JXB Advance Access published online on July 30, 2004
Journal of Experimental Botany, doi:10.1093/jxb/erh200
© 2004 by Oxford University Press
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
1 INRA - ENSAM1, Laboratoire d'Ecophysiologie des Plantes sous Stress Environnementaux, 2, Place Pierre Viala, F-34060 Montpellier cedex 1, France; Present address: CEA - LBDP. Laboratoire de Biologie et du Développement des Plantes. Cadarache, France
* To whom correspondence should be addressed. E-mail: francois.tardieu{at}ensam.inra.fr.
Quantitative genetics of adaptive traits is made difficult by the genotypexenvironment interaction. A classical assumption is that QTLs identified in both stressed and control conditions correspond to constitutive traits whereas those identified only in stressed treatments are stress-specific and correspond to adaptive traits. This hypothesis was tested by comparing, in the same set of experiments, two ways of analysing the genetic variability of the responses of maize leaf growth to water deficit. One QTL detection was based on raw phenotypic traits (length and width of leaf 6) of 100 recombinant inbred lines (RILs) in four experiments with either well-watered or stressing conditions in the field or in the greenhouse. Another detection followed a method proposed recently which consists of analysing intrinsic responses of the same RILs to environmental conditions, determined jointly over several experiments. QTLs of three responses were considered: (i) leaf elongation rate per unit thermal time in the absence of stress, (ii) its response to evaporative demand in well-watered plants, and (iii) its response to soil water status in the absence of evaporative demand. The QTL of leaf length differed between experiments, but colocalized in seven cases out of 13 with QTLs of the intrinsic leaf elongation rate, even in experiments with stressing conditions. No colocalization was found between QTLs of leaf length under water deficit and QTLs of responses to air or soil water status. By contrast, QTLs of leaf width colocalized in all experiments, regardless of environmental conditions. The classical method of identifying the QTL of constitutive versus adaptive traits therefore did not apply to the experiments presented here. It is suggested that identification of the QTL of parameters of response curves provides a promising alternative for dealing with the genetic variability of adaptive traits.
Accepted May 14, 2004
Water Saving Agriculture Special Issue Article
Dealing with the genotypexenvironment interaction via a modelling approach: a comparison of QTLs of maize leaf length or width with QTLs of model parameters
2 INRA - ENSAM1, Laboratoire d'Ecophysiologie des Plantes sous Stress Environnementaux, 2, Place Pierre Viala, F-34060 Montpellier cedex 1, France
![]()
Abstract ![]()
CiteULike
Connotea
Del.icio.us What's this?
This article has been cited by other articles:
![]() |
R. Tuberosa, S. Salvi, S. Giuliani, M. C. Sanguineti, M. Bellotti, S. Conti, and P. Landi Genome-wide Approaches to Investigate and Improve Maize Response to Drought Crop Sci., December 18, 2007; 47(Supplement_3): S-120 - S-141. [Abstract] [Full Text] [PDF] |
||||
![]() |
B. Hirel, J. Le Gouis, B. Ney, and A. Gallais The challenge of improving nitrogen use efficiency in crop plants: towards a more central role for genetic variability and quantitative genetics within integrated approaches J. Exp. Bot., July 1, 2007; 58(9): 2369 - 2387. [Abstract] [Full Text] [PDF] |
||||
![]() |
C Welcker, B Boussuge, C Bencivenni, J-M Ribaut, and F Tardieu Are source and sink strengths genetically linked in maize plants subjected to water deficit? A QTL study of the responses of leaf growth and of Anthesis-Silking Interval to water deficit J. Exp. Bot., January 1, 2007; 58(2): 339 - 349. [Abstract] [Full Text] [PDF] |
||||
![]() |
B. Muller, G. Bourdais, B. Reidy, C. Bencivenni, A. Massonneau, P. Condamine, G. Rolland, G. Conejero, P. Rogowsky, and F. Tardieu Association of Specific Expansins with Growth in Maize Leaves Is Maintained under Environmental, Genetic, and Developmental Sources of Variation Plant Physiology, January 1, 2007; 143(1): 278 - 290. [Abstract] [Full Text] [PDF] |
||||
![]() |
J. HILLIER, D. MAKOWSKI, and B. ANDRIEU Maximum Likelihood Inference and Bootstrap Methods for Plant Organ Growth via Multi-phase Kinetic Models and their Application to Maize Ann. Bot., July 1, 2005; 96(1): 137 - 148. [Abstract] [Full Text] [PDF] |
||||



