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Advances in Single-Cell Transcriptome Sequencing and Spatial Transcriptome Sequencing in Plants.
Lv, Zhuo; Jiang, Shuaijun; Kong, Shuxin; Zhang, Xu; Yue, Jiahui; Zhao, Wanqi; Li, Long; Lin, Shuyan.
Afiliação
  • Lv Z; Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China.
  • Jiang S; Bamboo Research Institute, Nanjing Forestry University, Nanjing 210037, China.
  • Kong S; College of Life Science, Nanjing Forestry University, Nanjing 210037, China.
  • Zhang X; Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China.
  • Yue J; Bamboo Research Institute, Nanjing Forestry University, Nanjing 210037, China.
  • Zhao W; College of Life Science, Nanjing Forestry University, Nanjing 210037, China.
  • Li L; Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China.
  • Lin S; Bamboo Research Institute, Nanjing Forestry University, Nanjing 210037, China.
Plants (Basel) ; 13(12)2024 Jun 18.
Article em En | MEDLINE | ID: mdl-38931111
ABSTRACT
"Omics" typically involves exploration of the structure and function of the entire composition of a biological system at a specific level using high-throughput analytical methods to probe and analyze large amounts of data, including genomics, transcriptomics, proteomics, and metabolomics, among other types. Genomics characterizes and quantifies all genes of an organism collectively, studying their interrelationships and their impacts on the organism. However, conventional transcriptomic sequencing techniques target population cells, and their results only reflect the average expression levels of genes in population cells, as they are unable to reveal the gene expression heterogeneity and spatial heterogeneity among individual cells, thus masking the expression specificity between different cells. Single-cell transcriptomic sequencing and spatial transcriptomic sequencing techniques analyze the transcriptome of individual cells in plant or animal tissues, enabling the understanding of each cell's metabolites and expressed genes. Consequently, statistical analysis of the corresponding tissues can be performed, with the purpose of achieving cell classification, evolutionary growth, and physiological and pathological analyses. This article provides an overview of the research progress in plant single-cell and spatial transcriptomics, as well as their applications and challenges in plants. Furthermore, prospects for the development of single-cell and spatial transcriptomics are proposed.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Plants (Basel) Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Plants (Basel) Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China