Alexis Matynia

Patrick Sambou

Elissa El Rassy

Elissa El

Empirical evaluation of the efficiency of genetic and particle swarm algorithms for kinetic mechanism optimization

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

Empirical evaluation of the efficiency of Genetic and Particle Swarm algorithms for kinetic mechanism optimization.

A. Matynia, P. Sambou, E. El Rassy Sorbonne Université, Centre National de la Recherche Scientifique, UMR 7190, Institut Jean Le Rond ∂'Alembert, F-75005 Paris, France alexis.matynia@sorbonne-universite.fr

Context and Objective

• Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are two evolutionnary algorithm widely used for optimization • GA is well known and used for detailed kinetic mechanisms optimization [1] but, so far, PSO is not • Objective: compare the performances with the open-source tool Brookesia [2] 2. Error computation • Kinetic mechanism -GRI-Mech 3.0 (53 sp. 325r.) [4] • Degraded mechanism to be optimized -the 7th most important reactions for each of the 7 targets randomly modified -Importance evaluated on the basis of the direct interaction coefficients between a species A and a reaction r i , (see ref.

Conclusions

The comparison of the PSO to GA optimization approach led to the following observations:

• some strategies are more efficient than GA. • those strategies come along with very high convergence rates • high sensitivity to the choice of parameters • lower reliability to the success of an optimization Given the simplicity of the PSO approach, this work demonstrates the interest in considering PSO optimization as a good alternative to GA.

  [5])3. a. Optimization by Genetic Algorithm• Concept 1. from randomly modified kinetic mechanisms a series of simulation is performed 2. based on the result analysis, the best mechanisms (individuals) are retained (Selection operator) 3. individuals will share parameters (Cross-Over operator) to generate new mechanisms (childs) 4. some individuals will be partially randomly modified (Mutation operator) 5. a new series of simulation is performed and the cycle is repeated • Strategies • Performances number of individuals: 20 (*) number of occurence each strategies repeated 20 times: -Mean error is averaged over the 20 trials -the standard deviation measured between trials is shown below • Comments -Optimization efficiency seems relatively insensitive to the strategy -Strategies 10 and 11 show the best results indicating the importance of a good setting of the mutation rate.

3

  . b. Optimization by Particle Swarm Algorithm • Concept 1. from randomly modified kinetic mechanisms a series of simulation is performed 2. each kinetic mechanism is a particle, its dynamics is governed by: -an inertial component, relative to the speed of the iteration of the previous iteration -a cognitive component based on the best solution found by the individual during the optimization process -a social component based on the best location the neighbours of the particle found up to the iteration 3. a new series of simulation is performed and the cycle is repeated • Strategies • Performances number of individuals: 20 Each strategies repeated 20 times: -Mean error is averaged over the 20 trials -the standard deviation measured between trials is shown below • Comments -Best results for strategies 3 and 7 -Efficient strategies also present very high convergence rate -Standard deviations are higher than GA indicating lower reliability for optimization quality 3. c. Simulation results CH 4 /air Φ=0.5 T = 1500 K

  CH 4 , CO, CO 2 , C 2 H 4 , C 2 H 6

					1. Simulations
					• 6 Conditions	• 7 Targets
					-Constant pressure	-ignition delay time
					& enthalpy reactor (Cantera [3])	-temperature
					-composition :	-species:
					-CH 4 /air
					-Φ = 0.5, 1.0, 1.5
					-p = 10 5 Pa / T = 1050, 1500 K
	• Ignition delay	• T and species profiles
	Er(δ) = 1 -	δ opt δ ref	Er(i) ≈	|A ref -A opt | A ref
	with:	Er: relative error ref / opt: simulation from reference / optimized mechanism δ: ignition delay time A: area below the profile


Laina Freyer

Lorea Iturri

Anne Biton

Elisa Gomez

Overlapping Definitive Progenitor Waves Divide and Conquer to Build a Layered Hematopoietic System

Keywords: developmental hematopoiesis, erythro-myeloid progenitors, hematopoietic stem cells, ontogeny, myeloid

EMP-to-HSC switch in fetal liver myelopoiesis occurs late in gestation • EMP are efficient at producing early transit amplifying erythroid and myeloid intermediates • scRNA-seq reveals three trajectories of EMP myelopoiesis • Myeloid lineage commitment during development is cell

INTRODUCTION

Attempts to delineate mechanisms of developmental hematopoiesis are faced with many challenges brought on by the complexity of layering that has evolved to meet the needs of the growing embryo while simultaneously setting the groundwork for a lifetime of hematopoietic maintenance. The persistence versus resolution of different layers of the innate immune system (reviewed in [START_REF] Perdiguero | The development and maintenance of resident macrophages[END_REF] highlights the importance of exploring the link between developmental events and adult disease [START_REF] Bennett | A Combination of Ontogeny and CNS Environment Establishes Microglial Identity[END_REF][START_REF] Honold | Resident and Monocyte-Derived Macrophages in Cardiovascular Disease[END_REF][START_REF] Loyher | Macrophages of distinct origins contribute to tumor development in the lung[END_REF][START_REF] Zhu | Tissue-Resident Macrophages in Pancreatic Ductal Adenocarcinoma Originate from Embryonic Hematopoiesis and Promote Tumor Progression[END_REF]. Furthermore, understanding how hematopoietic progenitor survival, expansion and differentiation is regulated with respect to ontogeny has further translational relevance to the production of immune cells in vitro.

The mammalian hematopoietic system is comprised of mature cells originating from at least two distinct waves of definitive progenitors, erythro-myeloid progenitors (EMP) and hematopoietic stem cells (HSC). EMP are generated from the blood island and vascular plexus of the extraembryonic yolk sac between embryonic days E8.25 and E11.5 [START_REF] Mcgrath | Distinct Sources of Hematopoietic Progenitors Emerge before HSCs and Provide Functional Blood Cells in the Mammalian Embryo[END_REF][START_REF] Kasaai | Erythro-myeloid progenitors can differentiate from endothelial cells and modulate embryonic vascular remodeling[END_REF][START_REF] Lux | All primitive and definitive hematopoietic progenitor cells emerging before E10 in the mouse embryo are products of the yolk sac[END_REF][START_REF] Palis | Development of erythroid and myeloid progenitors in the yolk sac and embryo proper of the mouse[END_REF]. They are responsible for red blood cells that support embryonic survival until birth [START_REF] Chen | Erythroid/myeloid progenitors and hematopoietic stem cells originate from distinct populations of endothelial cells[END_REF][START_REF] Soares-Da-Silva | Yolk sac erythromyeloid progenitors sustain erythropoiesis throughout embryonic life[END_REF] and tissue resident macrophages and mast cells that persist into adult life and replenish independently of HSC [START_REF] Ajami | Infiltrating monocytes trigger EAE progression, but do not contribute to the resident microglia pool[END_REF][START_REF] Gentek | Hemogenic Endothelial Fate Mapping Reveals Dual Developmental Origin of Mast Cells[END_REF][START_REF] Ginhoux | Primitive Macrophages[END_REF][START_REF] Gomez Perdiguero | Tissue-resident macrophages originate from yolk-sac-derived erythro-myeloid progenitors[END_REF][START_REF] Hashimoto | Tissueresident macrophages self-maintain locally throughout adult life with minimal contribution from circulating monocytes[END_REF][START_REF] Hoeffel | C-Myb+ Erythro-Myeloid Progenitor-Derived Fetal Monocytes Give Rise to Adult Tissue-Resident Macrophages[END_REF][START_REF] Schulz | A lineage of myeloid cells independent of myb and hematopoietic stem cells[END_REF][START_REF] Yona | Fate Mapping Reveals Origins and Dynamics of Monocytes and Tissue Macrophages under Homeostasis[END_REF][START_REF] Yona | Fate Mapping Reveals Origins and Dynamics of Monocytes and Tissue Macrophages under Homeostasis[END_REF]. Overlapping with EMP production is the wave of HSC that emerge intraembryonically (Ana [START_REF] Cumano | Lymphoid Potential, Probed before Circulation in Mouse, Is Restricted to Caudal Intraembryonic Splanchnopleura[END_REF][START_REF] Cumano | Intraembryonic, but not yolk sac hematopoietic precursors, isolated before circulation, provide long-term multilineage reconstitution[END_REF][START_REF] Medvinsky | Definitive hematopoiesis is autonomously initiated by the AGM region[END_REF][START_REF] Yvernogeau | Restricted intra-embryonic origin of bona fide hematopoietic stem cells in the chicken[END_REF] from the aorta-gonad-mesonephros (AGM) region and other hemogenic sites (placenta, vitelline and umbilical arteries) between embryonic days E10 and E12 [START_REF] De Bruijn | Definitive hematopoietic stem cells first develop within the major arterial regions of the mouse embryo[END_REF][START_REF] Gekas | The placenta is a niche for hematopoietic stem cells[END_REF][START_REF] Ottersbach | The murine placenta contains hematopoietic stem cells within the vascular labyrinth region[END_REF]. HSC are defined by the ability for longterm multilineage reconstitution when transplanted to adults. Adding to the complexity of these overlapping waves are developmentally restricted HSC that specialize in tissue resident lymphoid output [START_REF] Beaudin | A Transient Developmental Hematopoietic Stem Cell Gives Rise to Innate-like B and T Cells[END_REF][START_REF] Elsaid | Hematopoiesis: a layered organization across species[END_REF][START_REF] Simic | Distinct Waves from the Hemogenic Endothelium Give Rise to Layered Lymphoid Tissue Inducer Cell Ontogeny[END_REF]. Therefore there exist cells that are functionally important in adults but which are only produced during development.

