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A RUNX–CBFβ-driven enhancer directs the Irf8 dose-dependent lineage choice between DCs and monocytes

Abstract

The transcription factor IRF8 is essential for the development of monocytes and dendritic cells (DCs), whereas it inhibits neutrophilic differentiation. It is unclear how Irf8 expression is regulated and how this single transcription factor supports the generation of both monocytes and DCs. Here, we identified a RUNX–CBFβ-driven enhancer 56 kb downstream of the Irf8 transcription start site. Deletion of this enhancer in vivo significantly decreased Irf8 expression throughout the myeloid lineage from the progenitor stages, thus resulting in loss of common DC progenitors and overproduction of Ly6C+ monocytes. We demonstrated that high, low or null expression of IRF8 in hematopoietic progenitor cells promotes differentiation toward type 1 conventional DCs, Ly6C+ monocytes or neutrophils, respectively, via epigenetic regulation of distinct sets of enhancers in cooperation with other transcription factors. Our results illustrate the mechanism through which IRF8 controls the lineage choice in a dose-dependent manner within the myeloid cell system.

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Fig. 1: Identification of a putative enhancer 56 kb downstream of the Irf8 TSS.
Fig. 2: The +56 kb Irf8 enhancer is required for the development of cDC1s but not monocytes.
Fig. 3: The dose-dependent impact of IRF8 on the generation of cDCs, monocytes and neutrophils.
Fig. 4: Enhancer landscapes in myeloid progenitors are determined in an Irf8 dose-dependent manner.
Fig. 5: Comparison of IRF8-bound enhancers between WT monocytes and cDC1s.
Fig. 6: Clustering of active enhancers indicates RUNXs as the TFs acting on the +56 kb Irf8 enhancer.
Fig. 7: RUNX–CBFβ induces Irf8 expression via the +56 kb Irf8 enhancer.

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Data availability

The data supporting the findings of this study are available from the corresponding authors (T.T. and A.N.) upon reasonable request. The sequencing data generated in this study were deposited in the Gene Expression Omnibus database (https://www.ncbi.nlm.nih.gov/geo/). RNA-seq data, ChIP-seq data and ATAC-seq data are available at GSE149762. The following data were retrieved from Gene Expression Omnibus database: RNA-seq for WT pDCs (GSE121446); RNA-seq for WT B cells, WT CD4+ T cells and WT CD8+ T cells (GSE127267); RNA-seq for WT CLPs (GSE109805); RUNX1 ChIP-seq for Hoxb8-FL cells (GSE84328); RUNX1 ChIP-seq for FDC-P1 cells (GSE81179); RUNX2 ChIP-seq for MA9CL cells (GSE120063); and microarray for IRF8 and IRF8+ LMPPs (GSE113748). The following data were retrieved from DNA Data Bank of Japan Sequence Read Archive (https://www.ddbj.nig.ac.jp/): H3K27ac ChIP-seq for WT GMP, WT MDP, WT cMoP, WT Ly6C+ monocyte, WT CDP, WT neutrophil, Irf8–/– GMP, Irf8–/– MDP and Irf8–/– cMoP (PRJDB3411); and IRF8 ChIP-seq for WT MDP (PRJDB3411). The sequencing data and public data used in this study are listed in Supplementary Table 2. Additionally, the table contains information on the figures associated with these data. Source data are provided with this paper.

References

  1. Shlyueva, D., Stampfel, G. & Stark, A. Transcriptional enhancers: from properties to genome-wide predictions. Nat. Rev. Genet. 15, 272–286 (2014).

    Article  CAS  PubMed  Google Scholar 

  2. Tamura, T., Kurotaki, D. & Koizumi, S. Regulation of myelopoiesis by the transcription factor IRF8. Int. J. Hematol. 101, 342–351 (2015).

    Article  CAS  PubMed  Google Scholar 

  3. Sichien, D. et al. IRF8 transcription factor controls survival and function of terminally differentiated conventional and plasmacytoid dendritic cells, respectively. Immunity 45, 626–640 (2016).

