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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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In silico perturbations predict key regulators of blood development(a) Network stable states for wild-type and Sox7 overexpression. Red indicates expressed; blue indicates not expressed. (b) Colony assays with or without doxycycline from genotyped E8.25 embryos from iSox7+rtTA+ mice crossed with wild types. (c) Quantification of primitive erythroid colonies after 4 days (mean and s.e.m for the number of embryos indicated). P-value was determined using the student’s t-test for the number of embryos indicated.
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Figure 5: In silico perturbations predict key regulators of blood development(a) Network stable states for wild-type and Sox7 overexpression. Red indicates expressed; blue indicates not expressed. (b) Colony assays with or without doxycycline from genotyped E8.25 embryos from iSox7+rtTA+ mice crossed with wild types. (c) Quantification of primitive erythroid colonies after 4 days (mean and s.e.m for the number of embryos indicated). P-value was determined using the student’s t-test for the number of embryos indicated.

Mentions: Next, we assessed whether our network models faithfully recapitulate blood and cardiovascular development, in which endothelial and primitive blood cells emerge from a common mesodermal progenitor. To do this, we determined the stable states of the network model, which correspond to those expression patterns for the 20 TFs that satisfy all the Boolean network rules, and therefore can remain stable. We found that only eight stable states are reachable in total across all possible models, including “endothelial-like” (WT-S7) and “blood-like” expression states (WT-S2 to S6) (Figure 5a). Of note, 432 models had both the endothelial-like state and at least one of the blood-like states (WT-6) as stable states, thus capturing the functionality of bipotential Flk1+ precursors.


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)

In silico perturbations predict key regulators of blood development(a) Network stable states for wild-type and Sox7 overexpression. Red indicates expressed; blue indicates not expressed. (b) Colony assays with or without doxycycline from genotyped E8.25 embryos from iSox7+rtTA+ mice crossed with wild types. (c) Quantification of primitive erythroid colonies after 4 days (mean and s.e.m for the number of embryos indicated). P-value was determined using the student’s t-test for the number of embryos indicated.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4374163&req=5

Figure 5: In silico perturbations predict key regulators of blood development(a) Network stable states for wild-type and Sox7 overexpression. Red indicates expressed; blue indicates not expressed. (b) Colony assays with or without doxycycline from genotyped E8.25 embryos from iSox7+rtTA+ mice crossed with wild types. (c) Quantification of primitive erythroid colonies after 4 days (mean and s.e.m for the number of embryos indicated). P-value was determined using the student’s t-test for the number of embryos indicated.
Mentions: Next, we assessed whether our network models faithfully recapitulate blood and cardiovascular development, in which endothelial and primitive blood cells emerge from a common mesodermal progenitor. To do this, we determined the stable states of the network model, which correspond to those expression patterns for the 20 TFs that satisfy all the Boolean network rules, and therefore can remain stable. We found that only eight stable states are reachable in total across all possible models, including “endothelial-like” (WT-S7) and “blood-like” expression states (WT-S2 to S6) (Figure 5a). Of note, 432 models had both the endothelial-like state and at least one of the blood-like states (WT-6) as stable states, thus capturing the functionality of bipotential Flk1+ precursors.

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