Skip to main content
NCBI home page
Plant Physiology logoLink to Plant Physiology
. 2016 Jun 24;172(2):707–717. doi: 10.1104/pp.16.00750

Surveying Rubisco Diversity and Temperature Response to Improve Crop Photosynthetic Efficiency1,[OPEN]

Douglas J Orr 1,2,3,4,*, André Alcântara 1,2,3,4,2, Maxim V Kapralov 1,2,3,4, P John Andralojc 1,2,3,4, Elizabete Carmo-Silva 1,2,3,4, Martin AJ Parry 1,2,3,4
PMCID: PMC5047088  PMID: 27342312

Species diversity in Rubisco catalysis shows consistencies in temperature response, which can be used to improve crop photosynthetic efficiency.

Abstract

The threat to global food security of stagnating yields and population growth makes increasing crop productivity a critical goal over the coming decades. One key target for improving crop productivity and yields is increasing the efficiency of photosynthesis. Central to photosynthesis is Rubisco, which is a critical but often rate-limiting component. Here, we present full Rubisco catalytic properties measured at three temperatures for 75 plants species representing both crops and undomesticated plants from diverse climates. Some newly characterized Rubiscos were naturally “better” compared to crop enzymes and have the potential to improve crop photosynthetic efficiency. The temperature response of the various catalytic parameters was largely consistent across the diverse range of species, though absolute values showed significant variation in Rubisco catalysis, even between closely related species. An analysis of residue differences among the species characterized identified a number of candidate amino acid substitutions that will aid in advancing engineering of improved Rubisco in crop systems. This study provides new insights on the range of Rubisco catalysis and temperature response present in nature, and provides new information to include in models from leaf to canopy and ecosystem scale.

In a changing climate and under pressure from a population set to hit nine billion by 2050, global food security will require massive changes to the way food is produced, distributed, and consumed (Ort et al., 2015). To match rising demand, agricultural production must increase by 50 to 70% in the next 35 years, and yet the gains in crop yields initiated by the green revolution are slowing, and in some cases, stagnating (Long and Ort, 2010; Ray et al., 2012). Among a number of areas being pursued to increase crop productivity and food production, improving photosynthetic efficiency is a clear target, offering great promise (Parry et al., 2007; von Caemmerer et al., 2012; Price et al., 2013; Ort et al., 2015). As the gatekeeper of carbon entry into the biosphere and often acting as the rate-limiting step of photosynthesis, Rubisco, the most abundant enzyme on the planet (Ellis, 1979), is an obvious and important target for improving crop photosynthetic efficiency.

Rubisco is considered to exhibit comparatively poor catalysis, in terms of catalytic rate, specificity, and CO2 affinity (Tcherkez et al., 2006; Andersson, 2008), leading to the suggestion that even small increases in catalytic efficiency may result in substantial improvements to carbon assimilation across a growing season (Zhu et al., 2004; Parry et al., 2013; Galmés et al., 2014a; Carmo-Silva et al., 2015). If combined with complimentary changes such as optimizing other components of the Calvin Benson or photorespiratory cycles (Raines, 2011; Peterhansel et al., 2013; Simkin et al., 2015), optimized canopy architecture (Drewry et al., 2014), or introducing elements of a carbon concentrating mechanism (Furbank et al., 2009; Lin et al., 2014a; Hanson et al., 2016; Long et al., 2016), Rubisco improvement presents an opportunity to dramatically increase the photosynthetic efficiency of crop plants (McGrath and Long, 2014; Long et al., 2015; Betti et al., 2016). A combination of the available strategies is essential for devising tailored solutions to meet the varied requirements of different crops and the diverse conditions under which they are typically grown around the world.

Efforts to engineer an improved Rubisco have not yet produced a “super Rubisco” (Parry et al., 2007; Ort et al., 2015). However, advances in engineering precise changes in model systems continue to provide important developments that are increasing our understanding of Rubisco catalysis (Spreitzer et al., 2005; Whitney et al., 2011a, 2011b; Morita et al., 2014; Wilson et al., 2016), regulation (Andralojc et al., 2012; Carmo-Silva and Salvucci, 2013; Bracher et al., 2015), and biogenesis (Saschenbrecker et al., 2007; Whitney and Sharwood, 2008; Lin et al., 2014b; Hauser et al., 2015; Whitney et al., 2015).

A complementary approach is to understand and exploit Rubisco natural diversity. Previous characterization of Rubisco from a limited number of species has not only demonstrated significant differences in the underlying catalytic parameters, but also suggests that further undiscovered diversity exists in nature and that the properties of some of these enzymes could be beneficial if present in crop plants (Carmo-Silva et al., 2015). Recent studies clearly illustrate the variation possible among even closely related species (Galmés et al., 2005, 2014b, 2014c; Kubien et al., 2008; Andralojc et al., 2014; Prins et al., 2016).

Until recently, there have been relatively few attempts to characterize the consistency, or lack thereof, of temperature effects on in vitro Rubisco catalysis (Sharwood and Whitney, 2014), and often studies only consider a subset of Rubisco catalytic properties. This type of characterization is particularly important for future engineering efforts, enabling specific temperature effects to be factored into any attempts to modify crops for a future climate. In addition, the ability to coanalyze catalytic properties and DNA or amino acid sequence provides the opportunity to correlate sequence and biochemistry to inform engineering studies (Christin et al., 2008; Kapralov et al., 2011; Rosnow et al., 2015). While the amount of gene sequence information available grows rapidly with improving technology, knowledge of the corresponding biochemical variation resulting has yet to be determined (Cousins et al., 2010; Carmo-Silva et al., 2015; Sharwood and Whitney, 2014; Nunes-Nesi et al., 2016).

This study aimed to characterize the catalytic properties of Rubisco from diverse species, comprising a broad range of monocots and dicots from diverse environments. The temperature dependence of Rubisco catalysis was evaluated to tailor Rubisco engineering for crop improvement in specific environments. Catalytic diversity was analyzed alongside the sequence of the Rubisco large subunit gene, rbcL, to identify potential catalytic switches for improving photosynthesis and productivity. In vitro results were compared to the average temperature of the warmest quarter in the regions where each species grows to investigate the role of temperature in modulating Rubisco catalysis.

RESULTS

Variability in Rubisco Catalysis across Plant Species

Diversity in Rubisco catalytic properties determined at 20, 25, and 30°C was measured across 75 species belonging to 10 families, expanding the range of previously characterized Rubiscos (Fig. 1; full data set available in Supplemental Table S1). This is the largest data set of complete Rubisco catalytic properties produced to date. ANOVA revealed significant differences in carboxylation efficiency (kcatc/Kcair; Supplemental Fig. S1) and specificity (SC/O; Supplemental Fig. S2).

