Sugar sensing in C4 source leaves: a gap that needs to be filled.

Plant growth depends on sugar production and export by photosynthesising source leaves and sugar allocation and import by sink tissues (grains, roots, stems, young leaves). Photosynthesis and sink demand are tightly coordinated through metabolic (substrate, allosteric) feedback and signalling (sugar, hormones) mechanisms. Sugar signalling integrates sugar production with plant development and environmental cues. In C3 plants (e.g., wheat, rice), it is well documented that sugar accumulation in source leaves, due to source-sink imbalance, negatively feedbacks on photosynthesis and plant productivity. However, we have a limited understanding about the molecular mechanisms underlying those feedback regulations, especially in C4 plants (e.g., maize, sorghum, sugarcane). Recent work with the C4 model Setaria viridis suggested that C4 leaves have different sugar sensing thresholds and behaviours relative to C3 counterparts. Addressing this research priority is critical because improving crop yield requires a better understanding of how plants coordinate source activity with sink demand. Here we review the literature, present a model of action for sugar sensing in C4 source leaves and suggest ways forward.

Variation in leaf dark respiration among C3 and C4 grasses is associated with use of different substrates.

Measurements of respiratory properties have often been made at a single time point either during daytime using dark-adapted leaves or during night-time. The influence of the day-night cycle on respiratory metabolism has received less attention but is crucial to understand photosynthesis and photorespiration. Here, we examined how CO2- and O2-based rates of leaf dark respiration (Rdark) differed between midday (after 30-minute dark adaptation) and midnight in eight C3 and C4 grasses. We used these data to calculate the respiratory quotient (RQ; ratio of CO2 release to O2 uptake), and assessed relationships between Rdark and leaf metabolome. Rdark was higher at midday than midnight, especially in C4 species. The day-night difference in Rdark was more evident when expressed on a CO2 than O2 basis, with the RQ being higher at midday than midnight in all species, except in rice (Oryza sativa). Metabolomic analyses showed little correlation of Rdark or RQ with leaf carbohydrates (sucrose, glucose, fructose or starch) but strong multivariate relationships with other metabolites. The results suggest that rates of Rdark and differences in RQ were determined by several concurrent CO2-producing and O2-consuming metabolic pathways, not only the tricarboxylic acid cycle (organic acids utilisation), but also the pentose phosphate pathway, galactose metabolism, and secondary metabolism. As such, Rdark was time-, type- (C3/C4) and species-dependent, due to the use of different substrates.

Spatial expression patterns of genes encoding sugar sensors in leaves of C4 and C3 grasses.

BACKGROUND AND AIMS: The mechanisms of sugar sensing in grasses remain elusive, especially those using C4 photosynthesis even though a large proportion of the world's agricultural crops utilize this pathway. We addressed this gap by comparing the expression of genes encoding components of sugar sensors in C3 and C4 grasses, with a focus on source tissues of C4 grasses. Given C4 plants evolved into a two-cell carbon fixation system, it was hypothesized this may have also changed how sugars were sensed. METHODS: For six C3 and eight C4 grasses, putative sugar sensor genes were identified for target of rapamycin (TOR), SNF1-related kinase 1 (SnRK1), hexokinase (HXK) and those involved in the metabolism of the sugar sensing metabolite trehalose-6-phosphate (T6P) using publicly available RNA deep sequencing data. For several of these grasses, expression was compared in three ways: source (leaf) versus sink (seed), along the gradient of the leaf, and bundle sheath versus mesophyll cells. KEY RESULTS: No positive selection of codons associated with the evolution of C4 photosynthesis was identified in sugar sensor proteins here. Expressions of genes encoding sugar sensors were relatively ubiquitous between source and sink tissues as well as along the leaf gradient of both C4 and C3 grasses. Across C4 grasses, SnRK1ß1 and TPS1 were preferentially expressed in the mesophyll and bundle sheath cells, respectively. Species-specific differences of gene expression between the two cell types were also apparent. CONCLUSIONS: This comprehensive transcriptomic study provides an initial foundation for elucidating sugar-sensing genes within major C4 and C3 crops. This study provides some evidence that C4 and C3 grasses do not differ in how sugars are sensed. While sugar sensor gene expression has a degree of stability along the leaf, there are some contrasts between the mesophyll and bundle sheath cells.

The role of SWEET4 proteins in the post-phloem sugar transport pathway of Setaria viridis sink tissues.

