Kerstin B Kaufmann

Andy G X Zeng

Etienne-Marie Coyaud

Laura Garcia-Prat

Efthymia Papalexi

Alex Murison

Estelle M N Laurent

Michelle Chan-Seng-Yue

Olga I Gan

Kristele Pan

Jessica Mcleod

Héléna Boutzen

Sasan Zandi

Shin-Ichiro Takayanagi

Rahul Satija

Brian Raught

Stephanie Z Xie

John E Dick
email: john.dick@uhnresearch.ca

A latent subset of human hematopoietic stem cells resists regenerative stress to preserve stemness

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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Extended Data Fig. 1 INKA1 and H4K16ac are mutually exclusive. (b-e) Single cell RNA-seq data from CD34 + CD38 - CD45RA -index-sorted mPB HSC (n=3, also stained and indexed for CD49f, CD90) visualized by diffusion mapping overlaid with (b) cell cycle score (Tirosh et al., 2016) and indicated transcript expression; (c) donor origin, (d) ITGA (CD49f) transcript expression, (e) CD49f and CD90 indexed protein surface expression and (f) retrospectively gated HSC subsets (LT-, IT90 + , IT90 -, ST-HSC). Extended Data Fig. 3 Protein single cell pseudotime analysis. (e) Individual cell fluorescence intensities (IntDen) of nuclear CDK6, H4K16ac, PAK4 and DAPI across pseudotime for HSC subsets (n=2913). Curve fit was performed with nonlinear regression excluding 1-2% of outliers (fifth order polynomial). (f) Pseudotime was split in early, mid and late fractions to visualize distribution of HSC subsets and Progenitors and marker levels across these fractions for all 3442 cells (histograms) or per population and CB (n=2-3, bar plots). Single cell distribution for each population across pseudotime is also shown in horizontal violin plot. Mean±SD, two sided t-test (compared to "early"; *p<0.05; **p<0.01; ***p<0.001).

Extended Data Fig. 4 Pharmacological PAK4 inhibition. Kaufmann_Extende d_Data_Fig4.tif (a) Brightfield images of HSPC (CD34 + CD38 -) and Progenitors (CD34 + CD38 + ) after 5 d treatment with either DMSO or PF-3758309, reproducible across all independent repetitions (n>9). scale bar = 100 µm.

(b-e) CB Lin -cells were treated after 2d of prestimulation with either DMSO or PF-3758309 (PF). Concentration as indicated. After 5d of treatment cells were counted (c, n=2), cell cycle (b, d) combined with CD34 analysis was performed (pool of n=2).

(f-g) CB Lin -cells treated after 2 days prestimulation for 5 d with 0.25 uM PF-3758309 or DMSO equivalent were subjected to AnnexinV and CD34 staining (n=3-4).

Mean±SD; two-sided ratio paired t-test.

(h-j) CB HSPC and Progenitors treated for 4 and 6 d with 0.25 uM PF-3758309 or DMSO equivalent were subjected to cell cycle analysis (h), counting (i: HSPC; j: Progenitors). Mean±SD, two-sided paired t-test (*p<0.05; **p<0.01; ***p<0.001).

(k) Cell counts of treated HSPC on day of injection (d5 treatment, d7 culture). Mean±SD.

(l) Secondary LDA (8 wk) in NSG and NSG-SGM3 mice of human CD45 + cells from CB Lin -cells transplanted NSG grafts (24 wk). Extended Data Fig. 5 INKA1-OE mediated effects in vitro.

INTRODUCTION

Continuous and life-long blood cell production hinges on the ability of rare multipotent LT-HSCs to balance two fundamental stem cell properties: self-renewal versus capacity to generate differentiated progeny. This balance ensures not only continuous hematopoietic output but also long-term maintenance of the LT-HSC pool. Maintenance occurs because HSC reside predominantly in a quiescent state that can last for weeks to years before intrinsic and extrinsic cues activate some LT-HSC to either self-renew or generate short-term (ST-)HSC, while others remain restrained in quiescence [START_REF] Bernitz | Hematopoietic Stem Cells Count and Remember Self-Renewal Divisions[END_REF][START_REF] Scala | Dynamics of genetically engineered hematopoietic stem and progenitor cells after autologous transplantation in humans[END_REF][START_REF] Laurenti | CDK6 levels regulate quiescence exit in human hematopoietic stem cells[END_REF] . However, serial challenges, such as transplantation or inflammation, can lead to HSC attrition, exhaustion and biases in lineage output manifesting as cytopenias, late graft failure following HSC transplantation and compromised immune function upon aging [START_REF] Takizawa | Pathogen-Induced TLR4-TRIF Innate Immune Signaling in Hematopoietic Stem Cells Promotes Proliferation but Reduces Competitive Fitness[END_REF][5][START_REF] Muller | The Immune System and Its Dysregulation with Aging[END_REF] . Understanding in vivo HSC dynamics and the mechanisms that ensure HSC longevity on a molecular, cellular and population level is crucial for enabling cell therapies that permit both rapid regeneration and sustained long-term hematopoiesis.

Although murine studies provided considerable insights into cellular and molecular mechanisms of HSC quiescence, poor understanding remains how quiescence control integrates with the fate decisions HSCs must make to either remain quiescent, differentiate and/or self-renew [START_REF] Cabezas-Wallscheid | Vitamin A-Retinoic Acid Signaling Regulates Hematopoietic Stem Cell Dormancy[END_REF][START_REF] Rodriguez-Fraticelli | Single-cell lineage tracing unveils a role for TCF15 in haematopoiesis[END_REF] . In humans, the longer lifespan and massively higher cellular output make dynamic integration of these fundamental stem cell properties even more acute. We particularly lack understanding of the processes underlying the activation and/or resistance of human HSC to adapt to varying hematopoietic demands during homeostasis or emergency hematopoiesis triggered by inflammation, acute blood loss or transplantation. Although human immunophenotypic CD90 + CD49f -LT-and CD90 -CD49f -ST-HSCs are both multipotent and possess engraftment capacity, ST-HSCs have markedly reduced self-renewal potential and faster quiescence exit kinetics [START_REF] Laurenti | CDK6 levels regulate quiescence exit in human hematopoietic stem cells[END_REF][START_REF] Notta | Isolation of single human hematopoietic stem cells capable of long-term multilineage engraftment[END_REF] . Despite these functional differences between human LT-and ST-HSC subsets, published studies have not uncovered clear transcriptomic differences at the population level or by single cell (sc)RNA-seq and instead pointed to the continuous nature of early hematopoietic commitment [START_REF] Velten | Human haematopoietic stem cell lineage commitment is a continuous process[END_REF][START_REF] Laurenti | The transcriptional architecture of early human hematopoiesis identifies multilevel control of lymphoid commitment[END_REF] .

Functional screens offer an alternative approach to identify mechanisms that distinguish LT-HSC from ST-HSC. As normal HSC and leukemia stem cells (LSC) in acute myeloid leukemia (AML) share many similarities in stemness properties, we recently undertook a functional stemness screen of potential LSC regulators. We revealed INKA1 (also known as FAM212A, C3orf54) as a regulator of LSC self-renewal [START_REF] Kaufmann | A stemness screen reveals C3orf54/INKA1 as a promoter of human leukemia stem cell latency[END_REF] .

This study linked human LSC quiescence and latency to INKA1-mediated inhibition of p21(Cdc42/Rac)activated kinase 4 (PAK4) and to reduction of H4K16 acetylation (H4K16ac). However, this signaling axis was not studied in normal hematopoiesis. PAK4 plays a role in numerous cellular functions [START_REF] Dart | P21-activated kinase 4--not just one of the PAK[END_REF] and only a single study in human cell lines and a limited number of studies in frogs, fish and mice established that Inka1 is an endogenous inhibitor of Pak4 and essential for neural crest development [START_REF] Baskaran | An in cellulo-derived structure of PAK4 in complex with its inhibitor Inka1[END_REF][START_REF] Luo | Inca: a novel p21-activated kinase-associated protein required for cranial neural crest development[END_REF] . H4K16ac is associated with activated transcription of single genes, but this chromatin mark is not strongly correlated with changes in global gene expression as assessed in HeLa cells and murine HSC [START_REF] Grigoryan | LaminA/C regulates epigenetic and chromatin architecture changes upon aging of hematopoietic stem cells[END_REF][START_REF] Mcbrian | Histone acetylation regulates intracellular pH[END_REF] . Here, we uncovered a mechanistic link between PAK4 and H4K16ac, and its role in human hematopoiesis, demonstrating that a molecular network with INKA1 at its center governs the long-term regenerative capacity of human HSC. Moreover, we show that human LT-HSC are not homogeneous but composed of two cellular entities distinguished on the basis of CD112 expression, each with distinct alternative states of quiescence and repopulation kinetics.

RESULTS

INKA1 and H4K16ac delineated HSC heterogeneity

To explore the relevance of INKA1 and PAK4 in normal human hematopoiesis, we first interrogated published RNA expression datasets 18,[START_REF] Xie | Sphingolipid Modulation Activates Proteostasis Programs to Govern Human Hematopoietic Stem Cell Self-Renewal[END_REF] . INKA1 was highly expressed in HSC and progenitor enriched CD34 + cells compared to mature CD34 -populations, whereas PAK4 showed low expression across the hematopoietic hierarchy (Fig. 1a). Analysis of protein expression and chromatin acetylation by confocal analysis of four CD34 + CD38 -CD45RA -HSC subsets sub-fractionated by CD90/CD49f expression from cord blood (CB) showed heterogeneity in INKA1 and H4K16ac abundance at single-cell resolution. The majority of cells (85.5±8.2%) in these four populations were high in H4K16ac with low to background signals for nuclear INKA1 (INKA1 lo ; Fig. 1b-d and Extended Data Fig. 1a-c). Cells with concomitant faint staining for both markers further revealed intranuclear spatial separation when analyzed after conversion into binary images (Extended Data Fig. 1c) suggesting these cells were in transition to either becoming INKA1 hi or H4K16ac hi and that these molecules actively excluded one another. High nuclear signal for INKA1 (INKA1 hi ) was detected in a minor population (10-20%) with small nuclear diameter and low or negative staining for H4K16ac (Fig. 1e and Extended Data Fig. 1d). To determine if INKA1 hi cells were in an alternative state of stem cell quiescence, we used CDK6 as a definitive marker of the activated/poised stem cell state [START_REF] Laurenti | CDK6 levels regulate quiescence exit in human hematopoietic stem cells[END_REF] and compared INKA1 versus CDK6 content in LT-and ST-HSCs .