Figure 1.

Figure 1.

Open in a new tab

Range of Rubisco carboxylation rate (kcatc; A), Michaelis-Menten constant for CO2 (Kc; B), and specificity factor (SC/O; C) at 20, 25, and 30°C. The range of values previously reported for C3 plants in the literature at 25°C (Lit 25°C) is shown for reference. Literature data are from a survey of publications available as of January 2016. Box plot lines represent the median value and the 10, 25, 75, and 90th percentiles.

Carboxylation rates (kcatc) at 25°C ranged from 1.9 s−1 in Euphorbia helioscopia (Euphorbiaceae) to 7.1 s−1 in the C4-photosynthesis type annual grass Eragrostis tef (Poaceae). Affinity for CO2 was highest in rice (Oryza sativa ssp. indica; Kc = 7 µm at 25°C) and lowest in C4 grasses included in this study (Kc ∼34–37 µm, E. tef and Panicum spp.). Across the diverse group of species analyzed, the CO2/O2 specificity (SC/O) showed a large range of values, from a 25°C high of 111 in the grass Poa palustris (Poaceae) to a low of 82 in the C4 dicot Chrysanthellum indicum (Asteraceae). C3 plants surveyed ranged in SC/O from 111 to 91. Catalytic values generally agreed with previously reported ranges (Ishikawa et al., 2011; Galmés et al., 2014b; Occhialini et al., 2016).

Modeling of leaf photosynthesis shows that the direct replacement of native Rubisco in a crop, such as soybean (Glycine max), with two high-performing monocot Rubiscos would support significant improvements of leaf-level photosynthetic rates at current atmospheric CO2 levels and high irradiance (Fig. 2). Photosynthesis improvement was particularly evident at low internal CO2 concentrations when leaf photosynthesis is typically limited by Rubisco activity.

Figure 2.

Figure 2.

Open in a new tab

Potential photosynthetic improvement in soybean that would result from replacement of native Rubisco with Rubisco from P. palustris (yellow) or Puccinellia maritima (brown) at 25°C. Rates of net CO2 assimilation (A) were derived from the model of Farquhar et al. (1980) as detailed by von Caemmerer (2000) and using in vitro measurements of Rubisco catalysis. Modeling assumed: Rubisco content = 30 µmol m−2; Rd = 0.015 × Vc,max; J = 1.75 × Vc,max; and O2 = 21%.

Linking rbcL Sequence Variation with Rubisco Biochemical Diversity

Accompanying the biochemical analysis of a large range of species with an analysis of variation in the highly conserved chloroplast rbcL gene, which encodes the catalytic subunit of Rubisco, provides the opportunity to identify amino acid replacements potentially responsible for changes in Rubisco catalysis. Positive selection analysis identified residue positions that were correlated with particular catalytic properties, namely, high carboxylation efficiency (kcatc/Kcair), high kcatc, low Kcair, and high SC/O. Five Rubisco large subunit residues were associated with changes in particular catalytic characteristics across the 75 species data set (Fig. 3), with at least one residue linked to each parameter. The full list of residue positions under positive selection, their structural location, and possible molecular interactions is provided in Supplemental Table S2.

Figure 3.

Figure 3.

Open in a new tab

Tree diagram illustrating Rubisco large subunit amino acid positions under positive selection linked to superior Rubisco properties in monocot species (A) and dicot species (B). Eff, Carboxylation efficiency (kcatc/Kcair). Color highlighting indicates amino acid substitutions at residues that are under positive selection along phylogenetic tree branches leading to species with particular catalytic properties (e.g. high kcatc). Dashed green lines indicate species groupings for analysis of temperature response. Group 1, monocots, Poaceae/Musaceae (n = 39); group 2, Amaranthaceae (n = 5); group 3, Asteraceae/Solanaceae (n = 5); group 4, Euphorbiaceae/Curcubitaceae (n = 8); group 5, Fabaceae (n = 18).

Importantly, in a large analysis of sequence diversity alongside catalytic properties, phylogenetically distant species may have acquired similar changes in Rubisco catalysis via different amino acid substitutions, which makes finding common catalytic switches difficult. Thus, a subsequent separate analysis of the monocot and dicot species subsets (n = 39 and 36, respectively) was conducted. Different sets of residues associated with catalytic changes were highlighted for these two groups with little overlap (Fig. 3, A and B). Among the six residues found within the monocots, three positions were linked to high carboxylation efficiency, one to high SC/O and two to low Kcair. In the dicot subset analysis, two residue positions were associated with high catalytic rates (kcatc), while a further residue position was linked to high carboxylation efficiency (kcatc/Kcair).

Correlations between Catalytic Parameters at a Range of Temperatures

Using phylogenetically independent contrast analyses, correlation coefficients between catalytic parameters for each measurement temperature were calculated (Fig. 4). The classical trade-off between increasing kcatc and decreasing CO2 affinity (increased Kc or Kcair) was evident (Tcherkez et al., 2006). However, the significance and strength of this correlation varied at the different measurement temperatures examined. At 20 and 25°C, the strength and significance was high (P ≤ 0.01), while at 30°C, there was no significant correlation between increasing kcatc and CO2 affinity (Kc or Kcair). SC/O correlated positively with kcatc, Kc, and Kcair, most significantly at 20 and 25°C, and negatively with carboxylation efficiency at 25°C. The relationship between kcatc and carboxylation efficiency was notably inconsistent across the three measurement temperatures.

Figure 4.

Figure 4.

Open in a new tab

Correlation coefficients of phylogenetically independent contrasts calculated for Rubisco catalytic parameters of 75 species, using data from measurements at 20, 25, or 30°C. Significant correlations are marked: ***P < 0.001, **P < 0.01, and *P < 0.05.

To explore how climate may correlate with Rubisco catalysis in diverse species, the temperature of the warmest quarter of the year (TWQ) where each species grows served as a proxy for conditions during the main part of the growing season. TWQ was negatively correlated with SC/O measured at 20 and 30°C (at 25°C the correlation was not significant; Fig. 4), indicating that Rubisco from species growing in higher temperature climates had lower SC/O. Oxygenation parameters (Ko and Vo) consistently showed a significant positive correlation with TWQ. Carboxylation efficiency was negatively correlated with TWQ at 20 and 25°C, but the correlation was not significant for measurements at 30°C.

