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Chd4 choreographs self-antigen expression for central immune tolerance

Abstract

Autoreactive T cells are eliminated in the thymus to prevent autoimmunity by promiscuous expression of tissue-restricted self-antigens in medullary thymic epithelial cells. This expression is dependent on the transcription factor Fezf2, as well as the transcriptional regulator Aire, but the entire picture of the transcriptional program has been obscure. Here, we found that the chromatin remodeler Chd4, also called Mi-2β, plays a key role in the self-antigen expression in medullary thymic epithelial cells. To maximize the diversity of self-antigen expression, Fezf2 and Aire utilized completely distinct transcriptional mechanisms, both of which were under the control of Chd4. Chd4 organized the promoter regions of Fezf2-dependent genes, while contributing to the Aire-mediated induction of self-antigens via super-enhancers. Mice deficient in Chd4 specifically in thymic epithelial cells exhibited autoimmune phenotypes, including T cell infiltration. Thus, Chd4 plays a critical role in integrating Fezf2- and Aire-mediated gene induction to establish central immune tolerance.

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Fig. 1: Distinct features of Fezf2-induced TRA genes expressed by mTECs.
Fig. 2: Distinct expression pattern of Aire- and Fezf2-induced genes in mTECs.
Fig. 3: Identification of a Fezf2-interacting partner Chd4.
Fig. 4: Chd4 and Fezf2 cooperatively regulate chromatin structure and transcription.
Fig. 5: Chd4 controls chromatin accessibility of super-enhancers in mTECs.
Fig. 6: Autoimmune phenotypes in Chd4 cKO mice.

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Data availability

The ATAC-Seq, ChIP-Seq and RNA-Seq datasets reported in this manuscript can be accessed in the Gene Expression Omnibus with the accession code GSE144880. Specifically, data on analyses of mTECs are available from accession codes GSE144877 (RNA-Seq), GSE144878 (ChIP-Seq) and GSE144879 (ATAC-Seq). The other referenced publically available datasets are: single-cell RNA-Seq and H3K4me3 and H3K27me3 ChIP-Seq for mTECs (GSE53111); H3K27ac, H3K4me1 and Aire ChIP-Seq in mTECs and ATAC-Seq for wild-type or Aire KO mTECs (GSE92597 and GSE92594); H3K4me2 ChIP-Seq in mTEC-II (GSE103969); H3K4ac and H3K9ac ChIP-Seq in mTECs (GSE114713); and a microarray dataset for various tissues and cells (GSE10246). The microarray dataset for the I-BET 151-treated wild-type or Aire KO mTECs was provided by H. Yoshida and D. Mathis37. Other data that support the findings of this study are available from the corresponding author upon request. Source data are provided with this paper.

Code availability

Scripts needed to reconstruct analysis files will be made available on request.

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Acknowledgements

We thank P. A. Sharp, Y. Kurikawa and L. Danks for insightful and valuable comments, D. Mathis and H. Yoshida for providing information on super-enhancers and the microarray data on Brd4, B. Hendrich for providing Chd4 floxed mice, B. Malissen for providing Foxp3-ires-GFP mice, T. Tsubokawa for technical assistance, and other laboratory members for helpful discussions. This work was supported by a Takeda Visionary Research Grant to H. Takaba from the Takeda Science Foundation, a grant to H. Takaba from the Astellas Foundation for Research on Metabolic Disorders, a grant for Challenging Exploratory Research (26670231), a Challenging Research (Exploratory) Grant (17K19545), a Young Scientists A Grant (16H06228) to H. Takaba, and a Specially Promoted Research Grant (15H05703) to H. Takayanagi from MEXT/JSPS of Japan. This work was also supported by AMED-CREST (20gm1210008) to H. Takayanagi. Studies conducted by H.I.S. at the Massachusetts Institute of Technology were supported by United States Public Health Service grants R01-GM034277 and R01-CA133404 to P. A. Sharp and P01-CA042063 to T. Jacks from the NIH, as well as a Koch Institute Support (core) grant (P30-CA14051) from the National Cancer Institute, and supported in part by an agreement between the Whitehead Institute for Biomedical Research and Novo Nordisk.

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Contributions

Y.T. and H. Takaba designed the experiments, performed most of the experiments and bioinformatics analyses, and wrote the manuscript. R.B., C.D.P.M., Y.A., T.O. and Y.M. performed the experiments using mice. H.I.S., A.T. and T.K. performed the next-generation sequencing and bioinformatics analyses. H. Takayanagi supervised the project and wrote the manuscript.

