Dynamics of Gene Expression in Single Root Cells of Arabidopsis thaliana

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.

Genome organization and botanical diversity

The rich diversity of angiosperms, both the planet's dominant flora and the cornerstone of agriculture, is integrally intertwined with a distinctive evolutionary history. Here, we explore the interplay between angiosperm genome organization and botanical diversity, empowered by genomic approaches ranging from genetic linkage mapping to analysis of gene regulation. Commonality in the genetic hardware of plants has enabled robust comparative genomics that has provided a broad picture of angiosperm evolution and implicated both general processes and specific elements in contributing to botanical diversity. We argue that the hardware of plant genomes-both in content and in dynamics-has been shaped by selection for rather substantial differences in gene regulation between plants and animals such as maize and human, organisms of comparable genome size and gene number. Their distinctive genome content and dynamics may reflect in part the indeterminate development of plants that puts strikingly different demands on gene regulation than in animals. Repeated polyploidization of plant genomes and multiplication of individual genes together with extensive rearrangement and differential retention provide rich raw material for selection of morphological and/or physiological variations conferring fitness in specific niches, whether natural or artificial. These findings exemplify the burgeoning information available to employ in increasing knowledge of plant biology and in modifying selected plants to better meet human needs.

Nitrogen sensing and regulatory networks: it's about time and space

A plant's response to external and internal nitrogen signals/status relies on sensing and signaling mechanisms that operate across spatial and temporal dimensions. From a comprehensive systems biology perspective, this involves integrating nitrogen responses in different cell types and over long distances to ensure organ coordination in real time and yield practical applications. In this prospective review, we focus on novel aspects of nitrogen (N) sensing/signaling uncovered using temporal and spatial systems biology approaches, largely in the model Arabidopsis. The temporal aspects span: transcriptional responses to N-dose mediated by Michaelis-Menten kinetics, the role of the master NLP7 transcription factor as a nitrate sensor, its nitrate-dependent TF nuclear retention, its "hit-and-run" mode of target gene regulation, and temporal transcriptional cascade identified by "network walking." Spatial aspects of N-sensing/signaling have been uncovered in cell type-specific studies in roots and in root-to-shoot communication. We explore new approaches using single-cell sequencing data, trajectory inference, and pseudotime analysis as well as machine learning and artificial intelligence approaches. Finally, unveiling the mechanisms underlying the spatial dynamics of nitrogen sensing/signaling networks across species from model to crop could pave the way for translational studies to improve nitrogen-use efficiency in crops. Such outcomes could potentially reduce the detrimental effects of excessive fertilizer usage on groundwater pollution and greenhouse gas emissions.

Sugar transporters spatially organize microbiota colonization along the longitudinal root axis of Arabidopsis

Plant roots are functionally heterogeneous in cellular architecture, transcriptome profile, metabolic state, and microbial immunity. We hypothesized that axial differentiation may also impact spatial colonization by root microbiota along the root axis. We developed two growth systems, ArtSoil and CD-Rhizotron, to grow and then dissect Arabidopsis thaliana roots into three segments. We demonstrate that distinct endospheric and rhizosphere bacterial communities colonize the segments, supporting the hypothesis of microbiota differentiation along the axis. Root metabolite profiling of each segment reveals differential metabolite enrichment and specificity. Bioinformatic analyses and GUS histochemistry indicate microbe-induced accumulation of SWEET2, 4, and 12 sugar uniporters. Profiling of root segments from sweet mutants shows altered spatial metabolic profiles and reorganization of endospheric root microbiota. This work reveals the interdependency between root metabolites and microbial colonization and the contribution of SWEETs to spatial diversity and stability of microbial ecosystem.

Following the p63/Keratin5 basal cells in the sensory and non-sensory epithelia of the vomeronasal organ