    Article  CAS  PubMed  Google Scholar 

  4. Kurotaki, D. et al. IRF8 inhibits C/EBPα activity to restrain mononuclear phagocyte progenitors from differentiating into neutrophils. Nat. Commun. 5, 4978 (2014).

    Article  CAS  PubMed  Google Scholar 

  5. Tamura, T., Nagamura-Inoue, T., Shmeltzer, Z., Kuwata, T. & Ozato, K. ICSBP directs bipotential myeloid progenitor cells to differentiate into mature macrophages. Immunity 13, 155–165 (2000).

    Article  CAS  PubMed  Google Scholar 

  6. Bigley, V. et al. Biallelic interferon regulatory factor 8 mutation: a complex immunodeficiency syndrome with dendritic cell deficiency, monocytopenia and immune dysregulation. J. Allergy Clin. Immunol. 141, 2234–2248 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Cytlak, U. et al. Differential IRF8 transcription factor requirement defines two pathways of dendritic cell development in humans. Immunity 53, 353–370 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Geissmann, F. et al. Development of monocytes, macrophages, and dendritic cells. Science 327, 656–661 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Guilliams, M., Mildner, A. & Yona, S. Developmental and functional heterogeneity of monocytes. Immunity 49, 595–613 (2018).

    Article  CAS  PubMed  Google Scholar 

  10. Guilliams, M. et al. Dendritic cells, monocytes and macrophages: a unified nomenclature based on ontogeny. Nat. Rev. Immunol. 14, 571–578 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Dress, R. J. et al. Plasmacytoid dendritic cells develop from Ly6D+ lymphoid progenitors distinct from the myeloid lineage. Nat. Immunol. 20, 852–864 (2019).

    Article  CAS  PubMed  Google Scholar 

  12. Anderson, D. A. III, Dutertre, C.-A., Ginhoux, F. & Murphy, K. M. Genetic models of human and mouse dendritic cell development and function. Nat. Rev. Immunol. https://doi.org/10.1038/s41577-020-00413-x (2020).

  13. Pietras, E. M. et al. Functionally distinct subsets of lineage-biased multipotent progenitors control blood production in normal and regenerative conditions. Cell Stem Cell 17, 35–46 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Fogg, D. K. et al. A clonogenic bone marrow progenitor specific for macrophages and dendritic cells. Science 311, 83–87 (2006).

    Article  CAS  PubMed  Google Scholar 

  15. Yáñez, A. et al. Granulocyte-monocyte progenitors and monocyte-dendritic cell progenitors independently produce functionally distinct monocytes. Immunity 47, 890–902 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Weinreb, C., Rodriguez-Fraticelli, A., Camargo, F. D. & Klein, A. M. Lineage tracing on transcriptional landscapes links state to fate during differentiation. Science 367, eaaw3381 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Liu, Z. et al. Fate mapping via Ms4a3-expression history traces monocyte-derived cells. Cell 178, 1509–1525 (2019).

    Article  CAS  PubMed  Google Scholar 

  18. Hettinger, J. et al. Origin of monocytes and macrophages in a committed progenitor. Nat. Immunol. 14, 821–830 (2013).

    Article  CAS  PubMed  Google Scholar 

  19. Kurotaki, D. et al. Essential role of the IRF8-KLF4 transcription factor cascade in murine monocyte differentiation. Blood 121, 1839–1849 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Kurotaki, D. et al. Epigenetic control of early dendritic cell lineage specification by the transcription factor IRF8 in mice. Blood 133, 1803–1813 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Kurotaki, D. et al. Transcription factor IRF8 governs enhancer landscape dynamics in mononuclear phagocyte progenitors. Cell Rep. 22, 2628–2641 (2018).

    Article  CAS  PubMed  Google Scholar 

  22. Grajales-Reyes, G. E. et al. Batf3 maintains autoactivation of Irf8 for commitment of a CD8α+ conventional DC clonogenic progenitor. Nat. Immunol. 16, 708–717 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Schonheit, J. et al. PU.1 level-directed chromatin structure remodeling at the Irf8 gene drives dendritic cell commitment. Cell Rep. 3, 1617–1628 (2013).

