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Emerging properties of animal gene regulatory networks

Abstract

Gene regulatory networks (GRNs) provide system level explanations of developmental and physiological functions in the terms of the genomic regulatory code. Depending on their developmental functions, GRNs differ in their degree of hierarchy, and also in the types of modular sub-circuit of which they are composed, although there is a commonly employed sub-circuit repertoire. Mathematical modelling of some types of GRN sub-circuit has deepened biological understanding of the functions they mediate. The structural organization of various kinds of GRN reflects their roles in the life process, and causally illuminates both developmental and evolutionary process.

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Figure 1: ‘Birdseye’ views of structural properties of representative developmental GRNs.
Figure 2: Structural characteristics of downstream effector gene cassettes and their control functions.

References

  1. Oliveri, P., Tu, Q. & Davidson, E. H. Global regulatory logic for specification of an embryonic cell lineage. Proc. Natl Acad. Sci. USA 105, 5955–5962 (2008)This paper provides proof of principle that if a developmental GRN is essentially complete, then it provides causal explanations for the biological functions of the process it controls.

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  2. Peter, I. S. & Davidson, E. H. Modularity and design principles in the sea urchin embryo gene regulatory network. FEBS Lett. 583, 3948–3958 (2009)This paper presents the latest comprehensive review of the sea urchin endomesoderm GRN, so far the most extensively validated large scale embryonic GRN, with special emphasis on the topologies of its spatial control sub-circuits.

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Davidson, E. H. The Regulatory Genome. Gene Regulatory Networks in Development and Evolution (Academic Press/Elsevier, 2006)

    Google Scholar 

  4. Alon, U. Network motifs: theory and experimental approaches. Nature Rev. Genet. 8, 450–461 (2007)

    CAS  PubMed  Google Scholar 

  5. Mangan, S. & Alon, U. Structure and function of the feed-forward loop network motif. Proc. Natl Acad. Sci. USA 100, 11980–11985 (2003)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  6. Davidson, E. H. Network design principles from the sea urchin embryo. Curr. Opin. Genet. Dev. 19, 535–540 (2009)

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Ma, W., Trusina, A., El-Samad, H., Lim, W. A. & Tang, C. Defining network topologies that can achieve biochemical adaptation. Cell 138, 760–773 (2009)

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Peter, I. S. & Davidson, E. H. The endoderm gene regulatory network in sea urchin embryos up to mid-blastula stage. Dev. Biol. 340, 188–199 (2010)

    CAS  PubMed  Google Scholar 

  9. Oliveri, P. & Davidson, E. H. Built to run, not fail. Science 315, 1510–1511 (2007)

    CAS  PubMed  Google Scholar 

  10. Koide, T., Hayata, T. & Cho, K. W. Y. Xenopus as a model system to study transcriptional regulatory networks. Proc. Natl Acad. Sci. USA 102, 4943–4948 (2005)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  11. Maduro, M. F. Structure and evolution of the C. elegans embryonic endomesoderm network. Biochim. Biophys. Acta 1789, 250–260 (2009)

    CAS  PubMed  Google Scholar 

  12. Chan, T.-M. et al. Developmental gene regulatory networks in the zebrafish embryo. Biochim. Biophys. Acta 1789, 279–298 (2009)

    CAS  PubMed  Google Scholar 

  13. Morley, R. H. et al. A gene regulatory network directed by zebrafish No tail accounts for its roles in mesoderm formation. Proc. Natl Acad. Sci. USA 106, 3829–3834 (2009)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  14. Stathopoulos, A. & Levine, M. Genomic regulatory networks and animal development. Dev. Cell 9, 449–462 (2005)

    CAS  PubMed  Google Scholar 

  15. Hong, J.-W., Hendrix, D. A., Papatsenko, D. & Levine, M. S. How the Dorsal gradient works: insights from postgenome technologies. Proc. Natl Acad. Sci. USA 105, 20072–20076 (2008)This review summarizes work regulatory control of Dorsal target genes expressed spatially along the dorsal/ventral axis of the syncytial Drosophila embryo.

