T rees for the future I

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T rees for the future I mproving water-use

http://www.nancy.inra.fr/ guehl@nancy.inra.fr C.

1 T rees for the future I mproving water-use efficiency and adaptation to drought constraints Jean-Marc Guehl UMR INRA-UHP Ecologie et Ecophysiologie Forestières Nancy, France guehl@nancy.inra.fr C. Plomion The Marcus Wallenberg Prize Symposium Stockholm, 27 September 2002

2 Expected change in summer (NE) average soil moisture content from to ( business as usual ) HadCM3 HadCM2 Includes cooling effect of sulphate aerosols Hadley Centre for Climate Prediction and Research. The Met. Office.

3 Paradigm of Changing environment Optimise growth in drought limited conditions (breeding, construction of genotypes). 380 [CO 2 ] ppmv Mauna Loa - Hawaii changes 370 of natural tree populations (phenotypic Keeling & Whorf, Oak Ridge National Laboratory Assess the potential of adaptation to environmental plasticity and genetic adaptation) Year

4 Stomates, the dilemna: maximise CO 2 entry or minimise H 2 O losses? Fagus silvatica Pinus nigra N. Ningre C. Körner Pinus nigra Metabolic signals Water status CO 2 H 2 O VPD Light [CO 2 ] atmos. C. Bodet

Stomatal research: Famous early players Erasmus Darwin

coating leaves with oil and observing their subsequent

pores» Charles Darwin (1809-1882) Francis Darwin

5 Stomatal research: Famous early players Erasmus Darwin ( ) «predicted the existence of stomata; after coating leaves with oil and observing their subsequent death, he concluded that they must breathe through tiny pores» Charles Darwin ( ) Francis Darwin ( ) «showed that stomata on leaves respond to environmental stimuli»

6 Cowan & Farquhar (1977). Optimisation theory (teleonomic). E/ A = λ = cst Tyree & Sperry (1988). Importance of hydraulic constraint on stomata. Farquhar, O Leary & Berry (1982). Timeintegrated assessment of leaf gas exchange regulation traits (stable carbon isotope approach, 13 C/ 12 C ratio in plants can be related to leaf function).

7 Isotope ratio mass spectrometry (IRMS) δ notation, δ = isotopic composition vs. universal standard Standard = Pee Dee Belemnite δ 13 C ( ) = 1000 (R sample - R PDB )/R PDB R ( 13 C / 12 C ) δ 13 C ( ) C3 plants C4 plants PDB Atmospheric CO 2 >0 = carbon isotope discrimination against 13 CO 2 during CO 2 assimilation

In C 3 plants, carbon isotope discrimination during CO 2 assimilation is related to leaf level Water-use efficiency (Farquhar, O'Leary & Berry 1982) D.

8 In C 3 plants, carbon isotope discrimination during CO 2 assimilation is related to leaf level Water-use efficiency (Farquhar, O'Leary & Berry 1982) D. Bonal δ 13 C b = 27 Carbon isotope discrimination ( ) : δ 13 C a δ 13 C = a +(b a) C i C a Leaf level Water-use efficiency (WUE l ) : δ 13 C a, C a C i a = 4.4 Biochemical fractionation Diffusional isotopic fractionation WUE l = A Ca( 1 C i ) gs = C a 1.6 A, CO 2 assimilation rate gs, Stomatal conductance for H 2 0

9 Validation of the carbon isotope discrimination model at plant level. Maritime pine provenances. Plant water-use efficiency, WUE p (10-3 g g-1) Landes P. Vecchio Tamjoute y = x r 2 = Carbon isotope discrimination, ( )

10 Intraspecific Variability of and WUE among populations of trees

r 2 = 0.37 p<0.001 Ruscas, dry Mediterranean site 90 80 70 60 r 2 = 0.47 p<0.

11 Variability of WUE among Pinus pinaster provenances in field trials WUE l derived from Tree ring Cellulose δ 13 C Two contrasted sites WUE l (µmol mol -1 ) r 2 = 0.37 p<0.001 Ruscas, dry Mediterranean site r 2 = 0.47 p< Rainfall area of origin (mm year -1 ) Pierroton, humid Atlantic site

12 Transpiration rate, hydraulic parameters and osmoregulation in Pinus pinaster provenances with contrasting origins (common growth environment) Provenance Transpiration rate, E Tree Hydraulic Conductance, K Leaf specific Hydraulic Cond., K/S mmol m -2 s -1 mmol m -2 s -1 mmol m -2 s -1 MPa -1 Landes (wet) 5.5 a 6.7 a 7.4 a Esterel (wet) 5.2 a 7.6 a 6.3 a Tamjoute (dry) 6.7 b 11.2 b 10.8 b Osmoregulation efficiency (MPa) 0.3 Tamjoute Landes Nguyen-Queyrens & Bouchet-Lannat (in press) Rainfall area of origin (mm year -1 )

13 Variability of stomatal regulation and drought tolerance in Pinus pinaster provenances Conceptual scheme of interpretation Transpiration rate (E) Vapour phase Stomatal conductance or CO 2 assimilation rate Genetic adaptation of stomatal regulation & higher drought tolerance K leaf K stem Ψ leaf Liquid phase Dry provenance K root Ψ root Wet provenance Absorption Ψ soil (adapted from Ewers and Cruiziat, 1990) Wet site Dry site Soil or atmospheric drought intensity Leaf-to-air water vapour pressure difference Water potential gradient E = g ν = K/S (Ψ leaf - Ψ soil ) g, stomatal conductance for water vapour. K/S, leaf specific hydraulic conductance. Vapour phase Liquid phase