The vomeronasal organ (VNO) is a part of the accessory olfactory system, which detects pheromones and chemical factors that trigger a spectrum of sexual and social behaviors. The vomeronasal epithelium (VNE) shares several features with the epithelium of the main olfactory epithelium (MOE). However, it is a distinct neuroepithelium populated by chemosensory neurons that differ from the olfactory sensory neurons in cellular structure, receptor expression, and connectivity. The vomeronasal organ of rodents comprises a sensory epithelium (SE) and a thin non-sensory epithelium (NSE) that morphologically resembles the respiratory epithelium. Sox2-positive cells have been previously identified as the stem cell population that gives rise to neuronal progenitors in MOE and VNE. In addition, the MOE also comprises p63 positive horizontal basal cells, a second pool of quiescent stem cells that become active in response to injury. Immunolabeling against the transcription factor p63, Keratin-5 (Krt5), Krt14, NrCAM, and Krt5Cre tracing experiments highlighted the existence of horizontal basal cells distributed along the basal lamina of SE of the VNO. Single cell sequencing and genetic lineage tracing suggest that the vomeronasal horizontal basal cells arise from basal progenitors at the boundary between the SE and NSE proximal to the marginal zones. Moreover, our experiments revealed that the NSE of rodents is, like the respiratory epithelium, a stratified epithelium where the p63/Krt5+ basal progenitor cells self-replicate and give rise to the apical columnar cells facing the lumen of the VNO.

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.

Advances in the Application of Single-Cell Transcriptomics in Plant Systems and Synthetic Biology

Plants are complex systems hierarchically organized and composed of various cell types. To understand the molecular underpinnings of complex plant systems, single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for revealing high resolution of gene expression patterns at the cellular level and investigating the cell-type heterogeneity. Furthermore, scRNA-seq analysis of plant biosystems has great potential for generating new knowledge to inform plant biosystems design and synthetic biology, which aims to modify plants genetically/epigenetically through genome editing, engineering, or re-writing based on rational design for increasing crop yield and quality, promoting the bioeconomy and enhancing environmental sustainability. In particular, data from scRNA-seq studies can be utilized to facilitate the development of high-precision Build-Design-Test-Learn capabilities for maximizing the targeted performance of engineered plant biosystems while minimizing unintended side effects. To date, scRNA-seq has been demonstrated in a limited number of plant species, including model plants (e.g., Arabidopsis thaliana), agricultural crops (e.g., Oryza sativa), and bioenergy crops (e.g., Populus spp.). It is expected that future technical advancements will reduce the cost of scRNA-seq and consequently accelerate the application of this emerging technology in plants. In this review, we summarize current technical advancements in plant scRNA-seq, including sample preparation, sequencing, and data analysis, to provide guidance on how to choose the appropriate scRNA-seq methods for different types of plant samples. We then highlight various applications of scRNA-seq in both plant systems biology and plant synthetic biology research. Finally, we discuss the challenges and opportunities for the application of scRNA-seq in plants.

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.

Single-cell transcriptome analysis dissects lncRNA-associated gene networks in Arabidopsis

The plant genome produces an extremely large collection of long noncoding RNAs (lncRNAs) that are generally expressed in a context-specific manner and have pivotal roles in regulation of diverse biological processes. Here, we mapped the transcriptional heterogeneity of lncRNAs and their associated gene regulatory networks at single-cell resolution. We generated a comprehensive cell atlas at the whole-organism level by integrative analysis of 28 published single-cell RNA sequencing (scRNA-seq) datasets from juvenile Arabidopsis seedlings. We then provided an in-depth analysis of cell-type-related lncRNA signatures that show expression patterns consistent with canonical protein-coding gene markers. We further demonstrated that the cell-type-specific expression of lncRNAs largely explains their tissue specificity. In addition, we predicted gene regulatory networks on the basis of motif enrichment and co-expression analysis of lncRNAs and mRNAs, and we identified putative transcription factors orchestrating cell-type-specific expression of lncRNAs. The analysis results are available at the single-cell-based plant lncRNA atlas database (scPLAD; https://biobigdata.nju.edu.cn/scPLAD/). Overall, this work demonstrates the power of integrative single-cell data analysis applied to plant lncRNA biology and provides fundamental insights into lncRNA expression specificity and associated gene regulation.

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.

Single-Cell Transcriptome Atlas and Regulatory Dynamics in Developing Cotton Anthers

Plant anthers are composed of different specialized cell types with distinct roles in plant reproduction. High temperature (HT) stress causes male sterility, resulting in crop yield reduction. However, the spatial expression atlas and regulatory dynamics during anther development and in response to HT remain largely unknown. Here, the first single-cell transcriptome atlas and chromatin accessibility survey in cotton anther are established, depicting the specific expression and epigenetic landscape of each type of cell in anthers. The reconstruction of meiotic cells, tapetal cells, and middle layer cell developmental trajectories not only identifies novel expressed genes, but also elucidates the precise degradation period of middle layer and reveals a rapid function transition of tapetal cells during the tetrad stage. By applying HT, heterogeneity in HT response is shown among cells of anthers, with tapetal cells responsible for pollen wall synthesis are most sensitive to HT. Specifically, HT shuts down the chromatin accessibility of genes specifically expressed in the tapetal cells responsible for pollen wall synthesis, such as QUARTET 3 (QRT3) and CYTOCHROME P450 703A2 (CYP703A2), resulting in a silent expression of these genes, ultimately leading to abnormal pollen wall and male sterility. Collectively, this study provides substantial information on anthers and provides clues for heat-tolerant crop creation.

