转录组
生物
计算生物学
基因组学
有机体
蛋白质组学
代谢组学
功能基因组学
人口
从头转录组组装
单细胞测序
基因
群体基因组学
基因组
遗传学
生物信息学
基因表达
表型
外显子组测序
人口学
社会学
作者
Zhuo Lv,Shuaijun Jiang,Shuxin Kong,Xu Zhang,Jiahui Yue,Wanqi Zhao,Long Li,Shuyan Lin
出处
期刊:Plants
[Multidisciplinary Digital Publishing Institute]
日期:2024-06-18
卷期号:13 (12): 1679-1679
被引量:28
标识
DOI:10.3390/plants13121679
摘要
"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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