A single-cell view of the transcriptome during lateral root initiation in Arabidopsis thaliana

A single-nuclei transcriptome census of the Arabidopsis maturing root identifies that MYB67 controls phellem cell maturation

The periderm provides a protective barrier in many seed plant species. The development of the suberized phellem, which forms the outermost layer of this important tissue, has become a trait of interest for enhancing both plant resilience to stresses and plant-mediated CO2 sequestration in soils. Despite its importance, very few genes driving phellem development are known. Employing single-nuclei sequencing, we have generated an expression census capturing the complete developmental progression of Arabidopsis root phellem cells, from their progenitor cell type, the pericycle, through to their maturation. With this, we identify a whole suite of genes underlying this process, including MYB67, which we show has a role in phellem cell maturation. Our expression census and functional discoveries represent a resource, expanding our comprehension of secondary growth in plants. These data can be used to fuel discoveries and engineering efforts relevant to plant resilience and climate change.

RAPID LEAF FALLING 1 facilitates chemical defoliation and mechanical harvesting in cotton

Chemical defoliation stands as the ultimate tool in enabling the mechanical harvest of cotton, offering economic and environmental advantages. However, the underlying molecular mechanism that triggers leaf abscission through defoliant remains unsolved. In this study, we meticulously constructed a transcriptomic atlas through single-nucleus mRNA sequencing (snRNA-seq) of the abscission zone (AZ) from cotton petiole. We identified two newly-formed cell types, abscission cells and protection layer cells in cotton petiole AZ after defoliant treatment. GhRLF1 (RAPID LEAF FALLING 1), as one of the members of the cytokinin oxidase/dehydrogenase (CKX) gene family, was further characterized as a key marker gene unique to the abscission cells following defoliant treatment. Overexpression of GhRLF1 resulted in reduced cytokinin accumulation and accelerated leaf abscission. Conversely, CRISPR/Cas9-mediated loss of GhRLF1 function appeared to delay this process. Its interacting regulators, GhWRKY70, acting as "Pioneer" activator, and GhMYB108, acting as "Successor" activator, orchestrate a sequential modulation of GhWRKY70/GhMYB108-GhRLF1-CTK (cytokinin) within the AZ to regulate cotton leaf abscission. GhRLF1 not only regulates leaf abscission but also reduces cotton yield. Consequently, transgenic lines that exhibit rapid leaf falling and require less defoliant but show unaffected cotton yield were developed for mechanical harvesting. This was achieved using a defoliant-induced petiole-specific promoter, proPER21, to drive GhRLF1 (proPER21::RLF1). This pioneering biotechnology offers a new strategy for the chemical defoliation of machine-harvested cotton, ensuring stable production and reducing leaf debris in harvested cotton, thereby enhancing environmental sustainability.

A rhizobacterium-secreted protein induces lateral root development through the IAA34-PUCHI pathway

Lateral roots (LRs) can continuously forage water and nutrients from soil. In Arabidopsis thaliana, LR development depends on a canonical auxin signaling pathway involving the core transcription factors INDOLE-3-ACETIC ACIDs (IAAs) and AUXIN RESPONSE FACTORs (ARFs). In this study, we identified a protein, bacillolysin, secreted by the beneficial rhizobacterium Bacillus velezensis SQR9, that is able to stimulate LR formation of Arabidopsis. The receptor protein kinase C-TERMINALLY ENCODED PEPTIDE RECEPTOR2 (CEPR2) interacts with bacillolysin and plays a critical role in LR development. In the bacillolysin-regulated signaling pathway, the transcriptional repressor IAA34 interacts with PUCHI to activate downstream LATERAL ORGAN BOUNDARIES-DOMAIN33 (LBD33) expression, consequently inducing LR development. This study reveals interkingdom communication via a protein that mediates a novel pathway to induce LR development.

Sinomonas gamaensis NEAU-HV1 remodels the IAA14-ARF7/19 interaction to promote plant growth

Sinomonas species typically reside in soils or the rhizosphere and can promote plant growth. Sinomonas enrichment in rhizospheric soils is positively correlated with increases in plant biomass. However, the growth promotion mechanisms regulated by Sinomonas remain unclear. By using soil systems, we studied the growth-promoting effects of Sinomonas gamaensis NEAU-HV1 on various plants. Through a combination of phenotypic analyses and microscopic observations, the effects of NEAU-HV1 on root development were evaluated. We subsequently conducted molecular and genetic experiments to reveal the mechanism promoting lateral root (LR) development. We demonstrated that NEAU-HV1 significantly promoted the growth of lettuce, wheat, maize, peanut and Arabidopsis. This effect was associated with multiple beneficial traits, including phosphate solubilization, indole-3-acetic acid and 1-aminocyclopropane-1-carboxylic acid deaminase production and survival ability in the rhizosphere and within the inner tissue of roots. In addition, NEAU-HV1 could secrete metabolites to promote LR development by affecting auxin transport and signaling. Importantly, we found that the influence of auxin signaling may be attributed to the remodeling interaction between SOLITARY-ROOT (SLR)/IAA14 and ARF7/19, occurring independently of the auxin receptor TIR1/AFB2. Our results indicate that NEAU-HV1-induced LR formation is dependent on direct remodeling interactions between transcription factors, providing novel insights into plant-microbe interactions.

ACT2.6: Global Gene Coexpression Network in Arabidopsis thaliana Using WGCNA

BACKGROUND/OBJECTIVES

Genes with similar expression patterns across multiple samples are considered coexpressed, and they may participate in similar biological processes or pathways. Gene coexpression networks depict the degree of similarity between the expression profiles of all genes in a set of samples. Gene coexpression tools allow for the prediction of functional gene partners or the assignment of roles to genes of unknown function. Weighted Gene Correlation Network Analysis (WGCNA) is an R package that provides a multitude of functions for constructing and analyzing a weighted or unweighted gene coexpression network.

METHODS

Previously preprocessed, high-quality gene expression data of 3500 samples of Affymetrix microarray technology from various tissues of the Arabidopsis thaliana plant model species were used to construct a weighted gene coexpression network, using WGCNA.

RESULTS

The gene dendrogram was used as the basis for the creation of a new Arabidopsis coexpression tool (ACT) version (ACT2.6). The dendrogram contains 21,273 leaves, each one corresponding to a single gene. Genes that are clustered in the same clade are coexpressed. WGCNA grouped the genes into 27 functional modules, all of which were positively or negatively correlated with specific tissues.

