Efficient escape from local optima in a highly rugged fitness landscape by evolving RNA virus populations

[EN] Predicting viral evolution has proven to be a particularly difficult task, mainly owing to our incomplete knowledge of some of the fundamental principles that drive it. Recently, valuable information has been provided about mutation and recombination rates, the role of genetic drift and the dis...

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Hauptverfasser: Cervera-Benet, Héctor, Lalic, Jasna, Elena Fito, Santiago Fco
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Sprache:eng
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Zusammenfassung:[EN] Predicting viral evolution has proven to be a particularly difficult task, mainly owing to our incomplete knowledge of some of the fundamental principles that drive it. Recently, valuable information has been provided about mutation and recombination rates, the role of genetic drift and the distribution of mutational, epistatic and pleiotropic fitness effects. However, information about the topography of virus' adaptive landscapes is still scarce, and to our knowledge no data has been reported so far on how its ruggedness may condition virus' evolvability. Here, we show that populations of an RNA virus move efficiently on a rugged landscape and scape from the basin of attraction of a local optimum. We have evolved a set of Tobacco etch virus genotypes located at increasing distances from a local adaptive optimum in a highly rugged fitness landscape, and we observed that few evolved lineages remained trapped in the local optimum, while many others explored distant regions of the landscape. Most of the diversification in fitness among the evolved lineages was explained by adaptation, while historical contingency and chance events contribution was less important. Our results demonstrate that the ruggedness of adaptive landscapes is not an impediment for RNA viruses to efficiently explore remote parts of it. This project was funded by grant nos. BFU2012-30805 and BFU2015-65037P from the Spanish Ministry of Economy and Competitiveness (MINECO), PROMETEOII/2014/021 from Generalitat Valenciana and EvoEvo (ICT610427) from the European Commission 7th Framework Program to S.F.E. H.C. was supported by contract BES2013-065595 from MINECO. J.L. was supported by a JAE-pre contract from CSIC. Cervera-Benet, H.; Lalic, J.; Elena Fito, SF. (2016). Efficient escape from local optima in a highly rugged fitness landscape by evolving RNA virus populations. Proceedings of the Royal Society B: Biological Sciences. 283:1-8. https://doi.org/10.1098/rspb.2016.0984