The physiological basis for genetic variation in water use efficiency and carbon isotope composition in Arabidopsis thaliana
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Ecologists and physiologists have documented extensive variation in water use efficiency (WUE) in Arabidopsis thaliana, as well as association of WUE with climatic variation. Here, we demonstrate correlations of whole-plant transpiration efficiency and carbon isotope composition (δ13C) among life history classes of A. thaliana. We also use a whole-plant cuvette to examine patterns of co-variation in component traits of WUE and δ13C. We find that stomatal conductance (g s) explains more variation in WUE than does A. Overall, there was a strong genetic correlation between A and g s, consistent with selection acting on the ratio of these traits. At a more detailed level, genetic variation in A was due to underlying variation in both maximal rate of carboxylation (V cmax) and maximum electron transport rate (Jmax). We also found strong effects of leaf anatomy, where lines with lower WUE had higher leaf water content (LWC) and specific leaf area (SLA), suggesting a role for mesophyll conductance (g m) in variation of WUE. We hypothesize that this is due to an effect through g m, and test this hypothesis using the abi4 mutant. We show that mutants of ABI4 have higher SLA, LWC, and g m than wild-type, consistent with variation in leaf anatomy causing variation in g m and δ13C. These functional data also add further support to the central, integrative role of ABI4 in simultaneously altering ABA sensitivity, sugar signaling, and CO2 assimilation. Together our results highlight the need for a more holistic approach in functional studies, both for more accurate annotation of gene function and to understand co-limitations to plant growth and productivity.
KeywordsABI4 Carbon isotope composition Mesophyll conductance Photosynthetic capacity Stomatal conductance
The efficiency with which plants fix CO2 relative to their rate of H2O loss is called water use efficiency (WUE), and when high, WUE can mitigate the tradeoff between CO2 uptake and H2O loss. In C3 plants, low stomatal conductance (g s) minimizes water loss (transpiration, E) and can be a rapid and effective strategy; however, it results in reduced CO2 uptake (A) and growth (Schulze 1986; Geber and Dawson 1997; Condon et al. 2002). Genetically based variation in WUE has been documented in both crops and non-cultivated species (McKay et al. 2003; Hall et al. 2005). Physiologists are interested in intrinsic WUE (A/g s) as a tool for studying how the fundamental trade-off of losing water for gaining CO2 is regulated by stomatal and other physiological adjustments (Buckley and Mott 2002; Comstock 2002). Evolutionary biologists have studied variation in WUE as it is likely an important component of local adaptation (Donovan and Ehleringer 1994; Heschel et al. 2002; Geber and Griffen 2003; Caruso et al. 2005). Likewise, plant breeders have long considered WUE an important target (Passioura 1977).
WUE can be estimated in a variety of ways at various spatio-temporal scales, including with lysimeter studies, gas exchange measurements, or stable carbon isotope composition. Tissue carbon isotope composition is an increasingly popular approach, and its advantages include integration over long periods of gas exchange and development, amenability to high throughput sampling, relatively low cost, and high heritability. Stable carbon isotope composition of leaves (δ13C) (the ratio of the amount of 13C to 12C isotopes in a sample relative to a standard), provides a time-integrated estimate of intrinsic WUE (Farquhar et al. 1989; Dawson et al. 2002). In Arabidopsis thaliana (here after Arabidopsis), common garden experiments have identified substantial variation in δ13C among natural accessions and some of this variation likely represents local adaptation to climate (McKay et al. 2003, 2008; Juenger et al. 2005, 2010; Christman et al. 2008; Monda et al. 2011; Des Marais et al. 2012; Lasky et al. 2012). In addition, QTL have been identified for δ13C (Juenger et al. 2005; Masle et al. 2005; McKay et al. 2008).
In plant breeding, WUE is an important target of selection, although the complexity of the trait, and difficulty of phenotyping has prevented many breeding programs from attempting to select on WUE directly (Araus et al. 2002). Many studies have shown variation in δ13C among cultivars. In crops, one particularly successful example is an Australian wheat breeding program, where selection on δ13C in a greenhouse environment led to new varieties that had increased yield in semiarid rainfed conditions (Rebetzke et al. 2002). Conversely, in conditions where water is not limiting, selection for reduced WUE may lead to greater yields (Passioura 1977; Fischer et al. 1998).