DISCUSSION

Genes known to be involved in common metabolic pathways were discovered in the same module. By comparing the current ACT version with the previous one, it was shown that the new version outperforms the old one in discovering the functional connections between gene partners. ACT2.6 is a major upgrade over the previous version and a significant addition to the collection of public gene coexpression tools.

Advancing our understanding of root development: Technologies and insights from diverse studies

Understanding root development is critical for enhancing plant growth and health, and advanced technologies are essential for unraveling the complexities of these processes. In this review, we highlight select technological innovations in the study of root development, with a focus on the transformative impact of single-cell gene expression analysis. We provide a high-level overview of recent advancements, illustrating how single-cell RNA sequencing (scRNA-seq) has become a pivotal tool in plant biology. scRNA-seq has revolutionized root biology by enabling detailed, cell-specific analysis of gene expression. This has allowed researchers to create comprehensive root atlases, predict cell development, and map gene regulatory networks (GRNs) with unprecedented precision. Complementary technologies, such as multimodal profiling and bioinformatics, further enrich our understanding of cellular dynamics and gene interactions. Innovations in imaging and modeling, combined with genetic tools like CRISPR, continue to deepen our knowledge of root formation and function. Moreover, the integration of these technologies with advanced biosensors and microfluidic devices has advanced our ability to study plant-microbe interactions and phytohormone signaling at high resolution. These tools collectively provide a more comprehensive understanding of root system architecture and its regulation by environmental factors. As these technologies evolve, they promise to drive further breakthroughs in plant science, with substantial implications for agriculture and sustainability.

SCEMENT: scalable and memory efficient integration of large-scale single-cell RNA-sequencing data

MOTIVATION

Integrative analysis of large-scale single-cell data collected from diverse cell populations promises an improved understanding of complex biological systems. While several algorithms have been developed for single-cell RNA-sequencing data integration, many lack the scalability to handle large numbers of datasets and/or millions of cells due to their memory and run time requirements. The few tools that can handle large data do so by reducing the computational burden through strategies such as subsampling of the data or selecting a reference dataset to improve computational efficiency and scalability. Such shortcuts, however, hamper the accuracy of downstream analyses, especially those requiring quantitative gene expression information.

RESULTS

We present SCEMENT, a SCalablE and Memory-Efficient iNTegration method, to overcome these limitations. Our new parallel algorithm builds upon and extends the linear regression model previously applied in ComBat to an unsupervised sparse matrix setting to enable accurate integration of diverse and large collections of single-cell RNA-sequencing data. Using tens to hundreds of real single-cell RNA-seq datasets, we show that SCEMENT outperforms ComBat as well as FastIntegration and Scanorama in runtime (upto 214× faster) and memory usage (upto 17.5× less). It not only performs batch correction and integration of millions of cells in under 25 min, but also facilitates the discovery of new rare cell types and more robust reconstruction of gene regulatory networks with full quantitative gene expression information.

AVAILABILITY AND IMPLEMENTATION

Source code freely available for download at https://github.com/AluruLab/scement, implemented in C++ and supported on Linux.

A function of TPL/TBL1-type corepressors is to nucleate the assembly of the preinitiation complex

The plant corepressor TPL is recruited to diverse chromatin contexts, yet its mechanism of repression remains unclear. Previously, we leveraged the fact that TPL retains its function in a synthetic transcriptional circuit in the yeast model Saccharomyces cerevisiae to localize repressive function to two distinct domains. Here, we employed two unbiased whole-genome approaches to map the physical and genetic interactions of TPL at a repressed locus. We identified SPT4, SPT5, and SPT6 as necessary for repression with SPT4 acting as a bridge connecting TPL to SPT5 and SPT6. We discovered the association of multiple additional constituents of the transcriptional preinitiation complex at TPL-repressed promoters, specifically those involved early in transcription initiation. These findings were validated in yeast and plants, including a novel method to analyze the conditional loss of function of essential genes in plants. Our findings support a model where TPL nucleates preassembly of the transcription activation machinery to facilitate the rapid onset of transcription once repression is relieved.

Opportunities and challenges in the application of single-cell transcriptomics in plant tissue research

Single-cell transcriptomics overcomes the limitations of conventional transcriptome methods by isolating and sequencing RNA from individual cells, thus capturing unique expression values for each cell. This technology allows unprecedented precision in observing the stochasticity and heterogeneity of gene expression within cells. However, single-cell RNA sequencing (scRNA-seq) experiments often fail to capture all cells and genes comprehensively, and single-modality data is insufficient to explain cell states and systemic changes. To address this, the integration of multi-source scRNA-seq and single-cell multi-modality data has emerged, enabling the construction of comprehensive cell atlases. These integration methods also facilitate the exploration of causal relationships and gene regulatory mechanisms across different modalities. This review summarizes the fundamental principles, applications, and value of these integration methods in revealing biological changes, and analyzes the advantages, disadvantages, and future directions of current approaches.

Orthologous marker groups reveal broad cell identity conservation across plant single-cell transcriptomes

Single-cell RNA sequencing (scRNA-seq) is widely used in plant biology and is a powerful tool for studying cell identity and differentiation. However, the scarcity of known cell-type marker genes and the divergence of marker expression patterns limit the accuracy of cell-type identification and our capacity to investigate cell-type conservation in many species. To tackle this challenge, we devise a novel computational strategy called Orthologous Marker Gene Groups (OMGs), which can identify cell types in both model and non-model plant species and allows for rapid comparison of cell types across many published single-cell maps. Our method does not require cross-species data integration, while still accurately determining inter-species cellular similarities. We validate the method by analyzing published single-cell data from species with well-annotated single-cell maps, and we show our methods can capture majority of manually annotated cell types. The robustness of our method is further demonstrated by its ability to pertinently map cell clusters from 1 million cells, 268 cell clusters across 15 diverse plant species. We reveal 14 dominant groups with substantial conservation in shared cell-type markers across monocots and dicots. To facilitate the use of this method by the broad research community, we launch a user-friendly web-based tool called the OMG browser, which simplifies the process of cell-type identification in plant datasets for biologists.

