Abstract

The histone H3 Lys27-specific demethylase UTX (or KDM6A) is targeted by loss-of-function mutations in multiple cancers. Here, we demonstrate that UTX suppresses myeloid leukemogenesis through noncatalytic functions, a property shared with its catalytically inactive Y-chromosome paralog, UTY (or KDM6C). In keeping with this, we demonstrate concomitant loss/mutation of KDM6A (UTX) and UTY in multiple human cancers. Mechanistically, global genomic profiling showed only minor changes in H3K27me3 but significant and bidirectional alterations in H3K27ac and chromatin accessibility; a predominant loss of H3K4me1 modifications; alterations in ETS and GATA-factor binding; and altered gene expression after Utx loss. By integrating proteomic and genomic analyses, we link these changes to UTX regulation of ATP-dependent chromatin remodeling, coordination of the COMPASS complex and enhanced pioneering activity of ETS factors during evolution to AML. Collectively, our findings identify a dual role for UTX in suppressing acute myeloid leukemia via repression of oncogenic ETS and upregulation of tumor-suppressive GATA programs.

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Acknowledgements

This study was primarily funded by a joint Bloodwise Program Grant (17006) to B.J.P.H. and G.S.V. Work in the laboratory of B.J.P.H. is also funded by an ERC consolidator award (grant 647685 COMAL), a Cancer Research UK program award, the Medical Research Council, (MRC) the Wellcome Trust (WT) and the Cambridge NIHR BRC. We acknowledge the WT/MRC Center grant (097922/Z/11/Z) and support from WT strategic award 100140. G.S.V. is funded by a Cancer Research UK Senior Cancer Research Fellowship (C22324/A23015). The laboratory of G.S.V. is also supported by the Kay Kendall Leukemia Fund and core funding from the Sanger Institute (WT098051).

Author information

Author notes

  1. These authors jointly supervised this work: George S. Vassiliou, Brian J. P. Huntly.

Affiliations

  1. Haematological Cancer Genetics, Wellcome Trust Sanger Institute, Hinxton, UK

    • Malgorzata Gozdecka
    • , Milena Mazan
    • , Konstantinos Tzelepis
    • , Monika Dudek
    • , Grace Collord
    • , Oliver Dovey
    • , Dimitrios A. Garyfallos
    • , Etienne De Braekeleer
    • , Jonathan Cooper
    •  & George S. Vassiliou
  2. Wellcome Trust–MRC Stem Cell Institute, Cambridge Biomedical Campus, University of Cambridge, Cambridge, UK

    • Malgorzata Gozdecka
    • , Eshwar Meduri
    • , Milena Mazan
    • , Haiyang Yun
    • , George S. Vassiliou
    •  & Brian J. P. Huntly
  3. Genomics of Gene Regulation, Wellcome Trust Sanger Institute, Hinxton, UK

    • Andrew J. Knights
  4. Proteomic Mass Spectrometry, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK

    • Mercedes Pardo
    • , Lu Yu
    •  & Jyoti S. Choudhary
  5. Mouse Genomics, Wellcome Trust Sanger Institute, Hinxton, UK

    • Emmanouil Metzakopian
  6. Experimental Cancer Genetics, Wellcome Trust Sanger Institute, Hinxton, UK

    • Vivek Iyer
    •  & David Adams
  7. Sequencing Research Group, Wellcome Trust Sanger Institute, Cambridge, UK

    • Naomi Park
  8. Instituto de Biomedicina y Biotecnología de Cantabria (CSIC-UC-Sodercan), Departamento de Biología Molecular, Universidad de Cantabria, Santander, Spain

    • Ignacio Varela
  9. New Pipeline Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK

    • Ruben Bautista
  10. Laboratory of Molecular Genetics, Institute of Medical Science, University of Tokyo, Tokyo, Japan

    • Saki Kondo
  11. Cambridge Institute for Medical Research and Wellcome Trust–Medical Research Council, Stem Cell Institute and Department of Haematology, University of Cambridge, Cambridge, UK

    • Berthold Göttgens
    •  & Brian J. P. Huntly
  12. Department of Internal Medicine III, Ulm University Medical Centre, Ulm, Germany

    • Lars Bullinger
  13. Medical Department, Division of Hematology, Oncology and Tumour Immunology, Charité Universitätsmedizin Berlin, Berlin, Germany

