Profiling of Single-cell-type-specific MicroRNAs in Arabidopsis Roots by Immunoprecipitation of Root
Lusheng Fan1, Bin Gao1, Xuemei Chen1
1Department of Botany and Plant Sciences, Institute for Integrative Genome Biology, University of California, Riverside, USA.
Abstract:
MicroRNAs (miRNA) are small (21-24 nt) non-coding RNAs involved in many biological processes in both plants and animals. The biogenesis of plant miRNAs starts with the transcription of MIRNA (MIR ) genes by RNA polymerase II; then, the primary miRNA transcripts are cleaved by Dicer-like proteins into mature miRNAs, which are then loaded into Argonaute (AGO) proteins to form the effector complex, the miRNA-induced silencing complex (miRISC). In Arabidopsis , some MIR genes are expressed in a tissue-specific manner; however, the spatial patterns of MIR gene expression may not be the same as the spatial distribution of miRISCs due to the non-cell autonomous nature of some miRNAs, making it challenging to characterize the spatial profiles of miRNAs. A previous study utilized protoplasting of green fluorescent protein (GFP) marker transgenic lines followed by fluorescence-activated cell sorting (FACS) to isolate cell-type-specific small RNAs. However, the invasiveness of this approach during the protoplasting and cell sorting may stimulate the expression of stress-related miRNAs. To non-invasively profile cell-type-specific miRNAs, we generated transgenic lines in which root cell layer-specific promoters drive the expression of AGO1 and performed immunoprecipitation to non-invasively isolate cell-layer-specific miRISCs. In this protocol, we provide a detailed description of immunoprecipitation of root cell layer-specific GFP-AGO1 using EN7::GFP-AGO1 and ACL5::GFP-AGO1 transgenic plants, followed by small RNA sequencing to profile single-cell-type-specific miRNAs. This protocol is also suitable to profile cell-type-specific miRISCs in other tissues or organs in plants, such as flowers or leaves. This protocol was validated in: Dev Cell (2022), DOI: 10.1016/j.devcel.2022.03.015 Graphical abstract.
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