In silico study of the role of cell growth factors in photosynthesis using a virtual leaf tissue generator coupled to a microscale photosynthesis gas exchange model

Defining the scope for altering rice leaf anatomy to improve photosynthesis: a modelling approach

Leaf structure plays an important role in photosynthesis. However, the causal relationship and the quantitative importance of any single structural parameter to the overall photosynthetic performance of a leaf remains open to debate. In this paper, we report on a mechanistic model, eLeaf, which successfully captures rice leaf photosynthetic performance under varying environmental conditions of light and CO₂ . We developed a 3D reaction-diffusion model for leaf photosynthesis parameterised using a range of imaging data and biochemical measurements from plants grown under ambient and elevated CO₂ and then interrogated the model to quantify the importance of these elements. The model successfully captured leaf-level photosynthetic performance in rice. Photosynthetic metabolism underpinned the majority of the increased carbon assimilation rate observed under elevated CO₂ levels, with a range of structural elements making positive and negative contributions. Mesophyll porosity could be varied without any major outcome on photosynthetic performance, providing a theoretical underpinning for experimental data. eLeaf allows quantitative analysis of the influence of morphological and biochemical properties on leaf photosynthesis. The analysis highlights a degree of leaf structural plasticity with respect to photosynthesis of significance in the context of attempts to improve crop photosynthesis.

CropPainter: an effective and precise tool for trait-to-image crop visualization based on generative adversarial networks

BACKGROUND

Virtual plants can simulate the plant growth and development process through computer modeling, which assists in revealing plant growth and development patterns. Virtual plant visualization technology is a core part of virtual plant research. The major limitation of the existing plant growth visualization models is that the produced virtual plants are not realistic and cannot clearly reflect plant color, morphology and texture information.

RESULTS

This study proposed a novel trait-to-image crop visualization tool named CropPainter, which introduces a generative adversarial network to generate virtual crop images corresponding to the given phenotypic information. CropPainter was first tested for virtual rice panicle generation as an example of virtual crop generation at the organ level. Subsequently, CropPainter was extended for visualizing crop plants (at the plant level), including rice, maize and cotton plants. The tests showed that the virtual crops produced by CropPainter are very realistic and highly consistent with the input phenotypic traits. The codes, datasets and CropPainter visualization software are available online.

CONCLUSION

In conclusion, our method provides a completely novel idea for crop visualization and may serve as a tool for virtual crops, which can assist in plant growth and development research.

Potassium availability influences the mesophyll structure to coordinate the conductance of CO2 and H2 O during leaf expansion

Leaf growth relies on photosynthesis and hydraulics to provide carbohydrates and expansion power; in turn, leaves intercept light and construct organism systems for functioning. Under potassium (K) deficiency stress, leaf area, photosynthesis and hydraulics are all affected by alterations in leaf structure. However, the connection between changes in leaf growth and function caused by the structure under K regulation is unclear. Consequently, the leaf hydraulic conductance (K_leaf ) and photosynthetic rate (A) combined with leaf anatomical characteristics of Brassica napus were continuously observed during leaf growth under different K supply levels. The results showed that K_leaf and A decreased simultaneously after leaf area with the increasing K deficiency stress. K deficiency significantly increased longitudinal mesophyll cell investment, leading to a reduced volume fraction of intercellular air-space (f_ias ) and decreased leaf expansion rate. Furthermore, reduced f_ias decreased mesophyll and chloroplast surfaces exposed to intercellular airspace and gas phase H₂ O transport, which induced coordinated changes in CO₂ mesophyll conductance and hydraulic conductance in extra-xylem pathways. Adequate K supply facilitated higher f_ias through smaller palisade tissue cell density (loose mesophyll cell arrangement) and smaller spongy tissue cell size, which coordinated CO₂ and H₂ O conductance and promoted leaf area expansion.

A Sight on Single-Cell Transcriptomics in Plants Through the Prism of Cell-Based Computational Modeling Approaches: Benefits and Challenges for Data Analysis

Single-cell technology is a relatively new and promising way to obtain high-resolution transcriptomic data mostly used for animals during the last decade. However, several scientific groups developed and applied the protocols for some plant tissues. Together with deeply-developed cell-resolution imaging techniques, this achievement opens up new horizons for studying the complex mechanisms of plant tissue architecture formation. While the opportunities for integrating data from transcriptomic to morphogenetic levels in a unified system still present several difficulties, plant tissues have some additional peculiarities. One of the plants' features is that cell-to-cell communication topology through plasmodesmata forms during tissue growth and morphogenesis and results in mutual regulation of expression between neighboring cells affecting internal processes and cell domain development. Undoubtedly, we must take this fact into account when analyzing single-cell transcriptomic data. Cell-based computational modeling approaches successfully used in plant morphogenesis studies promise to be an efficient way to summarize such novel multiscale data. The inverse problem's solutions for these models computed on the real tissue templates can shed light on the restoration of individual cells' spatial localization in the initial plant organ-one of the most ambiguous and challenging stages in single-cell transcriptomic data analysis. This review summarizes new opportunities for advanced plant morphogenesis models, which become possible thanks to single-cell transcriptome data. Besides, we show the prospects of microscopy and cell-resolution imaging techniques to solve several spatial problems in single-cell transcriptomic data analysis and enhance the hybrid modeling framework opportunities.

Variability in the chloroplast area lining the intercellular airspace and cell walls drives mesophyll conductance in gymnosperms

The photosynthetic efficiency of plants in different environments is controlled by stomata, hydraulics, biochemistry, and mesophyll conductance (gm). Recently, gm was demonstrated to be the key limitation of photosynthesis in gymnosperms. Values of gm across gymnosperms varied over 20-fold, but this variation was poorly explained by robust structure-bound integrated traits such as leaf dry mass per area. Understanding how the component structural traits control gm is central for identifying the determinants of variability in gm across plant functional and phylogenetic groups. Here, we investigated the structural traits responsible for gm in 65 diverse gymnosperms. Although the integrated morphological traits, shape, and anatomical characteristics varied widely across species, the distinguishing features of all gymnosperms were thick mesophyll cell walls and low chloroplast area exposed to intercellular airspace (Sc/S) compared with angiosperms. Sc/S and cell wall thickness were the fundamental traits driving variations in gm across gymnosperm species. Chloroplast thickness was the strongest limitation of gm among liquid-phase components. The variation in leaf dry mass per area was not correlated with the key ultrastructural traits determining gm. Thus, given the absence of correlating integrated easy-to-measure traits, detailed knowledge of underlying component traits controlling gm across plant taxa is necessary to understand the photosynthetic limitations across ecosystems.