Single-cell transcriptome atlas of the leaf and root of rice seedlings

Leaf growth - complex regulation of a seemingly simple process

Understanding the underlying mechanisms of plant development is crucial to successfully steer or manipulate plant growth in a targeted manner. Leaves, the primary sites of photosynthesis, are vital organs for many plant species, and leaf growth is controlled by a tight temporal and spatial regulatory network. In this review, we focus on the genetic networks governing leaf cell proliferation, one major contributor to final leaf size. First, we provide an overview of six regulator families of leaf growth in Arabidopsis: DA1, PEAPODs, KLU, GRFs, the SWI/SNF complexes, and DELLAs, together with their surrounding genetic networks. Next, we discuss their evolutionary conservation to highlight similarities and differences among species, because knowledge transfer between species remains a big challenge. Finally, we focus on the increase in knowledge of the interconnectedness between these genetic pathways, the function of the cell cycle machinery as their central convergence point, and other internal and environmental cues.

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.

scPlantDB: a comprehensive database for exploring cell types and markers of plant cell atlases

Recent advancements in single-cell RNA sequencing (scRNA-seq) technology have enabled the comprehensive profiling of gene expression patterns at the single-cell level, offering unprecedented insights into cellular diversity and heterogeneity within plant tissues. In this study, we present a systematic approach to construct a plant single-cell database, scPlantDB, which is publicly available at https://biobigdata.nju.edu.cn/scplantdb. We integrated single-cell transcriptomic profiles from 67 high-quality datasets across 17 plant species, comprising approximately 2.5 million cells. The data underwent rigorous collection, manual curation, strict quality control and standardized processing from public databases. scPlantDB offers interactive visualization of gene expression at the single-cell level, facilitating the exploration of both single-dataset and multiple-dataset analyses. It enables systematic comparison and functional annotation of markers across diverse cell types and species while providing tools to identify and compare cell types based on these markers. In summary, scPlantDB serves as a comprehensive database for investigating cell types and markers within plant cell atlases. It is a valuable resource for the plant research community.

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

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

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.

Single-cell RNA-sequencing profiles reveal the developmental landscape of the Manihot esculenta Crantz leaves

Cassava (Manihot esculenta Crantz) is an important crop with a high photosynthetic rate and high yield. It is classified as a C3-C4 plant based on its photosynthetic and structural characteristics. To investigate the structural and photosynthetic characteristics of cassava leaves at the cellular level, we created a single-cell transcriptome atlas of cassava leaves. A total of 11,177 high-quality leaf cells were divided into 15 cell clusters. Based on leaf cell marker genes, we identified 3 major tissues of cassava leaves, which were mesophyll, epidermis, and vascular tissue, and analyzed their distinctive properties and metabolic activity. To supplement the genes for identifying the types of leaf cells, we screened 120 candidate marker genes. We constructed a leaf cell development trajectory map and discovered 6 genes related to cell differentiation fate. The structural and photosynthetic properties of cassava leaves analyzed at the single cellular level provide a theoretical foundation for further enhancing cassava yield and nutrition.

Genome-wide identification and expression analysis of heat shock protein gene family in cassava

Heat shock proteins are important molecular chaperones that are involved in plant growth and stress responses. However, members of the Hsp family have been poorly studied in cassava. In this study, 225 MeHsp genes were identified in the cassava genome, and their genetic structures exhibited relatively conserved features within each subfamily. The 225 MeHsp genes showed random chromosomal distribution, and at least 74 pairs of segmentally duplicated MeHsp genes. Eleven tandemly duplicated MeHsp genes were identified. Cis-element analysis revealed the importance of MeHsps in plant adaptations to the environment. The prediction of protein interactions suggested that MeHsp70-20 may play a critical regulatory role in the interactive network. Furthermore, the expression profiles of MeHsps in different tissues and cell subsets were analyzed using bulk transcriptomics and single-cell transcriptomic data. Several subfamily genes exhibited unique expression patterns in the transcriptome and were selected for detailed analysis of the single-cell transcriptome. Quantitative real-time polymerase chain reaction (qRT-PCR) revealed the expression patterns of these genes under temperature stress, further supporting the prediction of cis-acting elements. This study provides valuable information for understanding the functional characteristics of MeHsp genes and the evolutionary relationships between MeHsps.

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.

