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Decoding the regulatory network of early blood development from single-cell gene expression measurements.

Moignard V, Woodhouse S, Haghverdi L, Lilly AJ, Tanaka Y, Wilkinson AC, Buettner F, Macaulay IC, Jawaid W, Diamanti E, Nishikawa S, Piterman N, Kouskoff V, Theis FJ, Fisher J, Göttgens B - Nat. Biotechnol. (2015)

Bottom Line: Here we describe a strategy to address this problem that combines gene expression profiling of large numbers of single cells with data analysis based on diffusion maps for dimensionality reduction and network synthesis from state transition graphs.Several model predictions concerning the roles of Sox and Hox factors are validated experimentally.Our results demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that underpin organogenesis.

View Article: PubMed Central - PubMed

Affiliation: 1] Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK. [2] Wellcome Trust - Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK.

ABSTRACT
Reconstruction of the molecular pathways controlling organ development has been hampered by a lack of methods to resolve embryonic progenitor cells. Here we describe a strategy to address this problem that combines gene expression profiling of large numbers of single cells with data analysis based on diffusion maps for dimensionality reduction and network synthesis from state transition graphs. Applying the approach to hematopoietic development in the mouse embryo, we map the progression of mesoderm toward blood using single-cell gene expression analysis of 3,934 cells with blood-forming potential captured at four time points between E7.0 and E8.5. Transitions between individual cellular states are then used as input to develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model of blood development. Several model predictions concerning the roles of Sox and Hox factors are validated experimentally. Our results demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that underpin organogenesis.

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Single-cell gene expression analysis of early blood development(a) Flk1 and Runx1 staining in E7.5 mesoderm and blood band, respectively. Scale bar is 100 μm. (b) Single cells sorted from five populations at four anatomically distinct stages from E7.0-8.25. (c) Quantification of cells sorted and retained for analysis after quality control. (d) Quantification of Flk1+, GFP+ or Flk1+GFP− cells in embryos at each time point from FACS data (Supplementary Fig. 1a). Line indicates median. (e) Unsupervised hierarchical clustering of gene expression for the 33 TFs and 7 markers in all cells. Coloured bar indicates embryonic stage. Major clusters indicated. ND, not detected.
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Figure 1: Single-cell gene expression analysis of early blood development(a) Flk1 and Runx1 staining in E7.5 mesoderm and blood band, respectively. Scale bar is 100 μm. (b) Single cells sorted from five populations at four anatomically distinct stages from E7.0-8.25. (c) Quantification of cells sorted and retained for analysis after quality control. (d) Quantification of Flk1+, GFP+ or Flk1+GFP− cells in embryos at each time point from FACS data (Supplementary Fig. 1a). Line indicates median. (e) Unsupervised hierarchical clustering of gene expression for the 33 TFs and 7 markers in all cells. Coloured bar indicates embryonic stage. Major clusters indicated. ND, not detected.

Mentions: The first wave of primitive haematopoiesis originates from Flk1+ mesoderm1,2,10, with all haematopoietic potential in the mouse contained within the Flk1+ population from E7.0 onwards. Although some blood progenitor cells lose Flk1 expression just before the onset of circulation11, previous work using a LacZ reporter knocked into the Runx1 locus showed that haematopoietic potential remains confined to the Runx1+ fraction12, which was confirmed with a GFP reporter driven by the Runx1 +23 enhancer, which reproduces Runx1 expression 8. Using Flk1 expression in combination with a Runx1-ires-GFP reporter mouse13 therefore allowed us to capture cells with blood potential at distinct anatomical stages across a time course of mouse development (Fig. 1a,b). Single Flk1+ cells were flow sorted at E7.0 (primitive streak, PS), E7.5 (neural plate, NP) and E7.75 (head fold, HF) stages. We subdivided E8.25 cells into putative blood and endothelial populations by isolating GFP+ cells (four somite, 4SG) and Flk1+GFP− cells (4SFG−), respectively (Fig. 1b, Supplementary Fig. 1a). Cells were sorted from multiple embryos at each time point, with 3,934 cells going on to subsequent analysis (Fig. 1c). Total cell numbers (Supplementary Fig. 1b) and numbers of cells of appropriate phenotypes (Fig. 1d) present in each embryo were estimated from FACS data, indicating that for the first three stages, more than one embryo equivalent of Flk1+ cells was collected.


