SINGLE-CELL RNA SEQUENCING-GUIDED FATE-MAPPING TOOLKIT DELINEATES THE CONTRIBUTION OF YOLK SAC ERYTHRO-MYELOID PROGENITORS

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Article Single-cell RNA sequencing-guided fate-mapping toolkit delineates the contribution of yolk sac

erythro-myeloid progenitors Graphical abstract

d

scRNA-seq profiles of early yolk sac identify primitive and definitive subsets of EMPs

d

Csf1r pEMPs generate Csf1r

+

pEMPs

d

Only Csf1r pEMPs contribute to ECs transiently during early embryogenesis

d

pEMPs and dEMPs give rise to different tissue-resident macrophages

Y.X. Zhao, J.Y. Song, X.W. Bao, ..., X.L. Bai, T.B. Liang, J.P. Sheng

Zhao et al. found that Csf1r pEMPs can differentiate into Csf1r

+

pEMPs, and only Csf1r pEMPs are responsible for transiently contributing to endothelial cells during early embryogenesis, suggesting that pEMPs and dEMPs give rise to distinct populations of tissue-resident macrophages.

Zhao et al., 2023, Cell Reports42, 113364 November 28, 2023ª 2023 The Authors.

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Single-cell RNA sequencing-guided

fate-mapping toolkit delineates the contribution of yolk sac erythro-myeloid progenitors

Y.X. Zhao,1,2,3,8J.Y. Song,1,2,3,8X.W. Bao,4,8J.L. Zhang,1,2,3,8J.C. Wu,1,2,3,8L.Y. Wang,5C. He,6W. Shao,7,*X.L. Bai,1,2,3,*

T.B. Liang,1,2,3,*and J.P. Sheng1,2,3,9,*

1Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310002, China

2Zhejiang Provincial Key Laboratory of Pancreatic Disease, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310002, China

3Zhejiang University Cancer Center, Zhejiang University, Hangzhou 310002, China

4Department of Medical Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310002, China

5Eye Center, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, Zhejiang, China

6Infinity Scope Biotechnology Co., Ltd., Hangzhou 311200, China

7College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210000, China

8These authors contributed equally

Erythro-myeloid progenitors of the yolk sac that originates during early embryo development has been sug-gested to generate tissue-resident macrophage, mast cell, and even endothelial cell populations from fetal to adult stages. However, the heterogeneity of erythro-myeloid progenitors (EMPs) is not well characterized. Here, we adapt single-cell RNA sequencing to dissect the heterogeneity of EMPs and establish several fate-mapping tools for each EMP subset to trace the contributions of different EMP subsets. We identify two primitive and one definitive EMP subsets from the yolk sac. In addition, we find that primitive EMPs are decoupled from definitive EMPs. Furthermore, we confirm that primitive and definitive EMPs give rise to microglia and other tissue-resident macrophages, respectively. In contrast, only Kit

+

Csf1r

primitive EMPs generate endothelial cells transiently during early embryo development. Overall, our results delineate the contribution of yolk sac EMPs more clearly based on the single-cell RNA sequencing (scRNA-seq)-guided fate-mapping toolkit.

Erythro-myeloid progenitors emerge in the yolk sac of the mouse embryo at embryonic day 7.25 (E7.25) as the first detectable he-matopoietic progenitors.1 The predominant hematopoiesis output of this E7.25 erythro-myeloid progenitor (EMP) is a large-size nucleated red blood cell expressing embryonic globin genes that is very distinct compared to the adult form of small-size enucleated red blood cells (RBCs). Thus, E7.25 EMPs were also called primitive EMPs.1,2Primitive EMPs could also give rise to macrophage and megakaryocyte lineages.1,3,4

Shortly after the onset of primitive EMPs, the definitive EMP emerges in the yolk sac of the mouse conceptus at E8.25.1 Definitive EMPs produce definitive erythroid and myeloid cell types such as neutrophils, mast cells, and macrophages.5 Both primitive and definitive EMPs are major sources of hemato-poiesis in the early conceptus to cover the developing require-ments before forming a permanent blood system.

