Abstracts (first author)


Genome-wide analysis of the genetic architecture of flowering time and fitness in wheat experimental populations

Author(s): Thépot S, Goldringer I, Mackay I, Enjalbert J


Flowering time is a major adaptive trait, as it allows plants to synchronize their vegetative cycle with optimal environmental conditions and thus to maximize their fitness. This trait has been studied over 20 generations in different experimental wheat populations, relying on three gene pools: two selfing pools obtained by pyramid crosses of two sets of 16 parents. The third is an outcrossing pool obtained by random crossing of 61 parents by the use of male sterility. These three pools have been dispatched over 12 sites in France, and then cultivated year after year in isolation, without migration or human selection. Fast evolution, both over time and in space, was noticed for flowering time. Using both shifts in allelic, or association genetics, these adaptations were in part explained by polymorphisms at key genes controlling vernalisation or photoperiod sensitivity (Rhoné et al. 2008, 2010). We recently developed an extended study of the outcrossing population, genotyping about 400 SSD lines with a 9k SNPs array (Chao et al. 2010), and performing an extended phenotyping of flowering time, under contrasted environmental conditions (variations in vernalization and photoperiod). With this highly recombinant and highly diverse population we describe the distribution of effects over detected QTNs, the major QTNs corresponding to previously described candidate genes. The detected QTNs x environment interactions highlight the genetics of local adaptation. Comparing major genes handled by plant breeders, and results obtained on wheat experimental populations, we will show how the genetic architecture of flowering time and its strong interaction with environment can explain the genetic architecture of fitness traits in natural populations.


Chairman: Octávio S. Paulo
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XIV Congress of the European Society for Evolutionary Biology

Organization Team
Department of Animal Biology (DBA)
Faculty of Sciences of the University of Lisbon
P-1749-016 Lisbon


Computational Biology & Population Genomics Group