Arteries and veins are specified by antagonistic transcriptional programs. However, during development and regeneration, new arteries can arise from pre-existing veins through a poorly understood process of cell fate conversion. Here, using single-cell RNA sequencing and mouse genetics, we show that vein cells of the developing heart undergo an early cell fate switch to create a pre-artery population that subsequently builds coronary arteries. Vein cells underwent a gradual and simultaneous switch from venous to arterial fate before a subset of cells crossed a transcriptional threshold into the pre-artery state. Before the onset of coronary blood flow, pre-artery cells appeared in the immature vessel plexus, expressed mature artery markers, and decreased cell cycling. The vein-specifying transcription factor COUP-TF2 (also known as NR2F2) prevented plexus cells from overcoming the pre-artery threshold by inducing cell cycle genes. Thus, vein-derived coronary arteries are built by pre-artery cells that can differentiate independently of blood flow upon the release of inhibition mediated by COUP-TF2 and cell cycle factors.

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  1. 1.

    Chen, X., Qin, J., Cheng, C.-M., Tsai, M.-J. & Tsai, S. Y. COUP-TFII is a major regulator of cell cycle and Notch signaling pathways. Mol. Endocrinol. 26, 1268–1277 (2012).

  2. 2.

    Fish, J. E. & Wythe, J. D. The molecular regulation of arteriovenous specification and maintenance. Dev. Dyn. 244, 391–409 (2015).

  3. 3.

    Isogai, S., Lawson, N. D., Torrealday, S., Horiguchi, M. & Weinstein, B. M. Angiogenic network formation in the developing vertebrate trunk. Development 130, 5281–5290 (2003).

  4. 4.

    Red-Horse, K., Ueno, H., Weissman, I. L. & Krasnow, M. A. Coronary arteries form by developmental reprogramming of venous cells. Nature 464, 549–553 (2010).

  5. 5.

    Xu, C. et al. Arteries are formed by vein-derived endothelial tip cells. Nat. Commun. 5, 5758 (2014).

  6. 6.

    Kametani, Y., Chi, N. C., Stainier, D. Y. R. & Takada, S. Notch signaling regulates venous arterialization during zebrafish fin regeneration. Genes Cells 20, 427–438 (2015).

  7. 7.

    Wu, B. et al. Endocardial cells form the coronary arteries by angiogenesis through myocardial-endocardial VEGF signaling. Cell 151, 1083–1096 (2012).

  8. 8.

    Chen, H. I. et al. The sinus venosus contributes to coronary vasculature through VEGFC-stimulated angiogenesis. Development 141, 4500–4512 (2014).

  9. 9.

    Volz, K. S. et al. Pericytes are progenitors for coronary artery smooth muscle. eLife 4, e10036 (2015).

  10. 10.

    Ivins, S. et al. The CXCL12/CXCR4 axis plays a critical role in coronary artery development. Dev. Cell 33, 455–468 (2015).

  11. 11.

    Sharma, B., Chang, A. & Red-Horse, K. Coronary artery development: progenitor cells and differentiation pathways. Annu. Rev. Physiol. 79, 1–19 (2017).

  12. 12.

    Todorov, V. & Filzmoser, P. An object-oriented framework for robust multivariate analysis. J. Stat. Softw. 32, 1–47 (2009).

  13. 13.

    Gokce, O. et al. Cellular taxonomy of the mouse striatum as revealed by single-cell RNA-seq. Cell Reports 16, 1126–1137 (2016).

  14. 14.

    Rivera-Feliciano, J. et al. Development of heart valves requires Gata4 expression in endothelial-derived cells. Development 133, 3607–3618 (2006).

  15. 15.

    Zhang, H. et al. Endocardium minimally contributes to coronary endothelium in the embryonic ventricular free walls. Circ. Res. 118, 1880–1893 (2016).

  16. 16.

    Chen, Q. et al. Endothelial cells are progenitors of cardiac pericytes and vascular smooth muscle cells. Nat. Commun. 7, 12422 (2016).

