1. Immunology and Inflammation

Integrative analysis of scRNA-seq and scATAC-seq revealed transit-amplifying thymic epithelial cells expressing autoimmune regulator

  1. Takahisa Miyao
  2. Maki Miyauchi
  3. S Thomas Kelly
  4. Tommy W Terooatea
  5. Tatsuya Ishikawa
  6. Eugene Oh
  7. Sotaro Hirai
  8. Kenta Horie
  9. Yuki Takakura
  10. Houko Ohki
  11. Mio Hayama
  12. Yuya Maruyama
  13. Takao Seki
  14. Hiroto Ishii
  15. Haruka Yabukami
  16. Masaki Yoshida
  17. Azusa Inoue
  18. Asako Sakaue-Sawano
  19. Atsushi Miyawaki
  20. Masafumi Muratani
  21. Aki Minoda
  22. Nobuko Akiyama  Is a corresponding author
  23. Taishin Akiyama  Is a corresponding author
  1. Laboratory for Immune Homeostasis, RIKEN Center for Integrative Medical Sciences, Japan
  2. Immunobiology, Graduate School of Medical Life Science, Yokohama City University, Japan
  3. Laboratory for Cellular Epigenomics, RIKEN Center for Integrative Medical Sciences, Japan
  4. YCI Laboratory for Immunological Transcriptomics, RIKEN Center for Integrative Medical Sciences, Japan
  5. YCI Laboratory for Metabolic Epigenetics, RIKEN Center for Integrative Medical Sciences, Japan
  6. Laboratory for Cell Function Dynamics, RIKEN Center for Brain Science, Japan
  7. Transborder Medical Research Center, and Department of Genome Biology, Faculty of Medicine, University of Tsukuba, Japan
https://doi.org/10.7554/eLife.73998
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Cite this article
  1. Takahisa Miyao
  2. Maki Miyauchi
  3. S Thomas Kelly
  4. Tommy W Terooatea
  5. Tatsuya Ishikawa
  6. Eugene Oh
  7. Sotaro Hirai
  8. Kenta Horie
  9. Yuki Takakura
  10. Houko Ohki
  11. Mio Hayama
  12. Yuya Maruyama
  13. Takao Seki
  14. Hiroto Ishii
  15. Haruka Yabukami
  16. Masaki Yoshida
  17. Azusa Inoue
  18. Asako Sakaue-Sawano
  19. Atsushi Miyawaki
  20. Masafumi Muratani
  21. Aki Minoda
  22. Nobuko Akiyama
  23. Taishin Akiyama
(2022)
Integrative analysis of scRNA-seq and scATAC-seq revealed transit-amplifying thymic epithelial cells expressing autoimmune regulator
eLife 11:e73998.
https://doi.org/10.7554/eLife.73998
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8 figures, 1 table and 9 additional files

Figures

Figure 1 with 3 supplements
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Droplet-based single-cell assays for transposase-accessible chromatin sequencing (scATAC-seq) analysis of thymic epithelial cells (TECs) in 4-week mice.

(A) Uniform manifold approximation and production (UMAP) plot of scATAC-seq data from TECs (EpCAM+ CD45– TER119–) from 4-week mice. Cell clusters are separated by colors and numbers in the plot. The …

Figure 1—figure supplement 1
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Violin plot of chromatin accessibility in thymic epithelial cell (TEC) marker gene regions in each cluster.
Figure 1—figure supplement 2
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Comparison of uniform manifold approximation and production (UMAP) plots of single-cell assays for transposase-accessible chromatin sequencing (scATAC-seq) between two experiments.

(A) Uniform manifold approximation and production (UMAP) plots of single-cell assays for transposase-accessible chromatin sequencing (scATAC-seq) data of murine thymic epithelial cells (TECs). Two …

Figure 1—figure supplement 3
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Comparison of single-cell assays for transposase-accessible chromatin sequencing (scATAC-seq) data between two experiments.

(A) Violin plot depicting chromatin accessibility in Aire gene regions in each cluster. Two single-cell assays for transposase-accessible chromatin sequencing (scATAC-seq) data (Experiment #1 and …

Figure 2 with 6 supplements
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Droplet-based single-cell RNA sequencing (scRNA-seq) analysis of thymic epithelial cells (TECs) in 4-week mice.

