Single-cell RNA sequencing of developing maize ears facilitates functional analysis and trait candidate gene discovery

Histological and single-nucleus transcriptome analyses reveal the specialized functions of ligular sclerenchyma cells and key regulators of leaf angle in maize

Leaf angle (LA) is a crucial factor that affects planting density and yield in maize. However, the regulatory mechanisms underlying LA formation remain largely unknown. In this study, we performed a comparative histological analysis of the ligular region across various maize inbred lines and revealed that LA is significantly influenced by a two-step regulatory process involving initial cell elongation followed by subsequent lignification in the ligular adaxial sclerenchyma cells (SCs). Subsequently, we performed both bulk and single-nucleus RNA sequencing, generated a comprehensive transcriptomic atlas of the ligular region, and identified numerous genes enriched in the hypodermal cells that may influence their specialization into SCs. Furthermore, we functionally characterized two genes encoding atypical basic-helix-loop-helix (bHLH) transcription factors, bHLH30 and its homolog bHLH155, which are highly expressed in the elongated adaxial cells. Genetic analyses revealed that bHLH30 and bHLH155 positively regulate LA expansion, and molecular experiments demonstrated their ability to activate the transcription of genes involved in cell elongation and lignification of SCs. These findings highlight the specialized functions of ligular adaxial SCs in LA regulation by restricting further extension of ligular cells and enhancing mechanical strength. The transcriptomic atlas of the ligular region at single-nucleus resolution not only deepens our understanding of LA regulation but also enables identification of numerous potential targets for optimizing plant architecture in modern maize breeding.

Factors specifying sex determination in maize

Plant architecture is an important feature for agronomic performance in crops. In maize, which is a monoecious plant, separation of floral organs to produce specific gametes has been studied from different perspectives including genetic, biochemical and physiological. Maize mutants affected in floral organ development have been key to identifying genes, hormones and other factors like miRNAs important for sex determination. In this review, we describe floral organ formation in maize, representative mutants and genes identified with a function in establishing sexual identity either classified as feminizing or masculinizing, and its relationship with hormones associated with sexual organ identity as jasmonic acid, brassinosteroid and gibberellin. Finally, we discuss the challenges and scopes of future research in maize sex determination.

Toward unveiling transcriptome dynamics and regulatory modules at the maternal/filial interface of developing maize kernel

The basal region of maize (Zea mays) kernels, which includes the pedicel, placenta-chalazal, and basal endosperm transfer layers, serves as the maternal/filial interface for nutrient transfer from the mother plant to the developing seed. However, transcriptome dynamics of this maternal/filial interface remain largely unexplored. To address this gap, we conducted high-temporal-resolution RNA sequencing of the basal and upper kernel regions between 4 and 32 days after pollination and deeply analyzed transcriptome dynamics of the maternal/filial interface. Utilizing 790 specifically and highly expressed genes in the basal region, we performed the gene ontology (GO) term and weighted gene co-expression network analyses. In the early-stage basal region, we identified five MADS-box transcription factors (TFs) as hubs. Their homologs have been demonstrated as pivotal regulators at the maternal/filial interface of rice or Arabidopsis, suggesting their potential roles in maize kernel development. In the filling-stage basal region, numerous GO terms associated with transcriptional regulation and transporters are significantly enriched. Furthermore, we investigated the molecular function of three hub TFs. Through genome-wide DNA affinity purification sequencing combined with promoter transactivation assays, we suggested that these three TFs act as regulators of 10 basal-specific transporter genes involved in the transfer of sugars, amino acids, and ions. This study provides insights into transcriptomic dynamic and regulatory modules of the maternal/filial interface. In the future, genetic investigation of these hub regulators must advance our understanding of maternal/filial interface development and function.

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.

The role of omics in improving the orphan crop tef

Tef or teff [Eragrostis tef (Zucc.) Trotter] is a cereal crop indigenous to the Horn of Africa, where it is a staple food for a large population. The popularity of tef arises from its resilience to environmental stresses and its nutritional value. For many years, tef has been considered an orphan crop, but recent research initiatives from across the globe are helping to unravel its undisclosed potential. Advanced omics tools and techniques have been directed toward the exploration of tef's diversity with the aim of increasing its productivity. In this review, we report on the most recent advances in tef omics that brought the crop into the spotlight of international research.