In the developing seeds of all higher plants, filial cells are symplastically isolated from the maternal tissue supplying photosynthate to the reproductive structure. Photoassimilates must be transported apoplastically, crossing several membrane barriers, a process facilitated by sugar transporters. Sugars Will Eventually be Exported Transporters (SWEETs) have been proposed to play a crucial role in apoplastic sugar transport during phloem unloading and the post-phloem pathway in sink tissues. Evidence for this is presented here for developing seeds of the C4 model grass Setaria viridis. Using immunolocalization, SvSWEET4 was detected in various maternal and filial tissues within the seed along the sugar transport pathway, in the vascular parenchyma of the pedicel, and in the xylem parenchyma of the stem. Expression of SvSWEET4a in Xenopus laevis oocytes indicated that it functions as a high-capacity glucose and sucrose transporter. Carbohydrate and transcriptional profiling of Setaria seed heads showed that there were some developmental shifts in hexose and sucrose content and consistent expression of SvSWEET4 homologues. Collectively, these results provide evidence for the involvement of SWEETs in the apoplastic transport pathway of sink tissues and allow a pathway for post-phloem sugar transport into the seed to be proposed.

Faster induction of photosynthesis increases biomass and grain yield in glasshouse-grown transgenic Sorghum bicolor overexpressing Rieske FeS.

Sorghum is one of the most important crops providing food and feed in many of the world's harsher environments. Sorghum utilizes the C4 pathway of photosynthesis in which a biochemical carbon-concentrating mechanism results in high CO2 assimilation rates. Overexpressing the Rieske FeS subunit of the Cytochrome b6 f complex was previously shown to increase the rate of photosynthetic electron transport and stimulate CO2 assimilation in the model C4 plant Setaria viridis. To test whether productivity of C4 crops could be improved by Rieske overexpression, we created transgenic Sorghum bicolor Tx430 plants with increased Rieske content. The transgenic plants showed no marked changes in abundances of other photosynthetic proteins or chlorophyll content. The steady-state rates of electron transport and CO2 assimilation did not differ between the plants with increased Rieske abundance and control plants, suggesting that Cytochrome b6 f is not the only factor limiting electron transport in sorghum at high light and high CO2 . However, faster responses of non-photochemical quenching as well as an elevated quantum yield of Photosystem II and an increased CO2 assimilation rate were observed from the plants overexpressing Rieske during the photosynthetic induction, a process of activation of photosynthesis upon the dark-light transition. As a consequence, sorghum with increased Rieske content produced more biomass and grain when grown in glasshouse conditions. Our results indicate that increasing Rieske content has potential to boost productivity of sorghum and other C4 crops by improving the efficiency of light utilization and conversion to biomass through the faster induction of photosynthesis.

Increased sedoheptulose-1,7-bisphosphatase content in Setaria viridis does not affect C4 photosynthesis.

Sedoheptulose-1,7-bisphosphatase (SBPase) is one of the rate-limiting enzymes of the Calvin cycle, and increasing the abundance of SBPase in C3 plants provides higher photosynthetic rates and stimulates biomass and yield. C4 plants usually have higher photosynthetic rates because they operate a biochemical CO2-concentrating mechanism between mesophyll and bundle sheath cells. In the C4 system, SBPase and other enzymes of the Calvin cycle are localized to the bundle sheath cells. Here we tested what effect increasing abundance of SBPase would have on C4 photosynthesis. Using green foxtail millet (Setaria viridis), a model C4 plant of NADP-ME subtype, we created transgenic plants with 1.5 to 3.2 times higher SBPase content compared to wild-type plants. Transcripts of the transgene were found predominantly in the bundle sheaths suggesting the correct cellular localization of the protein. The abundance of ribulose-1,5-bisphosphate carboxylase/oxygenase large subunit was not affected in transgenic plants overexpressing SBPase, and neither was leaf chlorophyll content or photosynthetic electron transport parameters. We found no association between SBPase content in S. viridis and saturating rates of CO2 assimilation. Moreover, a detailed analysis of CO2 assimilation rates at different CO2 partial pressures, irradiances, and leaf temperatures showed no improvement of photosynthesis in plants overexpressing SBPase. We discuss the potential implications of these results for understanding the role of SBPase in regulation of C4 photosynthesis.

Enhancing crop yields through improvements in the efficiency of photosynthesis and respiration.

