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Large-volume fully automated cell reconstruction generates a cell atlas of plant tissues.
Hu, Zijian; Liu, Jiazheng; Shen, Shiya; Wu, Weiqian; Yuan, Jingbin; Shen, Weiwei; Ma, Lingyu; Wang, Guangchao; Yang, Shunyao; Xu, Xiuping; Cui, Yaning; Li, Zhenchen; Shen, Lijun; Li, Linlin; Bian, Jiahui; Zhang, Xi; Han, Hua; Lin, Jinxing.
Afiliación
  • Hu Z; State Key Laboratory of Tree Genetics and Breeding, State Key Laboratory of Efficient Production of Forest Resources, National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China.
  • Liu J; Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
  • Shen S; School of Future Technology, School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 101408, China.
  • Wu W; State Key Laboratory of Tree Genetics and Breeding, State Key Laboratory of Efficient Production of Forest Resources, National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China.
  • Yuan J; State Key Laboratory of Tree Genetics and Breeding, State Key Laboratory of Efficient Production of Forest Resources, National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China.
  • Shen W; Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
  • Ma L; State Key Laboratory of Tree Genetics and Breeding, State Key Laboratory of Efficient Production of Forest Resources, National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China.
  • Wang G; Research Institute of Wood Industry, Chinese Academy of Forestry, Beijing 100091, China.
  • Yang S; State Key Laboratory of Tree Genetics and Breeding, State Key Laboratory of Efficient Production of Forest Resources, National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China.
  • Xu X; State Key Laboratory of Tree Genetics and Breeding, State Key Laboratory of Efficient Production of Forest Resources, National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China.
  • Cui Y; Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China.
  • Li Z; State Key Laboratory of Tree Genetics and Breeding, State Key Laboratory of Efficient Production of Forest Resources, National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China.
  • Shen L; Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
  • Li L; School of Future Technology, School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 101408, China.
  • Bian J; Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
  • Zhang X; Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
  • Han H; State Key Laboratory of Tree Genetics and Breeding, State Key Laboratory of Efficient Production of Forest Resources, National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China.
  • Lin J; State Key Laboratory of Tree Genetics and Breeding, State Key Laboratory of Efficient Production of Forest Resources, National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China.
Plant Cell ; 2024 Sep 16.
Article en En | MEDLINE | ID: mdl-39283506
ABSTRACT
The geometric shape and arrangement of individual cells play a role in shaping organ functions. However, analyzing multicellular features and exploring their connectomes in centimeter-scale plant organs remain challenging. Here, we established a set of frameworks named Large-Volume Fully Automated Cell Reconstruction (LVACR), enabling the exploration of three-dimensional (3D) cytological features and cellular connectivity in plant tissues. Through benchmark testing, our framework demonstrated superior efficiency in cell segmentation and aggregation, successfully addressing the inherent challenges posed by light sheet fluorescence microscopy (LSFM) imaging. Using LVACR, we successfully established a cell atlas of different plant tissues. Cellular morphology analysis revealed differences of cell clusters and shapes in between different poplar (P. simonii Carr. and P. canadensis Moench.) seeds, whereas topological analysis revealed that they maintained conserved cellular connectivity. Furthermore, LVACR spatiotemporally demonstrated an initial burst of cell proliferation, accompanied by morphological transformations at an early stage in developing the shoot apical meristem. During subsequent development, cell differentiation produced anisotropic features, thereby resulting in various cell shapes. Overall, our findings provided valuable insights into the precise spatial arrangement and cellular behavior of multicellular organisms, thus enhancing our understanding of the complex processes underlying plant growth and differentiation.
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Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Plant Cell Asunto de la revista: BOTANICA Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Plant Cell Asunto de la revista: BOTANICA Año: 2024 Tipo del documento: Article País de afiliación: China