Single-cell transcriptome analyses reveal cellular and molecular responses to low nitrogen in burley tobacco leaves

Tobacco (Nicotiana tabacum) is cultivated and consumed worldwide. It requires great amounts of nitrogen (N) to achieve the best yield and quality. With a view to sustainable and environmentally friendly agriculture, developing new genotypes with high productivity under low N conditions is an important approach. It is unclear how genes in tobacco are expressed at the cellular level and the precise mechanisms by which cells respond to environmental stress, especially in the case of low N. Here, we characterized the transcriptomes in tobacco leaves grown in normal and low-N conditions by performing scRNA-seq. We identified 10 cell types with 17 transcriptionally distinct cell clusters with the assistance of marker genes and constructed the first single-cell atlas of tobacco leaves. Distinct gene expression patterns of cell clusters were observed under low-N conditions, and the mesophyll cells were the most important responsive cell type and displayed heterogene responses among its three subtypes. Pseudo-time trajectory analysis revealed low-N stress decelerates the differentiation towards mesophyll cells. In combination with scRNA-seq, WGCNA, and bulk RNA-seq results, we found that genes involved in porphyrin metabolism, nitrogen metabolism, carbon fixation, photosynthesis, and photosynthesis-antenna pathway play an essential role in response to low N. Moreover, we identified COL16, GATA24, MYB73, and GLK1 as key TFs in the regulation of N-responsive genes. Collectively, our findings are the first observation of the cellular and molecular responses of tobacco leaves under low N stress and lay the cornerstone for future tobacco scRNA-seq investigations.

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.

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.

scRNA-seq Reveals the Mechanism of Fatty Acid Desaturase 2 Mutation to Repress Leaf Growth in Peanut (Arachis hypogaea L.)

Fatty Acid Desaturase 2 (FAD2) controls the conversion of oleic acids into linoleic acids. Mutations in FAD2 not only increase the high-oleic content, but also repress the leaf growth. However, the mechanism by which FAD2 regulates the growth pathway has not been elucidated in peanut leaves with single-cell resolution. In this study, we isolated fad2 mutant leaf protoplast cells to perform single-cell RNA sequencing. Approximately 24,988 individual cells with 10,249 expressed genes were classified into five major cell types. A comparative analysis of 3495 differentially expressed genes (DEGs) in distinct cell types demonstrated that fad2 inhibited the expression of the cytokinin synthesis gene LOG in vascular cells, thereby repressing leaf growth. Further, pseudo-time trajectory analysis indicated that fad2 repressed leaf cell differentiation, and cell-cycle evidence displayed that fad2 perturbed the normal cell cycle to induce the majority of cells to drop into the S phase. Additionally, important transcription factors were filtered from the DEG profiles that connected the network involved in high-oleic acid accumulation (WRKY6), activated the hormone pathway (WRKY23, ERF109), and potentially regulated leaf growth (ERF6, MYB102, WRKY30). Collectively, our study describes different gene atlases in high-oleic and normal peanut seedling leaves, providing novel biological insights to elucidate the molecular mechanism of the high-oleic peanut-associated agronomic trait at the single-cell level.

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.

Mass spectrometry imaging and single-cell transcriptional profiling reveal the tissue-specific regulation of bioactive ingredient biosynthesis in Taxus leaves

Taxus leaves provide the raw industrial materials for taxol, a natural antineoplastic drug widely used in the treatment of various cancers. However, the precise distribution, biosynthesis, and transcriptional regulation of taxoids and other active components in Taxus leaves remain unknown. Matrix-assisted laser desorption/ionization-mass spectrometry imaging analysis was used to visualize various secondary metabolites in leaf sections of Taxus mairei, confirming the tissue-specific accumulation of different active metabolites. Single-cell sequencing was used to produce expression profiles of 8846 cells, with a median of 2352 genes per cell. Based on a series of cluster-specific markers, cells were grouped into 15 clusters, suggesting a high degree of cell heterogeneity in T. mairei leaves. Our data were used to create the first Taxus leaf metabolic single-cell atlas and to reveal spatial and temporal expression patterns of several secondary metabolic pathways. According to the cell-type annotation, most taxol biosynthesis genes are expressed mainly in leaf mesophyll cells; phenolic acid and flavonoid biosynthesis genes are highly expressed in leaf epidermal cells (including the stomatal complex and guard cells); and terpenoid and steroid biosynthesis genes are expressed specifically in leaf mesophyll cells. A number of novel and cell-specific transcription factors involved in secondary metabolite biosynthesis were identified, including MYB17, WRKY12, WRKY31, ERF13, GT_2, and bHLH46. Our research establishes the transcriptional landscape of major cell types in T. mairei leaves at a single-cell resolution and provides valuable resources for studying the basic principles of cell-type-specific regulation of secondary metabolism.