The EMP origin of tissue resident macrophages and mast cells has been described [START_REF] Gentek | Hemogenic Endothelial Fate Mapping Reveals Dual Developmental Origin of Mast Cells[END_REF][START_REF] Gomez Perdiguero | Tissue-resident macrophages originate from yolk-sac-derived erythro-myeloid progenitors[END_REF][START_REF] Hoeffel | C-Myb+ Erythro-Myeloid Progenitor-Derived Fetal Monocytes Give Rise to Adult Tissue-Resident Macrophages[END_REF][START_REF] Schulz | A lineage of myeloid cells independent of myb and hematopoietic stem cells[END_REF], but the extent to which EMP and fetal HSC contribute to other mature hematopoietic cells during development and postnatal life has only recently begun to be revealed for erythroid and lymphoid lineages [START_REF] Elsaid | A wave of bipotent T / ILC-restricted progenitors shapes the embryonic thymus microenvironment in a time-dependent manner A wave of bipotent T / ILC-restricted progenitors shapes the embryonic thymus microenvironment in a time-dependent manner[END_REF][START_REF] Simic | Distinct Waves from the Hemogenic Endothelium Give Rise to Layered Lymphoid Tissue Inducer Cell Ontogeny[END_REF][START_REF] Soares-Da-Silva | Yolk sac erythromyeloid progenitors sustain erythropoiesis throughout embryonic life[END_REF]. Among myeloid cells, it is known that EMP are efficient at generating macrophages and megakaryocytes by direct differentiation within their niche of origin, the yolk sac [START_REF] Mcgrath | Distinct Sources of Hematopoietic Progenitors Emerge before HSCs and Provide Functional Blood Cells in the Mammalian Embryo[END_REF]Iturri et al., 2021). However, knowledge about the regulation of EMP expansion and differentiation once they have seeded the fetal liver is limited. EMP are the first to colonize the fetal liver, followed shortly thereafter by HSC [START_REF] Kieusseian | Immature hematopoietic stem cells undergo maturation in the fetal liver[END_REF], and it is within that environment that they are thought to excel at producing committed intermediate progenitors responsible for transit amplification prior to differentiation.

The differentiation of HSC has long been characterized as a canonical hierarchical cascade of progenitor states based on expression of the cell surface markers CD16/32 and CD34. In this manner, a common myeloid progenitor (CMP) has been isolated from bone marrow that subsequently gives rise to further committed megakaryocyte-erythroid progenitors (MEP) and granulocyte-monocyte progenitors (GMP) [START_REF] Akashi | A clonogenic common myeloid progenitor that gives rise to all myeloid lineages[END_REF]. While this hierarchy is phenotypically and functionally conserved in the E14.5 fetal liver [START_REF] Traver | Fetal liver myelopoiesis occurs through distinct, prospectively isolatable progenitor subsets[END_REF], there were notable differences in burst activity in colony-forming unit (CFU) assays, and a distinction was not made between EMP-and HSC-derived progenitors due to the unavailability of lineage tracing tools at the time. Pulse chase labeling using Tie2 MeriCreMer suggest that HSC do not contribute significantly to GMP and MEP compartments until late in gestation, thereby leading to the hypothesis that they are predominantly of EMP origin [START_REF] Gomez Perdiguero | Tissue-resident macrophages originate from yolk-sac-derived erythro-myeloid progenitors[END_REF].

Identifying fetal immune cells that are of EMP or HSC origin is complicated by many factors. Inherent to EMP and HSC development are their endothelial-to-hematopoietic origins and co-habitation in the fetal liver. This has complicated efforts to distinguish progeny from one another due to many shared cell surface markers and therefore necessitates timed lineage tracing methodologies validated by multiple approaches. Pulse chase labeling has proven indispensable for tracing EMP independently of HSC using Csf1r MeriCreMer mice (Gomez [START_REF] Gomez Perdiguero | Tissue-resident macrophages originate from yolk-sac-derived erythro-myeloid progenitors[END_REF][START_REF] Schulz | A lineage of myeloid cells independent of myb and hematopoietic stem cells[END_REF]. Recently, Cdh5 CreERT2 mice have been used to label EMP or HSC by separating the timing of labeling to encompass endothelial cells that give rise to hemogenic endothelia at different stages [START_REF] Gentek | Hemogenic Endothelial Fate Mapping Reveals Dual Developmental Origin of Mast Cells[END_REF][START_REF] Simic | Distinct Waves from the Hemogenic Endothelium Give Rise to Layered Lymphoid Tissue Inducer Cell Ontogeny[END_REF].