Corresponding author

Correspondence to Hiroshi Takayanagi.

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Peer review information L. A. Dempsey was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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Extended data

Extended Data Fig. 1 Fezf2-induced genes have distinct features.

a, Venn diagram displaying number of Fezf2-induced genes and Aire-induced genes (fold-change > 2, q < 0.1). RNA-seq was performed for Fezf2 or Aire knockout (KO) (n=3 biologically independent replicates for each genotype) and the wild-type (WT) (control for Fezf2 KO n=3, control for Aire KO n=3 biologically independent replicates) mTECs. P-values were calculated with DESeq2 algorithm (two-tailed Wald test), and p-values were corrected for multiple testing using the Benjamini-Hochberg method. b, Density plot of the entropy score for all genes. Genes with a low entropy score (< 4.5) were defined as TRAs. c, Entropy score of representative Fezf2-induced TRA genes, Aire-induced TRA genes and house-keeping genes. d, Expression of Fabp9 (Fezf2-induced TRA), Mup4 (Aire-induced TRA) and Gapdh (House-keeping genes) in peripheral tissues and cells (GSE10246). e, Density plot of the log2 expression intensity (mean read count per gene in cells expressing the gene) for Fezf2-induced genes (n=623) versus Aire-induced genes (n=1521) at the single-cell level. p = 4.0e-4 (two tailed Wilcoxon rank-sum test). f, Boxplot of the number of Fezf2-induced or Aire-induced genes in single mTECs (n=174). Boxplot indicating median, boxed interquartile range, whiskers extending to the most extreme points within the range between (lower quantile - 1.5 IQR) and (lower quantile + 1.5 IQR), and outliers beyond the range of whiskers are indicated as dots. p = 9.5e-3 (two tailed Wilcoxon rank-sum test). g-j, Result of the affinity-propagation clustering of the expression matrix for randomly selected genes whose number was matched to Aire-induced genes (n=1521) (g) or Fezf2-induced genes (n=623) (i) in single mTECs. Heatmaps of the inter-gene Pearson correlation which are control for Fig. 2b (g) and Fig. 2d (i) are shown. Net similarity calculated from the result of 1000 times affinity-propagation clustering of the expression matrix for randomly selected genes whose number was matched to Aire-induced genes (h) or Fezf2-induced genes (j) are shown as histogram. The arrow indicates the net similarity calculated from the result of affinity-propagation clustering of the expression matrix for Aire-induced genes (h) or Fezf2-induced genes. k, Plot of the tag density for H3K4me3 in mTECs around the TSS of the Fezf2-induced TRA genes (n=159) versus Aire-induced TRA genes (n=541). Average tag counts are presented as lines and standard errors are presented as shades of line. Boxplot depicting the tag density of H3K4me3 around the TSS of Fezf2-induced TRA genes and Aire-induced TRA genes. Boxplot indicating median, boxed interquartile range, whiskers extending to the most extreme points within the range between (lower quantile - 1.5 IQR) and (lower quantile + 1.5 IQR), and outliers beyond the range of whiskers are indicated as dots. p = 3.4e-13 (two tailed Wilcoxon rank-sum test). l, Plot of tag density for H3K27me3 in mTECs around the TSS of Fezf2-induced TRA genes (n=159) versus Aire-induced TRA genes (n=541). Average tag counts are presented as lines and standard errors are presented as shades of line. Boxplot depicting the tag density of H3K27me3 around the TSS of Fezf2-induced TRA genes and Aire-induced TRA genes. Boxplot indicating median, boxed interquartile range, whiskers extending to the most extreme points within the range between (lower quantile - 1.5 IQR) and (lower quantile + 1.5 IQR), and outliers beyond the range of whiskers are indicated as dots. p = 8.8e-8 (two tailed Wilcoxon rank-sum test). m, Average plot (top) and heatmap (bottom) of ChIP-seq reads for H3K4ac, H3K4me2, H3K9ac and H3K27ac in mTECs around the TSS of Fezf2-induced genes (n=640) versus Aire-induced genes (n=1553). Average tag counts are presented as lines and standard errors are presented as shades of line. n, Average plot (top) and heatmap (bottom) of ChIP-seq reads for H3K4ac, H3K4me2, H3K9ac, H3K27ac and H3K4me1 in mTECs around the enhancer of mTECs whose nearest genes were Fezf2-induced genes (n=814) or Aire-induced genes (n=1166). Average tag counts are presented as lines and standard errors are presented as shades of line. o,p, Plot of the ATAC-seq tag density in mTECs for Fezf2-induced genes (n=640) versus Aire-induced genes (n=1553) (o) or Fezf2-induced TRA genes (n=159) versus Aire-induced TRA genes (n=541) (p).