A spatial transcriptome map of the developing maize ear

A comprehensive understanding of inflorescence development is crucial for crop genetic improvement, as inflorescence meristems give rise to reproductive organs and determine grain yield. However, dissecting inflorescence development at the cellular level has been challenging owing to a lack of specific marker genes to distinguish among cell types, particularly in different types of meristems that are vital for organ formation. In this study, we used spatial enhanced resolution omics-sequencing (Stereo-seq) to construct a precise spatial transcriptome map of the developing maize ear primordium, identifying 12 cell types, including 4 newly defined cell types found mainly in the inflorescence meristem. By extracting the meristem components for detailed clustering, we identified three subtypes of meristem and validated two MADS-box genes that were specifically expressed at the apex of determinate meristems and involved in stem cell determinacy. Furthermore, by integrating single-cell RNA transcriptomes, we identified a series of spatially specific networks and hub genes that may provide new insights into the formation of different tissues. In summary, this study provides a valuable resource for research on cereal inflorescence development, offering new clues for yield improvement.

Lost in space: what single-cell RNA sequencing cannot tell you

Plant scientists are rapidly integrating single-cell RNA sequencing (scRNA-seq) into their workflows. Maximizing the potential of scRNA-seq requires a proper understanding of the spatiotemporal context of cells. However, positional information is inherently lost during scRNA-seq, limiting its potential to characterize complex biological systems. In this review we highlight how current single-cell analysis pipelines cannot completely recover spatial information, which confounds biological interpretation. Various strategies exist to identify the location of RNA, from classical RNA in situ hybridization to spatial transcriptomics. Herein we discuss the possibility of utilizing this spatial information to supervise single-cell analyses. An integrative approach will maximize the potential of each technology, and lead to insights which go beyond the capability of each individual technology.

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.

Unraveling the molecular mechanisms governing axillary meristem initiation in plants

MAIN CONCLUSION

Axillary meristems (AMs) located in the leaf axils determine the number of shoots or tillers eventually formed, thus contributing significantly to the plant architecture and crop yields. The study of AM initiation is unavoidable and beneficial for crop productivity. Shoot branching is an undoubted determinant of plant architecture and thus greatly impacts crop yield due to the panicle-bearing traits of tillers. The emergence of the AM is essential for the incipient bud formation, and then the bud is dormant or outgrowth immediately to form a branch or tiller. While numerous reviews have focused on plant branching and tillering development networks, fewer specifically address AM initiation and its regulatory mechanisms. This review synthesizes the significant advancements in the genetic and hormonal factors governing AM initiation, with a primary focus on studies conducted in Arabidopsis (Arabidopsis thaliana L.) and rice (Oryza sativa L.). In particular, by elaborating on critical genes like LATERAL SUPPRESSOR (LAS), which specifically regulates AM initiation and the networks in which they are involved, we attempt to unify the cascades through which they are positioned. We concentrate on clarifying the precise mutual regulation between shoot apical meristem (SAM) and AM-related factors. Additionally, we examine challenges in elucidating AM formation mechanisms alongside opportunities provided by emerging omics approaches to identify AM-specific genes. By expanding our comprehension of the genetic and hormonal regulation of AM development, we can develop strategies to optimize crop production and address global food challenges effectively.

Large-scale single-cell profiling of stem cells uncovers redundant regulators of shoot development and yield trait variation

Stem cells in plant shoots are a rare population of cells that produce leaves, fruits and seeds, vital sources for food and bioethanol. Uncovering regulators expressed in these stem cells will inform crop engineering to boost productivity. Single-cell analysis is a powerful tool for identifying regulators expressed in specific groups of cells. However, accessing plant shoot stem cells is challenging. Recent single-cell analyses of plant shoots have not captured these cells, and failed to detect stem cell regulators like CLAVATA3 and WUSCHEL . In this study, we finely dissected stem cell-enriched shoot tissues from both maize and arabidopsis for single-cell RNA-seq profiling. We optimized protocols to efficiently recover thousands of CLAVATA3 and WUSCHEL expressed cells. A cross-species comparison identified conserved stem cell regulators between maize and arabidopsis. We also performed single-cell RNA-seq on maize stem cell overproliferation mutants to find additional candidate regulators. Expression of candidate stem cell genes was validated using spatial transcriptomics, and we functionally confirmed roles in shoot development. These candidates include a family of ribosome-associated RNA-binding proteins, and two families of sugar kinase genes related to hypoxia signaling and cytokinin hormone homeostasis. These large-scale single-cell profiling of stem cells provide a resource for mining stem cell regulators, which show significant association with yield traits. Overall, our discoveries advance the understanding of shoot development and open avenues for manipulating diverse crops to enhance food and energy security.

