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Tracing haematopoietic stem cell formation at single-cell resolution

Nature volume 533, pages 487–492 (2016)Cite this article

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Abstract

Haematopoietic stem cells (HSCs) are derived early from embryonic precursors, such as haemogenic endothelial cells and pre-haematopoietic stem cells (pre-HSCs), the molecular identity of which still remains elusive. Here we use potent surface markers to capture the nascent pre-HSCs at high purity, as rigorously validated by single-cell-initiated serial transplantation. Then we apply single-cell RNA sequencing to analyse endothelial cells, CD45− and CD45+ pre-HSCs in the aorta–gonad–mesonephros region, and HSCs in fetal liver. Pre-HSCs show unique features in transcriptional machinery, arterial signature, metabolism state, signalling pathway, and transcription factor network. Functionally, activation of mechanistic targets of rapamycin (mTOR) is shown to be indispensable for the emergence of HSCs but not haematopoietic progenitors. Transcriptome data-based functional analysis reveals remarkable heterogeneity in cell-cycle status of pre-HSCs. Finally, the core molecular signature of pre-HSCs is identified. Collectively, our work paves the way for dissection of complex molecular mechanisms regulating stepwise generation of HSCs in vivo, informing future efforts to engineer HSCs for clinical applications.

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Figure 1: Identification of T1 pre-HSCs at single-cell resolution.
Figure 2: Enhanced enrichment of T2 pre-HSCs by single-cell RNA-seq.
Figure 3: Global gene expression dynamics during HSC formation.
Figure 4: Specific role of mTORC2 signalling during HSC formation.
Figure 5: Signature genes and cell-cycle heterogeneity of pre-HSCs.

Accession codes

Primary accessions

Gene Expression Omnibus

Data deposits

All of the single-cell and ten-cell RNA-seq data have been deposited in Gene Expression Omnibus under accession numbers GSE67120 and GSE66954.

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Acknowledgements

We thank H. Wu, J. Zheng, and H. Guo for discussion, and S. Hou and L. Zhang for technique support. This work was supported by the Chinese National Key Program on Basic Research (2011CB964800, 2012CB966904, 2012CB966704, 2012CB966604), the National Natural Science Foundation of China (31425012, 31371185, 81400076, 31322037, 81561138005, 81421002, 81561138003, 81370596, 91439128), National Key Program on Stem Cell and Translational Research (SQ2016ZY05002341), and a SKLEH-Pilot Research Grant (ZK12-04 and ZK13-04).

Author information

Author notes

  1. Fan Zhou, Xianlong Li, Weili Wang, Ping Zhu, Jie Zhou and Wenyan He: These authors contributed equally to this work.

Authors and Affiliations

  1. State Key Laboratory of Proteomics, Translational Medicine Center of Stem Cells, 307-Ivy Translational Medicine Center, Laboratory of Oncology, Affiliated Hospital, Academy of Military Medical Sciences, Beijing, 100071, China

    Fan Zhou, Jie Zhou, Wenyan He, Meng Ding, Fuyin Xiong, Xiaona Zheng, Zhuan Li, Yanli Ni & Bing Liu

  2. Biodynamic Optical Imaging Center, College of Life Sciences, Peking University, Beijing, 100871, China

    Xianlong Li, Ping Zhu, Lu Wen & Fuchou Tang

  3. State Key Laboratory of Experimental Hematology, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences, Tianjin, 300020, China

    Weili Wang, Xiaohuan Mu, Tao Cheng, Weiping Yuan & Bing Liu

  4. Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China

    Ping Zhu & Fuchou Tang

  5. Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, 100871, China

    Lu Wen & Fuchou Tang

  6. Collaborative Innovation Center for Cancer Medicine, National Institute of Biological Sciences, Tianjin, 300020, China

    Tao Cheng

  7. State Key Laboratory of Proteomics, Genetic Laboratory of Development and Diseases, Institute of Biotechnology, Beijing, 100071, China

    Yu Lan

  8. Center for Molecular and Translational Medicine (CMTM), Beijing, 100101, China

    Fuchou Tang

  9. Institute of Hematology, Medical College of Jinan University, Guangzhou, 510632, China

    Bing Liu

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Contributions

B.L., F.T., and W.Y. designed the study. F.Z. performed the pre-HSC-related experiments with help from Z.L. and X.Z.; W.W. and W.H. performed the HSC transplantation and HPC assay of Rictor mutant embryos with help from X.M.; Y.N. performed the flow cytometry with help from F.Z.; X.L. performed the single-cell RNA-sequencing; and P.Z. and J.Z. performed the bioinformatics analysis with help from F.X., M.D., and L.W. B.L., F.T., W.Y., and Y.L. wrote the manuscript with support from T.C.

