Impact of genetic variation in stomatal conductance on water use efficiency in Quercus robur. Oliver Brendel. INRA Nancy France

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1 Impact of genetic variation in stomatal conductance on water use efficiency in Quercus robur Oliver Brendel INRA Nancy France Unit of Forest Ecology and Ecophysiology In collaboration with INRA Pierroton BIOGECO

2 What is Water Use Efficiency? Water use efficiency WUE Integrated Transpiration Efficiency TE Accumulated biomass Evapotranspired water Accumulated biomass Transpired water Intrinsic W i Net CO 2 Assimilation Rate Stomatal Conductance H2O How to estimate WUE when interested in genetic diversity?

3 1984) Carbon Isotope Discrimination between atmospheric CO 2 and Carbon of Plant Material C MO 13 C MO W i (µmol CO 2 mol -1 H 2 O) R²=0.71; p< C Ft ( ) 45% TE (mg DM g -1 H 2 O) R²=0.71; p< C Bt ( ) - Data from Roussel et al 2009 Ann For Sci... as technique to study genetic variability of Intrinsic Water Use Efficiency (Farquhar et al.

4 White oaks in France Quercus robur Pedunculate oak Quercus petraea Sessile oak (Meusel et al. 1965) Major forest tree species in France : 3.6 Mio ha, 561 Mio m3 (23% of total) Decline episodes following drought periods (1976, 1990) affected particularly Q. robur Improvement programme in France based on exploration of natural genetic variability (provenance trials, seed source selection )

5 Ecology of pedunculate and sessile oaks less Water Fertility Clay Higher tolerance to soil drought Q petraea more Different ecological requirements Q robur Q. petraea : acidic, desaturated and drained soils Higher tolerance to root hypoxia Q. robur : fertile and humid soils

6 Ecology of pedunculate and sessile oaks less Water Fertility Clay Higher tolerance to soil drought Q petraea more Isotopic discrimination shoot ( ) (, ) 18,4 18,0 17,6 17,2 16,8 16,4 16,0 15,6 15,2 Q. petraea Q. robur higher *** W: +7.5% individus stressés DROUGHT Ponton et al *** W:+7% individus témoins CONTROL Wi Q robur lower Higher tolerance to root hypoxia Difference in intrinsic water use efficiency between the two species

7 Diversity of WUE in oaks less Water Fertility Clay Higher tolerance to soil drought Q petraea more higher Wi Q robur lower Is there a variability within species? Higher tolerance to root hypoxia Is this variability genetically determined?

8 Diversity of WUE within species less Water Fertility Clay Higher tolerance to soil drought Q petraea more lower Wi higher Wi Q robur lower Higher tolerance to root hypoxia higher pure mixed mixed pure Q. petraea Q. robur Faivre, B Dupouey JL Dreyer, E

9 Diversity of WUE within species less Water Fertility Clay Higher tolerance to soil drought Q petraea more higher Wi population differences within species spatially organized related to soil gradient Q robur lower Higher tolerance to root hypoxia Is this variability genetically determined?

10 Genetic determinism : QTL approach for pedunculate oak Parents Full-sib family X Genotype Phenotype Genetic map Coll : INRA Pierroton A. Kremer QTL Linkage group

11 Within species variation : one pedunculate oak F1 family ~ 50% Wi No of obs plantations δ 13 C [ ] 3 years of measurements Brendel et al 2008 TGG large variability of W i within this family

12 Major QTL for δ 13 C / W i LG11F LG11M 0.0 ssrqrzag18b 0.0 ssrqrzag18a PEPC activity leaf nitrogen RuBisCO conc. Chlorophylles a/b Carotenoides SF 02 d13c 02 d13c ME E-AAG/M-CTA-70/3 E-AAG/M-CTA-144/5 E-AAG/M-CTT-217/5 ssrqrzag111 E-AAC/M-CTT-296/3 d13c 00- d13c 01- d13c 02- Linkage group 11 male %N 00- d13c ME %N ME LMA 01+ LMA 02+ LMA ME E-AAC/M-CAT-96/5 E-AAC/M-CCT-57/4 P-CAG/M-AGC-308/4* E-AAC/M-CAT-200/3 δ 13 C, A/g A, g[co2] effect Chlorophylles a/ b Carotenoides LMA E-AAC/M-CCT-175/5 ssrqrzag111 E-AAG/M-CTA-256/5 P-CAG/M-AGC-152/4** Thèse X. Torti trait map LG L PEV N effect norm L BS p G δ 13 C M ± δ 13 C F ± Brendel et al 2008 TGG

13 6 regions controlling δ 13 C explaining 36% to 48% of observed variability Brendel et al TGG -> oligogenic control of WUE in Q. robur?

