TET2 Deficiency Increases the Competitive Advantage of Hematopoietic Stem Cells through Upregulation of Thrombopoietin Receptor Signaling

doi:10.21203/rs.3.rs-4151500/v1

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TET2 Deficiency Increases the Competitive Advantage of Hematopoietic Stem Cells through Upregulation of Thrombopoietin Receptor Signaling

https://doi.org/10.21203/rs.3.rs-4151500/v1

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Ten-Eleven Translocation-2 (TET2) mutations drive the expansion of mutant hematopoietic stem cells (HSCs) in clonal hematopoiesis (CH). However, the precise mechanisms by which TET2 mutations confer a competitive advantage to HSCs remain unclear. Here, through an epigenetic drug screen, we discovered that inhibition of disruptor of telomeric silencing 1-like (DOT1L), a H3K79 methyltransferase, selectively reduced the fitness of Tet2 knockout (Tet2^KO) hematopoietic stem and progenitor cells (HSPCs). Mechanistically, we found that TET2 deficiency increased H3K79 dimethylation and expression of Mpl, which encodes the thrombopoietin receptor (TPO-R). Correspondingly, TET2 deficiency was associated with a higher proportion of primitive Mpl-expressing (Mpl⁺) cells in the HSC compartment. Importantly, inhibition of Mpl expression or the signaling downstream of TPO-R was sufficient to reduce the competitive advantage of murine and human TET2-deficient HSPCs. Our findings demonstrate a critical role for aberrant TPO-R signaling in TET2 mutation-driven CH and uncover potential therapeutic strategies against this condition.

Biological sciences/Stem cells/Haematopoietic stem cells

Biological sciences/Cancer/Cancer prevention

Clonal hematopoiesis (CH) refers to a condition in which a hematopoietic stem cell (HSC) acquires genetic alterations that confer the mutant cell a competitive advantage over wild-type (WT) HSCs, resulting in its clonal expansion over time.¹ Clonal hematopoiesis of indeterminate potential (CHIP) is a more narrowly defined condition in which cancer-associated mutations are present at ≥ 2% variant allele frequency (VAF) in the blood cells of an individual without evidence of a blood cancer.² CHIP carriers are at a higher risk of developing hematologic malignancies and other age-related inflammatory illnesses such as cardiovascular diseases, relative to non-carriers.^1,3,4

Ten-Eleven Translocation-2 (TET2), which encodes a methylcytosine dioxygenase,⁵ is the second most frequently mutated gene in CHIP.^6,7 Loss-of-function (LoF) mutations in TET2 are found in 10–30% of CHIP carriers.^8–10 TET2 regulates gene expression by catalyzing DNA demethylation via the conversion of 5-methylcytosine (5-mC) to 5-hydroxymethylcytosine (5-hmC).^11,12 In murine models, TET2 deficiency increases the self-renewal of HSCs as assessed by competitive transplantation assays and leads to an expansion of the HSC compartment over time.^13–16 These findings indicate that TET2 activity is critical regulator of stemness properties in HSCs. However, the precise mechanisms by which loss of TET2 activity leads to the competitive advantage of TET2-mutated HSCs remain elusive.

To uncover potential mechanisms, we performed an epigenetic drug screen to identify differential dependencies between Tet2 knockout (KO) and Tet2 wildtype (WT) HSPCs. Through this screen, we discovered that aberrant thrombopoietin receptor (TPO-R) signaling plays a critical role in promoting the competitive advantage of TET2-deficient HSCs.

Chemical library screen reveals a dependency on DOT1L activity in Tet2^KO HSPCs

To identify potential differential dependencies between Tet2^KO and Tet2^WT HSPCs, we first generated an isogenic cell line system by overexpressing human Homeobox B4 (HOXB4), a transcription factor involved in self-renewal of stem cells,¹⁷ and a fluorescent reporter (Venus) in Sca-1⁺ HSPCs isolated from a Tet2^KO mouse and a sex-matched Tet2^WT littermate (Figures S1A and S1B). ¹⁵ Overexpression of HOXB4 has been shown to immortalize murine hematopoietic progenitor cells (HPCs) without frank leukemic transformation.¹⁸ The resulting cells (hereafter referred to as HPC^HOXB4) could be grown indefinitely in cytokine supplemented medium and displayed a granulocyte-monocyte progenitor (GMP)-like surface immunophenotype (Lin⁻ / Sca-1⁻ / c-Kit⁺ / CD34⁺ / CD16/32⁺) (Figure S1C). The immunophenotype profiles were similar between Tet2^WT and Tet2^KO HPC^HOXB4 cells (Figure S1C). The Tet2^KOHPC^HOXB4 cells demonstrated a strong competitive growth advantage over Tet2^WTHPC^HOXB4 cells in culture (Fig. 1A).

Given the epigenetic role of TET2, we reasoned that its deficiency could be associated with dependencies on the activity of other epigenetic regulators. Therefore, we used the isogenic cell lines to conduct a drug screen of 36 well-characterized and specific epigenetic chemical probes from the Structural Genomics Consortium (SGC).¹⁹ To conduct the screen, Tet2^KOHPC^HOXB4 cells were mixed at a 1:4 ratio with Tet2^WTHPC^HOXB4 competitor cells that were marked by blue fluorescent protein (BFP) expression. The mixed population was then treated with each probe for 14 days (Figure S1D). The screen identified SGC0946, an inhibitor of the activity of histone H3 at lysine 79 (H3K79) methyltransferase disruptor of telomeric silencing 1-like (DOT1L),²⁰ as the top compound that reduced the competitive advantage of Tet2^KOHPC^HOXB4 cells (Fig. 1B). Treatment with SGC0946, but not the inactive control compound SGC0649, selectively decreased the growth of Tet2^KOHPC^HOXB4 cells by reducing their viability and cell proliferation (Figs. 1C, S1E and S1F). A similar impact on Tet2^KOHPC^HOXB4 cells was seen with pinometostat, another DOT1L inhibitor (Figs. 1C, S1E and S1F).²¹ SGC0946 treatment also increased the expression of the myeloid differentiation markers, CD11b and CD16/32, to a greater extent on Tet2^KO than Tet2^WT HPC^HOXB4 cells (Figure S1G). To further validate these findings, we downregulated Dot1l expression using RNA interference (RNAi) (Figure S1H) and observed a selective reduction in the competitive advantage of Tet2^KOHPC^HOXB4 cells (Fig. 1D). SGC0946 treatment or genetic knockdown of Dot1l also selectively reduced the competitive advantage of unmodified Tet2^KO Lin⁻/c-Kit⁺ (LK) HSPCs (Figs. 1E, 1F and S1H) and the clonogenic potential of Tet2^KO Sca-1⁺ HSPCs (Fig. 1G), indicating that the dependency on DOT1L was not an artifact of HOXB4 overexpression. Together, our findings indicate that TET2-deficient HSPCs are dependent on DOT1L activity to maintain their advantage over WT HSPCs.

TET2 deficiency increases DOT1L-mediated H3K79 dimethylation of the Mpl locus and Mpl gene expression in HSPCs

To identify candidate genes that mediate this differential effect, we performed bulk RNA sequencing (RNA-seq) and H3K79 dimethylation (H3K79me2) chromatin immunoprecipitation followed by sequencing (ChIP-seq) analyses on untreated and SGC0946-treated Tet2^KO and Tet2^WT HPC^HOXB4 cells. Given that H3K79me2 is correlated with active gene transcription, we reasoned that the candidate genes should be more highly expressed and associated with higher H3K79me2 levels in Tet2^KO cells relative to Tet2^WT cells. Furthermore, their gene expression and associated H3K79me2 levels should be reduced with DOT1L inhibition. The RNA-seq analysis revealed 598 differentially upregulated genes in Tet2^KO cells relative to Tet2^WT cells and 70 differentially downregulated genes in SGC0946-treated Tet2^KO cells relative to untreated Tet2^KO cells (Fig. 2A). Twenty genes overlapped between these two sets (Figs. 2B and 2C). Next, we analyzed for potential differences in H3K79 methylation at the global and locus-specific level between Tet2^KO and Tet2^WT HPC^HOXB4 cells. Total H3K79me2, H3K79me3, and DOT1L proteins levels as determined by Western blotting were similar between these two cell types (Figures S2A and S2B). ChIP-seq analysis also showed that genome-wide levels and distribution of H3K79me2 were similar between untreated Tet2^KO and Tet2^WT HPC^HOXB4 cells (Fig. 2D). As anticipated, treatment with SGC0946 decreased the level of H3K79me2 in both Tet2^KO and Tet2^WT HPC^HOXB4 cells (Figs. 2D and S2A). However, the magnitude of decrease was greater in Tet2^KO cells, which could be due to their higher proliferation rate resulting in faster passive dilution of the H3K79me2 mark (Figure S1F). Differential H3K79me2 analysis at the locus-specific level identified 732 genes with increased H3K79me2 in Tet2^KO cells relative to Tet2^WT cells, 4,225 genes with decreased H3K79me2 in SGC0946-treated Tet2^KO cells relative to untreated Tet2^KO cells, and 338 overlapping genes between these two sets (Fig. 2E and S2C). Intriguingly, the intersection between the 4 sets of genes defined by differential gene expression and H3K79me2 levels contained only two genes, St8sia6 and Mpl (Fig. 2F), which encode a sialyltransferase and a receptor for the cytokine, thrombopoietin (TPO), respectively.^22–24 We decided to focus on the role of Mpl in our subsequent studies because 1) Mpl was more significantly differentially expressed than St8sia6 (Figures S2D and S2E) and 2) TPO signaling has been shown to regulate hematopoietic stem cell (HSC) self-renewal and expansion.^25–27 Quantitative RT-PCR analysis confirmed that Mpl expression was significantly higher in Tet2^KO compared with Tet2^WT cells at baseline and decreased after SGC0946 treatment in both HPC^HOXB4 and unmodified LK HSPCs (Fig. 2G). The changes in gene expression were associated with a higher level of H3K79me2 at the body and promoter region of the Mpl gene in Tet2^KO relative to Tet2^WT HPC^HOXB4 cells and a decrease in the histone mark after SGC0946 treatment (Fig. 2H). To confirm that this finding was not restricted to HOXB4-overexpressing cells, we conducted ChIP-qPCR analysis of unmodified LK HSPCs and observed a higher enrichment of H3K79me2 at the Mpl locus in Tet2^KO than Tet2^WT cells (Figure S2F). Taken together, these findings provide evidence that TET2 deficiency causes aberrant H3K79 hypermethylation at the Mpl locus and a consequent increase in Mpl gene expression.

