INVESTIGADORES
FRANKEL Nicolas
artículos
Título:
Gene regulatory network architecture in different developmental contexts influences the genetic basis of morphological evolution
Autor/es:
SEBASTIAN KITTELMANN; ALEXANDRA D. BUFFRY; FRANZISKA A. FRANKE; ISABEL ALMUDI; MARIANNE YOTH; GONZALO SABARIS; JUAN PABLO COUSO; MARIA D. S.NUNES; NICOLÁS FRANKEL; JOSÉ LUIS GÓMEZ-SKARMETA; JOSE PUEYO-MARQUES; SAAD ARIF; ALISTAIR P. MCGREGOR
Revista:
PLOS Genetics
Editorial:
Plos
Referencias:
Año: 2018 vol. 14
Resumen:
Convergent phenotypic evolution is often caused by recurrent changes at particular nodes in the underlying gene regulatory networks (GRNs). The genes at such evolutionary ?hotspots? are thought to maximally affect the phenotype with minimal pleiotropic consequences. This has led to the suggestion that if a GRN is understood in sufficient detail, the path of evolution may be predictable. The repeated evolutionary loss of larval trichomes among Drosophila species is caused by the loss of shavenbaby (svb) expression. svb is also required for development of leg trichomes, but the evolutionary gain of trichomes in the ?naked valley? on T2 femurs in Drosophila melanogaster is caused by reduced microRNA-92a (miR-92a) expression rather than changes in svb. We compared the expression and function of components between the larval and leg trichome GRNs to investigate why the genetic basis of trichome pattern evolution differs in these developmental contexts. We found key differences between the two networks in both the genes employed, and in the regulation and function of common genes. These differences in the GRNs reveal why mutations in svb are unlikely to contribute to leg trichome evolution and how instead miR-92a represents the key evolutionary switch in this context. Our work shows that variability in GRNs across different developmental contexts, as well as whether a morphological feature is lost versus gained, influence the nodes at which a GRN evolves to cause morphological change. Therefore, our findings have important implications for understanding the pathways and predictability of evolution.