A history-dependent integrase recorder of plant gene expression with single-cell resolution

During development, most cells experience a progressive restriction of fate that ultimately results in a fully differentiated mature state. Understanding more about the gene expression patterns that underlie developmental programs can inform engineering efforts for new or optimized forms. Here, we present a four-state integrase-based recorder of gene expression history and demonstrate its use in tracking gene expression events in Arabidopsis thaliana in two developmental contexts: lateral root initiation and stomatal differentiation. The recorder uses two serine integrases to mediate sequential DNA recombination events, resulting in step-wise, history-dependent switching between expression of fluorescent reporters. By using promoters that express at different times along each of the two differentiation pathways to drive integrase expression, we tie fluorescent status to an ordered progression of gene expression along the developmental trajectory. In one snapshot of a mature tissue, our recorder is able to reveal past gene expression with single cell resolution. In this way, we are able to capture heterogeneity in stomatal development, confirming the existence of two alternate paths of differentiation.

Multiple layers of regulators emerge in the network controlling lateral root organogenesis

Lateral root (LR) formation is a postembryonic organogenesis process that is crucial for plant root system development and adaptation to heterogenous soil environments. Since the early 1990s, a wealth of experimental data on arabidopsis (Arabidopsis thaliana) has helped reveal the LR formation regulatory network, in which dynamic auxin distribution and transcriptional cascades direct root cells through their organogenesis pathway. Some parts of this network appear conserved across diverse plant species or distinct developmental contexts. Recently, our knowledge of this process dramatically expanded thanks to technical advances, from single cell profiling to whole-root system phenotyping. Interestingly, new players are now emerging in this network, such as fatty acids and reactive oxygen species (ROS), transforming our knowledge of this hidden half of plant biology.

Transcriptional landscape of sweetpotato root tip development at the single-cell level

Single-cell transcriptome sequencing (scRNA-seq) is a powerful tool for describing the transcriptome dynamics of plant development but has not yet been utilized to analyze the tissue ontology of sweetpotato. This study established a stable method for isolating single protoplast cells for scRNA-seq to reveal the cell heterogeneity of sweetpotato root tip meristems at the single-cell level. The study analyzed 12,172 single cells and 27,355 genes in the root tips of the sweetpotato variety Guangshu 87, which were distributed into 15 cell clusters. Pseudo-time analysis showed that there were transitional cells in the apical development trajectory of mature cell types from stem cell niches. Furthermore, we identified novel development regulators of sweetpotato tubers via trajectory analysis. The transcription factor IbGATA4 was highly expressed in the adventitious roots during the development of sweetpotato root tips, where it may regulate the development of sweetpotato root tips. In addition, significant differences were observed in the transcriptional profiles of cell types between sweetpotato, Arabidopsis thaliana, and maize. This study mapped the single-cell transcriptome of sweetpotato root tips, laying a foundation for studying the types, functions, differentiation, and development of sweetpotato root tip cells.

What Is a Plant Cell Type in the Age of Single-Cell Biology? It's Complicated

One of the fundamental questions in developmental biology is how a cell is specified to differentiate as a specialized cell type. Traditionally, plant cell types were defined based on their function, location, morphology, and lineage. Currently, in the age of single-cell biology, researchers typically attempt to assign plant cells to cell types by clustering them based on their transcriptomes. However, because cells are dynamic entities that progress through the cell cycle and respond to signals, the transcriptome also reflects the state of the cell at a particular moment in time, raising questions about how to define a cell type. We suggest that these complexities and dynamics of cell states are of interest and further consider the roles signaling, stochasticity, cell cycle, and mechanical forces play in plant cell fate specification. Once established, cell identity must also be maintained. With the wealth of single-cell data coming out, the field is poised to elucidate both the complexity and dynamics of cell states.

Single-Cell Transcriptomics Applied in Plants

Single-cell RNA sequencing (scRNA-seq) is a high-tech method for characterizing the expression patterns of heterogeneous cells in the same tissue and has changed our evaluation of biological systems by increasing the number of individual cells analyzed. However, the full potential of scRNA-seq, particularly in plant science, has not yet been elucidated. To explore the utilization of scRNA-seq technology in plants, we firstly conducted a comprehensive review of significant scRNA-seq findings in the past few years. Secondly, we introduced the research and applications of scRNA-seq technology to plant tissues in recent years, primarily focusing on model plants, crops, and wood. We then offered five databases that could facilitate the identification of distinct expression marker genes for various cell types. Finally, we analyzed the potential problems, challenges, and directions for applying scRNA-seq in plants, with the aim of providing a theoretical foundation for the better use of this technique in future plant research.

An atlas of Brachypodium distachyon lateral root development

The root system of plants is a vital part for successful development and adaptation to different soil types and environments. A major determinant of the shape of a plant root system is the formation of lateral roots, allowing for expansion of the root system. Arabidopsis thaliana, with its simple root anatomy, has been extensively studied to reveal the genetic program underlying root branching. However, to get a more general understanding of lateral root development, comparative studies in species with a more complex root anatomy are required. Here, by combining optimized clearing methods and histology, we describe an atlas of lateral root development in Brachypodium distachyon, a wild, temperate grass species. We show that lateral roots initiate from enlarged phloem pole pericycle cells and that the overlying endodermis reactivates its cell cycle and eventually forms the root cap. In addition, auxin signaling reported by the DR5 reporter was not detected in the phloem pole pericycle cells or young primordia. In contrast, auxin signaling was activated in the overlying cortical cell layers, including the exodermis. Thus, Brachypodium is a valuable model to investigate how signaling pathways and cellular responses have been repurposed to facilitate lateral root organogenesis.

Single-cell network analysis reveals gene expression programs for Arabidopsis root development and metabolism

Single-cell RNA-sequencing datasets of Arabidopsis roots have been generated, but related comprehensive gene co-expression network analyses are lacking. We conducted a single-cell gene co-expression network analysis with publicly available scRNA-seq datasets of Arabidopsis roots using a SingleCellGGM algorithm. The analysis identified 149 gene co-expression modules, which we considered to be gene expression programs (GEPs). By examining their spatiotemporal expression, we identified GEPs specifically expressed in major root cell types along their developmental trajectories. These GEPs define gene programs regulating root cell development at different stages and are enriched with relevant developmental regulators. As examples, a GEP specific for the quiescent center (QC) contains 20 genes regulating QC and stem cell niche homeostasis, and four GEPs are expressed in sieve elements (SEs) from early to late developmental stages, with the early-stage GEP containing 17 known SE developmental regulators. We also identified GEPs for metabolic pathways with cell-type-specific expression, suggesting the existence of cell-type-specific metabolism in roots. Using the GEPs, we discovered and verified a columella-specific gene, NRL27, as a regulator of the auxin-related root gravitropism response. Our analysis thus systematically reveals GEPs that regulate Arabidopsis root development and metabolism and provides ample resources for root biology studies.

