The antioxidant system (AOS) maintains the optimal concentration of reactive oxygen species (ROS) in a cell and protects it against oxidative stress. In plants, the AOS consists of seven main classes of antioxidant enzymes, low-molecular antioxidants (e.g., ascorbate, glutathione, and their oxidized forms) and thioredoxin/glutaredoxin systems which can serve as reducing agents for antioxidant enzymes. The number of genes encoding AOS enzymes varies between classes, and same class enzymes encoded by different gene copies may have different subcellular localizations, functional loads and modes of evolution. These facts hereafter reinforce the complex nature of AOS regulation and functioning. Further studies can describe new trends in the behavior and functioning of systems components, and provide new fundamental knowledge about systems regulation. The system is revealed to have a lot of interactions and interplay pathways between its components at the subcellular level (antioxidants, enzymes, ROS level, and hormonal and transcriptional regulation). These facts should be taken into account in further studies during the AOS modeling by describing the main pathways of generating and utilizing ROS, as well as the associated signaling processes and regulation of the system on cellular and organelle levels, which is a complicated and ambitious task. Another objective for studying the phenomenon of the AOS is related to the influence of cell dynamics and circadian rhythms on it. Therefore, the AOS requires an integrated and multi-level approach to study. We focused this review on the existing scientific background and experimental data used for the systems biology research of the plant AOS.

The availability and intensity of sunlight are among the major factors of growth, development and metabolism in plants. However, excessive illumination disrupts the electronic balance of photosystems and leads to the accumulation of reactive oxygen species in chloroplasts, further mediating several regulatory mechanisms at the subcellular, genetic, and molecular levels. We carried out a comprehensive bioinformatic analysis that aimed to identify genetic systems and candidate transcription factors involved in the response to high light stress in Arabidopsis thaliana L. using resources GEO NCBI, string-db, ShinyGO, STREME, and Tomtom, as well as programs metaRE, CisCross, and Cytoscape. Through the meta-analysis of five transcriptomic experiments, we selected a set of 1151 differentially expressed genes, including 453 genes that compose the gene network. Ten significantly enriched regulatory motifs for TFs families ZF-HD, HB, C2H2, NAC, BZR, and ARID were found in the promoter regions of differentially expressed genes. In addition, we predicted families of transcription factors associated with the duration of exposure (RAV, HSF), intensity of high light treatment (MYB, REM), and the direction of gene expression change (HSF, S1Fa-like). We predicted genetic components systems involved in a high light response and their expression changes, potential transcriptional regulators, and associated processes.

Background: Plant cell metabolism inevitably forms reactive oxygen species (ROS), which can damage cells or lead to their death. The antioxidant system (AOS) evolved to eliminate a high concentration of ROS. For plants, this system consists of the seven classes of antioxidant enzymes and antioxidant compounds. Each enzymatic class contains a various number of genes which may vary from species to species. In such a multi-copy genetic system, the integration of evolutionary characteristics and expression data makes it possible to effectively predict promising breeding targets for the design of highly-yielding cultivars. In the plant cells, ROS production can increase as a result of abiotic stresses. Accordingly, AOS responds to stress by altering the expression of the genes of its components. Expression profiles of AOS enzymes, including their changes under stress, remains incomplete. A comprehensive study of the system behavior in response to stress for different species gives the key to identify the general mechanisms of AOS regulation. In this article, we studied stress-induced changes in the expression of AOS genes in photosynthetic tissues for rice and bread wheat. Methods: A meta-analysis of genome-wide transcriptome data on stress-induced changes in expression profiles of antioxidant genes using microarray and next generation sequencing (NGS) experiments from the GEO NCBI database for rice and bread wheat was carried out. Experimental study of expression changes in short (6 h) and prolonged (24 h) cold stress responses for selected AOS genes of bread wheat cultivars Saratovskaya29 and Yanetzkis Probat was conducted using qPCR. Results: The large-scale meta-transcriptome and complementary experimental analysis revealed a summary of fold changes in the AOS gene expression in response to cold and water deficiency for rice and bread wheat.