Due to the immunophenotypic similarities between EMP and fetal HSC, the mechanism(s) that distinguish them functionally remains an open question. Genetic manipulations and prolonged in vitro culture from precirculatory concepti support the notion that yolk sac EMP develop from functionally distinct hemogenic endothelia compared to intraembryonic sources of HSC, suggesting a role for cell intrinsic programming [START_REF] Chen | Erythroid/myeloid progenitors and hematopoietic stem cells originate from distinct populations of endothelial cells[END_REF][START_REF] Ganuza | Murine hematopoietic stem cell activity is derived from pre-circulation embryos but not yolk sacs[END_REF]. Both EMP and HSC express the transcription factor MYB, although it is only required for survival of HSC and not EMP [START_REF] Mukouyama | Hematopoietic cells in cultures of the murine embryonic aorta-gonad-mesonephros region are induced by c-Myb[END_REF][START_REF] Schulz | A lineage of myeloid cells independent of myb and hematopoietic stem cells[END_REF][START_REF] Sumner | Initiation of adult myelopoiesis can occur in the absence of c-Myb whereas subsequent development is strictly dependent on the transcription factor[END_REF][START_REF] Iturri | Two Sequential and Independent Pathways of Erythromyeloid Progenitor Commitment in Their Niche of Emergence[END_REF]. Furthermore, HSC rely on blood flow hemodynamic forces and Notch signaling within the AGM whereas EMP are independent of these factors [START_REF] Kasaai | Erythro-myeloid progenitors can differentiate from endothelial cells and modulate embryonic vascular remodeling[END_REF][START_REF] Kumano | Notch1 but not Notch2 is essential for generating hematopoietic stem cells from endothelial cells[END_REF][START_REF] Sumner | Initiation of adult myelopoiesis can occur in the absence of c-Myb whereas subsequent development is strictly dependent on the transcription factor[END_REF]. While intrinsic factors are likely at play in functionally separating EMP from HSC, the impact of their secondary niche cannot be denied. The fetal liver provides a stromal microenvironment important for both structural support as well as a trophic secretion of growth factors utilized in HSPC expansion and commitment [START_REF] Gao | The hematopoietic stem cell niche: From embryo to adult[END_REF]. EMP are highly sensitized to erythropoietin compared to HSC [START_REF] Soares-Da-Silva | Yolk sac erythromyeloid progenitors sustain erythropoiesis throughout embryonic life[END_REF], indicating that a competition for limiting growth factors within the fetal liver niche may act as a driving force for differentiation. Whether the same holds true for myeloid progenitors remains to be determined.

In this study, we utilized Cdh5 CreERT2 and Csf1r MeriCreMer mice for in vivo pulse chase labeling of EMP and HSC.

We found that HSC contributed minimally to myeloid cells during development, primarily monocytes followed by a late production of mast cells and neutrophils just before birth. Rather, the majority of fetal liver myeloid cells were of EMP origin until E16 and could still be found circulating in significant numbers postnatally. This prompted us to trace their origins at the progenitor level with respect to CMP, GMP and MEP classification. This revealed that the phenotypic CMP compartment in the fetal liver was almost entirely populated by HSC whereas EMP rapidly delegated to GMP and MEP intermediates. Around E15, an EMP-to-HSC switch in the production of GMP and MEP was observed followed one day later by a switch in the appearance of mature cells. The generation of mature myeloid cells from both EMP and HSC was lineage-and ontogeny-dependent with uncoupling of granulopoiesis and monopoiesis despite presumptions that they would be produced in an unbiased manner from the same GMP intermediates. This was supported by single cell RNA-sequencing (scRNA-seq) of EMP-derived progenitors in the fetal liver that were largely biased towards mast cell and granulocyte intermediates at E12.5. Underrepresentation of molecular signatures for Kit + presumptive macrophage-producing myeloid progenitors that would be capable of locally giving rise to tissue macrophages suggested that commitment of these progenitors may occur mostly within the yolk sac. This is in line with observations that the intraembryonic trafficking of pre-macrophages peaks at E10.5 and is nearly complete by E12.5 [START_REF] Stremmel | Yolk sac macrophage progenitors traffic to the embryo during defined stages of development[END_REF]. Therefore, the expansion of fetal liver tissue macrophages from E12.5 could be accounted for by local proliferation rather than input from fetal liver myeloid progenitors.

Collectively, we report that HSC are not a predominant source of fetal myeloid cells during development and that the in vivo execution of myeloid differentiation within the mouse fetal liver utilizes molecular programs that differ both in developmental time and lineage selection between EMP and fetal HSC.

RESULTS

HSC do not contribute significantly to mature myeloid cells until late gestation

To determine the level at which HSC contribute to mature hematopoietic cells during development, we analyzed Cdh5 CreERT2 Rosa26 YFP embryos. A critical advantage of this system compared to the Csf1r MeriCreMer Rosa26 YFP approach is that it bypasses lineage bias that may occur due to role of Csf1r in myeloid cells. By taking advantage of spatiotemporal differences in the generation of EMP and HSC from endothelia [START_REF] Gentek | Hemogenic Endothelial Fate Mapping Reveals Dual Developmental Origin of Mast Cells[END_REF][START_REF] Simic | Distinct Waves from the Hemogenic Endothelium Give Rise to Layered Lymphoid Tissue Inducer Cell Ontogeny[END_REF], HSC were selectively labeled by injection of 4-hydroxytamoxifen (OHT) at E10.5, whereas EMP were labeled by injection of OHT at E7.5 with the caveat that this also labeled some precursors of HSC-generating endothelium (Figure S1A-B). To control for inherent variabilities between individual pulse chase labeling manipulations and to take into account the labeling of HSC by both injection timepoints, the percentage of YFP among mature cells was normalized either to the percentage of YFP among microglia (MG, CD45 + Kit neg F4/80 hi CD11b + ) for E7.5 OHT or to the percentage of YFP among LSK (Lin neg Sca1 + Kit + ) for E10.5 OHT (Figure 1A-B). Flow cytometry identified mature erythroid (red blood cell, RBC; megakaryocyte, Mk) and myeloid (mast cell, Mast; macrophage, MF; monocyte, MO; neutrophil, Nt) cells (Figure S1C).

As expected, tissue macrophages (CD45 + Kit neg F4/80 hi CD11b + ) derived predominantly from EMP as reflected by the high percentage of YFP labeling that paralleled that of the microglia (Figure 1A, Figure S1A). The input from HSC to tissue macrophages, starting only at E18.5, was insignificant considering the total number F4/80 hi YFP + macrophages per fetal liver. Furthermore, Kupffer cells retained postnatal labeling that was induced by E7.5 OHT injection in utero (Figure S1B). Other mature myeloid cells, such as monocytes (CD45 + Kit neg F4/80 lo CD11b + CSF1R + Ly6C +/-), neutrophils (CD45 + Kit neg CSF1R neg CD11b + Ly6G + ) and mast cell progenitors (MCp) or mast cells (Lin neg Sca1 neg Kit + Itgb7 hi CD16/32 hi ) [START_REF] Grootens | Deciphering the differentiation trajectory from hematopoietic stem cells to mast cells[END_REF] displayed an EMP-to-HSC switch around E16 (Figure 1A-B). Mature red blood cells (RBC, Lin + CD45 neg Kit neg ) and megakaryocytes (Lin neg CD45 neg Kit neg CD41 + ) also followed this pattern (Figure 1C). Notably, the normalization of labeling among macrophages and megakaryocytes following E7.5 OHT injection did not equilibrate with microglia labeling, supporting the observation that they begin differentiation locally in the yok sac niche at earlier developmental stages [START_REF] Mcgrath | Distinct Sources of Hematopoietic Progenitors Emerge before HSCs and Provide Functional Blood Cells in the Mammalian Embryo[END_REF][START_REF] Iturri | Two Sequential and Independent Pathways of Erythromyeloid Progenitor Commitment in Their Niche of Emergence[END_REF].

Taken altogether, EMP are responsible for generating the majority of tissue macrophages, mast cells and neutrophils during development whereas HSC myeloid output is largely limited to fetal monocytes and late waves of mast cells and neutrophils. The late (>E16) EMP-to-HSC switch in production of mature myeloid cells is also conserved for mature erythroid cells indicating that EMP are given privilege over HSC for erythromyeloid differentiation during embryonic development.

