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The transcription factor BCL-6 controls early development of innate-like T cells

Nature Immunology volume 21, pages 1058–1069 (2020)Cite this article

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Abstract

Innate T cells, including invariant natural killer T (iNKT) and mucosal-associated innate T (MAIT) cells, are a heterogeneous T lymphocyte population with effector properties preprogrammed during their thymic differentiation. How this program is initiated is currently unclear. Here, we show that the transcription factor BCL-6 was transiently expressed in iNKT cells upon exit from positive selection and was required for their proper development beyond stage 0. Notably, development of MAIT cells was also impaired in the absence of Bcl6. BCL-6-deficient iNKT cells had reduced expression of genes that were associated with the innate T cell lineage, including Zbtb16, which encodes PLZF, and PLZF-targeted genes. BCL-6 contributed to a chromatin accessibility landscape that was permissive for the expression of development-related genes and inhibitory for genes associated with naive T cell programs. Our results revealed new functions for BCL-6 and illuminated how this transcription factor controls early iNKT cell development.

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Fig. 1: The gene expression profile of ST0 and ST1 iNKT cells.
Fig. 2: BCL-6 is expressed specifically in ST0 iNKT cells.
Fig. 3: BCL-6-deficient mice lack iNKT and MAIT cells.
Fig. 4: Accumulation of immature iNKT cells in the absence of BCL-6.
Fig. 5: BCL-6-deficient mice lack mature iNKT cells.
Fig. 6: Impaired progression from ST0 to ST1 in the absence of BCL-6.
Fig. 7: BCL-6 is required for repression of a subset of PLZF target genes.
Fig. 8: Chromatin accessibility around developmentally regulated genes depends on BCL-6.

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Data availability

RNA-seq and ATAC-seq data have been deposited to the Gene Expression Omnibus with the accession code GSE134212. Source data for Figs. 2–5, 7 and 8 and Extended Data Figs. 1–6 are provided with the paper. The data that support the findings of this study are available from the corresponding authors upon request.

References

  1. Verykokakis, M. & Kee, B. L. Transcriptional and epigenetic regulation of innate-like T lymphocyte development. Curr. Opin. Immunol. 51, 39–45 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  2. Bendelac, A., Savage, P. B. & Teyton, L. The biology of NKT cells. Annu Rev. Immunol. 25, 297–336 (2007).

    CAS  PubMed  Google Scholar 

  3. Griewank, K. et al. Homotypic interactions mediated by Slamf1 and Slamf6 receptors control NKT cell lineage development. Immunity 27, 751–762 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Kovalovsky, D. et al. The BTB-zinc finger transcriptional regulator PLZF controls the development of invariant natural killer T cell effector functions. Nat. Immunol. 9, 1055–1064 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Savage, A. K. et al. The transcription factor PLZF directs the effector program of the NKT cell lineage. Immunity 29, 391–403 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Kreslavsky, T. et al. TCR-inducible PLZF transcription factor required for innate phenotype of a subset of γδ T cells with restricted TCR diversity. Proc. Natl Acad. Sci. USA 106, 12453–12458 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Verykokakis, M. et al. Inhibitor of DNA binding 3 limits development of murine slam-associated adaptor protein-dependent “innate” γδ T cells. PLoS ONE 5, e9303 (2010).

    PubMed  PubMed Central  Google Scholar 

  8. Constantinides, M. G., McDonald, B. D., Verhoef, P. A. & Bendelac, A. A committed precursor to innate lymphoid cells. Nature 508, 397–401 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. Lee, Y. J. et al. Lineage-specific effector signatures of invariant NKT cells are shared amongst γδ T, innate lymphoid, and Th cells. J. Immunol. 197, 1460–1470 (2016).

    CAS  PubMed  Google Scholar 

  10. Benlagha, K., Kyin, T., Beavis, A., Teyton, L. & Bendelac, A. A thymic precursor to the NKT cell lineage. Science 296, 553–555 (2002).