It is widely accepted that EMPs generate tissue-resident mac-rophages in the early embryonic development stages. However, the detailed contribution of EMP subsets is debated. Ginhoux et al. suggested that brain-resident macrophages, microglia, originated from primitive EMPs and that other tissue-resident macrophages mainly originated from Myb+ definitive EMP-derived fetal monocytes.2,4,6 On the other hand, Schulz et al. suggested that a single wave of Myb-independent EMPs contributed to all tissue-resident macrophages, including microglia.7

The above findings were mainly based on the Cre/lox fate-mapping system. In such a system, a defined cell population at a selected time was labeled by irreversible activation of the expression of a Cre-responsive reporter transgene driven by a carefully chosen promoter specific to a progenitor. For example, EMPs were often defined as CD45/lowKit+Csf1r+, and the gen-eration of EMPs depends on the Runx1 gene. Thus, Ginhoux et al. mainly utilized Runx1MerCreMerto label EMPs, while Schulz

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et al. mainly utilized Csf1rMerCreMerto label EMPs. After inducible or constitutive activation of Cre recombinase, marked cells are detected later to determine how the originally labeled progeni-tors contribute to specific structures and cell types during pre-and postnatal development.8

Similarly, Plein et al. utilized Csf1rCre, Csf1rMerCreMer, and KitCreERT2lineage-tracing tools to label EMPs and analyze the contribution of EMPs to endothelial cells (ECs). They observed that ECs were tagged by fluorescent reporters in many organs from early embryonic development to the adult stage after tamoxifen induction in the Csf1rCre, Csf1rMerCreMer, and KitCreERT2fate-mapping system, including the heart, lung, and, especially, liver.9Thus, they claimed that the hematopoietic sys-tem’s EMPs served as a complementary source of embryonic vascular endothelium, which lasted into the adult stage.9 How-ever, in an independent study by Feng et al., the authors utilized the same Csf1rMerCreMer lineage-tracing tool and redeveloped Csf1rCreand CD45Crelineage-tracing systems based on different genetic designs. No EC was tagged in any lineage-tracing sys-tems throughout embryonic development. Based on their obser-vation, Feng et al. suggested that EMPs were not the origin of in-traembryonic ECs, and it was unlikely that the contribution of EMPs to ECs could be detected in the adult stage.10

The controversial findings regarding the contribution of EMPs were likely due to two reasons. First, the heterogeneity within the EMP population was not clearly defined. Second, the single pro-moter chosen to drive Cre recombinase expression might not be specific enough. Controversial findings and misinterpretations of the fate-mapping results are often due to the fate-mapping model utilized. To increase the specificity of a fate-mapping model, a Dre/Rox recombination system was introduced in the fate-mapping studies.11Two different promoters, respectively, drove Cre and Dre recombinases, and combinatory usage of Cre and Dre recombinases increases the labeling specificity of progenitors to be studied.12

To solve this discrepancy and determine the contributions from EMPs, we first performed single-cell RNA sequencing (scRNA-seq) for E7.5 and E8.5 YSs (yolk sacs) to dissect EMP heterogeneity comprehensively. Based on the EMP subsets identified, we developed three fate-mapping systems for each subset using Cre and Dre systems. With the scRNA-seq-guided fate-mapping system design, we could delineate the contribu-tions of EMPs more accurately.

Single-cell atlas of early mouse YS

The heterogeneity of EMPs may cause a discrepancy in the EC ontogeny study. However, the heterogeneity of EMPs was not addressed clearly in the previous study.9,10Thus, we first per-formed scRNA-seq for E7.5 and E8.5 YSs for comprehensive characterization of EMPs’ heterogeneity (Figures 1A and S1) with scRNA-seq technology.13 38,099 cells were sequenced with high quality, and 14 cell populations were found (Figures 1B and 1C). The cell count, frequency, and top 3 feature genes are shown (Figures 1C and 1D). The cell population’s iden-tity was annotated by SingleR with manual assistance based on

their feature gene expression since the reference for early mouse YS cells was inadequate (Figures 1B–1D;Table S1).

Cluster 0 (15,507 cells, 40.70%) was defined as erythroid cells due to the high expression level of hemoglobin (hemoglobin beta adult t chain [Hbb-bt]) (Figure 1D). Cluster 1 (9,321 cells, 24.47%) carried epithelial marker Ttr14and Epcam and was defined as Ttr+epithelial cells.15Cluster 2 (4,296 cells, 11.28%) was defined as ECs due to the expression of endothelial markers such as Vwf, Sparc, and Col4a216–18(Figure 1D).

