Dissection of miRNA Pathways Using Arabidopsis Mesophyll Protoplasts

MicroRNAs (miRNAs) control gene expression mostly post-transcriptionally by guiding transcript cleavage and/or translational repression of complementary mRNA targets, thereby regulating developmental processes and stress responses. Despite the remarkable expansion of the field, the mechanisms underlying miRNA activity are not fully understood. In this article, we describe a transient expression system in Arabidopsis mesophyll protoplasts, which is highly amenable for the dissection of miRNA pathways. We show that by transiently overexpressing primary miRNAs and target mimics, we can manipulate miRNA levels and consequently impact on their targets. Furthermore, we developed a set of luciferase-based sensors for quantifying miRNA activity that respond specifically to both endogenous and overexpressed miRNAs and target mimics. We demonstrate that these miRNA sensors can be used to test the impact of putative components of the miRNA pathway on miRNA activity, as well as the impact of specific mutations, by either overexpression or the use of protoplasts from the corresponding mutants. We further show that our miRNA sensors can be used for investigating the effect of chemicals on miRNA activity. Our cell-based transient expression system is fast and easy to set up, and generates quantitative results, being a powerful tool for assaying miRNA activity in vivo.

Whole Genome Analysis of Gene Expression Reveals Coordinated Activation of Signaling and Metabolic Pathways during Pollen-Pistil Interactions in Arabidopsis

Plant reproduction depends on the concerted activation of many genes to ensure correct communication between pollen and pistil. Here, we queried the whole transcriptome of Arabidopsis (Arabidopsis thaliana) in order to identify genes with specific reproductive functions. We used the Affymetrix ATH1 whole genome array to profile wild-type unpollinated pistils and unfertilized ovules. By comparing the expression profile of pistils at 0.5, 3.5, and 8.0 h after pollination and applying a number of statistical and bioinformatics criteria, we found 1,373 genes differentially regulated during pollen-pistil interactions. Robust clustering analysis grouped these genes in 16 time-course clusters representing distinct patterns of regulation. Coregulation within each cluster suggests the presence of distinct genetic pathways, which might be under the control of specific transcriptional regulators. A total of 78% of the regulated genes were expressed initially in unpollinated pistil and/or ovules, 15% were initially detected in the pollen data sets as enriched or preferentially expressed, and 7% were induced upon pollination. Among those, we found a particular enrichment for unknown transcripts predicted to encode secreted proteins or representing signaling and cell wall-related proteins, which may function by remodeling the extracellular matrix or as extracellular signaling molecules. A strict regulatory control in various metabolic pathways suggests that fine-tuning of the biochemical and physiological cellular environment is crucial for reproductive success. Our study provides a unique and detailed temporal and spatial gene expression profile of in vivo pollen-pistil interactions, providing a framework to better understand the basis of the molecular mechanisms operating during the reproductive process in higher plants.