The rate with which crop yields per hectare increase each year is plateauing at the same time that human population growth and other factors increase food demand. Increasing yield potential ( Y p ) of crops is vital to address these challenges. In this review, we explore a component of Y p that has yet to be optimised - that being improvements in the efficiency with which light energy is converted into biomass ( ε c ) via modifications to CO2 fixed per unit quantum of light (α), efficiency of respiratory ATP production ( ε prod ) and efficiency of ATP use ( ε use ). For α, targets include changes in photoprotective machinery, ribulose bisphosphate carboxylase/oxygenase kinetics and photorespiratory pathways. There is also potential for ε prod to be increased via targeted changes to the expression of the alternative oxidase and mitochondrial uncoupling pathways. Similarly, there are possibilities to improve ε use via changes to the ATP costs of phloem loading, nutrient uptake, futile cycles and/or protein/membrane turnover. Recently developed high-throughput measurements of respiration can serve as a proxy for the cumulative energy cost of these processes. There are thus exciting opportunities to use our growing knowledge of factors influencing the efficiency of photosynthesis and respiration to create a step-change in yield potential of globally important crops.

A cross-scale analysis to understand and quantify the effects of photosynthetic enhancement on crop growth and yield across environments.

Photosynthetic manipulation provides new opportunities for enhancing crop yield. However, understanding and quantifying the importance of individual and multiple manipulations on the seasonal biomass growth and yield performance of target crops across variable production environments is limited. Using a state-of-the-art cross-scale model in the APSIM platform we predicted the impact of altering photosynthesis on the enzyme-limited (Ac ) and electron transport-limited (Aj ) rates, seasonal dynamics in canopy photosynthesis, biomass growth, and yield formation via large multiyear-by-location crop growth simulations. A broad list of promising strategies to improve photosynthesis for C3 wheat and C4 sorghum were simulated. In the top decile of seasonal outcomes, yield gains were predicted to be modest, ranging between 0% and 8%, depending on the manipulation and crop type. We report how photosynthetic enhancement can affect the timing and severity of water and nitrogen stress on the growing crop, resulting in nonintuitive seasonal crop dynamics and yield outcomes. We predicted that strategies enhancing Ac alone generate more consistent but smaller yield gains across all water and nitrogen environments, Aj enhancement alone generates larger gains but is undesirable in more marginal environments. Large increases in both Ac and Aj generate the highest gains across all environments. Yield outcomes of the tested manipulation strategies were predicted and compared for realistic Australian wheat and sorghum production. This study uniquely unpacks complex cross-scale interactions between photosynthesis and seasonal crop dynamics and improves understanding and quantification of the potential impact of photosynthesis traits (or lack of it) for crop improvement research.

A single promoter-TALE system for tissue-specific and tuneable expression of multiple genes in rice.

In biological discovery and engineering research, there is a need to spatially and/or temporally regulate transgene expression. However, the limited availability of promoter sequences that are uniquely active in specific tissue-types and/or at specific times often precludes co-expression of multiple transgenes in precisely controlled developmental contexts. Here, we developed a system for use in rice that comprises synthetic designer transcription activator-like effectors (dTALEs) and cognate synthetic TALE-activated promoters (STAPs). The system allows multiple transgenes to be expressed from different STAPs, with the spatial and temporal context determined by a single promoter that drives expression of the dTALE. We show that two different systems-dTALE1-STAP1 and dTALE2-STAP2-can activate STAP-driven reporter gene expression in stable transgenic rice lines, with transgene transcript levels dependent on both dTALE and STAP sequence identities. The relative strength of individual STAP sequences is consistent between dTALE1 and dTALE2 systems but differs between cell-types, requiring empirical evaluation in each case. dTALE expression leads to off-target activation of endogenous genes but the number of genes affected is substantially less than the number impacted by the somaclonal variation that occurs during the regeneration of transformed plants. With the potential to design fully orthogonal dTALEs for any genome of interest, the dTALE-STAP system thus provides a powerful approach to fine-tune the expression of multiple transgenes, and to simultaneously introduce different synthetic circuits into distinct developmental contexts.

Mining for allelic gold: finding genetic variation in photosynthetic traits in crops and wild relatives.

Improvement of photosynthetic traits in crops to increase yield potential and crop resilience has recently become a major breeding target. Synthetic biology and genetic technologies offer unparalleled opportunities to create new genetics for photosynthetic traits driven by existing fundamental knowledge. However, large 'gene bank' collections of germplasm comprising historical collections of crop species and their relatives offer a wealth of opportunities to find novel allelic variation in the key steps of photosynthesis, to identify new mechanisms and to accelerate genetic progress in crop breeding programmes. Here we explore the available genetic resources in food and fibre crops, strategies to selectively target allelic variation in genes underpinning key photosynthetic processes, and deployment of this variation via gene editing in modern elite material.