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  16. Liberman, L. M. & Stathopoulos, A. Design flexibility in cis-regulatory control of gene expression: synthetic and comparative evidence. Dev. Biol. 327, 578–589 (2009)This paper presents a novel experimental evidence of cis-regulatory design features in the syncytial dorsal-ventral Drosophila specification system.

    CAS  PubMed  Google Scholar 

  17. Levine, M. & Davidson, E. H. Gene regulatory networks for development. Proc. Natl Acad. Sci. USA 102, 4936–4942 (2005)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  18. Ochoa-Espinosa, A., Yu, D., Tsirigos, A., Struffi, P. & Small, S. Anterior-posterior positional information in the absence of a strong Bicoid gradient. Proc. Natl Acad. Sci. USA 106, 3823–3828 (2009)This paper provides experimental evidence that the anterior/posterior specification system of the Drosophila embryo is controlled by a network of gene interactions rather than only by quantitative positional values of Bicoid.

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  19. Liberman, L. M., Teeves, G. T. & Stathopoulos, A. Quantitative imaging of the Dorsal nuclear gradient reveals limitations to threshold-dependent patterning in Drosophila . Proc. Natl Acad. Sci. USA 106, 22317–22322 (2009)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  20. Huang, A. M., Rusch, J. & Levine, M. An anteroposterior Dorsal gradient in the Drosophila embryo. Genes Dev. 11, 1963–1973 (1997)

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Saka, Y. & Smith, J. C. A mechanism for sharp transition of morphogen gradient interpretation in Xenopus . BMC Dev. Biol. 7, 47–55 (2007)

    PubMed  PubMed Central  Google Scholar 

  22. Davidson, E. H. Genomic Regulatory Systems: Development and Evolution (Academic Press/Elsevier, 2001)

    Google Scholar 

  23. Su, Y.-H. et al. A perturbation model of the gene regulatory network for oral and aboral ectoderm specification in the sea urchin embryo. Dev. Biol. 329, 410–421 (2009)

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Nikitina, N., Sauka-Spengler, T. & Bronner-Fraser, M. Dissecting early regulatory relationships in the lamprey neural crest gene network. Proc. Natl Acad. Sci. USA 105, 20083–20088 (2008)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  25. Woodland, H. R. & Zorn, A. M. The core endodermal gene network of vertebrates: combining developmental precision with evolutionary flexibility. Bioessays 30, 757–765 (2008)

    PubMed  Google Scholar 

  26. Cvekl, A. & Duncan, M. K. Genetic and epigenetic mechanisms of gene regulation during lens development. Prog. Retin. Eye Res. 26, 555–597 (2007)

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Kumar, J. P. The molecular circuitry governing retinal determination. Biochim. Biophys. Acta 1789, 306–314 (2009)

    CAS  PubMed  Google Scholar 

  28. Pimanda, J. E. et al. Gata2, Fli1, and Scl form a recursively wired gene-regulatory circuit during early hematopoietic development. Proc. Natl Acad. Sci. USA 104, 17692–17697 (2007)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  29. Smith, P. A. & Mango, S. E. Role of T-box gene tbx-2 for anterior foregut muscle development in C. elegans . Dev. Biol. 302, 25–39 (2007)

    CAS  PubMed  Google Scholar 

  30. Cripps, R. M. & Olson, E. N. Control of cardiac development by an evolutionarily conserved transcription network. Dev. Biol. 246, 14–28 (2002)

    CAS  PubMed  Google Scholar 

  31. Reim, I., Mohler, J. P. & Frasch, M. Tbx20-related genes, mid and H15 are required for tinman expression, proper patterning, and normal differentiation of cardioblasts in Drosophila . Mech. Dev. 122, 1056–1069 (2005)