Although it is heritable, appears to be under selection in nature, and may correlate with yield in C3 crops (Condon et al. 1987), the mechanistic basis of genetic variation in δ13C is still unclear. Variation in δ13C can be due to variation in photosynthetic biochemistry, conductance of CO2 to the leaf interior and chloroplast, or a combination of these (Seibt et al. 2008). Thus, similar leaf δ13C and similar WUE can evolve via mutations that cause low A with low conductance or mutations that cause high A with proportionally higher conductance (Farquhar et al. 1989). This is further complicated because conductance from ambient air to the interior of the leaf is influenced both by g s and additional variability of conductance into leaf mesophyll cells and chloroplasts (g m), which can change over the long-term with leaf morphology (von Caemmerer and Evans 1991; Evans et al. 1994, 2009; Tosens et al. 2012) and over the short-term through changes in protein-mediated chloroplast membrane permeability (Flexas et al. 2006; Uehlein et al. 2008; Heckwolf et al. 2011). When examining the combined effects of g s and g m, it is important to recognize that they operate in series rather than in parallel and that the regulation of g m is poorly understood. Within a genotype, g s and g m usually respond in a correlated way to environmental stimuli (Flexas et al. 2007, 2008; Warren 2008; Barbour et al. 2010) although, opposite responses have also been observed (Galle et al. 2012). Patterns of genetic covariation of g s and g m have not been investigated. However, it is known that variation in g m contributes to leaf carbon isotope discrimination, further increasing the importance of considering g s and g m in interpretations of δ13C (Warren and Adams 2006; Barbour et al. 2010).
Understanding the physiological basis of variation in δ13C and intrinsic WUE is important for improving plant productivity and understanding the evolution of wild species. Here, we report a series of experiments designed to investigate a mechanistic understanding of the physiological basis of variation in intrinsic WUE in Arabidopsis. At the coarse level, we can ask if variation in intrinsic WUE is primarily due to variation in A or g s. For example, threefold variation in g s and twofold variation in leaf N concentration among natural accessions of Arabidopsis suggest substantial variation in g s and A may separately or in concert be responsible for the observed variation in δ13C (Christman et al. 2008; Des Marais et al. 2012). Des Marais et al. (2012) found large differences in physiology between life history classes in Arabidopsis. Although, the Des Marais study focused on variation in gene expression, they also reported constitutive variation in leaf structural traits between life history classes. Winter annual types had higher intrinsic WUE. This is consistent with coordinated selection on WUE, A, and g s and life history observed in other species (Geber and Dawson 1997). Higher WUE was associated with lower leaf water content (LWC) and specific leaf area (SLA) (Des Marais et al. 2012). Taken together, these results suggest that increased leaf density is associated with higher photosynthetic capacity (Terashima et al. 2011), but may come at the cost of lower stomatal and mesophyll conductance to CO2 (Parkhurst and Mott 1990; Evans et al. 1994; Syvertsen et al. 1995; Kogami et al. 2001).
Studies in Arabidopsis have identified extensive natural variation in plant–water relations and gas exchange physiology (Juenger et al. 2005, 2010; Masle et al. 2005; Bouchabke et al. 2008; Christman et al. 2008; McKay et al. 2008; Monda et al. 2011; Des Marais et al. 2012; Pons 2012). The present study was undertaken to examine natural variation in leaf physiological traits that are the likely cause of the observed variation in δ13C and associated WUE parameters in natural accessions of Arabidopsis, and to determine if these traits vary independently or co-vary in a coordinated and predictable manner. First, we tested if the expected relationship between transpiration efficiency (shoot dry mass/transpiration; TE) and leaf δ13C was present in 96 natural accessions of Arabidopsis. In a smaller set of 18 natural accessions spanning the range of variation in δ13C, we measured rosette A, g s, and intercellular CO2 concentration (C i) and examined the relationship of C i and δ13C. To further characterize natural variation in A, we examined maximal carboxylation rate (V cmax) and photosynthetic electron transport rate (Jmax) in three accessions using photosynthetic carbon dioxide response curves (Sharkey et al. 2007). Additionally, we used gas exchange measurements coupled with online isotopic measurements to determine instantaneous carbon isotope discrimination using tunable diode laser spectroscopy (TDL) (Flexas et al. 2006; Barbour et al. 2007; Heckwolf et al. 2011) to estimate g m in stomatal regulation mutants to investigate the relationship of these mechanistically related traits (Warren et al. 2003; Yamori et al. 2006).
