The histone H3.3 chaperone HIRA restrains erythroid-biased differentiation of adult hematopoietic stem cells

Abstract

Histone variants contribute to the complexity of the chromatin landscape and play an integral role in defining DNA domains and regulating gene expression. The histone H3 variant H3.3 is incorporated into genic elements independent of DNA replication by its chaperone HIRA. Here we demonstrate that Hira is required for the self-renewal of adult hematopoietic stem cells (HSCs) and to restrain erythroid differentiation. Deletion of Hira led to rapid depletion of HSCs while differentiated hematopoietic cells remained largely unaffected. Depletion of HSCs after Hira deletion was accompanied by increased expression of bivalent and erythroid genes, which was exacerbated upon cell division and paralleled increased erythroid differentiation. Assessing H3.3 occupancy identified a subset of polycomb-repressed chromatin in HSCs that depends on HIRA to maintain the inaccessible, H3.3-occupied state for gene repression. HIRA-dependent H3.3 incorporation thus defines distinct repressive chromatin that represses erythroid differentiation of HSCs.

Keywords: Hira; differentiation; epigenetics; erythropoiesis; hematopoiesis; hematopoietic stem cell; histone H3.3; polycomb.

Graphical abstract

Figure 1

Hira is essential for adult but not fetal HSC maintenance (A) Quantification of the three major histone H3 variants in WBM or LK cells from wild-type (WT) mice as assessed by HPLC (n = 3 mice). (B) A diagram showing two mouse models of Hira conditional knockout in the hematopoietic system with Vav1-iCre and Mx1-Cre. (C) Immunoblotting assay shows that Hira deletion reduced HIRA protein levels in the bone marrow (BM) cells after deleting Hira. (D) Cellularity of fetal liver, BM, and spleen from Vav1-iCre; Hira^fl/fl and Hira^fl/fl mice at different developmental time points (n = 3–8 mice). (E) Frequency of CD3⁺ T cells, B220⁺ B cells, Mac1⁺Gr-1⁺ myeloid cells, and Ter119⁺ erythroid cells in Vav1-iCre; Hira^fl/fl and Hira^fl/fl mice in the BM and spleen at the indicated ages (n = 4–7 mice). (F) Survival curve for Vav1-iCre; Hira^fl/fl and Hira^fl/fl mice (n = 14). (G) Complete blood count of peripheral blood in Vav1-iCre; Hira^fl/fl and Hira^fl/fl mice at the indicated ages (RBC, red blood cell; WBC, white blood cell) (n = 3–7 mice). (H) The total numbers of LSKs, MPPs, and HSCs in the liver or BM of Vav1-iCre; Hira^fl/fl and Hira^fl/fl mice at the indicated ages (n = 3–8 mice). (I) Frequency of MEPs, common myeloid progenitors (CMP), and granulocyte-macrophage progenitors (GMP) in the BM of Vav1-iCre; Hira^fl/fl and Hira^fl/fl mice at different developmental time points (n = 4–7 mice). (J) Diagram of the poly(I:C) treatment schedule. We treated mice with two doses of poly(I:C) and analyzed the mice 17 days after the first injection. (K) Frequency of HSC, MPP, HPC1, HPC2, and LSK cells in Mx1-Cre; Hira^fl/fl and Hira^fl/fl mice 17 days after treatment with poly(I:C) (n = 6–9 mice). All data represent the mean ± standard deviation; ^∗p < 0.05, ^∗∗p < 0.01, and ^∗∗∗p < 0.001 by Student's t test, except for the comparison of the survival curves, in which the significance was accessed by a log-rank test. See also Figure S1.

Figure 2

HIRA prevents precocious differentiation of HSCs (A) Colony-forming assays with singly sorted HSCs/MPPs from either Hira^fl/fl (WT) or Mx1-Cre; Hira^fl/fl (KO) mice and scored for colonies containing granulocytes, erythrocytes, monocytes, and megakaryocytes (GEMM), granulocytes and monocytes (GM), or only megakaryocytes (MK) (n = 6–13 mice). (B) Frequencies of cells with the indicated marker expression within colonies from (A). (C) Representative images of colonies formed by HSCs or MPPs from WT and KO mice. (D) Number of secondary colonies produced from HSCs and MPPs in three serial replatings of 10,000 cells (n = 3 mice). (E) Adult WBM competitive transplant assays with 10⁶ untreated Hira^fl/fl (WT), Mx1-Cre; Hira^+/fl (HET), or Mx1-Cre; Hira^fl/fl (KO, all CD45.2⁺) donor BM cells competing against 5 × 10⁵ CD45.1⁺ BM cells in CD45.1 recipient mice (n = 5 mice). Recipient mice were treated with seven injections of poly(I:C) 4 weeks after transplant (red arrow). Frequencies of CD45.2⁺ WBCs in the peripheral blood tracked over 4 months post-transplantation are shown with statistical significance assessed between WT and KO. (F) Diagram showing the experimental strategy used for the fetal liver (FL) and adult HSC competitive transplants in (G). (G) Donor-derived chimerism of CD45.2⁺ WBCs (overall) and myeloid, B, and T cells in the peripheral blood tracked over 4 months post-transplantation for FL and adult HSC competitive transplants from (F) (n = 5 mice). (H) Donor-derived chimerism, as assessed by GFP positivity, within RBC and platelets (PLT) from transplanted HSCs isolated from Ubc-GFP; Hira^fl/fl (WT) or Ubc-GFP; Mx1-Cre; Hira^fl/fl (KO) mice (n = 3–5 mice). (I and J) A representative flow cytometry plot (I) and quantification (J) of the five fractions of erythroid progenitors expressing CD71 and/or Ter119 in the GFP⁺ BM cells 8 weeks post-transplantation (n = 3–4 mice). (K) Frequency of CD71⁺ erythroid cells after sorting HSCs into culture (n = 3 mice). All data represent the mean ± standard deviation; ^∗p < 0.05, ^∗∗p < 0.01, and ^∗∗∗p < 0.001 by Student's t test. See also Figure S2.