Extended Data Fig. 2 Construction of 3xFlag-Fezf2 knock-in mice.

a, Thymus sections from WT mice at 3 weeks old stained with anti-Chd4, Fezf2 or Aire antibodies and with DAPI (blue). Scale bars indicate 100 μm. Representative data from two independent experiments is indicated. b, Schematic diagram of 3xFlag-Fezf2 knock-in (KI) mice strategy. The Fezf2 genomic locus following homologous recombination after cleavage with CRISPR/Cas9. Fezf2 exons are represented in grey boxes. Guided RNA (gRNA) was designed to cleave after the first base pair of the start codon of Fezf2. An oligo DNA sequence with 45bp with complementary sites was designed to introduce a triple epitope Flag peptide followed with a serine-4xglycine- serine linker into exon 1 of Fezf2. c, FACS profiles for EpCAM and CD45 (top) or Ly51 and UEA-1 of EpCAM+CD45-TECs (bottom) derived from 3xFlag-Fezf2 KI mice or control mice at 6 weeks old. (n=6 biologically independent samples per each genotype). d, The number of TEC (EpCAM+CD45-), mTEC (UEA-1+Ly51-TEC) or cTEC (UEA-1-Ly51+TEC). P-values were calculated by two-tailed unpaired t-test. Center line indicates mean. Error bars, SEM. e, Immunohistochemistry of WT and KI mice staining for Fezf2, Aire, cytokeratin 5 (Krt5), and DAPI (left) or Flag, Aire, Krt5 and DAPI (right). Independent experiments were repeated twice (n=2, 3 biologically independent samples for each experiment). Scale bar, 100μm.

Extended Data Fig. 3 Analysis of TEC and T cell development in the thymus of Chd4 cKO mice.

a, FACS profiles for CD4 and CD8 in the total thymocytes of the control and Chd4 cKO mice at 4-weeks old (left panels). The frequency and number of CD4 single positive (CD4SP), CD8 single positive (CD8SP), CD4 and CD8 double positive (DP) thymocyte populations are indicated (right panels). (n=6, 5 biologically independent replicates for control and Chd4 cKO mice). b, TCRβ and CD69 expression profiles of DP thymocytes from the control and Chd4 cKO mice at 4-weeks old (left panels). The frequency and number of TCRβ+CD69+ cells in the DP thymocytes are indicated (right panels) (n = 6, 5 for control and Chd4 cKO mice). c, FACS profiles for CD25 and Foxp3 in CD4SP thymocytes from control and Chd4 cKO mice at 4-weeks old (left panels). The frequency and number of CD25+Foxp3+ cells in CD4SP thymocytes are indicated (right panels) (n = 3 biologically independent replicates per each genotypes). d, Structure of the thymus in Chd4 cKO mice or control mice at 4-weeks old (H&E staining). C; cortex, and M; medulla. Scale bars indicate 1mm (top) or 100μm (bottom). Independent experiments were repeated twice (n=1, 2 biologically independent samples for each experiment). e, Thymus sections from Chd4 cKO mice or control mice at 4-weeks old stained with anti-Keratin 5 (Krt5), Keratin 8 (Krt8), Fezf2 and Aire antibodies. Scale bars indicate 100μm. Three technically and biologically independent experiments were performed. f, FACS profiles for Ly51 and UEA-1 of EpCAM+CD45-TECs derived from Chd4 cKO mice or control mice at 3-weeks old (left panels). The frequency and number of Ly51+UEA-1- (cTECs) or Ly51-UEA-1+ (mTECs) among the TECs (right panels). (n=6 biologically independent replicates per each genotypes). g, FACS profiles for CD80 and MHC class II in mTECs derived from Chd4 cKO mice or control mice at 3-weeks old (left panels). The frequency and number of CD80hiMHCIIhi mTECs (mTEChi) or CD80loMHCIIlo mTECs (mTEClo) are indicated (right panels) (n=6 biologically independent replicates per each genotypes). h, FACS profiles of CD4 and CD8 of the total cells in the spleen or lymph node of control and Chd4 cKO mice at 6-7 months old (left panels). The frequency and number of the CD4 single positive (CD4SP) and CD8 single positive (CD8SP) populations are indicated (right panels). (n=8 biologically independent replicates per each genotypes). (***p < 0.0001, unpaired two tailed t-test). Error bars, SEM.