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 RNA Sequencing Reveals the Cellular Landscape of Longissimus Dorsi in a Newborn Suhuai Pig

The introduction of single-cell RNA sequencing (scRNA-seq) technology has spurred additional advancements in analyzing the cellular composition of tissues. The longissimus dorsi (LD) in pigs serves as the primary skeletal muscle for studying meat quality in the pig industry. However, the single-cell profile of porcine LD is still in its infancy stage. In this study, we profiled the transcriptomes of 16,018 cells in the LD of a newborn Suhuai pig at single-cell resolution. Subsequently, we constructed a cellular atlas of the LD, identifying 11 distinct cell populations, including endothelial cells (24.39%), myotubes (18.82%), fibro-adipogenic progenitors (FAPs, 18.11%), satellite cells (16.74%), myoblasts (3.99%), myocytes (5.74%), Schwann cells (3.81%), smooth muscle cells (3.22%), dendritic cells (2.99%), pericytes (1.86%), and neutrophils (0.33%). CellChat was employed to deduce the cell-cell interactions by evaluating the gene expression of receptor-ligand pairs across different cell types. The results show that FAPs and pericytes are the primary signal contributors in LD. In addition, we delineated the developmental trajectory of myogenic cells and examined alterations in the expression of various marker genes and molecular events throughout various stages of differentiation. Moreover, we found that FAPs can be divided into three subclusters (NR2F2-FAPs, LPL-FAPs, and TNMD-FAPs) according to their biological functions, suggesting that the FAPs could be associated with the differentiation of tendon cell. Taken together, we constructed the cellular atlas and cell communication network in LD of a newborn Suhuai pig, and analyzed the developmental trajectory of myogenic cells and the heterogeneity of FAPs subpopulation cells. This enhances our comprehension of the molecular features involved in skeletal muscle development and the meat quality control in pigs.

Boosting Triticeae crop grain yield by manipulating molecular modules to regulate inflorescence architecture: insights and knowledge from other cereal crops

One of the challenges for global food security is to reliably and sustainably improve the grain yield of cereal crops. One solution is to modify the architecture of the grain-bearing inflorescence to optimize for grain number and size. Cereal inflorescences are complex structures, with determinacy, branching patterns, and spikelet/floret growth patterns that vary by species. Recent decades have witnessed rapid advancements in our understanding of the genetic regulation of inflorescence architecture in rice, maize, wheat, and barley. Here, we summarize current knowledge on key genetic factors underlying the different inflorescence morphologies of these crops and model plants (Arabidopsis and tomato), focusing particularly on the regulation of inflorescence meristem determinacy and spikelet meristem identity and determinacy. We also discuss strategies to identify and utilize these superior alleles to optimize inflorescence architecture and, ultimately, improve crop grain yield.

Cultivating potential: Harnessing plant stem cells for agricultural crop improvement

Meristems are stem cell-containing structures that produce all plant organs and are therefore important targets for crop improvement. Developmental regulators control the balance and rate of cell divisions within the meristem. Altering these regulators impacts meristem architecture and, as a consequence, plant form. In this review, we discuss genes involved in regulating the shoot apical meristem, inflorescence meristem, axillary meristem, root apical meristem, and vascular cambium in plants. We highlight several examples showing how crop breeders have manipulated developmental regulators to modify meristem growth and alter crop traits such as inflorescence size and branching patterns. Plant transformation techniques are another innovation related to plant meristem research because they make crop genome engineering possible. We discuss recent advances on plant transformation made possible by studying genes controlling meristem development. Finally, we conclude with discussions about how meristem research can contribute to crop improvement in the coming decades.