TET2 deficiency increases the proportion of Mpl⁺ cells in the HSC compartment

Mpl expression in HSCs has previously been shown to be associated with stemness properties including self-renewal, quiescence, and long-term repopulation potential.^28,29 Based on these and our findings above, we hypothesized that a potential mechanism by which TET2 deficiency confers a competitive advantage to mutant HSCs is through increased Mpl expression in the HSC compartment in a DOT1L-dependent manner. To test this hypothesis, we transplanted Tet2^WT or Tet2^KO whole bone marrow (WBM) cells from sex-matched littermates in a non-competitive manner into lethally irradiated mice. At 4 weeks after transplantation, we treated the engrafted mice with vehicle or pinometostat at 60mg/kg twice a day by subcutaneous injection (n = 2 of each treatment condition and genotype). This in vivo dosing regimen has previously been reported to reduce H3K79 methylation and suppress tumor growth in mice.³⁰ After 21 days of treatment, we isolated LK cells from the recipients and performed single cell RNA-seq (scRNA-seq) analysis (Fig. 3A).³¹ Pinometostat treatment reduced the global level of H3K79me2 by ~ 60% in the LK cells (Figures S3A and S3B). Data integration and clustering analysis of the scRNA-seq data identified 27 transcriptional clusters and nine stem and progenitor fractions according to a murine HSPC gene expression reference dataset (Fig. 3B).^32,33 The clustering pattern was similar between Tet2^KO and Tet2^WT LK HSPCs (Figure S3C). Consistent with prior studies, the proportion of transcriptomically-defined HSCs was higher in Tet2^KO LK cells than that in Tet2^WT LK cells (Figs. 3C and S3D).^33–35 Pinometostat treatment reduced the proportion of HSCs in Tet2^KO samples to a level comparable to that of untreated Tet2^WT samples (Figs. 3C and S3D). Among the transcriptomically-defined HSC subsets, the impact of TET2 deficiency and pinometostat was most pronounced in the unprimed HSC-1 cluster (Fig. 3D). These findings indicate that the expansion of HSCs due to TET2 deficiency is dependent on DOT1L activity.

Gene signature analysis revealed an enrichment of genes associated with stemness and quiescence in Tet2^KO HSCs compared with Tet2^WT HSCs (Figure S3E), suggesting that TET2 deficiency might increase the proportion of a more primitive subset of cells in the heterogeneous transcriptomically-defined HSC cluster. Since we found that TET2 deficiency upregulated Mpl expression, which has previously to shown to be a marker of long-term HSCs (LT-HSCs),²⁹ we analyzed the pattern of Mpl expression in our scRNA-seq dataset. Mpl expression was mostly restricted to cells in the HSC and megakaryocyte progenitor (MkP) clusters (Fig. 3E). Notably, the proportion of cells with any detectable Mpl transcript in the HSC clusters was higher in Tet2^KO than in Tet2^WT samples (Fig. 3F). To confirm this finding, we employed a more stringent threshold of ≥ 3 detectable Mpl transcripts to define high Mpl expression (Mpl^Hi). The proportion of Mpl^Hi cells in the HSC clusters was significantly higher in Tet2^KO than in Tet2^WT samples, a difference that was abrogated by pinometostat treatment (Figs. 3G, S3F and S3G). Pinometostat did not decrease Mpl expression in MkPs, indicative of a cell-type specific drug effect (Figures S3F and S3G). To determine if Mpl expression identified a more primitive subset of HSCs in our dataset, we performed gene set enrichment and differential gene expression analyses comparing the Mpl⁺ versus Mpl⁻ fraction in the HSC-1 cluster of vehicle-treated samples. These analyses revealed an upregulation of genes associated with stemness (e.g., Hoxb5, Mycn, and Mecom) and downregulation of genes associated with differentiation (e.g., Mpo and Csf1r) in the Mpl⁺ fraction compared with the Mpl⁻ fraction (Figs. 3H and 3I), providing evidence that the Mpl⁺ fraction was more immature than the Mpl⁻ fraction in the HSC-1 cluster. Importantly, the expression of stemness-related genes was similar between the Mpl⁺ fraction in Tet2^WT versus Tet2^KO samples (Figs. 3H, 3I, and S3H), suggesting that while TET2 deficiency increases the proportion of Mpl-expressing cells, it does not further alter the stemness properties of the Mpl⁺ cell fraction. Altogether, these findings demonstrate that TET2 deficiency increases the primitive Mpl⁺ cell fraction in the HSC compartment in a DOT1L dependent manner.

TET2-deficient HSPCs are dependent on thrombopoietin receptor signaling to maintain their competitive advantage

The thrombopoietin receptor (TPO-R), encoded by Mpl, has previously been shown to not only be a marker of LT-HSCs but also play a functional role in preserving the stemness properties of LT-HSCs and promoting their expansion through its downstream signaling pathways upon TPO activation.^29,36,37 Based on these considerations, we hypothesized that TET2 deficiency could endow a greater proportion of HSCs with the ability to respond to TPO, thereby enhancing the competitive advantage of mutant HSCs over WT HSCs. To test this hypothesis, we performed an in vitro competition experiment in which Mpl was knocked down in both CD45.2⁺Tet2^KO and CD45.1⁺Tet2^WT LK HSPCs through RNAi and observed a reduction in the competitive advantage of Tet2^KO cells (Fig. 4A). A similar finding was observed using Tet2^KO and Tet2^WT HPC^HOXB4 cells in competition assays (Figure S4A). Given the challenges in assessing HSC activity in vitro, we performed an in vivo competition experiment in which we mixed CD45.1⁺Tet2^WT and CD45.2⁺Tet2^KO Lin⁻ bone marrow (BM) cells, transduced them with a lentiviral vector expressing a doxycycline-inducible non-targeting (NT) or Mpl-targeting shRNA, and transplanted the mixed population into lethally irradiated murine recipients (Fig. 4B). Three weeks after transplantation, we determined the baseline level of chimerism in the transduced peripheral blood (PB) cell population and induced shRNA expression with the addition of doxycycline in drinking water. After 17 weeks of doxycycline treatment (20 weeks post-transplantation), Mpl knockdown reduced the proportion of CD45.2⁺Tet2^KO PB cells relative to baseline, whereas the proportion of CD45.2⁺Tet2^KO PB cells expressing NT shRNA increased over the same period (Figs. 4C and S4B). Importantly, Mpl knockdown decreased the proportion of LSK HSPCs and immunophenotypic LT-HSCs (LSK / CD150⁺ / CD48⁻) in the transduced BM cell population at endpoint (Fig. 4D). These findings demonstrate that TET2-deficient HSPCs are dependent on TPO-R signaling to maintain their competitive advantage over WT HSPCs.

Inhibition of TPO-R/JAK2 signaling reduces the competitive advantage of murine and human TET2-deficient HSPCs

Upon ligand (TPO) binding, the TPO-R dimerizes and activates Janus Kinase 2 (JAK2), an intracellular tyrosine kinase that is associated with the cytoplasmic domain of the receptor.³⁸ JAK2 activation, in turn, triggers a cascade of signaling events including the phosphorylation and nuclear import of Signal Transducer and Activator of Transcription 5 (STAT5), which plays a critical role in HSC maintenance and self-renewal.³⁹ Although direct TPO-R antagonists have not been developed, JAK2 inhibitors are available and have been in clinical use for the treatment of myelofibrosis, polycythemia vera, graft-versus-host disease, and several autoimmune conditions.^40–42 Therefore, we decided to test if pharmacologic inhibition of JAK2 activity would reduce the competitive advantage of TET2-deficient HSPCs. Ruxolitinib, fedratinib, and AZ960 are potent JAK2 inhibitors with 50% inhibitory concentrations (IC₅₀) of < 3nM in cell-free enzymatic assays.^43–45 Treatment with these compounds at sub-micromolar concentrations for 7 days effectively reduced the competitive advantage of Tet2^KOHPC^HOXB4 cells over Tet2^WTHPC^HOXB4 cells (Figure S4C). Ruxolitinib treatment also selectively reduced the competitive advantage and clonogenic capacity of unmodified Tet2^KO HSPCs, indicating that the drug effect was not dependent on HOXB4 overexpression (Fig. 4E and 4F).