    Article  PubMed  Google Scholar 

  24. Durai, V. et al. Cryptic activation of an Irf8 enhancer governs cDC1 fate specification. Nat. Immunol. 20, 1161–1173 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Bagadia, P. et al. An Nfil3Zeb2Id2 pathway imposes Irf8 enhancer switching during cDC1 development. Nat. Immunol. 20, 1174–1185 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Kawano, Y. et al. Stable lines and clones of long-term proliferating normal, genetically unmodified murine common lymphoid progenitors. Blood 131, 2026–2035 (2018).

    Article  CAS  PubMed  Google Scholar 

  27. Lara-Astiaso, D. et al. Chromatin state dynamics during blood formation. Science 345, 943–949 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Chopin, M. et al. Transcription factor PU.1 promotes conventional dendritic cell identity and function via induction of transcriptional regulator DC-SCRIPT. Immunity 50, 77–90 (2019).

    Article  CAS  PubMed  Google Scholar 

  29. Tamura, T. et al. IFN regulatory factor-4 and -8 govern dendritic cell subset development and their functional diversity. J. Immunol. 174, 2573–2581 (2005).

    Article  CAS  PubMed  Google Scholar 

  30. Lee, J. et al. Lineage specification of human dendritic cells is marked by IRF8 expression in hematopoietic stem cells and multipotent progenitors. Nat. Immunol. 18, 877–888 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Gonzalez, A. J., Setty, M. & Leslie, C. S. Early enhancer establishment and regulatory locus complexity shape transcriptional programs in hematopoietic differentiation. Nat. Genet. 47, 1249–1259 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Schlitzer, A. et al. Identification of cDC1- and cDC2-committed DC progenitors reveals early lineage priming at the common DC progenitor stage in the bone marrow. Nat. Immunol. 16, 718–728 (2015).

    Article  CAS  PubMed  Google Scholar 

  33. Factor, D. C. et al. Epigenomic comparison reveals activation of “seed” enhancers during transition from naive to primed pluripotency. Cell Stem Cell 14, 854–863 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Kim, S. et al. High amount of transcription factor IRF8 engages AP1-IRF composite elements in enhancers to direct type 1 conventional dendritic cell identity. Immunity 53, 759–774 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Scott, E. W., Simon, M. C., Anastasi, J. & Singh, H. Requirement of transcription factor PU.1 in the development of multiple hematopoietic lineages. Science 265, 1573–1577 (1994).

    Article  CAS  PubMed  Google Scholar 

  36. Heinz, S. et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38, 576–589 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Satpathy, A. T. et al. Runx1 and Cbfβ regulate the development of Flt3+ dendritic cell progenitors and restrict myeloproliferative disorder. Blood 123, 2968–2977 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Guo, H., Ma, O., Speck, N. A. & Friedman, A. D. Runx1 deletion or dominant inhibition reduces Cebpa transcription via conserved promoter and distal enhancer sites to favor monopoiesis over granulopoiesis. Blood 119, 4408–4418 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Hamey, F. K. et al. Reconstructing blood stem cell regulatory network models from single-cell molecular profiles. Proc. Natl Acad. Sci. USA 114, 5822–5829 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Behrens, K. et al. Runx1 downregulates stem cell and megakaryocytic transcription programs that support niche interactions. Blood 127, 3369–3381 (2016).

    Article  CAS  PubMed  Google Scholar 

  41. Volk, A. et al. A CHAF1B-dependent molecular switch in hematopoiesis and leukemia pathogenesis. Cancer Cell 34, 707–723 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Sigvardsson, M. Transcription factor dose links development to disease. Blood 120, 3630–3631 (2012).

    Article  CAS  PubMed  Google Scholar 

  43. Wilkinson, A. C., Nakauchi, H. & Gottgens, B. Mammalian transcription factor networks: recent advances in interrogating biological complexity. Cell Syst. 5, 319–331 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Heinz, S., Romanoski, C. E., Benner, C. & Glass, C. K. The selection and function of cell type-specific enhancers. Nat. Rev. Mol. Cell Biol. 16, 144–154 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Stadhouders, R., Filion, G. J. & Graf, T. Transcription factors and 3D genome conformation in cell-fate decisions. Nature 569, 345–354 (2019).