    • Lars Bullinger
  14. Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany

    • Paul A. Northcott
  15. Developmental Neurobiology, St Jude Children’s Research Hospital, Memphis, TN, USA

    • Paul A. Northcott
  16. Department of Haematology, Cambridge University Hospitals NHS Trust, Cambridge, UK

    • George S. Vassiliou
    •  & Brian J. P. Huntly

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Contributions

M.G., G.S.V. and B.J.P.H. conceived the study, designed the experiments and prepared the manuscript. M.G. conducted most of the experiments. E. Meduri performed ChIP–seq, ATAC–seq and motif analysis. A.J.K. performed ATAC–seq experiments. M.P. and M.G. prepared samples for mass spectrometry; M.P., L.Y. and J.S.C. conducted mass spectrometry and related data analysis. E. Metzakopian designed and generated pKLV-puro vectors. V.I. and D.A. performed exome analysis. H.Y. performed promoter–enhancer interaction analysis. N.P. and I.V. performed experimental and computational analysis. G.C., M.M., M.D., O.D., K.T., D.A.G., E.D.B. and J.C. performed cell culture and mouse experiments. R.B. performed analysis of RNA-seq data. P.A.N., B.G. and L.B. provided genomic data and expertise. S.K. helped with vector generation. All authors reviewed and agreed with the final submission.

Competing interests

The authors declare no competing interests.

Corresponding authors

Correspondence to George S. Vassiliou or Brian J. P. Huntly.

Integrated supplementary information

  1. Supplementary Figure 1 Additional blood count results from sick Utx−/− vs Utx+/+ mice. Exome sequencing.

    (a) WBC (b) PLT and (c) HGB counts of diseased Utx+/+, Utx+/− and Utx−/− mice; the mean ± s.e.m is shown; n = number of mice per genotype. P value was determined by one-way ANOVA with Bonferroni correction; for PLT: t = 2.733, df=56; for HGB: t = 2.43; df = 56. (d) Mutated genes and (e) copy-number changes (from exome sequencing) in 7 individual Utx−/− AMLs. (f) Deletion of Utx exon3 in comparison to exon4 was detected in all Utx−/− AMLs. The mean ± s.e.m is shown; n = number of mice; P by two-sided t-test (t = 13, df = 12). (g) c-KIT+ BM cells were isolated form Utx+/+ and Utx−/−mice (n = 3 mice per genotype) and transduced with lentivral vectors expressing AML-ETO9a. Cells were transplanted into lethally irradiated syngeneic recipient mice and mouse survival was monitored. (h) Kaplan-Meier survival curves of mice transplanted with Utx−/−; AML-ETO9a and control Utx+/+; AML-ETO9a cells; n = number of mice; P by Log-rank (Mantel-Cox) test, df = 1. (i) Spleen sizes of mice in h, the mean ± s.e.m is shown; n = number of mice; P by two-sided t-test (t = 2.798, df = 15).

  2. Supplementary Figure 2 Gating strategy for progenitor analysis by FACS.

    (a) Gating strategy and fluorophores used for separation of LT-HSC, ST-HSC, LSK, MPP, LMPP as well as (b) GMP, CMP, MEP and (c) CLP populations in Utx+/+ and Utx−/−mice.

  3. Supplementary Figure 3 Mature blood cell numbers in Utx−/−, Utx+/− and Utx−/Y mice.

    (a) Cell numbers from pre-leukemic Utx+/+, Utx+/−, and Utx−/− in a serial re-plating assay (for Utx+/+ vs Utx−/− in plating: 1, t = 7.018; df = 25; plating 2, t = 8.668, df = 25; plating 4 t = 3.342, df = 19). Mature cell frequencies in pre-leukemic (b) BM and (c) spleen as well as (c) PLT counts in Utx+/+, Utx+/−,and Utx−/− mice (t = 2.977, df = 27). (e) Relative mature cell frequencies in blood of 36-week old mice; P calculated vs Utx+/+ control; only significant P values are shown. For Utx+/+ vs Utx−/− comparison, MAC1 (t = 6.718, df = 15), B220 (4.442, df = 15); for Utx+/+ vs Utx+/− comparison, MAC1 (t = 2.571; df = 15) (f) WBC (t = 3.879, df = 15) and (g) PLT counts (t = 6.487, df = 15) from aged (36-week-old) Utx+/+, Utx+/− and Utx−/−. (h) Spleen (i) liver weights, (j) WBC, (k) PLT and (l) HGB in aged (for 22 months) Utx+/Y, and Utx−/Y. The mean ± s.e.m is shown; n = number of mice per genotype. In a, d, e, f, and g, P value was determined by one-way ANOVA with Bonferroni correction. In b, c, h-i P was determined by two-sided t-test as ns.