Late commitment of HSC to erythroid and myeloid progenitors

The lack of production of mature erythroid and myeloid cells from HSC in the fetal liver prompted us to examine the ontogeny of lineage commitment at the progenitor level. Using the paradigm of CMP to GMP/MEP commitment [START_REF] Akashi | A clonogenic common myeloid progenitor that gives rise to all myeloid lineages[END_REF][START_REF] Traver | Fetal liver myelopoiesis occurs through distinct, prospectively isolatable progenitor subsets[END_REF], we examined cell surface of expression of CD16/32 and CD34 among lineage traced progenitors (LK, Lin neg Kit + Sca1 neg ) (Figure 2A-B, Figure S2).

Using the Cdh5 CreERT2 Rosa26 YFP pulse chase labeling approach, the relative contributions of EMP or HSC were compared among CMP, GMP, MCp/Mast and MEP populations (Figure 2C, Figure S2C). The same normalization approach was used as described for Cdh5 CreERT2 Rosa26 YFP labeling of mature cells (Figure 1A,C). Erythroid (MEP) and myeloid (GMP and MCp/Mast) progenitor compartments were populated between E12.5 and E15.5 by EMP progeny (labeled by E7.5 OHT). Conversely, CMP appeared to be largely representative of HSC progeny in the fetal liver (labeled by E10.5 OHT). This was better visualized by normalizing YFP + progenitors to YFP + LSK (Figure 2D), since both injection timepoints label LSK. With this representation, it can be seen that the EMP wave never exceeded equilibration with CMP from E12.5 onwards because these CMP were almost exclusively from the HSC wave. HSC progeny began allocating to erythroid and myeloid compartments from around E15 onwards, one day prior to the EMP-to-HSC switch observed for mature cells. The numbers of HSC progeny per fetal liver (Figure S2C) peaked at E16.5 followed by a decline, possibly due to transition in the hematopoietic niche to the bone marrow that occurs prior to birth.

Early amplification erythro-myeloid progenitor intermediates by EMP

Further study of the early expansion and commitment of EMP erythroid and myeloid progenitors using the Cdh5 CreERT2 Rosa26 YFP approach was complicated by the concomitant labeling of EMP and LSK with E7.5 OHT injection. Instead, we used the Csf1r MeriCreMer Rosa26 YFP model that reliably marks newly emerged EMP independently of HSC (Figure 3, Figure S3). Since EMP are produced in the yolk sac successively over the course of several days, we assessed labeling by injection of OHT at E8.5 or E9.5, however later timepoints were not pursued as they result in labeling of HSC [START_REF] Elsaid | A wave of bipotent T / ILC-restricted progenitors shapes the embryonic thymus microenvironment in a time-dependent manner A wave of bipotent T / ILC-restricted progenitors shapes the embryonic thymus microenvironment in a time-dependent manner[END_REF]. Fetal liver LK (Lin neg Kit + Sca1 neg ) were collected between E10.5 and E14.5 and characterized by flow cytometry.

For EMP progeny that were labeled by E8.5 and E9.5 OHT injection, the percentage of YFP labeling among all hematopoietic progenitors (LK) was the same when comparing LK in the yolk sac to those in the peripheral blood. However, the labeling of LK in the fetal liver remained elevated at E11.5 (for E8.5 pulsed) and E12.5 (for E9.5 pulsed) (Figure S3A) indicating an expansion of EMP-derived LK in the fetal liver during these times.

Differences in labeling efficiency of EMP by E9.5 compared to E8.5 OHT injection were observed, perhaps explained by an abundance of EMP-derived erythroid committed progenitors generated in the yolk sac between E9.5 and E10.5 [START_REF] Iturri | Two Sequential and Independent Pathways of Erythromyeloid Progenitor Commitment in Their Niche of Emergence[END_REF] that are no longer expressing Csf1r. There was also higher efficiency of microglia labeling likely due to labeling of pre-macrophages expressing Csf1r at E9.5. Therefore, for comparability of E8.5 and E9.5 pulse chase labeled progenitor cells (LK, Lin neg Kit + ), we could not normalize the percent labeling among LK subsets to labeling of microglia, but rather we normalized to labeling of megakaryocytes (Mk, Kit neg CD45 neg CD41 hi ) (Figure 3A), since Mk at these stages are yolk sac derived [START_REF] Iturri | Two Sequential and Independent Pathways of Erythromyeloid Progenitor Commitment in Their Niche of Emergence[END_REF]. There was limited contribution of EMP to the CMP compartment with either E8.5 or E9.5 OHT injection, whereas EMP-derived GMP, MCp/Mast and MEP expanded at E11.5 and E12.5 respectively (Figure 3A-B). EMP progeny that were pulse chase labeled at E8.5 or E9.5 generated similar numbers of YFP + myeloid progenitors within the fetal liver when quantified 72 hours after the time of OHT injection.

Therefore, erythroid-and myeloid-committed progenitors in the early fetal liver are rapidly generated by EMP. This is followed by late and gradual commitment from HSC-derived CMP, suggesting that fetal HSC may undergo tighter regulation of erythro-myeloid differentiation compared to EMP or that they may compete for signals from the niche. Early EMP-derived myeloid progenitors (GMP and MCp/Mast) from two different timepoints undergo 72 hours of transit amplification prior to differentiation, linking their time of birth in the yolk sac to their time of differentiation, suggesting that this may be intrinsically regulated.

Three pathways of fetal liver EMP myelopoiesis

We observed that the production of mature myeloid cells during development is ontogeny-and lineagespecific. This led us to further examine the molecular basis for myeloid progenitor heterogeneity in the fetal liver using single-cell RNA sequencing (scRNA-seq). Since the ontogeny of erythro-myeloid progenitors in the fetal liver prior to E15 could be traced back to yolk sac EMP, we used Csf1r MeriCreMer Rosa26 YFP embryos pulsed at E8.5 by OHT injection to isolate EMP-derived LK (Lin neg Kit + YFP + ) from E10.5 and E12.5 fetal livers.

We performed massively parallel single-cell RNA sequencing (MARS-seq) [START_REF] Jaitin | Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types[END_REF][START_REF] Keren-Shaul | MARS-seq2.0: an experimental and analytical pipeline for indexed sorting combined with single-cell RNA sequencing[END_REF] because it permits index sorting for retrospective analysis of cell surface markers corresponding to individual cell transcriptomes. 1,590 cells from E10.5 fetal liver and 1,405 cells and E12.5 were analyzed (Figure S4A-C). Due to the overwhelming abundance of erythroid progenitors in the fetal liver, sampling of E12.5 fetal liver MEP was selectively downsized to enrich for non-MEP (see Methods). UMAP representation of clustered cells demonstrated two major pan-myeloid (clusters 2-5) and pan-erythroid (clusters 6-10) branches (Figure 4A) exemplified by up-or down-regulation of the erythroid and myeloid specific transcription factors PU1 (Sfpi1) and GATA1 (Gata1) (Figure S4D).

Clustering was not driven by cell cycle phase (Figure 4B) or differences in embryonic stage (Figure 4C), but rather by expression of cluster specific markers (Figure 4D). Erythroid and myeloid branches were bridged by the EMP cluster that was characterized by combinatorial erythroid and myeloid genes and limited expression of markers that were not shared among other clusters (Figure 4E). To assign a cell type to each cluster, we performed pairwise correlation using the average cluster expression profiles from our dataset compared to those of previously annotated E14 fetal liver hematopoietic cells from the Mouse Cell Atlas project [START_REF] Han | Mapping the Mouse Cell Atlas by Microwell-Seq[END_REF] (Figure S4E). The EMP cluster correlated most closely with stem/progenitor cells while additional myeloid clusters were identified as GP (granulocyte progenitors, highly correlated with Elane hi neutrophils and less with more mature Ngp hi neutrophils) and Mast cells.