Phenotypic variation in photosynthetic traits in wheat grown under field versus glasshouse conditions.

Recognition of the untapped potential of photosynthesis to improve crop yields has spurred research to identify targets for breeding. The CO2-fixing enzyme Rubisco is characterized by a number of inefficiencies, and frequently limits carbon assimilation at the top of the canopy, representing a clear target for wheat improvement. Two bread wheat lines with similar genetic backgrounds and contrasting in vivo maximum carboxylation activity of Rubisco per unit leaf nitrogen (Vc,max,25/Narea) determined using high-throughput phenotyping methods were selected for detailed study from a panel of 80 spring wheat lines. Detailed phenotyping of photosynthetic traits in the two lines using glasshouse-grown plants showed no difference in Vc,max,25/Narea determined directly via in vivo and in vitro methods. Detailed phenotyping of glasshouse-grown plants of the 80 wheat lines also showed no correlation between photosynthetic traits measured via high-throughput phenotyping of field-grown plants. Our findings suggest that the complex interplay between traits determining crop productivity and the dynamic environments experienced by field-grown plants needs to be considered in designing strategies for effective wheat crop yield improvement when breeding for particular environments.

Dark respiration rates are not determined by differences in mitochondrial capacity, abundance and ultrastructure in C4 leaves.

Our understanding of the regulation of respiration in C4 plants, where mitochondria play different roles in the different types of C4 photosynthetic pathway, remains limited. We examined how leaf dark respiration rates (Rdark ), in the presence and absence of added malate, vary in monocots representing the three classical biochemical types of C4 photosynthesis (NADP-ME, NAD-ME and PCK) using intact leaves and extracted bundle sheath strands. In particular, we explored to what extent rates of Rdark are associated with mitochondrial number, volume and ultrastructure. Based on examination of a single species per C4 type, we found that the respiratory response of NAD-ME and PCK type bundle sheath strands to added malate was associated with differences in mitochondrial number, volume, and/or ultrastructure, while NADP-ME type bundle sheath strands did not respond to malate addition. In general, mitochondrial traits reflected the contributions mitochondria make to photosynthesis in the three C4 types. However, despite the obvious differences in mitochondrial traits, no clear correlation was observed between these traits and Rdark . We suggest that Rdark is primarily driven by cellular maintenance demands and not mitochondrial composition per se, in a manner that is somewhat independent of mitochondrial organic acid cycling in the light.

The crucial roles of mitochondria in supporting C4 photosynthesis.

C4 photosynthesis involves a series of biochemical and anatomical traits that significantly improve plant productivity under conditions that reduce the efficiency of C3 photosynthesis. We explore how evolution of the three classical biochemical types of C4 photosynthesis (NADP-ME, NAD-ME and PCK types) has affected the functions and properties of mitochondria. Mitochondria in C4 NAD-ME and PCK types play a direct role in decarboxylation of metabolites for C4 photosynthesis. Mitochondria in C4 PCK type also provide ATP for C4 metabolism, although this role for ATP provision is not seen in NAD-ME type. Such involvement has increased mitochondrial abundance/size and associated enzymatic capacity, led to changes in mitochondrial location and ultrastructure, and altered the role of mitochondria in cellular carbon metabolism in the NAD-ME and PCK types. By contrast, these changes in mitochondrial properties are absent in the C4 NADP-ME type and C3 leaves, where mitochondria play no direct role in photosynthesis. From an eco-physiological perspective, rates of leaf respiration in darkness vary considerably among C4 species but does not differ systematically among the three C4 types. This review outlines further mitochondrial research in key areas central to the engineering of the C4 pathway into C3 plants and to the understanding of variation in rates of C4 dark respiration.

Elucidating the role of SWEET13 in phloem loading of the C4 grass Setaria viridis.

