Abstract
Dynamic changes in the expression of transcription factors (TFs) can influence the specification of distinct CD8+ T cell fates, but the observation of equivalent expression of TFs among differentially fated precursor cells suggests additional underlying mechanisms. Here we profiled the genome-wide histone modifications, open chromatin and gene expression of naive, terminal-effector, memory-precursor and memory CD8+ T cell populations induced during the in vivo response to bacterial infection. Integration of these data suggested that the expression and binding of TFs contributed to the establishment of subset-specific enhancers during differentiation. We developed a new bioinformatics method using the PageRank algorithm to reveal key TFs that influence the generation of effector and memory populations. The TFs YY1 and Nr3c1, both constitutively expressed during CD8+ T cell differentiation, regulated the formation of terminal-effector cell fates and memory-precursor cell fates, respectively. Our data define the epigenetic landscape of differentiation intermediates and facilitate the identification of TFs with previously unappreciated roles in CD8+ T cell differentiation.
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Change history
27 March 2017
In the version of this article initially published online, some labels in Figure 2 were illegible or incorrect. Those should read "Enhancers (× 103)" along the top and "TE, MP and M" (top to bottom) along the left margin of Figure 2a; "N, TE, MP and M" (left to right) above the plot in Figure 2b; and "GO" below the plot in Figure 2c. Also, in the third sentence of the final paragraph of the final subsection of Results (Validation of PageRank-predicted TFs), the description of the control cells ("shCon-transfected") was incorrect. The correct text is "...lower among shNr3c1-transduced cells than among shCon-transduced cells...". The errors have been corrected in the print, PDF and HTML versions of this article.
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Acknowledgements
We thank the Immgen core team for help in gene-expression data processing; and C. Murre, A. Phan, K. Omilusik, L.A. Shaw, K. Brennan and members of the Goldrath laboratory for critical discussions and review of the manuscript. Supported by the University of California, San Diego (Dr. Huang Memorial Scholarship to B.Y.), the US National Institutes of Health (AI067545 and A1072117 to A.W.G.; U19AI109976 to A.W.G, S.C. and M.E.P.; U54HG006997 and AR070310 to W.W.; and R01 AI109842 and AI40127 to A.R. for research by R.M.P. and J.P.S.-B.), the Leukemia and Lymphoma Society (A.W.G.), the Pew Scholars Fund (A.W.G.), the Pew Latin American Fellows Program in the Biomedical Sciences (R.M.P.) and the Fraternal Order of Eagles Fellow of the Damon Runyon Cancer Research Foundation (J.P.S.-B.).
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B.Y. designed and performed experiments, analyzed the data and wrote the paper; K.Z. performed computational analysis and wrote the paper; B.Y., J.J.M., C.T. and R.C. performed shRNA-mediated knockdown; J.P.S.-B. and R.M.P. provided ATAC-seq data sets for polyclonal CD8+ T cell populations; S.C. and M.E.P. provided reagents, advice for the design of experiments and analysis of experiments and assisted in writing the paper; J.T.C. provided advice and assisted in writing the paper; W.W. supervised the computational analysis and wrote the paper; and A.W.G. supervised the project, designed the experiments, analyzed the data and wrote the paper.
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Integrated supplementary information
Supplementary Figure 1 Transcriptional program of the TE and MP CD8+ T cell subsets.
(a) Comparison of gene expression of TE and MP CD8+ T cell subsets by microarray. Genes that are 1.5-fold upregulated in TE or MP CD8+ T cell subsets are highlighted as blue or orange, respectively. Transcripts did not differ significantly in expression following correction with FDR therefore a fold-change cut-off of 1.5-fold was used for comparisons.(b) Volcano plots of the comparison of total effector and memory CD8+ T cells highlighting TE- or MP-enriched genes. Numbers in bottom corners indicate the number of highlighted genes in that region. (c) The ratio of gene expression of known TFs in TE versus MP subset from microarray. (d) Histograms of protein abundance of key TFs in TE versus MP subset. (e) Comparison of gene expression of TE and MP CD8+ T cell subsets by RNA-seq. Genes that are 2-fold upregulated in TE or MP CD8+ T cell subsets are highlighted as blue or orange, respectively. (f) GSEA plot of total effector versus memory CD8+ T cells with TE- or MP-enriched gene signature generated from (e). (g) The ratio of gene expression of known TFs in TE versus MP subset from RNA-seq. Data are the mean value of gene expression from three independent experiments with pooled spleens from three mice except the TE subset in (a) which is from two independent experiments. Data in (d) are representative of two independent experiments with three mice per group.
