Coordinatore | TEL AVIV UNIVERSITY
Organization address
address: RAMAT AVIV contact info |
Nazionalità Coordinatore | Israel [IL] |
Totale costo | 100˙000 € |
EC contributo | 100˙000 € |
Programma | FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) |
Code Call | FP7-PEOPLE-2007-4-3-IRG |
Funding Scheme | MC-IRG |
Anno di inizio | 2009 |
Periodo (anno-mese-giorno) | 2009-02-01 - 2013-05-31 |
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TEL AVIV UNIVERSITY
Organization address
address: RAMAT AVIV contact info |
IL (TEL AVIV) | coordinator | 0.00 |
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'Mixing of genetic material coming from different individuals is central for the generation of new genetic combinations, and plays a major role in evolution. Most evolutionary models implicitly assume that genetic mixing has a uniform rate at all times. In contrast, this research will investigate an alternative hypothesis: that genetic mixing is plastic, its rate depending on the state of the organism, so that less fit individuals have a higher tendency for mixing. The research will concentrate on three mechanisms of mixing: sexual reproduction, outcrossing and dispersal. The investigator will develop and analyze mathematical models and simulations of fitness associated mixing, in order to identify conditions favoring the evolution of fitness associated mixing, and to predict its implications for adaptation. This research is a necessary step towards understanding the evolutionary basis and the implications of plastic genetic variation. By improving our understanding of the way genetic variation acts and evolves, the results of this research will affect many evolutionary and ecological models, and guide future experimental efforts. In addition to its direct theoretical significance, it would improve our understanding of how populations react to a changing environment – an issue of critical importance in conservation biology. It may also provide new insights regarding the accelerated evolution of drug resistant pathogen strains in response to successful drug treatment.'
New genetic combinations are central to evolution. Simulation of genetic mixing can predict the implications of adaptation, particularly relevant in the face of increasing incidence of drug-resistant microbes.