To explore the translational relevance of our findings, we tested the effect of ruxolitinib treatment on the competitive advantage of Tet2^KO HSPCs in vivo. We mixed CD45.2⁺Tet2^KO whole BM cells with CD45.1⁺Tet2^WT competitor cells at a 3:7 ratio and transplanted the mixed cell population into lethally irradiated recipients. At 3 weeks post-transplantation, we determined the baseline level of chimerism in PB and randomized the mice to receive treatment with ruxolitinib at 60mg/kg twice a day or vehicle by oral administration for 13 weeks (Fig. 4G). The proportion of CD45.2⁺ Tet2^KO cells in PB between the treatment groups was similar at baseline (Figure S4D). Ruxolitinib treatment reduced STAT5 phosphorylation in CD45.2⁺Tet2^KO Lin⁻ BM cells (Figure S4E) and the proportion of CD45.2⁺ Tet2^KO cells across stem and progenitor cell fractions in the BM compared with vehicle treatment (Figures S4F and S4G). Ruxolitinib treatment also reduced the proportion of CD45.2⁺ Tet2^KO cells in total PB cells and specifically in the B220⁺ B cell and CD11b⁺ myeloid cell fractions relative to vehicle treatment (Fig. 4H and 4I). These findings along with results of the Mpl knockdown studies above provide evidence that TET2-deficient HSPCs are dependent on signaling through the TPO-R/JAK2 axis to maintain their competitive advantage.

To determine the potential relevance of our findings in humans, we used CRISPR/Cas9-mediated gene editing to knockout TET2 in Lin⁻ cord blood HSPCs. We designed two sets of multi-guide guide RNAs (gRNAs) targeting TET2 (designated “KO-S” and “KO-D”) and a negative control targeting a pseudogene, OR2W5P. The gRNAs were complexed with recombinant SpCas9 and delivered into Lin⁻ cord blood cells using nucleofection, resulting in an indel efficiency of 82% for KO-S and 95% for KO-D in the cell pools (Figure S4H). The proportion of cells expressing the myeloid markers, CD11b and CD14, was less in the two TET2^KO cell pools than in control cells at day 21 after nucleofection (Figure S4I). CD34 enriched TET2^KO cells also demonstrated a higher clonogenic potential than control cells (Fig. 4J). These findings confirm the known impact of TET2 deficiency on self-renewal and differentiation of HSPCs. Importantly, the expression of TPO-R was higher in the CD34⁺CD38⁻ fraction of TET2^KO cells than in control TET2^WT cells, an effect that was reversed by DOT1L inhibition (Fig. 4K). Moreover, treatment with DOT1L and JAK2 inhibitors preferentially reduced the clonogenic potential and viability of TET2^KO HSPCs over their TET2^WT counterparts (Figs. 4J and S4J). Finally, we assessed if attenuation of TPO-R signaling could suppress the clonal expansion of TET2-mutated HSPCs derived from human samples with naturally acquired CH. We enriched Lin⁻ cells from two mobilized peripheral blood (mPB) samples with each carrying at least one predicted TET2 loss-of-function mutation (Figure S4K). The purified cells were cultured in TPO-containing medium, and the size of the mutant clones at different time points was monitored using sample-specific TaqMan genotyping probes and droplet digital PCR (ddPCR). A lower TPO concentration and treatment with SGC0946 or ruxolitinib decreased the rate of expansion of TET2-mutated clones (Figs. 4L and 4M). Our findings demonstrate that human TET2-mutated HSPCs express higher levels of TPO-R and are dependent on TPO-R signaling to sustain their competitive advantage.

Our findings demonstrate that TET2-deficient HSCs are dependent on TPO-R signaling to outcompete their TET2^WT counterparts. This differential dependency is mediated through aberrant DOT1L-mediated H3K79 methylation of the Mpl locus, leading to an increase in the proportion of Mpl-expressing HSCs. Mpl⁺ HSCs have a more primitive phenotype and are endowed with the ability to respond to TPO stimulation. We further showed that inhibition of DOT1L or the TPO-R/JAK2 signaling axis is effective in suppressing the competitive advantage of TET2-mutated HSPCs, thus identifying tractable therapeutic targets against TET2 mutation-driven CH.

Although TET2 deficiency has been shown to increase the stemness properties of HSCs, the underlying mechanisms remain unclear.^13,46 Our data indicate that aberrant expression of Mpl in the HSC compartment is a fundamental driver of this effect. We found that TET2 deficiency increases the overall stemness potential of mutant HSCs by expanding the proportion of Mpl⁺ cells. Moreover, we showed that the transcriptomes of Mpl⁺ HSCs were enriched for gene signatures associated with stemness, indicative of their more primitive cell state. Notably, we observed that TET2 deficiency did not further upregulate the expression of stemness-related genes in the Mpl⁺ fraction of HSCs, indicating the impact of TET2 deficiency on stemness is primarily mediated through modulation of TPO-R signaling. In addition to the direct impact of TPO-R signaling on mutant HSCs, it may also indirectly enhance their relative fitness by conferring resistance to the suppressive effects of pro-inflammatory cytokines such as tumor necrosis factor alpha (TNF-α).⁴⁷

Although DOT1L has been shown to be essential for normal hematopoiesis and the maintenance of mixed lineage leukemia (MLL)-rearranged leukemias,^48–50 a requirement for DOT1L activity in the expansion of TET2-deficient HSPCs has not previously been reported. Our study showed that while TET2 deficiency did not cause global changes in H3K79 methylation, it was associated with locus-specific changes, revealing a connection between TET2 and this epigenetic mark. Specifically, we found that the level of H3K79me2 was higher at the Mpl locus in Tet2-mutated HSCs. The precise mechanisms by which TET2 deficiency leads to these locus-specific changes are unclear. We speculate that TET2 might bind directly or indirectly via other interacting proteins to DOT1L or lysine demethylase 2B (KDM2B),⁵¹ a H3K79 demethylase, and its loss could lead to aberrant localization of one or both epigenetic modifiers, resulting in locus-specific changes in H3K79 methylation levels. Another potential mechanism might involve a crosstalk between the 5-mC/5-hmC and H3K79 methylation mark, whereby locus-specific changes in 5-mC/5-hmC due to TET2 deficiency cause localized alterations in H3K79 methylation. Further studies are required to delineate the precise link between TET2 and DOT1L activity.

The presence of CHIP is associated with an increased risk of a growing list of hematologic malignancies and age-related illnesses.^52,53 Interventions that effectively suppress the expansion of mutant HSCs can potentially lower the risk of CHIP-associated adverse outcomes and positively impact the health of a large segment of the aging population. Our findings here reveal DOT1L and the TPO-R/JAK2 signaling axis as potential therapeutic targets against TET2 mutation-driven CHIP.

Our study was focused on identifying dependencies associated with TET2 mutations. It is unclear if the observed dependencies on DOT1L activity and TPO-R signaling are specific for TET2 mutations or shared across CH-related mutations. It is conceivable that mutations affecting functionally different genes in CH (e.g., DNMT3A and splicing factor genes) share common pathogenic mechanisms and dependencies with TET2 mutations.

In addition, although a larger clone size has generally been associated with a higher risk of developing hematologic malignancies and other CHIP-related illnesses, it is not known if the suppression of clonal expansion alone is sufficient to decrease the risk of these adverse outcomes.^7,54–57 There are limitations to current in vitro assays and animal models to vigorously test this hypothesis. Clinical trials involving interventions that suppress the expansion of mutant clones in CHIP carries are ultimately required to address this important clinically relevant question.

Mouse models

Tet2 ^KO (strain name: B6(Cg)-Tet2^tm1.2Rao/J) parental mice were ordered from the Jackson Laboratory and crossed with Tet2^WT C57BL/6J mice to heterozygous (Tet2^HET) mice. The Tet2^HET mice were then crossed to generate Tet2^WT and Tet2^KO animals in the same litter. CD45.1⁺ Tet2^WT mice in the C57BL/6J background (strain name: B6.SJL-Ptprca Pepcb/BoyJ) were ordered from the Jackson Laboratory.

Generation of the HPC^HOXB4cell models

Bone marrow cells were isolated from 8-week-old male Tet2^WT and Tet2^KO littermates from a Tet2^HET x Tet2^HET breeding pair. Sca-1⁺ HSPCs were enriched using the EasySep^™ mouse SCA1 positive selection kit (STEMCELL, #18756). Enriched cells were then infected with retroviral particles expressing HOXB4-Venus (a gift from Norman Iscove’s lab). Briefly, Tet2^WT or Tet2^KO cells were seeded at a density of 2x10⁵ cells/mL in a well in a 24-well TC-treated tissue culture plate (Falcon, #353047) and infected with 50uL of viral supernatant diluted in 450uL of growth medium (see ‘Tissue culture’ section) in the presence of 8ug/mL of polybrene (Millipore, #TR10039). Growth medium was replaced on the next day. The level of Venus fluorescence was measured by flow cytometry at 72 hours post infection to access transduction efficiency.

Human mobilized peripheral blood (mPB) samples

Human mPB samples were obtained with informed consent from Princess Margaret Cancer Centre following the procedures approved by the University Health Network (UHN) research ethic board. Mononuclear cells were isolated by density gradient centrifugation using Ficoll-Paque^™ (Fisher Scientific, #45001749), and hematopoietic progenitors were enriched through lineage marker depletion (STEMCELL, #14056).

Human cord blood samples

Human cord blood samples were obtained with informed consent from Princess Margaret Cancer Centre following the procedures approved by the University Health Network (UHN) research ethic board. Mononuclear cells from 1–5 pooled female and male donors were isolated and enriched for HSPCs using the above-mentioned protocols.

