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Beyond Arabidopsis: BBX Regulators in Crop Plants.

ABSTRACT: B-box proteins represent diverse zinc finger transcription factors and regulators forming large families in various plants. A unique domain structure defines them-besides the highly conserved B-box domains, some B-box (BBX) proteins also possess CCT domain and VP motif. Based on the presence of these specific domains, they are mostly classified into five structural groups. The particular members widely differ in structure and fulfill distinct functions in regulating plant growth and development, including seedling photomorphogenesis, the anthocyanins biosynthesis, photoperiodic regulation of flowering, and hormonal pathways. Several BBX proteins are additionally involved in biotic and abiotic stress response. Overexpression of some BBX genes stimulates various stress-related genes and enhanced tolerance to different stresses. Moreover, there is evidence of interplay between B-box and the circadian clock mechanism. This review highlights the role of BBX proteins as a part of a broad regulatory network in crop plants, considering their participation in development, physiology, defense, and environmental constraints. A description is also provided of how various BBX regulators involved in stress tolerance were applied in genetic engineering to obtain stress tolerance in transgenic crops.

SUBMITTER: Talar U

PROVIDER: S-EPMC7999331 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Plant modeling can provide a more detailed overview regarding the basis of plant development throughout the life cycle. Three-dimensional processing algorithms are rapidly expanding in plant phenotyping programmes and in decision-making for agronomic management. Several methods have already been tested, but for practical implementations the trade-off between equipment cost, computational resources needed and the fidelity and accuracy in the reconstruction of the end-details needs to be assessed and quantified. This study examined the suitability of two low-cost systems for plant reconstruction. A low-cost Structure from Motion (SfM) technique was used to create 3D models for plant crop reconstruction. In the second method, an acquisition and reconstruction algorithm using an RGB-Depth Kinect v2 sensor was tested following a similar image acquisition procedure. The information was processed to create a dense point cloud, which allowed the creation of a 3D-polygon mesh representing every scanned plant. The selected crop plants corresponded to three different crops (maize, sugar beet and sunflower) that have structural and biological differences. The parameters measured from the model were validated with ground truth data of plant height, leaf area index and plant dry biomass using regression methods. The results showed strong consistency with good correlations between the calculated values in the models and the ground truth information. Although, the values obtained were always accurately estimated, differences between the methods and among the crops were found. The SfM method showed a slightly better result with regard to the reconstruction the end-details and the accuracy of the height estimation. Although the use of the processing algorithm is relatively fast, the use of RGB-D information is faster during the creation of the 3D models. Thus, both methods demonstrated robust results and provided great potential for use in both for indoor and outdoor scenarios. Consequently, these low-cost systems for 3D modeling are suitable for several situations where there is a need for model generation and also provide a favourable time-cost relationship.

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Beyond Arabidopsis: BBX Regulators in Crop Plants.

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