A Single-Nucleus Resolution Atlas of Transcriptome and Chromatin Accessibility for Peanut (Arachis Hypogaea L.) Leaves

The peanut is an important worldwide cash-crop for edible oil and protein. However, the kinetic mechanisms that determine gene expression and chromatin accessibility during leaf development in peanut represented allotetraploid leguminous crops are poorly understood at single-cell resolution. Here, a single-nucleus atlas of peanut leaves is developed by simultaneously profiling the transcriptome and chromatin accessibility in the same individual-cell using fluorescence-activated sorted single-nuclei. In total, 5930 cells with 50 890 expressed genes are classified into 18 cell-clusters, and 5315 chromatin fragments are enriched with 26 083 target genes in the chromatin accessible landscape. The developmental trajectory analysis reveals the involvement of the ethylene-AP2 module in leaf cell differentiation, and cell-cycle analysis demonstrated that genome replication featured in distinct cell-types with circadian rhythms transcription factors (TFs). Furthermore, dual-omics illustrates that the fatty acid pathway modulates epidermal-guard cells differentiation and providescritical TFs interaction networks for understanding mesophyll development, and the cytokinin module (LHY/LOG) that regulates vascular growth. Additionally, an AT-hook protein AhAHL11 is identified that promotes leaf area expansion by modulating the auxin content increase. In summary, the simultaneous profiling of transcription and chromatin accessibility landscapes using snRNA/ATAC-seq provides novel biological insights into the dynamic processes of peanut leaf cell development at the cellular level.

Dynamic transcriptome landscape of developing maize ear

Seed number and harvesting ability in maize (Zea mays L.) are primarily determined by the architecture of female inflorescence, namely the ear. Therefore, ear morphogenesis contributes to grain yield and as such is one of the key target traits during maize breeding. However, the molecular networks of this highly dynamic and complex grain-bearing inflorescence remain largely unclear. As a first step toward characterizing these networks, we performed a high-spatio-temporal-resolution investigation of transcriptomes using 130 ear samples collected from developing ears with length from 0.1 mm to 19.0 cm. Comparisons of these mRNA populations indicated that these spatio-temporal transcriptomes were clearly separated into four distinct stages stages I, II, III, and IV. A total of 23 793 genes including 1513 transcription factors (TFs) were identified in the investigated developing ears. During the stage I of ear morphogenesis, 425 genes were predicted to be involved in a co-expression network established by eight hub TFs. Moreover, 9714 ear-specific genes were identified in the seven kinds of meristems. Additionally, 527 genes including 59 TFs were identified as especially expressed in ear and displayed high temporal specificity. These results provide a high-resolution atlas of gene activity during ear development and help to unravel the regulatory modules associated with the differentiation of the ear in maize.

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.

Transcriptomic analysis of wheat reveals possible resistance mechanism mediated by Yr10 to stripe rust

Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is a catastrophic disease that threatens global wheat yield. Yr10 is a race-specific all-stage disease resistance gene in wheat. However, the resistance mechanism of Yr10 is poorly characterized. Therefore, to elucidate the potential molecular mechanism mediated by Yr10, transcriptomic sequencing was performed at 0, 18, and 48 h post-inoculation (hpi) of compatible wheat Avocet S (AvS) and incompatible near-isogenic line (NIL) AvS + Yr10 inoculated with Pst race CYR32. Respectively, 227, 208, and 4050 differentially expressed genes (DEGs) were identified at 0, 18, and 48 hpi between incompatible and compatible interaction. The response of Yr10 to stripe rust involved various processes and activities, as indicated by the results of Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Specifically, the response included photosynthesis, defense response to fungus, metabolic processes related to salicylic acid (SA) and jasmonic acid (JA), and activities related to reactive oxygen species (ROS). Ten candidate genes were selected for qRT-PCR verification and the results showed that the transcriptomic data was reliable. Through the functional analysis of candidate genes by the virus-induced gene silencing (VIGS) system, it was found that the gene TaHPPD (4-hydroxyphenylpyruvate dioxygenase) negatively regulated the resistance of wheat to stripe rust by affecting SA signaling, pathogenesis-related (PR) gene expression, and ROS clearance. Our study provides insight into Yr10-mediated resistance in wheat.