Materials and methods
δ13C and transpiration efficiency (Experiment 1)
Our first goal was to use a relatively high throughput approach to look for variation and co-variation across the species range. 96 natural accessions were selected from the native range of Arabidopsis to evaluate plant biomass production and water use (Nordborg et al. 2005). Individual plants were grown in 250-mL plastic cups, each filled with a standard mass of 1:1 fritted clay and Promix BT potting soil mix. We measured field capacity of the soil mix following a 24-h gravitational drain of saturated soil. Each cup was covered with parafilm and sealed with a plastic lid that had a 6-mm diameter hole. Two replicates of each of 96 ecotypes were planted and cold stratified in the dark for 7 days at 4 °C. Plants were grown in two independent growth chambers at 200 μmol m−2 s−1 PPFD in a randomized block design. Photoperiod was 12 h light/12 h dark and the temperature cycled 23/18 °C (light/dark). Every 2 days, each container was weighed and additional water was added with a syringe to bring the soil in each container to 90 % field capacity. Total transpiration (E total) was summed for the 35 days growing period for each experimental plant. Plants were harvested, and aboveground material was oven dried and weighed (DW). We assessed evaporative loss from the containers using “blanks” lacking an Arabidopsis plant. Total evaporation from the blank containers was <4 % of the average E total from pots in the experiment. Transpiration efficiency (TE) of each plant was calculated as DW/E total. Dried leaves were ground to a fine powder and δ13C was determined at the UC Davis Stable Isotope Facility (http://stableisotopefacility.ucdavis.edu/). When grown outside in free air, the use of carbon isotope discrimination, Δ, is preferred (Farquhar et al. 1982), but when growth chamber and greenhouse studies are included the value of air δ13C is uncertain and variable, thus requiring the use of leaf δ13C instead of Δ. Differences in δ13C within the same experiment indicate differences in intercellular CO2 concentration, but δ13C must be viewed with caution when comparing different experimental conditions.
Whole-shoot gas exchange (Experiment 2)
To follow up on the patterns from the 96 accessions, 18 natural accessions of Arabidopsis were used in whole-shoot gas exchange experiments to evaluate the physiological basis of variation in δ13C. Eleven of the accessions were spring annuals, and seven were winter annuals. Four replicates of each genotype were grown in a growth chamber in a randomized block design. Each plant was grown in a pot constructed from a 50-mL centrifuge tube with the bottom cut off and “planted” in a 164-mL Conetainer™ pots (Stuewe and Sons, Corvallis, OR) filled with a 1:1 mixture of potting mix (Sunshine mix, Sun Gro Horticulture, Bellevue, WA) and fritted clay. After planting, pots were cold stratified at 4 °C for 7 days, then transferred to a growth chamber. Photoperiod was 12 h with 350 μmol m−2 s−1 PPFD and temperature was cycled 23/20 °C (light/dark).
A:C i responses were measured for three accessions (Tsu-1, SQ-8, and Kas-1) which differed in A and δ13C. Cuvette conditions were the same as above, but light was increased to 1,000 μmol m−2 s−1 PPFD. Photosynthetic carbon dioxide response curves were measured on four rosettes of each accession. The number of replications of A:C i measurements were limited by chamber environment equilibration time at each CO2 set point. The least squares iterative curve-fitting procedure (Sharkey et al. 2007) model was used to fit Farquhar et al.’s (1980) biochemical model of photosynthesis and obtain maximal carboxylation rate (V cmax) and maximal photosynthetic electron transport rate (Jmax).
Leaf water content (Experiment 3)
39 natural accessions from the native range of Arabidopsis previously used in Mckay et al. (2003) were measured for LWC and leaf δ13C. Four replicates of each ecotype were grown in a greenhouse at UC Davis in a randomized block design. Seeds were sown in 250-mL pots in peat-based potting mix with slow-release fertilizer and vernalized at 4 °C for 5 days. Day length was extended to 16 h using supplemental lighting at 350 μmol m−2 s−1 PPFD. Greenhouse mean relative humidity and air temperature were 44 % and 23 °C, respectively. Shoots were harvested at the initiation of flowering and shoot fresh weight (FW) was determined, leaf area was determined from scans of dissected rosettes using Scion Image (Scion Corporation, Frederick, MD, USA), and shoots were dried and weighed (DW). Entire dried shoots were ground and processed for carbon isotope analysis at the UC Davis Stable Isotope Facility (http://stableisotopefacility.ucdavis.edu/). LWC (%) was calculated as 100 × (FW − DW)/DW.
