemical compound, drug | papain | Worthington Biochemical Corporation | LS003126 | Prepare papain solution to dissociation cells |
| Chemical compound, drug | DNase I | Sigma | Cat#DN25 | Prepare papain solution to dissociate cells |
| Chemical compound, drug | L-cysteine | Sigma | Cat#C6852 | Prepare papain solution to dissociate cells |
| Chemical compound, drug | DMEM/F12 | Invitrogen | Cat#11330032 | Prepare papain solution to dissociate cells |
| Chemical compound, drug | 45% glucose | Gibco | Cat#04196545SB | Prepare wash buffer during dissociation |
| Chemical compound, drug | HEPES | Sigma | Cat#H4034 | Prepare wash buffer during dissociation |
| Chemical compound, drug | FBS | Gibco | Cat#10270106 | Prepare wash buffer during dissociation |
| Chemical compound, drug | DPBS | Invitrogen | Cat#14190–144 | Prepare wash buffer during dissociation |
| Chemical compound, drug | MS222 | Sigma | Cat#A5040 | Anaesthesia |
| Chemical compound, drug | Low melting agarose | Sigma | Cat#A0701 | Embedded fish |
| Software, algorithm | R 3.5.1 | R-project | https://www.r-project.org/ | Data analysis |
| Software, algorithm | Cell Ranger Single Cell Software Suite (v2.1.0) | 10× Genomics | https://support.10xgenomics.com | scRNA-seq data analysis |
| Software, algorithm | Seurat | https://satijalab.org/seurat/ | http://satijalab.org/seurat/ | scRNA-seq data analysis |
| Software, algorithm | bioDist | https://www.bioconductor.org | https://www.bioconductor.org/packages/release/bioc/html/bioDist.html | |
| Software, algorithm | scclusteval | R-package, Jaccard index | https://github.com/crazyhottommy/scclusteval; Tang et al., 2020 | Jaccard index could be used to evaluate the robustness of clusters |
| Software, algorithm | TreeDist | R-package, calculate two tree similarity | https://github.com/ms609/TreeDist; Smith, 2021 | Calculate tree distance |
| Software, algorithm | FIJI | PMID:22743772 | http://fiji.sc/ | Analysis image |
| Software, algorithm | GraphPad Prism | GraphPad Software | https://www.graphpad.com | Data analysis |
| Software, algorithm | FV10-ASW 4.0 Viewer | Olympus | https://www.olympus-global.com | Analysis image |
| Software, algorithm | clusterProfiler | R-package | https://bioconductor.org/packages/release/bioc/html/clusterProfiler.html | GO analysis |
| Software, algorithm | NNLS | R-package, non-negative least squares solver from Lawson and Hanson | https://github.com/rdeits/NNLS.jl; Deits, 2021 | Compare correlation of clusters |