    Article  CAS  PubMed  Google Scholar 

  46. DeKoter, R. P. & Singh, H. Regulation of B lymphocyte and macrophage development by graded expression of PU.1. Science 288, 1439–1441 (2000).

    Article  CAS  PubMed  Google Scholar 

  47. Rosenbauer, F. et al. Acute myeloid leukemia induced by graded reduction of a lineage-specific transcription factor, PU.1. Nat. Genet. 36, 624–630 (2004).

    Article  CAS  PubMed  Google Scholar 

  48. Tamura, A. et al. C/EBPβ is required for survival of Ly6C monocytes. Blood 130, 1809–1818 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Friedman, A. D. C/EBPα in normal and malignant myelopoiesis. Int. J. Hematol. 101, 330–341 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Briscoe, J. & Small, S. Morphogen rules: design principles of gradient-mediated embryo patterning. Development 142, 3996–4009 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Naito, Y., Hino, K., Bono, H. & Ui-Tei, K. CRISPRdirect: software for designing CRISPR/Cas guide RNA with reduced off-target sites. Bioinformatics 31, 1120–1123 (2015).

    Article  CAS  PubMed  Google Scholar 

  52. Hashimoto, M. & Takemoto, T. Electroporation enables the efficient mRNA delivery into the mouse zygotes and facilitates CRISPR/Cas9-based genome editing. Sci. Rep. 5, 11315 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Sakai, K. et al. Usp26 mutation in mice leads to defective spermatogenesis depending on genetic background. Sci. Rep. 9, 13757 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  54. Tamura, T., Thotakura, P., Tanaka, T. S., Ko, M. S. & Ozato, K. Identification of target genes and a unique cis element regulated by IRF-8 in developing macrophages. Blood 106, 1938–1947 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Naldini, L., Blomer, U., Gage, F. H., Trono, D. & Verma, I. M. Efficient transfer, integration, and sustained long-term expression of the transgene in adult rat brains injected with a lentiviral vector. Proc. Natl Acad. Sci. USA 93, 11382–11388 (1996).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Ban, T. et al. Lyn kinase suppresses the transcriptional activity of IRF5 in the TLR-MyD88 pathway to restrain the development of autoimmunity. Immunity 45, 319–332 (2016).

    Article  CAS  PubMed  Google Scholar 

  57. Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).

    Article  CAS  PubMed  Google Scholar 

  58. Li, B., Ruotti, V., Stewart, R. M., Thomson, J. A. & Dewey, C. N. RNA-Seq gene expression estimation with read mapping uncertainty. Bioinformatics 26, 493–500 (2010).

    Article  PubMed  Google Scholar 

  59. Corces, M. R. et al. Lineage-specific and single-cell chromatin accessibility charts human hematopoiesis and leukemia evolution. Nat. Genet. 48, 1193–1203 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Langmead, B., Trapnell, C., Pop, M. & Salzberg, S. L. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10, R25 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  61. Saldanha, A. J. Java Treeview–extensible visualization of microarray data. Bioinformatics 20, 3246–3248 (2004).

    Article  CAS  PubMed  Google Scholar 

  62. Whyte, W. A. et al. Master transcription factors and mediator establish super-enhancers at key cell identity genes. Cell 153, 307–319 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The authors thank M. Ichino, I. Harada, M. Yoshinari, S. Honma, H. Sato, G. R. Sato and M. Tachikawa at Yokohama City University for their help with the experiments. This work was supported by Grants-in-Aid for Scientific Research from the Japan Society for the Promotion of Science/Ministry of Education, Culture, Sports, Science and Technology (MEXT; grant nos. 18K19345 and 15H04860 to T.T. and 19K07372 to A.N.); a Uehara Memorial Foundation Research Grant (to T.T.); a Japanese Society of Hematology Research Grant (to T.T.); and the MEXT Joint Usage/Research Center Program at the Advanced Medical Research Center, Yokohama City University (funding for Y.S., T.K. and T.T.).