Pleiotropy, a feature or a bug? Toward co-ordinating plant growth, development, and environmental responses through engineering plant hormone signaling

The advent of gene editing technologies such as CRISPR has simplified co-ordinating trait development. However, identifying candidate genes remains a challenge due to complex gene networks and pathways. These networks exhibit pleiotropy, complicating the determination of specific gene and pathway functions. In this review, we explore how systems biology and single-cell sequencing technologies can aid in identifying candidate genes for co-ordinating specifics of plant growth and development within specific temporal and tissue contexts. Exploring sequence-function space of these candidate genes and pathway modules with synthetic biology allows us to test hypotheses and define genotype-phenotype relationships through reductionist approaches. Collectively, these techniques hold the potential to advance breeding and genetic engineering strategies while also addressing genetic diversity issues critical for adaptation and trait development.

6-BA Reduced Yield Loss under Waterlogging Stress by Regulating the Phenylpropanoid Pathway in Wheat

Waterlogging stress causes substantial destruction to plant growth and production under climatic fluctuations globally. Plants hormones have been widely explored in numerous crops, displaying an imperative role in crop defense and growth mechanism. However, there is a paucity of research on the subject of plant hormones regulating waterlogging stress responses in wheat crop. In this study, we clarified the role of 6-BA in waterlogging stress through inducing phenylpropanoid biosynthesis in wheat. The application of 6-BA (6-benzyladenine) enhanced the growth and development of wheat plants under waterlogging stress, which was accompanied by reduced electrolyte leakage, high chlorophyll, and soluble sugar content. ROS scavenging was also enhanced by 6-BA, resulting in reduced MDA and H2O2 accumulation and amplified antioxidant enzyme activities. Additionally, under the effect of 6-BA, the acceleration of lignin content and accumulation in the cell walls of wheat tissues, along with the activation of PAL (phenylalanine ammonia lyase), TAL (tyrosine ammonia lyase), and 4CL (4-hydroxycinnamate CoA ligase) activities and the increase in the level of transcription of the TaPAL and Ta4CL genes, were observed under waterlogging stress. Also, 6-BA improved the root growth system under waterlogging stress conditions. Further qPCR analysis revealed increased auxin signaling (TaPR1) in 6-BA-treated plants under waterlogging stress that was consistent with the induction of endogenous IAA hormone content under waterlogging stress conditions. Here, 6-BA also reduced yield loss, as compared to control plants. Thus, the obtained data suggested that, under the application of 6-BA, phenylpropanoid metabolism (i.e., lignin) was stimulated, playing a significant role in reducing the negative effects of waterlogging stress on yield, as evinced by the improved plant growth parameters.

Opportunities and Challenges in Advancing Plant Research with Single-cell Omics

Plants possess diverse cell types and intricate regulatory mechanisms to adapt to the ever-changing environment of nature. Various strategies have been employed to study cell types and their developmental progressions, including single-cell sequencing methods which provide high-dimensional catalogs to address biological concerns. In recent years, single-cell sequencing technologies in transcriptomics, epigenomics, proteomics, metabolomics, and spatial transcriptomics have been increasingly used in plant science to reveal intricate biological relationships at the single-cell level. However, the application of single-cell technologies to plants is more limited due to the challenges posed by cell structure. This review outlines the advancements in single-cell omics technologies, their implications in plant systems, future research applications, and the challenges of single-cell omics in plant systems.

ScRNA-seq reveals dark- and light-induced differentially expressed gene atlases of seedling leaves in Arachis hypogaea L

Although the regulatory mechanisms of dark and light-induced plant morphogenesis have been broadly investigated, the biological process in peanuts has not been systematically explored on single-cell resolution. Herein, 10 cell clusters were characterized using scRNA-seq-identified marker genes, based on 13 409 and 11 296 single cells from 1-week-old peanut seedling leaves grown under dark and light conditions. 6104 genes and 50 transcription factors (TFs) displayed significant expression patterns in distinct cell clusters, which provided gene resources for profiling dark/light-induced candidate genes. Further pseudo-time trajectory and cell cycle evidence supported that dark repressed the cell division and perturbed normal cell cycle, especially the PORA abundances correlated with 11 TFs highly enriched in mesophyll to restrict the chlorophyllide synthesis. Additionally, light repressed the epidermis cell developmental trajectory extending by inhibiting the growth hormone pathway, and 21 TFs probably contributed to the different genes transcriptional dynamic. Eventually, peanut AHL17 was identified from the profile of differentially expressed TFs, which encoded protein located in the nucleus promoted leaf epidermal cell enlargement when ectopically overexpressed in Arabidopsis through the regulatory phytohormone pathway. Overall, our study presents the different gene atlases in peanut etiolated and green seedlings, providing novel biological insights to elucidate light-induced leaf cell development at the single-cell level.

Identification of Novel Regulators of Leaf Senescence Using a Deep Learning Model

Deep learning has emerged as a powerful tool for investigating intricate biological processes in plants by harnessing the potential of large-scale data. Gene regulation is a complex process that transcription factors (TFs), cooperating with their target genes, participate in through various aspects of biological processes. Despite its significance, the study of gene regulation has primarily focused on a limited number of notable instances, leaving numerous aspects and interactions yet to be explored comprehensively. Here, we developed DEGRN (Deep learning on Expression for Gene Regulatory Network), an innovative deep learning model designed to decipher gene interactions by leveraging high-dimensional expression data obtained from bulk RNA-Seq and scRNA-Seq data in the model plant Arabidopsis. DEGRN exhibited a compared level of predictive power when applied to various datasets. Through the utilization of DEGRN, we successfully identified an extensive set of 3,053,363 high-quality interactions, encompassing 1430 TFs and 13,739 non-TF genes. Notably, DEGRN's predictive capabilities allowed us to uncover novel regulators involved in a range of complex biological processes, including development, metabolism, and stress responses. Using leaf senescence as an example, we revealed a complex network underpinning this process composed of diverse TF families, including bHLH, ERF, and MYB. We also identified a novel TF, named MAF5, whose expression showed a strong linear regression relation during the progression of senescence. The mutant maf5 showed early leaf decay compared to the wild type, indicating a potential role in the regulation of leaf senescence. This hypothesis was further supported by the expression patterns observed across four stages of leaf development, as well as transcriptomics analysis. Overall, the comprehensive coverage provided by DEGRN expands our understanding of gene regulatory networks and paves the way for further investigations into their functional implications.