  17. 17.

    Lin, C.-J., Lin, C.-Y., Chen, C.-H., Zhou, B. & Chang, C.-P. Partitioning the heart: mechanisms of cardiac septation and valve development. Development 139, 3277–3299 (2012).

  18. 18.

    Adams, R. H. et al. Roles of ephrinB ligands and EphB receptors in cardiovascular development: demarcation of arterial/venous domains, vascular morphogenesis, and sprouting angiogenesis. Genes Dev. 13, 295–306 (1999).

  19. 19.

    Sacilotto, N. et al. MEF2 transcription factors are key regulators of sprouting angiogenesis. Genes Dev. 30, 2297–2309 (2016).

  20. 20.

    The Tabula Muris Consortium, Quake, S. R., Wyss-Coray, T. & Darmanis, S. Single-cell transcriptomic characterization of 20 organs and tissues from individual mice creates a Tabula Muris. Preprint at https://www.biorxiv.org/content/early/2018/03/29/237446 (2018).

  21. 21.

    Mack, J. J. et al. NOTCH1 is a mechanosensor in adult arteries. Nat. Commun. 8, 1620 (2017).

  22. 22.

    Tian, X. et al. Vessel formation. De novo formation of a distinct coronary vascular population in neonatal heart. Science 345, 90–94 (2014).

  23. 23.

    Chen, H. I. et al. VEGF-C and aortic cardiomyocytes guide coronary artery stem development. J. Clin. Invest. 124, 4899–4914 (2014).

  24. 24.

    Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005).

  25. 25.

    Akimoto, S., Mitsumata, M., Sasaguri, T. & Yoshida, Y. Laminar shear stress inhibits vascular endothelial cell proliferation by inducing cyclin-dependent kinase inhibitor p21(Sdi1/Cip1/Waf1). Circ. Res. 86, 185–190 (2000).

  26. 26.

    Lin, K. et al. Molecular mechanism of endothelial growth arrest by laminar shear stress. Proc. Natl Acad. Sci. USA 97, 9385–9389 (2000).

  27. 27.

    Fang, J. S. et al. Shear-induced Notch–Cx37–p27 axis arrests endothelial cell cycle to enable arterial specification. Nat. Commun. 8, 2149 (2017).

  28. 28.

    You, L.-R. et al. Suppression of Notch signalling by the COUP-TFII transcription factor regulates vein identity. Nature 435, 98–104 (2005).

  29. 29.

    Qin, J. et al. COUP-TFII inhibits TGF-β-induced growth barrier to promote prostate tumorigenesis. Nature 493, 236–240 (2013).

  30. 30.

    Grieskamp, T., Rudat, C., Lüdtke, T. H.-W., Norden, J. & Kispert, A. Notch signaling regulates smooth muscle differentiation of epicardium-derived cells. Circ. Res. 108, 813–823 (2011).

  31. 31.

    Gawad, C., Koh, W. & Quake, S. R. Single-cell genome sequencing: current state of the science. Nat. Rev. Genet. 17, 175–188 (2016).

  32. 32.

    Treutlein, B. et al. Reconstructing lineage hierarchies of the distal lung epithelium using single-cell RNA-seq. Nature 509, 371–375 (2014).

  33. 33.

    Velten, L. et al. Human haematopoietic stem cell lineage commitment is a continuous process. Nat. Cell Biol. 19, 271–281 (2017).

  34. 34.

    Sun, Y. et al. Islet 1 is expressed in distinct cardiovascular lineages, including pacemaker and coronary vascular cells. Dev. Biol. 304, 286–296 (2007).

  35. 35.

    Wang, Y. et al. Ephrin-B2 controls VEGF-induced angiogenesis and lymphangiogenesis. Nature 465, 483–486 (2010).

  36. 36.

    Miquerol, L. et al. Endothelial plasticity drives arterial remodeling within the endocardium after myocardial infarction. Circ. Res. 116, 1765–1771 (2015).