Integrated mass spectrometry imaging and single-cell transcriptome atlas strategies provide novel insights into taxoid biosynthesis and transport in Taxus mairei stems

Taxol, which is a widely used important chemotherapeutic agent, was originally isolated from Taxus stem barks. However, little is known about the precise distribution of taxoids and the transcriptional regulation of taxoid biosynthesis across Taxus stems. Here, we used MALDI-IMS analysis to visualize the taxoid distribution across Taxus mairei stems and single-cell RNA sequencing to generate expression profiles. A single-cell T. mairei stem atlas was created, providing a spatial distribution pattern of Taxus stem cells. Cells were reordered using a main developmental pseudotime trajectory which provided temporal distribution patterns in Taxus stem cells. Most known taxol biosynthesis-related genes were primarily expressed in epidermal, endodermal, and xylem parenchyma cells, which caused an uneven taxoid distribution across T. mairei stems. We developed a single-cell strategy to screen novel transcription factors (TFs) involved in taxol biosynthesis regulation. Several TF genes, such as endodermal cell-specific MYB47 and xylem parenchyma cell-specific NAC2 and bHLH68, were implicated as potential regulators of taxol biosynthesis. Furthermore, an ATP-binding cassette family transporter gene, ABCG2, was proposed as a potential taxoid transporter candidate. In summary, we generated a single-cell Taxus stem metabolic atlas and identified molecular mechanisms underpinning the cell-specific transcriptional regulation of the taxol biosynthesis pathway.

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

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

Analysis of meristems and plant regeneration at single-cell resolution

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

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.

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.

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.

Differentially-expressed genes related to glutathione metabolism and heavy metal transport reveals an adaptive, genotype-specific mechanism to Hg2+ exposure in rice (Oryza sativa L.)

Rice consumption is an essential cause of mercury (Hg) exposure for humans in Asia. However, the mechanism of Hg transport and accumulation in rice plants (Oryza sativa L.) remains unclear. Here, rice genotypes with contrasting Hg uptake and translocation abilities, i.e. H655 (high Hg-accumulator) and H767 (low Hg-accumulator), were selected from 261 genotypes. Through comparative physiological and transcriptome analyses, we investigated the processes responsible for the relationship between Hg accumulation, transport and tolerance. The results showed significant stimulation of antioxidative metabolism, particularly glutathione (GSH) accumulation, and up-regulated expression of regulatory genes of glutathione metabolism for H655, but not for H767. In addition, up-regulated expression of GSH S-transferase (GST) and OsPCS1 in H655 that catalyzes the binding of Hg and GSH, enhances the Hg detoxification capacity, while high-level expression of YSL2 in H655 enhances the transport ability for Hg. Conclusively, Hg accumulation in rice is a consequence of enhanced expression of genes related to Hg binding with GSH and Hg transport. With these results, the present study contributes to the selection of rice genotypes with limited Hg accumulation and to the mitigation of Hg migration in food chains thereby enhancing nutritional safety of Hg-polluted rice fields.

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.

Molecular Hydrogen Confers Resistance to Rice Stripe Virus

Although molecular hydrogen (H2) has potential therapeutic effects in animals, whether or how this gas functions in plant disease resistance has not yet been elucidated. Here, after rice stripe virus (RSV) infection, H2 production was pronouncedly stimulated in Zhendao 88, a resistant rice variety, compared to that in a susceptible variety (Wuyujing No.3). External H2 supply remarkably reduced the disease symptoms and RSV coat protein (CP) levels, especially in Wuyujing No.3. The above responses were abolished by the pharmacological inhibition of H2 production. The transgenic Arabidopsis plants overexpressing a hydrogenase gene from Chlamydomonas reinhardtii also improved plant resistance. In the presence of H2, the transcription levels of salicylic acid (SA) synthetic genes were stimulated, and the activity of SA glucosyltransferases was suppressed, thus facilitating SA accumulation. Genetic evidence revealed that two SA synthetic mutants of Arabidopsis (sid2-2 and pad4) were more susceptible to RSV than the wild type (WT). The treatments with H2 failed to improve the resistance to RSV in two SA synthetic mutants. The above results indicated that H2 enhances rice resistance to RSV infection possibly through the SA-dependent pathway. This study might open a new window for applying the H2-based approach to improve plant disease resistance. IMPORTANCE Although molecular hydrogen has potential therapeutic effects in animals, whether or how this gas functions in plant disease resistance has not yet been elucidated. RSV was considered the most devastating plant virus in rice, since it could cause severe losses in field production. This disease was thus selected as a classical model to explore the interrelationship between molecular hydrogen and plant pathogen resistance. In this study, we discovered that both exogenous and endogenous H2 could enhance plant resistance against Rice stripe virus infection by regulating salicylic acid signaling. Compared with some frequently used agrochemicals, H2 is almost nontoxic. We hope that the findings presented here will serve as an opportunity for the scientific community to push hydrogen-based agriculture forward.