Comprehensive integration of single-cell transcriptomic data illuminates the regulatory network architecture of plant cell fate specification

Plant morphogenesis relies on precise gene expression programs at the proper time and position which is orchestrated by transcription factors (TFs) in intricate regulatory networks in a cell-type specific manner. Here we introduced a comprehensive single-cell transcriptomic atlas of Arabidopsis seedlings. This atlas is the result of meticulous integration of 63 previously published scRNA-seq datasets, addressing batch effects and conserving biological variance. This integration spans a broad spectrum of tissues, including both below- and above-ground parts. Utilizing a rigorous approach for cell type annotation, we identified 47 distinct cell types or states, largely expanding our current view of plant cell compositions. We systematically constructed cell-type specific gene regulatory networks and uncovered key regulators that act in a coordinated manner to control cell-type specific gene expression. Taken together, our study not only offers extensive plant cell atlas exploration that serves as a valuable resource, but also provides molecular insights into gene-regulatory programs that varies from different cell types.

TARGET OF MONOPTEROS: key transcription factors orchestrating plant development and environmental response

Plants have an incredible ability to sustain root and vascular growth after initiation of the embryonic root and the specification of vascular tissue in early embryos. Microarray assays have revealed that a group of transcription factors, TARGET OF MONOPTEROS (TMO), are important for embryonic root initiation in Arabidopsis. Despite the discovery of their auxin responsiveness early on, their function and mode of action remained unknown for many years. The advent of genome editing has accelerated the study of TMO transcription factors, revealing novel functions for biological processes such as vascular development, root system architecture, and response to environmental cues. This review covers recent achievements in understanding the developmental function and the genetic mode of action of TMO transcription factors in Arabidopsis and other plant species. We highlight the transcriptional and post-transcriptional regulation of TMO transcription factors in relation to their function, mainly in Arabidopsis. Finally, we provide suggestions for further research and potential applications in plant genetic engineering.

A conserved function of corepressors is to nucleate assembly of the transcriptional preinitiation complex

The plant corepressor TPL is recruited to diverse chromatin contexts, yet its mechanism of repression remains unclear. Previously, we have leveraged the fact that TPL retains its function in a synthetic transcriptional circuit in the yeast model Saccharomyces cerevisiae to localize repressive function to two distinct domains. Here, we employed two unbiased whole genome approaches to map the physical and genetic interactions of TPL at a repressed locus. We identified SPT4, SPT5 and SPT6 as necessary for repression with the SPT4 subunit acting as a bridge connecting TPL to SPT5 and SPT6. We also discovered the association of multiple additional constituents of the transcriptional preinitiation complex at TPL-repressed promoters, specifically those involved in early transcription initiation events. These findings were validated in yeast and plants through multiple assays, including a novel method to analyze conditional loss of function of essential genes in plants. Our findings support a model where TPL nucleates preassembly of the transcription activation machinery to facilitate rapid onset of transcription once repression is relieved.

Studying plant vascular development using single-cell approaches

Vascular cells form a highly complex and heterogeneous tissue. Its composition, function, shape, and arrangement vary with the developmental stage and between organs and species. Understanding the transcriptional regulation underpinning this complexity thus requires a high-resolution technique that is capable of capturing rapid events during vascular cell formation. Single-cell and single-nucleus RNA sequencing (sc/snRNA-seq) approaches provide powerful tools to extract transcriptional information from these lowly abundant and dynamically changing cell types, which allows the reconstruction of developmental trajectories. Here, we summarize and reflect on recent studies using single-cell transcriptomics to study vascular cell types and discuss current and future implementations of sc/snRNA-seq approaches in the field of vascular development.

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.

Microfluidic platform for omics analysis on single cells with diverse morphology and size: A review

BACKGROUND

Microfluidic techniques have emerged as powerful tools in single-cell research, facilitating the exploration of omics information from individual cells. Cell morphology is crucial for gene expression and physiological processes. However, there is currently a lack of integrated analysis of morphology and single-cell omics information. A critical challenge remains: what platform technologies are the best option to decode omics data of cells that are complex in morphology and size?

RESULTS

This review highlights achievements in microfluidic-based single-cell omics and isolation of cells based on morphology, along with other cell sorting methods based on physical characteristics. Various microfluidic platforms for single-cell isolation are systematically presented, showcasing their diversity and adaptability. The discussion focuses on microfluidic devices tailored to the distinct single-cell isolation requirements in plants and animals, emphasizing the significance of considering cell morphology and cell size in optimizing single-cell omics strategies. Simultaneously, it explores the application of microfluidic single-cell sorting technologies to single-cell sequencing, aiming to effectively integrate information about cell shape and size.

SIGNIFICANCE AND NOVELTY

The novelty lies in presenting a comprehensive overview of recent accomplishments in microfluidic-based single-cell omics, emphasizing the integration of different microfluidic platforms and their implications for cell morphology-based isolation. By underscoring the pivotal role of the specialized morphology of different cells in single-cell research, this review provides robust support for delving deeper into the exploration of single-cell omics data.

Single-cell transcriptomics is revolutionizing the improvement of plant biotechnology research: recent advances and future opportunities

Single-cell approaches are a promising way to obtain high-resolution transcriptomics data and have the potential to revolutionize the study of plant growth and development. Recent years have seen the advent of unprecedented technological advances in the field of plant biology to study the transcriptional information of individual cells by single-cell RNA sequencing (scRNA-seq). This review focuses on the modern advancements of single-cell transcriptomics in plants over the past few years. In addition, it also offers a new insight of how these emerging methods will expedite advance research in plant biotechnology in the near future. Lastly, the various technological hurdles and inherent limitations of single-cell technology that need to be conquered to develop such outstanding possible knowledge gain is critically analyzed and discussed.

