EVOLGA
Modeling the Evolutionary Properties of Complex Genetic Architectures
| Coordinatore | CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE
Organization address
address: Rue Michel -Ange 3 contact info |
| Nazionalità Coordinatore | France [FR] |
| Totale costo | 45˙000 € |
| EC contributo | 45˙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-2009-RG |
| Funding Scheme | MC-ERG |
| Anno di inizio | 2010 |
| Periodo (anno-mese-giorno) | 2010-09-01 - 2013-08-31 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE
Organization address
address: Rue Michel -Ange 3 contact info |
FR (PARIS) | coordinator | 45˙000.00 |
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Obiettivo del progetto (Objective)
'The genetic architecture of morphological, physiological and behavioral characters conditions and constrains the biodiversity of species and their ability to adapt to environmental changes. Gathering and processing qualitative and quantitative information about the genetic mechanisms that underly a trait of interest is thus of tremendous importance in plant and animal breeding, medicine, and evolutionary genetics. However, the complexity of genetic architectures is overwhelming. Recent advances in molecular biology, evo-devo and quantitative genetics have indeed highlighted how intricated were genetic, metabolic and developmental regulation mechanisms in the expression of the gene-to-phenotype relationship. Evolutionary quantitative genetics aims at predicting the evolutionary properties of a population or a species without detailing explicitly the complexity of the genotype-phenotype relationship. To do so, the models that are frequently used do not pretend to provide an exhaustive description of the genetic architecture, but rather to summarize it through some simple parameters, expected to catch key properties of the genotype-phenotype map in a population. The sharp contrast between the complexity of real architectures and the simple picture provided by most quantitative genetics models has often lead to some debate on the relevance of qualitative and quantitative predictions derived from the mathematical simplification of the evolutionary theory. The philosophy of this project is to challenge the capacity for some widely used models to describe and predict the evolutionary potential of populations and species, by contrasting their predictions with empirical data and/or more realistic models. The research objectives detailed thereafter thus focus on the validation and the improvement of the part of the theory of evolution dealing with the complexity of genotype-phenotype maps.'