  37. 37.

    Sheikh, A. Y. et al. In vivo genetic profiling and cellular localization of apelin reveals a hypoxia-sensitive, endothelial-centered pathway activated in ischemic heart failure. Am. J. Physiol. Heart Circ. Physiol. 294, H88–H98 (2008).

  38. 38.

    Alva, J. A. et al. VE-Cadherin-Cre-recombinase transgenic mouse: a tool for lineage analysis and gene deletion in endothelial cells. Dev. Dyn. 235, 759–767 (2006).

  39. 39.

    Picelli, S. et al. Full-length RNA-seq from single cells using Smart-seq2. Nat. Protocols 9, 171–181 (2014).

  40. 40.

    Koh, P. W. et al. An atlas of transcriptional, chromatin accessibility, and surface marker changes in human mesoderm development. Sci. Data 3, 160109 (2016).

  41. 41.

    Loh, K. M. et al. Mapping the pairwise choices leading from pluripotency to human bone, heart, and other mesoderm cell types. Cell 166, 451–467 (2016).

  42. 42.

    Diez-Roux, G. et al. A high-resolution anatomical atlas of the transcriptome in the mouse embryo. PLoS Biol. 9, e1000582 (2011).

  43. 43.

    D’Amato, G. et al. Sequential Notch activation regulates ventricular chamber development. Nat. Cell Biol. 18, 7–20 (2016).

  44. 44.

    Gross-Thebing, T., Paksa, A. & Raz, E. Simultaneous high-resolution detection of multiple transcripts combined with localization of proteins in whole-mount embryos. BMC Biol. 12, 55 (2014).

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We thank S. Tsai, M.-J. Tsai, S. Evans, B. Zhou, T. Quertermous and L. Iruela-Arispe for mice; M. Miyanishi for assistance with fluorescence-activated cell sorting; R. Morganti and G. Gulati for assistance with scRNA-seq; L. O’Brien, D. Bergmann, and V. Greco for manuscript comments; and J. Ban for technical assistance. T.S. is supported by the NIGMS of the National Institutes of Health (T32GM007276). K.R.-H. is supported by the NIH/NHLBL (R01-HL128503) and the New York Stem Cell Foundation (NYSCF-Robertson Investigator). T.T.D. is supported by the NIH/NHLBL T32 (HL098049) and an AHA Postdoctoral Fellowship. E.C.B. is supported by the NIH (R01-GM037734, R01-AI130471) and the Department of Veterans Affairs.

Reviewer information

Nature thanks R. Adams, C. Marr and A. Siekmann for their contribution to the peer review of this work.

Author information

Author notes

  1. These authors contributed equally: Tianying Su, Geoff Stanley, Rahul Sinha.


  1. Department of Biology, Stanford University, Stanford, CA, USA

    • Tianying Su
    • , Gaetano D’Amato
    • , Soumya Das
    • , Siyeon Rhee
    • , Andrew H. Chang
    • , Aruna Poduri
    • , Brian Raftrey
    •  & Kristy Red-Horse
  2. Program in Biophysics, Stanford University, Stanford, CA, USA

    • Geoff Stanley
  3. Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA, USA

    • Rahul Sinha
    • , Sean Wu
    •  & Irving Weissman
  4. Veterans Affairs Palo Alto Health Care System and The Palo Alto Veterans Institute for Research, Palo Alto, CA, USA

    • Thanh Theresa Dinh
    • , Walter A. Roper
    •  & Eugene C. Butcher
  5. Department of Pathology, Stanford University, Stanford, CA, USA

    • Thanh Theresa Dinh
    • , Walter A. Roper
    •  & Eugene C. Butcher
  6. Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA

    • Guang Li
    •  & Sean Wu
  7. Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    • Kelsey E. Quinn
    •  & Kathleen M. Caron
  8. Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA

    • Sean Wu
  9. Aix-Marseille Université, CNRS UMR 7288, IBDM, Marseille, France

    • Lucile Miquerol
  10. Department of Bioengineering, Stanford University, Stanford, CA, USA