Decoding the regulatory network of early blood development from single-cell gene expression measurements.

Moignard V, Woodhouse S, Haghverdi L, Lilly AJ, Tanaka Y, Wilkinson AC, Buettner F, Macaulay IC, Jawaid W, Diamanti E, Nishikawa S, Piterman N, Kouskoff V, Theis FJ, Fisher J, Göttgens B - Nat. Biotechnol. (2015)

Single-cell gene expression analysis of early blood development(a) Flk1 and Runx1 staining in E7.5 mesoderm and blood band, respectively. Scale bar is 100 μm. (b) Single cells sorted from five populations at four anatomically distinct stages from E7.0-8.25. (c) Quantification of cells sorted and retained for analysis after quality control. (d) Quantification of Flk1+, GFP+ or Flk1+GFP− cells in embryos at each time point from FACS data (Supplementary Fig. 1a). Line indicates median. (e) Unsupervised hierarchical clustering of gene expression for the 33 TFs and 7 markers in all cells. Coloured bar indicates embryonic stage. Major clusters indicated. ND, not detected.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4374163&req=5

Figure 1: Single-cell gene expression analysis of early blood development(a) Flk1 and Runx1 staining in E7.5 mesoderm and blood band, respectively. Scale bar is 100 μm. (b) Single cells sorted from five populations at four anatomically distinct stages from E7.0-8.25. (c) Quantification of cells sorted and retained for analysis after quality control. (d) Quantification of Flk1+, GFP+ or Flk1+GFP− cells in embryos at each time point from FACS data (Supplementary Fig. 1a). Line indicates median. (e) Unsupervised hierarchical clustering of gene expression for the 33 TFs and 7 markers in all cells. Coloured bar indicates embryonic stage. Major clusters indicated. ND, not detected.
Mentions: The first wave of primitive haematopoiesis originates from Flk1+ mesoderm1,2,10, with all haematopoietic potential in the mouse contained within the Flk1+ population from E7.0 onwards. Although some blood progenitor cells lose Flk1 expression just before the onset of circulation11, previous work using a LacZ reporter knocked into the Runx1 locus showed that haematopoietic potential remains confined to the Runx1+ fraction12, which was confirmed with a GFP reporter driven by the Runx1 +23 enhancer, which reproduces Runx1 expression 8. Using Flk1 expression in combination with a Runx1-ires-GFP reporter mouse13 therefore allowed us to capture cells with blood potential at distinct anatomical stages across a time course of mouse development (Fig. 1a,b). Single Flk1+ cells were flow sorted at E7.0 (primitive streak, PS), E7.5 (neural plate, NP) and E7.75 (head fold, HF) stages. We subdivided E8.25 cells into putative blood and endothelial populations by isolating GFP+ cells (four somite, 4SG) and Flk1+GFP− cells (4SFG−), respectively (Fig. 1b, Supplementary Fig. 1a). Cells were sorted from multiple embryos at each time point, with 3,934 cells going on to subsequent analysis (Fig. 1c). Total cell numbers (Supplementary Fig. 1b) and numbers of cells of appropriate phenotypes (Fig. 1d) present in each embryo were estimated from FACS data, indicating that for the first three stages, more than one embryo equivalent of Flk1+ cells was collected.

Bottom Line: Here we describe a strategy to address this problem that combines gene expression profiling of large numbers of single cells with data analysis based on diffusion maps for dimensionality reduction and network synthesis from state transition graphs.Several model predictions concerning the roles of Sox and Hox factors are validated experimentally.Our results demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that underpin organogenesis.

View Article: PubMed Central - PubMed

Affiliation: 1] Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK. [2] Wellcome Trust - Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK.

ABSTRACT
Reconstruction of the molecular pathways controlling organ development has been hampered by a lack of methods to resolve embryonic progenitor cells. Here we describe a strategy to address this problem that combines gene expression profiling of large numbers of single cells with data analysis based on diffusion maps for dimensionality reduction and network synthesis from state transition graphs. Applying the approach to hematopoietic development in the mouse embryo, we map the progression of mesoderm toward blood using single-cell gene expression analysis of 3,934 cells with blood-forming potential captured at four time points between E7.0 and E8.5. Transitions between individual cellular states are then used as input to develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model of blood development. Several model predictions concerning the roles of Sox and Hox factors are validated experimentally. Our results demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that underpin organogenesis.

Show MeSH
Related in: MedlinePlus