Temperature Response of Rubisco Catalysis

To examine the consistency of catalytic changes in response to temperature, the 75 species examined were divided into five natural groups based on their phylogenetic relationships (indicated in Fig. 3). A summary of the catalytic properties for each group at each temperature is shown in Table I, and nonlinear regression analysis was used to assess the groups and species variation in temperature response (Supplemental Fig. S3). There was variation in the temperature response of Rubisco catalysis for the diverse species and groups analyzed, but the trend of the response was consistent. The response of each catalytic property to temperature in soybean is provided as a representative example (Fig. 5). Group 3 consisted of a range of dicots, including Nicotiana tabacum and Artemisia spp., and could be fitted with a single model that explained temperature response of kcatc for the whole group (i.e. there was no significant difference in temperature response of kcatc between the species within group 3). For the other groups and individual species, the temperature response of kcatc was similarly explained by a linear model and, while individual species displayed a consistent slope for the model generated, significant variation in the intercept prevented the generation of a single model to explain the entire group. These results show that the relative increase in kcatc with temperature was consistent, despite the significant variation in absolute values within groups.

Table I. Key Rubisco catalytic parameters for five phylogenetic groups.

kcatc, Maximum carboxylation rate; Kcair, Michaelis-Menten constant for CO2 at atmospheric levels of O2 (21%); SC/O, specificity for CO2 versus O2. For details of the species within each group, see Figure 3. Values are means ± se of the mean (n as indicated).

Group n kcatc (s−1)
 Kcair (µm)
 SC/O
20°C 25°C 30°C 20°C 25°C 30°C 20°C 25°C 30°C
1 34 2.3 ± 0.1 3.7 ± 0.2 5.7 ± 0.3 19.4 ± 0.9 28.6 ± 1.2 34.4 ± 1.7 114.9 ± 0.8 104.7 ± 0.6 92.6 ± 0.5
2 5 2.3 ± 0.2 3.9 ± 0.3 5.6 ± 0.1 14.8 ± 1.7 31.0 ± 2.9 40.1 ± 3.6 110.2 ± 1.9 99.4 ± 2.2 86.8 ± 0.9
3 4 2.3 ± 0.1 4.0 ± 0.3 7.2 ± 0.3 18.8 ± 3.9 39.5 ± 4.5 52.6 ± 8.3 110.0 ± 4.4 101.3 ± 3.1 88.5 ± 1.9
4 8 1.9 ± 0.1 3.1 ± 0.3 4.8 ± 0.3 16.4 ± 2.2 27.4 ± 1.9 30.3 ± 1.8 107.2 ± 1.1 99.8 ± 1.6 92.1 ± 1.3
5 18 1.9 ± 0.1 3.2 ± 0.2 5.2 ± 0.2 15.8 ± 1.0 25.9 ± 1.3 33.1 ± 2.4 107.7 ± 1.1 97.6 ± 1.2 87.2 ± 1.1
Open in a new tab

Figure 5.

Figure 5.

Open in a new tab

Temperature response of carboxylation rate (kcatc) and CO2 affinity in air (Kcair; A) and specificity factor (SC/O) and carboxylation efficiency (kcatc/Kcair; B) in soybean.

A group level model for Kcair could be fitted to groups 2 and 3, but not groups 1, 4, and 5. Each of the 75 species was modeled with a similar quadratic function; however, only groups 2 and 3 could have all its members statistically explained by a single model. Kcair increased with temperature and the rate of increase was lower above 25°C, reflected in the representative function shown in Figure 5A. As mentioned above, SC/O decreased with temperature. Consistent with previous data, this decrease was nonlinear and for each species/group was best described by a quadratic function. The decrease in SC/O was generally greater between 20 to 25°C than 25 to 30°C (Fig. 5B). In group 3, this response was reversed (greater decrease between 25 and 30°C). Carboxylation efficiency (kcatc/Kcair) was also described by a quadratic model with efficiency being highest at 20 and 30°C, and consistently lower at 25°C. Though the drop in efficiency around 25°C varied between species and groups, the quadratic effect was consistent across the range of species, with variation evident in both the slope and intercept of the functions generated (Supplemental Fig. S4).

DISCUSSION

Significant Variation in Rubisco Catalysis among Diverse Species

This study represents the largest single survey of Rubisco catalysis to date. A large number of studies have previously described Rubisco catalysis (for review, see Parry et al., 2007, 2013; Whitney et al., 2011b; Carmo-Silva et al., 2015). However, this still represents a very small fraction of known lands plants (approximately 0.2% based on current literature). Unfortunately, many studies have also only partially characterized Rubisco catalysis, with specificity (SC/O) in particular lacking from most available datasets (Sharwood and Whitney, 2014). This study dramatically expands upon our knowledge of Rubisco catalytic variability through full characterization of 75 plant species and provides a large comparative data set to inform future engineering efforts. The results presented here reinforce that despite the relatively highly conserved nature of the Rubisco large subunit gene rbcL (Kapralov and Filatov, 2007; Wang et al., 2011), key catalytic parameters vary significantly across diverse plant taxa. Carboxylation rates in particular varied by almost 3-fold at 25°C. Leaf scale modeling predicted that direct replacement strategies using newly characterized Rubiscos could substantially improve maximum photosynthetic capacity, though this will likely require further advances in our ability to test foreign Rubiscos in tobacco-based systems (Whitney et al., 2011a). Nevertheless, this demonstrates the potential gains in photosynthetic capacity through Rubisco substitution. This data set characterizing a broad range of species at multiple temperatures will also be of use in modeling of photosynthesis at different scales (Smith and Dukes, 2013) and complement in planta studies seeking to adapt models of various scales for the increased temperatures expected in many regions in the coming decades (Bagley et al., 2015).

Targeting Improvements through Mutagenesis

The large subunit of Rubisco, encoded by the chloroplast rbcL gene, contains the catalytic sites and is believed to be primarily, though not solely, responsible for the catalytic profile of the holoenzyme (Sharwood et al., 2008). A number of residues were identified that warrant mutagenic testing in model systems, including a number of new candidates not previously highlighted. The residues identified differed dependent on the set of species included in the analysis, demonstrating the need to consider the phylogenetic background of a target Rubisco when determining the potential impact of point mutations. It may also signify the diversity of catalytic solutions found by nature and the likely difficulty in finding a “one size fits all” approach to targeted improvement of Rubisco. There is also some evidence for a role of the small subunit in explaining some of the catalytic variation found in nature, though further investigation in this area is required (discussed below). Potential unintended effects on assembly could be a factor when mutating residues known to be involved in interactions between the large and small subunits. Careful consideration must also be given to avoiding effects on holoenzyme assembly and compatibility with ancillary proteins or assembly chaperones (Carmo-Silva et al., 2015; Whitney et al., 2015). This presents a promising avenue for future work in model systems, testing these residues either singly or in combination, with previous studies having shown strong potential for modifying Rubisco catalysis with targeted amino acid substitutions (Whitney et al., 2011b).

