Department of Life and Environmental Sciences, College of Natural and Health Sciences, Zayed University, Abu Dhabi, UAE.
Department of Bioinformatics, Biocenter, University of Wuerzburg, Wuerzburg, Germany.
Methods Mol Biol. 2020;2094:113-118. doi: 10.1007/978-1-0716-0183-9_12.
The advent of multi-OMICS approaches has a significant impact on the investigation of biological processes occurring in plants. RNA-SEQ, cellular proteomics, and metabolomics have added a considerable ease in studying the dynamics of stem cell niches. New cell sorting approaches coupled with the labeling of stem cell population specific marker genes are highly instrumental in enriching distinct cellular populations for various types of analysis. One more promising field of OMICS is the mapping of cellular interactomes. The plant stem cells research is barely profited from this newly emerging field of OMICS. Generation of stem cell/niche-specific interactome is a time-consuming and labor-intensive task. Here, we describe a method on how to assemble a SAM-based interactome after using the available generic Arabidopsis interactomes. To define the context of SAM in a generic interactome, we used SAM cell population transcriptome datasets. Our step-by-step protocol can easily be adopted for other stem cell niches such as RAM and lateral meristems keeping in view the availability of transcriptome datasets for cellular populations of these niches.
多组学方法的出现对研究植物中发生的生物过程产生了重大影响。RNA-SEQ、细胞蛋白质组学和代谢组学极大地促进了干细胞龛动态的研究。新的细胞分选方法与标记干细胞群体特异性标记基因相结合,对于富集不同的细胞群体进行各种类型的分析非常有帮助。组学的另一个有前途的领域是细胞相互作用组的映射。植物干细胞研究几乎没有从这个新兴的组学领域中受益。生成干细胞/龛位特异性相互作用组是一项耗时耗力的任务。在这里,我们描述了一种在使用现有的拟南芥通用相互作用组后组装基于 SAM 的相互作用组的方法。为了在通用相互作用组中定义 SAM 的上下文,我们使用了 SAM 细胞群体转录组数据集。我们的逐步方案可以很容易地应用于其他干细胞龛位,如 RAM 和侧生分生组织,考虑到这些龛位的细胞群体的转录组数据集的可用性。