空格(标点符号)
转录组
空间分析
计算机科学
计算生物学
生物
数据科学
遥感
地理
基因表达
遗传学
基因
操作系统
作者
Kevin L. Cox,Sai Guna Ranjan Gurazada,Keith E. Duncan,Kirk J. Czymmek,Christopher N. Topp,Blake C. Meyers
出处
期刊:Plant Physiology
[Oxford University Press]
日期:2021-10-28
卷期号:188 (2): 703-712
被引量:24
标识
DOI:10.1093/plphys/kiab508
摘要
Abstract Plant cells communicate information for the regulation of development and responses to external stresses. A key form of this communication is transcriptional regulation, accomplished via complex gene networks operating both locally and systemically. To fully understand how genes are regulated across plant tissues and organs, high resolution, multi-dimensional spatial transcriptional data must be acquired and placed within a cellular and organismal context. Spatial transcriptomics (ST) typically provides a two-dimensional spatial analysis of gene expression of tissue sections that can be stacked to render three-dimensional data. For example, X-ray and light-sheet microscopy provide sub-micron scale volumetric imaging of cellular morphology of tissues, organs, or potentially entire organisms. Linking these technologies could substantially advance transcriptomics in plant biology and other fields. Here, we review advances in ST and 3D microscopy approaches and describe how these technologies could be combined to provide high resolution, spatially organized plant tissue transcript mapping.
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