Pseudotime analysis traced pathways extending to three budding branches of myeloid progenitor differentiation (Figure 4F). Most represented among these were the clusters of Mast and GP whereas the numbers of progenitors going towards macrophage fate were not well defined. This was evident by the poorly delineated trajectory leading towards a small number of pre-macrophages (cluster 4, Mac), identified as expressing F4/80 (Adgre1/Emr1) that were incidentally captured during the sorting process. This supports the notion that tissue macrophages differentiate in the yolk sac and traffic throughout the embryo from E10.5-E12.5 [START_REF] Stremmel | Yolk sac macrophage progenitors traffic to the embryo during defined stages of development[END_REF] where they can self-propagate within target tissues.

Lineage priming of EMP-derived progenitors in the fetal liver

We observed that EMP in the fetal liver preferentially produce mature mast and neutrophils in vivo and that the progenitors to these mature cells expand from E11.5-E12.5 within immunophenotypically defined GMP and MCp/Mast populations. scRNA-Seq revealed molecular signatures of EMP-derived myeloid progenitors in the fetal liver that were specifically enriched for mast and granulocyte potential, but lacking in monocyte/macrophage progenitor identity. These differential preferences for myeloid lineage output from EMP versus HSC raised the questions of whether EMP myeloid progenitors utilize the same pathways or can be characterized by the same immunophenotypes as those used to study HSC.

To examine cell intrinsic priming of EMP-derived myeloid progenitors in the fetal liver, we selected key transcription factors (TF) involved in lineage priming of adult myeloid progenitors [START_REF] Paul | Transcriptional Heterogeneity and Lineage Commitment in Myeloid Progenitors[END_REF] and examined their average expression levels among each cluster from our scRNA-seq dataset (Figure 5A).

Erythroid priming TF (Phf10 and Klf1 for red blood cells, Fli1 and Pbx1 for megakaryocytes) were highly conserved. Expression of Irf8 was mainly within the Mac cluster (with high levels of Maf) along with lower expression in the MP cluster. Expression of genes identifying monocytes or monocyte progenitors (Ly6c2, Flt3, Ccr2, S100a4) were mostly undetectable (Figure S5A) thereby showing minimal monocyte lineage priming among EMP progeny in the fetal liver. GP expressed high levels of the neutrophil priming TF Cebpe along with low level of Gfi1. The TF Lmo4, identified as basophilic among adult myeloid progenitors, was very highly expressed in the Mast cluster along with other TF identified by our analysis to be specifically enriched among this cluster (Foxo3, Gata2, Sox4).

To determine the molecular relationship between EMP-derived myeloid progenitors in the fetal liver and HSCderived myeloid progenitors from the bone marrow that have been isolated by immunophenotyping (CMP, GMP, MEP), we integrated our dataset with published Smart-seq2 analysis of index-sorted HSPC from adult bone marrow (Figure 5B, Figure S5B) [START_REF] Nestorowa | A single-cell resolution map of mouse hematopoietic stem and progenitor cell differentiation[END_REF]. Considering the failure of EMP to demonstrate lymphoid potential [START_REF] Elsaid | A wave of bipotent T / ILC-restricted progenitors shapes the embryonic thymus microenvironment in a time-dependent manner A wave of bipotent T / ILC-restricted progenitors shapes the embryonic thymus microenvironment in a time-dependent manner[END_REF], it was expected that EMP progeny did not integrate with adult longterm HSC (LT-HSC) or short-term HSC (ST-HSC), nor with HSPC upstream of CMP such as multipotent progenitors (MPP) or lymphoid multipotent progenitors (LMPP). However, adult bone marrow GMP and a subset of CMP locally mapped to regions of the UMAP populated by cells from our EMP, MP and GP clusters. Adult bone marrow MEP followed the same trajectory as EMP-derived MEP although the cells did not integrate until more advanced stages of erythroid differentiation (late_Ery). This may be explained by differences in fetal versus adult erythropoiesis, for example the rapid loss of CD45 expression on fetal red blood progenitors [START_REF] Soares-Da-Silva | Yolk sac erythromyeloid progenitors sustain erythropoiesis throughout embryonic life[END_REF].

Single-cell heterogeneity of EMP-derived myeloid progenitor immunophenotypes

TF and integration analyses showed that EMP-derived myeloid progenitors in the fetal liver share molecular characteristics with adult bone marrow HSC-derived CMP, GMP and MEP. To determine whether the isolation of EMP-derived myeloid progenitors from the fetal liver by immunophenotyping (CMP, GMP, MEP gating by flow cytometry) is predictive of their lineage potential, we generated dot plots of the cells from our scRNA-seq according to the median fluorescence intensity (MFI) of cell surface CD16/23 and CD34 captured by index sorting. Then we overlaid cells from each cluster onto the two-dimensional plots (Figure 6A-B, Figure S6). EMP, represented mainly by E10.5 cells, were localized mostly in the CMP region then more frequently among CD16/32 hi CD34 lo cells at E12.5. Other myeloid progenitors (MP and GP clusters) were also mostly within the CMP gate at E10.5, then later found predominantly in the GP gate at E12.5. Manual gating of MEP was efficient at including the vast majority of erythroid progenitors (EP, early_Ery, mid_Ery and late_Ery clusters, Figure S6) whereas this was largely not predictive for megakaryocyte progenitors (MkP cluster), as has been previously reported for megakaryocyte progenitors in the adult bone marrow [START_REF] Paul | Transcriptional Heterogeneity and Lineage Commitment in Myeloid Progenitors[END_REF].

Notably, the Mast cluster was strongly represented among CD16/32 hi CD34 lo cells demonstrating that nonconventional gating may enrich for mast cell progenitors in the fetal liver. Therefore, we searched for genes that met the criteria of being specifically expressed in the Mast cluster and that encode cell surface proteins for which there are commercially available fluorescently-coupled antibodies. We identified Itgb7 and Il1rl1 (ST2/Il33ra) (Figure 6C) as candidates and observed some fetal liver LK that expressed cell surface ITGB7 at E12.5. As expected based on the scRNA-seq with index sorting, flow cytometry demonstrated that these ITGB7 + LK were present among GMP but more enriched among CD16/32 hi CD34 lo cells (Figure 6C).

Therefore, immunophenotypic GMP in the early fetal liver are EMP-derived and composed of a heterogeneous mix of cells that are molecularly primed for production of neutrophils and mast cells.

DISCUSSION

During development, the fetal liver is the prime hematopoietic organ, supporting differentiation from two unique pools of hematopoietic progenitors with distinct extra-embryonic (EMP) versus intra-embryonic (HSC) origins.

We used two independent genetic pulse chase labeling models to lineage trace the origins of mature cells from EMP or HSC.

Surprisingly, the contribution of HSC to mature myeloid cells in the fetal liver was only evident late in gestation (>E16). Meanwhile, EMP robustly generated mast cells as well as neutrophils that were still found in circulation after birth (data not shown). The significant role of EMP in generating myeloid cells during development is similar to what has been reported for mature erythroid cells [START_REF] Soares-Da-Silva | Yolk sac erythromyeloid progenitors sustain erythropoiesis throughout embryonic life[END_REF]. On the contrary, HSC are an early source of lymphoid cells that cannot be generated by EMP [START_REF] Elsaid | A wave of bipotent T / ILC-restricted progenitors shapes the embryonic thymus microenvironment in a time-dependent manner A wave of bipotent T / ILC-restricted progenitors shapes the embryonic thymus microenvironment in a time-dependent manner[END_REF] and which may be partially replaced later in life by adult HSC. Collectively, our findings have led us to propose a model in which EMP and HSC 'divide and conquer' to build a functional hematopoietic system during development that serves to sustain survival and growth of the embryo while also laying the foundations for a complex layered immune system that is maintained throughout adult life. This division of labor may be a mechanism for managing the increased demands that are unique to the gestational period.