Figure 3

Hira loss increases erythroid gene expression in HSCs (A and B) GSEA of RNA-seq data from WT (Hira^fl/fl) and KO (Mx1-Cre; Hira^fl/fl) HSCs for PRC2 target genes that are bivalent (H3K27me3 and H3K4me3) or repressed (H3K27me3 only) (A) and heme metabolism hallmark gene set or genes expressed in nucleated erythrocytes (B). (C) Pairwise GSEAs assessing enrichment of genes that are upregulated in KO HSCs (top) or MPPs (bottom) in different hematopoietic cell types in a pairwise manner. The cumulative enrichment score of the gene sets for each hematopoietic cell type is shown (right). (D) Scatterplot of log₂(fold change) (L2FC) for erythroid differentially expressed genes (DEGs) (Ery) in HSCs, MPPs, or both (WT versus KO). (E) Expression of Rhag, Fech, Rhd, and Klf1 as determined by fragments per kilobase of transcript per million (FPKM) values. All data represent the mean ± standard deviation; ^∗p < 0.05 and ^∗∗p < 0.01 by Student's t test. See also Figure S3.

Figure 4

Cell division exacerbates the derepression of erythroid genes in Hira-deficient HSCs (A) Diagram showing treatment of Rosa26-M2rtTA; TetOP-H2B-GFP; Hira^fl/fl mice with or without Mx1-Cre to pulse-chase H2B-GFP labeling with doxycycline and delete Hira with poly(I:C). (B) Flow plots showing the gating used to separate H2B-GFP high/low fractions (n = 3 mice). (C) Frequencies of H2B-GFP high/low HSCs/MPPs in WT and KO mice (n = 3 mice). (D) The number of DEGs (WT versus KO) that are upregulated or downregulated between H2B-GFP high and low cells. (E) GO terms significantly enriched in WT versus KO HSCs that are either H2B-GFP high or low. (F–I) Unsupervised clustering of all DEGs (F), bivalent DEGs (G), nucleated erythrocyte DEGs (H), and DEGs associated with LT-HSCs (I) for H2B-GFP high/low cells. All data represent the mean ± standard deviation; ^∗∗p < 0.01, and ^∗∗∗p < 0.001 by Student's t test. See also Figure S4.

Figure 5

Hira loss increased DNA accessibility and decreased histone H3.3 at hematopoietic transcription factor motifs (A and B) Heatmaps and profile plots of ATAC-seq (A) and H3.3 ChIP-seq (B) data from WT and KO HSCs with six clusters of peaks identified by k-means clustering. (C and D) Motif enrichment analysis in differential ATAC-seq peaks called in KO versus WT HSCs (ATAC up, C) or in differential H3.3 ChIP-seq peaks called in WT versus KO HSCs (H3.3 down, D). (E) Genome-wide H3.3 ChIP-seq profile plot at RUNX1 motifs. (F) GSEA shows that genes in close proximity to RUNX1 motifs with reduced H3.3 binding in KO HSCs are derepressed.

Figure 6

H3.3 occupies a subset of polycomb-repressed genes in a Hira-dependent manner (A) Scatterplot correlating DNA accessibility in WT and Hira KO HSCs using ATAC-seq signals with overlapping H3.3 peaks that decreased (red) or increased (blue) in KO HSCs. The gray histogram shows ATAC-seq peaks not overlapping any H3.3 differential peaks. (B) ChromHMM emission parameters for an 18-chromatin-state model of HSCs with dark red indicating a high probability of each histone mark being found in each chromatin state (left). Each state is labeled based on the regulatory elements associated with their corresponding histone marks (right). (C) The fold enrichment of each WT HSC chromatin state overlapping bone marrow superenhancers and TSSs normalized to the maximum enrichment of each region for all chromatin states (range = 0–1). (D and E) GSEAs show that KO HSCs have derepression of genes with promoters or TSSs overlapping states 9 (D) or 10 (E). (F) Selected GO terms significantly associated with genes with promoter or TSS regions overlapping state 9, 10, or 11. (G) The fold enrichment of state 9, 10, or 11 within regions where ATAC-seq signals are increased (ATAC UP) or H3.3 is reduced (H3.3 DN) in KO HSCs normalized to the maximum enrichment of each region for all chromatin states (range = 0–1). (H) Profile plots of ATAC-seq and H3.3 ChIP-seq data at the H3.3+ polycomb repressed (state 10) chromatin state in WT and Hira KO HSCs.