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.

Bread wheat (Triticum aestivum L.) is one of the most important agricultural plants wearing abiotic stresses, such as water deficit and cold, that cause its productivity reduction. Since resistance to abiotic factors is a multigenic trait, therefore modern genome-wide approaches can help to involve various genetic material in breeding. One technique is full transcriptome analysis that reveals groups of stress response genes serving marker-assisted selection markers. Comparing transcriptome profiles of the same genetic material under several stresses is essential and makes the whole picture. Here, we addressed this by studying the transcriptomic response to water deficit and cold stress for two evolutionarily distant bread wheat varieties: stress-resistant cv. Saratovskaya 29 (S29) and stress-sensitive cv. Yanetzkis Probat (YP). For the first time, transcriptomes for these cultivars grown under abiotic stress conditions were obtained using Illumina based MACE technology. We identified groups of genes involved in response to cold and water deficiency stresses, including responses to each stress factor and both factors simultaneously that may be candidates for resistance genes. We discovered a core group of genes that have a similar pattern of stress-induced expression changes. The particular expression pattern was revealed not only for the studied varieties but also for the published transcriptomic data on cv. Jing 411 and cv. Fielder. Comparative transcriptome profiling of cv. S29 and cv. YP in response to water deficit and cold stress confirmed the hypothesis that stress-induced expression change is unequal within a homeologous gene group. As a rule, at least one changed significantly while the others had a relatively lower expression. Also, we found several SNPs distributed throughout the genomes of cv. S29 and cv. YP and distinguished the studied varieties from each other and the reference cv. Chinese Spring. Our results provide new data for genomics-assisted breeding of stress-tolerant wheat cultivars.

Microscopic images are widely used in plant biology as an essential source of information on morphometric characteristics of the cells and the topological characteristics of cellular tissue pattern due to modern computer vision algorithms. High-resolution 3D confocal images allow extracting quantitative characteristics describing the cell structure of leaf epidermis. For some issues in the study of cereal leaves development, it is required to apply the staining techniques with fluorescent dyes and to scan rather large fragments consisting of several frames. We aimed to develop a tool for processing multi-frame multi-channel 3D images obtained from confocal laser scanning microscopy and taking into account the peculiarities of the cereal leaves staining. We elaborated an ImageJ-plugin LSM-W2 that allows extracting data on Leaf Surface Morphology from Laser Scanning Microscopy images. The plugin is a crucial link in a workflow for obtaining data on structural properties of leaf epidermis and morphological properties of epidermal cells. It allows converting large lsm-files (laser scanning microscopy) into segmented 2D/3D images or tables with data on cells and/or nuclei sizes. In the article, we also represent some case studies showing the plugin application for solving biological tasks. Namely the plugin is applied in the following cases: defining parameters of jigsaw-puzzle pattern for maize leaf epidermal cells, analysis of the pavement cells morphological parameters for the mature wheat leaf grown under control and water deficit conditions, initiation of cell longitudinal rows, and detection of guard mother cells emergence at the initial stages of the stomatal morphogenesis in the growth zone of a wheat leaf. The proposed plugin is efficient for high-throughput analysis of cellular architecture for cereal leaf epidermis. The workflow implies using inexpensive and rapid sample preparation and does not require the applying of transgenesis and reporter genetic structures expanding the range of species and varieties to study. Obtained characteristics of the cell structure and patterns further could act as a basis for the development and verification for spatial models of plant tissues formation mechanisms accounting for structural features of cereal leaves. The implementation of this workflow is available as an ImageJ plugin distributed as a part of the Fiji project (FijiisjustImageJ: https://fiji.sc/ ). The plugin is freely available at https://imagej.net/LSM_Worker , https://github.com/JmanJ/LSM_Worker and http://pixie.bionet.nsc.ru/LSM_WORKER/ .