Mesophyll conductance (Experiment 4)
Arabidopsis seeds of ecotype Columbia and the abi4 mutant provided by the Arabidopsis Biological Resource Center (Columbus, OH, USA) were used for leaf mesophyll conductance to CO2 (g m) experiments. Seven replicates of each genotype were grown in a growth chamber in a randomized block design. Photoperiod was 12 h with 350 μmol m−2 s−1 PPFD and temperature was cycled 23/20 °C (light/dark). A LI-6400 (Li-Cor Inc., Lincoln, NE, USA) with whole-shoot Arabidopsis cuvette (Fig. 1) was coupled with online isotopic measurements of CO2 entering and leaving the shoot chamber to determine instantaneous carbon isotope discrimination and g m using TDL (Flexas et al. 2006; Barbour et al. 2007; Heckwolf et al. 2011). Calculations for g m were based on whole-shoot gas exchange measurements at 350, 700, and 175 (μmol m−2 s−1) PPFD using the slope-based approach given in Evans et al. (1986). Shoots were harvested after gas exchange, leaf area was determined from rosette photographs using Scion Image (Scion Corporation, Frederick, MD, USA), and shoots were dried and weighed (DW). LWC (%) was calculated as above and SLA was calculated as rosette area/DW.
We analyzed phenotypic data for physiological traits using standard fixed effect ANOVAs with the Proc GLM in SAS (SAS Institute 1999). We estimated correlations among physiological traits as the standard Pearson product-moment correlation between genotype means.
In the case of the TE experiment, we analyzed phenotypic data for physiological traits using a linear mixed model analysis with the Proc Mixed procedure in SAS (SAS Institute 1999). We fit a model including accessions as a random effect and chamber, experiment, and their interaction as fixed effects. The variance component for the random effect was estimated using restricted maximum likelihood (REML) and assessments of significance were based on likelihood ratio tests (Little et al. 1996). We obtained empirical best linear unbiased predictors (BLUPs) associated with the random effects and consider these breeding values for each accessions. BLUPs are robust estimates of the impact of a particular accession on the measured trait while controlling for the fixed effects (chamber and experimental run). For TE, we fit a model that included both chamber and experimental run as a fixed effect. For δ13C, we fit a simpler model including accession as a random variable and experimental run as a fixed effect. In this case, factors associated with chamber could not be included because replicates within each experimental run were pooled for mass spectroscopy analysis. All subsequent analyses involving TE and δ13C rely on BLUP estimates. The TE and δ13C values were normally distributed and residuals from analyses did not exhibit heteroscedasticity.
We estimated broad-sense heritability by computing the ratio V G/V P, where V G equals the among-accession variance component and V P equals the total phenotypic variance for the study phenotypes. We estimated genetic correlations (r G) among TE and δ13C as the standard Pearson product-moment correlation between genotype means or BLUPs.
Results and discussion
Variation in TE and δ13C
Summary of experiments
96 natural accessions representing a range of latitudes, elevations and climates.
200 μmol m−2 s−1 PPFD, 12 h photoperiod
Ag-0, Bil-5, Bur-0, C24
Got-22, HR5, Kas-1,
Knox-18, Ler-1, NFA-10,
Omo2-3, Sq-8, Tamm-2,
Ts-1, Tsu-1, Ws-2
Whole shoot gas exchange (A, g s, C i), δ13C, V cmax, Jmax
350 μmol m−2 s−1 PPFD, 12 h photoperiod
Aa-0, Ag-0, Cvi-0, Kas-1, Mh-0, Ms-0, Di-g, Est, Ws-3, Kondara, Da(1)-12, Hodja-Obi-garm, Je54, Petergof, Rubezhnoe-1, Sn(5)-1, Sorbo, An-1, Bch-3, Can-0, Db-1, Edi-0, Ei-4, En-1, Et-0, Jl-3, Ka-0, Mrk-0, Pi-0, Rd-0, Rsch-4, Sei-0, Ta-0, Wl-0, Wei-1, Tsu-1, Rld-2, Oy-1, Shahdara
350 μmol m−2 s−1 PPFD, 16 h photoperiod
abi4-1 (At2g40220), Columbia
Whole shoot gas exchange with online carbon isotope discrimination (A, g s, C i, g m, SLA, LWC)
350 μmol m−2 s−1 PPFD, 12 h photoperiod
Variation in components of WUE
Despite the lack of heritability of A and the weak correlation of A with δ13C, we did find a significant positive correlation between g s and A among accessions (r 2 = 0.78, P = 0.00001). This is consistent with the optimization of stomatal regulation to maximize carbon gain while minimizing the water loss (Katul et al. 2010). Accessions that have high conductance should be under selection for increased biochemical capacity (Bloom et al. 1985). Although, it is not formally stated, such optimality approaches interpret consistent patterns of correlation in physiological traits (Reich et al. 1997) as evidence of selection optimizing their ratios or covariances (Donovan et al. 2011). Under such a scenario, selection would favor mutations that lead to a co-limitation of g s and RuBP utilization and regeneration.