Supplementary Figure 2 Experimental design for the characterization of chromatin states and accessibility.
(a) Schematic view of sorting strategy for naive (N), terminal-effector (TE), memory-precursor (MP), and memory (M) CD8+ T cell subsets. (b) Schematic view of experimental design for characterization of the global epigenetic landscape and gene expression using ChIP-seq, ATAC-seq and microarray analyses.
Supplementary Figure 3 Dynamic enhancer establishment is associated with gene expression during CD8+ T cell differentiation.
(a) Violin plots showing the expression of genes associated with different enhancer clusters generated from Figure 2a in naive (N), total effector (EFF) and memory (M) CD8+ T cells generated from microarray data in Best et al. study17. (b) Volcano plots of the comparison of TE and MP CD8+ T cells showing expression of enhancer cluster associated genes. Data are representative of three independent experiments with three mice per group (median value). The statistical analysis was performed by a nonparametric Wilcoxon rank-sum test. n.s. *: p value <0.0001.
Supplementary Figure 4 Full list of TF motifs enriched in subset-specific regulatory elements.
(a) Schematic view of identification of candidate TFs enriched in subset-specific regulatory elements from ATAC-seq and ChIP-seq. (b) Venn diagram showing the overlap of enhancers between CD8+ T cell subsets. (c) Heatmap showing the p-value of transcription factor motif enrichment at subset-specific promoters (left) or enhancers (right) calculated by binomial test using randomly-picked open chromatin regions as background. Motif enrichment or depletion are indicated as red or blue, respectively.
Supplementary Figure 5 Network construction.
Construction of TF regulatory network in CD8+ T cell subsets using ChIP-seq and ATAC-seq as input.
Supplementary Figure 6 Full list of TFs identified by PageRank and comparison of PageRank with TFA.
(a) Heatmap showing PageRank fold enrichment of TFs across CD8+ T cell subsets. (b) A list of TFs revealed by PageRank analysis and motif enrichment in Figure 3. Known TFs important for CD8+ T cell differentiation are highlighted in red. (c) Heatmap showing Z score of PageRank score and TFA score of TFs across CD8+ T cell subsets generated by PageRank and TFA analysis, respectively. (d) Bar graph showing the percentage of known TFs with consistent roles in previous reports for each analysis. (e) Bar graphs showing the fold change of YY1 and Nr3c1 gene expression generated from microarray. Data in (e) are the mean value of gene expression from three independent experiments with pooled spleens from three mice.
Supplementary Figure 7 Ablation of Nr3c1 cofactor Ncor1 and treatment with dexamethasone affect the differentiation of MP CD8+ T cells.
(a) Schematic view of experimental design. OT-I CD8+ T cells were activated in vitro and transduced with control shRNA or shYy1 retroviral vectors and subsequently co-transferred into recipient mice followed by i.v. infection with Lm-OVA. Splenocytes were isolated and analyzed on day 7 of infection. (b) Flow cytometric analysis of KLRG1 and IL-7R expression for cells transduced with shCd4 and shNcor1 in PBL on day 8 of infection. (c) The percentage of TE and MP CD8+ T cells gated on transduced cells on day 8 of infection after knockdown of Ncor1. (d) Flow cytometric analysis of KLRG1 and IL-7R expression for donor cells in mice treated with either vehicle or dexamethasone for 7 days. (e) The percentage of TE and MP CD8+ T cells gated on donor cells on day 8 of Lm-OVA infection after drug treatment. Data are representative from two independent experiments with 5 mice per group. The statistical analysis was performed by two-tailed paired t-test in (c) and two-tailed unpaired t-test in (e). *: p<0.001
Supplementary information
Supplementary Text and Figures
Supplementary Figures 1–7 (PDF 1346 kb)
Supplementary Table 1
Processed RNA-seq gene count dataset of the TE and MP subsets (XLSX 920 kb)
Supplementary Table 2
List of T-bet regulated targets in the TE and MP subsets predictedby TF regulatory network (XLSX 14 kb)
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Yu, B., Zhang, K., Milner, J. et al. Epigenetic landscapes reveal transcription factors that regulate CD8+ T cell differentiation. Nat Immunol 18, 573–582 (2017). https://doi.org/10.1038/ni.3706
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DOI: https://doi.org/10.1038/ni.3706
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