Gene-by-environment interactions in plants: Molecular mechanisms, environmental drivers, and adaptive plasticity

Plants demonstrate a broad range of responses to environmental shifts. One of the most remarkable responses is plasticity, which is the ability of a single plant genotype to produce different phenotypes in response to environmental stimuli. As with all traits, the ability of plasticity to evolve depends on the presence of underlying genetic diversity within a population. A common approach for evaluating the role of genetic variation in driving differences in plasticity has been to study genotype-by-environment interactions (G × E). G × E occurs when genotypes produce different phenotypic trait values in response to different environments. In this review, we highlight progress and promising methods for identifying the key environmental and genetic drivers of G × E. Specifically, methodological advances in using algorithmic and multivariate approaches to understand key environmental drivers combined with new genomic innovations can greatly increase our understanding about molecular responses to environmental stimuli. These developing approaches can be applied to proliferating common garden networks that capture broad natural environmental gradients to unravel the underlying mechanisms of G × E. An increased understanding of G × E can be used to enhance the resilience and productivity of agronomic systems.

Single-cell transcriptome reveals dominant subgenome expression and transcriptional response to heat stress in Chinese cabbage

BACKGROUND

Chinese cabbage (Brassica rapa ssp. pekinensis) experienced a whole-genome triplication event and thus has three subgenomes: least fractioned, medium fractioned, and most fractioned subgenome. Environmental changes affect leaf development, which in turn influence the yield. To improve the yield and resistance to different climate scenarios, a comprehensive understanding of leaf development is required including insights into the full diversity of cell types and transcriptional networks underlying their specificity.

RESULTS

Here, we generate the transcriptional landscape of Chinese cabbage leaf at single-cell resolution by performing single-cell RNA sequencing of 30,000 individual cells. We characterize seven major cell types with 19 transcriptionally distinct cell clusters based on the expression of the reported marker genes. We find that genes in the least fractioned subgenome are predominantly expressed compared with those in the medium and most fractioned subgenomes in different cell types. Moreover, we generate a single-cell transcriptional map of leaves in response to high temperature. We find that heat stress not only affects gene expression in a cell type-specific manner but also impacts subgenome dominance.

CONCLUSIONS

Our study highlights the transcriptional networks in different cell types and provides a better understanding of transcriptional regulation during leaf development and transcriptional response to heat stress in Chinese cabbage.

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.

Chromatin accessibility illuminates single-cell regulatory dynamics of rice root tips

BACKGROUND

Root development and function have central roles in plant adaptation to the environment. The modification of root traits has additionally been a major driver of crop performance since the green revolution; however, the molecular underpinnings and the regulatory programmes defining root development and response to environmental stress remain largely unknown. Single-cell reconstruction of gene regulatory programmes provides an important tool to understand the cellular phenotypic variation in complex tissues and their response to endogenous and environmental stimuli. While single-cell transcriptomes of several plant organs have been elucidated, the underlying chromatin landscapes associated with cell type-specific gene expression remain largely unexplored.

RESULTS

To comprehensively delineate chromatin accessibility during root development of an important crop, we applied single-cell ATAC-seq (scATAC-seq) to 46,758 cells from rice root tips under normal and heat stress conditions. Our data revealed cell type-specific accessibility variance across most of the major cell types and allowed us to identify sets of transcription factors which associate with accessible chromatin regions (ACRs). Using root hair differentiation as a model, we demonstrate that chromatin and gene expression dynamics during cell type differentiation correlate in pseudotime analyses. In addition to developmental trajectories, we describe chromatin responses to heat and identify cell type-specific accessibility changes to this key environmental stimulus.

CONCLUSIONS

We report chromatin landscapes during rice root development at single-cell resolution. Our work provides a framework for the integrative analysis of regulatory dynamics in this important crop organ at single-cell resolution.

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.

Review: Challenges and perspectives in applying single nuclei RNA-seq technology in plant biology

Plant single-cell RNA-seq technology quantifies the abundance of plant transcripts at a single-cell resolution. Deciphering the transcriptomes of each plant cell, their regulation during plant cell development, and their response to environmental stresses will support the functional study of genes, the establishment of precise transcriptional programs, the prediction of more accurate gene regulatory networks, and, in the long term, the design of de novo gene pathways to enhance selected crop traits. In this review, we will discuss the opportunities, challenges, and problems, and share tentative solutions associated with the generation and analysis of plant single-cell transcriptomes. We will discuss the benefit and limitations of using plant protoplasts vs. nuclei to conduct single-cell RNA-seq experiments on various plant species and organs, the functional annotation of plant cell types based on their transcriptomic profile, the characterization of the dynamic regulation of the plant genes during cell development or in response to environmental stress, the need to characterize and integrate additional layers of -omics datasets to capture new molecular modalities at the single-cell level and reveal their causalities, the deposition and access to single-cell datasets, and the accessibility of this technology to plant scientists.