Author information

Authors and Affiliations

Authors

Contributions

K.M., H.S., A.N. and T.T. designed the study. K.M., H.S., A.N., D.K., W.K., T.B., S.K. and Y.S. conducted the experiments; K.M., H.S., A.N., J.N. and T.T. analyzed the data; K.M., A.N. and T.T. wrote the manuscript; K.O. provided key resources; H.N., K.O. and T.K. provided intellectual input; and T.T. supervised the project. K.M., H.S. and A.N. contributed equally to this work.

Corresponding authors

Correspondence to Akira Nishiyama or Tomohiko Tamura.

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The authors declare no competing interests.

Additional information

Peer review information Nature Immunology thanks Venetia Bigley, Charlotte Scott, Alberto Yáñez and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available. 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 Models of myeloid cell differentiation in WT and Irf8−/− mice.

Irf8 starts to be expressed at the MPP stage and its expression sharply increases in MDPs. The expression of Irf8 further increases as cells differentiate into the DC lineage, while remaining relatively low or downregulated in the monocytic lineage. Neutrophils do not express Irf8. Irf8–/– mice lack Ly6C+ monocytes, CDPs, pDCs, and cDC1s. Irf8–/– mononuclear phagocyte progenitors accumulate and aberrantly give rise to neutrophils. MPPs include both MPP3s and MPP4s/LMPPs that express low amounts of Irf8. The dashed lines denote disputed pathways. Cell populations affected by the enhancer or gene deletion are highlighted in green.

Extended Data Fig. 2 Flow cytometric analysis of bone marrow and spleen cells.

a-h, Representative FACS plots of HSPCs (a), myeloid progenitors (b), CLPs (c), mononuclear phagocyte progenitors (d), and cMoPs (e) in bone marrow and those of monocytes and neutrophils (f), cDCs (g), and pDCs (h) in spleens.

Extended Data Fig. 3 Creation of Irf8 enhancer-null mice by CRISPR/Cas9 genome editing.

a, The Genome Browser image of the regions deleted in each enhancer-null mouse strain. b, Representative cropped gel images of genomic PCR confirming the deletion. Primer sets are indicated. Data are representative of over 20 independent experiments for each genotype, which yielded similar results. Full scans are shown in Source Data. c, The Genome Browser image of input DNA data at the Irf8 gene locus on ∆+56 cMoP in ChIP-seq analysis. Gray boxes indicate known enhancers at –50, +41, and +32 kb.

Source data

Extended Data Fig. 4 The Irf8 +56 kb region regulates Irf8 expression and cell fate.

a, Representative FACS plots of pre-cDC1s, pre-cDC2s, pre-DCs, and Ly6C monocytes analyzed in Fig. 2a. b, IFN-α and IFN-β production by pDCs isolated from WT or ∆+56 mice followed by overnight stimulation with poly(U) (1.0 µg/mL) or CpG-A (10 µM) (n = 3 mice per genotype). Data are representative of two independent experiments, which yielded similar results. c, In vitro culture of MDPs. Ten thousand MDPs from WT, ∆+56, and Irf8–/– were cultured with Flt3L for 5 days. Representative FACS plots of DC subsets (upper panels) and their absolute cell numbers (lower panels) produced in the culture are shown (total n = 4 cell cultures). The data were pooled from two independent experiments. d,e, Bone marrow chimera experiments. WT or ∆+56 HSPCs (c-Kit+, 3.0 × 105 cells) were transplanted into irradiated mice (CD45.1+) together with 2.0 × 105 competitor WT whole bone marrow cells (CD45.1+). Cells were analyzed 2 months after transplantation by FACS and RT-qPCR. In (d), absolute numbers of progenitor populations in bone marrow and differentiated cells in spleens derived from WT or ∆+56 donor cells are shown. The data were pooled from two independent experiments (total n = 6 mice per genotype). In (e), Irf8 mRNA expression in donor-derived bone marrow progenitor populations (total n = 3 mice per genotype). The data were pooled from two independent experiments. Data in b, c (lower panels), d and e are shown as mean + SD. * P < 0.05, ** P < 0.01, *** P < 0.001 (two-tailed Student’s t test) with a fold-change greater than 1.5 or less than 0.66. The exact P values are provided in Source Data. N.D., not detected in (b) and not determined in (e).