Immunofluorescence analysis of LT-HSCs showed that INKA1 hi cells had significantly lower CDK6 protein abundance than INKA1 lo cells; differences not seen in ST-HSCs (Fig. 1f and Extended Data Fig. 1e). Hence, the inverse nuclear staining patterns of INKA1 and H4K16ac delineated at least two distinct populations within LT-HSCs that might be linked to alternative states of stem cell quiescence.

INKA1 and CDK6/PAK4 segregated quiescent single cells

To gain more insight into the heterogeneous subpopulations within the LT-HSC pool and determine whether they varied in stem cell activation signatures, we undertook single-cell transcriptomic analysis of HSCs from granulocyte-colony-stimulating factor (G-CSF)-mobilized peripheral blood (mPB). Since mPB cells are activated to exit the bone marrow in vivo, we hypothesized that they may result in improved transcriptional resolution of HSC activation dynamics. We confirmed that 95.7±2.9% of CD34 + CD38 -CD45RA HSCs from mPB were in G0 (Ki67 -, Extended Data Fig. 2a) and that phenotypically defined LT-and ST-HSCs recapitulated the differences in CDK6 protein abundance as previously described for CB (Fig. 2a) [START_REF] Laurenti | CDK6 levels regulate quiescence exit in human hematopoietic stem cells[END_REF] . Flow cytometric detection of CDK6 further partitioned Ki67 -G0 cells into canonically quiescent (CDK6 -) and primed (CDK6 + ) fractions (47.8±14.2%; Fig. 2b).

Single-cell index-sorting (signals indexed: CD34, CD38, CD45RA, CD90, CD49f) followed by full-length transcript scRNA-seq of CD34 + CD38 -CD45RA -mPB cells (from 3 donors) generated 1191 single-cell transcriptomes. To identify a trajectory of HSC activation, we applied diffusion pseudotime analysis while leveraging predictions of future cell states through RNA Velocity [START_REF] Manno | RNA velocity of single cells[END_REF][START_REF] Haghverdi | Diffusion pseudotime robustly reconstructs lineage branching[END_REF] (Fig. 2c and Extended Data Fig. 2b-f). We observed a gradual increase in CDK6 expression as well as cell cycle programs [START_REF] Tirosh | Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq[END_REF] from early to late pseudotime, confirming that we captured the transition from canonically quiescent to activated/poised HSC. Superimposing INKA1 and PAK4 expression onto the diffusion map revealed that the highest INKA1 expression occurred early in pseudotime and thereafter declined, while PAK4 expression increased late in pseudotime (Fig. 2d and Extended Data Fig. 2b). Despite early enrichment of ITGA6 transcripts (encoding CD49f), surface expression of CD49f and CD90 was homogenous across pseudotime, implying that all 4 HSC subsets followed the same trajectory of activation (Extended Data Fig. 2d-f). Collectively, these data established that LT-HSCs with high INKA1 are CDK6 lo and fall on the non-primed end of the quiescence spectrum.

H4K16ac and PAK4 demarcated HSC cell cycle activation

To examine whether H4K16ac and PAK4 played a role in HSC cell cycle priming, we interrogated cell cycle (Ki67) and H4K16ac status after cytokine stimulation by flow cytometry in lineage-depleted CB cells (CB Lin -) and by immunostaining in LT-and ST-HSCs (also including PAK4).

H4K16ac was significantly lower in CB Lin -cells remaining in G0 following cytokine exposure as compared to those that progressed into cell cycle. The signal peaked in late S-phase and subsequently declined in G2/M phase (Fig. 2e,f and Extended Data Fig. 3a). In agreement, higher abundance of H4K16ac and PAK4 were observed in Ki67 hi vs. Ki67 lo LT-and ST-HSCs (Fig. 2g and Extended Data Fig. 3b,c) suggesting upregulation upon cell cycle entry. To further resolve the longitudinal dynamics of H4K16ac and PAK4 expression during quiescence exit and entry into the first cell cycle of the most primitive HSC subsets, we performed multi-timepoint (6-100 h) single-cell protein imaging analysis under high-cytokine culture conditions. We used CDK6 as a G0 exit marker 3 and CD34 + CD38 + progenitors were used as an activated control. We observed a significant increase in the signal intensities for CDK6, PAK4 and H4K16ac at late timepoints (66 and 100 h) when compared to 6 hrs for both LTand ST-HSCs. However, LT-HSCs showed an overall lower CDK6 abundance than ST-HSC at 66 hrs in accordance with the expected delay in upregulation of CDK6 3 (Fig. 2h and Extended Data Fig. 3d). We captured a similar delay of PAK4 and H4K16ac upregulation in LT-HSCs as compared to ST-HSC.

To account for the asynchronous cell cycle priming and progression in the imaging study, we applied diffusion pseudotime analysis [START_REF] Haghverdi | Diffusion pseudotime robustly reconstructs lineage branching[END_REF] to our multidimensional single-cell protein imaging data (6 parameters: nuclear intensity for H4K16ac, CDK6, PAK4, DAPI; total cell intensity for CDK6, PAK4; n= 3454 cells). This method ordered single cells according to their phenotype independently of the actual timepoint harvested. Accordingly, at all timepoints of analysis CD34 + CD38 + progenitors as well as HSCs from all four CD34 + CD38 -CD45RA -subsets intermixed along the generated pseudotime trajectory that showed gradual upregulation of CDK6, H4K16ac and PAK4 along with DAPI/DNA intensity (Fig. 2i and Extended Data Fig. 3e,f). LT-HSCs were enriched earlier in pseudotime, in accordance with their known delayed cell cycle entry, whereas activated progenitor cells were skewed towards the late end of the trajectory (Extended Data Fig. 3f) [START_REF] Laurenti | CDK6 levels regulate quiescence exit in human hematopoietic stem cells[END_REF] . The upregulation of PAK4 protein abundance and H4K16 acetylation preceded the upregulation of CDK6 in this single cell immunofluorescence-based pseudotime analysis (Fig. 2i). Overall, these data suggested that PAK4 and H4K16ac might indicate early cell-cycle priming and progression in HSCs.

PAK4-inhibition induced G0 maintains regenerative potential

As INKA1 is an endogenous PAK4 inhibitor, we used pharmacological inhibition to obtain independent evidence that cell cycle progression depended on PAK4 activity. Such drug studies are difficult to undertake on highly purified HSC subpopulations so we used combined hematopoietic stem and progenitor cells (HSPC) subsets. Treatment of cytokine-stimulated CB CD34 + CD38 -HSPC and CD34 + CD38 + progenitors for 5 days with the PAK4 inhibitor PF-3758309, known to compete with INKA1 [START_REF] Baskaran | An in cellulo-derived structure of PAK4 in complex with its inhibitor Inka1[END_REF] , resulted in a dose-dependent reduction of cell expansion along with an accumulation of G0 cells (Ki67 -; Fig. 3a,b and Extended Data Fig. 4a-d). Cell viability was only mildly reduced and CD34 surface expression was retained (Extended Data Fig. 4e-g). PF-3758309 treatment without prior cytokine-stimulation had similar effects on cell counts and cell cycle (Extended Data Fig. 4h-j). Ex vivo treatment with PF-3758309 followed by limiting-dilution xenograft assays (LDA) in primary engrafted NSG mice did not demonstrate any change in HSC frequency or lineage output compared to DMSO controls (n=6; Fig. 3c,d and Extended Data Fig. 4k). Subsequently, HSC frequency in 4 of the 6 primary xenograft cohorts was assessed by serial LDA using human cytokine (SCF, GM-CSF, IL3) expressing NSG-SGM3 mice as a more sensitive secondary recipient as demonstrated by direct comparison with NSG mice (Extended Data Fig. 4l). We found a trend towards a 2.0-fold increase in HSC frequency following initial PAK4 inhibitor treatment (p=0.071, Fig. 3e,f). These results suggested that PAK4 inhibition transiently stalled cytokine-stimulated HSPC in G0 thereby maintaining their stem cell regenerative capacity.

INKA1-OE conferred selective resistance to activation

INKA1-OE and PAK4-KD transiently restrained repopulation

To directly test the functional impact that INKA1-OE might have on the in vivo properties of HSCs we utilized the xenograft assay. We previously observed that INKA1-OE in CB CD34 + CD38 - HSPCs induced delayed repopulation, indicative of a transient proliferative disadvantage of the transduced (BFP + ) fraction at the 4 wk timepoint that is overcome by 20 wk 12 . To explore the effects of INKA1 on stemness maintenance and activation, we carried out a more detailed analysis of CB HSPCs transduced with INKA1-OE or control vectors using serial xenotransplantation assays. We observed no differences in relative engraftment in the injected femurs at 2 wk (Fig. 5a and Extended Data Fig. 7a-c), whereas INKA1-OE resulted in a relative reduction of 4-fold (log2BFPratio=2) of gene-marked (BFP + ) cells at 4 wk, a timepoint when the majority of LT-HSCs are normally activated and cycling [START_REF] Laurenti | CDK6 levels regulate quiescence exit in human hematopoietic stem cells[END_REF] .

Examination of primary xenografts at 20 wk showed that the relative engraftment was comparable in both groups with no overt lineage skewing (Extended Data Fig. 7d). Secondary transplantation into NSG-SGM3 recipients was used to model successive rounds of stem cell activation and forced stress hematopoiesis due to the increased human pro-inflammatory cytokine exposure in NSG-SGM3 mice.