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.

Coexpression enhances cross-species integration of scRNA-seq across diverse plant species

Single-cell RNA sequencing is increasingly used to investigate cross-species differences driven by gene expression and cell-type composition in plants. However, the frequent expansion of plant gene families due to whole genome duplications makes identification of one-to-one orthologs difficult, complicating integration. Here, we demonstrate that coexpression can be used to identify non-orthologous gene pairs with proxy expression profiles, improving the performance of traditional integration methods and reducing barriers to integration across a diverse array of plant species.

Leveraging Single-Cell Populations to Uncover the Genetic Basis of Complex Traits

The ease and throughput of single-cell genomics have steadily improved, and its current trajectory suggests that surveying single-cell populations will become routine. We discuss the merger of quantitative genetics with single-cell genomics and emphasize how this synergizes with advantages intrinsic to plants. Single-cell population genomics provides increased detection resolution when mapping variants that control molecular traits, including gene expression or chromatin accessibility. Additionally, single-cell population genomics reveals the cell types in which variants act and, when combined with organism-level phenotype measurements, unveils which cellular contexts impact higher-order traits. Emerging technologies, notably multiomics, can facilitate the measurement of both genetic changes and genomic traits in single cells, enabling single-cell genetic experiments. The implementation of single-cell genetics will advance the investigation of the genetic architecture of complex molecular traits and provide new experimental paradigms to study eukaryotic genetics.

Application and prospects of single-cell and spatial omics technologies in woody plants

Over the past decade, high-throughput sequencing and high-resolution single-cell transcriptome sequencing technologies have undergone rapid development, leading to significant breakthroughs. Traditional molecular biology methods are limited in their ability to unravel cellular-level heterogeneity within woody plant tissues. Consequently, techniques such as single-cell transcriptomics, single-cell epigenetics, and spatial transcriptomics are rapidly gaining popularity in the study of woody plants. In this review, we provide a comprehensive overview of the development of these technologies, with a focus on their applications and the challenges they present in single-cell transcriptome research in woody plants. In particular, we delve into the similarities and differences among the results of current studies and analyze the reasons behind these differences. Furthermore, we put forth potential solutions to overcome the challenges encountered in single-cell transcriptome applications in woody plants. Finally, we discuss the application directions of these techniques to address key challenges in woody plant research in the future.

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.

Proteostasis governs differential temperature sensitivity across embryonic cell types

Embryonic development is remarkably robust, but temperature stress can degrade its ability to generate animals with invariant anatomy. Phenotypes associated with environmental stress suggest that some cell types are more sensitive to stress than others, but the basis of this sensitivity is unknown. Here, we characterize hundreds of individual zebrafish embryos under temperature stress using whole-animal single-cell RNA sequencing (RNA-seq) to identify cell types and molecular programs driving phenotypic variability. We find that temperature perturbs the normal proportions and gene expression programs of numerous cell types and also introduces asynchrony in developmental timing. The notochord is particularly sensitive to temperature, which we map to a specialized cell type: sheath cells. These cells accumulate misfolded protein at elevated temperature, leading to a cascading structural failure of the notochord and anatomic defects. Our study demonstrates that whole-animal single-cell RNA-seq can identify mechanisms for developmental robustness and pinpoint cell types that constitute key failure points.

Chromosome-level genomes of three key Allium crops and their trait evolution

Allium crop breeding remains severely hindered due to the lack of high-quality reference genomes. Here we report high-quality chromosome-level genome assemblies for three key Allium crops (Welsh onion, garlic and onion), which are 11.17 Gb, 15.52 Gb and 15.78 Gb in size with the highest recorded contig N50 of 507.27 Mb, 109.82 Mb and 81.66 Mb, respectively. Beyond revealing the genome evolutionary process of Allium species, our pathogen infection experiments and comparative metabolomic and genomic analyses showed that genes encoding enzymes involved in the metabolic pathway of Allium-specific flavor compounds may have evolved from an ancient uncharacterized plant defense system widely existing in many plant lineages but extensively boosted in alliums. Using in situ hybridization and spatial RNA sequencing, we obtained an overview of cell-type categorization and gene expression changes associated with spongy mesophyll cell expansion during onion bulb formation, thus indicating the functional roles of bulb formation genes.