Stem Cells: Engines of Plant Growth and Development

The development of both animals and plants relies on populations of pluripotent stem cells that provide the cellular raw materials for organ and tissue formation. Plant stem cell reservoirs are housed at the shoot and root tips in structures called meristems, with the shoot apical meristem (SAM) continuously producing aerial leaf, stem, and flower organs throughout the life cycle. Thus, the SAM acts as the engine of plant development and has unique structural and molecular features that allow it to balance self-renewal with differentiation and act as a constant source of new cells for organogenesis while simultaneously maintaining a stem cell reservoir for future organ formation. Studies have identified key roles for intercellular regulatory networks that establish and maintain meristem activity, including the KNOX transcription factor pathway and the CLV-WUS stem cell feedback loop. In addition, the plant hormones cytokinin and auxin act through their downstream signaling pathways in the SAM to integrate stem cell activity and organ initiation. This review discusses how the various regulatory pathways collectively orchestrate SAM function and touches on how their manipulation can alter stem cell activity to improve crop yield.

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.

Preparing Arabidopsis thaliana root protoplasts for cryo electron tomography

The use of protoplasts in plant biology has become a convenient tool for the application of transient gene expression. This model system has allowed the study of plant responses to biotic and abiotic stresses, protein location and trafficking, cell wall dynamics, and single-cell transcriptomics, among others. Although well-established protocols for isolating protoplasts from different plant tissues are available, they have never been used for studying plant cells using cryo electron microscopy (cryo-EM) and cryo electron tomography (cryo-ET). Here we describe a workflow to prepare root protoplasts from Arabidopsis thaliana plants for cryo-ET. The process includes protoplast isolation and vitrification on EM grids, and cryo-focused ion beam milling (cryo-FIB), with the aim of tilt series acquisition. The whole workflow, from growing the plants to the acquisition of the tilt series, may take a few months. Our protocol provides a novel application to use plant protoplasts as a tool for cryo-ET.

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.

Single-cell RNA sequencing analysis of the embryogenic callus clarifies the spatiotemporal developmental trajectories of the early somatic embryo in Dimocarpus longan

Plant embryogenic calli (ECs) can undergo somatic embryogenesis to regenerate plants. This process is mediated by regulatory factors, such as transcription factors and specifically expressed genes, but the precise molecular mechanisms underlying somatic embryogenesis at the single-cell level remain unclear. In this study, we performed high-resolution single-cell RNA sequencing analysis to determine the cellular changes in the EC of the woody plant species Dimocarpus longan (longan) and clarify the continuous cell differentiation trajectories at the transcriptome level. The highly heterogeneous cells in the EC were divided into 12 putative clusters (e.g., proliferating, meristematic, vascular, and epidermal cell clusters). We determined cluster-enriched expression marker genes and found that overexpression of the epidermal cell marker gene GDSL ESTERASE/LIPASE-1 inhibited the hydrolysis of triacylglycerol. In addition, the stability of autophagy was critical for the somatic embryogenesis of longan. The pseudo-timeline analysis elucidated the continuous cell differentiation trajectories from early embryonic cell division to vascular and epidermal cell differentiation during the somatic embryogenesis of longan. Moreover, key transcriptional regulators associated with cell fates were revealed. We found that ETHYLENE RESPONSIVE FACTOR 6 was characterized as a heat-sensitive factor that negatively regulates longan somatic embryogenesis under high-temperature stress conditions. The results of this study provide new spatiotemporal insights into cell division and differentiation during longan somatic embryogenesis at single-cell resolution.

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.

Cell signaling in the shoot apical meristem

Distinct from animals, plants maintain organogenesis from specialized tissues termed meristems throughout life. In the shoot apex, the shoot apical meristem (SAM) produces all aerial organs, such as leaves, from its periphery. For this, the SAM needs to precisely balance stem cell renewal and differentiation, which is achieved through dynamic zonation of the SAM, and cell signaling within functional domains is key for SAM functions. The WUSCHEL-CLAVATA feedback loop plays a key role in SAM homeostasis, and recent studies have uncovered new components, expanding our understanding of the spatial expression and signaling mechanism. Advances in polar auxin transport and signaling have contributed to knowledge of the multifaceted roles of auxin in the SAM and organogenesis. Finally, single-cell techniques have expanded our understanding of the cellular functions within the shoot apex at single-cell resolution. In this review, we summarize the most up-to-date understanding of cell signaling in the SAM and focus on the multiple levels of regulation of SAM formation and maintenance.

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.

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.

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.

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.

