Data-driven modelling of a gene regulatory network for cell fate decisions in the growing limb bud
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- dc.contributor.author Uzkudun, Manuca
- dc.contributor.author Marcon, Luciano, 1983-ca
- dc.contributor.author Sharpe, Jamesca
- dc.date.accessioned 2015-11-16T15:06:58Z
- dc.date.available 2015-11-16T15:06:58Z
- dc.date.issued 2015
- dc.description.abstract Parameter optimization coupled with model selection is a convenient approach to infer gene regulatory networks from experimental gene expression data, but so far it has been limited to single cells or static tissues where growth is not significant. Here, we present a computational study in which we determine an optimal gene regulatory network from the spatiotemporal dynamics of gene expression patterns in a complex 2D growing tissue (non-isotropic and heterogeneous growth rates). We use this method to predict the regulatory mechanisms that underlie proximodistal (PD) patterning of the developing limb bud. First, we map the expression patterns of the PD markers Meis1, Hoxa11 and Hoxa13 into a dynamic description of the tissue movements that drive limb morphogenesis. Secondly, we use reverse-engineering to test how different gene regulatory networks can interpret the opposing gradients of fibroblast growth factors (FGF) and retinoic acid (RA) to pattern the PD markers. Finally, we validate and extend the best model against various previously published manipulative experiments, including exogenous application of RA, surgical removal of the FGF source and genetic ectopic expression of Meis1. Our approach identifies the most parsimonious gene regulatory network that can correctly pattern the PD markers downstream of FGF and RA. This network reveals a new model of PD regulation which we call the "crossover model", because the proximal morphogen (RA) controls the distal boundary of Hoxa11, while conversely the distal morphogens (FGFs) control the proximal boundaryca
- dc.format.mimetype application/pdfca
- dc.identifier.citation Uzkudun M, Marcon L, Sharpe J. Data-driven modelling of a gene regulatory network for cell fate decisions in the growing limb bud. Molecular systems biology. 2015;11(7):815. DOI: 10.15252/msb.20145882ca
- dc.identifier.doi http://dx.doi.org/10.15252/msb.20145882
- dc.identifier.issn 1744-4292
- dc.identifier.uri http://hdl.handle.net/10230/25107
- dc.language.iso engca
- dc.publisher Wiley Blackwellca
- dc.relation.ispartof Molecular systems biology. 2015;11(7):815
- dc.rights © 2015 The Authors. Published under the terms of the CC BY 4.0 license. This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.ca
- dc.rights.accessRights info:eu-repo/semantics/openAccessca
- dc.rights.uri http://creativecommons.org/licenses/by-nc/4.0/ca
- dc.subject.keyword Gene regulatory networks
- dc.subject.keyword Limb development
- dc.subject.keyword Morphogen
- dc.subject.keyword Patterning
- dc.subject.keyword Reverse‐engineering
- dc.subject.other Regulació genèticaca
- dc.subject.other Morfogènesica
- dc.title Data-driven modelling of a gene regulatory network for cell fate decisions in the growing limb budca
- dc.type info:eu-repo/semantics/articleca
- dc.type.version info:eu-repo/semantics/publishedVersionca