Single cell RNA-seq in phytohormone signaling: a promising future

Phytohormone signaling regulates plant growth and development. Single cell RNA sequencing (scRNA-seq) provides unprecedented opportunities to decipher hormone-mediated spatiotemporal gene regulatory networks. In a recent study, Nolan et al. used time-series scRNA-seq to identify the cortex as a key site for brassinosteroid (BR)-mediated gene expression and revealed a signaling network during cell phase transition.

Endoreduplication in plant organogenesis: a means to boost fruit growth

Endoreduplication is the major source of somatic endopolyploidy in higher plants, and leads to variation in cell ploidy levels due to iterative rounds of DNA synthesis in the absence of mitosis. Despite its ubiquitous occurrence in many plant organs, tissues, and cells, the physiological meaning of endoreduplication is not fully understood, although several roles during plant development have been proposed, mostly related to cell growth, differentiation, and specialization via transcriptional and metabolic reprogramming. Here, we review recent advances in our knowledge of the molecular mechanisms and cellular characteristics of endoreduplicated cells, and provide an overview of the multi-scale effects of endoreduplication on supporting growth in plant development. In addition, the effects of endoreduplication in fruit development are discussed, since it is highly prominent during fruit organogenesis where it acts as a morphogenetic factor supporting rapid fruit growth, as illustrated by case of the model fleshy fruit, tomato (Solanum lycopersicum).

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.

Spatial regulation of plant hormone action

Although many plant cell types are capable of producing hormones, and plant hormones can in most cases act in the same cells in which they are produced, they also act as signaling molecules that coordinate physiological responses between different parts of the plant, indicating that their action is subject to spatial regulation. Numerous publications have reported that all levels of plant hormonal pathways, namely metabolism, transport, and perception/signal transduction, can help determine the spatial ranges of hormone action. For example, polar auxin transport or localized auxin biosynthesis contribute to creating a differential hormone accumulation across tissues that is instrumental for specific growth and developmental responses. On the other hand, tissue specificity of cytokinin actions has been proposed to be regulated by mechanisms operating at the signaling stages. Here, we review and discuss current knowledge about the contribution of the three levels mentioned above in providing spatial specificity to plant hormone action. We also explore how new technological developments, such as plant hormone sensors based on FRET (fluorescence resonance energy transfer) or single-cell RNA-seq, can provide an unprecedented level of resolution in defining the spatial domains of plant hormone action and its dynamics.

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.

scPlant: A versatile framework for single-cell transcriptomic data analysis in plants

Single-cell transcriptomics has been fully embraced in plant biological research and is revolutionizing our understanding of plant growth, development, and responses to external stimuli. However, single-cell transcriptomic data analysis in plants is not trivial, given that there is currently no end-to-end solution and that integration of various bioinformatics tools involves a large number of required dependencies. Here, we present scPlant, a versatile framework for exploring plant single-cell atlases with minimum input data provided by users. The scPlant pipeline is implemented with numerous functions for diverse analytical tasks, ranging from basic data processing to advanced demands such as cell-type annotation and deconvolution, trajectory inference, cross-species data integration, and cell-type-specific gene regulatory network construction. In addition, a variety of visualization tools are bundled in a built-in Shiny application, enabling exploration of single-cell transcriptomic data on the fly.

Epigenetic and transcription factors synergistically promote the high temperature response in plants

Temperature is one of the main environmental cues affecting plant growth and development, and plants have evolved multiple mechanisms to sense and acclimate to high temperature. Emerging research has shown that transcription factors, epigenetic factors, and their coordination are essential for plant temperature responses and the resulting phenological adaptation. Here, we summarize recent advances in molecular and cellular mechanisms to understand how plants acclimate to high temperature and describe how plant meristems sense and integrate environmental signals. Furthermore, we lay out future directions for new technologies to reveal heterogeneous responses in different cell types thus improving plant environmental plasticity.