Single-Cell RNA sequencing of leaf sheath cells reveals the mechanism of rice resistance to brown planthopper (Nilaparvata lugens)

The brown planthopper (BPH) (Nilaparvata lugens) sucks rice sap causing leaves to turn yellow and wither, often leading to reduced or zero yields. Rice co-evolved to resist damage by BPH. However, the molecular mechanisms, including the cells and tissues, involved in the resistance are still rarely reported. Single-cell sequencing technology allows us to analyze different cell types involved in BPH resistance. Here, using single-cell sequencing technology, we compared the response offered by the leaf sheaths of the susceptible (TN1) and resistant (YHY15) rice varieties to BPH (48 hours after infestation). We found that the 14,699 and 16,237 cells (identified via transcriptomics) in TN1 and YHY15 could be annotated using cell-specific marker genes into nine cell-type clusters. The two rice varieties showed significant differences in cell types (such as mestome sheath cells, guard cells, mesophyll cells, xylem cells, bulliform cells, and phloem cells) in the rice resistance mechanism to BPH. Further analysis revealed that although mesophyll, xylem, and phloem cells are involved in the BPH resistance response, the molecular mechanism used by each cell type is different. Mesophyll cell may regulate the expression of genes related to vanillin, capsaicin, and ROS production, phloem cell may regulate the cell wall extension related genes, and xylem cell may be involved in BPH resistance response by controlling the expression of chitin and pectin related genes. Thus, rice resistance to BPH is a complicated process involving multiple insect resistance factors. The results presented here will significantly promote the investigation of the molecular mechanisms underlying the resistance of rice to insects and accelerate the breeding of insect-resistant rice varieties.

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.

Current advances in the molecular regulation of abiotic stress tolerance in sorghum via transcriptomic, proteomic, and metabolomic approaches

Sorghum (Sorghum bicolor L. Moench), a monocot C4 crop, is an important staple crop for many countries in arid and semi-arid regions worldwide. Because sorghum has outstanding tolerance and adaptability to a variety of abiotic stresses, including drought, salt, and alkaline, and heavy metal stressors, it is valuable research material for better understanding the molecular mechanisms of stress tolerance in crops and for mining new genes for their genetic improvement of abiotic stress tolerance. Here, we compile recent progress achieved using physiological, transcriptome, proteome, and metabolome approaches; discuss the similarities and differences in how sorghum responds to differing stresses; and summarize the candidate genes involved in the process of responding to and regulating abiotic stresses. More importantly, we exemplify the differences between combined stresses and a single stress, emphasizing the necessity to strengthen future studies regarding the molecular responses and mechanisms of combined abiotic stresses, which has greater practical significance for food security. Our review lays a foundation for future functional studies of stress-tolerance-related genes and provides new insights into the molecular breeding of stress-tolerant sorghum genotypes, as well as listing a catalog of candidate genes for improving the stress tolerance for other key monocot crops, such as maize, rice, and sugarcane.

A Wox3-patterning module organizes planar growth in grass leaves and ligules

Grass leaves develop from a ring of primordial initial cells within the periphery of the shoot apical meristem, a pool of organogenic stem cells that generates all of the organs of the plant shoot. At maturity, the grass leaf is a flattened, strap-like organ comprising a proximal supportive sheath surrounding the stem and a distal photosynthetic blade. The sheath and blade are partitioned by a hinge-like auricle and the ligule, a fringe of epidermally derived tissue that grows from the adaxial (top) leaf surface. Together, the ligule and auricle comprise morphological novelties that are specific to grass leaves. Understanding how the planar outgrowth of grass leaves and their adjoining ligules is genetically controlled can yield insight into their evolutionary origins. Here we use single-cell RNA-sequencing analyses to identify a 'rim' cell type present at the margins of maize leaf primordia. Cells in the leaf rim have a distinctive identity and share transcriptional signatures with proliferating ligule cells, suggesting that a shared developmental genetic programme patterns both leaves and ligules. Moreover, we show that rim function is regulated by genetically redundant Wuschel-like homeobox3 (WOX3) transcription factors. Higher-order mutations in maize Wox3 genes greatly reduce leaf width and disrupt ligule outgrowth and patterning. Together, these findings illustrate the generalizable use of a rim domain during planar growth of maize leaves and ligules, and suggest a parsimonious model for the homology of the grass ligule as a distal extension of the leaf sheath margin.