When 2 wk primary samples were transplanted, only INKA1-OE cells engrafted (Fig. 5b). Similarly, INKA1-OE cells isolated from 4 wk primary xenografts generated grafts in all secondary recipients, indicative of self-renewal, while only half of control recipients were engrafted (Fig. 5b). Analysis of 20 wk primary xenografts revealed a dissociation between HSC function and immunophenotype, the INKA1-OE group had a 3.6-fold reduction of phenotypic LT-HSCs but a 4.5-fold increase in the frequency of functional HSCs as measured by serial LDA, as compared to controls (Fig. 5b-e and Extended Data Fig. 7e). Collectively, these data indicated that the transient restraint induced by INKA1-OE at early timepoints allowed them to retain their self-renewal and regenerative capacity at later timepoints despite their exposure to regeneration-mediated stress.

As INKA1-OE cells exhibited transient restraint during regeneration, we investigated whether the restrained HSCs were cycling more slowly in vivo. Xenotransplanted NSG mice were treated after 4 weeks of repopulation with 5-Fluorouracil (5-FU), a treatment known to deplete proliferating cells while inducing quiescent HSCs to become activated [START_REF] Randall | Phenotypic and functional changes induced at the clonal level in hematopoietic stem cells after 5-fluorouracil treatment[END_REF] . A single dose of 5-FU resulted in higher total CD45 + and BFP + cells counts in the INKA1-OE group at the 12-wk timepoint and a slight decline at 20 wk compared to 5-FU treated controls (Fig. 5e and Extended Data Fig. 7g,h). There was an expansion of the phenotypic HSC compartment of 5-FU treated, INKA1-OE mice, but depletion in control groups (Fig. 5f and Extended Data Fig. 7i). Serial LDA analysis showed higher HSC frequency within 5-FU versus PBStreated INKA1-OE grafts, while repopulation in 5-FU treated control groups was abolished (Fig. 5g,h). 5i and Extended Data Fig. 7j). Upon secondary transplantation, the residual cells harvested at 20 wk and injected at the same cell doses performed as poorly as controls (Fig. 5j). By contrast, both of the PAK4-KD groups recapitulated the INKA1-OE phenotype, showing delayed repopulation in primary xenograft assays and increased HSC frequency upon secondary transplantation, with the shPAK4-3 cohort showing a 7.6-fold increase (Fig. 5i,j and Extended Data Fig. 7k). PAK4-KD resulted in a higher abundance of lymphoid cells at the expense of myeloid and erythroid cells at 20 wk (Extended Data Fig. 7l). This result contrasts with the balanced output generated upon INKA1-OE, further implicating an additional INKA1 function beyond simply inhibiting PAK4. Collectively, INKA1-OE or PAK4-KD induced a reversible restraint of hematopoietic output that was coincident with enhancement of their long-term self-renewal and regenerative potential.

Interactome linked INKA1 via SIRT1 to H4K16 deacetylation

To gain further mechanistic insight into how INKA1 and PAK4 function and how they are linked to H4K16 acetylation, we studied their broader interactome via proximity-dependent biotin labelling (BioID) [START_REF] Coyaud | Global Interactomics Uncovers Extensive Organellar Targeting by Zika Virus[END_REF] . We generated inducible N-and C-terminal BirA* (BirA R118G)-fusions for both proteins. 87 high confidence interactors were identified that were either biotinylated by INKA1 fusions only (34), PAK4 fusions only (30), or both (23)(Fig. 6a, Supplementary Table 1). The transcripts of the majority of these retrieved proteins were also found highly expressed in CB LT-/ST-HSCs (GSE125345; Fig. 6a and Extended Data Fig. 8a).

Pathway enrichment analysis of the interactome confirmed enrichment for GTPase signaling, cell polarity, protein localization, signal transduction, cell cycle and regulation of lysine acetylation (Extended Data Fig. 8b). One of the INKA1 interactors was the NAD + -dependent deacetylase SIRT1, a known regulator of many biological processes that functions through targeting H4K16ac [START_REF] Chen | Quantitative acetylome analysis reveals the roles of SIRT1 in regulating diverse substrates and cellular pathways[END_REF] and other histone and non-histone proteins for deacetylation. We confirmed nuclear and cytoplasmic INKA1 interaction with SIRT1 in CB CD34 + CD38 -cells (Fig. 6b and Extended Data Fig. 8c). Staining of chromatin fibers from CD34 + CD38 -cells further confirmed chromatin association of SIRT1 and INKA1 that was inverse to H4K16ac (Extended Data Fig. 8d). INKA1-OE in CD34 + CD38 -cells showed increased relative redistribution of SIRT1 into the nucleus, while pharmacological SIRT1 inhibition with EX-527 accelerated DNA synthesis and partly rescued reduced EdU incorporation upon INKA1-OE (Fig. 6c and Extended Data Fig. 8e). Thus, the interaction of INKA1 with SIRT1 provided an explanation both for the

INKA1/PAK4 interactome identified CD112 as an HSPC marker

Among other high confidence INKA1/PAK4 interactors we found an adhesion and immune regulatory molecule, CD112 (PVRL2, Nectin-2; Fig. 6a) and a protein connecting Nectins to the actin cytoskeleton, MLLT4 (Afadin). Nectin2 (transcript for CD112) and Afadin showed a very distinct HSC/HSPC-specific transcript expression pattern (Extended Data Fig. 9a,b). CD112 and CD34 exhibited similar surface expression on CB mononuclear cells (MNC) although CD112 did not capture lymphoidprimed CD19 + CD34 + cells (Fig. 6d,e and Extended Data Fig. 9c,d). Across the CD34 + hierarchy, CD112 and CD34 expression was consistently higher in the more primitive fractions, with the exception of lymphoid-primed progenitors (MLP), which was CD112 lo CD34 hi (Extended Data Fig. 9e). In stromal differentiation assays we observed no lineage restriction for single cells (CD34 + CD38 -CD45RA -) with either low or high CD112 expression according to initial index-sorting (Extended Data Fig. 9f,g).

To validate the BioID results, we tested the impact of INKA1-OE on surface expression of CD112. INKA1-OE reduced CD112 surface expression on culture-derived LT-HSCs (cLT-HSCs) [START_REF] Xie | Sphingolipid Modulation Activates Proteostasis Programs to Govern Human Hematopoietic Stem Cell Self-Renewal[END_REF] and cST-HSCs, although total protein abundance was not altered (Fig. 6f and Extended Data Fig. 9h,i). We captured individual cST-HSCs with extremely high intracellular CD112 that were almost exclusive to INKA1-OE suggesting induction of receptor internalization (Extended Data Fig. 9i). Using the late endosome/lysosome marker LAMP1, we confirmed cytoplasmic colocalization with CD112 and INKA1 in LT-and ST-HSCs (Extended Data Fig. 9j). Extracellular CD112 immunostaining indicated that cells with high expression of CD112 on the surface are INKA1 lo and vice versa (Fig. 6g). Finally, our scRNAseq pseudotime analysis provided independent support for this inverse relationship; INKA1 expression was enriched early and CD112/Nectin2 was enriched late in pseudotime (Fig. 6h). Together, these data support a direct functional connection between INKA1 and CD112 and predict that they may mark alternative states of stem cell quiescence, with primed LT-HSCs being INKA1 lo and CD112/Nectin2 hi .

CD112 hi /CD112 lo marked alternative states of LT-HSCs

To determine if the relative abundance of CD112 can discriminate primed (high in CDK6 and H4K16ac) from non-primed (INKA1 hi ) cells, we sorted CD112 hi and CD112 lo cell fractions from purified LT-HSC and ST-HSC populations, that are >90% in G0 [START_REF] Laurenti | CDK6 levels regulate quiescence exit in human hematopoietic stem cells[END_REF] (Fig. 7a and Extended Data Fig. 10a,b). Cell cycle analysis revealed that the CD112 hi LT-HSC fraction had less non-primed (%CDK6 lo Ki67 -) cells and less cells in G0 vs. CD112 lo LT-HSCs (91.1±5.3% vs. 95.9±2.2% Ki67 -; Fig. 7b and Extended Data Fig. 10c). These differences were still evident upon short-term culture (42 hrs; Extended Data Fig. 10c,d). In accordance, CD112 hi LT-HSCs exhibited the highest acetylation of H4K16 and the lowest proportion of INKA1 hi cells compared to the other 3 populations, whereas CD112 lo LT-HSCs showed the highest INKA1 abundance (Fig. 7c,d and Extended Data Fig. 10e). No significant differences were seen between CD112 hi and CD112 lo ST-HSCs for all parameters assessed (Fig. 7b-e and Extended Data Fig. 10e-g).

These data suggest that CD112 enables prospective enrichment of LT-HSCs in alternative states of quiescence in a context specific manner reminiscent of the LT-HSC specific phenotypes induced by

INKA1-OE.

Quiescent LT-HSCs generate energy preferentially by glycolysis, in contrast to activated HSPC that rely on oxidative phosphorylation that yields reactive oxygen species (ROS) 5 . CD112 hi LT-HSC and both ST-HSC-derived populations showed similar ROS signals (CellROX; Fig. 7e and Extended Data 10f,g). By contrast CD112 lo LT-HSCs produced less ROS indicating that CD112 lo LT-HSCs are also metabolically less primed for activation. We have recently established chromatin accessibility signatures of quiescent (LT/HSPC signature) vs. activated states (Act/HSPC signature) of human HSPCs [START_REF] Takayama | The Transition from Quiescent to Activated States in Human Hematopoietic Stem Cells Is Governed by Dynamic 3D Genome Reorganization[END_REF] . We generated chromatin accessibility signatures of CD112 hi and CD112 lo LT-HSCs by ATAC-seq and projected them onto our published single cell ATAC-seq data from CB HSPCs [START_REF] Takayama | The Transition from Quiescent to Activated States in Human Hematopoietic Stem Cells Is Governed by Dynamic 3D Genome Reorganization[END_REF] . The CD112 lo signature was highly concordant with the LT/HSPC signature and inversely correlated with the Act/HSPC signature (Fig. 7f,g and Extended Data Figure 10h,i). By contrast, the more primed, CD112 hi population generated an epigenetic signature that overlapped with both established signatures. Hence, CD112 surface expression also delineated alternative chromatin states within quiescent LT-HSCs. These distinct states were also revealed from GSEA of RNA-seq data comparing CD112 hi and CD112 lo LT-HSC. CD112 hi LT-HSC upregulated several prototypical stem cell response pathways that were downregulated in LT-HSC upon INKA1-OE (Extended Data Fig. 10j) or included mTORC1 signaling (Fig. 7h) [START_REF] Rodgers | mTORC1 controls the adaptive transition of quiescent stem cells from G0 to G(Alert)[END_REF] . Overall, we retrieved 289 differentially expressed genes between these two distinctly quiescent LT-HSC subsets (Fig. 7i and Supplementary Table 2). Further GSEA analysis revealed that CD112 lo cells were enriched for the highly interconnected biological processes of cell adhesion, cytoskeleton regulation and GTPase signaling (Fig. 7j and Extended Data Fig. 10k,l). In summary, fractionation of LT-HSCs on the basis of CD112 expression identified pre-existing, molecularly-distinct subsets that fall on opposite ends of the quiescence spectrum, thereby revealing previously undescribed heterogeneity within the LT-HSC subset.