  4. Supplementary Figure 4 Extended hemopoietic phenotyping of pre-leukemic Utx+/Y and Utx−/Y mice.

    (a) Spleen weights of pre-leukemic Utx+/Y, and Utx−/Y. (b) HSPC/Lin- and (c) LT-HSC/ST-HSC frequency in BM cells from Utx+/Y, and Utx−/Y. (d) LK, CMP, GMP, MEP and (e) CLP frequency in BM from pre-leukemic Utx+/Y, and Utx−/Y. (f) BM colonies from Utx+/Y, and Utx−/Y in a serial re-plating assay. (g) Mature cell frequencies in pre-leukemic BM and (h) spleen as well as (i) PLT counts in Utx+/Y, and Utx−/Y mice. In a-i the mean ± s.e.m is shown; n = number of mice per genotype, P by two-sided t-test. For CLP, t = 4.206, df = 10; for MEP, t = 5.028, df = 8. Only significant P values are shown.

  5. Supplementary Figure 5 Interaction of promoter and putative enhancer regions in Utx−/− mice.

    (a) Proportion of differential H3K27ac peaks at non-promoter regions overlapped with promoter-interacting regions (PIRs). Based on promoter capture Hi-C data in HPC-7 cell line, a total number of 54,339 PIRs were defined as HindIII digested fragments that form significant interactions (CHiCAGO score ≥5) with promoter baits. (b) Regions marked by increased H3K27ac in Utx−/− vs Utx+/+ HSPCs interact with the Pax5 promoter in HPC-7 cells. (c) Regions marked by decreased H3K27ac in Utx−/− vs Utx+/+ HSPCs interact with the Map4k5 promoter in HPC-7 cells.(d) Immunoblots showing global levels of H3K27me3, H3K27ac and UTX protein in the Utx−/− and Utx+/+ pre-leukemic mouse BM cells. Histone 3 (H3) was used as protein loading control. Results of one representative experiment are shown (n = 3 experiments). Uncropped images are shown in Supplementary Fig. 12 (e) Overlap of peaks and (f) peak-associated genes between UTX-bound sites (6734 loci) and all differential H3K27ac modifications (2916 loci). Differential H3K27ac peaks (FDR<1%, -1.5>FC>1.5) were defined by DiffBind tool; n = 2 mice per genotype. (g) Genomic snapshot of UTX and PU.1 demonstrates enhanced PU.1 binding in the promoter region of Ets1, Ets2 and Fli1 in the absence of Utx. UTX also binds to the promoter of these genes in Utx+/+ mice. In e, P by Fisher's exact test for peak comparisons; in f, P by hypergeometric test for gene comparisons.

  6. Supplementary Figure 6 Overlap of UTX and PU.1 binding with differential H3K27ac and H3K4me1.

    (a) Overlap of peaks between PU.1-enriched sites and increased H3K27ac or (b) gained H3K4me1 sites. (c) Overlap of peaks and (d) peak-associated genes between UTX-bound regions (2916 genes) and regions with loss of H3K27ac sites (2054 genes) in the Utx−/−. (e) Genomic snapshot of UTX, H3K27ac, H3K27me3 ChIP-seq in Utx+/+ and Utx−/− Lin at the Cul4a locus showing no direct co-localisation of UTX binding with changes in H3K27ac. Instead UTX binds in proximity to these changes. (f) Co-IP showing association between UTX and both SMARCA4 and CHD4. Uncropped images are shown in Supplementary Fig. S12 P by Fisher's exact test for peak comparisons; P by hypergeometric test for gene comparisons. Differential peaks were defined by DiffBind tool; n = 2 mice per genotype for H3K27ac, H3K4me1 and UTX; n = 3 mice per genotype for PU.1 ChIP-seq.