Extended Data Fig. 4 Chd4 and Fezf2 cooperatively regulate specific chromatin structure and genes expression on a genome-wide scale.

a, b, Scatter plot of RNA-seq data of control (a) and Chd4 cKO (b) mTECs. Pearson correlation (number of genes = 21970) between three replicates were indicated. (Two-tailed t-test.) c, Heatmap of ATAC-seq reads for two replicates of WT, Fezf2 cKO and Chd4 cKO mTECs. Read count around promoter proximal or distal ATAC-seq peaks in mTECs were indicated. d, Scatter plot of ATAC-seq tag count in each replicate of WT, Fezf2 cKO and Chd4 cKO mTECs. Pearson correlation between two replicates were indicated (number of bin = 273213). e, Heatmap of ATAC-seq reads from WT, Fezf2 cKO or Chd4 cKO mTECs were indicated for each class of ATAC peaks in mTECs. Promoter proximal or distal ATAC peaks in mTECs were classified according to their dependency on Fezf2 or Chd4. f, Normalized ATAC-seq (WT, Fezf2 cKO and Chd4 cKO mTECs) profiles at promoter regions of genes in mTECs. Numbers to the left indicate the ranges of normalized tag counts. g, Effect of Chd4 on the accessibility of Fezf2-induced (fold-change in tag counts > 2), Fezf2-neutral (> 2 fold-change in tag counts > 0.5) and Fezf2-repressed (0.5 > fold-change in tag counts) peaks (left panels). Effect of Fezf2 on the accessibility of Chd4-induced (fold-change in the tag counts > 2), Chd4-neutral (> 2 fold-change in tag counts > 0.5) and Chd4-repressed (> 0.5 fold-change in tag counts) peaks (right panels). All peaks (top), promoter proximal peaks (middle), and promoter distal peaks (bottom) were analyzed. The cumulative distribution plot is presented as the cumulative probability (vertical axis) versus the log2 fold-change of the tag counts. p-values are provided in the figure (two-tailed Wilcoxon rank-sum test). h, Cumulative distribution plot of the Fezf2-dependent (left panels) or Chd4-dependent (right panels) expression change in genes near the peaks induced by Fezf2 and Chd4 (WT / Chd4 cKO > 2, WT / Fezf2 cKO > 2), or uninduced by Fezf2 and Chd4 (WT / Chd4 cKO < 2, WT / Fezf2 cKO < 2) was analyzed at all peaks (top), proximal promoter peaks (middle), and promoter distal peaks (bottom). Plots are presented as the cumulative probability (vertical axis) versus log2 fold-change of the expression values between the WT and Fezf2 KO mTECs (left panels), or control and Chd4 cKO mTECs (right panels) (horizontal axis). p-values are shown by one-tailed Wilcoxon rank-sum test.

Extended Data Fig. 5 ChIP-seq analysis of Fezf2.

a, Average plot (top) and heatmap (bottom) of Fezf2 ChIP-seq reads for replicate 1 and 2 around the promoter proximal Fezf2-binding sites (n=2018). Average tag counts are presented as lines and standard errors are presented as shades of line. b, Average plot (top) and heatmap (bottom) of ChIP-seq reads for H3K4ac, H3K4me2, H4K4me3, H3K9ac, H3K27ac and H3K27me3 in mTECs around the promoter proximal Fezf2-binding sites (n=2018, ChIP-seq peaks of Fezf2). Average tag counts are presented as lines and standard errors are presented as shades of line. c, Average plot (top) and heatmap (bottom) of mTEC ATAC-seq reads around the promoter proximal Fezf2-binding sites (n=2018). Average tag counts are presented as lines and standard errors are presented as shades of line. d, Plot of the tag density for Fezf2-ChIP around the TSS of the Fezf2-induced genes (n=640) versus Aire-induced genes (n=1553). Average tag counts are presented as lines and standard errors are presented as shades of line. e, Scatter and contour plot of log2 fold-change of ATAC-seq tag count at the Fezf2 (n=2018) or Aire (n=10761) ChIP-seq peaks. Red box; the peaks with log2 (WT / Chd4 cKO) > 1 and log2 (WT / Fezf2 cKO) > 1. Blue box; the peaks with log2 (WT / Chd4 cKO) < -1 and log2 (WT / Fezf2 cKO) < -1. Orange dotted vertical line, fold-change = -1 (left) or = 1 (right); green dotted horizontal line, fold-change = -1 (top) or = 1 (bottom). The frequency of peaks is shown in the red or blue boxes. p-values from two-tailed Fisher’s exact test are indicated.

