title: A theoretical framework for the regulation of Shh morphogen-controlled gene expression.
abstract: How morphogen gradients govern the pattern of gene expression in developing tissues is not well understood. Here, we describe a statistical thermodynamic model of gene regulation that combines the activity of a morphogen with the transcriptional network it controls. Using Sonic hedgehog (Shh) patterning of the ventral neural tube as an example, we show that the framework can be used together with the principled parameter selection technique of approximate Bayesian computation to obtain a dynamical model that accurately predicts tissue patterning. The analysis indicates that, for each target gene regulated by Gli, which is the transcriptional effector of Shh signalling, there is a neutral point in the gradient, either side of which altering the Gli binding affinity has opposite effects on gene expression. This explains recent counterintuitive experimental observations. The approach is broadly applicable and provides a unifying framework to explain the temporospatial pattern of morphogen-regulated gene expression.
authors.affiliation: MRC-National Institute for Medical Research, The Ridgeway, Mill Hill, London NW7 1AA, UK.
authors.forename: Michael
authors.initials: M
authors.lastname: Cohen
authors.affiliation: Department of Mathematics and CoMPLEX, University College London, Gower Street, London WC1E 6BT, UK.
authors.forename: Karen M
authors.initials: KM
authors.lastname: Page
authors.affiliation: Department of Mathematics and CoMPLEX, University College London, Gower Street, London WC1E 6BT, UK.
authors.forename: Ruben
authors.initials: R
authors.lastname: Perez-Carrasco
authors.affiliation: Department of Cell and Developmental Biology and Department of Genetics, Evolution and Environment, University College London, Gower Street, London WC1E 6BT, UK.
authors.forename: Chris P
authors.initials: CP
authors.lastname: Barnes
authors.affiliation: MRC-National Institute for Medical Research, The Ridgeway, Mill Hill, London NW7 1AA, UK jbrisco@nimr.mrc.ac.uk.
authors.forename: James
authors.initials: J
authors.lastname: Briscoe
mesh_terms: D000465:Algorithms; D000818:Animals; D001499:Bayes Theorem; D019521:Body Patterning; D029721:Drosophila Proteins / Q000378:metabolism*; D004331:Drosophila melanogaster / Q000196:embryology; D020869:Gene Expression Profiling; D018507:Gene Expression Regulation, Developmental; D053263:Gene Regulatory Networks; D053823:Hedgehog Proteins / Q000378:metabolism*; D008962:Models, Theoretical; D012984:Software; D013816:Thermodynamics
chemical_list: D029721:Drosophila Proteins; D053823:Hedgehog Proteins; C578287:Shh protein, Drosophila
keywords: Approximate Bayesian computation; Enhancer; Gene regulation; Gli; Mathematical modelling; Morphogen patterning; Shh; Transcriptional networks