The Effect of Temperature on Rubisco Catalysis

Few studies have explored the effect of temperature on Rubisco catalysis beyond model species (Sharwood and Whitney, 2014; Sharwood et al., 2016) and none at the scale of this study. Recent work has begun to make important inroads into this area (Perdomo et al., 2015; Prins et al., 2016). Analysis of the correlations between parameters at the three measurement temperatures largely agreed with previous observations regarding the trade-off between increasing carboxylation rate (kcatc) and decreasing CO2 affinity (increasing Kcair). However, the tight linking of these parameters was not evident at 30°C. This “uncoupling” at higher temperatures suggests the possibility of finding superior Rubiscos for operating at relatively high temperatures. This study found a negative correlation between warmer climates and specificity (SC/O). Galmés et al. (2005) found that in hot and dry conditions in the Mediterranean, this correlation was positive, with high Rubisco specificity found for plants from this region. This suggests a more complex relationship between climate and Rubisco specificity that is not solely based on temperature, but also needs consideration of additional climatic data such as precipitation.

Higher temperature environments (TWQ) did not consistently correlate with carboxylation parameters across assay temperatures, but did correlate with increasing Ko and Vo. The observed correlations suggest that Rubiscos from warmer climates are less efficient at lower temperatures. Fitting mathematical models to the response of key parameters to measurement temperature resulted primarily in nonlinear models, the exception being carboxylation rate (kcatc). The type of model that best explained temperature response of each parameter was consistent across species, though variation in the absolute values for each species largely prevented fitting a single model to the species groupings. In many cases, species within a group had parallel responses. This provides important new insights on the response of Rubisco catalysis to temperature and its consistency across diverse species, while further highlighting the diversity of catalysis. It is important to note that a number of plant groups such as trees and basal angiosperms remain either underrepresented in biochemical data sets or have only just begun to be surveyed (Galmés et al., 2014b) and provide potential areas where additional valuable information can be gleamed from characterization. Data are also lacking for crop species, with few represented in the literature and often with incomplete characterization. This is an important gap in our knowledge that will be important when targeting improvements to key crops. This study focused on C3 species, and the potential for C4 Rubiscos to respond differently has received increased interest recently (Boyd et al., 2015; Perdomo et al., 2015); however, there remains a need to characterize more Rubiscos from C4 species for thermal response.

Tailored Solutions Are Required for Optimizing Crop Carbon Assimilation

The variation in catalysis found during this study provides important information for future efforts to engineer improved Rubisco in crops via either replacement with a foreign Rubisco (Fig. 2) or point mutations of the endogenous gene (Fig. 3). In C3 plants, 20 to 35°C is considered the optimum temperature range for photosynthesis (Blankenship, 2014); thus, the effects of temperature on Rubisco catalysis should be considered so that an appropriate Rubisco suited to the growth environment can be engineered (Galmés et al., 2014a, 2015; Sharwood and Whitney, 2014). The subcellular environment of the crop is also an important factor; it has been suggested that diversity in Rubisco catalysis may have evolved, at least partly, as a consequence of the variability found in the subcellular environment of different plant leaves (Tcherkez et al., 2006; Galmés et al., 2014c). This remains an important area requiring investigation through the use of model systems such as tobacco and an important consideration for coengineering improved Rubisco catalysis alongside large anatomical changes, e.g. the conversion of C3 crops to C4 photosynthesis (Driever and Kromdijk, 2013). Direct replacement of Rubisco will also likely necessitate coengineering of ancillary proteins to achieve maximum results, as demonstrated recently through work with the cochaperone RAF1 (Whitney et al., 2015). The recent introduction of a faster cyanobacterial Rubisco that could sustain higher photosynthetic rates, albeit at high CO2 concentrations (Lin et al., 2014b; Occhialini et al., 2016), confirms the feasibility and potential of interspecies Rubisco substitutions.

The interaction of large and small subunits and the potential of the small subunit to influence catalysis also warrant further investigation. For example, in a recent study of close relatives of wheat (Triticum aestivum), the observed variability in catalysis appears unlikely to be related to differences in rbcL and may be the result of differences in Rubisco small subunit gene (rbcS) sequence (Prins et al., 2016). Wheat is known to contain a large rbcS family (Spreitzer, 2003); however, for many species, the number and sequence diversity of rbcS genes is unknown. The possible influence of environmental conditions on Rubisco small subunit composition may also need to be considered (Cavanagh and Kubien, 2014). The introduction of an rbcS gene from Sorghum into rice showed how the introduction of foreign small subunits can alter catalysis (Ishikawa et al., 2011) and reinforces the need for more information on the variability of the number, sequence, and expression of rbcS gene family members from wild species and crops of interest.

CONCLUSION

This study improves our understanding of the variability of Rubisco catalysis present in nature. Interrogation of this large data set provides new insights as to the consistency of the response of catalysis to temperature across a broad range of species. Analysis of detailed biochemical characterization alongside sequence information suggests that targeted mutation of key residues and/or replacement of crop Rubisco with superior existing enzymes will aid in efforts to engineer improved carbon assimilation in key crops. This work highlights the importance of characterizing the biochemistry of Rubisco at a range of key temperatures alongside sequence information to improve our understanding of the relationship between structure and function of this critical enzyme.

MATERIALS AND METHODS

Plant Material

Seeds and plant material were kindly provided by the Royal Botanic Gardens Millennium Seed Bank (UK); the USDA, Germplasm Resources Information Network (USDA-GRIN); International Rice Research Institute (IRRI); Mike Birkett, Yi Chen, Belinda Townsend (Rothamsted Research, UK); Guoxiong Chen (CAAS, Lanzhou, China); and Mel Oliver (USDA, Plant Genetics Research). Plants were grown in a glasshouse with a 16/8-h day/night cycle with temperatures of 26/19°C. During the day, supplemental lighting was used to maintain a minimum light level of 200 µmol m−2 s−1. Plants were kept well-watered. For all analyses, samples of leaf material were taken from young, healthy plants and immediately snap frozen in liquid nitrogen, then stored at −80°C.