  7. Supplementary Figure 7 Correlation of closed chromatin regions with UTX binding and altered H3K27ac.

    (a) Intersection of peaks between differentially closed chromatin and loss of H3K27ac followed by motif analysis of overlapping sites; number indicates motif rank. (b) Comparison of downregulated genes to closed chromatin regions in Utx−/− followed by motif analysis of the overlap; number indicates motif rank. Motif analysis in lower panels of a and b - by HOMER software. (c) Intersection of peaks between UTX-bound and open chromatin sites. (d) Intersection of closed chromatin sites and loss of H3K4me1. (e) Immunoblot showing UTX protein level in 416B-Cas9 cells edited with Utx gRNA or empty gRNA control. Actin was used as loading control (repeated in n = 3 experiments). Uncropped images are shown in Supplementary Fig.12 (f) ChIP for SMARCA4, CHD4, UTX followed by qPCR for Aff1 and (g) Lrrc8c loci shown as fold enrichment over control loci (GD_chr5, gene desert on chromosome 5) in 416B-Cas9 cells with edited Utx vs Empty-gRNA control. Genomic snapshots show chromatin co-occupacy of UTX, SMARCA4 and CHD4 at studied regions. The mean ± s.e.m is shown; n = 3-5 independent cell cultures; P by two-sided t-test. In f (Utx_ex3 gRNA vs Empty-gRNA) for SMARCA4 t = 2.371; df = 9; for CHD4 t = 2.793, df = 7; for UTX t = 2.671, df = 5. In g (Utx_ex3 gRNA vs Empty-gRNA) for SMARCA4 t = 4.723; df = 8; for CHD4 t = 2.818, df = 7; for UTX t = 6.009, df = 6. In a, c, and d, P by Fisher's exact test; in b, P by hypergeometric test. Differential peaks were defined by DiffBind tool; n = 2 mice per genotype for H3K27ac and UTX; n = 3 mice per genotype for ATAC-seq.

  8. Supplementary Figure 8 Functional redundancy between UTX and SMARCA4 loss for chromatin accessibility on GATA sites.

    (a) Schematic representation of experimental strategy: Cas9 expressing Utx−/− and Utx+/+ HSPCs were transduced with lentiviral vector expressing gRNA for Smarca4 and Chd4 and empty gRNA as a control. Six days post transduction we analysed chromatin accessibility by ATAC-seq. (b) Differential peaks between empty gRNA and Smarca4  gRNA in Utx+/+ cells (FDR<0.05; FC< −1.25) were compared with differential peaks lost upon Utx deletion (empty gRNA in Utx+/+ was compared to empty gRNA in Utx−/−; FDR<0.01; FC< −1.5) followed by motif analysis of the overlap. Differential peaks were defined by DiffBind tool; n = 2 mice per genotype, P for peak comparison by Fisher's exact test. Motif and statistical analysis in lower panel of b was determined by HOMER software. (c) Genomic snapshot of ATAC-seq at Kif5a locus. Note that Smarca4 editing but not Chd4 knockout phenocopy Utx loss at indicated in blue region.

  9. Supplementary Figure 9 Correlation of open chromatin sites with gain of H3K27ac, H3K4me1 and gene expression.

    (a) Intersection of peaks between differentially opened chromatin and gained H3K27ac and (b) gained H3K4me1 sites. (c) Comparison of upregulated genes to opened chromatin regions (2175 genes) in Utx−/− followed by motif analysis of the overlap, number indicates motif rank. P in a and b, by Fisher's exact test; P in c by hypergeometric test. Motif and statistical analysis was determined by HOMER software. Differential peaks were defined by DiffBind tool; n = 2 mice per genotype for H3K27ac and H3K4me1; n = 3 mice per genotype for ATAC-seq. (d) MONO-MAC6 proliferation upon editing of TCF3 and TCF12. BFP-positive fraction was compared with the non-transduced population and normalized to day 4 (d4) for each gRNA. The mean ± s.d. is shown; n = independent cell cultures; P by one-way ANOVA with Bonferroni correction; P shown for edited gene on day 19 vs control gRNA (EMPTY) d19; for TCF12, t = 18.81, df = 6; for TCF3, t = 14.22, df=6. d – day in culture.

  10. Supplementary Figure 10 UTX interaction network based on the mass spectrometry data.

    Previously reported interactions were obtained from STRING database, Uniprot annotations and literature searches. The graph was drawn with Cytoscape using the organic layout, which was modified manually to allow better visualization of the connections. Node size represents abundance of the protein. Grey edges represent novel interactions identified by UTX IP-MS, light blue edges represent interactions reported in the literature, and black edges represent previously reported interactions. Note that Esr1 and Banp were not identified in the UTX IP-MS experiment. The protein were included in the network to illustrate their interactions with the newly identified UTX-binding proteins.