Photosynthetic efficiency and sink demand are tightly correlated with rates of phloem loading, where maintaining low cytosolic sugar concentrations is paramount to prevent the downregulation of photosynthesis. Sugars Will Eventually be Exported Transporters (SWEETs) are thought to have a pivotal role in the apoplastic phloem loading of C4 grasses. SWEETs have not been well studied in C4 species, and their investigation is complicated by photosynthesis taking place across two cell types and, therefore, photoassimilate export can occur from either one. SWEET13 homologues in C4 grasses have been proposed to facilitate apoplastic phloem loading. Here, we provide evidence for this hypothesis using the C4 grass Setaria viridis. Expression analyses on the leaf gradient of C4 species Setaria and Sorghum bicolor show abundant transcript levels for SWEET13 homologues. Carbohydrate profiling along the Setaria leaf shows total sugar content to be significantly higher in the mature leaf tip compared with the younger tissue at the base. We present the first known immunolocalization results for SvSWEET13a and SvSWEET13b using novel isoform-specific antisera. These results show localization to the bundle sheath and phloem parenchyma cells of both minor and major veins. We further present the first transport kinetics study of C4 monocot SWEETs by using a Xenopus laevis oocyte heterologous expression system. We demonstrate that SvSWEET13a and SvSWEET13b are high-capacity transporters of glucose and sucrose, with a higher apparent Vmax for sucrose, compared with glucose, typical of clade III SWEETs. Collectively, these results provide evidence for an apoplastic phloem loading pathway in Setaria and possibly other C4 species.

Expression of a CO2-permeable aquaporin enhances mesophyll conductance in the C4 species Setaria viridis.

A fundamental limitation of photosynthetic carbon fixation is the availability of CO2. In C4 plants, primary carboxylation occurs in mesophyll cytosol, and little is known about the role of CO2 diffusion in facilitating C4 photosynthesis. We have examined the expression, localization, and functional role of selected plasma membrane intrinsic aquaporins (PIPs) from Setaria italica (foxtail millet) and discovered that SiPIP2;7 is CO2-permeable. When ectopically expressed in mesophyll cells of Setaria viridis (green foxtail), SiPIP2;7 was localized to the plasma membrane and caused no marked changes in leaf biochemistry. Gas exchange and C18O16O discrimination measurements revealed that targeted expression of SiPIP2;7 enhanced the conductance to CO2 diffusion from the intercellular airspace to the mesophyll cytosol. Our results demonstrate that mesophyll conductance limits C4 photosynthesis at low pCO2 and that SiPIP2;7 is a functional CO2 permeable aquaporin that can improve CO2 diffusion at the airspace/mesophyll interface and enhance C4 photosynthesis.

Explainable machine learning models of major crop traits from satellite-monitored continent-wide field trial data.

Four species of grass generate half of all human-consumed calories. However, abundant biological data on species that produce our food remain largely inaccessible, imposing direct barriers to understanding crop yield and fitness traits. Here, we assemble and analyse a continent-wide database of field experiments spanning 10 years and hundreds of thousands of machine-phenotyped populations of ten major crop species. Training an ensemble of machine learning models, using thousands of variables capturing weather, ground sensor, soil, chemical and fertilizer dosage, management and satellite data, produces robust cross-continent yield models exceeding R2 = 0.8 prediction accuracy. In contrast to 'black box' analytics, detailed interrogation of these models reveals drivers of crop behaviour and complex interactions predicting yield and agronomic traits. These results demonstrate the capacity of machine learning models to interrogate large datasets, generate new and testable outputs and predict crop behaviour, highlighting the powerful role of data in the future of food.

Wheat physiology predictor: predicting physiological traits in wheat from hyperspectral reflectance measurements using deep learning.

BACKGROUND: The need for rapid in-field measurement of key traits contributing to yield over many thousands of genotypes is a major roadblock in crop breeding. Recently, leaf hyperspectral reflectance data has been used to train machine learning models using partial least squares regression (PLSR) to rapidly predict genetic variation in photosynthetic and leaf traits across wheat populations, among other species. However, the application of published PLSR spectral models is limited by a fixed spectral wavelength range as input and the requirement of separate custom-built models for each trait and wavelength range. In addition, the use of reflectance spectra from the short-wave infrared region requires expensive multiple detector spectrometers. The ability to train a model that can accommodate input from different spectral ranges would potentially make such models extensible to more affordable sensors. Here we compare the accuracy of prediction of PLSR with various deep learning approaches and an ensemble model, each trained and tested using previously published data sets. RESULTS: We demonstrate that the accuracy of PLSR to predict photosynthetic and related leaf traits in wheat can be improved with deep learning-based and ensemble models without overfitting. Additionally, these models can be flexibly applied across spectral ranges without significantly compromising accuracy. CONCLUSION: The method reported provides an improved prediction of wheat leaf and photosynthetic traits from leaf hyperspectral reflectance and do not require a full range, high cost leaf spectrometer. We provide a web service for deploying these algorithms to predict physiological traits in wheat from a variety of spectral data sets, with important implications for wheat yield prediction and crop breeding.