Climatic Data

Georeferenced coordinates for all species were downloaded from the Global Biodiversity Information Facility (GBIF.org; accessed June–July 2015), and climate data (BioClim, worldclim.org/bioclim; Hijmans et al., 2005) were obtained using DIVA-GIS (diva-gis.org; Hijmans et al., 2001). Due to the incompleteness of publically available distribution databases (Maldonado et al., 2015), studies on climate niche typically use species mean values instead of climatic limits. This study used mean values of the average temperature across the warmest quarter for each species as a proxy for the main growing season, when most of the photosynthetic (and hence Rubisco) activity occurs. This value is referred to as TWQ (temperature of the warmest quarter) throughout the text, and values for each species are listed in Supplemental Table S1.

Rubisco Catalytic Properties

Rubisco was extracted and its catalytic properties determined essentially as previously described (Prins et al., 2016), with the following alterations: reactions were carried out in 0% and 21% O2 conditions only, with two technical replicates of each of these concentrations; and protein extracts were activated and assayed immediately after extraction and desalting.

Rubisco Specificity Factor

Rubisco from each genotype was purified essentially as described by Prins et al. (2016), with the exception that the final Sephacryl S-200 filtration step was found to be unnecessary for most of the genotypes in this study. Testing confirmed that excluding this step did not influence the assay results. Rubisco specificity (SC/O) was determined using the oxygen electrode method as described previously (Parry et al., 1989). For each species, at least four replicate measurements were made at each temperature. Values were normalized to a value for wheat (Triticum aestivum) at each temperature, as described by Parry et al. (1989).

Rubisco Content

An aliquot of the soluble protein extracted for measuring catalytic constants was used to determine total Rubisco content by 14C-CABP binding via either the method of Parry et al. (1997) or Whitney et al. (1999). Testing confirmed that using one or the other method did not influence the quantification results.

rbcL Sequencing

Genomic DNA was extracted from leaf tissue using the Qiagen DNEasy plant kit. Amplification of partial rbcL fragments equivalent to codons 1 to 463 (∼98% of the coding region) was carried out using Phusion HF polymerase (Invitrogen). Forward primer (5′-TAATTCATGAGTTGTAGGGAGGG-3′) was paired with cp063R (Dong et al., 2013; 5′-TTTCCATACTTCACAAGCAGCAGCTAG-3′). PCR products were then sequenced using the following primers (Eurofins Genomics): DRS19 (5′-GKGYTCCTATTGTAATGCATGACTACTTAAC-3′), rbcL_F1 (5′-ATGTCACCACAAACAGAAACTAAA-3′), and rbcL_F3 (CCRCCBCAYGGNATYCARG). At least two independent PCR reactions were performed and had product sequenced for each genotype. Sequences were submitted to EMBL (see Supplemental Table S3 for accession numbers).

Rubisco L-Subunit Sites under Positive Selection

DNA sequences of rbcL were aligned using MUSCLE (Edgar, 2004). The software MODELTEST 3.7 (Posada and Crandall, 1998; Posada and Buckley, 2004) was used to check for the best model before running the phylogenetic analyses using maximum-likelihood inference conducted with RAxML version 7.2.6 (Stamatakis, 2006). Rubisco amino acid residues under positive selection associated with particular kinetic traits were identified using codon-based substitution models in comparative analysis of protein-coding DNA sequences within the phylogenetic framework using branch-site tests of positive selection along prespecified foreground branches in the PAML v.4.7 package (Yang, 2007) as described (Kapralov et al., 2011, 2012; Galmés et al., 2014b). Branches leading to species with high or low Kcair, kcatc, Ko, kcato, and SC/O at 25°C were marked as foreground branches. The Rubisco L-subunit residues are numbered based on the spinach sequence. The location of sites under positive selection was done using Rubisco protein structure from spinach (Spinacia oleracea) obtained from the RCSB Protein Data Bank (http://www.rcsb.org; file 1RCX; Karkehabadi et al., 2003).

Phylogenetically Independent Contrasts

The Pearson correlation coefficient was calculated between pairwise combinations of the kinetic parameters Kc, Kcair, kcatc, Ko, Vo, and SC/O at the three temperatures of measurement. Correlations arising within groups of related taxa might reflect phylogenetic signal rather than true cause-effect relationships because closely related taxa are not necessarily independent data points and could violate the assumption of randomized sampling employed by conventional statistical methods (Felsenstein, 1985). To overcome this issue, tests were performed for the presence of phylogenetic signal in the data, and trait correlations were calculated with phylogenetically independent contrasts using the AOT module of PHYLOCOM (Webb et al., 2008) for the species phylogeny described above. All these tests were considered significant at P < 0.05.

Statistical Analyses

The 75 species were divided into five groups based on phylogenetic relationships (Fig. 3). To establish the significance of variation between these groups (and the species within the groups), the variation with temperature for each group was assessed using nonlinear regression analysis and the fitting of an asymptotic exponential/simple exponential model. The resulting best models were plotted. Analysis was carried out using GenStat (VSN International). The five C4 species in this study were not included when analyzing temperature response. With the exception of SC/O, all data were transformed via log function to conform to the assumptions of the analysis.

Accession Numbers

Sequence data from this article can be found in the GenBank/EMBL data libraries under accession numbers LT576791 to LT576865.

Supplemental Material

The following supplemental materials are available.

Supplementary Material

Supplemental Data
supp_172_2_707__index.html (892B, html)

Acknowledgments

We thank Jess Evans and Andrew Mead (Rothamsted Research) for support with statistical analyses, Alfred Keys (Rothamsted Research) for useful discussions, and numerous colleagues and institutions who provided plant material or seeds of the species studied (listed in “Materials and Methods”).

Footnotes

[OPEN]

Articles can be viewed without a subscription.

1

This work was supported through a sub-contract from the University of Illinois as part of the Bill and Melinda Gates Foundation award RIPE: Realizing Increases in Photosynthetic Efficiency.

