Gap gene regulatory dynamics evolve along a genotype network
Developmental gene networks implement the dynamic regulatory mechanisms that pattern and shape the organism. Over evolutionary time, the wiring of these networks changes, yet the patterning outcome is often preserved, a phenomenon known as "system drift." System drift is illustrate...
| Autores: | , , , |
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| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2016 |
| País: | España |
| Recursos: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10230/26864 |
| Acesso em linha: | http://hdl.handle.net/10230/26864 http://dx.doi.org/10.1093/molbev/msw013 |
| Access Level: | acceso abierto |
| Palavra-chave: | Biologia del desenvolupament Evolutionary developmental biology Evolutionary systems biology Gap gene network Network evolution Reverse engineering System drift |
| Resumo: | Developmental gene networks implement the dynamic regulatory mechanisms that pattern and shape the organism. Over evolutionary time, the wiring of these networks changes, yet the patterning outcome is often preserved, a phenomenon known as "system drift." System drift is illustrated by the gap gene network-involved in segmental patterning-in dipteran insects. In the classic model organism Drosophila melanogaster and the nonmodel scuttle fly Megaselia abdita, early activation and placement of gap gene expression domains show significant quantitative differences, yet the final patterning output of the system is essentially identical in both species. In this detailed modeling analysis of system drift, we use gene circuits which are fit to quantitative gap gene expression data in M. abdita and compare them with an equivalent set of models from D. melanogaster. The results of this comparative analysis show precisely how compensatory regulatory mechanisms achieve equivalent final patterns in both species. We discuss the larger implications of the work in terms of "genotype networks" and the ways in which the structure of regulatory networks can influence patterns of evolutionary change (evolvability). |
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