Source data

Extended Data Fig. 5 Phenotypes of the mice devoid of either the –50 kb or +32 kb Irf8 enhancer.

a-d, ∆–50 (a,b) and ∆+32 mouse (c,d) strains were analyzed by FACS and RT-qPCR. Absolute cell numbers of progenitor populations in bone marrow and differentiated cells in spleens are shown in (a) and (c). The data were pooled from two independent experiments (total n = 3 mice per genotype for pre-cDC1s, pre-cDC2s, and pre-DCs; total n = 4 mice per genotype for CD43+ Ly6C monocytes, CD43 Ly6C cells, and the other cell types of ∆–50 and ∆+32 mice; and total n = 6 mice for the other cell types of WT and Irf8–/– mice). Irf8 mRNA expression in the indicated cell populations are shown in (b) and (d). The data were pooled from two independent experiments (total n = 3 mice per genotype except for B cells of ∆–50 mice; n = 2 mice for B cells of ∆–50 mice). All data in Extended Data Figure 5 are shown as mean + SD. * P < 0.05, ** P < 0.01, *** P < 0.001 (two-tailed Student’s t test) with a fold-change greater than 1.5 or less than 0.66. The exact P values are provided in Source Data. N.D., not determined.

Source data

Extended Data Fig. 6 Expression of GFP, exogenous IRF8, and endogenous IRF8.

a, Representative FACS plots of immunostaining for IRF8 in Irf8–/– c-Kit+ cells transduced with a bicistronic retrovirus expressing IRF8 and GFP for two days. Cells in the lower and upper quarters were sorted into GFPlow and GFPhi populations (left panels). IRF8 expression concentrations in these populations are shown (right panel, n = 3 cell cultures). Data are representative of two independent experiments, which yielded similar results. b, IRF8 expression in bone marrow progenitor cells and splenic differentiated cells from WT and ∆+56 mice (n = 3 mice per genotype). Data are representative of two independent experiments, which yielded similar results. ΔMFI was calculated by subtracting the background MFI with isotype control IgG1. Data in a (right panel) and b are presented as mean + SD; * P < 0.05, ** P < 0.01, *** P < 0.001 (two-tailed Student’s t test). The exact P values are provided in Source Data. N.D., not determined.

Source data

Extended Data Fig. 7 Dynamics of MDP enhancers in WT, ∆+56, and Irf8−/− mice.

a, Box plots of the normalized H3K27ac ChIP-seq tag densities within the clusters 2, 3, 4, and 5 identified in Fig. 4a in the indicated cell types from WT, ∆+56, and Irf8–/– mice (horizontal lines within the box, median; the lower and upper ends of the box, 25th [Q1] and 75th [Q3] percentiles; the minimum limit of whiskers, minimum value or Q1 − 1.5× interquartile range [IQR]; the maximum limit of whiskers, maximum value or Q3 + 1.5× IQR). The P values were calculated by the paired two-tailed t test. The exact P values are provided in Source Data. b, A heat map illustrating normalized enrichment scores (NES) of GSEA for the genes nearest to the regions in the clusters 2, 3, 4, and 5. Each box shows a GSEA NES that compares the hematopoietic population on its left side with that on its upper side. mRNA expression data were obtained by RNA-seq. A positive NES means a greater value in the left-hand population. NaN, not-a-number. c, mRNA expression of the representative genes from the clusters 2, 3, 4, and 5 identified in Fig. 4a. The indicated cell types from WT, ∆+56, and Irf8–/– mice were analyzed by RNA-seq (n = 2 biologically independent samples per population). d, Expression of Klf4 mRNA analyzed by RNA-seq in the indicated cell types from WT, ∆+56, and Irf8–/– mice (n = 2 biologically independent samples per population). N.D., not determined. Data in c and d are presented as mean.

Source data

Extended Data Fig. 8 Expression of genes encoding TFs co-operating with IRF8.

mRNA expression amounts of the indicated genes in WT Ly6C+ monocytes and cDC1s determined by RNA-seq (n = 2 biologically independent samples per population). Data are shown as mean.