References

  1. Andersson I. (2008) Catalysis and regulation in Rubisco. J Exp Bot 59: 1555–1568 [DOI] [PubMed] [Google Scholar]
  2. Andralojc PJ, Bencze S, Madgwick PJ, Philippe H, Powers SJ, Shield I, Karp A, Parry MAJ (2014) Photosynthesis and growth in diverse willow genotypes. Food and Energy Security 3: 69–85 [Google Scholar]
  3. Andralojc PJ, Madgwick PJ, Tao Y, Keys A, Ward JL, Beale MH, Loveland JE, Jackson PJ, Willis AC, Gutteridge S, Parry MAJ (2012) 2-Carboxy-D-arabinitol 1-phosphate (CA1P) phosphatase: evidence for a wider role in plant Rubisco regulation. Biochem J 442: 733–742 [DOI] [PubMed] [Google Scholar]
  4. Bagley J, Rosenthal DM, Ruiz-Vera UM, Siebers MH, Kumar P, Ort DR, Bernacchi CJ (2015) The influence of photosynthetic acclimation to rising CO2 and warmer temperatures on leaf and canopy photosynthesis models. Global Biogeochem Cycles 29: 194–206 [Google Scholar]
  5. Betti M, Bauwe H, Busch FA, Fernie AR, Keech O, Levey M, Ort DR, Parry MAJ, Sage R, Timm S, Walker B, Weber AP (2016) Manipulating photorespiration to increase plant productivity: recent advances and perspectives for crop improvement. J Exp Bot 67: 2977–2988 [DOI] [PubMed] [Google Scholar]
  6. Blankenship RE. (2014) Molecular Mechanisms of Photosynthesis. Wiley-Blackwell, Chichester, UK [Google Scholar]
  7. Bracher A, Sharma A, Starling-Windhof A, Hartl FU, Hayer-Hartl M (2015) Degradation of potent Rubisco inhibitor by selective sugar phosphatase. Nat. Plants 1: 14002. [DOI] [PubMed] [Google Scholar]
  8. Boyd RA, Gandin A, Cousins AB (2015) Temperature responses of C4 photosynthesis: biochemical analysis of Rubisco, phosphoenolpyruvate carboxylase, and carbonic anhydrase in Setaria viridis. Plant Physiol 169: 1850–1861 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Carmo-Silva AE, Salvucci ME (2013) The regulatory properties of Rubisco activase differ among species and affect photosynthetic induction during light transitions. Plant Physiol 161: 1645–1655 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Carmo-Silva E, Scales JC, Madgwick PJ, Parry MAJ (2015) Optimizing Rubisco and its regulation for greater resource use efficiency. Plant Cell Environ 38: 1817–1832 [DOI] [PubMed] [Google Scholar]
  11. Cavanagh AP, Kubien DS (2014) Can phenotypic plasticity in Rubisco performance contribute to photosynthetic acclimation? Photosynth Res 119: 203–214 [DOI] [PubMed] [Google Scholar]
  12. Christin PA, Salamin N, Muasya AM, Roalson EH, Russier F, Besnard G (2008) Evolutionary switch and genetic convergence on rbcL following the evolution of C4 photosynthesis. Mol Biol Evol 25: 2361–2368 [DOI] [PubMed] [Google Scholar]
  13. Cousins AB, Ghannoum O, VON Caemmerer S, Badger MR (2010) Simultaneous determination of Rubisco carboxylase and oxygenase kinetic parameters in Triticum aestivum and Zea mays using membrane inlet mass spectrometry. Plant Cell Environ 33: 444–452 [DOI] [PubMed] [Google Scholar]
  14. Dong W, Xu C, Cheng T, Lin K, Zhou S (2013) Sequencing angiosperm plastid genomes made easy: a complete set of universal primers and a case study on the phylogeny of saxifragales. Genome Biol Evol 5: 989–997 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Drewry DT, Kumar P, Long SP (2014) Simultaneous improvement in productivity, water use, and albedo through crop structural modification. Glob Change Biol 20: 1955–1967 [DOI] [PubMed] [Google Scholar]
  16. Driever SM, Kromdijk J (2013) Will C3 crops enhanced with the C4 CO2-concentrating mechanism live up to their full potential (yield)? J Exp Bot 64: 3925–3935 [DOI] [PubMed] [Google Scholar]
  17. Edgar RC. (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32: 1792–1797 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Ellis RJ. (1979) The most abundant protein in the world. Trends Biochem Sci 4: 241–244 [Google Scholar]
  19. Farquhar GD, von Caemmerer S, Berry JA (1980) A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species. Planta 149: 78–90 [DOI] [PubMed] [Google Scholar]
  20. Felsenstein J. (1985) Phylogenies and the comparative method. Am Nat 125: 1–15 [Google Scholar]
  21. Furbank RT, von Caemmerer S, Sheehy J, Edwards G (2009) C4 rice: a challenge for plant phenomics. Funct Plant Biol 36: 845–856 [DOI] [PubMed] [Google Scholar]
  22. Galmés J, Andralojc PJ, Kapralov MV, Flexas J, Keys AJ, Molins A, Parry MAJ, Conesa MÀ (2014c) Environmentally driven evolution of Rubisco and improved photosynthesis and growth within the C3 genus Limonium (Plumbaginaceae). New Phytol 203: 989–999 [DOI] [PubMed] [Google Scholar]
  23. Galmés J, Conesa MÀ, Díaz-Espejo A, Mir A, Perdomo JA, Niinemets U, Flexas J (2014a) Rubisco catalytic properties optimized for present and future climatic conditions. Plant Sci 226: 61–70 [DOI] [PubMed] [Google Scholar]
  24. Galmés J, Flexas J, Keys AJ, Cifre J, Mitchell RAC, Madgwick PJ, Haslam RP, Medrano H, Parry MAJ (2005) Rubisco specificity factor tends to be larger in plant species from drier habitats and in species with persistent leaves. Plant Cell Environ 28: 571–579 [Google Scholar]
  25. Galmés J, Kapralov MV, Andralojc PJ, Conesa MA, Keys AJ, Parry MAJ, Flexas J (2014b) Expanding knowledge of the Rubisco kinetics variability in plant species: environmental and evolutionary trends. Plant Cell Environ 37: 1989–2001 [DOI] [PubMed] [Google Scholar]
  26. Galmés J, Kapralov MV, Copolovici LO, Hermida-Carrera C, Niinemets Ü (2015) Temperature responses of the Rubisco maximum carboxylase activity across domains of life: phylogenetic signals, trade-offs, and importance for carbon gain. Photosynth Res 123: 183–201 [DOI] [PubMed] [Google Scholar]
  27. Hanson MR, Lin MT, Carmo-Silva AE, Parry MA (2016) Towards engineering carboxysomes into C3 plants. Plant J J 10.1111/tpj.13139 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Hauser T, Bhat JY, Miličić G, Wendler P, Hartl FU, Bracher A, Hayer-Hartl M (2015) Structure and mechanism of the Rubisco-assembly chaperone Raf1. Nat Struct Mol Biol 22: 720–728 [DOI] [PubMed] [Google Scholar]