Plant biotechnology research with single-cell transcriptome: recent advancements and prospects

KEY MESSAGE

Single-cell transcriptomic techniques have emerged as powerful tools in plant biology, offering high-resolution insights into gene expression at the individual cell level. This review highlights the rapid expansion of single-cell technologies in plants, their potential in understanding plant development, and their role in advancing plant biotechnology research. Single-cell techniques have emerged as powerful tools to enhance our understanding of biological systems, providing high-resolution transcriptomic analysis at the single-cell level. In plant biology, the adoption of single-cell transcriptomics has seen rapid expansion of available technologies and applications. This review article focuses on the latest advancements in the field of single-cell transcriptomic in plants and discusses the potential role of these approaches in plant development and expediting plant biotechnology research in the near future. Furthermore, inherent challenges and limitations of single-cell technology are critically examined to overcome them and enhance our knowledge and understanding.

Introducing single cell stereo-sequencing technology to transform the plant transcriptome landscape

Single cell RNA-sequencing (scRNA-seq) advancements have helped detect transcriptional heterogeneities in biological samples. However, scRNA-seq cannot currently provide high-resolution spatial transcriptome information or identify subcellular organs in biological samples. These limitations have led to the development of spatially enhanced-resolution omics-sequencing (Stereo-seq), which combines spatial information with single cell transcriptomics to address the challenges of scRNA-seq alone. In this review, we discuss the advantages of Stereo-seq technology. We anticipate that the application of such an integrated approach in plant research will advance our understanding of biological process in the plant transcriptomics era. We conclude with an outlook of how such integration will enhance crop improvement.

Lateral root primordium: Formation, influencing factors and regulation

Roots are the primary determinants of water and nutrient uptake by plants. The structure of roots is largely determined by the repeated formation of new lateral roots (LR). A new lateral root primordium (LRP) is formed between the beginning and appearance of LR, which defines the organization and function of LR. Therefore, proper LRP morphogenesis is a crucial process for lateral root formation. The development of LRP is regulated by multiple factors, including hormone and environmental signals. Roots integrate signals and regulate growth and development. At the molecular level, many genes regulate the growth and development of root organs to ensure stable development plans, while also being influenced by various environmental factors. To gain a better understanding of the LRP formation and its influencing factors, this study summarizes previous research. The cell cycle involved in LRP formation, as well as the roles of ROS, auxin, other auxin-related plant hormones, and genetic regulation, are discussed in detail. Additionally, the effects of gravity, mechanical stress, and cell death on LRP formation are explored. Throughout the text unanswered or poorly understood questions are identified to guide future research in this area.

Single-cell transcriptomic analysis of pea shoot development and cell-type-specific responses to boron deficiency

Understanding how nutrient stress impacts plant growth is fundamentally important to the development of approaches to improve crop production under nutrient limitation. Here we applied single-cell RNA sequencing to shoot apices of Pisum sativum grown under boron (B) deficiency. We identified up to 15 cell clusters based on the clustering of gene expression profiles and verified cell identity with cell-type-specific marker gene expression. Different cell types responded differently to B deficiency. Specifically, the expression of photosynthetic genes in mesophyll cells (MCs) was down-regulated by B deficiency, consistent with impaired photosynthetic rate. Furthermore, the down-regulation of stomatal development genes in guard cells, including homologs of MUTE and TOO MANY MOUTHS, correlated with a decrease in stomatal density under B deficiency. We also constructed the developmental trajectory of the shoot apical meristem (SAM) cells and a transcription factor interaction network. The developmental progression of SAM to MC was characterized by up-regulation of genes encoding histones and chromatin assembly and remodeling proteins including homologs of FASCIATA1 (FAS1) and SWITCH DEFECTIVE/SUCROSE NON-FERMENTABLE (SWI/SNF) complex. However, B deficiency suppressed their expression, which helps to explain impaired SAM development under B deficiency. These results represent a major advance over bulk-tissue RNA-seq analysis in which cell-type-specific responses are lost and hence important physiological responses to B deficiency are missed. The reported findings reveal strategies by which plants adapt to B deficiency thus offering breeders a set of specific targets for genetic improvement. The reported approach and resources have potential applications well beyond P. sativum species and could be applied to various legumes to improve their adaptability to multiple nutrient or abiotic stresses.

Time series single-cell transcriptional atlases reveal cell fate differentiation driven by light in Arabidopsis seedlings

Light serves as the energy source for plants as well as a signal for growth and development during their whole life cycle. Seedling de-etiolation is the most dramatic manifestation of light-regulated plant development processes, as massive reprogramming of the plant transcriptome occurs at this time. Although several studies have reported about organ-specific development and expression induced by light, a systematic analysis of cell-type-specific differentiation and the associated transcriptional regulation is still lacking. Here we obtained single-cell transcriptional atlases for etiolated, de-etiolating and light-grown Arabidopsis thaliana seedlings. Informative cells from shoot and root tissues were grouped into 48 different cell clusters and finely annotated using multiple markers. With the determination of comprehensive developmental trajectories, we demonstrate light modulation of cell fate determination during guard cell specialization and vasculature development. Comparison of expression atlases between wild type and the pifq mutant indicates that phytochrome-interacting factors (PIFs) are involved in distinct developmental processes in endodermal and stomatal lineage cells via controlling cell-type-specific expression of target genes. These results provide information concerning the light signalling networks at the cell-type resolution, improving our understanding of how light regulates plant development at the cell-type and genome-wide levels. The obtained information could serve as a valuable resource for comprehensively investigating the molecular mechanism of cell development and differentiation in response to light.

Resolving plant development in space and time with single-cell genomics

Single-cell genomics technologies are ushering in a new research era. In this review, we summarize the benefits and current challenges of using these technologies to probe the transcriptional regulation of plant development. In addition to profiling cells at a single snapshot in time, researchers have recently produced time-resolved datasets to map cell responses to stimuli. Live-imaging and spatial transcriptomic techniques are rapidly being adopted to link a cell's transcriptional profile with its spatial location within a tissue. Combining these technologies is a powerful spatiotemporal approach to investigate cell plasticity and developmental responses that contribute to plant resilience. Although there are hurdles to overcome, we conclude by discussing how single-cell genomics is poised to address developmental questions in the coming years.