    CAS  PubMed  Google Scholar 

  11. Benlagha, K., Wei, D. G., Veiga, J., Teyton, L. & Bendelac, A. Characterization of the early stages of thymic NKT cell development. J. Exp. Med. 202, 485–492 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Gadue, P. & Stein, P. L. NKT cell precursors exhibit differential cytokine regulation and require Itk for efficient maturation. J. Immunol. 169, 2397–2406 (2002).

    CAS  PubMed  Google Scholar 

  13. Dickgreber, N. et al. Immature murine NKT cells pass through a stage of developmentally programmed innate IL-4 secretion. J. Leukoc. Biol. 92, 999–1009 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Lee, Y. J., Holzapfel, K. L., Zhu, J., Jameson, S. C. & Hogquist, K. A. Steady-state production of IL-4 modulates immunity in mouse strains and is determined by lineage diversity of iNKT cells. Nat. Immunol. 14, 1146–1154 (2013).

    CAS  PubMed  Google Scholar 

  15. D’Cruz, L. M., Yang, C. Y. & Goldrath, A. W. Transcriptional regulation of NKT cell development and homeostasis. Curr. Opin. Immunol. 22, 199–205 (2010).

    PubMed  PubMed Central  Google Scholar 

  16. Tripathi, S. et al. Meta- and orthogonal integration of influenza “OMICs” data defines a role for UBR4 in virus budding. Cell Host Microbe 18, 723–735 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Mao, A. P. et al. Multiple layers of transcriptional regulation by PLZF in NKT cell development. Proc. Natl Acad. Sci. USA 113, 7602–7607 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Krishnamoorthy, V. et al. The IRF4 gene regulatory module functions as a read-write integrator to dynamically coordinate T helper cell fate. Immunity 47, 481–497 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Engel, I. et al. Co-receptor choice by Vα14i NKT cells is driven by Th-POK expression rather than avoidance of CD8-mediated negative selection. J. Exp. Med. 207, 1015–1029 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Engel, I., Zhao, M., Kappes, D., Taniuchi, I. & Kronenberg, M. The transcription factor Th-POK negatively regulates Th17 differentiation in Vα14i NKT cells. Blood 120, 4524–4532 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Enders, A. et al. ZBTB7B (Th-POK) regulates the development of IL-17-producing CD1d-restricted mouse NKT cells. J. Immunol. 189, 5240–5249 (2012).

    CAS  PubMed  Google Scholar 

  23. Verykokakis, M. et al. Essential functions for ID proteins at multiple checkpoints in invariant NKT cell development. J. Immunol. 191, 5973–5983 (2013).

    CAS  PubMed  Google Scholar 

  24. Roychoudhuri, R. et al. BACH2 represses effector programs to stabilize Treg-mediated immune homeostasis. Nature 498, 506–510 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Tsukumo, S. et al. Bach2 maintains T cells in a naive state by suppressing effector memory-related genes. Proc. Natl Acad. Sci. USA 110, 10735–10740 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Zook, E. C. & Kee, B. L. Development of innate lymphoid cells. Nat. Immunol. 17, 775–782 (2016).

    CAS  PubMed  Google Scholar 

  27. Hollister, K. et al. Insights into the role of Bcl6 in follicular Th cells using a new conditional mutant mouse model. J. Immunol. 191, 3705–3711 (2013).

    CAS  PubMed  Google Scholar 

  28. Mathew, R. et al. A negative feedback loop mediated by the Bcl6–cullin 3 complex limits TFH cell differentiation. J. Exp. Med. 211, 1137–1151 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Carr, T. et al. The transcription factor lymphoid enhancer factor 1 controls invariant natural killer T cell expansion and Th2-type effector differentiation. J. Exp. Med. 212, 793–807 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Engel, I. et al. Innate-like functions of natural killer T cell subsets result from highly divergent gene programs. Nat. Immunol. 17, 728–739 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Hosoya, T. et al. Global dynamics of stage-specific transcription factor binding during thymocyte development. Sci. Rep. 8, 5605 (2018).

    PubMed  PubMed Central  Google Scholar 

  32. Shih, H. Y. et al. Developmental acquisition of regulomes underlies innate lymphoid cell functionality. Cell 165, 1120–1133 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Mao, A. P., Ishizuka, I. E., Kasal, D. N., Mandal, M. & Bendelac, A. A shared Runx1-bound Zbtb16 enhancer directs innate and innate-like lymphoid lineage development. Nat. Commun. 8, 863 (2017).