Single-cell RNA sequencing profiles reveal cell type-specific transcriptional regulation networks conditioning fungal invasion in maize roots

Stalk rot caused by Fusarium verticillioides (Fv) is one of the most destructive diseases in maize production. The defence response of root system to Fv invasion is important for plant growth and development. Dissection of root cell type-specific response to Fv infection and its underlying transcription regulatory networks will aid in understanding the defence mechanism of maize roots to Fv invasion. Here, we reported the transcriptomes of 29 217 single cells derived from root tips of two maize inbred lines inoculated with Fv and mock condition, and identified seven major cell types with 21 transcriptionally distinct cell clusters. Through the weighted gene co-expression network analysis, we identified 12 Fv-responsive regulatory modules from 4049 differentially expressed genes (DEGs) that were activated or repressed by Fv infection in these seven cell types. Using a machining-learning approach, we constructed six cell type-specific immune regulatory networks by integrating Fv-induced DEGs from the cell type-specific transcriptomes, 16 known maize disease-resistant genes, five experimentally validated genes (ZmWOX5b, ZmPIN1a, ZmPAL6, ZmCCoAOMT2, and ZmCOMT), and 42 QTL or QTN predicted genes that are associated with Fv resistance. Taken together, this study provides not only a global view of maize cell fate determination during root development but also insights into the immune regulatory networks in major cell types of maize root tips at single-cell resolution, thus laying the foundation for dissecting molecular mechanisms underlying disease resistance in maize.

Single-cell resolution analysis reveals the preparation for reprogramming the fate of stem cell niche in cotton lateral meristem

BACKGROUND

Somatic embryogenesis is a major process for plant regeneration. However, cell communication and the gene regulatory network responsible for cell reprogramming during somatic embryogenesis are still largely unclear. Recent advances in single-cell technologies enable us to explore the mechanism of plant regeneration at single-cell resolution.

RESULTS

We generate a high-resolution single-cell transcriptomic landscape of hypocotyl tissue from the highly regenerable cotton genotype Jin668 and the recalcitrant TM-1. We identify nine putative cell clusters and 23 cluster-specific marker genes for both cultivars. We find that the primary vascular cell is the major cell type that undergoes cell fate transition in response to external stimulation. Further developmental trajectory and gene regulatory network analysis of these cell clusters reveals that a total of 41 hormone response-related genes, including LAX2, LAX1, and LOX3, exhibit different expression patterns in the primary xylem and cambium region of Jin668 and TM-1. We also identify novel genes, including CSEF, PIS1, AFB2, ATHB2, PLC2, and PLT3, that are involved in regeneration. We demonstrate that LAX2, LAX1 and LOX3 play important roles in callus proliferation and plant regeneration by CRISPR/Cas9 editing and overexpression assay.

CONCLUSIONS

This study provides novel insights on the role of the regulatory network in cell fate transition and reprogramming during plant regeneration driven by somatic embryogenesis.

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.

Application of Multi-Perspectives in Tea Breeding and the Main Directions

Tea plants are an economically important crop and conducting research on tea breeding contributes to enhancing the yield and quality of tea leaves as well as breeding traits that satisfy the requirements of the public. This study reviews the current status of tea plants germplasm resources and their utilization, which has provided genetic material for the application of multi-omics, including genomics and transcriptomics in breeding. Various molecular markers for breeding were designed based on multi-omics, and available approaches in the direction of high yield, quality and resistance in tea plants breeding are proposed. Additionally, future breeding of tea plants based on single-cellomics, pangenomics, plant-microbe interactions and epigenetics are proposed and provided as references. This study aims to provide inspiration and guidance for advancing the development of genetic breeding in tea plants, as well as providing implications for breeding research in other crops.

The maturation and aging trajectory of Marchantia polymorpha at single-cell resolution

Bryophytes represent a sister to the rest of land plants. Despite their evolutionary importance and relatively simple body plan, a comprehensive understanding of the cell types and transcriptional states that underpin the temporal development of bryophytes has not been achieved. Using time-resolved single-cell RNA sequencing, we define the cellular taxonomy of Marchantia polymorpha across asexual reproduction phases. We identify two maturation and aging trajectories of the main plant body of M. polymorpha at single-cell resolution: the gradual maturation of tissues and organs along the tip-to-base axis of the midvein and the progressive decline of meristem activities in the tip along the chronological axis. Specifically, we observe that the latter aging axis is temporally correlated with the formation of clonal propagules, suggesting an ancient strategy to optimize allocation of resources to producing offspring. Our work thus provides insights into the cellular heterogeneity that underpins the temporal development and aging of bryophytes.