How to explore what is hidden? A review of techniques for vascular tissue expression profile analysis

The evolution of plants to efficiently transport water and assimilates over long distances is a major evolutionary success that facilitated their growth and colonization of land. Vascular tissues, namely xylem and phloem, are characterized by high specialization, cell heterogeneity, and diverse cell components. During differentiation and maturation, these tissues undergo an irreversible sequence of events, leading to complete protoplast degradation in xylem or partial degradation in phloem, enabling their undisturbed conductive function. Due to the unique nature of vascular tissue, and the poorly understood processes involved in xylem and phloem development, studying the molecular basis of tissue differentiation is challenging. In this review, we focus on methods crucial for gene expression research in conductive tissues, emphasizing the importance of initial anatomical analysis and appropriate material selection. We trace the expansion of molecular techniques in vascular gene expression studies and discuss the application of single-cell RNA sequencing, a high-throughput technique that has revolutionized transcriptomic analysis. We explore how single-cell RNA sequencing will enhance our knowledge of gene expression in conductive tissues.

Transcriptional Landscape of Cotton Roots in Response to Salt Stress at Single-cell Resolution

Increasing soil salinization has led to severe losses of plant yield and quality. Thus, it is urgent to investigate the molecular mechanism of the salt stress response. In this study, we took systematically analyzed cotton root response to salt stress by single-cell transcriptomics technology; 56,281 high-quality cells were totally obtained from 5-days-old lateral root tips of Gossypium arboreum under natural growth and different salt-treatment conditions. Ten cell types with an array of novel marker genes were synthetically identified and confirmed with in situ RNA hybridization, and some specific-type cells of pesudotime analysis also pointed out their potential differentiation trajectory. The prominent changes of cell numbers responding to salt stress were observed on outer epidermal and inner endodermic cells, which were significantly enriched in response to stress, amide biosynthetic process, glutathione metabolism, and glycolysis/gluconeogenesis. Other functional aggregations were concentrated on plant-type primary cell wall biogenesis, defense response, phenylpropanoid biosynthesis and metabolic pathways by analyzing the abundant differentially expressed genes (DEGs) identified from multiple comparisons. Some candidate DEGs related with transcription factors and plant hormones responding to salt stress were also identified, of which the function of Ga03G2153, an annotated auxin-responsive GH3.6, was confirmed by using virus-induced gene silencing (VIGS). The GaGH3.6-silenced plants presented severe stress-susceptive phenotype, and suffered more serious oxidative damages by detecting some physiological and biochemical indexes, indicating that GaGH3.6 might participate in salt tolerance in cotton through regulating oxidation-reduction process. For the first time, a transcriptional atlas of cotton roots under salt stress were characterized at a single-cell resolution, which explored the cellular heterogeneityand differentiation trajectory, providing valuable insights into the molecular mechanism underlying stress tolerance in plants.

Trehalose-6-phosphate signaling regulates lateral root formation in Arabidopsis thaliana

Plant roots explore the soil for water and nutrients, thereby determining plant fitness and agricultural yield, as well as determining ground substructure, water levels, and global carbon sequestration. The colonization of the soil requires investment of carbon and energy, but how sugar and energy signaling are integrated with root branching is unknown. Here, we show through combined genetic and chemical modulation of signaling pathways that the sugar small-molecule signal, trehalose-6-phosphate (T6P) regulates root branching through master kinases SNF1-related kinase-1 (SnRK1) and Target of Rapamycin (TOR) and with the involvement of the plant hormone auxin. Increase of T6P levels both via genetic targeting in lateral root (LR) founder cells and through light-activated release of the presignaling T6P-precursor reveals that T6P increases root branching through coordinated inhibition of SnRK1 and activation of TOR. Auxin, the master regulator of LR formation, impacts this T6P function by transcriptionally down-regulating the T6P-degrader trehalose phosphate phosphatase B in LR cells. Our results reveal a regulatory energy-balance network for LR formation that links the 'sugar signal' T6P to both SnRK1 and TOR downstream of auxin.

Exploring the identity of individual plant cells in space and time

In recent years, single-cell genomics, coupled to imaging techniques, have become the state-of-the-art approach for characterising biological systems. In plant sciences, a variety of tissues and species have been profiled, providing an enormous quantity of data on cell identity at an unprecedented resolution, but what biological insights can be gained from such data sets? Using recently published studies in plant sciences, we will highlight how single-cell technologies have enabled a better comprehension of tissue organisation, cell fate dynamics in development or in response to various stimuli, as well as identifying key transcriptional regulators of cell identity. We discuss the limitations and technical hurdles to overcome, as well as future directions, and the promising use of single-cell omics to understand, predict, and manipulate plant development and physiology.

Application of single-cell multi-omics approaches in horticulture research

Cell heterogeneity shapes the morphology and function of various tissues and organs in multicellular organisms. Elucidation of the differences among cells and the mechanism of intercellular regulation is essential for an in-depth understanding of the developmental process. In recent years, the rapid development of high-throughput single-cell transcriptome sequencing technologies has influenced the study of plant developmental biology. Additionally, the accuracy and sensitivity of tools used to study the epigenome and metabolome have significantly increased, thus enabling multi-omics analysis at single-cell resolution. Here, we summarize the currently available single-cell multi-omics approaches and their recent applications in plant research, review the single-cell based studies in fruit, vegetable, and ornamental crops, and discuss the potential of such approaches in future horticulture research.

Opportunities and challenges in the application of single-cell and spatial transcriptomics in plants

Single-cell and spatial transcriptomics have diverted researchers' attention from the multicellular level to the single-cell level and spatial information. Single-cell transcriptomes provide insights into the transcriptome at the single-cell level, whereas spatial transcriptomes help preserve spatial information. Although these two omics technologies are helpful and mature, further research is needed to ensure their widespread applicability in plant studies. Reviewing recent research on plant single-cell or spatial transcriptomics, we compared the different experimental methods used in various plants. The limitations and challenges are clear for both single-cell and spatial transcriptomic analyses, such as the lack of applicability, spatial information, or high resolution. Subsequently, we put forth further applications, such as cross-species analysis of roots at the single-cell level and the idea that single-cell transcriptome analysis needs to be combined with other omics analyses to achieve superiority over individual omics analyses. Overall, the results of this review suggest that combining single-cell transcriptomics, spatial transcriptomics, and spatial element distribution can provide a promising research direction, particularly for plant research.

Analysis of meristems and plant regeneration at single-cell resolution

Rapid development of high-throughput single-cell RNA sequencing (scRNA-seq) technologies offers exciting opportunities to reveal new and rare cell types, previously hidden cell states, and continuous developmental trajectories. In this review, we first illustrate the ways in which scRNA-seq enables researchers to distinguish between distinct plant cell populations, delineate cell cycle continuums, and infer continuous differentiation trajectories of diverse cell types in shoots, roots, and floral and vascular meristems with unprecedented resolution. We then highlight the emerging power of scRNA-seq to dissect cell heterogeneity in regenerating tissues and uncover the cellular basis of cell reprogramming and stem cell commitment during plant regeneration. We conclude by discussing related outstanding questions in the field.