    PubMed  PubMed Central  Google Scholar 

  34. Chang, P. P. et al. Identification of Bcl-6-dependent follicular helper NKT cells that provide cognate help for B cell responses. Nat. Immunol. 13, 35–43 (2012).

    CAS  Google Scholar 

  35. Lund, R. et al. Identification of genes involved in the initiation of human Th1 or Th2 cell commitment. Eur. J. Immunol. 35, 3307–3319 (2005).

    CAS  PubMed  Google Scholar 

  36. Fukuda, T. et al. The murine BCL6 gene is induced in activated lymphocytes as an immediate early gene. Oncogene 11, 1657–1663 (1995).

    CAS  PubMed  Google Scholar 

  37. DiToro, D. et al. Differential IL-2 expression defines developmental fates of follicular versus nonfollicular helper T cells. Science 361, eaao2933 (2018).

    PubMed  PubMed Central  Google Scholar 

  38. Ichii, H. et al. Role for Bcl-6 in the generation and maintenance of memory CD8+ T cells. Nat. Immunol. 3, 558–563 (2002).

    CAS  PubMed  Google Scholar 

  39. Ichii, H. et al. Bcl6 is essential for the generation of long-term memory CD4+ T cells. Int. Immunol. 19, 427–433 (2007).

    CAS  PubMed  Google Scholar 

  40. Wu, T. et al. The TCF1–Bcl6 axis counteracts type I interferon to repress exhaustion and maintain T cell stemness. Sci. Immunol. 1, eaai8593 (2016).

    PubMed  PubMed Central  Google Scholar 

  41. Im, S. J. et al. Defining CD8+ T cells that provide the proliferative burst after PD-1 therapy. Nature 537, 417–421 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Choi, Y. S. et al. Bcl6 expressing follicular helper CD4 T cells are fate committed early and have the capacity to form memory. J. Immunol. 190, 4014–4026 (2013).

    CAS  PubMed  Google Scholar 

  43. Bunting, K. L. & Melnick, A. M. New effector functions and regulatory mechanisms of BCL6 in normal and malignant lymphocytes. Curr. Opin. Immunol. 25, 339–346 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Huang, C., Hatzi, K. & Melnick, A. Lineage-specific functions of Bcl-6 in immunity and inflammation are mediated by distinct biochemical mechanisms. Nat. Immunol. 14, 380–388 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Huang, C. et al. The BCL6 RD2 domain governs commitment of activated B cells to form germinal centers. Cell Rep. 8, 1497–1508 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Liu, X. et al. Bcl6 expression specifies the T follicular helper cell program in vivo. J. Exp. Med. 209, 1841–1824 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Liu, X. et al. Genome-wide analysis identifies Bcl6-controlled regulatory networks during T follicular helper cell differentiation. Cell Rep. 14, 1735–1747 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  48. Hatzi, K. et al. BCL6 orchestrates TFH cell differentiation via multiple distinct mechanisms. J. Exp. Med. 212, 539–553 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Luckey, C. J. et al. Memory T and memory B cells share a transcriptional program of self-renewal with long-term hematopoietic stem cells. Proc. Natl Acad. Sci. USA 103, 3304–3309 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Abbas, A. R., Wolslegel, K., Seshasayee, D., Modrusan, Z. & Clark, H. F. Deconvolution of blood microarray data identifies cellular activation patterns in systemic lupus erythematosus. PLoS ONE 4, e6098 (2009).

    PubMed  PubMed Central  Google Scholar 

  51. Verykokakis, M., Boos, M. D., Bendelac, A. & Kee, B. L. SAP protein-dependent natural killer T-like cells regulate the development of CD8+ T cells with innate lymphocyte characteristics. Immunity 33, 203–215 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Moulos, P. & Hatzis, P. Systematic integration of RNA-seq statistical algorithms for accurate detection of differential gene expression patterns. Nucleic Acids Res. 43, e25 (2015).