A pan-grass transcriptome reveals patterns of cellular divergence in crops

Different plant species within the grasses were parallel targets of domestication, giving rise to crops with distinct evolutionary histories and traits1. Key traits that distinguish these species are mediated by specialized cell types2. Here we compare the transcriptomes of root cells in three grass species-Zea mays, Sorghum bicolor and Setaria viridis. We show that single-cell and single-nucleus RNA sequencing provide complementary readouts of cell identity in dicots and monocots, warranting a combined analysis. Cell types were mapped across species to identify robust, orthologous marker genes. The comparative cellular analysis shows that the transcriptomes of some cell types diverged more rapidly than those of others-driven, in part, by recruitment of gene modules from other cell types. The data also show that a recent whole-genome duplication provides a rich source of new, highly localized gene expression domains that favour fast-evolving cell types. Together, the cell-by-cell comparative analysis shows how fine-scale cellular profiling can extract conserved modules from a pan transcriptome and provide insight on the evolution of cells that mediate key functions in crops.

Asymmetric gene expression and cell-type-specific regulatory networks in the root of bread wheat revealed by single-cell multiomics analysis

BACKGROUND

Homoeologs are defined as homologous genes resulting from allopolyploidy. Bread wheat, Triticum aestivum, is an allohexaploid species with many homoeologs. Homoeolog expression bias, referring to the relative contribution of homoeologs to the transcriptome, is critical for determining the traits that influence wheat growth and development. Asymmetric transcription of homoeologs has been so far investigated in a tissue or organ-specific manner, which could be misleading due to a mixture of cell types.

RESULTS

Here, we perform single nuclei RNA sequencing and ATAC sequencing of wheat root to study the asymmetric gene transcription, reconstruct cell differentiation trajectories and cell-type-specific gene regulatory networks. We identify 22 cell types. We then reconstruct cell differentiation trajectories that suggest different origins between epidermis/cortex and endodermis, distinguishing bread wheat from Arabidopsis. We show that the ratio of asymmetrically transcribed triads varies greatly when analyzing at the single-cell level. Hub transcription factors determining cell type identity are also identified. In particular, we demonstrate that TaSPL14 participates in vasculature development by regulating the expression of BAM1. Combining single-cell transcription and chromatin accessibility data, we construct the pseudo-time regulatory network driving root hair differentiation. We find MYB3R4, REF6, HDG1, and GATAs as key regulators in this process.

CONCLUSIONS

Our findings reveal the transcriptional landscape of root organization and asymmetric gene transcription at single-cell resolution in polyploid wheat.

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.

Trehalose 6-phosphate metabolism in C4 species

Trehalose 6-phosphate (Tre6P), the intermediate of trehalose biosynthesis, is an essential signal metabolite in plants, linking growth and development to carbon status. Our current understanding of Tre6P metabolism and signaling pathways in plants is based almost entirely on studies performed with Arabidopsis thaliana, a model plant that performs C₃ photosynthesis. Conversely, our knowledge on the molecular mechanisms involved in Tre6P regulation of carbon partitioning and metabolism in C₄ plants is scarce. This topic is especially relevant due to the agronomic importance of crops performing C₄ photosynthesis, such as maize, sorghum and sugarcane. In this review, we focused our attention on recent developments related to Tre6P metabolism in C₄ species and raised some open questions that should be addressed in the near future to improve the yield of economically important crops.

Charting plant gene functions in the multi-omics and single-cell era

Despite the increased access to high-quality plant genome sequences, the set of genes with a known function remains far from complete. With the advent of novel bulk and single-cell omics profiling methods, we are entering a new era where advanced and highly integrative functional annotation strategies are being developed to elucidate the functions of all plant genes. Here, we review different multi-omics approaches to improve functional and regulatory gene characterization and highlight the power of machine learning and network biology to fully exploit the complementary information embedded in different omics layers. Finally, we discuss the potential of emerging single-cell methods and algorithms to further increase the resolution, allowing generation of functional insights about plant biology.

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.

Establishment of an efficient cotton root protoplast isolation protocol suitable for single-cell RNA sequencing and transient gene expression analysis

BACKGROUND

Cotton has tremendous economic value worldwide; however, its allopolyploid nature and time-consuming transformation methods have hampered the development of cotton functional genomics. The protoplast system has proven to be an important and versatile tool for functional genomics, tissue-specific marker gene identification, tracking developmental trajectories, and genome editing in plants. Nevertheless, the isolation of abundant viable protoplasts suitable for single-cell RNA sequencing (scRNA-seq) and genome editing remains a challenge in cotton.