The major biochemical limitations to photosynthesis, V cmax and Jmax, appeared optimized to accessions’ C i as indicated by δ13C. V cmax and Jmax were lower in low g s, high WUE accessions operating at lower C i. The higher ratio of V cmax to Jmax in Kas-1 compared to Sq-8 suggests a lack of limitation by Jmax under the low g s typical of Kas-1. Simultaneous changes in V cmax and Jmax are consistent with a limitation of photosynthesis by RuBP utilization and regeneration (Farquhar and Sharkey 1982). Likewise, proportional changes in components of photosynthetic apparatus and g s suggest acclimation of these processes are closely coupled (Cowan 1986).
Variation in structure
The ABI4 transcription factor causes changes in leaf anatomy and mesophyll conductance
To further test for a causal effect of leaf anatomy on gas exchange (experiment 4 in Table 1), we used abi4, a mutant of locus AT2G40220, which is an AP2/ERF transcription factor (TF). ABI4 is closely related to the DREB2 TFs and the mutant was initially described as ABA insensitive based on a germination screen (Finkelstein 1994). Subsequent work has shown that the transcript is expressed in seedlings (Soderman et al. 2000) and fully developed rosette leaves (Finkelstein et al. 1998). In addition to its key role in ABA signaling, further characterization of this transcription factor has proposed a large and diverse set of functions including sugar signaling and response (Husijer et al. 2000; Bossi et al. 2009), and root development (Signora et al. 2001; Shkolnik-Inbar and Bar-Zvi 2011). There are hundreds of loci whose expression is altered in the ABI4 mutant (Kerchev et al. 2011). Given that it is a transcription factor, this is not surprising, but does illustrate the challenge of functional annotation of such pleiotropic loci.
Although, a few of the AP2/ERF transcription factors in Arabidopsis have been the subject of detailed study, there are 122 of these loci in Arabidopsis (Nakano et al. 2006) and much remains unknown about their function. Recent studies have revealed increasingly complex roles for members of this transcription factor family. For example, a recent study identified eight AP2/ERFs induced by photorespiration (Foyer et al. 2012). This, combined with the known roles of ABI4 in sugar signaling to photosynthesis including repression of RBCS (Van Oosten et al. 1997; Teng et al. 2008), and our results showing effects on leaf density and g m, are expanding this picture.
Detailed measurements on a diverse set of accessions detail the traits underlying natural variation in intrinsic WUE and carbon isotope composition. Previous studies have shown that spring accessions have lower intrinsic WUE than accessions with winter life histories. Proportional changes in A, g s, V cmax, and Jmax suggest acclimation of these processes are closely coupled. We also show strong covariation between LWC and δ13C, where spring annuals tend to have higher LWC and lower intrinsic WUE. We hypothesize that this is due to an effect through g m, and test this hypothesis using the abi4 mutant. The abi4 mutant shows increased SLA and reduced g m compared to the wildtype, consistent with the pattern of covariance found in the natural accessions.
Previous separate studies in Arabidopsis have addressed variation in δ13C, plant–water relations, leaf anatomy, and photosynthetic capacity and limitations, including g m. Here, we use a whole canopy approach to examine variation and covariation in all of these components. As predicted by optimality, these traits are not independent, but instead covary as would be expected if selection and photosynthetic acclimation favors states of colimitation. In addition, we show that perturbation of a single transcription factor leads to this trait covariance. This emphasizes the need for whole plant approaches and high dimensional phenotyping to accurately annotate the gene function.
We thank P Rispin for help in completing the TE experiment. This research is supported by NSF grants DEB-1022196 and DEB-0618302 to JKM, DEB-0618347 to TEJ, IOS-0719118 to DTH, DEB-0618294 to JHR, USDA NIFA 2007-35100-18379 to TEJ, and NIH-NCRR P20RR18754. Support from the California and Colorado Agricultural Experiment Stations is also acknowledged.
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