Corresponding authors

Correspondence to Weiping Yuan, Fuchou Tang or Bing Liu.

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Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Identification of pre-HSCs in the E11 AGM region.

a, Expression of VE-cadherin in CD31+CD41lowCD45− cells of the E11 AGM region. b, FACS isolation of T1 pre-HSCs on the basis of AA4.1 expression. c, Donor chimaerism in peripheral blood of recipients receiving cultures of CD31+CD45-CD41lowc-Kit+AA4.1− and CD31+CD45−CD41lowc-Kit+AA4.1+ cells, respectively, 4 weeks after transplantation. d, Multi-lineage repopulation (8–12 weeks) in peripheral blood of secondary recipients (n = 17) receiving HSCs from three reconstituted primary recipients by single T1 pre-HSC-derived co-cultures. Donor-derived (CD45.1+CD45.2+) chimaerism in myeloid (Gr-1+/Mac-1+), B-lymphoid (B220+), and T-lymphoid (CD3+) cells are shown, and ‘a’, ‘b’ and ‘c’ indicate three different mice reconstituted by single-cell co-cultures. e, Expression of VE-cadherin in CD31+CD45+ cells of the E11 AGM region. f, FACS isolation of E11 T2 pre-HSCs with CD41. g, Donor chimaerism in peripheral blood of recipients receiving 6-day co-cultures from CD31+CD45+CD41low population (three cells per recipient, n = 16) monitored at 4, 8, 12, and 16 weeks after transplantation. h, Multi-lineage long-term (>16 weeks) repopulation in peripheral blood, bone marrow, spleen, and thymus of primary recipients transplanted with 6-day co-cultures initiated from the CD31+CD45+CD41low population. Donor-derived (CD45.1+CD45.2+) myeloid (Mac-1+/Gr-1+), B-lymphoid (B220+), and T-lymphoid (CD3+ or CD4+/CD8+) cells are shown in major haematopoietic organs of a representative recipient.

Source data

Extended Data Figure 2 Quality control of the RNA-seq data of single-cell and ten-cell samples.

a, Bar plot of mapping rate to mouse mm9 reference genome of each ten-cell sample. b, Number of detected RefSeq genes (FPKM > 1) in each ten-cell sample. c, Bar plot of mapping rate to mm9 reference genome of each single-cell sample. d, Number of detected RefSeq genes (FPKM > 1) of each single-cell sample. e, Regression fits between average expression level (log2(mean FPKM)) and logarithm-transformed copy number of ERCC RNA molecules spiked into lysis of each single-cell sample. All detected ERCC spike-ins above the expression threshold (FPKM > 1) were used for analysis.

Extended Data Figure 3 Gene expression dynamics during HSC formation.

a, Heat map of expression levels of the FACS markers for ten-cell-pool RNA-seq analysis. b, Heat map of expression levels of FACS markers for single-cell RNA-seq analysis. c, Unsupervised hierarchical clustering of transcriptome profiles of 35 ten-cell samples showing that the samples were accurately grouped together according to their cell types. d, Unsupervised hierarchical clustering of transcriptome profiles of 108 single-cell samples comprising ECs, T1 pre-HSCs, T2 CD41low cells, E12 HSCs, and E14 HSCs. e, Bar plot of RNA expression of Pecam1 (CD31), Itga2b (CD41), and Ptprc (CD45) in the two subpopulations of T2 CD41low cells. f, Endothelial or HSC and HPC markers specifically expressed in CD201-positive T2 CD41low cells as well as other HSC-competent populations, and granulocyte and macrophage markers specifically expressed in the CD201-negative T2 CD41low subpopulation. g, Donor-derived chimaerism in peripheral blood of recipients in the three-cell T2 pre-HSC group (CD31+CD45+c-Kit+CD201high) monitored at 4, 8, 12, and 16 weeks after transplantation. h, Quantification of T2 pre-HSC frequency by limiting dilution analysis.