(A) Uniform manifold approximation and production (UMAP) plot of scRNA-seq data from TECs (EpCAM+ CD45– TER119–) from 4-week mice. Cell clusters (R0 to R17) are indicated by colors and numbers in …

Figure 2—figure supplement 1
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Heatmap of the top five genes selectively expressed in each subcluster.

Yellow color indicates high expression.

Figure 2—figure supplement 2
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Comparison of single-cell RNA sequencing data between two experiments.

(A) Uniform manifold approximation and production (UMAP) plots of thymic epithelial cell (TEC) single-cell RNA sequencing (scRNA-seq) data. Two scRNA-seq data (Experiment #1 and Experiment #2) were …

Figure 2—figure supplement 3
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Violin plots of marker genes and cell cycle-related genes.

(A) Violin plots for expression level of typical thymic epithelial cell (TEC) marker genes in single-cell RNA sequencing (scRNA-seq) analysis of TECs. (B) Violin plots for expression level of cell …

Figure 2—figure supplement 4
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Comparison of single-cell RNA sequencing data between this study and previous studies.

(A) Integration of single-cell RNA sequencing (scRNA-seq) data derived from a previously reported well-based study (Bornstein et al., 2018) and scRNA-seq data derived from the present droplet-based …

Figure 2—figure supplement 5
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Dot plots of expression of marker genes for our single-cell RNA sequencing (scRNA-seq) clusters in clusters of other scRNA-seq datasets (Bornstein et al., 2018; Dhalla et al., 2020; Wells et al., 2020).
Figure 2—figure supplement 6
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Dot plots of expression of marker genes for Baran-Gales’s single-cell RNA sequencing (scRNA-seq) clusters (Baran-Gale et al., 2020) in clusters of our scRNA-seq datasets.
Figure 3 with 4 supplements
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Integrative analysis of single-cell assays for transposase-accessible chromatin sequencing (scATAC-seq) data and single-cell RNA sequencing (scRNA-seq) data of thymic epithelial cells (TECs).

(A) Gene expression was predicted from scATAC-seq data using Signac. Individual cells in the cluster from scATAC data (clusters 0 to 11) were assigned and transferred to the uniform manifold …

Figure 3—figure supplement 1
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Integrative analysis of single-cell assays for transposase-accessible chromatin sequencing (scATAC-seq) data and single-cell RNA sequencing (scRNA-seq) data of thymic epithelial cells (TECs).

Gene expression was predicted from individual cells in scATAC-seq data. Individual cells in the scATAC data were assigned to an scRNA-seq cluster (R0 to R17).

Figure 3—figure supplement 2
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Comparison of Integrative analysis of single-cell assays for transposase-accessible chromatin sequencing (scATAC-seq) data and single-cell RNA sequencing (scRNA-seq) data of thymic epithelial cells (TECs) between two experiments.

After cell types were annotated in single-cell assays for transposase-accessible chromatin (scATAC) dataset of thymic epithelial cells (TECs) by transferring clusters from an single-cell RNA …

Figure 3—figure supplement 3
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Pseudo-bulk accessibility tracks and frequency of sequenced fragments.

Typical differentially accessible regions between clusters 0 and 4 are depicted.

Figure 3—figure supplement 4
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Trajectory analysis of single-cell RNA sequencing data.

(A) RNA velocity analysis of single-cell RNA sequencing (scRNA-seq) data. (B) Monocle 3 trajectory analysis of single-cell assays for transposase-accessible chromatin sequencing (scATAC-seq) data. …

Figure 4 with 1 supplement
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Subcluster analysis of the thymic epithelial cell (TEC) subset expressing a high level of cell cycle-related genes.

(A) Uniform manifold approximation and production (UMAP) plot of single-cell RNA sequencing (scRNA-seq) data of each subcluster (R1A to R1G) in R1. Cell subclusters (R1A to R1G) are separated by …

Figure 4—figure supplement 1
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Integrative analysis of cluster 4 from single-cell assays for transposase-accessible chromatin sequencing (scATAC-seq) data and subclusters in R1 from single-cell RNA sequencing (scRNA-seq) data.