Our study has pinpointed an 'EMP-to-HSC-switch' that occurs around E16 in fetal liver hematopoiesis, demonstrated by ontogeny-specific production of mature cells and reflected at the progenitor level one day earlier. Investigation into the allocation of EMP and HSC to transit amplifying progenitor subsets showed that EMP rapidly generate GMP, MCp and MEP while HSC lag behind in this process. The amplification of MEPderived intermediates occurred 72 hours after their labeling in the yolk sac, regardless of the injection timepoint. This could possibly reflect intrinsic programming or alternatively may indicate the time needed for exposure to factors in the fetal liver niche. On the other hand, HSC were the primary source of phenotypic CMP and only contributed to GMP, MCp and MEP intermediates late in gestation. It remains unknown how these differences in timing are regulated. Addressing this question is complicated by the timing of colonization of the fetal liver niche by EMP and HSC that occurs early, is separated only by 24 hours and is a continuous process that spans several days of EMP and HSC production in their primary niches. Furthermore, the relationship between hematopoietic colonization and maturation of the fetal liver niche would need to be taken into consideration. One possibility is that EMP are more sensitized to growth factors in the niche and therefore outcompete their HSC counterparts. Since EMP do not appear to self-renew in the fetal liver, their depletion with time would then allow for HSC to thrive in their absence.

The predominance of EMP-derived myeloid cells in the early fetal liver led us to further investigate the lineageand ontogeny-specific characteristics of EMP differentiation at the molecular level. scRNA-seq identified three pathways to myeloid cell differentiation from EMP. The pathways to producing mast cells and neutrophils were dominant while there were few progenitors linked to differentiation of macrophages. We attributed this to the early differentiation of macrophages in the yolk sac niche. EMP-derived myeloid progenitors expressed key lineage defining transcription factors showing that many had already been primed for lineage choice. We did not identify gene signatures for monocyte-like progenitors, in line with our in vivo pulse chase labeling results.

Index sorting exposed the molecular heterogeneity of EMP-derived CMP, GMP, MCp and MEP (that were classified by cell surface intensity of CD16/32 and CD34) and demonstrated that conventional gating approaches were not sufficient to isolate lineage primed cells. For example, putative MCp were identified as ITGB7 + cells mainly localized in the CD16/32 hi CD34 lo region but also overlapping with GMP. It will interesting to validate the potential of putative MCp by in vitro colony-forming unit (CFU) assays and to test the enrichment of MCp from the fetal liver using a modified gating approach with ITGB7.

Other studies have proposed an EMP origin of monocytes that pass through a monocyte-dendritic progenitor (MDP) to cMoP (common monocyte progenitor) pathway [START_REF] Hoeffel | C-Myb+ Erythro-Myeloid Progenitor-Derived Fetal Monocytes Give Rise to Adult Tissue-Resident Macrophages[END_REF]. However, our in vivo lineage tracing did not provide evidence for a significant contribution of EMP to fetal liver monocytes. Instead, it appeared that HSC were more likely than EMP to make fetal liver monocytes and that this may largely be regulated by a pathway that was uncoupled to the production of neutrophils, for example via the MDP-cMoP-MO pathway. MDP are defined as CSF1R + Kit + Flt3 + and expression of Flt3 is localized to the HSC-derived CMP compartment of the fetal liver (data not shown). EMP-derived progenitors did not express Flt3 thus making it likely that fetal monocytes generated from MDP intermediates are HSC-derived. However, we cannot exclude the possibility that EMP produce some monocytes through a GMP intermediate [START_REF] Yáñez | Granulocyte-Monocyte Progenitors and Monocyte-Dendritic Cell Progenitors Independently Produce Functionally Distinct Monocytes[END_REF].

It remains unclear whether fetal liver GMP (derived from either EMP or HSC) are capable to generate monocytes/macrophages in vivo. Therefore it is of great interest to isolate EMP-derived versus HSC-derived GMP to first test their differentiation capacity in vitro by CFU assay. It is possible that saturating levels of cytokines will permit production of mixed granulocyte-monocyte/macrophage colonies regardless of ontogeny. This would suggest that lineage decisions made in vivo are driven by the microenvironment. In that case it would be essential to perform adoptive transfer in utero or in neonates to compare the potential of isolated progenitors within the liver niche.

METHODS

Mice

All mice used in this study have been previously described. Experimental procedures, housing and husbandry were conducted in compliance with the regulatory guidelines of the Institut Pasteur Committee for Ethics and Animal Experimentation (CETEA, dap160091). Strains included Csf1r MeriCreMer transgenic (FVB background, MGI:5433683), Rosa26 YFP knock-in (C57Bl6 background, MGI:2449038) and Cdh5 CreERT2 transgenic (C57Bl6 background, MGI:3848982) mice. To generate embryos for pulse chase labeling experiments, Rosa26 YFP/YFP males were crossed to Csf1r MeriCreMer/+ or Cdh5 CreERT2/+ females in timed matings and the date of vaginal plug was considered to be embryonic day E0.5. Embryonic stage was validated by counting somite pairs when possible (E10.5-11.5) or using morphological landmarks.

PCR Genotyping

DNA from tissue biopsy or embryonic sample was extracted using the Hot Shot method : tissue was lysed in 25µL (embryonic tissue) or 50µL (postnatal tissue) of alkaline lysis solution (25mM NaOH, 0.2mM EDTA) at 95°C for 20 minutes then equal amount of neutralizing solution was added (40mM Tris-HCl). PCR was performed using a BIOTAQ kit (Bioline). Csf1r MeriCreMer mice were genotyped using iCre-F-YL (5'-GTCTCCAACCTGCTGACTGTGC-3') and iCre-R (5'-CCAATGCTGTGTCCCTGGTGATG-3') oligos with 65°C annealing temperature (400bp product). Rosa26 YFP mice were genotyped using R_YFP_1 (5'-AAGTCGCTCTGAGTTGTTAT-3'), R_YFP_2 (5'-GGAGCGGGAGAAATGGATATG-3') and R_YFP_3 (5'-GCGAAGAGTTTGTCCTCAACC-3') oligos with 60°C annealing temperature (525bp product for wild-type and 300bp product for knock-in). Cdh5 CreERT2 mice were genotyped using Cre_Fwd (5'-GCCGAAATTGCCAGAATCAG-3') and Cre_Rev (5'-ACATTGGTCCAGCCACCAGC-3') oligos with 60°C annealing temperature (430bp product).

4-Hydroxytamoxifen (OHT) Preparation and Injection

50mg/mL stocks of 4-hydroxytamoxifen (OHT) (Sigma, H7904-25MG) were prepared by resuspending 25mg of OHT in 250µL of ethanol by vortexing for 15 minutes then sonicating for 30 minutes, followed by adding 250µL of Kolliphor (Sigma C5135-500G) and sonicating again for 30 minutes. 60µL aliquots (3mg) were stored at -20°C for up to 6 months. 10mg/mL stocks of progesterone (P3972-5G) were prepared by resuspending 25 mg of progesterone in 250µL of ethanol, vortexing, adding 2250µL of sunflower oil (Sigma S5007-250ML) and storing at -4°C for up to 2 weeks. For pulse labeling, OHT was co-injected with progesterone to reduce the risk of abortion. An injection solution was prepared by thawing 60µL of 50mg/mL OHT and sonicating for 30 minutes, then adding 240µL of 0.9% NaCl and sonicating for 30 minutes, then adding 150µL of 10mg/mL progesterone and sonicating for 30 minutes. For pulse labeling using the Csf1r MeriCreMer strain, females were weighed on day 8 of pregnancy and injected with 11µL/g for final concentration of 75µg/g OHT and 37.5µg/g progesterone. For pulse labeling using the Cdh5 CreERT2 strain, females were weighed on day 7 of pregnancy and injected with 8µL/g for final concentration of 50µg/g OHT and 25µg/g progesterone. Injections were performed using 1mL syringes with 29G needles at 13h. Live births of pulse chase labeled mice were complicated by OHT injection during pregnancy, therefore we performed caesarean sectioning followed by fostering with FVB females that had given birth within less than 5 days.