Single-cell RNA-seq reveals fate determination control of an individual fibre cell initiation in cotton (Gossypium hirsutum)

Cotton fibre is a unicellular seed trichome, and lint fibre initials per seed as a factor determines fibre yield. However, the mechanisms controlling fibre initiation from ovule epidermis are not understood well enough. Here, with single-cell RNA sequencing (scRNA-seq), a total of 14 535 cells were identified from cotton ovule outer integument of Xu142_LF line at four developmental stages (1.5, 1, 0.5 days before anthesis and the day of anthesis). Three major cell types, fibre, non-fibre epidermis and outer pigment layer were identified and then verified by RNA in situ hybridization. A comparative analysis on scRNA-seq data between Xu142 and its fibreless mutant Xu142 fl further confirmed fibre cluster definition. The developmental trajectory of fibre cell was reconstructed, and fibre cell was identified differentiated at 1 day before anthesis. Gene regulatory networks at four stages revealed the spatiotemporal pattern of core transcription factors, and MYB25-like and HOX3 were demonstrated played key roles as commanders in fibre differentiation and tip-biased diffuse growth respectively. A model for early development of a single fibre cell was proposed here, which sheds light on further deciphering mechanism of plant trichome and the improvement of cotton fibre yield.

PIN1 regulates epidermal cells development under drought and salt stress using single-cell analysis

Over the course of evolution, plants have developed plasticity to acclimate to environmental stresses such as drought and salt stress. These plant adaptation measures involve the activation of cascades of molecular networks involved in stress perception, signal transduction and the expression of stress related genes. Here, we investigated the role of the plasma membrane-localized transporter of auxin PINFORMED1 (PIN1) in the regulation of pavement cells (PCs) and guard cells (GCs) development under drought and salt stress conditions. The results showed that drought and salt stress treatment affected the development of PCs and GCs. Further analysis identified the different regulation mechanisms of PIN1 in regulating the developmental patterns of PCs and GCs under drought and salt stress conditions. Drought and salt stress also regulated the expression dynamics of PIN1 in pif1/3/4/5 quadruple mutants. Collectively, we revealed that PIN1 plays a crucial role in regulating plant epidermal cells development under drought and salt stress conditions, thus contributing to developmental rebustness and plasticity.

Single-cell technologies: From research to application

In recent years, more and more single-cell technologies have been developed. A vast amount of single-cell omics data has been generated by large projects, such as the Human Cell Atlas, the Mouse Cell Atlas, the Mouse RNA Atlas, the Mouse ATAC Atlas, and the Plant Cell Atlas. Based on these single-cell big data, thousands of bioinformatics algorithms for quality control, clustering, cell-type annotation, developmental inference, cell-cell transition, cell-cell interaction, and spatial analysis are developed. With powerful experimental single-cell technology and state-of-the-art big data analysis methods based on artificial intelligence, the molecular landscape at the single-cell level can be revealed. With spatial transcriptomics and single-cell multi-omics, even the spatial dynamic multi-level regulatory mechanisms can be deciphered. Such single-cell technologies have many successful applications in oncology, assisted reproduction, embryonic development, and plant breeding. We not only review the experimental and bioinformatics methods for single-cell research, but also discuss their applications in various fields and forecast the future directions for single-cell technologies. We believe that spatial transcriptomics and single-cell multi-omics will become the next booming business for mechanism research and commercial industry.

PlantPhoneDB: A manually curated pan-plant database of ligand-receptor pairs infers cell-cell communication

Ligand-receptor pairs play important roles in cell-cell communication for multicellular organisms in response to environmental cues. Recently, the emergence of single-cell RNA-sequencing (scRNA-seq) provides unprecedented opportunities to investigate cellular communication based on ligand-receptor expression. However, so far, no reliable ligand-receptor interaction database is available for plant species. In this study, we developed PlantPhoneDB (https://jasonxu.shinyapps.io/PlantPhoneDB/), a pan-plant database comprising a large number of high-confidence ligand-receptor pairs manually curated from seven resources. Also, we developed a PlantPhoneDB R package, which not only provided optional four scoring approaches that calculate interaction scores of ligand-receptor pairs between cell types but also provided visualization functions to present analysis results. At the PlantPhoneDB web interface, the processed datasets and results can be searched, browsed, and downloaded. To uncover novel cell-cell communication events in plants, we applied the PlantPhoneDB R package on GSE121619 dataset to infer significant cell-cell interactions of heat-shocked root cells in Arabidopsis thaliana. As a result, the PlantPhoneDB predicted the actively communicating AT1G28290-AT2G14890 ligand-receptor pair in atrichoblast-cortex cell pair in Arabidopsis thaliana. Importantly, the downstream target genes of this ligand-receptor pair were significantly enriched in the ribosome pathway, which facilitated plants adapting to environmental changes. In conclusion, PlantPhoneDB provided researchers with integrated resources to infer cell-cell communication from scRNA-seq datasets.