    PubMed  Google Scholar 

  53. Corces, M. R. et al. An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues. Nat. Methods 14, 959–962 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

    PubMed  PubMed Central  Google Scholar 

  56. Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  57. Zhang, Y. et al. Model-based analysis of ChIP-seq (MACS). Genome Biol. 9, R137 (2008).

    PubMed  PubMed Central  Google Scholar 

  58. Lun, A. T. & Smyth, G. K. csaw: a Bioconductor package for differential binding analysis of ChIP-seq data using sliding windows. Nucleic Acids Res. 44, e45 (2016).

    PubMed  Google Scholar 

Download references

Acknowledgements

This work was supported by a European Commission H2020-MSCA-IF grant (no. 655271) and a Hellenic Foundation for Research and Innovation grant (no. 486) to M.V. and grants from the National Institute of Allergy and Infectious Diseases (R56 AI104303 and R01 AI123396) to B.L.K. M.V. and P.M. were supported by a Stavros Niarchos Foundation start-up grant to BSRC Alexander Fleming (GRA-14451), as part of the Foundation’s initiative to support the Greek research ecosystem. M.S. was supported by Knut and Alice Wallenbergs Foundation and Cancerfonden. A.L.D. was supported by NIH 5R01 AI32771. This work benefited from the project “Strategic Development of the Biomedical Research Institute Alexander Fleming” (MIS 5002562) to P.H., which was implemented under “Action for the Strategic Development on the Research and Technological Sector”, funded by the Operational Programme “Competitiveness, Entrepreneurship and Innovation” (NSRF 2014–2020) and co-financed by Greece and the European Union. We thank A. Melnick (Weill Cornell Medicine) for advice and C. Dagla, G. van der Voort, A. Rao and L. Lenner for technical support. We also thank the InfrafrontierGR Infrastructure for providing mouse and flow cytometry facilities, BSRC Fleming Flow Facility, the University of Chicago Genomics Core Facility and the Cytometry and Antibodies Core Facility, the University of Chicago Comprehensive Cancer Center (P30 CA014599) and the NIH Tetramer Facility.

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Author notes

  1. These authors contributed equally: Marianthi Gioulbasani, Alexandros Galaras.

Authors and Affiliations

  1. Institute for Fundamental Biomedical Research, BSRC Alexander Fleming, Vari, Greece

    Marianthi Gioulbasani, Alexandros Galaras, Sofia Grammenoudi, Panagiotis Moulos, Pantelis Hatzis & Mihalis Verykokakis

  2. Department of Biochemistry and Biotechnology, University of Thessaly, Biopolis, Greece

    Alexandros Galaras

  3. Department of Microbiology and Immunology, Indiana University School of Medicine, Indianapolis, IN, USA

    Alexander L. Dent

  4. Department of Clinical and Experimental Medicine, Experimental Hematopoiesis Unit, Faculty for Health Sciences, Linköping University, Linköping, Sweden

    Mikael Sigvardsson

  5. Department of Pathology and Committee on Immunology, University of Chicago, Chicago, IL, USA

    Barbara L. Kee

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Contributions

M.G. designed, performed and analyzed experiments. A.G. performed bioinformatic analysis of RNA-seq and ATAC-seq data and analyzed experiments under the supervision of P.M. and P.H. S.G. assisted with flow cytometry cell sorting and flow cytometry analysis. A.L.D. provided the Bcl6F/F mouse strain. M.S. performed the RNA-seq experiments. B.L.K. obtained funding, performed ATAC-seq experiments, interpreted data and reviewed and edited the manuscript. M.V. conceptualized the project, obtained funding, supervised research, interpreted data, performed and analyzed experiments and wrote the manuscript. All authors read and approved the final manuscript.

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Correspondence to Barbara L. Kee or Mihalis Verykokakis.