Source data

Extended Data Fig. 9 RUNX–CBFβ regulates the development of cDCs.

a, Genome Browse images of RUNX1 and RUNX2 ChIP-seq tags in HSPC cell lines around the Irf8 gene and enhancers, retrieved from previous reports39,40,41. ATAC-seq data on WT MDPs newly obtained in this study (n = 2 biologically independent samples, each using 1 mouse) and H3K27ac ChIP-seq data on WT MDPs retrieved from our previous publication21 (n = 2 biologically independent samples, each using 20 mice) are shown for reference. b,c, WT LSK cells were transduced with a lentivirus encoding shRNA against Cbfb and cultured with SCF and Flt3L as in Fig. 7. Representative FACS plots on day 7 are shown in (b). The percentages of MDPs and CDPs (day 5, n = 3 cell cultures), cDCs, pDCs, and monocytes/macrophages (day 7, n = 4 cell cultures) among GFP+ cells are shown in (c). Data are representative of two independent experiments, which yielded similar results. The bar graphs are shown as mean + SD. * P < 0.05, ** P < 0.01, *** P < 0.001 (two-tailed Student’s t test). The exact P values are provided in Source Data. d, Representative histograms of reporter assays in MDPs shown in Fig. 7f. e, mRNA expression of Runx1, Runx2, Runx3, and Cbfb analyzed by RNA-seq in the indicated cell types from WT mice (n = 2 biologically independent samples). Data are shown as mean. f, Normalized microarray intensities of Runx1, Runx2, Runx3, Cbfb, and Irf8 in IRF8 and IRF8+ LMPPs (n = 2 biologically independent samples). Data are shown as mean. g, A Genome Browser image of sequence conservation at the human IRF8 gene locus against the mouse genome. The region corresponding to mouse +56 kb Irf8 enhancer (dotted line) and the region used for the +56 kb enhancer reporter assay (orange) are indicated. Positions of the two RUNX motifs are shown as blue arrow lines. Mac, macrophage; NC, negative control.

Source data

Extended Data Fig. 10 The proposed model of the IRF8-dose dependent myeloid lineage choice.

a, Schematic models of the phenotypes of three mouse strains devoid of the +56, +32 or –50 kb Irf8 enhancer. The models are described as in Extended Data Fig. 1. Phenotypes of WT and Irf8–/– mice are also displayed for comparison. b, Proposed model: The RUNX–CBFβ-driven Irf8 + 56 kb enhancer induces early IRF8 expression in myeloid progenitors. The +56 kb enhancer-mediated high IRF8 expression in myeloid progenitor cells is essential for the development of CDPs and cDC1s, whereas low IRF8 expression in myeloid progenitor cells preferentially induces monopoiesis. The absence of IRF8 expression leads to differentiation into neutrophils (Neu). The lineage choice is epigenetically determined in an IRF8 dose-dependent manner via cooperation or antagonism with other TFs to activate distinct sets of downstream enhancers. TFs, transcription factors.

Supplementary information

Reporting Summary

Peer Review Information

Supplementary Table 1

Oligonucleotides used in this study.

Supplementary Table 2

Datasets used in this study.

Source data

Source Data Fig. 1

Statistical source data with exact P values.

Source Data Fig. 2

Statistical source data with exact P values.

Source Data Fig. 3

Statistical source data with exact P values.

Source Data Fig. 4

Statistical source data with exact P values.

Source Data Fig. 5

Statistical source data with exact P values.

Source Data Fig. 7

Statistical source data with exact P values.

Source Data Extended Data Fig. 3

Full scans of gel images for genomic PCR.

Source Data Extended Data Fig. 4

Statistical source data with exact P values.

Source Data Extended Data Fig. 5

Statistical source data with exact P values.

Source Data Extended Data Fig. 6

Statistical source data with exact P values.

Source Data Extended Data Fig. 7

Statistical source data with exact P values.

Source Data Extended Data Fig. 8

Statistical source data with exact P values.

Source Data Extended Data Fig. 9

Statistical source data with exact P values.

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Murakami, K., Sasaki, H., Nishiyama, A. et al. A RUNX–CBFβ-driven enhancer directs the Irf8 dose-dependent lineage choice between DCs and monocytes. Nat Immunol 22, 301–311 (2021). https://doi.org/10.1038/s41590-021-00871-y

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