Tree Genetics & Genomes

, Volume 4, Issue 2, pp 263–278 | Cite as

Quantitative trait loci controlling water use efficiency and related traits in Quercus robur L.

  • Oliver Brendel
  • Didier Le Thiec
  • Caroline Scotti-Saintagne
  • Catherine Bodénès
  • Antoine Kremer
  • Jean-Marc Guehl
Original Paper


Genetic variation for intrinsic water use efficiency (Wi) and related traits was estimated in a full-sib family of Quercus robur L. over 3 years. The genetic linkage map available for this F1 family was used to locate quantitative trait loci (QTL) for Wi, as estimated by leaf carbon stable isotope composition (δ13C) or the ratio of net CO2 assimilation rate (A) to stomatal conductance to water vapour (gw) and related leaf traits. Gas exchange measurements were used to standardize estimates of A and gw and to model the sensitivity of gw to leaf-to-air vapour pressure deficit (sgVPD). δ13C varied by more than 3‰ among the siblings, which is equivalent to 40% variation of Wi. Most of the studied traits exhibited high clonal mean repeatabilities (>50%; proportion of clonal mean variability in global variance). Repeatabilities for δ13C, leaf mass per area (LMA) and leaf nitrogen content were higher than 70%. For δ13C, ten QTLs were detected, one of which was detected repeatedly for all 3 years and consistently explained more than 20% of measured variance. Four genomic regions were found in which co-localizing traits linked variation in Wi to variations in leaf chlorophyll and nitrogen content, LMA and sgVPD. A positive correlation using clonal means between δ13C and A/gw, as well as a co-localisation of QTL detected for both traits, can be seen as validation of the theoretical model linking the genetic architecture of these two traits.


Quercus robur Carbon isotope composition δ13Water use efficiency QTL 


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Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  • Oliver Brendel
    • 1
  • Didier Le Thiec
    • 1
  • Caroline Scotti-Saintagne
    • 2
    • 3
  • Catherine Bodénès
    • 2
  • Antoine Kremer
    • 2
  • Jean-Marc Guehl
    • 1
  1. 1.UMR INRA-UHP 1137, Ecologie et Ecophysiologie ForestièresCentre INRA de NancyChampenouxFrance
  2. 2.Equipe de GénétiqueUMR BIOGECO 1202 INRACestasFrance
  3. 3.Ecologie des forêts de Guyane (ECOFOG)UMR INRA-ENGREF-CIRAD-CNRS-UAGKourouFrance

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