Mapping a Transcriptome-Guided Arabidopsis SAM Interactome
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.
Key wordsSAM RAM Transcriptome OMICs Interactomes
We thank the German Research Foundation (DFG) for funding (TR124/B1) to TD and start-up grant (R18045) and RIF-grant by Zayed University to MN and UAE Space Agency grant (EU1804) to FMH.
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