Single-nucleus RNA sequencing of plant tissues using a nanowell-based system

Systematic Methods for Isolating High Purity Nuclei from Ten Important Plants for Omics Interrogation

Recent advances in developmental biology have been made possible by using multi-omic studies at single cell resolution. However, progress in plants has been slowed, owing to the tremendous difficulty in protoplast isolation from most plant tissues and/or oversize protoplasts during flow cytometry purification. Surprisingly, rapid innovations in nucleus research have shed light on plant studies in single cell resolution, which necessitates high quality and efficient nucleus isolation. Herein, we present efficient nuclei isolation protocols from the leaves of ten important plants including Arabidopsis, rice, maize, tomato, soybean, banana, grape, citrus, apple, and litchi. We provide a detailed procedure for nucleus isolation, flow cytometry purification, and absolute nucleus number quantification. The nucleus isolation buffer formula of the ten plants tested was optimized, and the results indicated a high nuclei yield. Microscope observations revealed high purity after flow cytometry sorting, and the DNA and RNA quality extract from isolated nuclei were monitored by using the nuclei in cell division cycle and single nucleus RNA sequencing (snRNA-seq) studies, with detailed procedures provided. The findings indicated that nucleus yield and quality meet the requirements of snRNA-seq, cell division cycle, and likely other omic studies. The protocol outlined here makes it feasible to perform plant omic studies at single cell resolution.

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 analysis of cell identity in the Arabidopsis root apical meristem: insights and opportunities

A fundamental question in developmental biology is how the progeny of stem cells become differentiated tissues. The Arabidopsis root is a tractable model to address this question due to its simple organization and defined cell lineages. In particular, the zone of dividing cells at the root tip-the root apical meristem-presents an opportunity to map the gene regulatory networks underlying stem cell niche maintenance, tissue patterning, and cell identity acquisition. To identify molecular regulators of these processes, studies over the last 20 years employed global profiling of gene expression patterns. However, these technologies are prone to information loss due to averaging gene expression signatures over multiple cell types and/or developmental stages. Recently developed high-throughput methods to profile gene expression at single-cell resolution have been successfully applied to plants. Here, we review insights from the first published single-cell mRNA sequencing and chromatin accessibility datasets generated from Arabidopsis roots. These studies successfully reconstruct developmental trajectories, phenotype cell identity mutants at unprecedented resolution, and reveal cell type-specific responses to environmental stimuli. The experimental insight gained from Arabidopsis paves the way to profile roots from additional species.

Plant Cell Identity in the Era of Single-Cell Transcriptomics

High-throughput single-cell transcriptomic approaches have revolutionized our view of gene expression at the level of individual cells, providing new insights into their heterogeneity, identities, and functions. Recently, technical challenges to the application of single-cell transcriptomics to plants have been overcome, and many plant organs and tissues have now been subjected to analyses at single-cell resolution. In this review, we describe these studies and their impact on our understanding of the diversity, differentiation, and activities of plant cells. We particularly highlight their impact on plant cell identity, including unprecedented views of cell transitions and definitions of rare and novel cell types. We also point out current challenges and future opportunities for the application and analyses of single-cell transcriptomics in plants. Expected final online publication date for the Annual Review of Genetics, Volume 55 is November 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Plant single-cell solutions for energy and the environment

Progress in sequencing, microfluidics, and analysis strategies has revolutionized the granularity at which multicellular organisms can be studied. In particular, single-cell transcriptomics has led to fundamental new insights into animal biology, such as the discovery of new cell types and cell type-specific disease processes. However, the application of single-cell approaches to plants, fungi, algae, or bacteria (environmental organisms) has been far more limited, largely due to the challenges posed by polysaccharide walls surrounding these species' cells. In this perspective, we discuss opportunities afforded by single-cell technologies for energy and environmental science and grand challenges that must be tackled to apply these approaches to plants, fungi and algae. We highlight the need to develop better and more comprehensive single-cell technologies, analysis and visualization tools, and tissue preparation methods. We advocate for the creation of a centralized, open-access database to house plant single-cell data. Finally, we consider how such efforts should balance the need for deep characterization of select model species while still capturing the diversity in the plant kingdom. Investments into the development of methods, their application to relevant species, and the creation of resources to support data dissemination will enable groundbreaking insights to propel energy and environmental science forward.

Enhancing Our Understanding of Plant Cell-to-Cell Interactions Using Single-Cell Omics

Plants are composed of cells that physically interact and constantly adapt to their environment. To reveal the contribution of each plant cells to the biology of the entire organism, their molecular, morphological, and physiological attributes must be quantified and analyzed in the context of the morphology of the plant organs. The emergence of single-cell/nucleus omics technologies now allows plant biologists to access different modalities of individual cells including their epigenome and transcriptome to reveal the unique molecular properties of each cell composing the plant and their dynamic regulation during cell differentiation and in response to their environment. In this manuscript, we provide a perspective regarding the challenges and strategies to collect plant single-cell biological datasets and their analysis in the context of cellular interactions. As an example, we provide an analysis of the transcriptional regulation of the Arabidopsis genes controlling the differentiation of the root hair cells at the single-cell level. We also discuss the perspective of the use of spatial profiling to complement existing plant single-cell omics.

FlsnRNA-seq: protoplasting-free full-length single-nucleus RNA profiling in plants

The broad application of single-cell RNA profiling in plants has been hindered by the prerequisite of protoplasting that requires digesting the cell walls from different types of plant tissues. Here, we present a protoplasting-free approach, flsnRNA-seq, for large-scale full-length RNA profiling at a single-nucleus level in plants using isolated nuclei. Combined with 10x Genomics and Nanopore long-read sequencing, we validate the robustness of this approach in Arabidopsis root cells and the developing endosperm. Sequencing results demonstrate that it allows for uncovering alternative splicing and polyadenylation-related RNA isoform information at the single-cell level, which facilitates characterizing cell identities.