Cluster 3 (3,416 cells, 8.97%) was defined as definitive EMPs due to high expression levels of Kit and Myb and a low level of CD45 (Kit+CD93CD45/lowMyb+), consistent with the previous description of definitive EMPs (Figures 1D and 1E).2In addition, Pf4, the marker found in early hematopoietic progenitors, was also identified in part of the cluster 3 definitive EMP cells19–22 (Figures 1D and 1E). Cluster 4 (1,650 cells, 4.33%) expressed high levels of Kit and CD93 and low levels of CD45 and Myb (Figures 1D and 1E). Thus, cellular cluster 4 was defined as prim-itive EMPs (Kit+ CD93+ CD45/low Myb).7 Please note that although both primitive EMPs and definitive EMPs were CD45/low and Kit+, primitive EMPs were CD93+Myb, while definitive EMPs were CD93Myb+. In addition, cluster 3 defini-tive EMPs emerged at E8.5, and cluster 4 primidefini-tive EMPs ap-peared at E7.5 (Figure 1F). The emergence timing also supported that cluster 3 was the definitive EMP and cluster 4 was the prim-itive EMP.

Cluster 5 (530 cells, 1.39%) cells were defined as hemogenic ECs since they expressed Mdk, Hmga2, and Meis2, all of which were detected in hemogenic ECs.23–25 Cluster 6 (675 cells, 1.77%) cells were defined as fibroblasts since a high amount of collagen was detected in cluster 6 (Figure 1D). Cluster 7 (1,136 cells, 2.98%) cells were defined as megakaryocyte pro-genitors due to their specific expression of Kit, Rap1b, and Tmsb4x.26,27 CD41 is a widely recognized marker for EMPs and megakaryocytes.28,29 As expected, our findings demon-strate that CD41 is expressed in definitive EMPs, primitive EMPs, and megakaryocyte progenitors (cluster 3, 4, and 7) in

Figures 1B and 1E.

Cluster 8 (668 cells, 1.75%) cells were defined as epithelial stem cells since they expressed epithelial marker Krt1830and Bex2, an important transcription factor for stemness maintenance31,32(Figure 1D). Cluster 9 (457 cells, 1.20%) ex-hibited significantly elevated expression of macrophage markers, including Lyz2, Cd74, and Cd68,33 as shown in

Figures 1D and 1E, confirming its categorization as a macro-phage population. Additionally, the presence of S100A8, S100A9, and major histocompatibility complex (MHC) class II expression further supported the identification of cluster 9 as maternal macrophages, as these markers were not expressed in fetal macrophages. These findings raise the possibility of maternal cell contamination.34 Cluster 10 cells (453 cells, 1.19%) were cytotoxic cells, and they expressed cytotoxic mol-ecules granzymes D and G (Figure 1D). Cluster 11 (211 cells, 0.55%) cells were identified as smooth muscle cells due to Tac2 and Pdgfrb expression35(Figure 1D). Cluster 12 (182 cells, 0.48%) was defined as tissue-resident macrophages since they expressed high levels of complement C1q B chain and Cd68 (Figure 1D).36 To elucidate the differences between the two

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Figure 1. scRNA-seq profiling of YSs

(A) Experimental scheme of scRNA-seq profiling of yolk sacs (YSs). YSs at E7.5 and E8.5 were collected, and scRNA-seq was performed for comprehensivecharacterization of EMP heterogeneity.

(B) 14 major populations are shown by t-distributed stochastic neighbor embedding (tSNE). Cell populations 0–13 were annotated based on their feature geneexpression.

(C) Cell count and proportion of 14 major populations.

(D) Heatmap showing the scaled expression level of top 3 feature genes for each cell population. The dot size indicates the percentage of cells that express thefeature gene, and the color indicates the average expression level.

(E) tSNE plots showing the expression of Kit, CD93, Ptprc (CD45), Myb, Pf4, Itga2b, Hbb-bh1, Cx3cr1, and Mrc1 at E7.5 (top) and E8.5 (bottom).(F) Split tSNE plots showing the cell distribution of the 14 major populations at E7.5 and E8.5.

