Journal of Experimental Botany最新文献

Plant physiology and metabolism rely on the function of stomata, structures on the surface of above-ground organs that facilitate the exchange of gases with the atmosphere. The morphology of the guard cells and corresponding pore that make up the stomata, as well as the density (number per unit area), are critical in determining overall gas exchange capacity. These characteristics can be quantified visually from images captured using microscopy, traditionally relying on time-consuming manual analysis. However, deep learning (DL) models provide a promising route to increase the throughput and accuracy of plant phenotyping tasks, including stomatal analysis. Here we review the published literature on the application of DL for stomatal analysis. We discuss the variation in pipelines used, from data acquisition, pre-processing, DL architecture, and output evaluation to post-processing. We introduce the most common network structures, the plant species that have been studied, and the measurements that have been performed. Through this review, we hope to promote the use of DL methods for plant phenotyping tasks and highlight future requirements to optimize uptake, predominantly focusing on the sharing of datasets and generalization of models as well as the caveats associated with utilizing image data to infer physiological function.

Enhancing crop water use efficiency (WUE) is a key target trait for climatic resilience and expanding cultivation on marginal lands. Engineering lower stomatal density to reduce stomatal conductance (gs) has improved WUE in multiple C3 crop species. However, reducing gs in C3 species often reduces photosynthetic carbon gain. A different response is expected in C4 plants because they possess specialized anatomy and biochemistry which concentrates CO2 at the site of fixation. This modifies the relationship of photosynthesis (AN) with intracellular CO2 concentration (ci), such that photosynthesis is CO2 saturated and reductions in gs are unlikely to limit AN. To test this hypothesis, genetic strategies were investigated to reduce stomatal density in the C4 crop sorghum. Constitutive expression of a synthetic epidermal patterning factor (EPF) transgenic allele in sorghum led to reduced stomatal densities, reduced gs, reduced plant water use, and avoidance of stress during a period of water deprivation. In addition, moderate reduction in stomatal density did not increase stomatal limitation to AN. However, these positive outcomes were associated with negative pleiotropic effects on reproductive development and photosynthetic capacity. Avoiding pleiotropy by targeting expression of the transgene to specific tissues could provide a pathway to improved agronomic outcomes.

Cause-and-effect arrows are drawn from genotype (G), environment (E), and agronomic management (M) to the plant phenotype in crop stands in a useful but incomplete framework that informs research questions, experimental design, statistical analysis, data interpretation, modelling, and breeding and agronomic applications. Here we focus on the overlooked bidirectionality of these arrows. The phenotype-to-genotype arrow includes increased mutation rates in stressed phenotypes, relative to basal rates. From a developmental viewpoint, the phenotype modulates gene expression returning multiple cellular phenotypes with a common genome. The phenotype-to-environment arrow is captured in the process of niche construction, which spans from persistent and global to transient and local. Research on crop rotations recognises the influence of the phenotype on the environment but is divorced of niche construction theory. The phenotype-to-management arrow involves, for example, a diseased crop that may trigger fungicide treatment. Making explicit the bidirectionality of the arrows in the G × E × M framework contributes to narrowing the gap between data-driven technologies and integrative theory and is an invitation to cautiously think of the internal teleonomy of plants in contrast to the view of the phenotype as the passive end of the arrows in the current framework.

The ratio of net CO2 uptake (Anet) and stomatal conductance (gs) is an intrinsic measurement of leaf water use efficiency (WUEi); however, its measurement can be challenging for large phenotypic screens. Measurements of the leaf carbon isotope composition (δ13Cleaf) may be a scalable tool to approximate WUEi for screening because it in part reflects the competing influences of Anet and gs on the CO2 partial pressure (pCO2) inside the leaf over time. However, in C4 photosynthesis, the CO2-concentrating mechanism complicates the relationship between δ13Cleaf and WUEi. Despite this complicated relationship, several studies have shown genetic variation in δ13Cleaf across C4 plants. Yet there has not been a clear demonstration of if Anet or gs are the causal mechanisms controlling WUEi and δ13Cleaf. Our approach was to characterize leaf photosynthetic traits of two Zea mays recombinant inbred lines (Z007E0067 and Z007E0150) which consistently differ for δ13Cleaf even though they have minimal confounding genetic differences. We demonstrate that these two genotypes contrasted in WUEi driven by differences in the speed of stomatal responses to changes in pCO2 and light that lead to unproductive leaf water loss. These findings provide support that differences in δ13Cleaf in closely related genotypes do reflect greater WUEi and further suggest that differences in stomatal kinetic response to changing environmental conditions is a key target to improve WUEi.

Stomata regulate CO2 and water vapor exchange between leaves and the atmosphere. Stomata are a target for engineering to improve crop intrinsic water use efficiency (iWUE). One example is by expressing genes that lower stomatal density (SD) and reduce stomatal conductance (gsw). However, the quantitative relationship between reduced SD, gsw, and the mechanisms underlying it is poorly understood. We addressed this knowledge gap using low-SD sugarcane (Saccharum spp. hybrid) as a case study alongside a meta-analysis of data from 10 species. Transgenic expression of EPIDERMAL PATTERNING FACTOR 2 from Sorghum bicolor (SbEPF2) in sugarcane reduced SD by 26-38% but did not affect gsw compared with the wild type. Further, no changes occurred in stomatal complex size or proxies for photosynthetic capacity. Measurements of gas exchange at low CO2 concentrations that promote complete stomatal opening to normalize aperture size between genotypes were combined with modeling of maximum gsw from anatomical data. These data suggest that increased stomatal aperture is the only possible explanation for maintaining gsw when SD is reduced. Meta-analysis across C3 dicots, C3 monocots, and C4 monocots revealed that engineered reductions in SD are strongly correlated with lower gsw (r2=0.60-0.98), but this response is damped relative to the change in anatomy.