    CAS  PubMed  Google Scholar 

  32. Albert, R. & Othmer, H. G. The topology of the regulatory interactions predicts the expression pattern of the segment polarity genes in Drosophila melanogaster . J. Theor. Biol. 223, 1–18 (2003)

    MathSciNet  CAS  PubMed  PubMed Central  Google Scholar 

  33. Nishi, Y., Ji, H., Wong, W. H., McMahon, A. P. & Vokes, S. A. Modeling the spatio-temporal network that drives patterning in the vertebrate central nervous system. Biochim. Biophys. Acta 1789, 299–305 (2009)

    CAS  PubMed  Google Scholar 

  34. Vokes, S. A., Ji, H., Wong, W. H. & McMahon, A. P. A genome-scale analysis of the cis-regulatory circuitry underlying sonic hedgehog-mediated patterning of the mammalian limb. Genes Dev. 22, 2651–2663 (2008)

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Ririe, T. O., Fernandes, J. S. & Sternberg, P. W. The Caenorhabditis elegans vulva: A post-embryonic gene regulatory network controlling organogenesis. Proc. Natl Acad. Sci. USA 105, 20095–20099 (2008)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  36. Graf, T. & Enver, T. Forcing cells to change lineages. Nature 462, 587–594 (2009)This review comprehensively traverses the process of terminal lineage fate choice in pluripotential hematopoietic systems.

    ADS  CAS  PubMed  Google Scholar 

  37. Swiers, G., Patient, R. & Loose, M. Genetic regulatory networks programming hematopoietic stem cells and erythroid lineage specification. Dev. Biol. 294, 525–540 (2006)

    CAS  PubMed  Google Scholar 

  38. Laslo, P. et al. Multilineage transcription priming and determination of alternate hematopoietic cell fates. Cell 126, 755–766 (2006)This paper exemplifies a commonly used mathematical approach invoking bi-stable state kinetics to explain lineage choice.

    CAS  PubMed  Google Scholar 

  39. Smith, J. & Davidson, E. H. Gene regulatory network subcircuit controlling a dynamic spatial pattern of signaling in the sea urchin embryo. Proc. Natl Acad. Sci. USA 105, 20089–20094 (2008)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  40. Zhang, P. et al. Negative cross-talk between hematopoietic regulators: GATA proteins repress PU.1. Proc. Natl Acad. Sci. USA 96, 8705–8710 (1999)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  41. Huang, S., Guo, Y.-P., May, G. & Enver, T. Bifurcation dynamics in lineage-commitment in bipotent progenitor cells. Dev. Biol. 305, 695–713 (2007)

    CAS  PubMed  Google Scholar 

  42. Stopka, T., Amanatullah, D. F., Papetti, M. & Skoultchi, A. I. PU.1 inhibits the erythroid program by binding to GATA-1 on DNA and creating a repressive chromatin structure. EMBO J. 24, 3712–3723 (2005)

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Starck, J. et al. Functional cross-antagonism between transcription factors FLI-1 and EKLF. Mol. Cell. Biol. 23, 1390–1402 (2003)

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Rothenberg, E. V. Decision by committee: new light on the CD4/CD8-lineage choice. Immunol. Cell Biol. 87, 109–112 (2009)

    CAS  PubMed  Google Scholar 

  45. Wang, L. & Bosselut, R. CD4–CD8 lineage differentiation: Thpok-ing into the nucleus. J. Immunol. 183, 2903–2910 (2009)

    CAS  PubMed  Google Scholar 

  46. Setoguchi, R. et al. Repression of the transcription factor Th-POK by Runx complexes in cytotoxic T cell development. Science 319, 822–825 (2008)

    ADS  CAS  PubMed  Google Scholar 

  47. Narula, J., Smith, A. M. & Gottgens, B. and Igoshin, O. A. Modeling reveals bistability and low-pass filtering in the network module determining blood stem cell fate. PLoS Comput. Biol. 6, e1000771 (2010)