14 Intraspecific Variability of and WUE within populations of trees

15 Relationships between and growth. Maritime pine, provenance Tamjoute Biomass (g plant -1 ) ns Well-watered r 2 = 0.66 Moderate drought Severe drought 10 0 r 2 = Carbon isotope discrimination, ( )

Detection of Quantitative Trait Loci (QTLs) for and leaf gas exchange traits Pinus pinaster, F2 progeny of a Landes x Corsican cross Nb of trees 60 40 20 GENETIC MAP 386 DNA markers (AFLP and RAPD)

31*** Quantitative trait loci (QTLs) : (r 2 = 12%) Stomatal conductance (r 2 = 15%) group 3 (141.95 cm) group 10 (111.42 cm) group 6 (169.42 cm) 100 0 18 20 22 24 Carbon isotope discrimination, ( ) 8.

16 Detection of Quantitative Trait Loci (QTLs) for and leaf gas exchange traits Pinus pinaster, F2 progeny of a Landes x Corsican cross Nb of trees GENETIC MAP 386 DNA markers (AFLP and RAPD) 27 protein markers INRA Bordeaux C Plomion Carbon isotope discrimination, ( ) Stomatal conductance, g (mmol m -2 s -1 ) 200 r 2 = 0.31*** Quantitative trait loci (QTLs) : (r 2 = 12%) Stomatal conductance (r 2 = 15%) group 3 ( cm) group 10 ( cm) group 6 ( cm) Carbon isotope discrimination, ( ) ACACCGG5/- ACACCGG11 /- ACGCCGC5/ + ACGCCCA12 /- ACGCCCA13 /- ACCCCGT15 /- ACGCCAT9/ + ACGCCCA20 /- ACACCGG15 / ACACCTA3/- ACCCCTG26/- ACGCCAT21 /+ ACGCCCA22 /+ ACCCCGT16 /+ ACACCGC1/- ACGCCAT24 /+ ACACCGG4/- ACACCTA17/ ACCCCAG4/ + ACGCCCA26 /+ ACGCCAT26 /- ACCCCAG13 /+ ACGCCGT5/- ACCCCTG7/ + Y14_636/- ACCCCTG19 /+ ACCCCTG4/- ACCCCTG23 /+ ACGCCAT10 /- ACCCCAG30 /- ACCCCTG16/- ACACCTA21/ -

Transcriptome analysis of responses to soil

17 Transcriptome analysis of responses to soil drought in poplar (Populus x interamericana) cdna filters Gene level regulations in roots Cell wall Synthesis Water transport at cellular level Collaboration F Martin, A Kohler, V Olié INRA Nancy UMR IaM LIGNOME project

Proteome analysis of responses to soil drought in needles of Pinus pinaster 114 seedlings, F2 progeny of a Landes x Corsican cross 163 proteins studied, 120 responsive to drought, 75 down regulated,

18 Proteome analysis of responses to soil drought in needles of Pinus pinaster 114 seedlings, F2 progeny of a Landes x Corsican cross 163 proteins studied, 120 responsive to drought, 75 down regulated, 45 up regulated. N167 N52 N178 N152 N168 N53 N116 N170 N169 N172 N173 N48: N47 N74 N73 N146 N126 N71 N72 N69 N67 N115 N109 N107 N175 N105 N108 N104 N106 N164 N165 N166 N127 N129 N51 N50 N128 N49 N177 N171 N46 N45 N161 N155 N157 N162 N38 N156 N156 N37 N36 N34 N35 N33 N130 N44 N43 N42 N41 N39 N40 N158 N159 N75 N160 N76 N78 N79 N81 N140 N176 N139 N80 N143 N179 N144 N68 N97: N100 Down regulated N159: MDH N148: RuP5Kinase N167: UDPase; N56, N55, and N54: three rubisco activases N46, N47, N48: glutamine synthetase isoforms Up regulated Proteins involved in lignification (N125: CCoA-OMT; N177: C- OMT) Defence related protein (N75:IFR) Oxygen radical scavenging enzymes (N142: GPx; N175: APx), Heat shock proteins (N166: HSP 70kD; N144 and N98: two HSPs)

19 C onclusions-perspectives Selection for possible. QTL statistical approach. Validation, namely by candidate gene approach (model species). Broaden genetic basis, population level (SNPs). Enlarge to other processes of drought tolerance. Holistic (integrative at plant level) approach promising (combination of eco-physiology, genomics, genetics). Modelling of phenotypic QTL (or allele) effects (Genotype X environment) is crucial. C. Plomion

20 A cknowledgements INRA Nancy Oliver Brendel Claude Brechet Didier Lethiec Darren Sandquist M-Béatrice Triboulot Erwin Dreyer Francis Martin D. Lethiec INRA Bordeaux-Pierroton Christophe Plomion Antoine Kremer Paolo Costa Anne Queyrens-Nguyen Denis Loustau

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

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