CD112 lo captured LT-HSC with delayed repopulation kinetics

To determine whether the quiescence-associated phenotype of CD112 lo LT-HSCs is functional and associated with delayed activation and post-transplant stem cell latency similar to what was observed with INKA1-OE, we assessed the repopulation kinetics of CD112 hi and CD112 lo LT-HSCs from 3 CB pools. Human CD45 chimerism in mouse cohorts transplanted with CD112 lo LT-HSCs tended to be lower than that of their CD112 hi LT-HSC-transplanted counterparts at 4 wk (p=0.102; Fig. 8a,b) and reaching significance at 12 wk (p=0.041). The percentage of CD45 + cells for both LT-HSC subsets increased from 4 to 12 wk resulting in high median engraftment (>60% for 2 of 3 CB). Median engraftment for CD112 lo LT-HSC remained stable thereafter to 20 wk, whereas it significantly decreased from 12 to 20 wk for CD112 hi LT-HSC. Similar to INKA1-OE experiments, no overt mature lineage shift was detected (Extended Data Fig. 10m). In secondary LDA, CD112 lo LT-HSCs from all 3 CB pools had a combined 3.6-fold higher HSC frequency compared to their CD112 hi LT-HSC counterparts (Fig. 7c,d andExtended Data Fig. 10n). These data suggested that CD112 hi LT-HSCs were primed for activation and able to generate hematopoietic output more rapidly; however, they subsequently showed signs of exhaustion in the primary recipients and possessed limited secondary transplantation capacity. By contrast, the delayed repopulation (latency) of low-primed (CD112 lo ) LT-HSCs was associated with superior retention of functional HSC, recapitulating the in vivo phenotype induced by both INKA1-OE or PAK4-KD. Thus, these data established the human LT-HSC pool was composed of at least two distinct cellular subsets marked by alternative states of quiescence. In the face of regeneration-mediated stress, these subsets showed differing physiological responses, one subset met acute demand while the other preserved stemness.

DISCUSSION

Our study provides key insights into the molecular underpinnings orchestrating the complex in vivo dynamics that human HSCs undergo during transplantation to permit rapid hematopoietic repopulation while also ensuring preservation of a stem cell reservoir. We identified functionally, transcriptionally and epigenetically distinct LT-HSC subsets that are positioned along a spectrum of varying depths of G0 quiescence. The distinct G0 states are defined by dichotomy between INKA1/SIRT1 and H4K16ac and along a spectrum of PAK4, CDK6 and CD112 protein expression; a molecular network directly linking cell surface to chromatin state. The G0 state that a LT-HSC resides in determines its longterm fate upon regeneration-mediated challenge. Activated LT-HSCs contribute rapidly to repopulation but lose self-renewal capacity and exhaust, while the most quiescent LT-HSCs exhibit latency in their repopulation kinetics but retain self-renewal and long-term regenerative capacity. The latency phenotype we uncovered illustrates the complexity of human HSC dynamics in vivo, and argues that latency, in addition to self-renewal, quiescence and differentiation, is a fundamental stem cell hallmark that preserves HSC pool size during regeneration-mediated demand.

Our discovery of functionally-distinct LT-HSC subsets is consistent with HSC clonal contribution dynamics from post-transplant gene therapy patients: Initial reconstitution occurs from transient clones, while long-term hematopoiesis originates from clones that only become activated after a 1-2-year latency phase [START_REF] Scala | Dynamics of genetically engineered hematopoietic stem and progenitor cells after autologous transplantation in humans[END_REF][START_REF] Biasco | In Vivo Tracking of Human Hematopoiesis Reveals Patterns of Clonal Dynamics during Early and Steady-State Reconstitution Phases[END_REF] . Our genetic models, combining ex vivo lentiviral transduction with xenografting, are analogous to gene therapy protocols and to previous clonal tracking studies of mice and xenografts [START_REF] Rodriguez-Fraticelli | Single-cell lineage tracing unveils a role for TCF15 in haematopoiesis[END_REF][START_REF] Belderbos | Donor-to-Donor Heterogeneity in the Clonal Dynamics of Transplanted HumanCord Blood Stem Cellsin Murine Xenografts[END_REF] that pointed to functional heterogeneity manifesting in two engraftment waves. Our study establishes that these distinct fates are neither stochastic nor induced by ex vivo culture but wired into distinct molecular states of human LT-HSCs. These can be prospectively isolated into latent (CD112 lo ) and primed (CD112 hi ) LT-HSC subsets even before exposure to regeneration-mediated stress. The resistance of latent LT-HSCs (CD112 lo or INKA1-OE) to activation early during reconstitution highlights that the regenerationmediated stress imposed by transplantation is in itself not a sufficient stressor to activate latent LT-HSC.

However, certain stimuli including longer times of repopulation, secondary transplantation or 5-FU treatment lift this restraint and trigger self-renewal of latent LT-HSC. All these stimuli increase demand on ST-HSCs to generate continuous hematopoietic output leading to their exhaustion [START_REF] Notta | Isolation of single human hematopoietic stem cells capable of long-term multilineage engraftment[END_REF][START_REF] Randall | Phenotypic and functional changes induced at the clonal level in hematopoietic stem cells after 5-fluorouracil treatment[END_REF] . Thus, we speculate that this loss of immediate progeny either triggers direct activation of latent LT-HSC or lifts their restraint; a concept predicted by murine in vivo dynamics modeling [START_REF] Klose | Hematopoietic Stem Cell Dynamics Are Regulated by Progenitor Demand: Lessons from a Quantitative Modeling Approach[END_REF] . The transient lineage output restraint we observed agrees with reported properties of murine low-output HSCs 8 but contrasts with transient myeloid-restricted "latent-HSCs" from aged mice [START_REF] Yamamoto | Large-Scale Clonal Analysis Resolves Aging of the Mouse Hematopoietic Stem Cell Compartment[END_REF] . Overall, these studies suggest that stimuli stronger than those experienced during primary transplantation might be needed to read out full stem cell potential.

While our earlier study 3 found differences in G0 exit kinetics between LT-and ST-HSCs, here we uncovered distinct quiescence states prior to LT-HSC activation. The increased purity achieved by CD112 enabled detection of changes in mTORC activity along the trajectory of LT-HSC cell priming that were previously obscured if only "bulk" of LTversus ST-HSCs were compared [START_REF] Laurenti | CDK6 levels regulate quiescence exit in human hematopoietic stem cells[END_REF] . Our findings are reminiscent to the mTorc1 activation properties of GAlert muscle stem cells that are primed to respond rapidly to stress [START_REF] Rodgers | mTORC1 controls the adaptive transition of quiescent stem cells from G0 to G(Alert)[END_REF] . Embryonic diapause is a reversible H4K16ac-negative dormant state that requires mTOR signaling and the H4K16 acetyltransferase Mof for activation [START_REF] Hussein | Metabolic Control over mTOR-Dependent Diapause-like State[END_REF][START_REF] Khoa | Histone Acetyltransferase MOF Blocks Acquisition of Quiescence in Ground-State ESCs through Activating Fatty Acid Oxidation[END_REF] . Thus, the molecular quiescence and priming programs we have uncovered in LT-HSC might be conserved across some species and tissues.

The distinct latent and primed molecular signatures we ascribed to distinct CD112 immunophenotypes shed light on RhoGTPase signaling, stress responses and cell adhesion; processes all found relevant for murine HSC function [START_REF] Reddy | p21-activated kinase 2 regulates HSPC cytoskeleton, migration, and homing via CDC42 activation and interaction with beta-Pix[END_REF][START_REF] Yang | Rho GTPase Cdc42 coordinates hematopoietic stem cell quiescence and niche interaction in the bone marrow[END_REF] . CD112/PVRL2 is a ligand for the immune checkpoint receptors TIGIT and CD226 [START_REF] Andrews | Inhibitory receptors and ligands beyond PD-1, PD-L1 and CTLA-4: breakthroughs or backups[END_REF] suggesting that cross talk between HSCs and T-and NK-cells might play a role in quiescence induction, HSC recruitment and/or immune surveillance [START_REF] Kalia | Quiescence of Memory CD8(+) T Cells Is Mediated by Regulatory T Cells through Inhibitory Receptor CTLA-4[END_REF] . Furthermore, CD112 upregulation upon cell cycling is similar to MHC-I in tissue stem cells [START_REF] Agudo | Quiescent Tissue Stem Cells Evade Immune Surveillance[END_REF] suggesting a role in quality control ensuring HSC pool integrity given their inefficient genomic repair during dormancy [START_REF] Beerman | Quiescent hematopoietic stem cells accumulate DNA damage during aging that is repaired upon entry into cell cycle[END_REF] . Conversely, INKA1-mediated CD112 downregulation may facilitate immune privilege of quiescent HSCs [START_REF] Hirata | CD150(high) Bone Marrow Tregs Maintain Hematopoietic Stem Cell Quiescence and Immune Privilege via Adenosine[END_REF] .