14 Post-QTL: an ecophysiological approach Decomposing intrinsic water use efficiency Looking at detailed processes A W i g s Photosynthetic Capacity Stomata Rubisco Pigments Nitrogen Morphology Responses

15 Post-QTL: an ecophysiological approach Decomposing intrinsic water use efficiency Looking at detailed processes A W i g s Photosynthetic Capacity Stomata Rubisco Pigments Nitrogen Morphology Responses Such physiological approaches are only possible on few individuals Use of phenotypic extremes of the family low δ 13 C WUE δ 13 C δ 13 C δ 13 C high δ 13 C WUE

16 Decomposition of W i into related traits 13 C W i low high low high Assimilation Rate high W i * high diurnal timecourse low high Stomatal density g s -2 s -1 ) s (mol m -2 s -1 ) :00 7:00 8:00 9:00 10:00 11:00 12:00 Hours UT (UT) low 13:00 14:00 δ 13 C low δ 13 C high high W i 15:00 16:00 17:00 g sat (mol m -2 s -1 ) low high W i Flush: 2 high low Flush: 3 high Stomatal conductance M Roussel et al 2009 J Ex Bot

17 Gene candidate for stomatal density Gene expression of ERECTA in Arabidopsis gene related to Wi and stomatal density Masle et al 2005 low high TE low SD high expression 6 qpcr on adult leaves ERECTA expression high W i low SD Coll. G. Le Provost Block INRA Pierroton High W i oak genotypes have low stomatal density and high ERECTA expression Roussel et al JExBot

18 Differences in daily gas exchange Stomatal conductance Assimilation low W i Genotypes with high W i -> higher overall stomatal conductance -> faster opening in the morning W i M Roussel et al 2009 TGG Daily cycle How to analyse these timecourses in more detail?

19 Modelling daily gas exchange at leaf level environmental data set of parameters Daily gas exchange model Farquhar / Jarvis model parameters are linked to physiological functions A modelled A observed 287B Time gas exchange data gs modelled gs observed 287B Time S. Vialet-Chabrand thesis 2010

20 Modelling daily gas exchange at leaf level genotypes * repetitions environmental data gas exchange data adjustment procedure : genetic algorithm Daily gas exchange model Farquhar / Jarvis model parameters are linked to physiological functions adjusted parameter sets genotypes * repetitions test differences among genotypes for model parameters S. Vialet-Chabrand thesis

21 Differences in Wi due to stomatal responses to light and VPD alphag [mmol CO 2 / µmol e - ] Slope of stomatal opening for a given level of light Mean±0.95 Conf. Interval High ** Wi Low alphag high alpha g low PPFD gvpd_slope [mmol CO 2 / Pa] Slope of stomatal opening for a given level of VPD High * Wi Low GVPD (high) 0.2 GVPD (low) VPD 1400 Time constant for stomatal * closure in response to 800 increasing VPD High Low S. Vialet-Chabrand thesis 2010 Wi Temp VPD down[s]

22 Influence of stomatal responses on Wi whole plant Time integrated Water use efficiency Carbon Isotope Discrimination [ ] C feuille ( ) R 2 = 68.6% 13 C cellulose ( ) R 2 = 73.1% alphag [mmol CO 2 / µmol e - ] A large part of the diversity observed in intrinsic water use efficiency is explained by the diversity of stomatal response to light Cfeuille ( ) R² = 92.7% 13 C cellulose ( ) R² = 95.2% alphag

23 Conclusions and Perspectives Oligogenic control in pedunculate oak family Genetic variability in WUE mainly due to differences in stomatal conductance high WUE pedunculate oak genotypes : lower stomatal density -> lower gmax open stomata less at a given level of light close stomata more rapidly with increasing VPD Testing of candidate functions and genes in specific experimental set-ups and under drought conditions Mapping of candidate functions and genes Investigating genetic control in other genetic backgrounds Is there a natural, local diversity for these traits/genes?

24 Thank you very much for your attention INRA Nancy Ecologie et Ecophysiologie Forestières O. Brendel, M. Roussel, S. Vialet-Chabrand, E. Dreyer, D. Le Thiec, J.L. Dupouey,, S. Ponton,, B. Faivre,... In collaboration with INRA Pierroton BIOGECO G. LeProvost, A. Kremer, C. Plomion, C. Bodénèse, C. Saintagne, S. Gerber, P. Géré