Gene expression was predicted from individual cells in cluster 4 of scATAC-seq data. Individual cells in the cluster 4 were assigned to the subclusters (R1A to R1G) in R1.

Figure 5 with 3 supplements
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A highly proliferative subset of Aire+ CD80hi medullary thymic epithelial cells (mTECs).

(A) Schematic depiction of cell cycles and Fucci fluorescence. (B) Flow cytometric analysis of TECs from Fucci2a mice crossed with Aire-GFP-reporter mice. The gating strategy is shown. Intensities …

Figure 5—figure supplement 1
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Flow cytometric analysis of medullary thymic epithelial cells (mTECs) from Fucci mouse.

Ly51–UEA-1+ TECs were separated by expression of Venus+ and CD80 (left). CD80 expression was detected in mCherryhi mTECs (red) and Venus+ mTECs (green) in right panels.

Figure 5—figure supplement 2
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Immunostaining of thymic sections from Fucci2a mice with anti-GFP (for Venus staining, green) and anti-keratin-5 (Krt5, blue) antibodies.

Typical panels of three independent experiments are exhibited. Scale bars, 100 μm.

Figure 5—figure supplement 3
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Gene set enrichment analysis of differentially expressed genes between Venus− and Venus + cells.

Gene sets of Aire-dependent tissue-specific antigens (TSAs) (Aire-dep TSAs), Aire-independent TSAs (Aire-indep TSAs), and all TSAs were tested. NES indicates normalized enrichment score.

Figure 6
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Fate mapping study with in vivo BrdU pulse-labeling of Fucci thymic epithelial cells (TECs).

(A) Schematic procedure of in vivo BrdU pulse labeling of Fucci mice, and analysis of BrdU staining in mCherryhiCD80hi and mCherryloCD80hi medullary TECs (mTECs) by flow cytometiric analysis. BrdU …

Figure 6—source data 1

Related to Figure 6B, C and D.

https://cdn.elifesciences.org/articles/73998/elife-73998-fig6-data1-v2.xlsx
Figure 7 with 3 supplements
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Fate mapping study of proliferating Aire+ medullary thymic epithelial cells (mTECs) in in vitro reaggregated thymic organ culture (RTOC).

(A) RTOC experiment to test the differentiation capacity of proliferating Aire+ mTECs. Proliferating Aire+ mTECs (mCherrylo) and E15.5 embryonic thymic cells were reaggregated and subsequently …

Figure 7—figure supplement 1
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Flow cytometric analysis and gene set enrichment analysis of reaggregation thymic organ culture experiments.

(A) Flow cytometric analysis for purity check for sorted mCherrylo medullary thymic epithelial cells (mTECs). (B) Ratio of Venus+ cells in sorted mCherrylo and RTOC. (C) Reaggregated thymic organ …

Figure 7—figure supplement 2
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Analysis of differentially expressed tissue specific antigen (TSA) genes between mCherryhi thymic epithelial cells (TECs) in reaggregated thymic organ culture (RTOC) and mCherrylo TECs.

(A) Gene set enrichment analyses of differentially expressed genes between mCherryhi thymic epithelial cells (TECs) in reaggregated thymic organ culture (RTOC) and mCherrylo TECs (left panels), …

Figure 7—figure supplement 3
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Integration of droplet-based single-cell RNA sequencing and well-based single-cell random displacement amplification sequencing data.

(A) Uniform manifold approximation and production (UMAP) plot of droplet-based single-cell RNA sequencing (scRNA-seq) and well-based single-cell random displacement amplification sequencing …

Figure 8 with 2 supplements
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Proliferating Aire+ CD80hi medullary thymic epithelial cells (mTECs) persist in older mice.

(A) Flow cytometry analysis of CD80hi mTEC subsets from Fucci2a mice aged 4, 8, and 19 weeks. Representative data are shown. Percentages of Venus+ cells in CD80hi mTEC subsets are summarized in the …

Figure 8—figure supplement 1
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Integration of single-cell RNA sequencing data of 4-week-old and fetal thymic epithelial cell.

