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
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?
1984) Carbon Isotope Discrimination between atmospheric CO 2 and Carbon of Plant Material... 13 C MO 13 C MO 3 6.0 W i (µmol CO 2 mol -1 H 2 O) 90 80 70 60 50 R²=0.71; p<0.05 17 18 19 20 13 C Ft ( ) 45% TE (mg DM g -1 H 2 O) 5.5 5.0 4.5 R²=0.71; p<0.05 4.0 13 14 15 16 17 18 13 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.
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 )
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
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. 2002 *** W:+7% individus témoins CONTROL Wi Q robur lower Higher tolerance to root hypoxia Difference in intrinsic water use efficiency between the two species
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?
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
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?
Genetic determinism : QTL approach for pedunculate oak Parents Full-sib family X Genotype Phenotype Genetic map Coll : INRA Pierroton A. Kremer QTL Linkage group
Within species variation : one pedunculate oak F1 family 90 80 70 4 ~ 50% Wi No of obs 60 50 40 30 20 10 0 2000 2001 2002-28 -27-26 -25-24 2 plantations δ 13 C [ ] 3 years of measurements Brendel et al 2008 TGG large variability of W i within this family
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 00+ 12.5 24.4 35.9 57.8 75.5 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 00-01-02- %N ME 01-02- LMA 01+ LMA 02+ LMA ME 01+02+ 9.7 14.0 20.7 42.0 51.6 57.9 65.5 87.1 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 00 01 02 00 01 02 00 01 02 δ 13 C M 11 63.9 20.7 30.8 24.3 158 106 190-0.26-0.35-0.29 63.9±1.9 0.0004 δ 13 C F 11 15.9 3.2 2.6 5.4 156 104 185 0.10 0.10 0.14 19.4±13.5 0.024 Brendel et al 2008 TGG
6 regions controlling δ 13 C...... explaining 36% to 48% of observed variability Brendel et al. 2008 TGG -> oligogenic control of WUE in Q. robur?
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
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 2002 2001 2000 δ 13 C δ 13 C δ 13 C high δ 13 C WUE
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 ) 0.45 0.40 0.35 0.30 0.25 0.20 0.15 0.10 0.05 0.00 6:00 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 ) 0.45 0.40 0.35 0.30 0.25 0.20 0.15 0.10 0.05 low high W i Flush: 2 high low Flush: 3 high Stomatal conductance M Roussel et al 2009 J Ex Bot
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 5 4 3 2 1 0 high W i low SD 1 2 3 4 Coll. G. Le Provost Block INRA Pierroton High W i oak genotypes have low stomatal density and high ERECTA expression Roussel et al. 2009 JExBot
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?
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 24 20 16 12 8 4 A modelled A observed 287B 0 0 10000 20000 30000 40000 Time gas exchange data 200 160 120 80 40 0 gs modelled gs observed 287B 0 10000 20000 30000 40000 Time S. Vialet-Chabrand thesis 2010
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
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 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 Mean±0.95 Conf. Interval High ** Wi Low 1.0 0.8 0.6 0.4 0.2 0.0 alphag high alpha g low 0 400 800 1200 PPFD gvpd_slope [mmol CO 2 / Pa] Slope of stomatal opening for a given level of VPD 0.014 0.012 0.010 0.008 0.006 0.004 0.002 0.000 High * Wi Low 1.0 0.8 0.6 0.4 GVPD (high) 0.2 GVPD (low) 0.0 0 1000 2000 3000 VPD 1400 Time constant for stomatal 1200 1000 * closure in response to 800 increasing VPD 600 400 200 0 High Low S. Vialet-Chabrand thesis 2010 Wi Temp VPD down[s]
Influence of stomatal responses on Wi whole plant Time integrated Water use efficiency Carbon Isotope Discrimination [ ] 21 20 19 18 17 16 15 14 13 12 13 C feuille ( ) R 2 = 68.6% 13 C cellulose ( ) R 2 = 73.1% 11 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 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 21 20 19 18 17 16 15 14 13 13 Cfeuille ( ) R² = 92.7% 13 C cellulose ( ) R² = 95.2% 12 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 alphag
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?
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