Plant environmental memory: implications, mechanisms and opportunities for plant scientists and beyond

Plants are extremely plastic organisms. They continuously receive and integrate environmental information and adjust their growth and development to favour fitness and survival. When this integration of information affects subsequent life stages or the development of subsequent generations, it can be considered an environmental memory. Thus, plant memory is a relevant mechanism by which plants respond adaptively to different environments. If the cost of maintaining the response is offset by its benefits, it may influence evolutionary trajectories. As such, plant memory has a sophisticated underlying molecular mechanism with multiple components and layers. Nonetheless, when mathematical modelling is combined with knowledge of ecological, physiological, and developmental effects as well as molecular mechanisms as a tool for understanding plant memory, the combined potential becomes unfathomable for the management of plant communities in natural and agricultural ecosystems. In this review, we summarize recent advances in the understanding of plant memory, discuss the ecological requirements for its evolution, outline the multilayered molecular network and mechanisms required for accurate and fail-proof plant responses to variable environments, point out the direct involvement of the plant metabolism and discuss the tremendous potential of various types of models to further our understanding of the plant's environmental memory. Throughout, we emphasize the use of plant memory as a tool to unlock the secrets of the natural world.

Single-cell transcriptomic analyses reveal cellular and molecular patterns of rubber tree response to early powdery mildew infection

As a perennial woody plant, the rubber tree (Hevea brasiliensis) must adapt to various environmental challenges through gene expression in multiple cell types. It is still unclear how genes in this species are expressed at the cellular level and the precise mechanisms by which cells respond transcriptionally to environmental stimuli, especially in the case of pathogen infection. Here, we characterized the transcriptomes in Hevea leaves during early powdery mildew infection using single-cell RNA sequencing. We identified 10 cell types and constructed the first single-cell atlas of Hevea leaves. Distinct gene expression patterns of the cell clusters were observed under powdery mildew infection, which was especially significant in the epidermal cells. Most of the genes involved in host-pathogen interactions in epidermal cells exhibited a pattern of dramatically increased expression with increasing pseudotime. Interestingly, we found that the HbCNL2 gene, encoding a nucleotide-binding leucine-rich repeat protein, positively modulated the defence of rubber leaves against powdery mildew. Overexpression of the HbCNL2 gene triggered a typical cell death phenotype in tobacco leaves and a higher level of reactive oxygen species in the protoplasts of Hevea leaves. The HbCNL2 protein was located in the cytomembrane and nucleus, and its leucine-rich repeat domain interacted with the histidine kinase-like ATPase domain of the molecular chaperone HbHSP90 in the nucleus. Collectively, our results provide the first observation of the cellular and molecular responses of Hevea leaves to biotrophic pathogen infection and can guide the identification of disease-resistance genes in this important tree species.

Development of High-Quality Nuclei Isolation to Study Plant Root-Microbe Interaction for Single-Nuclei Transcriptomic Sequencing in Soybean

Single-nucleus RNA sequencing (sNucRNA-seq) is an emerging technology that has been rapidly adopted and demonstrated to be a powerful tool for detailed characterization of each cell- and sub cell-types in complex tissues of higher eukaryotes. sNucRNA-seq has also been used to dissect cell-type-specific transcriptional responses to environmental or developmental signals. In plants, this technology is being utilized to identify cell-type-specific trajectories for the study of several tissue types and important traits, including the single-cell dissection of the genetic determinants regulating plant-microbe interactions. The isolation of high-quality nuclei is one of the prerequisite steps to obtain high-quality sNucRNA-seq results. Although nuclei isolation from several plant tissues is well established, this process is highly troublesome when plant tissues are associated with beneficial or pathogenic microbes. For example, root tissues colonized with rhizobium bacteria (nodules), leaf tissue infected with bacterial or fungal pathogens, or roots infected with nematodes pose critical challenges to the isolation of high-quality nuclei and use for downstream application. Therefore, isolation of microbe-free, high-quality nuclei from plant tissues are necessary to avoid clogging or interference with the microfluidic channel (e.g., 10× Genomics) or particle-templated emulsion that are used in sNucRNA-seq platforms. Here, we developed a simple, effective, and efficient method to isolate high-quality nuclei from soybean roots and root nodules, followed by washing out bacterial contamination. This protocol has been designed to be easily implemented into any lab environment, and it can also be scaled up for use with multiple samples and applicable to a variety of samples with the presence of microbes. We validated this protocol by successfully generating a barcoded library using the 10× Genomics microfluidic platform from tissue subjected to this procedure. This workflow was developed to provide an accessible alternative to instrument-based approaches (e.g., fluorescent cell sorting) and will expand the ability of researchers to perform experiments such as sNucRNA-seq and sNucATAC-seq on inherently heterogeneous plant tissue samples.