Source data

Extended Data Figure 4 Global and angiogenesis-related gene expression during HSC formation.

a, Unsupervised hierarchical clustering of 99 single cells. b, The t-distributed stochastic neighbour embedding display of transcriptome profiles of 99 single cells, indicating three major groups as ECs, pre-HSCs, and mature HSCs. c, Pseudo-time analysis of 99 single cells by the Monocle method. d, Heat map of differentially expressed genes between each of the two consecutive stages. The major biological process GO terms enriched in differentially expressed genes are shown to the right. e, Heat map of 58 angiogenesis genes with dynamic expression changes in different cell types. f, Box plot of the number of expressed angiogenesis genes in each individual cell of different cell types. Genes with expression level FPKM > 1 are defined as expressed genes in a single cell. g, Box plot of total expression level (total FPKM) of all of the angiogenesis genes expressed in each individual cell. h, Bar plot of the expression of selected artery (A) and vein (V) genes in each single cell.

Extended Data Figure 5 Signalling pathways enriched in pre-HSCs by GSEA/KEGG analysis.

a, Heat maps of genes enriched in representative signalling pathways. b, GSEA enrichment plot of KEGG signalling pathways. Nominal P value, empirical phenotype-based permutation test (P < 0.05, FDR < 0.25).

Extended Data Figure 6 Morphology and haematopoietic potential of Rictor mutant embryos.

a, Morphology of E10 f/f (37 somite pairs) and Tie2-Cre;f/f (39 somite pairs) embryos. The arrows indicate scattered haemorrhage. b, Cell number of E10 AGM after 72-h organ culture. Data are collected from eight (f/+ or f/f) and two (Tie2-Cre;f/f) embryos. c, d, Representative FACS analysis and quantification of 7-AAD− cells in E10 Tie2-Cre;Rictorf/f and control AGM after 72-h organ culture. Data are collected from three independent experiments using 11 (f/+ or f/f) and 7 (Tie2-Cre;f/f) embryos. e, f, FACS analysis and quantification of CD45+c-Kit+ cells in Tie2-Cre;Rictorf/f and control AGM after organ culture. Data are collected from 3 independent experiments using 11 (f/+ or f/f) and 7 (Tie2-Cre;f/f) embryos. g, h, B-lymphoid potential of the immunophenotypically defined ECs purified from the E10 yolk sac (YS) after co-culture with OP9 stromal cells. Data are mean ± s.d. of three independent experiments using six embryos per genotype. i, Quantification of CFU-Cs in the E10 yolk sac. Data are collected from three CFU-C cultures per genotype in a representative of two independent experiments. j, Schematic experimental design. k, Reconstitution potential of E12.5 AGM in Vav-Cre;Rictorf/f relative to the controls. Symbols represent the donor chimaerism of CD45.2+ cells in peripheral blood of individual recipients 4 months after transplantation. Data are collected from seven (f/+ or f/f) and eight (Vav-Cre;f/f) recipients. l, Donor chimaerism of myeloid (Gr-1+/Mac-1+), B-lymphoid (B220+) and T-lymphoid (CD3+) cells repopulated by the E12.5 AGM region of Vav-Cre;Rictorf/f and control embryos after 4 months of transplantation.

Source data

Extended Data Figure 7 Dynamic expression patterns and network of transcription factors during HSC formation.

a, Heat map of genes showing different expression patterns in ECs and pre-HSCs. Note four distinct expression patterns as highly expressed in pre-HSCs (I), highly expressed in T2 pre-HSCs (II), highly expressed in T1 pre-HSCs (III), and highly expressed in ECs (IV). b, Heat map of genes showing different expression patterns in pre-HSCs (T1 and T2) and mature HSCs (E12 and E14). Note five distinct expression patterns as highly expressed in T1 pre-HSCs (I), highly expressed in E14 HSCs (II), highly expressed in pre-HSCs (III), and heterogeneous in all cell types (IV), and highly expressed in T2 pre-HSCs (V). c, Heat map of expression dynamics of transcription factors highly related to the above patterns in these single cells. d, Network view of transcription factors (TFs) related to different expression patterns determined in Fig. 5b. Transcription factors were arranged using circle layout in Cytoscape. A deeper background colour of the gene names indicates higher correlations of transcription factors to that expression pattern. e, f, Bar plot of expression dynamics of selected transcription factors in single cells showing different expression patterns in distinct cell types.

