Best practices for the execution, analysis, and data storage of plant single-cell/nucleus transcriptomics.

Single-cell and single-nucleus RNA-sequencing technologies capture the expression of plant genes at an unprecedented resolution. Therefore, these technologies are gaining traction in plant molecular and developmental biology for elucidating the transcriptional changes across cell types in a specific tissue or organ, upon treatments, in response to biotic and abiotic stresses, or between genotypes. Despite the rapidly accelerating use of these technologies, collective and standardized experimental and analytical procedures to support the acquisition of high-quality data sets are still missing. In this commentary, we discuss common challenges associated with the use of single-cell transcriptomics in plants and propose general guidelines to improve reproducibility, quality, comparability, and interpretation and to make the data readily available to the community in this fast-developing field of research.

Single Cell RNA-Sequencing in Arabidopsis Root Tissues.

Droplet-based single-cell RNA-sequencing (scRNA-seq) empowers transcriptomic profiling with an unprecedented resolution, facilitating insights into the cellular heterogeneity of tissues, developmental progressions, stress-response dynamics, and more at single-cell level. In this chapter, we describe the experimental workflow of processing Arabidopsis root tissue into protoplasts and generating single-cell transcriptomes. We also describe the general computational workflow of visualizing and utilizing scRNA-seq data. This protocol can be used as a starting point for establishing a scRNA-seq workflow.

Advancing root developmental research through single-cell technologies.

Single-cell RNA-sequencing has greatly increased the spatiotemporal resolution of root transcriptomics data, but we are still only scratching the surface of its full potential. Despite the challenges that remain in the field, the orderly aligned structure of the Arabidopsis root meristem makes it specifically suitable for lineage tracing and trajectory analysis. These methods will become even more potent by increasing resolution and specificity using tissue-specific single-cell RNA-sequencing and spatial transcriptomics. Feeding multiple single-cell omics data sets into single-cell gene regulatory networks will accelerate the discovery of regulators of root development in multiple species. By providing transcriptome atlases for virtually any species, single-cell technologies could tempt many root developmental biologists to move beyond the comfort of the well-known Arabidopsis root meristem.

Single-cell transcriptome profiling of buffelgrass (Cenchrus ciliaris) eggs unveils apomictic parthenogenesis signatures.

Apomixis, a type of asexual reproduction in angiosperms, results in progenies that are genetically identical to the mother plant. It is a highly desirable trait in agriculture due to its potential to preserve heterosis of F1 hybrids through subsequent generations. However, no major crops are apomictic. Deciphering mechanisms underlying apomixis becomes one of the alternatives to engineer self-reproducing capability into major crops. Parthenogenesis, a major component of apomixis, commonly described as the ability to initiate embryo formation from the egg cell without fertilization, also can be valuable in plant breeding for doubled haploid production. A deeper understanding of transcriptional differences between parthenogenetic and sexual or non-parthenogenetic eggs can assist with pathway engineering. By conducting laser capture microdissection-based RNA-seq on sexual and parthenogenetic egg cells on the day of anthesis, a de novo transcriptome for the Cenchrus ciliaris egg cells was created, transcriptional profiles that distinguish the parthenogenetic egg from its sexual counterpart were identified, and functional roles for a few transcription factors in promoting natural parthenogenesis were suggested. These transcriptome data expand upon previous gene expression studies and will be a resource for future research on the transcriptome of egg cells in parthenogenetic and sexual genotypes.