Inferring cell diversity in single cell data using consortium-scale epigenetic data as a biological anchor for cell identity

Methods for cell clustering and gene expression from single-cell RNA sequencing (scRNA-seq) data are essential for biological interpretation of cell processes. Here, we present TRIAGE-Cluster which uses genome-wide epigenetic data from diverse bio-samples to identify genes demarcating cell diversity in scRNA-seq data. By integrating patterns of repressive chromatin deposited across diverse cell types with weighted density estimation, TRIAGE-Cluster determines cell type clusters in a 2D UMAP space. We then present TRIAGE-ParseR, a machine learning method which evaluates gene expression rank lists to define gene groups governing the identity and function of cell types. We demonstrate the utility of this two-step approach using atlases of in vivo and in vitro cell diversification and organogenesis. We also provide a web accessible dashboard for analysis and download of data and software. Collectively, genome-wide epigenetic repression provides a versatile strategy to define cell diversity and study gene regulation of scRNA-seq data.

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.

Single-cell and spatial multi-omics in the plant sciences: Technical advances, applications, and perspectives

Plants contain a large number of cell types and exhibit complex regulatory mechanisms. Studies at the single-cell level have gradually become more common in plant science. Single-cell transcriptomics, spatial transcriptomics, and spatial metabolomics techniques have been combined to analyze plant development. These techniques have been used to study the transcriptomes and metabolomes of plant tissues at the single-cell level, enabling the systematic investigation of gene expression and metabolism in specific tissues and cell types during defined developmental stages. In this review, we present an overview of significant breakthroughs in spatial multi-omics in plants, and we discuss how these approaches may soon play essential roles in plant research.

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.

Single-cell transcriptomic analysis reveals the developmental trajectory and transcriptional regulatory networks of pigment glands in Gossypium bickii

Comprehensive utilization of cottonseeds is limited by the presence of pigment glands and its inclusion gossypol. The ideal cotton has glandless seeds but a glanded plant, a trait found in only a few Australian wild cotton species, including Gossypium bickii. Introgression of this trait into cultivated species has proved to be difficult. Understanding the biological processes toward pigment gland morphogenesis and the associated underlying molecular mechanisms will facilitate breeding of cultivated cotton varieties with the trait of glandless seeds and glanded plant. In this study, single-cell RNA sequencing (scRNA-seq) was performed on 12 222 protoplasts isolated from cotyledons of germinating G. bickii seeds 48 h after imbibition. Clustered into 14 distinct clusters unsupervisedly, these cells could be grouped into eight cell populations with the assistance of known cell marker genes. The pigment gland cells were well separated from others and could be separated into pigment gland parenchyma cells, secretory cells, and apoptotic cells. By integrating the pigment gland cell developmental trajectory, transcription factor regulatory networks, and core transcription factor functional validation, we established a model for pigment gland formation. In this model, light and gibberellin were verified to promote the formation of pigment glands. In addition, three novel genes, GbiERF114 (ETHYLENE RESPONSE FACTOR 114), GbiZAT11 (ZINC FINGER OF ARABIDOPSIS THALIANA 11), and GbiNTL9 (NAC TRANSCRIPTION FACTOR-LIKE 9), were found to affect pigment gland formation. Collectively, these findings provide new insights into pigment gland morphogenesis and lay the cornerstone for future cotton scRNA-seq investigations.

Single-nucleus sequencing deciphers developmental trajectories in rice pistils

Angiosperms possess a life cycle with an alternation of sporophyte and gametophyte generations, which happens in plant organs like pistils. Rice pistils contain ovules and receive pollen for successful fertilization to produce grains. The cellular expression profile in rice pistils is largely unknown. Here, we show a cell census of rice pistils before fertilization through the use of droplet-based single-nucleus RNA sequencing. The ab initio marker identification validated by in situ hybridization assists with cell-type annotation, revealing cell heterogeneity between ovule- and carpel-originated cells. A comparison of 1N (gametophyte) and 2N (sporophyte) nuclei identifies the developmental path of germ cells in ovules with typical resetting of pluripotency before the sporophyte-gametophyte transition, while trajectory analysis of carpel-originated cells suggests previously neglected features of epidermis specification and style function. These findings gain a systems-level view of cellular differentiation and development of rice pistils before flowering and lay a foundation for understanding female reproductive development in plants.