  11. Supplementary Figure 11 Model.

    (a) In the presence of UTX or UTY, the oncogenic ETS transcriptional program is suppressed by tight regulation of ETS TF expression levels and through coordinated recruitment of chromatin remodelers such as SMARCA4 and the COMPASS complex to open chromatin and lay enhancer marks for important tumour suppressor TF such as GATA2. (b) However, when UTX/UTY are initially lost (in the pre-leukemic phase of disease) an increased expression and binding of ETS TFs occur across the genome, leading to novel enhancer generation with immediate effects upon gene expression at some loci (full arrow). For a larger number of regions ETS TFs bind to closed and compacted chromatin (dashed arrows). In addition, loss of UTX/UTY leads to a lack of coordinated binding and activity of SMARCA4 and the COMPASS complex closing off chromatin accessibility and leading to a loss of enhancer function at GATA binding sites, switching off the GATA program. In addition, the loss of H3K4me1 further leads to a failure to recruit and activate SMARCA4. (c) Subsequently and potentially related to the effects of cooperating mutations, the pioneering effects of ETS TFs lead to gene activation and this evolution of the leukemic transcriptional programs leads to the development of overt AML.

  12. Supplementary Figure 12

    Uncropped western blot images presented in the main and supplementary figures.

Supplementary information

  1. Supplementary Text and Figures

    Supplementary Figures 1–12

  2. Reporting Summary

  3. Supplementary Table 1

    UTX mutant cancer cell lines with affected UTY, from COSMIC database

  4. Supplementary Table 2

    Differentially expressed genes (adj. P-value<-0.5 and log2FC >0.5) between Utx-/- and Utx+/+ Lin- BM from preleukemic female mice, n = 2 mice per genotype; fold change and P was generated using DESeq2 as described in Methods section.

  5. Supplementary Table 3

    Differentially expressed genes (adj. P-value<0.05) between Utx-/Y and Utx+/Y Lin- BM from pre-leukemic male mice; n = 2 mice per genotype; fold change and P was generated using DESeq2.

  6. Supplementary Table 4

    Differentially expressed genes (adj. P-value<0.05, log2FC <-0.5 and log2FC >0.5) in Utx-/- with removed overlapping genes in Utx-/Y. RNA-Seq was performed in Lin- BM from pre-leukemic mice.

  7. Supplementary Table 5

    Differentially expressed genes (adj P-value<0.05, log2FC <-0.5 and log2FC >0.5) between Utx-/- AML (n = 3 mice) and Utx+/+ Lin- BM from pre-leukemic females (n = 2 mice). Fold change and P was generated using DESeq2.

  8. Supplementary Table 6

    UTX bound peaks in WT Lin- BM pre-leukemic female mice (n = 2 mice). Unspecific peaks found in IgG control ChIP (from n = 2 mice) were subtracted from UTX-bound peaks.

  9. Supplementary Table 7

    Downregulated (a) or upregulated (b) genes overlapping UTX bound peaks (adj P-value<0.05 and log2FC <-0.5 and log2FC >0.5) in Utx-/- Lin- BM.

  10. Supplementary Table 8

    Differentially bound peaks for H3K27me3 (FDR <0.01, FC <-1.5 and FC >1.5) between Utx-/- and Utx+/+ Lin- BM cells from pre-leukemic female mice (n = 2 mice per genotype).

  11. Supplementary Table 9

    Differentially bound, downregulated peaks for H3K27ac (FDR <0.01, FC <-1.5) between Utx-/- and Utx+/+ Lin- BM cells from pre-leukemic female mice (n = 2 mice per genotype).

  12. Supplementary Table 10

    Differentially bound, upregulated peaks for H3K27ac (FDR <0.01, FC > 1.5) between Utx-/- and Utx+/+ Lin- BM cells from pre-leukemic female mice (n = 2 mice per genotype).

  13. Supplementary Table 11

    Overlapping gene loci associated with UTX bound peaks and all differentially bound H3K27ac peaks (FDR<0.01, FC <-1.5 and FC >1.5) in Utx-/- Lin- BM (n = 2 mice per genotype).