Tet2 genotyping

Genomic DNA was extracted from mouse tails and the HPC^HOXB4 cell lines using standard protocols. Genotyping PCR was performed according to the protocol provided by the Jackson Laboratory for B6(Cg)-Tet2^tm1.2Rao/J mice. The sequence of the primers used are shown in Table S1. Genotyping PCR was conducted using Taq polymerase (NEB, #M0495S) and buffer (ThermoFisher, #18067017). PCR products were visualized on 1.5% (w/v) agarose gels with SYBR^™ Safe DNA gel stain (Thermo Scientific, #S33102).

Tissue culture

HPC^HOXB4 cells were cultured in IMDM medium (Wisent, #319-105-CL) containing 10% FBS (Wisent, #080–150), murine stem cell factor (mSCF, 100ng/mL; STEMCELL, #78064.2), recombinant human FLT3 ligand (FLT3-L, 50ng/mL; STEMCELL, #78009.2), and recombinant human thrombopoietin (TPO, 25ng/mL; STEMCELL, #78210.2).

Hematopoietic progenitor cells were isolated from human mPB samples using the EasySep^™ human progenitor cell enrichment kit (STEMCELL, #19356) and cultured in StemSpan SFEM II medium (STEMCELL, #09655) supplemented with 20% BIT 9500 (STEMCELL, #09500), 1% Gluta-Plus (Wisent, #609-066-EL), mSCF (100ng/mL), FLT3-L (100ng/mL), TPO (100ng/mL), StemReginin/SR1 (750nM, SelleckChem, S2858), and UM729 (500nM, STEMCELL, #72332).

Cord blood hematopoietic progenitor cells were isolated from cord blood samples using the EasySep^™ human progenitor cell enrichment kit (STEMCELL, #19356) and cultured in StemSpan SFEM II medium (STEMCELL, #09655) supplemented with 20% BIT 9500 (STEMCELL, #09500), 1% Gluta-Plus, mSCF (100ng/mL), FLT3-L (100ng/mL), and TPO (100ng/mL).

All cell lines and human samples were maintained in an incubator at 37°C with 5% CO₂.

Lentivirus production and transduction

HEK293T cells were grown in RPMI 1640 medium (Wisent, #350-035-CL) supplemented with 10% FBS (Wisent, #080–150) and 1% Gluta-Plus (Wisent, #609-066-EL). Cells were seeded in 15cm tissue culture plates (Sarstedt, #83.3903) at a density of 7 x10⁶ cells per plate one day before transfection. On the day of transfection, cells were co-transfected with lentiviral plasmid vectors, psPAX2 (Addgene, #12259), and pCMV-VSVG (Cell biolabs, #320023) using the jetPRIME transfection reagent (Polyplus, #CA89129-924) according to manufacturer’s protocol. Supernatant containing viral particles was collected at 48- and 72-hours post transfection and filtered through a 0.45 µm PVDF membrane (Sigma, #SE1M003M00). Viral particles were precipitated in 40%(w/v) polyethylene glycol (Sigma, #89510-1KG-F) overnight. On the next day, the viral particles were collected by centrifugation at 3,700rpm for 30 mins at 4°C. The pellet was resuspended in HBSS (Gibco, #14170112) + 25mM HEPES (Thermo Fisher, #15630-080) and stored at -80°C for long term storage.

For lentiviral transductions, non-TC-treated 24 well plates were coated with 20 µg/mL of Retronectin (Takara, Cat # T100B) for 2 hours at room temperature followed by aspiration and blocking with PBS containing 2% (w/v) BSA (Wisent Bioproducts, Cat # 800-096-EG) for 30 mins at room temperature. After aspiration of the blocking buffer, the concentrated virus suspension was added to wells. The plates were then centrifuged at 3,700 rpm for two hours at 4°C to allow virus binding. Following centrifugation, unbound virus was aspirated, and cells were added. The plates were then transferred to a 37°C incubator to initiate lentiviral infection.

Generation of Venus^‒ cells using CRISPR/Cas9

A synthetic sgRNA targeting Venus was ordered from Synthego. See Table S2 for sequence. Recombinant S.pyogenes Cas9 endonuclease at a concentration of 10ug/uL (62uM) was purchased (IDT, #1081058). The sgRNA was reconstituted in 15uL of TE buffer to reach a stock concentration of 0.1mM. 2.5uL of the sgRNA was then mixed with 1.5uL of SpCas9 in a final volume of 25uL of Lonza P3 nucleofection solution (Lonza, #V4XP-3024) and incubated at room temperature for 15 minutes to allow formation of the sgRNA/Cas9 RNP complex. 1x10⁶ Tet2^WTHPC^HOXB4 cells were resuspended in 75uL of P3 nucleofection solution, added to the sgRNA/Cas9 RNP complex, and transferred to a Lonza nucleofection microcuvette. Nucleofection was conducted using a Lonza Amaxa™ 4D-Nucleofector under the program CA137. The presence of Venus knockout (Venus^‒) cells was assessed by flow cytometry 4 days after nucleofection.

In vitro competition assays

Competition assays were conducted in 96-well round-bottom tissue culture plates (Sarstedt, #83.3925) with a total of 1×10⁴ cells seeded in each well.

For competition assays involving HPC^HOXB4 cells, BFP^‒ or Venus⁺ HPC^HOXB4 cells were mixed with BFP⁺ or Venus^‒ competitor cells, respectively, at a 1:4 starting ratio in HPC^HOXB4 growth medium to start the competition. BFP⁺ competitor cells were generated by transducing Tet2^WTHPC^HOXB4 cells with the pRSI9-U6-sh-UbiC-TagBFP-2A-puro vector (Addgene, #28289). Venus^‒Tet2^WT HPC^HOXB4 competitor cells were generated as above. The BFP⁺ and Venus^‒ competitor cells were sorted to > 99% purity using a Becton Dickinson Aria III CFI cell sorter.

For competition assays involving unmodified murine bone marrow HSPCs, CD45.2⁺ and CD45.1⁺ whole bone marrow cells were harvested from age-matched mice (10–15 weeks). Lin^-Kit⁺ bone marrow HSPCs were enriched using the EasySep mouse hematopoietic progenitor isolation kit (STEMCELL, #19856) followed by the c-KIT positive enrichment kit (STEMCELL, #18757). Enriched CD45.2⁺ and CD45.1⁺ cells were then mixed at a 1:4 starting ratio and cultured in MethoCult^™ GF M3434 medium (STEMCELL, #03434) supplemented with recombinant human TPO (25ng/mL).

Chemical library screen

Epigenetic probes were dissolved in DMSO to achieve a 20,000X stock solution and then diluted in PBS to achieve a 200X working stock solution. BFP⁺Tet2^WTHPC^HOXB4 was generated by lentiviral transduction of Tet2^WTHPC^HOXB4 with a pCDH-EF1-TagBFP-T2A vector and enriched by FACS sorting. BFP^‒Tet2^KOHPC^HOXB4 cells were mixed with BFP⁺Tet2^WTHPC^HOXB4 competitor cells at the ratio of 1:4 and then seeded in 96-well round-bottom TC-treated plates at 1x10⁴ total cells per well. The cells were cultured in HPC^HOXB4 growth medium and treated with each epigenetic probe at a final concentration shown in Table S3 or DMSO (0.01%). Cells were split at 1:10 ratio on day 7 by adding 20uL of cells from old wells to 180uL of media containing epigenetic probes at screen concentration. The percentage of BFP⁺ cells in each well was measured by flow cytometry after 14 days of treatment.

Flow cytometry

For staining of cell surface antigens, cells were incubated with antibodies at the recommended dilutions (Table S4) in FACS buffer (HBSS supplemented with 2% FBS and 0.1% sodium azide) for 20 mins at 4°C. The cells were washed once in FACS buffer prior to analysis. For Annexin V staining, cells were resuspended in Annexin V buffer and stained with APC-conjugated Annexin V diluted in 1:200 (Invitrogen, #A35110) for 15 mins at room temperature prior to analysis. Flow cytometry analysis was conducted using the Beckman Coulter CytoFLEX analyzer. FCS files were analyzed using the FlowJo^™ V10 software.

Intracellular flow cytometry

Intracellular flow cytometry staining for phospho-STAT5 in murine bone marrow cells was performed using the BD Cytofix/Cytoperm fixation and permeabilization kit according to the manufacturer’s protocol. Briefly, fixed and permeabilized cells were stained with a phospho-STAT5 antibody (CST, #9359) diluted 1:200 in HBSS supplemented with 2% FBS and 0.1% sodium azide for 1 hour at room temperature. The cells were then washed in FACS buffer and stained with an Alexa Fluor 647-conjugated anti-rabbit IgG (H + L) secondary antibody (CST, #4414S) diluted 1:2,000 in PBS with 1% FBS and 50mM EDTA for 30 mins at room temperature. A rabbit IgG isotype antibody (CST, #2985S) was used to determine the level of isotype control staining.

EdU proliferation assay

One day prior to the assay, drug-treated Tet2^WT and Tet2^KO HPC^HOXB4 cells were seeded in wells in a 24-well tissue culture plate at a cell density of 1×10⁵ cells/mL. On the next day, EdU dissolved in DMSO was directly added to the growth medium at a final concentration of 10uM. The cells were incubated with EdU for 1 hour at 37°C prior to staining. Staining for EdU incorporation was performed using the Click-iT Pacific Blue EdU flow cytometry assay kit (Invitrogen, #C10636) as per the manufacturer’s protocol.