Cell-specific clock-controlled gene expression program regulates rhythmic fiber cell growth in cotton

BACKGROUND

The epidermis of cotton ovule produces fibers, the most important natural cellulose source for the global textile industry. However, the molecular mechanism of fiber cell growth is still poorly understood.

RESULTS

Here, we develop an optimized protoplasting method, and integrate single-cell RNA sequencing (scRNA-seq) and single-cell ATAC sequencing (scATAC-seq) to systematically characterize the cells of the outer integument of ovules from wild type and fuzzless/lintless (fl) cotton (Gossypium hirsutum). By jointly analyzing the scRNA-seq data from wildtype and fl, we identify five cell populations including the fiber cell type and construct the development trajectory for fiber lineage cells. Interestingly, by time-course diurnal transcriptomic analysis, we demonstrate that the primary growth of fiber cells is a highly regulated circadian rhythmic process. Moreover, we identify a small peptide GhRALF1 that circadian rhythmically controls fiber growth possibly through oscillating auxin signaling and proton pump activity in the plasma membrane. Combining with scATAC-seq, we further identify two cardinal cis-regulatory elements (CREs, TCP motif, and TCP-like motif) which are bound by the trans factors GhTCP14s to modulate the circadian rhythmic metabolism of mitochondria and protein translation through regulating approximately one third of genes that are highly expressed in fiber cells.

CONCLUSIONS

We uncover a fiber-specific circadian clock-controlled gene expression program in regulating fiber growth. This study unprecedentedly reveals a new route to improve fiber traits by engineering the circadian clock of fiber cells.

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 transcriptomics unveils xylem cell development and evolution

BACKGROUND

Xylem, the most abundant tissue on Earth, is responsible for lateral growth in plants. Typical xylem has a radial system composed of ray parenchyma cells and an axial system of fusiform cells. In most angiosperms, fusiform cells comprise vessel elements for water transportation and libriform fibers for mechanical support, while both functions are performed by tracheids in other vascular plants such as gymnosperms. Little is known about the developmental programs and evolutionary relationships of these xylem cell types.

RESULTS

Through both single-cell and laser capture microdissection transcriptomic profiling, we determine the developmental lineages of ray and fusiform cells in stem-differentiating xylem across four divergent woody angiosperms. Based on cross-species analyses of single-cell clusters and overlapping trajectories, we reveal highly conserved ray, yet variable fusiform, lineages across angiosperms. Core eudicots Populus trichocarpa and Eucalyptus grandis share nearly identical fusiform lineages, whereas the more basal angiosperm Liriodendron chinense has a fusiform lineage distinct from that in core eudicots. The tracheids in the basal eudicot Trochodendron aralioides, an evolutionarily reversed trait, exhibit strong transcriptomic similarity to vessel elements rather than libriform fibers.

CONCLUSIONS

This evo-devo framework provides a comprehensive understanding of the formation of xylem cell lineages across multiple plant species spanning over a hundred million years of evolutionary history.

Single-cell transcriptome sequencing atlas of cassava tuberous root

INTRODUCTION

Single-cell transcriptome sequencing (ScRNA-seq) has emerged as an effective method for examining cell differentiation and development. In non-model plants, it hasn't been employed very much, especially in sink organs that are abundant in secondary metabolites.

RESULTS

In this study, we sequenced the single-cell transcriptomes at two developmental phases of cassava tuberous roots using the technology known as 10x Genomics (S1, S2). In total, 14,566 cells were grouped into 15 different cell types, primarily based on the marker genes of model plants known to exist. In the pseudotime study, the cell differentiation trajectory was defined, and the difference in gene expression between the two stages on the pseudotime axis was compared. The differentiation process of the vascular tissue and cerebral tissue was identified by the trajectory. We discovered the rare cell type known as the casparian strip via the use of up-regulated genes and pseudotime analysis, and we explained how it differentiates from endodermis. The successful creation of a protoplast isolation technique for organs rich in starch was also described in our study.

DISCUSSION

Together, we created the first high-resolution single-cell transcriptome atlas of cassava tuberous roots, which made significant advancements in our understanding of how these roots differentiate and develop.

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.