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Plant function is the result of the concerted action of single cells in different tissues. Advances in RNA-seq technologies and tissue processing allow us now to capture transcriptional changes at single-cell resolution. The incredible potential of single-cell RNA-seq lies in the novel ability to study and exploit regulatory processes in complex tissues based on the behaviour of single cells. Importantly, the independence from reporter lines allows the analysis of any given tissue in any plant. While there are challenges associated with the handling and analysis of complex datasets, the opportunities are unique to generate knowledge of tissue functions in unprecedented detail and to facilitate the application of such information by mapping cellular functions and interactions in a plant cell atlas. Insights Gained from Single-Cell ProfilingThe functionality of complex organs and organisms is the result of an orchestrated interplay of different cell types and their specific functions [1-3]. To completely understand and identify most critical cellular processes in complex tissues therefore requires changes to be captured at the cell-type or even single-cell level (Figure 1A). Progress in cell type-specific transcriptomics represented a vital first step in this direction and helped to reveal essential cellular activities involved in plant development and stress adaptation [2][3][4]. Recent advances in microfluidics-based approaches to single-cell RNA-seq (scRNA-seq) (see Glossary) equip us now with a unique opportunity to study transcriptional changes at cellular resolution in any given organism [5][6][7][8][9][10][11][12]. In animal-based research, scRNA-seq has revolutionised and stimulated cellular studies. In addition to facilitating the discovery of new cell types, it enables the study of stochastic principles in cellular gene network regulation and the trajectories of transcriptomic changes underlying cell fate choices and organ functionality [13][14][15][16][17].As a new technique that has thus far been substantially applied only in animal/human tissues, the true potential of scRNA-seq for diverse aspects of plant science has just started to be recognised. Here, we highlight the opportunities and challenges associated with performing scRNA-seq in plants. The scope of this review is to focus on droplet-based methods, primarily Drop-seq and 10X platforms, as these are the methods that have been applied to plant studies so far. However, analyses of data from other droplet-based methods are highly similar to what is reviewed below. Importantly, we introduce the technical principles of scRNA-seq approaches for plant-based studies, explain how scRNA-seq systems operate, and outline standard analytical workflows including underlying statistical analyses of scRNA-seq data.

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