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macrophage clusters in Figure 1, we compared their gene expression profiles. Our analysis revealed that these clusters exhibit distinct gene expression patterns, which may imply diver-gent functional roles or developmental stages for these macro-phages. The corresponding top 20 feature genes for each subset are provided inTable S1.

Cluster 13 (127 cells, 0.33%) was identified as a minor contamination of placenta cells, as evidenced by the expression of Ctla2a and Cryab37,38(Figure 1D). Given the developmental stage at which our study was conducted, it is currently imprac-tical to distinguish between YSs and other embryonic tissues that eventually contribute to placenta formation, such as allan-tois and chorion.

Overall, we profiled YS cells at E7.5 and E8.5 and discovered both primitive and definitive EMPs, which mainly differed in CD93 and Myb expressions.

Dissection of the heterogeneity of primitive and definitive EMPs

EMPs were our focus, and we wanted to dissect the EMP hetero-geneity further. In order to comprehensively analyze the primitive and definitive EMP populations, we conducted re-clustering and included all of the different definitive EMP (dEMP) clusters iden-tified in Figure 1B in our downstream analysis. Four subsets within primitive EMPs could be found (Figure 2AI). Feature genes for each subset were defined, and the top 3 feature genes were shown (Figure 2AII). These four subsets could be generally divided into two groups. Subsets 0, 2, and 3 formed a Kit+ Csf1rgroup, while subset 1 formed a Kit+Csf1r+group ( Fig-ure 2B, feature plot). In addition, we noticed that 2 out of the top 3 feature genes of Csf1r+CD11b+F4/80+EMPs (subset 1) were macrophage markers, including Lyve139–41 and Mrc1 (CD206)42(Figure 2AII), implying that Csf1r+EMPs were progen-itors for primitive macrophages. In addition, we have highlighted Cx3cr1 and Mrc1 in the t-distributed stochastic neighbor embedding (tSNE) plot presented inFigure 1E, which demon-strates that Cx3cr1 is predominantly enriched in tissue-resident macrophages (cluster 12), while Mrc1 is mainly enriched in prim-itive EMPs.

Furthermore, we noticed that subset 0 of primitive EMPs ex-pressed a high level of hemoglobin chains, including the embry-onic form of the hemoglobin beta chain, Hbb-bh1 (Figures 1E and

2AII). We also noticed that macrophage-oriented primitive EMPs

(subset 1) quickly shrunk from E7.5 to E8.5 (Figure 2C), indicating a transient wave of primitive macrophages. Then, we performed a pseudo-time analysis of primitive EMPs, and subset 0 primitive EMPs (pEMPs) were in the earliest node of differentiation ( Fig-ure 2D). Subset 1 EMPs were in the latest node of differentiation. Furthermore, we performed RNA velocity43analysis for pEMPs, which showed clearly that subset 0 gave rise to other subsets (Figure 2E). Both pseudo-time and RNA velocity results sug-gested that Csf1rpEMPs (Hbb-bH1+) were the progenitors for Csf1r+pEMPs, which were further differentiated by group skew-ing to the macrophage lineage compared with Csf1rpEMPs, consistent with the previous report that Hbb-bh1 was devoid from ECs and started to be expressed at E7 in YS EMPs.44

Similarly, four dEMP subsets (Figure 2AIII–2AIV) could be iden-tified and broadly separated into three categories. CD31+Myb CD45subset 2 (ECs), CD31Myb+CD45subset 0 (dEMPs), and CD31MybCD45+differentiated immune cells, including subset 1 (macrophage biased) and subset 3 (neutrophil biased) (Figure 2B). The macrophage-biased subset was found to ex-press C1qb and CD74, both of which are detectable on macro-phages. In contrast, the neutrophil-biased subset expressed the typical neutrophil marker MPO, as shown inFigure 2AIV, and it was clear that dEMP subsets appeared around E8.5 (Figure 2C). Pseudo-time analysis of dEMPs showed that subset 2 EMPs were in the earliest node of differentiation (Figure 2D), consistent with their CD31+MybCD45EC identity. CD31MybCD45+ subsets 1 and 3 were in the latest node of differentiation, consis-tent with the Myb CD45+ Csf1r+ macrophage phenotype (subset 1). However, RNA velocity analysis did not show a clear trend of development (Figure 2E).