    • Stephen Quake
  11. Chan Zuckerberg Biohub, San Francisco, CA, USA

    • Stephen Quake


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T.S., R.S., G.S. and K.R.-H. conceived the study. T.S. and R.S. captured cells and performed scRNA-seq. G.S. performed scRNA-seq computation. T.S., G.S. and K.R.-H. performed scRNA-seq analysis. G.D. performed CXCR7–GFP and FBLN2/ADM in situ hybridization. S.D. performed P2/P6 postnatal analysis. S.R. peformed EdU experiments. A.H.C. performed E14.5/E17.5 lineage quantification. A.P. performed the Isl1 experiment. B.R. performed GSEA. T.T.D. and W.A.R. provided Coup-tf2 flox mice. K.E.Q. and K.M.C. provided CXCR7–GFP mice. L.M. provided Cx40CreER mice. S.W. and G.L. provided adult scRNA-seq. T.S., G.S., and K.R.-H. prepared the manuscript. T.S. performed most wet lab experiments. R.S., E.C.B., I.W., S.Q., and K.R.-H. provided resources.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Kristy Red-Horse.

Extended data figures and tables

  1. Extended Data Fig. 1 Single cell analysis of ApjCreER lineage labelled cells.

    a, Comparison of rPCA and classical PCA at separation of subpopulations. PC scores were selected to best separate the Enpp+ Esam population. Cells are coloured by expression (log10 CPM, scaled to maximum per gene). n = 352 cells. b, Comparison of default and sum-of-60 modified PC scores. PC2 is the default PC score from rPCA; PC2.score is the modified sum-of-top-60 scores (expression is log10 CPM, scaled to maximum). Y-axis is the number of genes detected per cell (>1 count). n = 426 cells. c, Comparison of default and sum-of-top-60 scores. Scores were chosen that best separated the Vwf+ and Cxcr4 populations. n = 426 cells. d, Unique cell cycle signature on PC.pos/PC.neg biplots. PC1.pos (PC1.neg) is the sum of the top 30 genes by positive (negative) loading to PC1. Cells are coloured by expression. Lower panel is the same rPCA after removing the list of 202 cell cycle genes. Numbers in bold are the correlations between PC1.pos and PC1.neg. n = 674 cells. e, PC.pos/PC.neg biplot showing theoretical location of doublets expressing high levels of both gene sets. f, Schematic of the pairwise discreteness test on a discrete (left) and continuous (right) pair of subpopulations. g, FACS plots used to isolate GFP-positive cells (red box) from ApjCreER RosamTmG hearts at E12.5. h, Top, discreteness statistic generated by pairwise discreteness test as a function of number of intermediate cells (nint) for simulated distributions. Bottom, pairwise distributions of cell clusters in the data set and the fraction of intermediate cells estimated by pairwise discreteness analysis. i, rPCA plots and their accompanying gene expression patterns in the embryonic heart as reported by Euroexpress. In situ hybridization images show whole hearts (top); insets of specific areas are in lower panels with relative expression levels indicated. Expression levels in rPCA plots range from 0 (yellow) to 4 (brown) in log10CPM. Top, n = 843 cells. j, Summary of broadly defined cell populations as indicated by gene expression patterns. n = 843 cells. k, Example of manual clustering process. For i, n = 732 cells; ii, n = 531 cells; iii, n = 415 cells; iv, n = 284 cells; v, n = 261 cells. l, Comparison of pairwise discreteness test results for different numbers of genes per cell type signature (n).