  29. Hijmans RJ, Guarino L, Cruz M, Rojas E (2001) Computer tools for spatial analysis of plant genetic resources data: 1. DIVA-GIS. Plant Genet Resour Newsl 127: 15–19 [Google Scholar]
  30. Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A (2005) Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25: 1965–1978 [Google Scholar]
  31. Ishikawa C, Hatanaka T, Misoo S, Miyake C, Fukayama H (2011) Functional incorporation of sorghum small subunit increases the catalytic turnover rate of Rubisco in transgenic rice. Plant Physiol 156: 1603–1611 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Kapralov MV, Filatov DA (2007) Widespread positive selection in the photosynthetic Rubisco enzyme. BMC Evol Biol 7: 73. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Kapralov MV, Kubien DS, Andersson I, Filatov DA (2011) Changes in Rubisco kinetics during the evolution of C4 photosynthesis in Flaveria (Asteraceae) are associated with positive selection on genes encoding the enzyme. Mol Biol Evol 28: 1491–1503 [DOI] [PubMed] [Google Scholar]
  34. Kapralov MV, Smith JAC, Filatov DA (2012) Rubisco evolution in C₄ eudicots: an analysis of Amaranthaceae sensu lato. PLoS One 7: e52974. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Karkehabadi S, Taylor TC, Andersson I (2003) Calcium supports loop closure but not catalysis in Rubisco. J Mol Biol 334: 65–73 [DOI] [PubMed] [Google Scholar]
  36. Kubien DS, Whitney SM, Moore PV, Jesson LK (2008) The biochemistry of Rubisco in Flaveria. J Exp Bot 59: 1767–1777 [DOI] [PubMed] [Google Scholar]
  37. Lin MT, Occhialini A, Andralojc PJ, Devonshire J, Hines KM, Parry MAJ, Hanson MR (2014a) β-Carboxysomal proteins assemble into highly organized structures in Nicotiana chloroplasts. Plant J 79: 1–12 [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Lin MT, Occhialini A, Andralojc PJ, Parry MAJ, Hanson MR (2014b) A faster Rubisco with potential to increase photosynthesis in crops. Nature 513: 547–550 [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Long BM, Rae BD, Rolland V, Förster B, Price GD (2016) Cyanobacterial CO2-concentrating mechanism components: function and prospects for plant metabolic engineering. Curr Opin Plant Biol 31: 1–8 [DOI] [PubMed] [Google Scholar]
  40. Long SP, Marshall-Colon A, Zhu XG (2015) Meeting the global food demand of the future by engineering crop photosynthesis and yield potential. Cell 161: 56–66 [DOI] [PubMed] [Google Scholar]
  41. Long SP, Ort DR (2010) More than taking the heat: crops and global change. Curr Opin Plant Biol 13: 241–248 [DOI] [PubMed] [Google Scholar]
  42. Maldonado C, Molina CI, Zizka A, Persson C, Taylor CM, Albán J, Chilquillo E, Rønsted N, Antonelli A (2015) Estimating species diversity and distribution in the era of Big Data: to what extent can we trust public databases? Glob Ecol Biogeogr 24: 973–984 [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. McGrath JM, Long SP (2014) Can the cyanobacterial carbon-concentrating mechanism increase photosynthesis in crop species? A theoretical analysis. Plant Physiol 164: 2247–2261 [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Morita K, Hatanaka T, Misoo S, Fukayama H (2014) Unusual small subunit that is not expressed in photosynthetic cells alters the catalytic properties of rubisco in rice. Plant Physiol 164: 69–79 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Nunes-Nesi A, Nascimento VdeL, de Oliveira Silva FM, Zsögön A, Araújo WL, Sulpice R (2016) Natural genetic variation for morphological and molecular determinants of plant growth and yield. J Exp Bot 67: 2989–3001 [DOI] [PubMed] [Google Scholar]
  46. Occhialini A, Lin MT, Andralojc PJ, Hanson MR, Parry MAJ (2016) Transgenic tobacco plants with improved cyanobacterial Rubisco expression but no extra assembly factors grow at near wild-type rates if provided with elevated CO2. Plant J 85: 148–160 [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Ort DR, Merchant SS, Alric J, Barkan A, Blankenship RE, Bock R, Croce R, Hanson MR, Hibberd JM, Long SP, et al. (2015) Redesigning photosynthesis to sustainably meet global food and bioenergy demand. Proc Natl Acad Sci USA 112: 8529–8536 [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Parry MAJ, Andralojc PJ, Parmar S, Keys AJ, Habash D, Paul MJ, Alred R, Quick WP, Servaites JC (1997) Regulation of Rubisco by inhibitors in the light. Plant Cell Environ 20: 528–534 [Google Scholar]
  49. Parry MAJ, Andralojc PJ, Scales JC, Salvucci ME, Carmo-Silva AE, Alonso H, Whitney SM (2013) Rubisco activity and regulation as targets for crop improvement. J Exp Bot 64: 717–730 [DOI] [PubMed] [Google Scholar]
  50. Parry MAJ, Keys AJ, Gutteridge S (1989) Variation in the specificity factor of C3 higher plant Rubiscos determined by the total consumption of ribulose-P2. J Exp Bot 40: 317–320 [Google Scholar]
  51. Parry MAJ, Madgwick PJ, Carvalho JFC, Andralojc PJ (2007) Prospects for increasing photosynthesis by overcoming the limitations of Rubisco. J Agric Sci 145: 31–43 [Google Scholar]
  52. Perdomo JA, Cavanagh AP, Kubien DS, Galmés J (2015) Temperature dependence of in vitro Rubisco kinetics in species of Flaveria with different photosynthetic mechanisms. Photosynth Res 124: 67–75 [DOI] [PubMed] [Google Scholar]
  53. Peterhansel C, Blume C, Offermann S (2013) Photorespiratory bypasses: how can they work? J Exp Bot 64: 709–715 [DOI] [PubMed] [Google Scholar]
  54. Posada D, Buckley TR (2004) Model selection and model averaging in phylogenetics: advantages of akaike information criterion and bayesian approaches over likelihood ratio tests. Syst Biol 53: 793–808 [DOI] [PubMed] [Google Scholar]
  55. Posada D, Crandall KA (1998) MODELTEST: testing the model of DNA substitution. Bioinformatics 14: 817–818 [DOI] [PubMed] [Google Scholar]
  56. Price GD, Pengelly JJ, Forster B, Du J, Whitney SM, von Caemmerer S, Badger MR, Howitt SM, Evans JR (2013) The cyanobacterial CCM as a source of genes for improving photosynthetic CO2 fixation in crop species. J Exp Bot 64: 753–768 [DOI] [PubMed] [Google Scholar]