  14. Supplementary Table 12

    Differentially bound peaks for H3K4me1 (FDR <0.01, FC <-1.5 and FC >1.5) between Utx-/- and Utx+/+ Lin- BM cells from pre-leukemic female mice (n = 2 mice per genotype).

  15. Supplementary Table 13

    Differentially bound peaks for PU.1 ChIP-seq (FDR <0.01, FC <-1.5 and FC >1.5) between Utx-/- and Utx+/+ Lin- BM cells from pre-leukemic female mice (n = 3 mice per genotype).

  16. Supplementary Table 14

    Overlapping gene loci associated with UTX bound peaks and differentially downregulated H3K27ac peaks (FDR<0.01, FC <-1.5) in Utx-/- Lin- BM (n = 2 mice per genotype).

  17. Supplementary Table 15

    Mass spectrometry results of UTX interactors in 416b cells.

  18. Supplementary Table 16

    Mass spectrometry results of UTX interactors in 416b cells.

  19. Supplementary Table 17

    ATAC-seq. Differentially closed peaks in Utx-/- Lin- BM (FDR<0.01, FC <-1.5) in comparison to Utx+/+ Lin- BM, n = 3 mice per genotype.

  20. Supplementary Table 18

    ATAC-seq. Differentially open sites in Utx-/- Lin- BM (FDR<0.01, FC <-1.5) compared to Utx+/+ Lin- BM (n = 3 mice per genotype).

  21. Supplementary Table 19

    Overlapping downregulated gens with closed chromatin sites (ATAC-seq) in Utx-/- Lin- BM (FDR<0.01, FC <-1.5).

  22. Supplementary Table 20

    ATAC-seq in vitro. Differentially closed and open sites in Cas9, Utx+/+ Lin- BM (FDR<0.05, FC ≤ -1.25 and ≥ 1.25) upon knockout of SMARCA4 (Smarca4 gRNA) in comparison to control (Empty gRNA). Cells isolated from n = 2 mice per genotype.

  23. Supplementary Table 21

    ATAC-seq in vitro. Differentially closed and open sites in Cas9, Utx-/- Lin- BM (FDR<0.01, FC ≤ -1.5 and ≥ 1.5) expressing Empty gRNA in comparison to Cas9, Utx+/+ Lin- BM expressing Empty gRNA control. Cells isolated from n = 2 mice per genotype.

  24. Supplementary Table 22

    ATAC-seq in vitro. Differentially closed and open sites in Cas9, Utx-/- Lin- BM (FDR<0.05, FC ≤ -1.2 and ≥1.25) upon knockout of SMARCA4 (Smarca4 gRNA) in comparison to control (Empty gRNA).

  25. Supplementary Table 23

    ATAC-seq in vitro. Differentially closed and open sites in Cas9, Utx+/+ Lin- BM (FDR<0.01, FC ≤ -1.5 and ≥1.5) upon knockout of Chd4 (Chd4 gRNA) in comparison to control (Empty gRNA). Cells isolated from n = 2 mice per genotype.

  26. Supplementary Table 24

    Overlapping upregulated gens with open chromatin sites (ATAC-seq) in Utx-/- Lin- BM (FDR<0.01, FC >1.5).

  27. Supplementary Table 25

    Differentially expressed genes (adj P-value<0.05, log2FC <-0.5 and log2FC >0.5) between Utx-/- Lin- BM from pre-leukemic females (n = 2 mice) and Utx-/- AML (n = 3 mice).

  28. Supplementary Table 26

    Genes overexpressed in Utx-/- AML (but not in pre-leukaemic setting) and bound by PU.1 in closed in pre-leukaemic Utx-/- Lin- BM; (FDR<0.01, FC >1.5). duplicated names were removed.

  29. Supplementary Table 27

    Primer sequences used for qRT-PCR and ChIP-qPCR

  30. Supplementary Table 28

    Primer sequences used for Gibson cloning

  31. Supplementary Table 29

    gRNA sequences

  32. Supplementary Table 30

    Motif analysis presented in the study, output tables were obtained with Homer software. Statistical analysis was determined by HOMER software; n = 2 mice per genotype for RNA-seq, ChIP-seq and ATAC-seq in vitro; n = 3 mice per genotype for ATAC-seq in Lin-ve BM.

  33. Supplementary Table 31

    RNA-seq raw and process file description.