  2. Extended Data Fig. 2 Identification of a coronary progenitor niche within the SV.

    a, Gene expression patterns identify cell types in rPCA plots of the venous valve–SV–CV continuum. Expression levels are log10 CPM and range from 0 (yellow) to 4 (brown) as indicated. Left, n = 843 cells; right, n = 732 cells. b, c, Expression patterns in rPCA plots (b) and whole-mount confocal immunofluorescence (c) of selected genes. For b, n = 732 cells. d, Overlaying gene expression patterns suggests that the SV has two distinct domains, the SVc (sinus venosus, coronary adjacent) and the SVv (sinus venosus, valve adjacent). e, rPCA on the valve–SVv–SVc continuum identified specific markers of the SVv and SVc. Solid box, n = 732 cells. Dotted box, n = 415 cells. f, In situ hybridization of SVv and SVc markers revealed complementary localization in vivo. g, Colour coding showing subpopulations that were used to calculate average expression levels. Scale bars, b, 200 μm, e, 30 μm.

  3. Extended Data Fig. 3 Characterization of pre-artery cells.

    ad, rPCA plots of the E12.5 SVc–CV continuum. Each dot is an individual cell, and gene expression levels are indicated by the colour spectrum as shown in Fig. 1d, which reflects log10 CPM. a, Arterial genes highly enriched in the arterial areas of the plot. b, Arterial genes significantly upregulated in, but not specific to, the arterial area of the plot. c, Venous genes highly depleted in the arterial areas of the plot. d, Venous genes downregulated, but not depleted, in the arterial area of the plot. For ad, Bonferroni-adjusted P < 0.01; PCA plots, n = 415 cells. Centre and error bars are mean ± s.e.m. of log CPM expression values. e, Genes expressed in adult coronary artery cells. Data are from the Tubula Muris consortium. n = 445 cells. f, Assignment of artery, capillary, and vein in adult coronary cells based on gene expression enrichment in e. n = 445 cells. g, Schematic for comparing E12.5 coronary cells to those along the adult artery–capillary–vein continuum. h, Results of experiment schematized in g. The centre line correspond to the median; the upper and lower hinges correspond to the first and third quartile, respectively; the whiskers extend to the largest value or to 1.5 × IQR (inter-quartile range, or distance between quartiles), whichever is smaller. Pre-artery cells: n = 20 cells. CV: n = 277 cells. P = 6.2 × 10−13. Statistical test is two-tailed.

  4. Extended Data Fig. 4 Novel artery markers identified in scRNA-seq data.

    a, E12.5, E14.5, and adult coronary cell rPCA plots with genes highly enriched or specific to the arterial area during development. Each dot is an individual cell, and gene expression levels are indicated by the colour spectrum as shown in Fig. 1d, which reflects log10CPM. Genes in bold red are also enriched in adult artery cells. b, Fluorescence in situ hybridization (RNAscope) for Slc45a4, which is expressed (arrowheads) in vessels positive for the arterial marker Cx40, but not in Cx40-negative capillaries (arrows). c, Slc45a4 expression in pre-artery cells derived from the SV lineage (ApjCreER lineage-labelled; arrowheads). d, Genes enriched in, but not specific to, arterial cells at E12.5 and E14.5. Genes in bold red are arterial specific in both the developing and adult heart. In a and d: for PCA plots, n = 415 cells (top, E12.5); n = 347 cells (middle, E14.5); n = 445 cells (bottom, adult). For bar graphs E12.5, Art, n = 20 cells; CV, n = 277 cells; SV, n = 118 cells; E14.5, Art, n = 70 cells; CV, n = 454 cells; SV, n = 144 cells. Centre and error bars are mean ± s.e.m. of log CPM expression values. Dots represent individual cells. Scale bars, 100 μm.

  5. Extended Data Fig. 5 Additional whole mount immunofluorescence of marker genes.

    a, CX40 whole-mount immunohistochemistry in late gestation hearts (E17.5). CX40 is expressed only in cells lining large arteries and arterioles (overlapping blue and green signal). Low level, non-arterial signal is in myocardial cells. b, rPCA plots from E12.5 and E14.5 with accompanying whole-mount immunofluorescence in E13.5 hearts. VWF is enriched in the SV; while APLN–nlacZ signal and DACH1 are present throughout the coronary plexus. CXCR4, ACKR3–GFP, and CXCL12–DsRed are enriched in the pre-artery and artery areas of rPCA plots and are interspersed within the intramyocardial coronary plexus. n = 415 cells (left, E12.5); n = 347 cells (right, E14.5). Scale bars, 100 μm.