Colony-forming unit (CFU) assays

CD34⁺ human HSPCs were enriched from cord blood samples using the CD34⁺ positive selection kit (STEMCELL #17856). 1x10⁴ enriched Sca-1⁺ murine HSPCs or CD34⁺ human HSPCs were resuspended in 1.1mL of MethoCult^™ GF3434 medium or MethoCult^™ H4435 medium, respectively. The medium was supplemented with recombinant human TPO (25ng/mL). The resuspended cells were added to wells in a 6-well tissue culture plate. The number of colonies formed was determined after 7 days in culture and if necessary, the cells were replated.

RNA-sequencing analysis

Total RNA was extracted from cells using the Qiagen RNeasy plus kit (Qiagen, #74134) and quantified using a Nanodrop spectrophotometer. All samples had a RIN value greater than 9. Samples were submitted to Novogene Corporation for sequencing analysis. Library construction, sequencing, and processing of sequencing data were done by Novogene following their standard pipeline. Sequencing was performed on an Illumina NovaSeq 6000 system. Reads containing adaptors and low-quality reads with Phred scores less than 33 were filtered. Clean reads were then mapped to the reference genome using the STAR software v2.6.1d. Quantification of mapped reads was conducted on FeatureCounts (v1.5.0-p3) program and default parameters were applied.

For differential gene expression (DGE) analysis, triplicate pairwise samples were analyzed using DESeq2 R package (v1.20.0). P-values were adjusted using the Benjamini and Hochberg’s approach. |log2FC| > 1.5 and padj < 0.01 were used as the cutoffs for differentially expressed genes.

Chromatin-immunoprecipitation sequencing (ChIP-seq) analysis

Cells were fixed with 1% formaldehyde (Thermo Scientific, #410730050) according to the Active Motif ChIP cell fixation protocol. Fixed cell pellets were submitted to Active Motif for ChIP-seq analysis. Briefly, 15ug of chromatin and 10uL of H3K79me2 antibody (Active Motif, #39143) were used for each IP reaction. Illumina base-call data were processed and demultiplexed using bcl2fastq2 v2.20 and low-quality bases with Phred scores less than 33 were trimmed. 75 bp single-end sequence reads were subsequently mapped to the genome through BWA v0.7.12 algorithm with default settings. Low quality reads were filtered out and PCR duplicates were removed. Aligned sequencing reads, or tags, were extended to 200bp from the 3’ end, followed by dividing the genome into 32bp bins and counting the number of fragments in each bin. Determination of enriched regions was done using SICER 1.1 peak calling tool, with FDR < 1e-10 and gap parameter of 600bp used as cutoffs. False ChIP-seq peaks as defined within the ENCODE blacklist were removed. Differential methylation analysis was conducted using DiffBind R package version 3.10.0 and signals from each sample were normalized to library size. Hypermethylated regions in pairwise comparisons were defined using log2(FC in normalized reads) > 1.5 and padj < 0.01 as cutoffs. Hypomethylated regions were defined using log2(FC in normalized reads) < -1.5 and padj < 0.01 as cutoffs. Average peak signals from two replicates of each sample were obtained through randomly sampling 50 percent of reads from the corresponding BAM file of each replicate, and then merged using Samtools version 1.14. Average plots and heatmaps were generated using Deeptools version 3.5.1. BigWig files were visualized using WashU Epigenome browser.

RT-qPCR

Total RNA was extracted from cells using the Qiagen RNeasy plus kit and quantified on a Nanodrop spectrophotometer. Reverse transcription and quantitative PCR were performed using the Luna^® Universal One-step RT-qPCR kit (NEB, #E3005S) and the Bio-Rad CFX touch real-time PCR detection system. The primers used are listed in Table S5. The threshold cycle (Ct) value was determined using CFX Manager v3.1. Gene expression was calculated using the ^∆∆Ct method. Ct values were normalized to beta actin (Actb).

ChIP-qPCR

Lin^-Kit⁺ bone marrow HSPCs were enriched from Tet2^WT and Tet2^KO mice using selection kits (STEMCELL, #19856 and #18757). Chromatin for each CHIP reaction was prepared with 10⁶ HSPCs using Diagenode chromatin EasyShear kit following the manufacturer protocol (Diagenode # C01020010). Chromatin was sheared at 4ºC on a Bioruptor^® Pico sonicator in 100uL volume with 30s on and 30s off for 20 pulses. Each ChIP reaction was conducted using 7uL of H3K79me2 antibody (Active motif, #39143) following a published protocol (Bailey SD et al., Nat Genet. 2016). DNA was purified using Zymo ChIP DNA clean and concentrator (Zymo research, #D5205) and eluted in 40uL of deionized water. qPCR was performed with Biobasic qPCR mastermix (Biobasic, #QPCR004-S) and the Bio-Rad CFX touch real-time PCR detection system. qPCR primers against Mpl and two negative control regions were ordered from IDT. Sequences of ChIP-qPCR primers are listed in Table S6. Enrichment was calculated using the percent input method.

Single-cell RNA (scRNA) sequencing

Whole bone marrow cells were isolated from 15 to 20-week-old Tet2^WT and Tet2^KO male littermates following red blood cell depletion. Cells from each donor were transplanted into four lethally irradiated 8-week-old CD45.2 Tet2^WT recipients at 1x10⁶ cells per animal. Following four weeks of engraftment, mice were subject to pinometostat (60mg/kg) or vehicle (10% DMSO, 40% PEG300, 5% Tween-80, and 45% saline) treatment through subcutaneous injection twice a day (2 animals per cell type per treatment group) for 21 days. Mice were then euthanized and Lin^-Kit⁺ (LK) HSPCs were enriched from the bone marrow using selection kits (STEMCELL, #19856 and #18757). The purified cells were resuspended in IMDM medium (Wisent, #319-105-CL) and subjected to library preparation using 10x Genomics Chromium Single Cell 3′ v3.1 kit and 3’ sequencing on illumina Novaseq 6000 sequencing system. The FATSQ files were processed using Cellranger v7.0.0 pipeline to generate count matrices. Cells were filtered using the following cutoffs: 200 < nFeature < 9000; percent of mitochondrial reads < 12.5. The filtered reads were then normalized accounting for cell cycle difference using the SCTransform function from the Seurat package (v5.0.1). Samples showed a median of 22,504 Unique Molecular Identifiers (UMIs) per cell and 5,044 genes detected.

The filtered cells were subsequently assigned with a cell type label using the previously curated gene list (Izzo et al., Nat Genet. 2020). HSC = Hematopoietic stem cell; IMP = Immature myeloid progenitor, Mono = Monocyte progenitor, Neu = Neutrophil/granulocyte progenitor; EB = Erythroid/basophil progenitor; Ery = Erythroid progenitor; MkP = Megakaryocyte progenitor; CLP = Common lymphoid progenitor; Ba = Basophil progenitor; Eo = Eosinophil progenitor; B-cell-P = B cell progenitor; T-cell-P = T cell progenitor. Uniform Manifold Approximation and Projection (UMAP) reduction with the following parameters: reduction = “pca”, dims = 1:50 was employed for clustering.

AUCell (v1.25.0) package was used for gene signature enrichment analyses. Gene sets were imported from the molecular signatures database (MSigDB). Top 20 percent highest expressed genes were used in calculating the area under curve (AUC) for each gene set. Student T test was used to determine statistical significance between two groups.

Differential gene expression (DGE) analysis comparing Mpl⁺ vs Mpl^- HSCs from the vehicle treated group was performed using FindMarkers() function of the Seurat package. Non-paramatric Wilcoxon rank sum test was used to calculate differentially expressed genes. |Log₂FC| >1 was set as the fold-change cutoff. Only genes detected in equal or more than 0.01 percent of cells were tested. Genes passing the fold-change threshold were filtered again using adjust p value (padj) < 0.01 as cutoff. Cell type specific markers were imported from PanglaoDB (Franzén et al., Database. 2019) for Fig. 3I.

Western blot

Standard Western blotting techniques were performed. Blots were incubated with primary antibodies (Table S7) diluted in 5% (w/v) BSA in TBST overnight at 4°C on a shaking platform. On the next day, the blots were washed for five minutes for three times with TBST and incubated with a secondary antibody (LI-COR, #926-32213 or LICOR, #926-68073) at 1:2,000 dilution in 5% (w/v) BSA in TBST at room temperature for 1 hour. Membranes were washed three times again and imaged on the Odyssey CLx Imaging system (LI-COR Biosciences).

Droplet digital PCR (ddPCR)

Genomic DNA was extracted from treated cells. 125ng of DNA was used for each ddPCR reaction. The ddPCR reaction was prepared using the Bio-Rad ddPCR Supermix (Bio-Rad, #1863010). SNP assay primers and probes were ordered from Thermofisher (Table S8). Plates were read using a QX200 Droplet Digital PCR System (Bio-Rad). Results were analyzed using the QuantaSoft^™ software.

In vivo experiments

All in vivo experiments were performed in accordance with institutional guidelines approved by the University Health Network animal care committee. Study design and data collection were in accordance with the ARRIVE guidelines.

For the experiment testing the effect of ruxolitinib, CD45.2⁺ Tet2^KO BM cells from a 12-week-old male donor were mixed with CD45.1⁺ Tet2^WT BM cells from age-matched male donors at a 3:7 ratio. The mixed cells were resuspended in Opti-MEM medium and transplanted by tail vein injection into 8-week-old female CD45.2⁺ Tet2^WT recipient mice (1x10⁶ cells per mouse) conditioned with 12Gy of irradiation. At day 21 post-transplantation, the mice were randomized to receive vehicle or ruxolitinib. Ruxolitinib (Table S9) was dissolved in DMSO and then diluted in peanut oil. Mice were administered 2% DMSO in peanut oil (vehicle control) or ruxolitinib (60mg/kg) by oral gavage twice a day.