    PubMed  PubMed Central  Google Scholar 

  48. Hu, M. et al. Multilineage gene expression precedes commitment in the hemopoietic system. Genes Dev. 11, 774–785 (1997)

    CAS  PubMed  Google Scholar 

  49. Miyamoto, T. et al. Myeloid or lymphoid promiscuity as a critical step in hematopoietic lineage commitment. Dev. Cell 3, 137–147 (2002)

    CAS  PubMed  Google Scholar 

  50. Lagha, M. et al. Pax3:Foxc2 reciprocal repression in the somite modulates muscular versus vascular cell fate choice in multipotent progenitors. Dev. Cell 17, 892–899 (2009)

    CAS  PubMed  Google Scholar 

  51. Johnson, R. J., Jr, Chang, S., Etchberger, J. F., Ortiz, C. O. & Hobert, O. MicroRNAs acting in a double-negative feedback loop to control a neuronal cell fate decision. Proc. Natl Acad. Sci. USA 102, 12449–12454 (2005)

    ADS  Google Scholar 

  52. Vierbuchen, T. et al. Direct conversion of fibroblasts to functional neurons by defined factors. Nature 463, 1035–1041 (2010)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  53. Zhou, Q., Brown, J., Kanarek, A., Rajagopal, J. & Melton, D. A. In vivo reprogramming of adult pancreatic exocrine cells to β-cells. Nature 455, 627–632 (2008)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  54. Gilchrist, M. et al. Systems biology approaches identify ATF3 as a negative regulator of Toll-like receptor 4. Nature 441, 173–178 (2006)

    ADS  CAS  PubMed  Google Scholar 

  55. Hobert, O. Regulatory logic of neuronal diversity: Terminal selector genes and selector motifs. Proc. Natl Acad. Sci. USA 105, 20067–20071 (2008)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  56. Bröhl, D. et al. A transcriptional network coordinately determines transmitter and peptidergic fate in the dorsal spinal chord. Dev. Biol. 322, 381–393 (2008)

    PubMed  Google Scholar 

  57. Yun, K. & Wold, B. Skeletal muscle determination and differentiation: story of a core regulatory network and its context. Curr. Opin. Cell Biol. 8, 877–889 (1996)

    CAS  PubMed  Google Scholar 

  58. Pan, G. & Thomson, J. A. Nanog and transcriptional networks in embryonic stem cell pluripotency. Cell Res. 17, 42–49 (2007)

    CAS  PubMed  Google Scholar 

  59. Boyer, L. A. et al. Core transcriptional regulatory circuitry in human embryonic stem cells. Cell 122, 947–956 (2005)

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Zhou, Q., Chipperfield, H., Melton, D. A. & Wong, W. H. A gene regulatory network in mouse embryonic stem cells. Proc. Natl Acad. Sci. USA 104, 16438–16443 (2007)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  61. Boyer, L. A. et al. Polycomb complexes repress developmental regulators in murine embryonic stem cells. Nature 441, 349–353 (2006)

    ADS  CAS  PubMed  Google Scholar 

  62. Mortazavi, A., Chen Leeper Thompson, E., Garcia, S. T., Myers, R. M. & Wold, B. Comparative genomics modeling of the NRSF/REST repressor network: from single conserved sites to genome-wide repertoire. Genome Res. 16, 1208–1221 (2006)

    CAS  PubMed  PubMed Central  Google Scholar 

  63. Zhu, X. & Rosenfeld, M. G. Transcriptional control of precursor proliferation in the early phases of pituitary development. Curr. Opin. Genet. Dev. 14, 567–574 (2004)

    CAS  PubMed  Google Scholar 

  64. Bessa, J. et al. meis1 regulates cyclin D1 and c-myc expression, and controls the proliferation of the multipotent cells in the early developing zebrafish eye. Development 135, 799–803 (2008)

    CAS  PubMed  Google Scholar 

  65. Christiaen, L. et al. The transcription/migration interface in heart precursors of Ciona intestinalis . Science 320, 1349–1352 (2008)This paper presents direct evidence of the regulatory structure of a morphogenetic gene cassette, showing that only certain key genes are controlled by the upstream GRN while a majority are expressed anyway.