Recent research has shown that optimizing photosynthetic and stomatal traits holds promise for improved crop performance. However, standard phenotyping tools such as gas exchange systems have limited throughput. In this work, a novel approach based on a bespoke gas exchange chamber allowing combined measurement of the quantum yield of PSII (Fq'/Fm'), with an estimation of stomatal conductance via thermal imaging was used to phenotype a range of bread wheat (Triticum aestivum L.) genotypes. Using the dual-imaging methods and traditional approaches, we found broad and significant variation in key traits, including photosynthetic CO2 uptake at saturating light and ambient CO2 concentration (Asat), photosynthetic CO2 uptake at saturating light and elevated CO2 concentration (Amax), the maximum velocity of Rubisco for carboxylation (Vcmax), time for stomatal opening (Ki), and leaf evaporative cooling. Anatomical analysis revealed significant variation in flag leaf adaxial stomatal density. Associations between traits highlighted significant relationships between leaf evaporative cooling, leaf stomatal conductance, and Fq'/Fm', highlighting the importance of stomatal conductance and stomatal rapidity in maintaining optimal leaf temperature for photosynthesis in wheat. Additionally, gsmin and gsmax were positively associated, indicating that potential combinations of preferable traits (i.e. inherently high gsmax, low Ki, and maintained leaf evaporative cooling) are present in wheat. This work highlights the effectiveness of thermal imaging in screening dynamic gs in a panel of wheat genotypes. The wide phenotypic variation observed suggested the presence of exploitable genetic variability in bread wheat for dynamic stomatal conductance traits and photosynthetic capacity for targeted optimization within future breeding programmes.

Plants adapt to balance growth-defense tradeoffs in response to both biotic and abiotic stresses. Green leaf volatiles (GLVs) are released after biotic and abiotic stresses and function as damage-associated signals in plants. Although, GLVs enter plants primarily through stomata, the role of stomatal regulation on the kinetics of GLV uptake remains largely unknown. Here, we illustrate the effect of stomatal closure on the timing and magnitude of GLV uptake. We closed stomata by either exposing maize (Zea mays) plants to darkness or applying abscisic acid, a phytohormone that closes the stomata in light. Then, we exposed maize seedlings to (Z)-3-hexen-1-ol and compared its dynamic uptake under different stomatal conditions. Additionally, we used (E)-3-hexen-1-ol, an isomer of (Z)-3-hexen-1-ol not made by maize, to exclude the role of internal GLVs in our assays. We demonstrate that closed stomata effectively prevent GLV entry into exposed plants, even at high concentrations. Furthermore, our findings indicate that reduced GLV uptake impairs GLV-driven induction of biosynthesis of sesquiterpenes, a group of GLV-inducible secondary metabolites, with or without herbivory. These results elucidate how stomata regulate the perception of GLV signals, thereby dramatically changing the plant responses to herbivory, particularly under water stress or dark conditions.

The stomatal response to red light appears to link stomatal conductance (gs) with photosynthetic rates. Initially, it was suggested that changes in intercellular CO2 concentration (Ci) provide the main cue via a Ci-dependent response. However, evidence for Ci-independent mechanisms suggests an additional, more direct relationship with photosynthesis. While both Ci-dependent and -independent mechanisms clearly function in stomatal red light responses, little is known regarding their relative contribution. The present study aimed to quantify the relative magnitude of Ci-dependent and -independent mechanisms on the stomatal red light response, to characterize their interplay and to assess the putative link between plastoquinone redox state and Ci-independent stomatal responses. Red light response curves measured at a range of Ci values for wild-type Arabidopsis (Col-0) and the CO2 hyposensitive mutant ca1ca4 allowed deconvolution of Ci-dependent and -independent pathways. Surprisingly, we observed that both mechanisms contribute equally to stomatal red light responses, but Ci-independent stomatal opening is suppressed at high Ci. The present data are also consistent with the involvement of the plastoquinone redox state in coordinating the Ci-independent component. Overall, it seems that while Ci-independent mechanisms are distinct from responses to Ci, interplay between these two pathways is important to facilitate effective coordination between gs and photosynthesis.

Plants have developed complex mechanisms to perceive, transduce, and respond to environmental signals, such as light, which are essential for acquiring and allocating resources, including nitrogen (N). This review delves into the complex interaction between light signals and N metabolism, emphasising light-mediated regulation of N uptake and assimilation. Firstly, we discuss the details of light-mediated regulation of N uptake and assimilation, focusing on the light-responsive activity of nitrate reductase (NR) and nitrate transporters. Secondly, we discuss the influence of light on N-dependent developmental plasticity, elucidating how N availability regulates crucial developmental transitions such as flowering time, shoot branching, and root growth, as well as how light modulates these processes. Additionally, we discuss the molecular interaction between light and N signalling, focusing on photoreceptors and transcription factors such as HY5, which are necessary for N uptake and assimilation under varying light conditions. A recent understanding of the nitrate signalling and perception of low N is also highlighted. The insilico transcriptome analysis suggests a reprogramming of N signalling genes by shade and identifies NLP7, bZIP1, CPK30, CBL1, LBD37, LBD38 and HRS1 as crucial molecular regulators integrating light-regulated N metabolism.