Genomics and transcriptomics to protect rice (Oryza sativa. L.) from abiotic stressors: -pathways to achieving zero hunger

More over half of the world's population depends on rice as a major food crop. Rice (Oryza sativa L.) is vulnerable to abiotic challenges including drought, cold, and salinity since it grown in semi-aquatic, tropical, or subtropical settings. Abiotic stress resistance has bred into rice plants since the earliest rice cultivation techniques. Prior to the discovery of the genome, abiotic stress-related genes were identified using forward genetic methods, and abiotic stress-tolerant lines have developed using traditional breeding methods. Dynamic transcriptome expression represents the degree of gene expression in a specific cell, tissue, or organ of an individual organism at a specific point in its growth and development. Transcriptomics can reveal the expression at the entire genome level during stressful conditions from the entire transcriptional level, which can be helpful in understanding the intricate regulatory network relating to the stress tolerance and adaptability of plants. Rice (Oryza sativa L.) gene families found comparatively using the reference genome sequences of other plant species, allowing for genome-wide identification. Transcriptomics via gene expression profiling which have recently dominated by RNA-seq complements genomic techniques. The identification of numerous important qtl,s genes, promoter elements, transcription factors and miRNAs involved in rice response to abiotic stress was made possible by all of these genomic and transcriptomic techniques. The use of several genomes and transcriptome methodologies to comprehend rice (Oryza sativa, L.) ability to withstand abiotic stress have been discussed in this review.

Single-cell transcriptome of Nepeta tenuifolia leaves reveal differentiation trajectories in glandular trichomes

The peltate glandular trichomes (PGTs) on Nepeta tenuifolia leaves can secrete and store bioactive essential oils. ScRNA-seq is a powerful tool for uncovering heterogeneous cells and exploring the development and differentiation of specific cells. Due to leaves rich in PGTs, the young leaves were used to isolated protoplasts and successfully captured 33,254 protoplasts for sequencing purposes. After cell type annotation, all the cells were partitioned into six broad populations with 19 clusters. Cells from PGTs were identified based on the expression patterns of trichome-specific genes, monoterpene biosynthetic genes, and metabolic analysis of PGT secretions. The developmental trajectories of PGTs were delineated by pseudotime analysis. Integrative analysis of scRNA-seq data from N. tenuifolia leaves and Arabidopsis thaliana shoot revealed that PGTs were specific to N. tenuifolia. Thus, our results provide a promising basis for exploring cell development and differentiation in plants, especially glandular trichome initiation and development.

Global transcriptome and coexpression network analyses reveal cultivar-specific molecular signatures associated with different rooting depth responses to drought stress in potato

Potato is one of the most important vegetable crops worldwide. Its growth, development and ultimately yield is hindered by drought stress condition. Breeding and selection of deep-rooted and drought-tolerant potato varieties has become a prime approach for improving the yield and quality of potato (Solanum tuberosum L.) in arid and semiarid areas. A comprehensive understanding of root development-related genes has enabled scientists to formulate strategies to incorporate them into breeding to improve complex agronomic traits and provide opportunities for the development of stress tolerant germplasm. Root response to drought stress is an intricate process regulated through complex transcriptional regulatory network. To understand the rooting depth and molecular mechanism, regulating root response to drought stress in potato, transcriptome dynamics of roots at different stages of drought stress were analyzed in deep (C119) and shallow-rooted (C16) cultivars. Stage-specific expression was observed for a significant proportion of genes in each cultivar and it was inferred that as compared to C16 (shallow-rooted), approximately half of the genes were differentially expressed in deep-rooted cultivar (C119). In C16 and C119, 11 and 14 coexpressed gene modules, respectively, were significantly associated with physiological traits under drought stress. In a comparative analysis, some modules were different between the two cultivars and were associated with differential response to specific drought stress stage. Transcriptional regulatory networks were constructed, and key components determining rooting depth were identified. Through the results, we found that rooting depth (shallow vs deep) was largely determined by plant-type, cell wall organization or biogenesis, hemicellulose metabolic process, and polysaccharide metabolic process. In addition, candidate genes responding to drought stress were identified in deep (C119) and shallow (C16) rooted potato varieties. The results of this study will be a valuable source for further investigations on the role of candidate gene(s) that affect rooting depth and drought tolerance mechanisms in potato.

Cell-Type-Specific Profiling of the Arabidopsis thaliana Membrane Protein-Encoding Genes

Membrane proteins work in large complexes to perceive and transduce external signals and to trigger a cellular response leading to the adaptation of the cells to their environment. Biochemical assays have been extensively used to reveal the interaction between membrane proteins. However, such analyses do not reveal the unique and complex composition of the membrane proteins of the different plant cell types. Here, we conducted a comprehensive analysis of the expression of Arabidopsis membrane proteins in the different cell types composing the root. Specifically, we analyzed the expression of genes encoding membrane proteins interacting in large complexes. We found that the transcriptional profiles of membrane protein-encoding genes differ between Arabidopsis root cell types. This result suggests that different cell types are characterized by specific sets of plasma membrane proteins, which are likely a reflection of their unique biological functions and interactions. To further explore the complexity of the Arabidopsis root cell membrane proteomes, we conducted a co-expression analysis of genes encoding interacting membrane proteins. This study confirmed previously reported interactions between membrane proteins, suggesting that the co-expression of genes at the single cell-type level can be used to support protein network predictions.