RESULTS

We established an efficient transient gene expression system using protoplasts isolated from cotton taproots. The system enables the isolation of large numbers of viable protoplasts and uses an optimized PEG-mediated transfection protocol. The highest yield (3.55 × 10⁵/g) and viability (93.3%) of protoplasts were obtained from cotton roots grown in hydroponics for 72 h. The protoplasts isolated were suitable for scRNA-seq. The highest transfection efficiency (80%) was achieved when protoplasts were isolated as described above and transfected with 20 μg of plasmid for 20 min in a solution containing 200 mM Ca²⁺. Our protoplast-based transient expression system is suitable for various applications, including validation the efficiency of CRISPR vectors, protein subcellular localization analysis, and protein-protein interaction studies.

CONCLUSIONS

The protoplast isolation and transfection protocol developed in this study is stable, versatile, and time-saving. It will accelerate functional genomics and molecular breeding in cotton.

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.

Upcoming progress of transcriptomics studies on plants: An overview

Transcriptome sequencing or RNA-Sequencing is a high-resolution, sensitive and high-throughput next-generation sequencing (NGS) approach used to study non-model plants and other organisms. In other words, it is an assembly of RNA transcripts from individual or whole samples of functional and developmental stages. RNA-Seq is a significant technique for identifying gene predictions and mining functional analysis that improves gene ontology understanding mechanisms of biological processes, molecular functions, and cellular components, but there is limited information available on this topic. Transcriptomics research on different types of plants can assist researchers to understand functional genes in better ways and regulatory processes to improve breeding selection and cultivation practices. In recent years, several advancements in RNA-Seq technology have been made for the characterization of the transcriptomes of distinct cell types in biological tissues in an efficient manner. RNA-Seq technologies are briefly introduced and examined in terms of their scientific applications. In a nutshell, it introduces all transcriptome sequencing and analysis techniques, as well as their applications in plant biology research. This review will focus on numerous existing and forthcoming strategies for improving transcriptome sequencing technologies for functional gene mining in various plants using RNA- Seq technology, based on the principles, development, and applications.

Plant Single-Cell/Nucleus RNA-seq Workflow

Single-cell transcriptomics technologies allow researchers to investigate how individual cells, in complex multicellular organisms, differentially use their common genomic DNA. In plant biology, these technologies were recently applied to reveal the transcriptomes of various plant cells isolated from different organs and different species and in response to environmental stresses. These first studies support the potential of single-cell transcriptomics technology to decipher the biological function of plant cells, their developmental programs, cell-type-specific gene networks, programs controlling plant cell response to environmental stresses, etc. In this chapter, we provide information regarding the critical steps and important information to consider when developing an experimental design in plant single-cell biology. We also describe the current status of bioinformatics tools used to analyze single-cell RNA-seq datasets and how additional emerging technologies such as spatial transcriptomics and long-read sequencing technologies will provide additional information on the differential use of the genome by plant cells.

Unleashing the power within short-read RNA-seq for plant research: Beyond differential expression analysis and toward regulomics

RNA-seq has become a state-of-the-art technique for transcriptomic studies. Advances in both RNA-seq techniques and the corresponding analysis tools and pipelines have unprecedently shaped our understanding in almost every aspects of plant sciences. Notably, the integration of huge amount of RNA-seq with other omic data sets in the model plants and major crop species have facilitated plant regulomics, while the RNA-seq analysis has still been primarily used for differential expression analysis in many less-studied plant species. To unleash the analytical power of RNA-seq in plant species, especially less-studied species and biomass crops, we summarize recent achievements of RNA-seq analysis in the major plant species and representative tools in the four types of application: (1) transcriptome assembly, (2) construction of expression atlas, (3) network analysis, and (4) structural alteration. We emphasize the importance of expression atlas, coexpression networks and predictions of gene regulatory relationships in moving plant transcriptomes toward regulomics, an omic view of genome-wide transcription regulation. We highlight what can be achieved in plant research with RNA-seq by introducing a list of representative RNA-seq analysis tools and resources that are developed for certain minor species or suitable for the analysis without species limitation. In summary, we provide an updated digest on RNA-seq tools, resources and the diverse applications for plant research, and our perspective on the power and challenges of short-read RNA-seq analysis from a regulomic point view. A full utilization of these fruitful RNA-seq resources will promote plant omic research to a higher level, especially in those less studied species.