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Editor recognition statement 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 Bcl6 mRNA expression in ST0 and ST1 cells.

a, Flow cytometry plots showing the sorting strategy and purity of ST0 and ST1 cells after sorting. Shown one representative experiment out of three. b, Flow cytometry plots showing expression of PLZF, T-BET and RORγt in ST1 wild-type cells. Graphs show mean percentage and number ± SEM of the indicated populations. n = 7 (PLZFhi, PLZFhiT-BET+, and PLZFloT-BET+), or n = 3 (PLZFintRORγt+) independent experiments c, Graphs showing the normalized counts of Bcl6 mRNA in ST0 and ST1 cells based on RNA-seq data. n = 3 independent experiments (DESeq, **P < 0.01). d, Flow cytometry plots showing the expression of BCL-6 and CD69 (left) or BCL-6 and EGR-2 (right) in Tetr+TCRβ+CD24+CD44— iNKT cells. Shown one representative experiment out of four (CD69) or two (EGR-2).

Source data

Extended Data Fig. 2 The iNKT phenotype is cell-intrinsic.

a, The indicated populations were FACS-sorted from Cd4Cre-expressing heterozygous Bcl6 floxed mice and DNA was submitted to PCR genotyping. In ST3 iNKT, CD4 and DP thymocytes only the germline Bcl6 allele was amplified, whereas in DN and tail samples, both the floxed and the germline alleles were amplified. One experiment shown out of one. b, Flow cytometry plots showing the percentage of iNKT cells in CD45.1+ (wild-type competitor) and CD45.2+ controls (Bcl6F/F) in the thymus from competitive BM chimeric mice. Graphs show the mean percentage ± SEM of iNKT cells in the indicated chimeric mice. n = 5 independent experiments. c, Flow cytometry plots showing the percentage of iNKT cells in CD45.1+ (wild-type competitor) and CD45.2+ (Bcl6Δ/Δ) in the spleen from competitive BM chimeric mice. Graphs showing the mean percentage ± SEM of iNKT cells in the indicated chimeric mice. n = 3 independent experiments. d, Flow cytometry plots showing the percent of Tetr+TCRβ+ iNKT cells after MACS enrichment in the indicated mice. These experiments were repeated twice with similar results. e, f, Flow cytometry plots showing the percent of ST0 (e) and ST1–3 (f) cells in CD45.1+ (competitor) and CD45.2+ control (Bcl6F/F) iNKT cells in competitive bone marrow chimeras. Graphs indicate the mean percentage ± SEM. n = 3 (ST0) or n = 4 (ST1–3) independent experiments. Statistical analysis was performed with two-tailed unpaired t-test. ** P < 0.01.

Source data

Extended Data Fig. 3 Conventional T cell development is normal in the absence of BCL-6.

a, FACS plots showing the expression of CD4 and CD8 (upper panel), and TCRβ (lower panel) in total thymocytes from the indicated mouse strains. b, Histograms showing the total number of the indicated thymocyte populations in control and Bcl6Δ/Δ mice. Graphs show the mean ± SEM. n = 5 independent experiments. c, Histograms showing the abundance of Tcra Vα14-Jα18 and Sh2d1a transcripts in control and Bcl6Δ/Δ sorted DP thymocytes. Graphs show the mean ± SEM. n = 3 independent experiments. d, Histograms showing the expression of CD1D, CD150, and LY108 in DP thymocytes from control and Bcl6Δ/Δ mice. These experiments were repeated three times with identical results. Statistical analysis was performed with two-tailed unpaired t-test.

Source data

Extended Data Fig. 4 BCL-6—deficient spleens lack mature iNKT cells.

a, FACS plots of Tetr+TCRβ+ splenocytes showing the percentage of NKT1 (T-BET+PLZFlo), NKT2 (PLZFhiT-BET—) and NKT17 (RORγt+TBET—) cells in the indicated mouse strains. b, Cell number and percentage of NKT1, NKT2 and NKT17 cells in control and Bcl6Δ/Δ spleens. Graphs show mean ± SEM. n = 5 (NKT1 and NKT2), or n = 4 (NKT17) independent experiments. Statistical analysis was performed with two-tailed unpaired t-test. * P < 0.05, ** P < 0.01, *** P < 0.001. c, Histograms showing the fold reduction of Rorc mRNA in Bcl6Δ/Δ ST1 cells compared to wild-type, based on the RNA-seq data. n = 3 independent experiments (DESeq, **P < 0.01).