For the experiment testing the effect of Mpl knockdown, lineage-depleted (Lin^-) BM HSPCs from a 12-week-old male CD45.2⁺Tet2^KO mouse were mixed with Lin^- BM HSPCs from two age-matched CD45.1⁺Tet2^WT male mice at a 3:7 ratio. The mixed cells were co-transduced with a pRSITE-U6-shMpl-UbiC-TagBFP-T2A-Puro or pRSITE-U6-shNT-UbiC-TagBFP-T2A-puro lentiviral vector (Table S10). BFP⁺ cells were sorted on day 3 after transduction, resuspended in Opti-MEM, and transplanted by tail vein injection into lethally irradiated 8-week-old Tet2^WT female mice (1x10⁴ cells per mouse). At day 21 post-transplantation, doxycycline (Table S9) was added into the drinking water at a concentration of 2mg/mL to induce shRNA expression and replaced once a week.

Peripheral blood chimerism analysis

Peripheral blood samples were collected and incubated in 1X red blood cell lysis buffer (Biolegend, #420302). The RBC-depleted cells were incubated in 50uL of PBS containing a FcR blocker (Biolegend, #426103) at 1:2,000 dilution for 10 min at 4°C and then stained with fluorophore-conjugated antibodies in FACS buffer for 20 min at 4°C. The stained cells were washed and resuspended in FACS buffer containing Sytox^™ Green (Invitrogen, #S7020) at 1:1,000 dilution prior to flow cytometry analysis.

CRISPR/Cas9 mediated knockout of TET2 in human HSPCs

The synthetic TET2 KO-S sgRNAs (Table S2) were ordered from Synthego and resuspended in TE buffer to achieve a 100uM stock concentration. The synthetic TET2 KO-D and OR2W5P crRNAs were ordered from Integrated DNA Technologies and resuspended in TE buffer to achieve a 200uM stock concentration. TracrRNA was purchased from IDT (IDT, #1072532). To form the tracrRNA:crRNA complex, 1uL of each crRNA was mixed with 2uL of tracrRNA, heated at 95°C for 5 min on a thermocycler, and cooled. To form RNPs, 1.7uL of SpCas9 was diluted in 2.1uL of pre-warmed PBS and incubated with 1.2uL of the crRNA:tracrRNA complex or 2.5uL of sgRNAs at room temperature for 15 minutes. 1uL of Cas9 electroporation enhancer (IDT, #1075915) was added to the RNP complex solution. Cord blood HSPCs were enriched and cultured for 48 hours prior to nucleofection. After culturing, 5×10⁵ HSPCs were resuspended in 100uL of Lonza P3 nucleofection solution containing supplements. The RNP complex was added to the cells. The cells were transferred to a Lonza nucleofection microcuvette and electroporated using program DZ100 on a Lonza Amaxa^™ 4D-Nucleofector. Following electroporation, 1mL of culture medium was added to each microcuvette, and the cells were transferred to wells in a 24-well tissue culture plate. The culture medium was changed on the next day. Genomic DNA was extracted 1 day after nucleofection and subjected to PCR amplification using the primers listed in Table S11. PCR products were purified and submitted for Sanger sequencing. Estimation of knockout efficiency was determined using the ICE CRISPR Analysis Tool (Synthego).

Statistical analysis

Data are shown as means ± SD, unless otherwise indicated. Unpaired two-tailed Student’s T test was used to determine the level of significance between 2 sets of values. If needed, P-values were corrected for multiple comparisons using the Holm-Sidak method. P-values < 0.05 were considered significant. R bioinformatic analyses were conducted in R v4.3.2. Data were analyzed and visualized using the following R packages: ggplot2 (v3.4.4), ComplexHeatmap (v2.4.3), EnhancedVolcano (v1.6.0), VennDiagram (v1.7.3), ggpubr (v0.6.0), ggrepel (v0.9.4), AUCell (v1.24.0), msigdbr (v7.5.1), Seurat (v5.0.1), DESeq2 (v1.20.0).

Gene sets were downloaded from Molecular Signatures Database (MSigDB). Gene sets used for the enrichment analyses are: GRAHAM_NORMAL_QUIESCENT_VS_NORMAL_DIVIDING_UP; EPPERT_HSC_R; MALTA_CURATED_STEMNESS_MARKERS;PARK_HSC_VS_MULTIPOTENT_PROGENITORS_UP; IVANOVA_HEMATOPOIESIS_EARLY_PROGENITOR.

DATA AND MATERIAL AVAILABILITY:

HPC^HOXB4 cell lines and cloned vectors are available under a material transfer agreement with the University Health Network. Raw and processed data from RNA-seq, ChIP-seq, and scRNA-seq analyses are available for private peer review on Dryad: https://datadryad.org/stash/share/72jSqcRuq4JZsvccegD6x3tI-40OrpJFWE9byYQ-bQw. Raw and processed data will be published on GEO.

Acknowledgements:

We thank all members from Dr. Steven Chan’s lab for reading and providing advice on the manuscript; Mr. Robert Herrington from Dr. Norman Iscove lab for kindly gifting the HOXB4 retrovirus; the staff from SickKids-UHN Flow Cytometry Facility, the SickKids TCAG Sequencing Center, the UHN Bioinformatics and HPC core, the Princess Margaret Geonomics Centre, and the Max Bell Animal Resources Center for providing technical support; the patients from Princess Margaret Hospital for donating samples for this study.

Funding:

Leukemia and Lymphoma Society of Canada Blood Cancer Research Jump Start Grant (SMC)

University of Toronto Medicine by Design Cycle 2 Award (SMC)

Canadian Institutes of Health Research Project Grants DCP-186319 and PJT-175186 (SMC)

Author contributions:

Conceptualization: YY, SMC

Funding acquisition: SMC

Methodology: YY, SC, RV, and SMC

Investigation: YY, AS, SC, ACL, AM, MH, and DMA

Visualization: YY, ACL

Supervision: AS, SMC

Writing and editing: YY, SMC

Declaration of interests:

Authors declare that they have no competing interests.

The authors declare no potential conflicts of interest.