Identifying the H4K16 deacetylase SIRT1 as an INKA1 interactor suggests a mechanism explaining the dichotomy between INKA1 and H4K16ac. SIRT1 is a stress sensor that regulates the cellular adaptation to metabolic stress while also exerting anti-inflammatory activity via negative regulation of mTOR [START_REF] Ryall | The NAD(+)-dependent SIRT1 deacetylase translates a metabolic switch into regulatory epigenetics in skeletal muscle stem cells[END_REF][START_REF] Wang | Histone Deacetylase SIRT1 Negatively Regulates the Differentiation of Interleukin-9-Producing CD4(+) T Cells[END_REF] . H4K16ac, in addition to deacetylation by SIRT1, is also regulated by pH changes, depends on acetyl-CoA and is involved in the regulation of DNA damage response during the cell cycle [START_REF] Mcbrian | Histone acetylation regulates intracellular pH[END_REF][START_REF] Cluntun | The rate of glycolysis quantitatively mediates specific histone acetylation sites[END_REF][START_REF] Sharma | MOF and histone H4 acetylation at lysine 16 are critical for DNA damage response and double-strand break repair[END_REF] . Thus, H4K16ac may indicate the metabolic changes occurring upon HSC activation and cell cycle progression while also ensuring HSC quality control. The molecular interplay that arises from the complex INKA1-interactome we identified, points to additional mechanistic roles for INKA1 beyond PAK4 inhibition and emphasizes the need for studies across all blood cell lineages and other tissue hierarchies.

Collectively, our work has uncovered a potential pivot point for the balance between varying hematopoietic demands and long-term sustainability of the hematopoietic system and identified latency as a fundamental property of stem cells that integrates quiescence control with HSC fate decisions. (e) BFP + cell counts of input and in BM of injected femurs as inferred by total cell count/femur x %BFP + .

FIGURE LEGENDS

Mean±SEM of 5-10 mice/timepoint and condition, two-sided Mann-Whitney-test.

(f) Total BM (20w) of 5-FU or PBS treated mice was subjected to hierarchy analysis.

(g,h) Secondary LDA analysis of CD45 + BFP + cells from 20 w primary grafts (+8wk; >0.1% hCD45 + ).

(i,j) Relative %BFP + engraftment (primary xenografts; i, Mean±SD, two-sided t-test, *p<0.05; **p=0.0010) and HSC frequency by secondary LDA (8 wk) for KD vectors (j). (f) Cultured and transduced HSPC were analyzed 6 days later for CD112 levels of subgated cLT-(CD34 + CD45RA -CD90 + ), cST-(CD34 + CD45RA -CD90 -) HSCs, cProgenitors (CD34 + CD45RA + ) or total cHSPCs (CD34 + ) c= cultured.

(g) LT-HSCs preincubated with anti-CD112 before fixation to only stain for cell surface expression were subjected to immunostaining and quantified intensity for total INKA1 and surface CD112 were plotted against each other (n=68 from 3 CB). Scale bar =2 µm.

(h) Nectin2/CD112 RNA expression levels against scRNAseq diffusion pseudotime. Kolmogorov-Smirnov statistic.

(i) Differential gene expression for CD112 hi vs. CD112 lo LT-HSCs (RNA-seq, 2-3 independent CB pools).

(j) Enrichment map visualization of GSEA results for CD112 hi versus CD112 lo RNA-seq data (3472 GO biological processes; gene set size 25-500; FDR<0.1). (d) Combined secondary LDA analysis from 3 CB pools. Chisquare likelihood ratio test statistic.

METHODS

Materials and Reagents

Detailed information of commercially available reagents and other materials used in this study is summarized in Supplementary Table 3.

Cages are changed every <7 days under a biological safety cabinet. Health status is monitored using a combination of soiled bedding sentinels and environmental monitoring.

Flow Cytometric Analysis and Sorting

Primary human cells were thawed by dropwise addition of X-VIVO 10 + 50% fetal calf serum supplemented with DNase (100 μg/mL final concentration) and resuspended at a density of 5 × 10 6 cells/mL. Cells were then incubated (30 min, 4°C) with the following antibodies: FITC-or BV421-anti-CD45RA (1/50), PE-or APC-anti-CD90 (1/100), PECy5-anti-CD49f (1/50), PECy7-anti-CD38 (1/100), APCCy7-anti-CD34 (1/200) and if applicable APC-anti-CD112(1/100) for sorting and/or flow cytometric analysis or anti-Nectin2 (goat) for subsequent surface immunostaining via confocal analysis. After washing cells were resuspended at 0.5-10x10 6 cells/mL in PBS, 5% FBS supplemented with 0.1 μg/L propidium iodide (PI) and sorted on a BD FACS Aria III instrument.

For flow cytometric analysis of CB MNC in addition to SYTOX blue the following antibodies were used: V500-anti-CD45 (1/100), APC-Cy7-anti-CD34 (1/200), PE-Dazzle-CD38 (1/100), APC-anti-CD112

(1/100), BV786-anti-CD33 (1/100), PE-anti-CD19(1/100), PE-anti-GlyA (1/100), FITC-anti-CD3

(1/100). Cell preparation for intracellular staining of sorted cells was performed with BD Cytofix/Cytoperm as described before [START_REF] Laurenti | CDK6 levels regulate quiescence exit in human hematopoietic stem cells[END_REF] and incubated with antibodies as applicable (FITC or PE-anti-Ki67 (1/30), AF647-anti-CDK6 (1/30), AF488-anti-H4K16ac (1/100)) in PermWash solution (BD) overnight. If applicable, Edu Click-IT reaction was performed according to manufacturer's instructions and prior to flow cytometry analysis cells were stained with Hoechst 33342 (1:2000; Thermo Fisher) or DAPI (1 μg/mL; Sigma). Other flow cytometry-based assays were performed according to the manufacturer's protocol: AnnexinV-FITC or -APC Kit (BD) and CellROX staining (ThermoFisher) in X-Vivo 10, 1% BSA, L-Glutamine, Pen/Strep. Cells were sorted on BD FACS Aria III or analyzed on BD Canto II, BD Fortessa or BD Celesta instruments. Positive gates were set according to unstained or isotype controls. Data was analyzed by FlowJo.

Immunostaining

Sorted cells were spun onto Poly-L-Lysine (Sigma)-coated slides (Ibidi, 200 xg, 10 min), fixed with 4% formaldehyde (Sigma) and permeabilized with 0.5% Triton X-100 (Sigma) before blocking (PBS, 10% FBS, 5% BSA; 30 min, RT). Slides were incubated with primary antibodies (Anti-INKA1(1/100), Anti-PAK4 (1/50), AF647-Anti-CDK6 (1/50), AF488-Anti-H4K16ac(1/100), Anti-SIRT1(1/100), Anti-Nectin2 (1/100), AF647-Anti-Ki67 (1/100)) in blocking solution O/N at 4°C. If necessary Anti-FAM212A and Anti-PAK4 antibodies were directly labeled using the Zip Alexa Fluor 555 Rapid Antibody Labeling Kit (Thermo Fisher) at a 0.1x antibody concentration but otherwise according to manufacturer's instructions to allow co-staining with other directly labeled rabbit or mouse antibodies, respectively. As applicable, secondary antibodies (1/400) were added (PBS, 0.025% Tween 20, Sigma, 1.5 h, RT). After washing, nuclei were stained with 1 μg/mL DAPI (Sigma) and slides were mounted (FluoromountG). Single cell images were captured by a Zeiss LSM700 Confocal Microscope (oil, 63x/1.4NA, Zen 2012) and processed and analyzed with ImageJ/Fiji and FlowJo10 or Python. In case of high inter-experimental variability between independent stainings data were normalized by z-score transformation. Pixel Intensity Spatial Correlation Analysis of colocalization was carried out using the Coloc2/Fiji plugin for ImageJ Software to obtain Spearman's rank correlation values for a region of interest incorporating either an individual cell, its nucleus or its non-nuclear area. The Coloc2 plugin was run with a PSF of 4.1-4.7 depending on channel combination and with 50 Costes' randomizations. For pseudotime analysis using single cell immunofluorescence data, fluorescence values were log transformed and scaled (CDK6, nuclear CDK6, DAPI, H4K16ac, PAK4, and nuclear PAK4). Diffusion mapping embedding was subsequently calculated as well as diffusion pseudotime [START_REF] Haghverdi | Diffusion pseudotime robustly reconstructs lineage branching[END_REF] within scanpy . For the CellROX assay sorted cells were washed, resuspended in cytokine-free medium (X-Vivo 10, 1% BSA, L-Glutamine, Pen/Strep) supplemented with 5 μM CellROX Green and then incubated for 30 min at 37°C in Poly-L-Lysine coated chambered glass coverslips/ μ-slides (Ibidi). Subsequently, slides were spun (200 xg, 10 min), medium was removed, and cells were fixed, washed, permeabilized and blocking was performed as before. Slides were then incubated with AF647-anti-CDK6 (1/50) antibody in blocking solution for 1 hr at RT. After washing, nuclei were stained with 1 μg/mL DAPI, chambers were washed, covered with FluoromountG and images were captured by a Zeiss LSM700 Confocal Microscope (20x/0.8 NA, Zen 2012).

Proximity Ligation Assay

Proximity ligation assay (PLA) was performed after sample preparation for immunostaining as described followed by using the Duolink® In Situ Orange Starter Kit Mouse/Rabbit (Millipore Sigma) according to manufacturer's instructions with few adaptations: Before primary antibody incubation overnight in PBS, 10% FBS, 5% BSA, slides were blocked with PBS, 10% FBS, 5% BSA for 5 hrs at 4°C. After two washes with Wash Buffer A (Kit), slides were incubated with the Duolink® Blocking solution for 3 hrs at 37°C. For all subsequent steps manufacturer's instructions were followed. Images were captured by a Zeiss LSM700 Confocal Microscope (20x/0.8 NA, Zen 2012) and processed and analyzed with ImageJ/Fiji. Background signal was determined according to several control HSPC/Progenitor specimens incubated with either no primary antibody (AB), no primary or secondary AB, anti-SIRT1(1/100) as only primary AB, anti-FAM212A (1/100) as only primary AB, anti-SIRT191/100) or anti-PAK4 (1/50) in combination with rabbit IgG (anti-V5; 1/100), anti-FAM212A in combination with mouse IgG (anti-BrdU; (1/100 or 1/50; respectively)).

