Year: 2018
Type: article
Abstract: Phenotypic variation is the raw material of adaptive Darwinian evolution. The phenotypic variation found in organismal development is biased towards certain phenotypes, but the molecular mechanisms behind such biases are still poorly understood. Gene regulatory networks have been proposed as one cause of constrained phenotypic variation. However, most pertinent evidence is theoretical rather than experimental. Here, we study evolutionary biases in two synthetic gene regulatory circuits expressed in Escherichia coli that produce a gene expression stripe—a pivotal pattern in embryonic development. The two parental circuits produce the same phenotype, but create it through different regulatory mechanisms. We show that mutations cause distinct novel phenotypes in the two networks and use a combination of experimental measurements, mathematical modelling and DNA sequencing to understand why mutations bring forth only some but not other novel gene expression phenotypes. Our results reveal that the regulatory mechanisms of networks restrict the possible phenotypic variation upon mutation. Consequently, seemingly equivalent networks can indeed be distinct in how they constrain the outcome of further evolution.
Source: Molecular Systems Biology
Authors: Yolanda Schaerli, Alba Jiménez, José M. Duarte, Ljiljana Mihajlovic, Julien Renggli, Mark Isalan, James Sharpe, Andreas Wagner
Institutions: University of Zurich, University of Lausanne, Universitat Pompeu Fabra, European Molecular Biology Laboratory, Centre for Genomic Regulation, Centre for Independent Social Research, Imperial College London, Institució Catalana de Recerca i Estudis Avançats, SIB Swiss Institute of Bioinformatics, Santa Fe Institute
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,596
Funders: National Science Foundation, Wellcome Trust, European Commission, Volkswagen Foundation, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Generalitat de Catalunya, Ministerio de Economía y Competitividad, Universität Zürich, Ministerio de Asuntos Económicos y Transformación Digital, Gobierno de España, SystemsX.ch, Seventh Framework Programme, H2020 Excellent Science, H2020 European Research Council
Awards: G119964413, G1323383031, G1835917608, Noise and robustness in the evolution of novel protein phenotypes, Gene network engineering: quantifying emergent gene expression in cancer and antibiotic resistance., G2924091460, G3207356259, G3639294010, G3691775108, G393177772, A theoretical framework for swarms of GRN-controlled agents which display adaptive tissue-like organisation, G4104599821, G434337789, Robustness and evolutionary parameter drift of stripe-forming gene regulatory networks, G5110352083, Phenotypic innovation, robustness, and recombination in genome-scale metabolic networks, G5702163051, Evolutionary Synthetic Biology: System drift in action, G8550171036
OpenAlex ID: W2890052694