Fitting Structure to Function in Gene Regulatory Networks

Overview

Journal Hist Philos Life Sci

Specialty Biology

Date 2017 Oct 18

PMID 29038942

Citations 1

Authors

Ellen V Rothenberg

Affiliations

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Abstract

Cascades of transcriptional regulation are the common source of the forward drive in all developmental systems. Increases in complexity and specificity of gene expression at successive stages are based on the collaboration of varied combinations of transcription factors already expressed in the cells to turn on new genes, and the logical relationships between the transcription factors acting and becoming newly expressed from stage to stage are best visualized as gene regulatory networks. However, gene regulatory networks used in different developmental contexts underlie processes that actually operate through different sets of rules, which affect the kinetics, synchronicity, and logical properties of individual network nodes. Contrasting early embryonic development in flies and sea urchins with adult mammalian hematopoietic development from stem cells, major differences are seen in transcription factor dosage dependence, the silencing or damping impacts of repression, and the impact of cellular regulatory history on the parts of the genome that are accessible to transcription factor action in a given cell type. These different features not only affect the kinds of models that can illuminate developmental mechanisms in the respective biological systems, but also reflect the evolutionary needs of these biological systems to optimize different aspects of development.

Citing Articles

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PMID: 31120326 PMC: 6763957. DOI: 10.1089/cmb.2019.0087.

References

Stathopoulos A, Levine M . Localized repressors delineate the neurogenic ectoderm in the early Drosophila embryo. Dev Biol. 2005; 280(2):482-93. DOI: 10.1016/j.ydbio.2005.02.003. View

Nikitina N, Sauka-Spengler T, Bronner-Fraser M . Dissecting early regulatory relationships in the lamprey neural crest gene network. Proc Natl Acad Sci U S A. 2008; 105(51):20083-8. PMC: 2629288. DOI: 10.1073/pnas.0806009105. View

Markstein M, Zinzen R, Markstein P, Yee K, Erives A, Stathopoulos A . A regulatory code for neurogenic gene expression in the Drosophila embryo. Development. 2004; 131(10):2387-94. DOI: 10.1242/dev.01124. View

Britten R, Davidson E . Gene regulation for higher cells: a theory. Science. 1969; 165(3891):349-57. DOI: 10.1126/science.165.3891.349. View

Viets K, Eldred K, Johnston Jr R . Mechanisms of Photoreceptor Patterning in Vertebrates and Invertebrates. Trends Genet. 2016; 32(10):638-659. PMC: 5035628. DOI: 10.1016/j.tig.2016.07.004. View

Schutte J, Wang H, Antoniou S, Jarratt A, Wilson N, Riepsaame J . An experimentally validated network of nine haematopoietic transcription factors reveals mechanisms of cell state stability. Elife. 2016; 5:e11469. PMC: 4798972. DOI: 10.7554/eLife.11469. View

Yuh C, Bolouri H, Davidson E . Genomic cis-regulatory logic: experimental and computational analysis of a sea urchin gene. Science. 1998; 279(5358):1896-902. DOI: 10.1126/science.279.5358.1896. View

Ji H, Ehrlich L, Seita J, Murakami P, Doi A, Lindau P . Comprehensive methylome map of lineage commitment from haematopoietic progenitors. Nature. 2010; 467(7313):338-42. PMC: 2956609. DOI: 10.1038/nature09367. View

Rekhtman N, Radparvar F, Evans T, SKOULTCHI A . Direct interaction of hematopoietic transcription factors PU.1 and GATA-1: functional antagonism in erythroid cells. Genes Dev. 1999; 13(11):1398-411. PMC: 316770. DOI: 10.1101/gad.13.11.1398. View

10.

Miccio A, Wang Y, Hong W, Gregory G, Wang H, Yu X . NuRD mediates activating and repressive functions of GATA-1 and FOG-1 during blood development. EMBO J. 2009; 29(2):442-56. PMC: 2824460. DOI: 10.1038/emboj.2009.336. View

11.

Davidson E . Emerging properties of animal gene regulatory networks. Nature. 2010; 468(7326):911-20. PMC: 3967874. DOI: 10.1038/nature09645. View

12.

Bonzanni N, Garg A, Feenstra K, Schutte J, Kinston S, Miranda-Saavedra D . Hard-wired heterogeneity in blood stem cells revealed using a dynamic regulatory network model. Bioinformatics. 2013; 29(13):i80-8. PMC: 3694641. DOI: 10.1093/bioinformatics/btt243. View

13.

Zhang P, Behre G, Pan J, Iwama A, Wara-Aswapati N, Radomska H . Negative cross-talk between hematopoietic regulators: GATA proteins repress PU.1. Proc Natl Acad Sci U S A. 1999; 96(15):8705-10. PMC: 17580. DOI: 10.1073/pnas.96.15.8705. View

14.

Istrail S, Ben-Tabou de-Leon S, Davidson E . The regulatory genome and the computer. Dev Biol. 2007; 310(2):187-95. DOI: 10.1016/j.ydbio.2007.08.009. View

15.

Del Real M, Rothenberg E . Architecture of a lymphomyeloid developmental switch controlled by PU.1, Notch and Gata3. Development. 2013; 140(6):1207-19. PMC: 3585658. DOI: 10.1242/dev.088559. View

16.

Oguro H, Yuan J, Ichikawa H, Ikawa T, Yamazaki S, Kawamoto H . Poised lineage specification in multipotential hematopoietic stem and progenitor cells by the polycomb protein Bmi1. Cell Stem Cell. 2010; 6(3):279-86. DOI: 10.1016/j.stem.2010.01.005. View

17.

Yui M, Rothenberg E . Developmental gene networks: a triathlon on the course to T cell identity. Nat Rev Immunol. 2014; 14(8):529-45. PMC: 4153685. DOI: 10.1038/nri3702. View

18.

Erwin D, Davidson E . The evolution of hierarchical gene regulatory networks. Nat Rev Genet. 2009; 10(2):141-8. DOI: 10.1038/nrg2499. View

19.

Taghon T, Yui M, Rothenberg E . Mast cell lineage diversion of T lineage precursors by the essential T cell transcription factor GATA-3. Nat Immunol. 2007; 8(8):845-55. PMC: 3140173. DOI: 10.1038/ni1486. View

20.

Hobert O . Development of left/right asymmetry in the Caenorhabditis elegans nervous system: from zygote to postmitotic neuron. Genesis. 2014; 52(6):528-43. DOI: 10.1002/dvg.22747. View