Chromatin fiber assay

For visualizing epigenetic information and proteins bound to chromatin extended chromatin fibers were prepared as described elsewhere 45,[START_REF] Sullivan | Optical mapping of protein-DNA complexes on chromatin fibers[END_REF] with few modifications: CB HSPC CD34 + CD38 -were resuspended in PBS at 2.5x10 5 cells/mL, 8 µl were spotted as a line on a glass slide and air-dried before 150 µl lysis buffer (500 mM NaCl, 500 mM Urea, 25 mM Tris, 1% Triton X-100, pH 7.5) was added. After 15 min at RT slides were placed in a 25° angle to extend fibers by gravity. For fixation slides were treated for 10 min with 4% PFA and then washed for 30 min in PBS. After 1 hr of blocking (PBS, 10% FBS, 5% BSA) primary antibody incubation followed (90 min, RT; 1/50 in blocking solution). Subsequently slides were washed in PBS, 0.025% Tween (10 min, RT) and incubated with secondary antibodies (1/400 in PBS, 0.025% Tween; 90 min, RT). After 1x washing in PBS, 0.025% Tween (10 min), slides were washed 2x with PBS and incubated with 5 µg/mL Hoechst 33342 in PBS (30 min, RT). Slides were then washed (PBS), mounted with FluoromountG and analyzed with a Zeiss LSM700 Confocal Microscope (oil, 63x/1.4NA, Zen 2012).

Cell Culture

For the time course experiment ~1000 sorted cells were cultured in Terasaki plates in 25 µl. To align G0 exit kinetics with previous data 3 cells were cultured under high cytokine conditions: StemPro-34 SFM media (Thermo Fisher) with the supplied supplement, 1x L-Glutamine, 1x Pen/Strep, 0.02% Human LDL and the following cytokines: FLT3L (20 ng/mL), GM-CSF (20 ng/mL), SCF (100 ng/mL), TPO (100 ng/mL), EPO (3 U/mL), IL-3 (10 ng/mL), IL-6 (50 ng/mL). Cells were harvested at indicated timepoints and subjected to immunostaining. For all other primary cell cultures cells were cultured at a density of 0.4-5x10 5 cell/mL in 96-well round-bottom plates with low-cytokine condition media: X-VIVO 10 media, 1 % BSA supplemented with 1x Pen/Strep, L-Glutamine and the following cytokines: SCF (100 ng/ml), Flt3L (100 ng/ml), TPO (50 ng/ml) and IL7 (10 ng/ml). For experiments with the PAK4 inhibitor PF-3758309 (solvent: DMSO), the SIRT1 inhibitor EX-527 (final concentration 25 µM; solvent: DMSO) or EdU (final concentration 10 µM) 1 volume of complete medium with 2x reagent or equivalent DMSO concentration as indicated was added to 1 volume of cell suspension. For PF-3758309 treated cells after 3 days a half medium exchange was performed with complete medium supplemented with 1x inhibitor concentration. For LDA experiments initial cell input was: 160-500 (low dose), 800-2500 (mid dose), 4000-12500 (high dose).

Lentiviral Vector Production

VSV-G pseudotyped lentiviral vector particles were produced, and titers were determined as previously described [START_REF] Kaufmann | A stemness screen reveals C3orf54/INKA1 as a promoter of human leukemia stem cell latency[END_REF] . The negative control (CTRL) vector for overexpression encodes gp91 phox P415H (catalytic inactive gp91 phox /CYBB) and for knockdown a shRNA directed against Renilla luciferase (shCTRL) [START_REF] Kaufmann | A stemness screen reveals C3orf54/INKA1 as a promoter of human leukemia stem cell latency[END_REF] .

Additional shRNA were generated as described before [START_REF] Kaufmann | A stemness screen reveals C3orf54/INKA1 as a promoter of human leukemia stem cell latency[END_REF] .

Lentiviral Transduction

If for a particular assay not stated otherwise, after 16-20 hours of pre-stimulation in low cytokine condition medium cells were transduced with OE or KD and control vectors at matching multiplicity of infection [START_REF] Kaufmann | A stemness screen reveals C3orf54/INKA1 as a promoter of human leukemia stem cell latency[END_REF] aiming at mid-range (20-40%) transduction efficiencies but without lentiviral preparation exceeding 20% of total culture volume. Transduction efficiency (%BFP + ) was determined at day 3 and day 6 post-transduction by flow cytometry on a BD Celesta and for xenotransplantation assays the mean of both timepoints served as initial input estimate.

Quantitative RT-PCR for PAK4 and INKA1

RNA from FACS-sorted fractions was isolated with TRIzol (Invitrogen) or for low cell numbers (<20,000 cells) with PicoPure RNA Isolation Kit (Thermo Fisher) according to manufacturer's protocol.

Quantitative RT-PCR analysis was performed using the QuantiFast SYBR Green PCR Kit (Qiagen) on the LightCycler 480 Instrument II (Roche). All signals were quantified using the ΔCt method and were normalized to the levels of GAPDH.

Methylcellulose Colony Forming Unit Assay

LT-HSC and ST-HSC were sorted and cultured in low cytokine medium for 4 hours and then transduced with CTRL or INKA1-OE lentiviral vectors. At day 3 post-transduction, 200 BFP + cells were sorted directly into 2 mL methylcellulose (H4034, Stem Cell Technologies), supplemented with FLT3 Ligand (10 ng/mL) and IL6 (10 ng/mL) and plated onto 2x35 mm dishes as duplicates. Colonies were allowed to differentiate for 12-14 days and then morphologically assessed in a blind fashion by a second investigator. Subsequently, colonies from replicate plates were pooled, resuspended in PBS/5% FBS, washed and 0.5% of progeny from LT-HSC and 1% of progeny of ST-HSC was added to fresh methylcellulose as above, replated and scored after 12-13 days.

Single Cell Stromal Assays

Single cell in vitro assays were set up as with low passage murine MS-5 stroma cells [START_REF] Itoh | Reproducible establishment of hemopoietic supportive stromal cell lines from murine bone marrow[END_REF] seeded at a density of 1500 cells per 96-well and grown for 2-4 days in H5100 media (StemCell Technologies, 05150). Oneday prior to co-culture initiation, the H5100 media was removed and replaced with 100 μl erythromyeloid differentiation media: StemPro-34 SFM media (Thermo Fisher) with the supplied supplement, 1x L-Glutamine, 1x Pen/Strep, 0.02% Human LDL and the following cytokines: FLT3L (20 ng/mL), GM-CSF (20 ng/mL), SCF (100 ng/mL), TPO (100 ng/mL), EPO (3 U/mL), IL-2 (10 ng/mL), IL-3 (10 ng/mL), IL-6 (50 ng/mL), IL-7 (20 ng/mL), and IL-11 (50 ng/mL).

Single cell stromal assays: INKA1-OE

LT-, IT90+, IT90-and ST-HSC were sorted from CB Lin-and cultured in low cytokine medium for 4 hours before transduction with CTRL or INKA1-OE lentiviral vectors. On day 3 post-transduction, cells were washed, resuspended in PBS, 2.5% FBS, 0.1 μg/L PI and PI -BFP + single cells were deposited onto seeded MS5 stromal layers in 96 well plates using a BD FACSAria III. Single cells were co-cultured to proliferate and differentiate for 15 days (18 days post-transduction) with an addition of 100 μl erythromyeloid differentiation media per well on day 8. Wells with hematopoietic cell content were marked 1 day prior and the total number of wells with colonies was used to estimate single cell cloning efficiency.

On the day of final analysis cultures were trypsinized, blocked with FBS, filtered (8027, Pall), stained and flow cytometric analyzed on a BD Celesta using the high-throughput sampler (HTS) unit. The following antibodies were used: V500-anti-CD45 (1/100), BV786-anti-CD33 (1/100), FITC-anti-CD56 (1/100), PEanti-GlyA (1/100), PECy5-anti-CD14 (1/100), APC-anti-CD71 (1/100) and APC-Cy7-anti-CD41 (1/200).

Erythroid cells were defined as CD45 negative and positive for CD71 and/or GlyA.

CD112 Index-sorted Single Cell Stromal Assay

On the day of the experiment, CB Lin -cells were stained as above to sort and deposit Sytox Blue - CD34 + CD38 -CD45RA -single cells onto seeded MS5 stromal layers in 96 well plates while single cell fluorescence intensities for PECy5-anti-CD49f, PE-anti-CD90 and APC-anti-CD112 were indexed using a BD FACSAria III. Single cells were cultured for 18 days with an addition of 100 μl erythro-myeloid differentiation media per well at day 8. Wells with hematopoietic cell content were marked 1 day prior and the total number of wells with colonies was used to estimate single cell cloning efficiency. On day 18 of co-culture cells hematopoietic cells were resuspended, filtered (8027, Pall), stained and flow cytometric analyzed on a BD Celesta using the HTS unit. The following antibodies were used: V500-anti-CD45(1/100), BV786-anti-CD33 (1/100), BV605-anti-CD56 (1/100), PE-anti-GlyA (1/100), PECy5-anti-CD11b (1/200), FITC-anti-CD71 (1/100), APC-Cy7-anti-CD41(1/200) and APC-anti-CD34(1/100).

Clonal lineage output was scored and aligned with indexed single cell fluorescence intensity for CD112 at initial single cell deposition generating an .fcs file for visualization in FlowJo10.

Xenotransplantation

Aged and gender matched 8-16 wk old male and female recipient NOD.Cg-PrkdcscidIl2rgtm1Wjl/SzJ (NSG) or NOD.Cg-PrkdcscidIl2rgtm1WjlTg(CMVIL3,CSF2,KITLG)1Eav/MloySzJ (NSG-SGM3) mice were sublethally irradiated (224-225 cGy) 24 hours prior to intra-femoral injection. Cells were either injected directly after sorting, the progeny of 10 4 CD34 + CD38 -transduced cells one day after transduction or the progeny of initially plated CD34 + CD38 -cells treated in culture with PF-3758309 or DMSO. For analysis, mice were euthanized, injected femur and other long bones (non-injected femur, tibiae) were flushed separately in Iscove's modified Dulbecco's medium (IMDM) and 5% of cells were analyzed by flow cytometry (BD Celesta). For primary transplant analysis of initially ex vivo cultured cells, mice were euthanized at indicated timepoints (2, 4, 12, 20 weeks) after transplantation and human chimerism was assessed along with BFP and the following antibodies in addition to staining with Fixable Viability Dye eFluor 506 (1/500): PECy5-anti-CD45(1/100), APCCy7-anti-CD34(1/200), BV786-anti-CD33(1/100), pseudotime. To assign cells as LT-HSC, ST-HSC, IT90+ and IT90-, 40 th percentile cutoffs were applied for both CD90 and CD49f surface intensities as measured through index sorting.