Extended Data Fig. 6 Chd4 and Aire control chromatin structure at super-enhancers (SEs).

a, Cumulative distribution plot of the Chd4-dependency of the TRA genes induced by the Fezf2 (n=519) or Aire (n=1304) and other TRA genes (n=708), presented as the cumulative probability (vertical axis) versus log2 fold-change of the expression values between the control and Chd4 cKO mTECs (horizontal axis). P-values from two-tailed Wilcoxon rank-sum test are indicated. b-d, Effect of Aire on the accessibility of Chd4-induced (fold-change in the tag counts > 2), Chd4-neutral (> 2 fold-change in the tag counts > 0.5) and Chd4-repressed (> 0.5 fold-change in the tag counts) peaks (left panels). Effect of Chd4 on the accessibility of Aire-induced (fold-change in the tag counts > 2), Aire-neutral (> 2 fold-change in the tag counts > 0.5) and Aire-repressed (> 0.5 fold-change in the tag counts) peaks (right panels) was analyzed at all peaks (b), promoter proximal peaks (c), and promoter distal peaks (d). The cumulative distribution plot is presented as the cumulative probability (vertical axis) versus log2 fold-change of the tag counts. p-values are provided in the figure (two-tailed Wilcoxon rank-sum test). e, Raw mapped read at SEs by Chd4 ATAC-seq and H3K27ac ChIP-seq analyses in mTECs. Numbers are the ranges of normalized tag densities. SE loci; blue bar. f, Workflow of the identification of the co-expression of microclusters among the Chd4-, Aire-, and Fezf2-induced genes and super-enhancer (SE) neighborhood genes. For expression matrices containing genes regulated by Aire, Chd4, or Fezf2, or random genes and SE neighborhood genes, in which the TSS was nearest to the center of the SE, gene-by-gene Pearson correlations were calculated and affinity-propagation clustering was performed based on the Pearson correlations, with no preset number of clusters (SE neighborhood genes, n = 978; Aire-induced genes, n = 1485; Chd4-induced genes, n = 1358; Fezf2-induced genes, n = 566; random genes (matched to Aire-induced genes), n = 1485). Heatmaps of the Pearson correlations of selected co-expression clusters are shown in Fig. 5h. g, Heatmaps of the gene-by-gene Pearson correlations calculated from the expression matrix containing the SE neighborhood genes and genes induced by Aire, Chd4 or Fezf2, or random genes (Aire-induced genes and SE genes, n = 2463; Chd4-induced genes and SE genes, n = 2336; Fezf2-induced genes and SE genes, n = 1544; random genes (matched to Aire-induced genes) and SE genes, n = 2463). h, Distribution of the mean intracluster correlation of the co-expression clusters containing the SE neighborhood genes and genes induced by Aire, Chd4 or Fezf2, or random genes. For each of the Aire-, Chd4-, and Fezf2-induced genes, 1000 random permutations of the same size as the target gene sets were performed (gray histogram). i, Relationship between the mean intracluster correlation of the co-expression clusters and the number of Chd4-, Aire-, and Fezf2-induced genes or SE neighborhood genes included in each co-expression cluster. Note that one significant cluster include about 15-19 (median) Aire- or Chd4-depedent TRA genes and only a few SE neighborhood genes. j, Quantification of the interactions between the SE neighborhood genes and Aire- or Chd4-induced genes, defined as local (< 1 Mb on the same chromosome), intrachromosomal (> 1 Mb on the same chromosome), or interchromosomal (different chromosomes) in the significant co-expression microclusters shown in panel Fig. 5h.

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Tomofuji, Y., Takaba, H., Suzuki, H.I. et al. Chd4 choreographs self-antigen expression for central immune tolerance. Nat Immunol 21, 892–901 (2020). https://doi.org/10.1038/s41590-020-0717-2

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