Jaiswal, S., and Ebert, B.L. (2019). Clonal hematopoiesis in human aging and disease. Science (1979) 366. 10.1126/science.aan4673.
Steensma, D.P., Bejar, R., Jaiswal, S., Lindsley, R.C., Sekeres, M.A., Hasserjian, R.P., and Ebert, B.L. (2015). Clonal hematopoiesis of indeterminate potential and its distinction from myelodysplastic syndromes. Preprint, 10.1182/blood-2015-03-631747 10.1182/blood-2015-03-631747.
Marnell, C.S., Bick, A., and Natarajan, P. (2021). Clonal hematopoiesis of indeterminate potential (CHIP): Linking somatic mutations, hematopoiesis, chronic inflammation and cardiovascular disease. J Mol Cell Cardiol. 10.1016/j.yjmcc.2021.07.004.
Libby, P., Sidlow, R., Lin, A.E., Gupta, D., Jones, L.W., Moslehi, J., Zeiher, A., Jaiswal, S., Schulz, C., Blankstein, R., et al. (2019). Clonal Hematopoiesis: Crossroads of Aging, Cardiovascular Disease, and Cancer: JACC Review Topic of the Week. J Am Coll Cardiol 74, 567–577. 10.1016/J.JACC.2019.06.007.
Ito, S., Dalessio, A.C., Taranova, O. V., Hong, K., Sowers, L.C., and Zhang, Y. (2010). Role of Tet proteins in 5mC to 5hmC conversion, ES cell self-renewal, and ICM specification. Nature 466, 1129. 10.1038/NATURE09303.
Jaiswal, S., Natarajan, P., Silver, A.J., Gibson, C.J., Bick, A.G., Shvartz, E., McConkey, M., Gupta, N., Gabriel, S., Ardissino, D., et al. (2017). Clonal Hematopoiesis and Risk of Atherosclerotic Cardiovascular Disease. New England Journal of Medicine 377, 111–121. 10.1056/NEJMOA1701719/SUPPL_FILE/NEJMOA1701719_DISCLOSURES.PDF.
Abelson, S., Collord, G., Ng, S.W.K., Weissbrod, O., Mendelson Cohen, N., Niemeyer, E., Barda, N., Zuzarte, P.C., Heisler, L., Sundaravadanam, Y., et al. (2018). Prediction of acute myeloid leukaemia risk in healthy individuals. Nature 559, 400–404. 10.1038/s41586-018-0317-6.
Genovese, G., Kähler, A.K., Handsaker, R.E., Lindberg, J., Rose, S.A., Bakhoum, S.F., Chambert, K., Mick, E., Neale, B.M., Fromer, M., et al. (2014). Clonal Hematopoiesis and Blood-Cancer Risk Inferred from Blood DNA Sequence. New England Journal of Medicine. 10.1056/nejmoa1409405.
Xie, M., Lu, C., Wang, J., McLellan, M.D., Johnson, K.J., Wendl, M.C., McMichael, J.F., Schmidt, H.K., Yellapantula, V., Miller, C.A., et al. (2014). Age-related mutations associated with clonal hematopoietic expansion and malignancies. Nat Med. 10.1038/nm.3733.
Buscarlet, M., Provost, S., Zada, Y.F., Bourgoin, V., Mollica, L., Dubé, M.P., and Busque, L. (2018). Lineage restriction analyses in CHIP indicate myeloid bias for TET2 and multipotent stem cell origin for DNMT3A. Blood 132, 277–280. 10.1182/BLOOD-2018-01-829937.
He, Y.F., Li, B.Z., Li, Z., Liu, P., Wang, Y., Tang, Q., Ding, J., Jia, Y., Chen, Z., Li, N., et al. (2011). Tet-mediated formation of 5-carboxylcytosine and its excision by TDG in mammalian DNA. Science (1979). 10.1126/science.1210944.
Ito, S., Shen, L., Dai, Q., Wu, S.C., Collins, L.B., Swenberg, J.A., He, C., and Zhang, Y. (2011). Tet proteins can convert 5-methylcytosine to 5-formylcytosine and 5-carboxylcytosine. Science (1979). 10.1126/science.1210597.
Moran-Crusio, K., Reavie, L., Shih, A., Abdel-Wahab, O., Ndiaye-Lobry, D., Lobry, C., Figueroa, M.E., Vasanthakumar, A., Patel, J., Zhao, X., et al. (2011). Tet2 loss leads to increased hematopoietic stem cell self-renewal and myeloid transformation. Cancer Cell 20, 11–24. 10.1016/J.CCR.2011.06.001.
Quivoron, C., Couronné, L., Della Valle, V., Lopez, C.K., Plo, I., Wagner-Ballon, O., Do Cruzeiro, M., Delhommeau, F., Arnulf, B., Stern, M.H., et al. (2011). TET2 Inactivation Results in Pleiotropic Hematopoietic Abnormalities in Mouse and Is a Recurrent Event during Human Lymphomagenesis. Cancer Cell 20, 25–38. 10.1016/j.ccr.2011.06.003.
Ko, M., Bandukwala, H.S., An, J., Lamperti, E.D., Thompson, E.C., Hastie, R., Tsangaratou, A., Rajewsky, K., Koralov, S.B., and Rao, A. (2011). Ten-eleven-translocation 2 (TET2) negatively regulates homeostasis and differentiation of hematopoietic stem cells in mice. Proc Natl Acad Sci U S A 108, 14566–14571. 10.1073/PNAS.1112317108/-/DCSUPPLEMENTAL/PNAS.201112317SI.PDF.
Kunimoto, H., Fukuchi, Y., Sakurai, M., Sadahira, K., Ikeda, Y., Okamoto, S., and Nakajima, H. (2012). Tet2 disruption leads to enhanced self-renewal and altered differentiation of fetal liver hematopoietic stem cells. Scientific Reports 2012 2:1 2, 1–10. 10.1038/srep00273.
Sauvageau, G., Thorsteinsdottir, U., Eaves, C.J., Lawrence, H.J., Largman, C., Lansdorp, P.M., and Humphries, R.K. (1995). Overexpression of HOXB4 in hematopoietic cells causes the selective expansion of more primitive populations in vitro and in vivo. Genes Dev 9, 1753–1765. 10.1101/gad.9.14.1753.
Cusan, M., Vegi, N.M., Mulaw, M.A., Bamezai, S., Kaiser, L.M., Deshpande, A.J., Greif, P.A., Quintanilla-Fend, L., Göllner, S., Müller-Tidow, C., et al. (2017). Controlled stem cell amplification by HOXB4 depends on its unique proline-rich region near the N terminus. Blood. 10.1182/blood-2016-04-706978.
Ackloo, S., Brown, P.J., and Müller, S. (2017). Chemical probes targeting epigenetic proteins: Applications beyond oncology. Epigenetics. 10.1080/15592294.2017.1279371.
Yu, W., Chory, E.J., Wernimont, A.K., Tempel, W., Scopton, A., Federation, A., Marineau, J.J., Qi, J., Barsyte-Lovejoy, D., Yi, J., et al. (2012). Catalytic site remodelling of the DOT1L methyltransferase by selective inhibitors. Nat Commun. 10.1038/ncomms2304.
Stein, E.M., Garcia-Manero, G., Rizzieri, D.A., Tibes, R., Berdeja, J.G., Savona, M.R., Jongen-Lavrenic, M., Altman, J.K., Thomson, B., Blakemore, S.J., et al. (2018). The DOT1L inhibitor pinometostat reduces H3K79 methylation and has modest clinical activity in adult acute leukemia. Blood. 10.1182/blood-2017-12-818948.
Vigon, I., Mornon, J.P., Cocault, L., Mitjavila, M.T., Tambourin, P., Gisselbrecht, S., and Souyri, M. (1992). Molecular cloning and characterization of MPL, the human homolog of the v- mpl oncogene: Identification of a member of the hematopoietic growth factor receptor superfamily. Proc Natl Acad Sci U S A. 10.1073/pnas.89.12.5640.
Skoda, R.C., Seldin, D.C., Chiang, M.K., Peichel, C.L., Vogt, T.F., and Leder, P. (1993). Murine c-mpl: A member of the hematopoietic growth factor receptor superfamily that transduces a proliferative signal. EMBO Journal. 10.1002/j.1460-2075.1993.tb05925.x.
Takashima, S., Ishida, H.K., Inazu, T., Ando, T., Ishida, H., Kiso, M., Tsuji, S., and Tsujimoto, M. (2002). Molecular cloning and expression of a sixth type of alpha 2,8-sialyltransferase (ST8Sia VI) that sialylates O-glycans. J Biol Chem 277, 24030–24038. 10.1074/JBC.M112367200.
Sitnicka, E., Lin, N., Priestley, G. V., Fox, N., Broudy, V.C., Wolf, N.S., and Kaushansky, K. (1996). The Effect of Thrombopoietin on the Proliferation and Differentiation of Murine Hematopoietic Stem Cells. Blood 87, 4998–5005. 10.1182/BLOOD.V87.12.4998.BLOODJOURNAL87124998.
Yagi, M., Ritchie, K.A., Sitnicka, E., Storey, C., Roth, G.J., and Bartelmez, S. (1999). Sustained ex vivo expansion of hematopoietic stem cells mediated by thrombopoietin. Proc Natl Acad Sci U S A 96, 8126–8131. 10.1073/PNAS.96.14.8126.
Fox, N., Priestley, G., Papayannopoulou, T., and Kaushansky, K. (2002). Thrombopoietin expands hematopoietic stem cells after transplantation. J Clin Invest 110, 389–394. 10.1172/JCI15430.
Katayamaa, N., Itoh, R., Kato, T., Sugawara, T., Mahmud, N., Ohish, K., Masuya, M., Aoki, M., Minami, N., Miyazaki, H., et al. (1997). Role for C-MPL and its Ligand Thrombopoietin in Early Hematopoiesis. Leuk Lymphoma 28, 51–56. 10.3109/10428199709058330.
Yoshihara, H., Arai, F., Hosokawa, K., Hagiwara, T., Takubo, K., Nakamura, Y., Gomei, Y., Iwasaki, H., Matsuoka, S., Miyamoto, K., et al. (2007). Thrombopoietin/MPL signaling regulates hematopoietic stem cell quiescence and interaction with the osteoblastic niche. Cell Stem Cell 1, 685–697. 10.1016/J.STEM.2007.10.020.
Waters, N.J., Daigle, S.R., Rehlaender, B.N., Basavapathruni, A., Campbell, C.T., Jensen, T.B., Truitt, B.F., Olhava, E.J., Pollock, R.M., Stickland, K.A., et al. (2015). Exploring drug delivery for the DOT1L inhibitor pinometostat (EPZ-5676): Subcutaneous administration as an alternative to continuous IV infusion, in the pursuit of an epigenetic target. Journal of Controlled Release 220, 758–765. 10.1016/j.jconrel.2015.09.023.
Satija, R., Farrell, J.A., Gennert, D., Schier, A.F., and Regev, A. (2015). Spatial reconstruction of single-cell gene expression data. Nat Biotechnol 33, 495–502. 10.1038/NBT.3192.
Paul, F., Arkin, Y., Giladi, A., Jaitin, D.A., Kenigsberg, E., Keren-Shaul, H., Winter, D., Lara-Astiaso, D., Gury, M., Weiner, A., et al. (2015). Transcriptional Heterogeneity and Lineage Commitment in Myeloid Progenitors. Cell 163, 1663–1677. 10.1016/j.cell.2015.11.013.
Izzo, F., Lee, S.C., Poran, A., Chaligne, R., Gaiti, F., Gross, B., Murali, R.R., Deochand, S.D., Ang, C., Jones, P.W., et al. (2020). DNA methylation disruption reshapes the hematopoietic differentiation landscape. Nat Genet 52, 378–387. 10.1038/s41588-020-0595-4.
Xie, J., Sheng, M., Rong, S., Zhou, D., Wang, C., Wu, W., Huang, J., Sun, Y., Wang, Y., Chen, P., et al. (2023). STING activation in TET2-mutated hematopoietic stem/progenitor cells contributes to the increased self-renewal and neoplastic transformation. Leukemia 37, 2457–2467. 10.1038/s41375-023-02055-z.
Li, Z., Cai, X., Cai, C.L., Wang, J., Zhang, W., Petersen, B.E., Yang, F.C., and Xu, M. (2011). Deletion of Tet2 in mice leads to dysregulated hematopoietic stem cells and subsequent development of myeloid malignancies. Blood 118, 4509. 10.1182/BLOOD-2010-12-325241.
Kimura, S., Roberts, A.W., Metcalf, D., and Alexander, W.S. (1998). Hematopoietic stem cell deficiencies in mice lacking c-Mpl, the receptor for thrombopoietin. Proceedings of the National Academy of Sciences 95, 1195–1200. 10.1073/PNAS.95.3.1195.
Solar, G.P., Kerr, W.G., Zeigler, F.C., Hess, D., Donahue, C., De Sauvage, F.J., and Eaton, D.L. (1998). Role of c-mpl in early hematopoiesis. Blood 92, 4–10. 10.1182/blood.v92.1.4.413k38_4_10.
Ezumi, Y., Takayama, H., and Okuma, M. (1995). Thrombopoietin, c-Mpl ligand, induces tyrosine phosphorylation of Tyk2, JAK2, and STAT3, and enhances agonists-induced aggregation in platelets in vitro. FEBS Lett. 10.1016/0014-5793(95)01072-M.
Miyakawa, Y., Oda, A., Druker, B.J., Miyazaki, H., Handa, M., Ohashi, H., and Ikeda, Y. (1996). Thrombopoietin induces tyrosine phosphorylation of Stat3 and Stat5 in human blood platelets. Blood. 10.1182/blood.v87.2.439.bloodjournal872439.
Escamilla Gómez, V., García-Gutiérrez, V., López Corral, L., García Cadenas, I., Pérez Martínez, A., Márquez Malaver, F.J., Caballero-Velázquez, T., González Sierra, P.A., Viguria Alegría, M.C., Parra Salinas, I.M., et al. (2020). Ruxolitinib in refractory acute and chronic graft-versus-host disease: a multicenter survey study. Bone Marrow Transplant. 10.1038/s41409-019-0731-x.
O’Shea, J.J., Kontzias, A., Yamaoka, K., Tanaka, Y., and Laurence, A. (2013). Janus kinase inhibitors in autoimmune diseases. Ann Rheum Dis. 10.1136/annrheumdis-2012-202576.
Vainchenker, W., Leroy, E., Gilles, L., Marty, C., Plo, I., and Constantinescu, S.N. (2018). JAK inhibitors for the treatment of myeloproliferative neoplasms and other disorders. F1000Res 7. 10.12688/F1000RESEARCH.13167.1/DOI.
Gozgit, J.M., Bebernitz, G., Patil, P., Ye, M., Parmentier, J., Wu, J., Su, N., Wang, T., Ioannidis, S., Davies, A., et al. (2008). Effects of the JAK2 inhibitor, AZ960, on Pim/BAD/BCL-xL survival signaling in the human JAK2 V617F cell line SET-2. Journal of Biological Chemistry. 10.1074/jbc.M803813200.
Wernig, G., Kharas, M.G., Okabe, R., Moore, S.A., Leeman, D.S., Cullen, D.E., Gozo, M., McDowell, E.P., Levine, R.L., Doukas, J., et al. (2008). Efficacy of TG101348, a Selective JAK2 Inhibitor, in Treatment of a Murine Model of JAK2V617F-Induced Polycythemia Vera. Cancer Cell. 10.1016/j.ccr.2008.02.009.
Mascarenhas, J., and Hoffman, R. (2012). Ruxolitinib: The first FDA approved therapy for the treatment of myelofibrosis. Clinical Cancer Research. 10.1158/1078-0432.CCR-11-3145.
Ko, M., Bandukwala, H.S., An, J., Lamperti, E.D., Thompson, E.C., Hastie, R., Tsangaratou, A., Rajewsky, K., Koralov, S.B., and Rao, A. (2011). Ten-eleven-translocation 2 (TET2) negatively regulates homeostasis and differentiation of hematopoietic stem cells in mice. Proc Natl Acad Sci U S A 108, 14566–14571. 10.1073/PNAS.1112317108/SUPPL_FILE/PNAS.201112317SI.PDF.
Abegunde, S.O., Buckstein, R., Wells, R.A., and Rauh, M.J. (2018). An inflammatory environment containing TNFα favors Tet2-mutant clonal hematopoiesis. Exp Hematol 59, 60–65. 10.1016/J.EXPHEM.2017.11.002.
Feng, Y., Yang, Y., Ortega, M.M., Copeland, J.N., Zhang, M., Jacob, J.B., Fields, T.A., Vivian, J.L., and Fields, P.E. (2010). Early mammalian erythropoiesis requires the Dot1L methyltransferase. Blood. 10.1182/blood-2010-03-276501.
Nguyen, A.T., He, J., Taranova, O., and Zhang, Y. (2011). Essential role of DOT1L in maintaining normal adult hematopoiesis. Cell Res 21, 1370–1373. 10.1038/cr.2011.115.
Bernt, K.M., Zhu, N., Sinha, A.U., Vempati, S., Faber, J., Krivtsov, A. V., Feng, Z., Punt, N., Daigle, A., Bullinger, L., et al. (2011). MLL-Rearranged Leukemia Is Dependent on Aberrant H3K79 Methylation by DOT1L. Cancer Cell 20, 66–78. 10.1016/j.ccr.2011.06.010.
Kang, J.Y., Kim, J.Y., Kim, K.B., Park, J.W., Cho, H., Hahm, J.Y., Chae, Y.C., Kim, D., Kook, H., Rhee, S., et al. (2018). KDM2B is a histone H3K79 demethylase and induces transcriptional repression via sirtuin-1–mediated chromatin silencing. FASEB Journal 32, 5737–5750. 10.1096/fj.201800242R.
Warren, J.T., and Link, D.C. (2020). Clonal hematopoiesis and risk for hematologic malignancy. Blood 136, 1599–1605. 10.1182/BLOOD.2019000991.
Jaiswal, S. (2020). Clonal hematopoiesis and nonhematologic disorders. Blood 136, 1606–1614. 10.1182/BLOOD.2019000989.
Bolton, K.L., Ptashkin, R.N., Gao, T., Braunstein, L., Devlin, S.M., Kelly, D., Patel, M., Berthon, A., Syed, A., Yabe, M., et al. (2020). Cancer therapy shapes the fitness landscape of clonal hematopoiesis. Nature Genetics 2020 52:11 52, 1219–1226. 10.1038/s41588-020-00710-0.
Dorsheimer, L., Assmus, B., Rasper, T., Ortmann, C.A., Ecke, A., Abou-El-Ardat, K., Schmid, T., Brüne, B., Wagner, S., Serve, H., et al. (2019). Association of Mutations Contributing to Clonal Hematopoiesis With Prognosis in Chronic Ischemic Heart Failure. JAMA Cardiol 4, 25–33. 10.1001/JAMACARDIO.2018.3965.
Jaiswal, S., Natarajan, P., Silver, A.J., Gibson, C.J., Bick, A.G., Shvartz, E., McConkey, M., Gupta, N., Gabriel, S., Ardissino, D., et al. (2017). Clonal Hematopoiesis and Risk of Atherosclerotic Cardiovascular Disease. New England Journal of Medicine. 10.1056/nejmoa1701719.
Jaiswal, S., and Libby, P. (2020). Clonal haematopoiesis: connecting ageing and inflammation in cardiovascular disease. Nat Rev Cardiol 17, 137–144. 10.1038/S41569-019-0247-5.