Regarding the relationship between the tissue-resident mac-rophages (clusters 12) in Figure 1and the Kit+Csf1r+pEMPs (Figure 2), we included the tissue-resident macrophages from

Figure 1in the RNA velocity analysis inFigure S2. Considering the potential contamination of maternal cells in the maternal macrophage (cluster 9) in Figure 1, we did not include the maternal macrophage in RNA velocity analysis in order to ensure a more accuracy representation of the developmental trajectory of fetal macrophage. The updated analysis provides further in-sights into the dynamic transcriptional changes and potential developmental trajectories of these macrophage populations. We noticed that resident macrophages were derived from Kit+ Csf1r+pEMPs.

Figure 2. Primitive and definitive EMP subsets

(A) Primitive EMPs were further re-clustered into four subsets, shown in the uniform manifold approximation and projection (UMAP) plot in (AI). Subsets 0, 2, and 3formed the Kit+

Csf1rCD11bF4/80group (red circle), and subset 1 formed the Kit+

group (blue circle). Heatmap showing the scaledexpression levels of the top 3 feature genes for each subset of primitive EMPs is in (AII). Definitive EMPs were re-clustered into five subsets, shown in (AIII). Cluster2 formed CD93KitCD45Pecam+

endothelial cells (ECs) (red circle). Cluster 0 formed CD93Kit+

definitive EMPs. Clusters 1 and 3 formedCD93KitCD45+

Mybmature immune cells, including Csf1r+

monocytes and macrophages (yellow circle). Heatmap showing the scaled expression level ofthe top 3 feature genes for each subset of definitive EMPs is in (AIV).

(B) Expression levels of feature markers of Kit, CD93, Ptprc (CD45), Myb, Pecam1, Csf1r, Adgre1, and Itgam are shown in the UMAP plots, separated by primitive(top) and definitive (bottom) EMP populations.

(C) UMAP plots showing the primitive EMP subsets and definitive EMP subsets at E7.5 and E8.5.

(D) Pseudo-time analysis of primitive and definitive EMP subsets. Potential trajectory of primitive (top) and definitive (bottom) EMP subsets identified distinct cellfates colored by cluster. The branches show the potential evolutionary direction in the trajectory.

(E) RNA velocity analysis was performed to infer developmental lineages and cellular dynamics of primitive (top) and definitive (bottom) EMP subsets.(F) Heatmap showing the transcriptional factor activities inferred by SCENIC analysis in primitive (top) and definitive (bottom) EMP subsets. The color indicates theintensity of regulon activity for each transcription factor (TF) in the primitive EMP (pEMP) and definitive EMP (dEMP) subsets.

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Additionally, we have compared the Csf1r+pEMP and macro-phage-biased dEMP populations and noted that Csf1r+pEMPs were more specialized in morphogenesis, while macrophage-biased dEMPs were specialized in immune response (Figures S3A and S3B). We also provided a better explanation for the relationship between the EC cluster inFigure 2AIII and the main ECs inFigure 1. We have performed differential gene expression analysis, which suggests that the EC cluster in Fig-ure 2AIII represents a distinct subset of ECs that have undergone further differentiation. Our analysis has revealed that the main EC population was more specialized in development and angiogen-esis, while the ECs inFigure 2AIII were more specialized in im-mune functions (Figures S3C–S3E). Moreover, we compared cluster 5 (hemogenic ECs) inFigure 1B with cluster 0 in the dEMPs inFigure 2AIII and observed that hemogenic ECs were more specialized in development and morphogenesis, while cluster 0 dEMPs were more specialized in coagulation pro-cesses compared to hemogenic ECs (Figures S3F and S3G). These findings provide further insights into the heterogeneity and functional diversity of ECs in different developmental stages. Next, we performed SCENIC analysis for both pEMPs and dEMPs (Figure 2F). We noticed distinct transcription require-ments for different EMP subsets. Ets1 and Elk3 seemed impor-tant for the macrophage-oriented pEMP subset 1, and Klf1 seemed involved in developing pEMP subset 0.