Extended Data Figure 8 Expression of functional molecules and surface markers during HSC formation.

a, Bar plot of expression of the documented heptad transcription factors in each single cell during HSC formation. b, Bar plot of expression of the definitive HSC-reprogramming factors in each single cell during HSC formation. c, Mean value of expression (FPKM, log2) of upregulated innate immune/inflammatory genes in pre-HSCs and/or HSCs. d, Bar plot of expression dynamics of selected surface markers in single cells showing different expression patterns in distinct cell types. e, FACS sorting of E10 mouse AGM cells into four subpopulations: CD47+ ECs, CD47− ECs, CD47+ pre-HSCs (CD47+CD31+CD41+CD45−Ter119−), and CD47− pre-HSCs (CD47−CD31+CD41+CD45−Ter119−). Symbols represent the donor chimaerism in peripheral blood at 16 weeks after transplantation of co-cultured cells with the four subpopulations, respectively. f, FACS sorting of c-Kit+CD47+ and c-Kit+CD47− subpopulations from the E11 mouse AGM region. Symbols represent the donor chimaerism in peripheral blood of recipients at 4 and 16 weeks after direct transplantation of c-Kit+CD47+ and c-Kit+CD47− subpopulations. g, Multi-lineage long-term (>16 weeks) repopulation in peripheral blood, bone marrow, spleen, and thymus of recipients transplanted with E11 HSCs (c-Kit+CD47+), or with 6-day co-cultures initiated from E10 pre-HSCs (CD31+CD45−Ter119−CD41+CD47+). Donor-derived (CD45.1+CD45.2+) myeloid (Mac-1+/Gr-1+), B-lymphoid (B220+), and T-lymphoid (CD3+ or CD4+/CD8+) cells are shown in major haematopoietic organs of a representative recipient.

Source data

Extended Data Figure 9 Expression pattern of lncRNAs during HSC formation.

a, Bar plot of total copy numbers of the lncRNAs in each individual cell. b, Unsupervised hierarchical clustering of lncRNA expression profiles of 99 samples indicating three major groups as ECs, pre-HSCs, and mature HSCs. c, Heat map of expression dynamics of 35 differentially expressed lncRNAs of each two consecutive developmental stages. Z score with colour from blue to red indicates expression level from low to high. d, Dynamic expression changes of differentially expressed lncRNAs through five developmental stages for each two developmentally consecutive cell types in shaded areas, with the number of differentially expressed lncRNAs listed on the right panel. e, Bar plot of expression dynamics of representative differentially expressed lncRNAs in single cells during HSC formation. f, Bar plot of expression pattern of 26 adult HSC-specific lncRNAs which were documented in ref. 40 in single cells during HSC formation. H19 and Malat1 were significantly expressed in most HSC-related cells. The expression of Meg3 was relatively abundant in ECs and E14 HSCs, and higher expression of Gm15706 was observed in the T1 pre-HSCs.

Extended Data Figure 10 Signature genes and cell-cycle heterogeneity of pre-HSCs.

a, Heat map of 98 pre-HSC signature genes in various cell types. b, Distribution of biological process GO terms of the annotated pre-HSC signature genes. c, Network view of transcription factors in pre-HSC signature genes. A deeper background colour of the gene names indicates higher correlations of transcription factors to the signature gene expression pattern. Highlights in red font represent transcription factors in 98 pre-HSC signature genes. d, Heat map representation of different cell-cycle status in pre-HSCs and adult HSCs. Q, quiescent; P, proliferative. Numbers within brackets indicate the number of single-cell RNA-seq samples. e, Cell-cycle status analysis of the CD31+CD41lowCD45− population by Ki67/7-AAD staining. f, Distinct proliferation capacities of single T1 (CD31+CD45−CD41lowc-Kit+ CD201high) and T2 (CD31+CD45+c-Kit+CD201high) pre-HSCs. The single-cell co-cultures show differential proliferation capacities in vitro, from − /low, medium (hundreds of progeny cells), to high (>1,000 progeny cells) degree. Of note, 11 of the 12 repopulated recipients (four T1 and seven T2 pre-HSCs) received the single-cell co-cultures with high proliferation capacity, and the remaining one (T1 pre-HSC) with medium proliferation capacity.

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Zhou, F., Li, X., Wang, W. et al. Tracing haematopoietic stem cell formation at single-cell resolution. Nature 533, 487–492 (2016). https://doi.org/10.1038/nature17997

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