Flow Cytometry

For embryonic experiments, the protocol for preparing cells for flow cytometry analysis has been previously described in greater detail [START_REF] Iturri | Identification of erythromyeloid progenitors and their progeny in the mouse embryo by flow cytometry[END_REF]. The pregnant mouse was killed by cervical dislocation and the uterus was removed and placed in PBS. Embryos were isolated by opening the uterus and removing the extraembryonic membranes without severing the vitelline and umbilical vessels. To collect peripheral blood, the embryo was separated from the placenta by severing the vitelline and umbilical vessels and rapidly placing the embryo in a 12-well plate with 2mL of 2mM EDTA. Bleeding was facilitated by completely detaching the vitelline and umbilical vessels from the embryo and leaving them for 10 minutes. Organs were dissected in cold PBS and placed in 24-well plates with 500µL cold digestion buffer composed of PBS with 1mg/mL collagenase D (Sigma 11088882001), 100 U/mL DNaseI (DN25-100mg) and 3% Fetal Bovine Serum. When dissection was complete, the digestion plates were placed at 37°C for 30 minutes. Digestion was stopped by transferring tissue to 100µm strainers placed in 6-well plates with 5mL filtered FACS Buffer (0.5% BSA and 2mM EDTA in PBS), then the cells were passed through the strainer by mashing with the piston of a 5mL syringe. Cells were pelleted at 320g for 7 minutes. Blocking was performed with 5% FBS and 1:20 Mouse IgG (Interchim 015-000-003) in FACS Buffer followed by 30 minutes of antibody staining. Cells were washed and incubated with fluorescently-conjugated streptavidin for 20 minutes.

For experiments with adult mice, pieces of organs were patted dry and weighed prior to digestion and 2.4mg

Dispase was added to the digestion buffer. Tissue was minced with scissors before starting digestion. Blood was collected by retro-orbital bleeding. Red blood cell lysis was performed on all organs one time and twice for blood. Bone marrow was flushed from the femur and tibia using a 25G needle. Stained cells were passed on the BD Symphony A5 cytometer (Diva software).

To quantify cells, the following formula was used : (# of cells acquired) x (volume of resuspended cells after staining and washing/volume of cells acquired) x (volume of cell suspension in blocking buffer prior to staining/volume of cells plated for staining). The Symphony does not record volume, so the volume of cells acquired was noted after passing an entire aliquot. Results were analyzed and plots generated using FlowJo.

Antibodies

Single-Cell Library Preparation

Cells were prepared for fluorescence-activated cell sorting (FACS) as described for flow cytometry. Embryos were screened for YFP expression by rapidly dissociating the head with a syringe, filtering, then passing unstained cells on the Beckman Coulter Cytoflex cytometer. YFP + embryos were pooled. Lineage cells (Ter119 + F4/80 + Gr1 + ) were depleted using magnetic anti-biotin Microbeads (1:5) (Miltenyi Biotec 130-090-485) and MS columns . Lin neg Kit + YFP + cells were index sorted using a 70µm nozzle onto 384-well capture plates (10% Triton X-100, 40U/µL RNasin plus, dispensed at 4°C using the Bravo pipetting robot) with 4 wells that were left empty as control. Since MEP represent more than 90% of fetal liver LK at this E12.5, the sorting of E12.5 MEP were limited to half of each plate in order to enrich for myeloid progenitors (this selection was not made for sorting of E10.5 fetal liver). Plates were stored at -80°C until the library preparation step. During library preparation, cDNA from each 384-well plate was divided into two pools termed 'A' and 'H' half-plates which each contained cDNA from 192 uniquely barcoded wells (barcode oligos prepared by Baptiste Saudemont, UTECHS CB). The protocol and reagents for MARS-Seq library preparation have already been described in detail [START_REF] Jaitin | Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types[END_REF][START_REF] Keren-Shaul | MARS-seq2.0: an experimental and analytical pipeline for indexed sorting combined with single-cell RNA sequencing[END_REF].

High-Throughput Sequencing

Libraries were pooled in equimolar amounts of 20fmol per half-plate for final concentration of 1-2nM. Pooled libraries were sequenced using the NextSeq 500/550 High Output Kit v2 for 75 cycles (Illumina FC-404-2005).

Base calling accuracy was greater than 80% (>=Q30, >40G) and 75-80% clusters passed filter. Analyzed data included results from two different sequencing runs. Barcode extraction, alignment, generation of QC reports and creation of umi.tab expression tables were performed by Yann Loe Mie (Bioinformatics and Biostatistics Hub, pipeline available at http://compgenomics.weizmann.ac.il/tanay/?page_id=672). Raw and processed data will be made available on GEO.

Cell and Gene Filtering

The number of UMIs (counts) and features (detected genes) were filtered to eliminate cells with less than 3,000 detected genes. Cells were filtered to remove those that had a mitochondrial gene fraction that was greater than 5%. Median Fluorescence Intensity (MFI) values for CD34 and CD16/32 from index sorting were matched to individual transcriptomes by their well ID and added to metadata of a Seurat object. Doublet detection for each plate was performed using default parameters of scDblFinder then filtered to remove cells classified as doublet. Expressed genes were defined as being detected in at least 5% of cells from each condition (E10.5_Fetal_Liver, E12.5_Fetal_Liver) were intersected across all plates per condition.

Data Normalization, Merging and Clustering

Batch effects due to technical noise were minimized using multiBatchNorm to downscale all batches (i.e. halfplates) to match the coverage of the least-sequenced batch. Feature selection was performed by selecting genes with the largest positive average biological component across all batches. PCA computation was performed on the selected set of genes across all batches using multiBatchPCA which ensures that each batch contributes equally to the definition of the PC space. Batches were then merged using fastMNN to detect mutual nearest neighbors (MNN) of cells in different batches to correct the values in each PCA subspace.

Merging was performed using chosen variable genes selected among all expressed genes and detected within at least 5% of cells across all runs and conditions. Samples were first merged 'by condition' (all half-plates per condition) then 'across conditions' (E10.5 and E12.5). Seurat tSNE and UMAP values were calculated using fastMNN reduction with 1:50 dims. Clustering was obtained by random walks (cluster_walktrap, k=12) on a shared nearest-neighbor (SNN) graph (buildSNNGraph).

Bioinformatic Analysis

Markers for each cluster were identified (findMarkers) using pairwise t-tests to keep genes that were differentially expressed in at least half of the pairwise comparisons with the other clusters (https://osca.bioconductor.org/marker-detection.html). Average expression per cluster was determined using AverageExpression on clusters that were subset using Seurat. Pseudo-time analysis was inferred using slingshot and the EMP cluster was used as a starting point. Genes associated with pseudo-time were obtained by adjusting the p-values using the Bonferroni method. Correlation to the Mouse Cell Atlas was made by comparison with a provided reference matrix and exclusion of cell types that matched less than 10 cells (https://github.com/ggjlab/scMCA). Normalized data from Nestorowa et al. were provided by the Hemberg lab (https://hemberg-lab.github.io/scRNA.seq.datasets, https://github.com/hemberg-lab/scRNA.seq.datasets/)

and cells were integrated using fastMNN. Overlay of cells from each cluster onto two-dimensional flow cytometry plots was performed by defining a bi-exponential scale using ggplot2. Code will be made available on GitHub.

