Originally published as Genetics Published Articles Ahead of Print on April 2, 2006.

Genetics, Vol. 173, 1023-1031, June 2006, Copyright © 2006
doi:10.1534/genetics.104.036541

Building of an Experimental Cline With Arabidopsis thaliana to Estimate Herbicide Fitness Cost

Fabrice Roux^*,1, Sandra Giancola^,, Stéphanie Durand^, and Xavier Reboud^*,2

^* UMR Biologie et Gestion des Adventices, Institut National de la Recherche Agronomique, 21065 Dijon Cedex, France, Centre National de Génotypage, 91057 Evry Cedex, France and Station de Génétique et Amélioration des Plantes, INRA, 78026 Versailles Cedex, France

² Corresponding author: UMR Biologie et Gestion des Adventices, 17 rue Sully, Institut National de la Recherche Agronomique, BP86510, 21065 Dijon Cedex, France.
E-mail: reboud{at}dijon.inra.fr

Various management strategies aim at maintaining pesticide resistance frequency under a threshold value by taking advantage of the benefit of the fitness penalty (the cost) expressed by the resistance allele outside the treated area or during the pesticide selection "off years." One method to estimate a fitness cost is to analyze the resistance allele frequency along transects across treated and untreated areas. On the basis of the shape of the cline, this method gives the relative contributions of both gene flow and the fitness difference between genotypes in the treated and untreated areas. Taking advantage of the properties of such migration–selection balance, an artificial cline was built up to optimize the conditions where the fitness cost of two herbicide-resistant mutants (acetolactate synthase and auxin-induced target genes) in the model species Arabidopsis thaliana could be more accurately measured. The analysis of the microevolutionary dynamics in these experimental populations indicated mean fitness costs of 15 and 92% for the csr1-1 and axr2-1 resistances, respectively. In addition, negative frequency dependence for the fitness cost was also detected for the axr2-1 resistance. The advantages and disadvantages of the cline approach are discussed in regard to other methods of cost estimation. This comparison highlights the powerful ability of an experimental cline to measure low fitness costs and detect sensibility to frequency-dependent variations.

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