Source data

Extended Data Fig. 5 Proliferation and apoptosis of immature iNKT cells is independent of BCL-6.

a, Graphs show the percentage of EDU+ and Ki67+ cells in ST0 and ST1 cells in control littermates and Bcl6Δ/Δ mice. Data represent mean ± SEM. n = 3 independent experiments. b, FACS plots showing expression of IL-7 receptor and LEF1, in control littermates and Bcl6Δ/Δ mice. Experiments were repeated three times with identical results. c, Percentage of FLICA+ cells in the indicated iNKT cell stages, in control littermates and Bcl6Δ/Δ mice. Graphs show mean ± SEM. n = 3 independent experiments with 3 (control) and 4 (Bcl6Δ/Δ) mice. d, Flow cytometry plots showing the percent of total iNKT thymocytes, as Tetramer+TCRβ+ cells, in 10-days old control littermates and Bcl6Δ/Δ mice. e, Numbers and percentage of iNKT cells in the indicated mouse strains. Graphs represent mean ± SEM. n = 2 independent experiments with 5 control and 9 Bcl6Δ/Δ mice. * P < 0.05, ** P < 0.01, *** P < 0.001. Statistical analysis was performed with two-tailed unpaired t-test (a, e), or one-tailed unpaired t-test (c).

Source data

Extended Data Fig. 6 PLZF expression is reduced in the absence of BCL-6.

a, qPCR analysis showing the transcript levels of Zbtb16 in sorted ST0 and ST1 cells from control and Bcl6Δ/Δ mice. Graphs represent the mean ± SEM. n = 3 independent experiments with 3–5 pooled thymi for each genotype. b, FACS plots showing the expression of PLZF protein in ST0 (upper panel) and ST1 (lower panel) cells from the indicated mouse strains. Graphs show the mean percentage ± SEM of PLZF+ cells in the indicated populations. n = 5 (ST0) and n = 8 (ST1) independent experiments. c, Graph showing the geometric MFI of PLZF expression in PLZF-expressing ST0 cells. Graphs represent the mean ± SEM. n = 4 independent experiments. d, Histograms showing the expression of PLZF in ST2 and ST3 cells in the indicated mouse strains. Graphs show the mean percentage ± SEM of PLZF— cells. n = 5 independent experiments. e, Histograms showing the expression of CD69 and CD5 in ST0 iNKT cells from the indicated mouse strains. The corresponding graphs show the mean geometric MFI ± SEM. n = 3 independent experiments. * P < 0.05, ** P < 0.01, *** P < 0.001. Statistical analysis was performed with one-sample t-test (a), two-tailed unpaired t-test (b, d, and e) or two-tailed paired t-test (c).

Source data

Extended Data Fig. 7 Impaired progression from ST0 to ST1 in the absence of BCL-6.

a, GSEA analysis showing enrichment of NKT0-associated genes in ST0 cells, compared to ST1 cells. b, GSEA analysis showing enrichment of NKT17-associated genes in wild-type ST1 cells, compared to Bcl6Δ/Δ ST1 cells. c, GSEA analysis showing enrichment of NKT2-associated genes in Bcl6Δ/Δ ST1 cells, compared to wild-type ST1 cells. n = 3 independent experiments. Normalized enrichment scores (NES) and FDR as implemented by GSEA, based on 1,000 permutations.

Extended Data Fig. 8 Chromatin accessibility profiles near genes that are developmentally regulated.

a, Genome track views of several loci of developmentally-regulated genes in the indicated populations from wild-type mice. b, Heatmaps showing aligned ATAC-seq reads around the center of peaks that are more accessible in ST1 cells (left), or in ST0 cells (right), in the indicated populations. c, Genome track views of Bach2 and Sell genes in wild-type and Bcl6Δ/Δ ST1 cells. d, Genome track views of several loci of developmentally-regulated genes in wild-type and Bcl6Δ/Δ ST0 cells.

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Gioulbasani, M., Galaras, A., Grammenoudi, S. et al. The transcription factor BCL-6 controls early development of innate-like T cells. Nat Immunol 21, 1058–1069 (2020). https://doi.org/10.1038/s41590-020-0737-y

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