Bulk RNA-seq processing and analysis CD112 high and CD112 low LT-HSC, total LT-HSC and ST-HSC were sorted from 3 independent CB pools and either directly resuspended and frozen (-80°C) in PicoPure RNA Isolation Kit Extraction Buffer or after transduction followed by a second sort (PI -BFP + ) on day 6 post-transduction (average cell count: 10 4 ; range 0.25-3x10 4 ). RNA was isolated using the PicoPure RNA Isolation Kit (Thermo Fisher) according to manufacturer's instructions. Samples that passed quality control according to integrity (RIN>7) and concentration as verified on a Bioanalyzer pico chip (Agilent Technologies) were subjected to further processing by the Center for Applied Genomics, Sick Kids Hospital: cDNA conversion was performed using SMART-Seq v4 Ultra Low Input RNA Kit for Sequencing (Takara) and libraries were prepared using Nextera XT DNA Library Preparation Kit (Illumina). Equimolar quantities of libraries were pooled and sequenced with 3-4 cDNA libraries per lane on a High Throughput Run Mode Flowcell with v4 sequencing chemistry on the Illumina HiSeq 2500 following manufacturer's protocol generating paired-end reads of 125-bp in length to reach depth of 60-80 million reads per sample. Reads were then aligned with STAR v2.5.2b against hg38 and annotated with ensembl v90. Default parameters were used except for the following: chimSegmentMin 12; chimJunctionOverhangMin 12; alignSJDBoverhangMin 10; alignMatesGapMax 100000; alignIntronMax 100000; chimSegmentReadGapMax parameter 3; alignSJstitchMismatchNmax 5 -1 5 5. Read counts were generated using HTSeq v0.7.2 and general statistics were obtained from picard v2.6.0. Differential gene expression was performed using DESeq2 v1.22.2 following recommended practices. Genes were ranked using the formula -sign(logFC) * -log10(pvalue). The rank files from each comparison were used in pathway analysis (GSEA) using 2000 permutations and default parameters if not specified otherwise, against pathway collections from databases (MsigDB; HALLMARK, GOBP from http://baderlab.org/GeneSets, version February 2020) or retrieved from the literature (HSC_120_COMMON [START_REF] Fares | EPCR expression marks UM171-expanded CD34(+) cord blood stem cells[END_REF] ). The gene set aHSC/MPP_UP_(vs_dHSC) was of 147 bp. A set of 500 bp windows over hg19, overlapping by 250bp was generated and for each sample the windows overlapping a called peak were identified. Windows were considered to be present in each condition if they overlapped a peak in 2 replicates. Windows only considered present in one condition were considered specific to that condition. Motif enrichment was performed using HOMER against a catalogue of all peaks called in any hematopoietic population was produced by merging all called peaks which overlapped by at least one base pair using bedtools. As described in Takayama et al. [START_REF] Takayama | The Transition from Quiescent to Activated States in Human Hematopoietic Stem Cells Is Governed by Dynamic 3D Genome Reorganization[END_REF] , cells from three sorted CD34+CD38-CD45RA-and three CD34+CD38+ populations were processed on the 10X Genomics single cell ATAC-seq platform, and 12,414 single cells were retained based on default cellranger QC criterion and chromVAR depth filtering. Cellranger-reanalyze (1.1, 10x Genomics) was subsequently used to map reads over the sites identified in the bulk ATAC-Seq catalogue, and read counts were binarized. chromVAR (with default settings) was used to calculate the enrichment of each of the hematopoietic signatures identified in this paper in each single cell, as well as for the windows considered specific to the CD112 low or CD112 high LT-HSC subsets.

Statistical Analysis

GraphPad Prism or MS Excel were used for all statistical analyses except RNA-seq, which was analyzed

  Figure # Figure titleOne sentence only

  Representative sorting scheme to obtain LT-, ST-, IT90+-IT90-HSCs or CD34+CD38-and CD34+CD38+ cells from lineage depleted CB. (b) Confocal images of 2 individual ST-HSC to visualize heterogeneity and representative for n=3 independent CB pools analyzed. Scale bar = 2 μm. (c) Confocal images of 4 individual, uncultured LT-HSC next to thereof derived images for INKA1 and H4K16ac channels after thresholding and binary conversion using ImageJ to visualize intracellular invers staining pattern in double dim cells of the heterogenous cell pool and representative for n=3 independent CB. Scale bar = 4 μm. (d) Percentage INKA1 + cells in HSC subsets according to INKA1 + cell gate in Fig. 1d (immunostaining, ∅50 cells/population and CB, n=3 independent CB pools). Mean±SD. (e) Confocal images and quantification (MFI) of prospectively isolated LT-and ST-HSC stained for INKA1 and CDK6 and representative for n=3 independent CB as summarized in right panel. Gating as used for Figure 1F is indicated. Scale bar = 2 μm. Cell cycle analysis (Ki-67, Hoechst, CDK6) of prospectively isolated HSC subsets (LT-, IT90 + -, IT90 -, ST-HSC) from mPB (n=3) by flow cytometry. CB HSPC (CD34 + CD38 -) and Progenitors (Prog, CD34 + CD38 + ) served as gating controls. Mean±SD; two-sided paired ttest (**p=0.002).

  Gating strategy for cell cycle phases of 2d with 20 hr EdU pulse cultured CB Lin-. (b,c) CB LT-and ST-HSC analyzed by immunostaining for Ki-67, H4K16ac, PAK4 and DAPI after 72 hrs of culture; plots in (h) show data combined from 3 independent CB pools (∅50 cells/population and sample). Scale bar = 4 µm. (d) Longitudinal confocal imaging of LT-HSC harvested at 5 timepoints of culture in high-cytokine conditions. Two individual LT-HSC are shown per timepoint. Scale bar = 4 μm.

  c) CTRL and INKA1-OE HSPC were sorted (BFP+) d6 post transduction and subjected to immunostaining (n=2) and INKA1 levels were determined (a); two-sided t-test. Colocalization was quantified in (b) by Coloc2/ImageJ and Spearman's rank correlation values for single cells with Costes' P-value = 1.00 (**p=0.0041); and in (c) by proximity ligation assay (PLA) with background set according to negative controls (IgG1: anti-PAK4 + rabbit IgG; IgG2 anti-INKA1 + mouse IgG); two-sided Mann-Whitney-test (b,c; ***p<0.0001).(d) Cell viability of transduced HSPC was determined via dye exclusion (PI, 7AAD; n=9). (e) CTRL and INKA1-OE LT-and ST-HSC (n=4-5) were sorted (BFP + ) d6 post transduction and subjected to cell cycle analysis by flow cytometry. (f) Distribution of PAK4 protein levels in nucleus vs. cytoplasm according to confocal analysis of CTRL and INKA1-OE LT-and ST-HSC; two-sided Mann-Whitneytest (***p=0.0005). (g) Differentially expressed genes with adjusted p-value<0.01 (according to DESeq2, **p=0.003, ***pvalue range: <10 -4 -10 -26 ) in either LT-or ST-HSC transduced with INKA1-OE vs CTRL (log2FC). Extended Data Fig. 6 INKA1-OE mediated effects in in vitro differentiation assays. Kaufmann_Extende d_Data_Fig6.tif (a) CB LT-and ST-HSC were cultured, transduced (OE) and on day 3 ptd BFP + cells were sorted into methylcellulose for colony formation, scored and harvested 12 days later and replated (right) for 12 additional days (n=4). Colony type composition of primary and secondary colony formation assays (CFU-C) is shown in the lower panels; Mean±SD, two-sided paired t-test. (b) Total single cell colony output (d15) from stromal coculture assays per CB (n=3 independent pools, Mean±SD) and subfraction of CTRL and INKA1-OE transduced HSC subsets as indicated. My= myeloid (CD33 + ), E= erythroid (CD45 -GlyA + /CD71 + ), Mk = megakaryocytic (CD41 + ), NK = CD56 + cells. Upper right panel shows proliferative potential and lower panel total colony output per assay, population and condition as assessed by flow cytometry; two-sided paired t-test. Extended Data Fig. 7 INKA1-OE, shINKA1 and shPAK4 in xenograft assays. Kaufmann_Extende d_Data_Fig7.tif (a) Gating strategy for BM analysis from xenografts. (b) Human CD45 chimerism in injected femur (right, RF) and non-injected bone marrow of CB HSPC transduced with CTRL or INKA1-OE at various timepoints posttransplant (5 independent CB pools

  To gain more mechanistic insight into how INKA1 functions as an endogenous PAK4 inhibitor within HSC subsets and influences their priming status, we utilized an INKA1 overexpressing (INKA1-OE) lentiviral vector that co-expressed blue fluorescent protein (BFP) to track transduced cells. By focussing on BFP + INKA1-OE and control transduced CB CD34 + CD38 -cells, we established that INKA1 protein was elevated and that PAK4 and INKA1 were colocalized (Extended Data Fig. 5a-d). INKA1-OE in LT-HSCs, but not in ST-HSCs, reduced CDK6 intensity, H4K16ac and the relative abundance of PAK4 in the nucleus and increased the percentage of cells retained in G0 (2.6±1.5 fold; n=5; Fig. 4a,b and Extended Data Fig. 5e,f) compared to controls. Gene set enrichment analysis (GSEA) of RNA-seq data further showed that INKA1-OE vs. controls preserved established HSC stemness signatures and induced a transcriptionally suppressed cell state in LT-HSCs, as evidenced by negative enrichment of multiple stem cell associated and inflammatory signaling pathways, stress responses, and cell cycle related gene sets (Fig. 4c,d and Extended Data Fig. 5g). To assess whether INKA1-OE interfered with HSC function we performed both single cell stroma-based differentiation assays and colony-forming assays (CFU-C). INKA1-OE did not change lineage outcome, however, INKA1-OE in LT-HSCs resulted in decreased primary CFU-C output without differences in secondary replating assays (Extended Data Fig. 6a,b). Collectively, these data demonstrated that INKA1-OE functioned selectively in LT-HSCs by suppressing stem cell activation programs and inducing a transient restraint in colony formation without affecting their potential to generate multilineage hematopoietic progeny.