In terms of dEMPs, Maf seemed to regulate the CD45+Csf1r+ monocytes/macrophages (dEMP subset 1), consistent with the previous report about the critical role played by the Maf family within macrophages,45,46and Mef2c was found to be involved in the regulation of CD31+subset 2, consistent with the previous report that Mef2c was pivotal for the hematopoietic progenitor generation from hemogenic ECs.47

Overall, we identified two CD93+MybpEMP subsets (Csf1r and Csf1r+pEMPs), one CD93Myb+dEMP subset, and the CD45+Csf1r+monocyte/macrophage population. In addition, trajectory analysis and RNA velocity results suggested that Csf1rpEMPs gave rise to Csf1r+pEMPs.

Independence of pEMPs and dEMPs

Next, we wanted to determine the relationship between pEMPs and dEMPs. Although progeny of pEMPs and dEMPs were quite distinct,2,5the independence between pEMPs and dEMPs has not been validated in a proper fate-mapping model. The previous

model utilized was not specific enough. For example, E8.5 tamoxifen treatment in Csf1rMerCreMertagged Kit+Csf1r+pEMPs and CD45+ Csf1r+ monocytes/macrophages, and tamoxifen treatment in KitMerCreMer and Runx1MerCreMer mice could tag both pEMPs and dEMPs (Figure 3A).

Three models were developed for each EMP subset ( Fig-ure 3B). The fetal form of the hemoglobin Hbb-bH1 gene was shown to be explicitly expressed in Kit+ Csf1r pEMPs via scRNA-seq (Figure 2AI). The expression specificity of Hbb-bH1 was also validated at the protein level by fluorescence staining (Figure S4A). Hbb-bH1 was not detected in CD31+ECs (precur-sor for EMP generation) or Csf1r+cells (Kit+Csf1r+pEMPs or monocytes/macrophages) (Figure S4B). An Hbb-bH1Cremouse (model I) was constructed, and the Cre transgene was inserted into the 30UTR of Hbb-bH1 to avoid the disruption of the original gene (Figure S4C). To specifically tag Kit+Csf1r+pEMPs, the KitMerCreMermouse was crossed to the Csf1rDreERT2mouse, fol-lowed by mating with the LSL-RSR-tandemTomato reporter mouse (model II; Figures 3B and S4C). Similarly, KitMerCreMer mice were crossed to MybDreERT2mice to tag Myb+Kit+Csf1r dEMPs (model III;Figures 3B andS4C).

We established a flow cytometry gate strategy for different EMP subsets based on scRNA-seq analysis. First, pEMPs and dEMPs were separated by CD93. CD93+pEMPs consisted of Kit+Csf1r pEMPs and Kit+Csf1r+pEMPs. CD93CD45/low Kit+ Csf1r cells were defined as dEMPs, and CD93 Kit CD45+Csf1r+cells were identified as monocytes/macrophages (Figure 3C).

In the model I fate-mapping system, Kit+ Csf1r and Kit+ Csf1r+pEMPs were labeled, indicating that Kit+Csf1r+pEMPs were derived from Kit+Csf1r progenitors, and neither Myb+ Kit+Csf1rdEMPs nor CD45+Csf1r+monocytes/macrophages were labeled, proving the independence of pEMPs and dEMPs (Figures 3D and 3E).

In the model II fate-mapping system, only Kit+Csf1r+pEMPs were tagged, showing that Kit+ Csf1r+ pEMPs could not generate Kit+ Csf1r pEMPs in a reverse way, and dEMPs were not labeled either, further proving the independence of pEMPs and dEMPs (Figures 3D and 3E).

In the model III fate-mapping system, both Myb+Kit+Csf1r dEMPs and CD45+ Csf1r+ monocytes/macrophage were labeled, indicating that CD45+Csf1r+monocytes/macrophages were derived from Myb+Kit+Csf1rdEMPs (Figures 3D and 3E)

Figure 3. Independence of pEMPs and dEMPs revealed by fate-mapping toolkits

(A) Summary of three previously established fate-mapping models and their associated tagging populations, including Csf1rMerCreMer, Runx1MerCreMer, andKitMerCreMer

. These models have been used to trace the developmental fate of EMPs in previous studies.