(A) Single-cell RNA sequencing (scRNA-seq) data in this study (4-week-old mice) were integrated with scRNA-seq data reported by others (Kernfeld et al., 2018) by Seurat package (Find integration …

Figure 8—figure supplement 2
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Single-cell RNA sequencing (scRNA-seq) data of feta thymus (Kernfeld et al., 2018) were integrated with other adult scRNA-seq data (Bornstein et al., 2018; Dhalla et al., 2020; Wells et al., 2020).

Tables

Appendix 1—key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
Genetic reagent (Mus musculus)B6.Cg-Aire < tm2Mmat>/RbrcRIKEN BioResource Research CenterBRC No:RBRC03515
Genetic reagent (Mus. musculus)B6;129-Gt(ROSA)26Sor < tm1(Fucci2aR)Jkn>RIKEN BioResource Research CenterBRC No:RBRC06511
Genetic reagent (Mus. musculus)B6(Cg)-Foxn1tm3(cre)Nrm/JJackson LaboratoryIMSR Cat#JAX:018448, RRID:IMSR_JAX:018448
Genetic reagent (Mus. musculus)CAG-Cre transgenic miceProvided by Jun-ichi Miyazaki
AntibodyPurified anti-mouse CD16/32(Rat monoclonal)BioLegendCat#101302, RRID:AB_312801FACS(1:200)
AntibodyAPC/Cyanine7 anti-mouse CD45(Rat monoclonal)BioLegendCat#103116, RRID:AB_312981FACS (1:200)
AntibodyPE Rat anti-mouse CD45(Rat monoclonal)eBioscienceCat#12-0451-82, RRID:AB_465668FACS (1:200)
AntibodyAPC/Cyanine7 anti-mouse TER-119/Erythroid Cells(Rat monoclonal)BioLegendCat#116223, RRID:AB_2137788FACS (1:200)
AntibodyPE anti-mouse TER-119/Erythroid Cells(Rat monoclonal)eBioscienceCat#12-5921-82, RRID:AB_466042FACS (1:200)
AntibodyBrilliant Violet 510 anti-mouse CD326 (Ep-CAM)(Rat monoclonal)BioLegendCat#118231, RRID:AB_2632774FACS (1:400)
AntibodyFITC anti-mouse CD326 Ep-CAM (Rat monoclonal)BioLegendCat#118208, RRID:AB_1134107FACS (1:400)
AntibodyAlexa Fluor 647 anti-mouse Ly-51 (Rat monoclonal)BioLegendCat#108312, RRID:AB_2099613FACS (1:400)
Chemical compound, drugBiotinylated Ulex Europaeus Agglutinin I (UEA I)Vector LaboratoriesCat#B-1065–2FACS (1:800)
Chemical compound, drugStreptavidin PE/Cyanine7 ConjugateeBioscienceCat#25-4317-82FACS (1:800)
Chemical compound, drugStreptavidin APC/Cyanine7 ConjugateBD PharmingenCat#554063 RRID:AB_10054651FACS (1:400)
AntibodyPE anti-mouse CD80 (Armenian hamster monoclonal)eBioscienceCat#12-0801-81, RRID:AB_465751FACS (1:300)
AntibodyPacific Blue anti-mouse CD80 Antibody (Armenian hamster monoclonal)BioLegendCat#104724, RRID:AB_2075999FACS (1:300)
AntibodyAlexa Fluor 647 anti-mouse Aire (Rat monoclonal)eBioscienceCat#51-5934-80IHC (1:100)
AntibodyPurified Rabbit anti-Keratin 5 (rabbit polyclonal)BioLegendCat#905504, RRID:AB_2616956IHC (1:400)
AntibodyAlexa Fluor 647 anti-Rabbit IgG (H + L)(Donkey polyclonal)InvitrogenCat#A-31573, RRID:AB_2536183IHC (1:1000)
Chemical compound, drugLiberase TMRoche DiagnosticsCat#5401127001
Chemical compound, drug7-Aminoactinomycin DCalbiochemCat#129935-1MGCN
Chemical compound, drugSYTOX Blue Nucleic Acid StainInvitrogenCat#S11348
Software, algorithmFlowJo version 10BDFlowJo, RRID:SCR_008520
Software, algorithmCell Ranger v3.0.010× GenomicsCell Ranger, RRID:SCR_017344
Software, algorithmSEURAT version 4.1.0https://github.com/satijalab/seurat/blob/master/vignettes/install.RmdSEURAT, RRID:SCR_007322
Software, algorithmVelocyto version 0.6https://github.com/velocyto-team/velocyto.RVelocyto, RRID:SCR_018167
Software, algorithmpagoda2 version 1.0.9https://github.com/kharchenkolab/pagoda2pagoda2, RRID:SCR_017094
Software, algorithmCell Ranger ATAC version1.1.010× GenomicsCell Ranger ATAC, RRID:SCR_021160
Software, algorithmSignac version 1.5.0https://github.com/timoast/signac/blob/master/vignettes/install.RmdSignac, RRID:SCR_021158
Software, algorithmMonocle3, version 0.2.3https://cole-trapnell-lab.github.io/monocle3/docs/installation/Monocle3, RRID:SCR_018685
Software, algorithmCLC Genomics Workbench Version 7.5.1QIAGENCLC Genomics Workbench, RRID:SCR_011853
Commercial assay or kitChromium Single Cell 3’ Library & Gel Bead Kit v210× GenomicsCat#PN-120237
Commercial assay or kitChromium Single Cell A Chip Kit10× GenomicsCat#PN-120236
Commercial assay or kitChromium i7 Multiplex Kit10× GenomicsCat#PN-120262
Commercial assay or kitChromium Next GEM Single Cell ATAC Library & Gel Bead Kit10× GenomicsCat#PN-1000176
Commercial assay or kitChromium Next GEM Chip H Single Cell Kit10× GenomicsCat#PN-1000162
Commercial assay or kitSingle Index Kit N, Set A10× GenomicsCat#PN-1000212
Commercial assay or kitNEBNext rRNA Depletion KitNew England BiolabsCat#E6310
Commercial assay or kitNEBNext Ultra Directional RNA Library Prep Kit for IlluminaNew England BiolabsCat#E7420
Commercial assay or kitKAPALibraryQuantificationKits Illumina/UniversalNippon GeneticsCat#KK4824
Chemical compound, drugKAPAHiFi DNA PolymeraseNippon GeneticsCat#KK2102
Commercial assay or kitAgilent High Sensitivity DNA KitAgilent TechnologiesCat#5067–4626
Commercial assay or kitMultina DNA-12000SHIMADZUCat#S292-36600-91