WUSCHEL-RELATED HOMEOBOX 13 suppresses de novo shoot regeneration via cell fate control of pluripotent callus

Plants can regenerate their bodies via de novo establishment of shoot apical meristems (SAMs) from pluripotent callus. Only a small fraction of callus cells is eventually specified into SAMs but the molecular mechanisms underlying fate specification remain obscure. The expression of WUSCHEL (WUS) is an early hallmark of SAM fate acquisition. Here, we show that a WUS paralog, WUSCHEL-RELATED HOMEOBOX 13 (WOX13), negatively regulates SAM formation from callus in Arabidopsis thaliana. WOX13 promotes non-meristematic cell fate via transcriptional repression of WUS and other SAM regulators and activation of cell wall modifiers. Our Quartz-Seq2-based single cell transcriptome revealed that WOX13 plays key roles in determining cellular identity of callus cell population. We propose that reciprocal inhibition between WUS and WOX13 mediates critical cell fate determination in pluripotent cell population, which has a major impact on regeneration efficiency.

Deciphering plant cell-cell communications using single-cell omics data

Plants have various cell types that respond to different environmental factors, and cell-cell communication is the fundamental process that controls these plant responses. The emergence of single-cell techniques provides opportunities to explore features unique to each cell type and construct a comprehensive cell-cell communication (CCC) network. Although the most current successes of CCC inference were achieved in animal research, computational methods can also be directly applied to plants. This review describes the current major models for cell-cell communication inference and summarizes the computational tools based on single-cell omics datasets. In addition, we discuss the limitations of plant cell-cell communication research and propose new directions to expand the field in meaningful ways.

An auxin-mediated ultradian rhythm positively influences root regeneration via EAR1/EUR1 in Arabidopsis

Ultradian rhythms have been proved to be critical for diverse biological processes. However, comprehensive understanding of the short-period rhythms remains limited. Here, we discover that leaf excision triggers a gene expression rhythm with ~3-h periodicity, named as the excision ultradian rhythm (UR), which is regulated by the plant hormone auxin. Promoter-luciferase analyses showed that the spatiotemporal patterns of the excision UR were positively associated with de novo root regeneration (DNRR), a post-embryonic developmental process. Transcriptomic analysis indicated more than 4,000 genes including DNRR-associated genes were reprogramed toward ultradian oscillation. Genetic studies showed that EXCISION ULTRADIAN RHYTHM 1 (EUR1) encoding ENHANCER OF ABSCISIC ACID CO-RECEPTOR1 (EAR1), an abscisic acid signaling regulator, was required to generate the excision ultradian rhythm and enhance root regeneration. The eur1 mutant exhibited the absence of auxin-induced excision UR generation and partial failure during rescuing root regeneration. Our results demonstrate a link between the excision UR and adventitious root formation via EAR1/EUR1, implying an additional regulatory layer in plant regeneration.

Lateral root branching: evolutionary innovations and mechanistic divergence in land plants

The root system architecture in plants is a result of multiple evolutionary innovations over time in response to changing environmental cues. Dichotomy and endogenous lateral branching in the roots evolved in lycophytes lineage but extant seed plants use lateral branching instead. This has led to the development of complex and adaptive root systems, with lateral roots playing a key role in this process exhibiting conserved and divergent features in different plant species. The study of lateral root branching in diverse plant species can shed light on the orderly yet distinct nature of postembryonic organogenesis in plants. This insight provides an overview of the diversity in lateral root (LR) development in various plant species during the evolution of root system in plants.

An integrase toolbox to record gene-expression during plant development

There are many open questions about the mechanisms that coordinate the dynamic, multicellular behaviors required for organogenesis. Synthetic circuits that can record in vivo signaling networks have been critical in elucidating animal development. Here, we report on the transfer of this technology to plants using orthogonal serine integrases to mediate site-specific and irreversible DNA recombination visualized by switching between fluorescent reporters. When combined with promoters expressed during lateral root initiation, integrases amplify reporter signal and permanently mark all descendants. In addition, we present a suite of methods to tune the threshold for integrase switching, including: RNA/protein degradation tags, a nuclear localization signal, and a split-intein system. These tools improve the robustness of integrase-mediated switching with different promoters and the stability of switching behavior over multiple generations. Although each promoter requires tuning for optimal performance, this integrase toolbox can be used to build history-dependent circuits to decode the order of expression during organogenesis in many contexts.

Going broad and deep: sequencing-driven insights into plant physiology, evolution, and crop domestication

Deep sequencing is a term that has become embedded in the plant genomic literature in recent years and with good reason. A torrent of (largely) high-quality genomic and transcriptomic data has been collected and most of this has been publicly released. Indeed, almost 1000 plant genomes have been reported (www.plabipd.de) and the 2000 Plant Transcriptomes Project has long been completed. The EarthBioGenome project will dwarf even these milestones. That said, massive progress in understanding plant physiology, evolution, and crop domestication has been made by sequencing broadly (across a species) as well as deeply (within a single individual). We will outline the current state of the art in genome and transcriptome sequencing before we briefly review the most visible of these broad approaches, namely genome-wide association and transcriptome-wide association studies, as well as the compilation of pangenomes. This will include both (i) the most commonly used methods reliant on single nucleotide polymorphisms and short InDels and (ii) more recent examples which consider structural variants. We will subsequently present case studies exemplifying how their application has brought insight into either plant physiology or evolution and crop domestication. Finally, we will provide conclusions and an outlook as to the perspective for the extension of such approaches to different species, tissues, and biological processes.

Single-cell analysis opens a goldmine for plant functional studies

Functional studies in biology require the identification of genes, regulatory elements, and networks, followed by a deep understanding of how they orchestrate to specify cell types, mediate signaling, and respond to internal and external cues over evolutionary timescales. Advances in single-cell analysis have enabled biologists to tackle these questions at the resolution of the individual cell. Here, we highlight recent studies in plants that have embraced single-cell analyses to facilitate functional studies. This review will provide guidance and perspectives for incorporating these advanced approaches in plant research for the coming decades.

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.