(B) Mating and experimental strategy of three fate-mapping tools used in this study to trace the developmental fate of EMPs. Model I involves the use of respectively. Tamoxifen was administered to models II and III at E8.5, and YS tissue was collected at E10.5 from all three models for fate-mapping analysis.(C) Gating strategies used to isolate different EMP subsets for scRNA-seq analysis. CD93+CD45/lowcells were identified as pEMPs and further separated intoKit+

Csf1rand Kit+

subsets based on their expression of these markers. Kit+

CD93CD45/lowcells were identified as dEMPs and were separated fromLSL-RSR-tan-demTomato (n = 6, 8, and 5), respectively. The histograms show the expression levels of YFP (model I) and tanLSL-RSR-tan-demTomato (models II and III) in EMPs.(E) Statistical results of fate-mapping reporters in EMPs from the different fate-mapping models used in this study. Model I utilizes Hbb-bH1Cre

LSL-RSR-tandemTomato, respectively. Data are pre-sented as means± SEM of 6, 8, and 5 embryos in each group from 2 independent experiments.

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since CD45+Csf1r+monocytes/macrophages did not express Kit or Myb (Figure 2B). In addition, pEMPs were not tagged in the model III fate-mapping system, indicating that the reversal generation from dEMPs to pEMPs was not likely.

Overall, we developed three specific fate-mapping systems for each EMP subset based on the scRNA-seq results, and we showed that pEMPs and dEMPs were independent of each other.

Kit+myb+hematopoietic progenitors contribute to most tissue-resident macrophages

The ontogeny of macrophage origin has been hotly debated48; thus, we decided to trace the contribution of early hematopoietic progenitors through the newly developed fate-mapping tools. We have included the gating strategy for each tissue-resident macrophage inFigure S5. Microglia were efficiently labeled in the Hbb-bH1Cre constant fate-mapping system and the KitMerCreMer::Csf1rDreERT2inducible fate-mapping system, which corresponded to the Kit+Csf1rpEMP and Kit+Csf1r+pEMP subsets, indicating microglia were derived pEMPs (Figures 4A and 4B). In contrast, other resident macrophages in the colon, kidney, lung, spleen, and peritoneum were mainly tagged in KitMerCreMer::MybDreERT2(Figures 4A and 4B). In addition, epithe-lium Langerhans cells were tagged in Hbb-bH1Cre, KitMerCreMer:Csf1rDreERT2, and KitMerCreMer::MybDreERT2 fate-map-ping systems, indicating that both pEMPs and dEMPs contrib-uted to Langerhans cells (LCs) (Figures 4A and 4B).

We have conducted additional experiments to investigate the contribution of pEMPs and dEMPs to tissue-resident macro-phages during fetal development. Our results demonstrate that, in both models I and II, the contribution from pEMPs to liver tissue-resident macrophages decreases over time, while the contribution from dEMPs increases during fetal development. Interestingly, in model III, we observed a different trend, with the contribution from dEMPs increasing throughout fetal devel-opment (Figure S6). Our results were in good accordance with Ginhoux et al.2,4that primitive macrophages gave rise to micro-glia and that Myb+dEMPs contributed to most tissue-resident macrophages.

Only Kit+Csf1rpEMPs contributed to ECs

After the dissection of heterogeneity within the EMP population, we wanted to analyze the contribution of the Kit+Csf1r and Kit+Csf1r+EMP subsets to ECs. Since EMPs are known to be precursors of microglia,49,50 microglia-labeling efficiency was used as an internal reference. Like the previous tamoxifen-induc-tion schedule inFigure 3B, we treated KitMerCreMer::Csfr1DreERT2 and KitMerCreMer::MybDreERT2 fate-mapping mice with tamox-ifen at E8.5, and the Hbb-bh1Cremice allowed consecutive

label-ing of Csf1r+/pEMPs. Brain and YS from the E10.5 embryos were harvested and analyzed.

Brain microglia were gated as CD45intCD11b+F4/80+, and ECs were gated as CD45CD11bCD31+(Figure 5A), and we noticed that brain ECs and YS ECs were negative for Kit expres-sion (Figures 5B andS4B).

After E8.5 tamoxifen treatment in KitMerCreMer::Csf1rDreERT2 fate-mapping mice, about 0% of ECs were tagged by tandemTomato, and 20% of microglia were tagged. In contrast, after E8.5 tamoxifen treatment in KitMerCreMer MybDreERT2 fate-mapping mice, about 0% of ECs and microglia were tagged (Figures 5C and 5D).