Deciphering the molecular basis of tissue-specific gene expression in plants: Can synthetic biology help?

Gene expression differences between distinct cell types are orchestrated by specific sets of transcription factors and epigenetic regulators acting upon the genome. In plants, the mechanisms underlying tissue-specific gene activity remain largely unexplored. Although transcriptional and epigenetic profiling of individual organs, tissues, and more recently, of single cells can easily detect the molecular signatures of different biological samples, how these unique cell identities are established at the mechanistic level is only beginning to be decoded. Computational methods, including machine learning, used in combination with experimental approaches, enable the identification and validation of candidate cis-regulatory elements driving cell-specific expression. Synthetic biology shows great promise not only as a means of testing candidate DNA motifs but also for establishing the general rules of nature driving promoter architecture and for the rational design of genetic circuits in research and agriculture to confer tissue-specific expression to genes or molecular pathways of interest.

Advances and applications of single-cell omics technologies in plant research

Single-cell sequencing approaches reveal the intracellular dynamics of individual cells and answer biological questions with high-dimensional catalogs of millions of cells, including genomics, transcriptomics, chromatin accessibility, epigenomics, and proteomics data across species. These emerging yet thriving technologies have been fully embraced by the field of plant biology, with a constantly expanding portfolio of applications. Here, we introduce the current technical advances used for single-cell omics, especially single-cell genome and transcriptome sequencing. Firstly, we overview methods for protoplast and nucleus isolation and genome and transcriptome amplification. Subsequently, we use well-executed benchmarking studies to highlight advances made through the application of single-cell omics techniques. Looking forward, we offer a glimpse of additional hurdles and future opportunities that will introduce broad adoption of single-cell sequencing with revolutionary perspectives in plant biology.

Gene regulatory networks shape developmental plasticity of root cell types under water extremes in rice

Understanding how roots modulate development under varied irrigation or rainfall is crucial for development of climate-resilient crops. We established a toolbox of tagged rice lines to profile translating mRNAs and chromatin accessibility within specific cell populations. We used these to study roots in a range of environments: plates in the lab, controlled greenhouse stress and recovery conditions, and outdoors in a paddy. Integration of chromatin and mRNA data resolves regulatory networks of the following: cycle genes in proliferating cells that attenuate DNA synthesis under submergence; genes involved in auxin signaling, the circadian clock, and small RNA regulation in ground tissue; and suberin biosynthesis, iron transporters, and nitrogen assimilation in endodermal/exodermal cells modulated with water availability. By applying a systems approach, we identify known and candidate driver transcription factors of water-deficit responses and xylem development plasticity. Collectively, this resource will facilitate genetic improvements in root systems for optimal climate resilience.

Single-Cell RNA Sequencing for Plant Research: Insights and Possible Benefits

In recent years, advances in single-cell RNA sequencing (scRNA-seq) technologies have continued to change our views on biological systems by increasing the spatiotemporal resolution of our analysis to single-cell resolution. Application of scRNA-seq to plants enables the comprehensive characterization of both common and rare cell types and cell states, uncovering new cell types and revealing how cell types relate to each other spatially and developmentally. This review provides an overview of scRNA-seq methodologies, highlights the application of scRNA-seq in plant science, justifies why scRNA-seq is a master player of sequencing, and explains the role of single-cell transcriptomics technologies in environmental stress adaptation, alongside the challenges and prospects of single-cell transcriptomics. Collectively, we put forward a central role of single-cell sequencing in plant research.

Identification of novel regulators required for early development of vein pattern in the cotyledons by single-cell RNA-sequencing

The leaf veins of higher plants contain a highly specialized vascular system comprised of xylem and phloem cells that transport water, organic compounds and mineral nutrients. The development of the vascular system is controlled by phytohormones that interact with complex transcriptional regulatory networks. Before the emergence of true leaves, the cotyledons of young seedlings perform photosynthesis that provides energy for the sustainable growth and survival of seedlings. However, the mechanisms underlying the early development of leaf veins in cotyledons are still not fully understood, in part due to the complex cellular composition of this tissue. To better understand the development of leaf veins, we analyzed 14 117 single cells from 3-day-old cotyledons using single-cell RNA sequencing. Based on gene expression patterns, we identified 10 clusters of cells and traced their developmental trajectories. We discovered multiple new marker genes and developmental features of leaf veins. The transcription factor networks of some cell types indicated potential roles of CYCLING DOF FACTOR 5 (CDF5) and REPRESSOR OF GA (RGA) in the early development and function of the leaf veins in cotyledons. These new findings lay a foundation for understanding the early developmental dynamics of cotyledon veins. The mechanisms underlying the early development of leaf veins in cotyledons are still not fully understood. In this study, we comprehensively characterized the early differentiation and development of leaf veins in 3-day-old cotyledons based on single-cell transcriptome analysis. We identified the cell types and novel marker genes of leaf veins and characterized the novel regulators of leaf vein.