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TET2 Deficiency Increases the Competitive Advantage of Hematopoietic Stem Cells through Upregulation of Thrombopoietin Receptor Signaling

Status:

Version 1

Abstract

Figures

INTRODUCTION

RESULTS

TET2-deficient HSPCs are dependent on thrombopoietin receptor signaling to maintain their competitive advantage

Inhibition of TPO-R/JAK2 signaling reduces the competitive advantage of murine and human TET2-deficient HSPCs

DISCUSSION

LIMITATIONS OF THE STUDY

MATERIALS AND METHODS

Mouse models

Generation of the HPC^HOXB4cell models

Human mobilized peripheral blood (mPB) samples

Human cord blood samples

Tissue culture

Lentivirus production and transduction

Generation of Venus^‒ cells using CRISPR/Cas9

Chemical library screen

Flow cytometry

Intracellular flow cytometry

EdU proliferation assay

Colony-forming unit (CFU) assays

RNA-sequencing analysis

Chromatin-immunoprecipitation sequencing (ChIP-seq) analysis

RT-qPCR

ChIP-qPCR

Single-cell RNA (scRNA) sequencing

Western blot

Droplet digital PCR (ddPCR)

Peripheral blood chimerism analysis

Statistical analysis

DECLARATIONS

REFERENCES

Additional Declarations

Supplementary Files

Status:

Version 1

TET2 Deficiency Increases the Competitive Advantage of Hematopoietic Stem Cells through Upregulation of Thrombopoietin Receptor Signaling

Status:

Version 1

Abstract

Figures

INTRODUCTION

RESULTS

TET2-deficient HSPCs are dependent on thrombopoietin receptor signaling to maintain their competitive advantage

Inhibition of TPO-R/JAK2 signaling reduces the competitive advantage of murine and human TET2-deficient HSPCs

DISCUSSION

LIMITATIONS OF THE STUDY

MATERIALS AND METHODS

Mouse models

Generation of the HPCHOXB4 cell models

Human mobilized peripheral blood (mPB) samples

Human cord blood samples

Tissue culture

Lentivirus production and transduction

Generation of Venus‒ cells using CRISPR/Cas9

Chemical library screen

Flow cytometry

Intracellular flow cytometry

EdU proliferation assay

Colony-forming unit (CFU) assays

RNA-sequencing analysis

Chromatin-immunoprecipitation sequencing (ChIP-seq) analysis

RT-qPCR

ChIP-qPCR

Single-cell RNA (scRNA) sequencing

Western blot

Droplet digital PCR (ddPCR)

Peripheral blood chimerism analysis

Statistical analysis

DECLARATIONS

REFERENCES

Additional Declarations

Supplementary Files

Status:

Version 1

Generation of the HPC^HOXB4cell models

Generation of Venus^‒ cells using CRISPR/Cas9