  6. Extended Data Fig. 6 Clustering and additional lineage analysis of pre-artery cells.

    a, Clusters and relationships generated by rPCA and the pairwise discreteness test (left) and clusters generated by the Seurat pipeline (Louvain/SNN clustering, resolution = 2) (right). n = 757 cells. b, Violin plots show that arterial gene enrichment and venous gene de-enrichment are better with manual, iterative clustering, suggesting that this method leads to more precise populations. c, Violin plots of cell cycle genes in the two CV plexus clusters generated by the indicated algorithms. Seurat clusters are more defined by cell cycle differences than iterative rPCA (iRPCA) clusters. b, c, Violin plots were made using Seurat VlnPlot. Each violin plot is one subtype and each dot corresponds to a cell. d, Quantification of SV and endocardium contributions to coronary arteries. Error bars show s.d. ApjCreER RCA: n = 11 hearts. ApjCreER LCA: n = 6 hearts. Nfatc1Cre RCA: n = 5 hearts. Nfatc1Cre LCA: n = 5 hearts. Centre, mean. e, Experimental design to lineage trace pre-artery cells. f, Lineage labelling in E12.5 Cx40CreER Rosatdtomato hearts induced with tamoxifen at E11.5. g, Arterial lineage labelling in hearts induced at E10.5. h, Example of clones in Cx40CreER Rosaconfetti heart at E15.5. Tamoxifen was administered at E12.5. Two groups of cells sharing the same fluorescent label (clones) are present: YFP-labelled (yellow circle) and nGFP labelled (green circle). Clone sizes are very small, consistent with low proliferation rates in pre-arterial cells. i, P8 heart lineage from Cx40CreER Rosatdtomato mice dosed with tamoxifen at E11.5. Heavy lineage labelling of the left coronary artery is shown (LCA). Arrowheads indicate branches of the right coronary artery. Myocardium (myo) of the left ventricle is also Cx40+ at E11.5, and is also lineage labelled. j, Images from P8 Cx40CreER Rosatdtomato hearts dosed with tamoxifen at E11.5 or E16.5. Only the E11.5 dosage results in capillary labelling (arrows) resulting from reversion of pre-artery cells that differentiate during the burst of pre-artery specification between E12.5 and E14.5. Arrowheads point to arterial lineage labelling. k, Postnatal lineage tracing in ApjCreER Rosatdtomato or Cx40CreER Rosatdtomato hearts where tamoxifen was injected at P2. Tips of arteries are lineage labelled with ApjCreER Rosatdtomato, but are depleted of Cx40CreER Rosatdtomato label, indicating that artery tips can extend by incorporating capillary cells that differentiate into arterial endothelial cells. Unpaired two-tailed t-test was used to calculate P values. For ApjCreER, n = 78 artery tips at P2, n = 41 artery tips at P6. P = 4.4608 × 10−19. For Cx40CreER, n = 81 artery tips at P2, n = 49 artery tips at P6. P = 1.61705 × 10−15. Error bars show s.d. ****P ≤ 0.0001. Centre is mean. Scale bars, d, e, f, j, k, 100 μm; g, 50 μm. Source Data

  7. Extended Data Fig. 7 A burst of pre-artery specification between E12.5 and E14.5 specifies cells that build most of the embryonic left and right coronary arteries.

