Isalan, M. | bioRxiv Science

bioRxiv2018

Turing patterns are common but not robust

Turing patterns (TPs) underlie many fundamental developmental processes, but they operate over narrow parameter ranges, raising the conundrum of how evolution can ever discover them. Here we explore TP design space to address this question and to distill design rules. We exhaustively analyze 2- and 3-node biological candidate Turing systems: crucially, network structure alone neither determines nor guarantees emergent TPs. A surprisingly large fraction (>60%) of network design space can produce TPs, but these are sensitive to even subtle changes in parameters, network structure and regulatory mechanisms. This implies that TP networks are more common than previously thought, and evolution might regularly encounter prototypic solutions. Importantly, we deduce compositional rules for TP systems that are almost necessary and sufficient (96% of TP networks contain them, and 95% of networks implementing them produce TPs). This comprehensive network atlas provides the blueprints for identifying natural TPs, and for engineering synthetic systems.

developmental biology↗

bioRxiv2017

Mechanistic causes of constrained phenotypic variation revealed by synthetic gene regulatory networks

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 restrictions are still poorly understood. Gene regulatory networks have been proposed as one cause of constrained phenotypic variation. However, most of the evidence for this is theoretical rather than experimental. Here, we study evolutionary biases in two synthetic gene regulatory circuits expressed in E. 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.

systems biology↗