  57. Prins A, Orr DJ, Andralojc PJ, Reynolds MP, Carmo-Silva E, Parry MAJ (2016) Rubisco catalytic properties of wild and domesticated relatives provide scope for improving wheat photosynthesis. J Exp Bot 67: 1827–1838 [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Raines CA. (2011) Increasing photosynthetic carbon assimilation in C3 plants to improve crop yield: current and future strategies. Plant Physiol 155: 36–42 [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Ray DK, Ramankutty N, Mueller ND, West PC, Foley JA (2012) Recent patterns of crop yield growth and stagnation. Nat Commun 3: 1293. [DOI] [PubMed] [Google Scholar]
  60. Rosnow JJ, Evans MA, Kapralov MV, Cousins AB, Edwards GE, Roalson EH (2015) Kranz and single-cell forms of C4 plants in the subfamily Suaedoideae show kinetic C4 convergence for PEPC and Rubisco with divergent amino acid substitutions. J Exp Bot 66: 7347–7358 [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Saschenbrecker S, Bracher A, Rao KV, Rao BV, Hartl FU, Hayer-Hartl M (2007) Structure and function of RbcX, an assembly chaperone for hexadecameric Rubisco. Cell 129: 1189–1200 [DOI] [PubMed] [Google Scholar]
  62. Sharwood RE, Ghannoum O, Whitney SM (2016) Prospects for improving CO2 fixation in C3-crops through understanding C4-Rubisco biogenesis and catalytic diversity. Curr Opin Plant Biol 31: 135–142 [DOI] [PubMed] [Google Scholar]
  63. Sharwood RE, von Caemmerer S, Maliga P, Whitney SM (2008) The catalytic properties of hybrid Rubisco comprising tobacco small and sunflower large subunits mirror the kinetically equivalent source Rubiscos and can support tobacco growth. Plant Physiol 146: 83–96 [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Sharwood RE, Whitney SM (2014) Correlating Rubisco catalytic and sequence diversity within C3 plants with changes in atmospheric CO2 concentrations. Plant Cell Environ 37: 1981–1984 [DOI] [PubMed] [Google Scholar]
  65. Simkin AJ, McAusland L, Headland LR, Lawson T, Raines CA (2015) Multigene manipulation of photosynthetic carbon assimilation increases CO2 fixation and biomass yield in tobacco. J Exp Bot 66: 4075–4090 [DOI] [PMC free article] [PubMed] [Google Scholar]
  66. Smith NG, Dukes JS (2013) Plant respiration and photosynthesis in global-scale models: incorporating acclimation to temperature and CO2. Glob Change Biol 19: 45–63 [DOI] [PubMed] [Google Scholar]
  67. Spreitzer RJ. (2003) Role of the small subunit in ribulose-1,5-bisphosphate carboxylase/oxygenase. Arch Biochem Biophys 414: 141–149 [DOI] [PubMed] [Google Scholar]
  68. Spreitzer RJ, Peddi SR, Satagopan S (2005) Phylogenetic engineering at an interface between large and small subunits imparts land-plant kinetic properties to algal Rubisco. Proc Natl Acad Sci USA 102: 17225–17230 [DOI] [PMC free article] [PubMed] [Google Scholar]
  69. Stamatakis A. (2006) RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics 22: 2688–2690 [DOI] [PubMed] [Google Scholar]
  70. Tcherkez GG, Farquhar GD, Andrews TJ (2006) Despite slow catalysis and confused substrate specificity, all ribulose bisphosphate carboxylases may be nearly perfectly optimized. Proc Natl Acad Sci USA 103: 7246–7251 [DOI] [PMC free article] [PubMed] [Google Scholar]
  71. von Caemmerer S. (2000) Biochemical Models of Leaf Photosynthesis. CSIRO Publishing, Collingwood, Australia [Google Scholar]
  72. von Caemmerer S, Quick WP, Furbank RT (2012) The development of C4 rice: current progress and future challenges. Science 336: 1671–1672 [DOI] [PubMed] [Google Scholar]
  73. Wang M, Kapralov MV, Anisimova M (2011) Coevolution of amino acid residues in the key photosynthetic enzyme Rubisco. BMC Evol Biol 11: 266. [DOI] [PMC free article] [PubMed] [Google Scholar]
  74. Webb CO, Ackerly DD, Kembel SW (2008) Phylocom: software for the analysis of phylogenetic community structure and trait evolution. Bioinformatics 24: 2098–2100 [DOI] [PubMed] [Google Scholar]
  75. Whitney SM, Birch R, Kelso C, Beck JL, Kapralov MV (2015) Improving recombinant Rubisco biogenesis, plant photosynthesis and growth by coexpressing its ancillary RAF1 chaperone. Proc Natl Acad Sci USA 112: 3564–3569 [DOI] [PMC free article] [PubMed] [Google Scholar]
  76. Whitney SM, Houtz RL, Alonso H (2011a) Advancing our understanding and capacity to engineer nature’s CO2-sequestering enzyme, Rubisco. Plant Physiol 155: 27–35 [DOI] [PMC free article] [PubMed] [Google Scholar]
  77. Whitney SM, Sharwood RE (2008) Construction of a tobacco master line to improve Rubisco engineering in chloroplasts. J Exp Bot 59: 1909–1921 [DOI] [PubMed] [Google Scholar]
  78. Whitney SM, Sharwood RE, Orr D, White SJ, Alonso H, Galmés J (2011b) Isoleucine 309 acts as a C4 catalytic switch that increases ribulose-1,5-bisphosphate carboxylase/oxygenase (rubisco) carboxylation rate in Flaveria. Proc Natl Acad Sci USA 108: 14688–14693 [DOI] [PMC free article] [PubMed] [Google Scholar]
  79. Whitney SM, von Caemmerer S, Hudson GS, Andrews TJ (1999) Directed mutation of the Rubisco large subunit of tobacco influences photorespiration and growth. Plant Physiol 121: 579–588 [DOI] [PMC free article] [PubMed] [Google Scholar]
  80. Wilson RH, Alonso H, Whitney SM (2016) Evolving Methanococcoides burtonii archaeal Rubisco for improved photosynthesis and plant growth. Sci Rep 6: 22284. [DOI] [PMC free article] [PubMed] [Google Scholar]
  81. Yang Z. (2007) PAML 4: phylogenetic analysis by maximum likelihood. Mol Biol Evol 24: 1586–1591 [DOI] [PubMed] [Google Scholar]
  82. Zhu XG, Portis AR, Long SP (2004) Would transformation of C3 crop plants with foreign Rubisco increase productivity? A computational analysis extrapolating from kinetic properties to canopy photosynthesis. Plant Cell Environ 27: 155–165 [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplemental Data
supp_172_2_707__index.html (892B, html)
supp_pp.16.00750_00750revsupp.docx (7.6MB, docx)

Articles from Plant Physiology are provided here courtesy of Oxford University Press

RESOURCES