In the Hbb-bh1Crefate-mapping mouse model, brain microglia were labeled at very high efficiency at 80% due to constitutive expression of Cre driven by Hbb-bh1, while ECs were labeled at about 20% (Figures 5C and 5D). This result suggested that ECs were partially derived from Csf1rpEMPs, as Csf1r+pEMPs did not generate any ECs (Figures 5C and 5D).

Fate-mapping results based on three different models sug-gested that EMPs could contribute to ECs partially and that only the Kit+Csf1rsubset of pEMPs could generate ECs. Kit+Csf1rEMPs served as a transient source of vascular endothelium at the early embryonic stage Next, we wanted to see if Csf1rpEMP-derived ECs at the early embryonic stage would persist during fetal development.9Since we already showed that ECs could only be tagged in the Hbb-bh1Creconstitutive labeling mouse, we analyzed the later time points only in this fate-mapping model. ECs from organs, including the brain, liver, heart, and spleen, were analyzed at different time points (Figure 6A).

We found that the proportion of YFP+ECs in the brain was about 20% at E10.5 (Figures 5C and 5D), and less than 2% of YFP-tagged ECs were detected in brain and fetal liver at E13.5, with the microglia-labeling efficiency around 80% at E13.5 (Figures 6B and 6C) in Hbb-bh1Cremice.

Next, we selected another time point during mouse develop-ment, pre-birth (E18.5–E19), to investigate the contribution to ECs by EMPs throughout mouse fetal development. Different or-gans were collected and analyzed, including the brain, heart, liver, and spleen. In the Hbb-bh1Cre fate-mapping mice, we showed that very few labeled ECs were found at the pre-natal stage, while the YFP-labeling efficiency of microglia reached about 80% (Figures 6B and 6C).

Therefore, fate-mapping results based on the Hbb-bh1Cre strain further confirmed that Kit+Csf1r pEMPs contributed ECs to blood vessels only transiently at the early embryonic stage and that vascular ECs derived from EMPs were barely found at the pre-birth stage.

Figure 4. Ontogeny of adult tissue-resident macrophages

(A) Representative histogram showing the expression levels of fate-mapping reporters in various adult tissue-resident macrophages following theexperimental settings shown inFigure 3B. Fate mapping was performed using Hbb-bH1Cre

::LSL-YFP (model I) and KitMerCreMer

::LSL-RSR-tan-demTomato/KitMerCreMer

LSL-RSR-tandemTomato (models II and III). The histograms show the expression levels of YFP (model I) andtandemTomato (models II and III) in different tissue-resident macrophages. The gating strategies are shown inFigure S5.

(B) Statistical results of fate-mapping reporters in various adult tissue-resident macrophages following the experimental settings shown inFigure 3B. Fatemapping was performed using Hbb-bH1Cre

::LSL-YFP (model I) and KitMerCreMer

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SINGLE-CELL RNA SEQUENCING-GUIDED FATE-MAPPING TOOLKIT DELINEATES THE CONTRIBUTION OF YOLK SAC ERYTHRO-MYELOID PROGENITORS

Article Single-cell RNA sequencing-guided fate-mapping toolkit delineates the contribution of yolk sac

erythro-myeloid progenitors Graphical abstract

scRNA-seq profiles of early yolk sac identify primitive and definitive subsets of EMPs

Csf1r pEMPs generate Csf1r

pEMPs

Only Csf1r pEMPs contribute to ECs transiently during early embryogenesis

pEMPs and dEMPs give rise to different tissue-resident macrophages

Y.X. Zhao, J.Y. Song, X.W. Bao, ..., X.L. Bai, T.B. Liang, J.P. Sheng

Zhao et al. found that Csf1r pEMPs can differentiate into Csf1r

pEMPs, and only Csf1r pEMPs are responsible for transiently contributing to endothelial cells during early embryogenesis, suggesting that pEMPs and dEMPs give rise to distinct populations of tissue-resident macrophages.

Single-cell RNA sequencing-guided

fate-mapping toolkit delineates the contribution of yolk sac erythro-myeloid progenitors

Csf1r

primitive EMPs generate endothelial cells transiently during early embryo development. Overall, our results delineate the contribution of yolk sac EMPs more clearly based on the single-cell RNA sequencing (scRNA-seq)-guided fate-mapping toolkit.

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