Watermelon(Citrullus lanatus) is sensitive to salt stress. For breeding applications, it is of great significance to explore the genetic mechanism underlying salt tolerance in watermelon by analyzing the dehydration r...Watermelon(Citrullus lanatus) is sensitive to salt stress. For breeding applications, it is of great significance to explore the genetic mechanism underlying salt tolerance in watermelon by analyzing the dehydration responsive element-binding(DREB) factor family members.However, they are rarely studied in watermelon. In this study, we identified ClaDREB gene family members in watermelon based on whole genome data;analyzed the physicochemical properties, evolution, and phylogeny;and studied their expression patterns under salt stress in two watermelon varieties with varying salt tolerance. In total, 57 DREB family members were identified in watermelon, and most of them were located in the nucleus. ClaDREBs were divided into six subgroups Ⅰ-Ⅵ. The promoter region of ClaDREBs from subgroup Ⅱ contained many defense-related and stress responsive elements. Among them, ClaDREB14 was significantly upregulated by salt stress and exhibited differential expression in salt-tolerant and salt-sensitive varieties. Moreover, overexpression of ClaDREB14 in watermelon roots significantly improved the salt tolerance of transgenic plants;mainly, it significantly increased the activities of POD, SOD, and CAT and significantly reduced MDA content.However, the results from gene-edited watermelon roots obtained using CRISPR/Cas9 vectors showed the opposite trend. Furthermore, we demonstrated that ClaDREB14 directly binds to the cis-acting element ACCGAC in the promoter region of ClaPOD6 and promotes its expression.Therefore, ClaDREB14 may enhance salt tolerance by increasing the activity of antioxidant enzymes in watermelon roots. This study provided valuable information on the DREB gene family in watermelon and laid the foundation for future functional validation and genetic engineering applications.展开更多
Nondestructive measurement technology of phenotype can provide substantial phenotypic data support for applications such as seedling breeding,management,and quality testing.The current method of measuring seedling phe...Nondestructive measurement technology of phenotype can provide substantial phenotypic data support for applications such as seedling breeding,management,and quality testing.The current method of measuring seedling phenotypes mainly relies on manual measurement which is inefficient,subjective and destroys samples.Therefore,the paper proposes a nondestructive measurement method for the canopy phenotype of the watermelon plug seedlings based on deep learning.The Azure Kinect was used to shoot canopy color images,depth images,and RGB-D images of the watermelon plug seedlings.The Mask-RCNN network was used to classify,segment,and count the canopy leaves of the watermelon plug seedlings.To reduce the error of leaf area measurement caused by mutual occlusion of leaves,the leaves were repaired by CycleGAN,and the depth images were restored by image processing.Then,the Delaunay triangulation was adopted to measure the leaf area in the leaf point cloud.The YOLOX target detection network was used to identify the growing point position of each seedling on the plug tray.Then the depth differences between the growing point and the upper surface of the plug tray were calculated to obtain plant height.The experiment results show that the nondestructive measurement algorithm proposed in this paper achieves good measurement performance for the watermelon plug seedlings from the 1 true-leaf to 3 true-leaf stages.The average relative error of measurement is 2.33%for the number of true leaves,4.59%for the number of cotyledons,8.37%for the leaf area,and 3.27%for the plant height.The experiment results demonstrate that the proposed algorithm in this paper provides an effective solution for the nondestructive measurement of the canopy phenotype of the plug seedlings.展开更多
基金funded by grants fromthe China Agriculture Research System of MOF and MARA(CARS-25)the Key Research and Development Program of Xinjiang Uygur autonomous region(Grant No.2023B02017)+3 种基金the Agricultural Science and Technology Innovation Program(CAAS-ASTIP-2021-ZFRI,CAAS-ASTIP-2024-WRI)the Basic Research Funds of Chinese Academy of Agricultural Sciences(Grant No.1610192023201)Natural Science Foundation of Henan Province(Grant No.252300421694)Joint Research on Agricultural Variety Improvement of Henan Province(Grant No.2022010503).
文摘Watermelon(Citrullus lanatus) is sensitive to salt stress. For breeding applications, it is of great significance to explore the genetic mechanism underlying salt tolerance in watermelon by analyzing the dehydration responsive element-binding(DREB) factor family members.However, they are rarely studied in watermelon. In this study, we identified ClaDREB gene family members in watermelon based on whole genome data;analyzed the physicochemical properties, evolution, and phylogeny;and studied their expression patterns under salt stress in two watermelon varieties with varying salt tolerance. In total, 57 DREB family members were identified in watermelon, and most of them were located in the nucleus. ClaDREBs were divided into six subgroups Ⅰ-Ⅵ. The promoter region of ClaDREBs from subgroup Ⅱ contained many defense-related and stress responsive elements. Among them, ClaDREB14 was significantly upregulated by salt stress and exhibited differential expression in salt-tolerant and salt-sensitive varieties. Moreover, overexpression of ClaDREB14 in watermelon roots significantly improved the salt tolerance of transgenic plants;mainly, it significantly increased the activities of POD, SOD, and CAT and significantly reduced MDA content.However, the results from gene-edited watermelon roots obtained using CRISPR/Cas9 vectors showed the opposite trend. Furthermore, we demonstrated that ClaDREB14 directly binds to the cis-acting element ACCGAC in the promoter region of ClaPOD6 and promotes its expression.Therefore, ClaDREB14 may enhance salt tolerance by increasing the activity of antioxidant enzymes in watermelon roots. This study provided valuable information on the DREB gene family in watermelon and laid the foundation for future functional validation and genetic engineering applications.
基金funded by the National Key Research and Development Program of China(Grant No.2019YFD1001900)the HZAU-AGIS Cooperation Fund(Grant No.SZYJY2022006).
文摘Nondestructive measurement technology of phenotype can provide substantial phenotypic data support for applications such as seedling breeding,management,and quality testing.The current method of measuring seedling phenotypes mainly relies on manual measurement which is inefficient,subjective and destroys samples.Therefore,the paper proposes a nondestructive measurement method for the canopy phenotype of the watermelon plug seedlings based on deep learning.The Azure Kinect was used to shoot canopy color images,depth images,and RGB-D images of the watermelon plug seedlings.The Mask-RCNN network was used to classify,segment,and count the canopy leaves of the watermelon plug seedlings.To reduce the error of leaf area measurement caused by mutual occlusion of leaves,the leaves were repaired by CycleGAN,and the depth images were restored by image processing.Then,the Delaunay triangulation was adopted to measure the leaf area in the leaf point cloud.The YOLOX target detection network was used to identify the growing point position of each seedling on the plug tray.Then the depth differences between the growing point and the upper surface of the plug tray were calculated to obtain plant height.The experiment results show that the nondestructive measurement algorithm proposed in this paper achieves good measurement performance for the watermelon plug seedlings from the 1 true-leaf to 3 true-leaf stages.The average relative error of measurement is 2.33%for the number of true leaves,4.59%for the number of cotyledons,8.37%for the leaf area,and 3.27%for the plant height.The experiment results demonstrate that the proposed algorithm in this paper provides an effective solution for the nondestructive measurement of the canopy phenotype of the plug seedlings.