Additional files

Supplementary file 1

List of genes specifically expressed in each cluster.

https://cdn.elifesciences.org/articles/73998/elife-73998-supp1-v2.xlsx
Supplementary file 2

Percentage of single-cell RNA sequencing (scRNA-seq) clusters in single-cell assays for transposase-accessible chromatin sequencing (scATAC-seq) clusters after the integration.

https://cdn.elifesciences.org/articles/73998/elife-73998-supp2-v2.xlsx
Supplementary file 3

Differentially chromatin-accessible regions between cluster 0 and cluster 4.

https://cdn.elifesciences.org/articles/73998/elife-73998-supp3-v2.xlsx
Supplementary file 4

Percentage of single-cell RNA sequencing (scRNA-seq) subclusters of R1 in single-cell assays for transposase-accessible chromatin sequencing (scATAC-seq) clusters after the integration.

https://cdn.elifesciences.org/articles/73998/elife-73998-supp4-v2.xlsx
Supplementary file 5

Gene ontology (GO) analysis of genes differentially expressed in Venus + cells.

https://cdn.elifesciences.org/articles/73998/elife-73998-supp5-v2.xlsx
Supplementary file 6

List of all, Aire-dependent, Aire-independent tissue-specific antigen genes.

https://cdn.elifesciences.org/articles/73998/elife-73998-supp6-v2.xlsx
Supplementary file 7

Summary for assignment of individual single cells in single-cell random displacement amplification sequencing (scRamDa-seq) of mCherryhi, mCherrylo, and mCherryhi-RTOC.

https://cdn.elifesciences.org/articles/73998/elife-73998-supp7-v2.xlsx
Supplementary file 8

Summary for assignment of individual single cells in single-cell random displacement amplification sequencing (scRamDa-seq) of mCherryhi, mCherrylo, and mCherryhi-RTOC.

https://cdn.elifesciences.org/articles/73998/elife-73998-supp8-v2.xlsx
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