    a, rPCA plots of the SVc–CV continuum show that Apj and Cx40 mark cells before and after pre-artery specification, respectively. n = 415 cells. b, Schematic of lineage tracing experiments. Black bars indicate tamoxifen dosing, and arrows indicate dates of removal. ce, Right lateral views of early hearts show zones with heavy pre-artery specification. f, g, i, Low magnification of right lateral views (leftmost panels) at late embryonic stages show labelling in the main right coronary artery; right panels focus on more distal branches of the right coronary artery. Table summarizes labelling and results. n ≥ 3 hearts for each experiment. h, Quantification of ApjCreER and Cx40CreER lineage labelling indicates that most of the embryonic coronary artery is formed by cells specified within the E12.5–E14.5 time window. n = 3 for each Cre. Data shown as mean ± s.d. Tam, tamoxifen. Scale bars, 100 μm. Source Data

  8. Extended Data Fig. 8 Gene expression curves in E12.5 cells.

    a, Expression of genes from the indicated categories along the SV–CV plexus–arterial differentiation continuum. The x-axis has individual cells organized as shown in Fig. 3a, and gene expression is plotted as LOESS curves. Raw data points are shown as dots. b, GSEA; cell cycle pathways shown in bold. c, Pre-artery cells (Cx40+Cxcr4+Apj) segregate to the non-cycling quadrant of rPCA plots. Arrows indicate cell cycle progression. d, Quantification of EdU labelling in pre-artery cells. Data shown as mean ± s.d. n = 6 hearts. ***P ≤ 0.001. Unpaired two-tailed t-test was used to calculate P value. Source Data

  9. Extended Data Fig. 9 Effect of COUP-TF2 overexpression during coronary vessel development.

    a, Schematic of transgenes used to study Coup-tf2 overexpression in coronary cells. b, c, Recombination is not complete in the SV with tamoxifen at E9.5 and E10.5 as shown in whole-mount confocal images (b) and quantification (c). Control GFP is visualized by direct fluorescence, and COUP-TF2OE through immunostaining for the myc tag. For c, ApjCreER RosamTmG, n = 5 hearts. ApjCreER Coup-tf2OE, n = 6 hearts. d, Tamoxifen dosing at E11.5 and E12.5 fills capillaries with recombined cells, but still resulted in Coup-tf2OE cells being excluded from arteries (A). e, Induction of Coup-tf2OE throughout vasculature shows that overexpressing cells can exist in arteries. f, Quantification of ventricle coverage at E12.5. n = 4 control hearts, n = 7 COUP-TF2OE hearts. ns, P > 0.05. P = 0.8868. g, Whole-mount confocal images of control and Coup-tf2OE hearts at different stages of development. Coronary migration (dotted line) on the dorsal side of the ventricle (outlined with solid line) is similar in both genotypes. h, High magnification of E12.5 Coup-tf2OE heart shown in g highlights the positioning of transgenic cells at both the leading front and trailing cells. i, COUP-TF2OE cells can become part of the JAG-1-positive artery if induced after pre-artery specification with Cx40CreER. j, Mosaic experiment in which constitutive expression of the NOTCH intracellular domain (NICD) is induced at the same time as Coup-tf2OE. This manipulation creates a vasculature containing three different transgene combinations: 1. NICD; 2. COUP-TF2OE; or 3. NICD + COUP-TF2OE (arrowheads). Those containing just the NICD (category 1) are the only transgenic cells that contribute to arterial vessels. k, Quantification of the percentage of endothelial cells in capillaries and arteries (Art) with the three transgenic combinations. NICD-expressing cells preferred arteries whereas COUP-TF2OE cells avoid arteries, the latter of which was not rescued by NICD. n = 6 hearts. **P ≤ 0.01; ****P ≤ 0.0001. For NICD capillary versus artery, P = 0.0070. For COUP-TF2OE capillary versus artery, P = 7.49224 × 10−5. For COUP-TF2OE + NICD capillary versus artery, P = 8.07734 × 10−5. l, The CDK inhibitor flavopiridol increased arterial specification (Cx40) in an SV sprouting assay. n = 33 control explants, n = 38 treated explants. ***P ≤ 0.001. m, Immunostaining of endothelial sprouts (VE-cadherin+) migrating from SV or atria tissue explants with Cx40 showed the increase in this arterial marker (arrowheads) with flavopiridol treatment. Data shown as mean ± s.d. A two-tailed unpaired t-test was performed to determine P values. Scale bars, b, 20 μm; d, e, gj, 100 μm; m, 25 μm. Source Data