  These data established that the transient restraint enforced by INKA1 was linked to reduced cycling in vivo. In addition to INKA1-OE protection from 5-FU-mediated stem cell depletion, exposure of INKA1-OE cells to a second challenge (5-FU) during the period of restrained regeneration resulted in activation of HSCs and stem cell expansion without exhaustion of self-renewal potential. To evaluate whether HSPC engraftment capacity depended on INKA1 and was mediated via PAK4 inhibition, we transduced CB CD34 + CD38 -HSPCs either with control, two INKA1-knockdown (KD) and two PAK4-KD vectors and performed in vivo assays in analogy to INKA1-OE studies. INKA1-KD resulted in 2-fold reduction in the relative proportion of BFP + cells at 4 wk and 20 wk in primary recipients (Fig.

  inverse staining patterns of INKA1 and H4K16ac in HSC subsets and the suppression of H4K16ac upon INKA1-OE. Broadly, the regulation of SIRT1 localization and activity by INKA1 reveals a novel function beyond PAK4 inhibition.

Fig. 1 :

 1 Fig. 1: INKA1 and H4K16ac show inverse abundance and visualize heterogeneity in HSC subsets.

Fig. 2 :

 2 Fig. 2: Single cell transcriptome and protein analysis validates that INKA1 vs its target PAK4 and

Fig. 3 :

 3 Fig. 3: PAK4 inhibition induces G0 arrest in vitro maintaining stem cell regenerative capacity.Sorted CB CD34 + CD38 -HSPC and CD34 + CD38 + progenitors were cultured, after 2 days medium was

Fig. 4 :

 4 Fig. 4: INKA1-OE LT-HSCs resist activation in vitro. (a,b) Immunostaining of prospectively isolated, transduced (OE) and BFP + -sorted CB LT-and ST-HSCs

Fig. 5 :

 5 Fig. 5: INKA1-OE and PAK4-KD preserve long-term stem cell regenerative potential under

Fig. 6 :

 6 Fig. 6: INKA1/PAK4 interactome identifies SIRT1 as link between INKA1 and H4K16ac and

Fig. 7 :

 7 Fig. 7: CD112 surface expression delineates alternatively quiescent states of LT-HSCs. (a) Gating strategy for sorting CD112 hi and CD112 lo CB CD90 + CD49f + LT-and CD90 -CD49f -ST-HSCs. (b) LT-and ST-HSCs sorted for CD112 hi and CD112 lo and subsequently analyzed by intracellular flow

  (h) Hallmark GSEA of CD112 hi vs. CD112 lo LT-HSCs and INKA1 expression (bulk RNA-seq).

Fig. 8 :

 8 Fig. 8: CD112 hi LT-HSCs are primed whereas CD112 lo demarcates latent LT-HSCs.Prospectively isolated CD112 hi and CD112 lo LT-HSCs from 3 independent CB pools were transplanted

  with R and Python. Unless otherwise indicated in Fig. legend, mean ± SD values are reported in the graphs and minimal to maximal values are represented in box-and-whisker plots. Statistical significance (*p < 0.05, **p < 0.01 and ***p < 0.001, n.s. represents non-significance) was determined if not otherwise indicated in Figure legends with two-sided Student's t-tests with or without Welch's correction as applicable. If normal-distribution assumptions were not valid, statistical significance was evaluated using the Mann-Whitney test (two-tailed) for single comparisons or Kruskal-Wallis test for multiple comparisons. A normal distribution of the data was tested using the Kolmogorov-Smirnov test if the sample size allowed. One-way ANOVA was used to compare means among three or more independent

Acknowledgments

We thank the obstetrics units of Trillium Health and William Osler Health Partners for CB; The UHN-SickKids Flow cytometry facility for cell sorting; M. Minden and the Leukemia Tissue Bank at Princess Margaret Cancer Centre/University Health Network for providing primary mPB samples. We thank E. Laurenti and all members of the Dick lab, in particular J.C.Y. Wang, for critical feedback. This research was supported by the Deutsche Forschungsgemeinschaft (K.B.K). and is part of the University of Toronto's Medicine by Design initiative which receives funding from the Canada First Research Excellence Fund. Work in J.E.D.'s laboratory is supported by funds from the Princess Margaret Cancer Centre Foundation, the Canadian Institutes of Health Research (Foundation: 154293 (J.E.D), Operating Grants # 154293 and # 89932 (J.E.D), International Development Research Centre, Canadian Cancer Society (Grant #703212 (J.E.D)), Terry Fox Research Institute Program Project Grant, Ontario Institute for Cancer Research through funding provided by the Government of Ontario, a Canada Research Chair, and the Ontario Ministry of Health and Long Term Care.

Data availability

The accession number for RNA-seq data generated for this manuscript is GEO: GSE148885, and GEO: GSE125345 for previously published RNAseq data used in this study. Raw RNA-seq and ATACseq data is available on EGA: EGAD00001006541 (Bulk RNA-Seq: EGAS00001004768; scRNAseq: EGAS00001004769; ATACseq: EGAS00001005121). For GSEA GOBP were retrieved from http://baderlab.org/GeneSets (version February 2020), the Hallmark gene set v.7.0 from ftp.broadinstitute.org://pub/gsea/gene_sets/h.all.v7.0.symbols.gmt and Eppert HSC-R from http://www.gsea-msigdb.org/gsea/msigdb/cards/EPPERT_HSC_R.html.

Code availability

Code generated during this study is available at GitHub https://github.com/andygxzeng/HSC_Pseudotime.

Methods-only References

If there are multiple files of the same type this should be the numerical indicator. i.e. "1" for Video 1, "2" for Video 2, etc. This should be the name the file is saved as when it is uploaded to our system, and should include the file extension. i.e.: Smith_ Supplementary_Video_1.mov PECy5-anti-CD49f and PE-anti-CD90 were additionally indexed using a BD FACSAria III. Single cells were immediately lysed when sorted into wells with a mix of 5× Maxima Transcription Buffer, dNTPs, and NXGen RNase inhibitor (Lucigen), custom 3'end reverse transcriptase primers [START_REF] Satija | Spatial reconstruction of single-cell gene expression data[END_REF] and water (detailed protocol deposited: https://dx.doi.org/10.17504/protocols.io.nkgdctw). Plates were spun and immediately transferred onto dry ice and stored at -80 until further processing. A modified version of the SMARTseq2 protocol [START_REF] Picelli | Full-length RNA-seq from single cells using Smart-seq2[END_REF] was performed with a custom modification in which a 12-base cell barcode was included in the 3′-end reverse transcriptase primer. This enabled us to perform multiplexed pooling before library preparation with the Nextera XT DNA sample prep kit (Illumina).The resulting libraries of 1536 single cell and simultaneously processed 192 CD34 + CD38 -CD45RA -BM cells were sequenced in a total of 4 lanes in Rapid Run mode on an Illumina HiSeq2500 instrument (Single index, paired end, 26bp read 1, 32bp read 2, 8bp index read with custom barcodes). Reads were aligned with STAR 2.6.0c. Default parameters were used except for the following: sjdbOverhang 30. RNA velocity was run on the bam files using the run_smartseq2 function in velocyto 0.17.8 with default settings [START_REF] Manno | RNA velocity of single cells[END_REF] . Cells with total read counts or total genes 4 median absolute deviations (MADs) below the median were removed, as were cells with a proportion of mitochondrial genes 4 MADs above the median. Denoising was performed using dca 0.2.2 and batch correction was applied using an mnncorrect implementation within scanpy 1.3.3 [START_REF] Haghverdi | Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors[END_REF]51 . After preprocessing, mPB data was projected onto a diffusion map embedding and diffusion pseudotime [START_REF] Haghverdi | Diffusion pseudotime robustly reconstructs lineage branching[END_REF] was calculated using default parameters. Imputed gene expression was subsequently compared against derived from published murine RNAseq data [START_REF] Cabezas-Wallscheid | Vitamin A-Retinoic Acid Signaling Regulates Hematopoietic Stem Cell Dormancy[END_REF] processing for the BioID assay was performed as described previously in HEK293 [START_REF] Coyaud | Global Interactomics Uncovers Extensive Organellar Targeting by Zika Virus[END_REF] . Briefly, high confidence interactors were identified fulfilling these criteria: iProphet>0.9, at least two unique peptides in each of 4 runs, and a Bayesian FDR< 1% comparing the two highest peptide counts of each given ID between 20 controls (FlagBirA* only construct) and 4 bait protein sample analysis. Data was loaded into Cytoscape for network visualization and in Cytoscape STRING enrichment (GO processes) was used for pathway analysis to subsequently generate the enrichment map of selected pathways with FDR<0.05.

Describe the contents of the file

ATAC-seq processing and analysis

Library preparation for ATAC-Seq was performed on 2000 cells with Nextera DNA Sample Preparation kit (Illumina), according to a previously reported protocol [START_REF] Buenrostro | Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position[END_REF] . 4 ATAC-seq libraries were sequenced per lane in HiSeq 2500 System (Illumina) to generate paired-end 50-bp reads. Reads were mapped against the hg19 human reference genome using BWA with default parameters. All duplicate reads, and reads mapped to mitochondria, chrY, an ENCODE blacklisted region or an unspecified contig were removed (ENCODE Project Consortium 2012). MACS 2.0.10 was used to call peaks with a uniform extension size groups. Applicable post hoc tests were used to compare all pairs of treatment groups when the overall P value was <0.05.