    ADS  CAS  PubMed  Google Scholar 

  66. Chanut-Delalande, H., Fernandes, I., Roch, F., Payre, F. & Plaza, S. Shavenbaby couples patterning to epidermal cell shape control. PLoS Biol. 4, 1549–1561 (2006)

    CAS  Google Scholar 

  67. Amit, I. et al. Unbiased reconstruction of a mammalian transcriptional network mediating pathogen responses. Science 326, 257–263 (2009)This paper presents the most complete analysis yet available of structure and function in a physiological GRN.

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  68. Rosenfeld, N. & Alon, U. Response delays and the structure of transcription networks. J. Mol. Biol. 329, 645–654 (2003)

    CAS  PubMed  Google Scholar 

  69. Bolouri, H. Computational Modeling of Gene Regulatory Networks – A Primer (Imperial College Press, 2008)

    Google Scholar 

  70. Sánchez, L. & Thieffry, D. A logical analysis of the gap gene system. J. Theor. Biol. 211, 115–141 (2001)

    PubMed  Google Scholar 

  71. Jaeger, J. et al. Dynamical analysis of regulatory interactions in the gap gene system of Drosophila melanogaster . Genetics 167, 1721–1737 (2004)

    CAS  PubMed  PubMed Central  Google Scholar 

  72. Perkins, T. J., Jaeger, J., Reintz, J. & Glass, L. Reverse engineering the gap gene network of Drosophila melanogaster . PLoS Comput. Biol. 2, e051 (2006)This paper provides a comprehensive computational treatment of the Drosophila gap gene network using estimates of numerous constants obtained by high resolution imaging.

    ADS  Google Scholar 

  73. Rivera-Pomar, R. & Jaeckle, H. From gradients to stripes in Drosophila mebryogenesis: filling in the gaps. Trends Genet. 12, 478–483 (1996)

    CAS  PubMed  Google Scholar 

  74. Kraut, R. & Levine, M. Mutually repressive interactions between the gap genes giant and Krüpple define middle body regions of the Drosophila embryo. Development 111, 611–621 (1991)

    CAS  PubMed  Google Scholar 

  75. Segal, E., Raveh-Sadka, T., Schroeder, M., Unnerstall, U. & Gaul, U. Predicting expression patterns from regulatory sequence in Drosophila segmentation. Nature 451, 535–540 (2008)

    ADS  CAS  PubMed  Google Scholar 

  76. Lembong, J., Yakoby, N. & Shvartsman, S. Y. Pattern formation by dynamically interacting network motifs. Proc. Natl Acad. Sci. USA 106, 3213–3218 (2009)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  77. Dessaud, E. et al. Dynamic assignment and maintenance of positional identity in the ventral neural tube by the morphogen Sonic hedgehog. PLoS Biol. 8, e1000382 (2010)This paper provides a new insight into how positional values of Hedgehog ligand are used to set transcriptional thresholds.

    PubMed  PubMed Central  Google Scholar 

  78. Ribes, V. & Briscoe, J. Establishing and interpreting graded Sonic Hedgehog signaling during vertebrate neural tube patterning: the role of negative feedback. Cold Spring Harb. Perspect. Biol. 1, a002014 (2009)

  79. Goentoro, L., Shoval, O., Kirschner, M. W. & Alon, U. The incoherent feedforward loop can provide fold-change detection in gene regulation. Mol. Cell 36, 894–899 (2009)This analysis shows how a common GRN sub-circuit can operate to interpret relative changes in signal strength.