Figure 1

A. B.

Figure 1. The 'switch' to HSC myelopoiesis occurs late and is lineage specific. A. Origins of mature myeloid cells during development as labeled by Cdh5 CreERT2 Rosa26 YFP injection of 4-hydroxytamoxifen (OHT) at E7.5 (left, to label EMP) or E10.5 (right, to label HSC). For E7.5 OHT pulse labeling, the percent of YFP labeling was normalized to % YFP + among microglia (CD45 + F4/80 + , see Figure S1A). For E10.5 OHT, the percent of YFP labeling was normalized to % YFP + among LSK (Lin neg Sca1 + Kit + , see Figure S1A). Red dashed lines indicates the switch between EMP and HSC output at E16. B. Collective representation of EMP and HSC contribution to myeloid lineages from E14 to birth based on pulse chase labeling results. C. Origins of mature erythroid cells as labeled by Cdh5 CreERT2 Rosa26 YFP injection of OHT at E7.5 or E10.5. YFP labeling was normalized using the same approach as in Panel A. MG, microglia; RBC, red blood cell; MCp, mast cell progenitor; MC, mast cell; MO, monocyte; Nt, neutrophil; MF, macrophage. Data are represented as mean ± SEM.

C.

MC

A.

E.

  Figure 2

Figure 2 .

 2 Figure 2. Delayed allocation of fetal HSC to erythroid and myeloid committed progenitor compartments. A. Simplified hematopoieteic progenitor hierarchy superimposed on a Waddington landscape to illustrate the bifurcated cascade of HSC into common myeloid progenitors (CMP) and common lymphoid progenitors (CLP) downstream of multipotent progenitors (MPP). CMP further give rise to megakaryocyte-erythrocyte progenitors (MEP) and granulocyte-monocyte progenitors (GMP). Hematopoiesis in the fetal liver niche is further complicated by the additional layer of EMP that migrate from the yolk sac. B. Gating of CMP, GMP, MEP and MCp/Mast (example from E12.5 fetal liver) progenitor subsets based on cell surface intensity of CD16/32 and CD34 among LK (Lin neg Kit + Sca1 neg ).C. Dynamics of EMP and HSC derived hematopoietic progenitor subsets labeled by Cdh5 CreERT2Rosa26 YFP with E7.5 OHT (left) or E10.5 OHT (right). The percent of YFP labeling among progenitor subsets was normalized to percent YFP among microglia (CD45 + F4/80 + ) for E7.5 OHT or LSK (Lin neg Sca1 + Kit + ) for E10.5 OHT (see FigureS1A). D. Representation of data from Panel C with normalization of both injection timepoints to LSK labeling. MG, microglia; RBC, red blood cell; Mk, megakaryocyte; MCp, mast cell progenitor; MC, mast cell; MO, monocyte; Nt, neutrophil; MF, macrophage; LTi, lymphoid tissue inducer; ILC, innate lymphoid cell. Data are represented as mean ± SEM.

Figure 4 .

 4 Figure 4. Molecular Heterogeneity among Fetal Liver EMP-derived Progenitors. A. UMAP representatiion of Lin negKit + YFP + fetal liver cells isolated from Csf1r MeriCreMer Rosa26 YFP embryos pulsed with E8.5 OHT (1,590 cells from E10.5 and 1,405 cells from E12.5, see FigureS3A-C for strategy and filtering parameters). Cells from two conditions (E10.5 fetal liver and E12.5 fetal liver) were merged using fastMNN and clustered using a walktrap algorithm. Pseudotime was inferred using Slingshot. Cells spread across two major myeloid (clusters 2-5) and erythroid (clusters 6-10) branches. B. UMAP colored by cell cycle phase. Proportion of cell cycle phase assignments per cluster (bar graph) or by condition (pie charts). C. UMAP colored by condition. Proportion of conditions per cluster (bar graph). D. The heatmap shows top 5 selected cluster markers (identified as differentially expressed in at least half of pairwise comparisons). Notably, the EMP cluster was characterized by mixed expression of both myeloid and erythroid genes. E. UpSet plot illustrating shared markers between clusters. Horizontal bars show the total number of markers per cluster. Vertical bars represent the size of the corresponding interaction represented in the dotplot. There were 34 markers specific to the EMP cluster (endothelial cell markers in blue). F. Heatmaps of differential gene expression along inferred pseudotime lineages from the EMP cluster to myeloid cell types (trajectories indicated in Panel A). EMP, erythromyeloid progenitor; MP, myeloid progenitor; GP, granulocyte progenitor; Mac, macrophage; EP, erythroid progenitor; Ery, erythroid; MkP megakaryocyte progenitor.

Figure 5 .Figure 6 Figure 6 .

 566 Figure 5

Figure 3. Transit Amplification of EMP-Derived Erythroid and Myeloid Progenitor Subsets in the Early Fetal Liver. A.

  Dynamics of yolk sac derived EMP labeled by Csf1r MeriCreMer Rosa26 YFP with E8.5 OHT are represented by percent YFP normalized to labeling among megakaryocytes (Mk, Kit neg CD45 neg CD41 hi ). EMP contribute poorly to CMP, but undergo expansion as GMP, MEP or MCp (mast cell progenitor) intermediates. B. Numbers of EMP derived CMP, GMP, MCp/Mast and MEP labeled by Csf1r MeriCreMer Rosa26 YFP with E8.5 OHT or E9.5 OHT in the fetal liver. The number of YFP + fetal liver hematopoietic progenitors peak 72 hours after injection regardless of injection timepoint. Data are represented as mean ± SEM.

ACKNOWLEDGEMENTS

We are indebted to Baptiste Saudemont and Yann Loe-Mie for critical advice, training, reagents and quality control for the MARS-Seq pipeline. We would like to thank Rebecca Gentek, Marc Bajénoff (CIML in Marseille) and Kémy Ade for providing and acquiring exploratory data for Cdh5 CreERT2 experiments, Pascal Dardenne and Yvan Lallemand for handling and injections of mice, Sébastien Bastide and Caroline Kaiser for advice on scRNA-Seq analysis with Seurat, Tobias Weinberger and Rebeca Ponce Landete for isolation of adult tissues, Anne Dejean for transfer of the Cdh5 CreERT2 strain and other members of the Gomez Perdiguero and Cumano groups for critical discussions and feedback. We appreciate the support and advice of the Cytometry and Biomarkers (UTECHS CB) platform (Sophie Novault and Sandrine Schmutz), the Center of Bioinformatics, Biostatistics and Integrative Biology (C3BI), the Institute Pasteur Single Cell Initiative (Heather Marlow) and the Animalerie Centrale. This work was funded by the Institut Pasteur, the CNRS, Revive (Investissement d'Avenir; ANR-10-LABX-73) and the European Research Council ERC investigator award (2016-StG-715320 to E.G.P.) E.G.P. also acknowledges financial support from the Fondation Schlumberger (FRM FSER 2017) and the Emergence(s) program from Ville de Paris (2016 DAE 190). L.I. was supported by a PhD fellowship from the Revive Labex and L.F. by a Florence Gould-Pasteur Foundation fellowship.