  10. Extended Data Fig. 10 Gene expression curves in E14.5 control and Coup-tf2OE cells.

    a, FACS plots of the GFP-marked cells from control and Coup-tf2OE hearts that were processed for scRNA-seq. b, Criteria for identifying Coup-tf2OE cells was >1 read of the flag and myc sequences included in the transgene. c, Comparing the number of flag and myc reads in control and Coup-tf2OE hearts confirms the specificity of this parameter for transgenic cells. Control: n = 409 cells. COUP-TF2OE: n = 714 cells. The centre line corresponds to the median; the upper and lower hinges correspond to the first and third quartile, respectively; the whiskers extend to the largest value or to 1.5 × IQR (inter-quartile range, or distance between quartiles), whichever is smaller. d, Expression of genes from the indicated categories along the vein–CV plexus–arterial axis. The x-axis has individual cells organized as shown in Fig. 5b. Lines are LOESS curves of gene expression and raw data points are shown as dots. Shaded region represents the 95% confidence interval of the LOESS curve. e, Hypoplastic coronary vasculature with heterozygous deletion of Coup-tf2 in endothelial cells. Scale bars, 100 μm.

Supplementary information

  1. Supplementary Information

    This file contains Supplementary Methods and Supplementary References

  2. Reporting Summary

  3. Supplementary Data 1

    Gating strategy for FACS isolation of cells used in scRNA-seq. (a-c) Gating strategy for FACS isolation of e12.5 (a), e14.5 control (b), and e14.5 COUP-TF2OE (c) cells. Red lines enclose the gated subpopulations. Arrows show the progression of gating

  4. Supplementary Table 1

    Differential gene regulation between e12.5 and adult endothelial cells. This table contains genes that are artery-enriched in adult coronary endothelial cells but not in pre-artery cells at e12.5. All genes were correlated separately to the embryonic SVc-CV plexus-arterial continuum and to the adult artery-capillary-venous continuum. P-values were corrected using Benjamini-Hochberg (FDR). Genes that were significantly (adjusted p < 0.05) positively correlated to artery-venous continuum in adult (enriched in artery), but not significantly (adjusted p > 0.1) correlated to the embryonic artery-venous continuum (neither artery nor vein enriched) were included in the spreadsheet, i.e. list shows genes only enriched in adult arterial. P values in the spreadsheet represent p-value of correlation to the artery-venous continuum. Adult: n=445 cells. E12.5: n=415 cells. Pearson correlation coefficient was calculated

  5. Supplementary Table 2

    Transcriptional changes between endothelial subtypes at e12.5. Genes are selected by log foldchange > 0.25, Bonferroni-adjusted p-value < 0.1, expressed in at least 10% of cells in either population (Seurat FindMarkers). Bonferroni correction based on the total number of genes in the dataset. Log fold change is calculated as arithmetic mean of log10 cpm values of one population minus the arithmetic mean of log10 cpm values of the second, and fold change is 10log_foldchange. Yellow highlight indicates a cell cycle inhibitor highly upregulated in pre-artery cells. Art: n=20 cells. CV: n=277 cells. SV: n=118 cells. P-values were calculated by the Wilcoxon rank sum test

  6. Supplementary Table 3

    Transcriptional changes between control and Coup-tf2OE cells at e14.5. Genes are selected by log foldchange > 0.25, Bonferroni-adjusted p-value < 0.1, expressed in at least 10% of cells in either population. Log fold change is calculated as arithmetic mean of log10 cpm values of one population minus the arithmetic mean of log10 cpm values of the second, and fold change is 10log_foldchange. N= 347 cells (WT), n=321 cells (Coup-TFIIOE). P-values were calculated by the Wilcoxon rank sum test

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