    CAS  PubMed  PubMed Central  Google Scholar 

  80. Goentoro, L. & Kirschner, M. W. Evidence that fold-change, and not absolute level, of β-catenin dictates Wnt signaling. Mol. Cell 36, 872–884 (2009)

    CAS  PubMed  PubMed Central  Google Scholar 

  81. Spooner, C. J. et al. A recurrent network involving the transcription factors PU.1 and Gfi1 orchestrates innate and adaptive immune cell fates. Immunity 31, 576–586 (2009)

    CAS  PubMed  PubMed Central  Google Scholar 

  82. Chickarmane, V., Enver, T. & Peterson, C. Computational modeling of the hematopoietic erythroid-myeloid switch reveals insights into cooperativity, priming, and irreversibility. PLoS Comput. Biol. 5, e1000268 (2009)This paper presents an alternative computational treatment of lineage choice in a haematopoietic system.

  83. Shea, M. A. & Ackers, G. K. The OR control system of bacteriophage lambda: A physical-chemical model for gene regulation. J. Mol. Biol. 181, 211–230 (1985)

    CAS  PubMed  Google Scholar 

  84. Bolouri, H. & Davidson, E. H. Transcriptional regulatory cascades in development: Initial rates, not steady state, determine network kinetics. Proc. Natl Acad. Sci. USA 100, 9371–9376 (2003)This paper models sea urchin regulatory cascade kinetics and demonstrates using measured constants that genes are successively activated long before any of the transcriptional functions attain steady state.

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  85. Materna, S. C., Nam, J. & Davidson, E. H. High accuracy, high-resolution prevalence measurement for the majority of locally expressed regulatory genes in early sea urchin development. Gene Expr. Patterns 10, 177–184 (2010)

    CAS  PubMed  PubMed Central  Google Scholar 

  86. Davidson, E. H. & Erwin, D. H. Gene regulatory networks and the evolution of animal body plans. Science 311, 796–800 (2006)This paper introduced the theory that highly conserved GRN sub-circuits account for the phylogenetic distribution of major characters of the animal body plan.

    ADS  CAS  PubMed  Google Scholar 

  87. Erwin, D. H. & Davidson, E. H. The evolution of hierarchical gene regulatory networks. Nature Rev. Genet. 10, 141–148 (2009)

    CAS  PubMed  Google Scholar 

  88. Davidson, E. H. & Erwin, D. H. An integrated view of Precambrian eumetazoan evolution. Cold Spring Harb. Symp. Quant. Biol. 74, 65–80 (2009)

    CAS  PubMed  Google Scholar 

  89. Gao, F. & Davidson, E. H. Transfer of a large gene regulatory apparatus to a new developmental address in echinoid evolution. Proc. Natl Acad. Sci. USA 105, 6091–6096 (2008)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  90. Hinman, V. F. & Davidson, E. H. Evolutionary plasticity of developmental gene regulatory network architecture. Proc. Natl Acad. Sci. USA 104, 19404–19409 (2007)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  91. Hinman, V. F., Yankura, K. A. & McCauley, B. S. Evolution of gene regulatory network architectures: Examples of subcircuit conservation and plasticity between classes of echinoderms. Biochim. Biophys. Acta 1789, 326–332 (2009)

    CAS  PubMed  Google Scholar 

  92. Bolouri, H. & Davidson, E. H. The gene regulatory network basis of the “community effect,” and analysis of a sea urchin embryo example. Dev. Biol. 340, 170–178 (2010)

    CAS  PubMed  Google Scholar 

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Acknowledgements

I am grateful for the reviews of the manuscript by E. V. Rothenberg and I. S. Peter. This work was supported by NIH grants HD-37105 and GM-61005 and by the Lucille P. Markey Charitable Trust.

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Correspondence to Eric H. Davidson.

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Davidson, E. Emerging properties of animal gene regulatory networks. Nature 468, 911–920 (2010). https://doi.org/10.1038/nature09645

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