A rice single cell transcriptomic atlas defines the developmental trajectories of rice floret and inflorescence meristems

Rice inflorescence development determines yield and relies on the activity of axillary meristems (AMs); however, high-resolution analysis of its early development is lacking. Here, we have used high-throughput single-cell RNA sequencing to profile 37 571 rice inflorescence cells and constructed a genome-scale gene expression resource covering the inflorescence-to-floret transition during early reproductive development. The differentiation trajectories of florets and AMs were reconstructed, and discrete cell types and groups of regulators in the highly heterogeneous young inflorescence were identified and then validated by in situ hybridization and with fluorescent marker lines. Our data demonstrate that a WOX transcription factor, DWARF TILLER1, regulates flower meristem activity, and provide evidence for the role of auxin in rice inflorescence branching by exploring the expression and biological role of the auxin importer OsAUX1. Our comprehensive transcriptomic atlas of early rice inflorescence development, supported by genetic evidence, provides single-cell-level insights into AM differentiation and floret development.

Single-cell genomics revolutionizes plant development studies across scales

Understanding the development of tissues, organs and entire organisms through the lens of single-cell genomics has revolutionized developmental biology. Although single-cell transcriptomics has been pioneered in animal systems, from an experimental perspective, plant development holds some distinct advantages: cells do not migrate in relation to one another, and new organ formation (of leaves, roots, flowers, etc.) continues post-embryonically from persistent stem cell populations known as meristems. For a time, plant studies lagged behind animal or cell culture-based, single-cell approaches, largely owing to the difficulty in dissociating plant cells from their rigid cell walls. Recent intensive development of single-cell and single-nucleus isolation techniques across plant species has opened up a wide range of experimental approaches. This has produced a rapidly expanding diversity of information across tissue types and species, concomitant with the creative development of methods. In this brief Spotlight, we highlight some of the technical developments and how they have led to profiling single-cell genomics in various plant organs. We also emphasize the contribution of single-cell genomics in revealing developmental trajectories among different cell types within plant organs. Furthermore, we present efforts toward comparative analysis of tissues and organs at a single-cell level. Single-cell genomics is beginning to generate comprehensive information relating to how plant organs emerge from stem cell populations.

Single-cell RNA sequencing technologies and applications: A brief overview

Single-cell RNA sequencing (scRNA-seq) technology has become the state-of-the-art approach for unravelling the heterogeneity and complexity of RNA transcripts within individual cells, as well as revealing the composition of different cell types and functions within highly organized tissues/organs/organisms. Since its first discovery in 2009, studies based on scRNA-seq provide massive information across different fields making exciting new discoveries in better understanding the composition and interaction of cells within humans, model animals and plants. In this review, we provide a concise overview about the scRNA-seq technology, experimental and computational procedures for transforming the biological and molecular processes into computational and statistical data. We also provide an explanation of the key technological steps in implementing the technology. We highlight a few examples on how scRNA-seq can provide unique information for better understanding health and diseases. One important application of the scRNA-seq technology is to build a better and high-resolution catalogue of cells in all living organism, commonly known as atlas, which is key resource to better understand and provide a solution in treating diseases. While great promises have been demonstrated with the technology in all areas, we further highlight a few remaining challenges to be overcome and its great potentials in transforming current protocols in disease diagnosis and treatment.

Development of a single-cell atlas for woodland strawberry (Fragaria vesca) leaves during early Botrytis cinerea infection using single cell RNA-seq

Pathogen invasion leads to fast, local-to-systemic signal transduction that initiates plant defense responses. Despite tremendous progress in past decades, aspects of this process remain unknown, such as which cell types respond first and how signals are transferred among cell types. Here, we used single-cell RNA-seq of more than 50 000 single cells to document the gene expression landscape in leaves of woodland strawberry during infection by Botrytis cinerea and identify major cell types. We constructed a single-cell atlas and characterized the distinct gene expression patterns of hydathode, epidermal, and mesophyll cells during the incubation period of B. cinerea infection. Pseudotime trajectory analysis revealed signals of the transition from normal functioning to defense response in epidermal and mesophyll cells upon B. cinerea infection. Genes related to disease resistance showed different expression patterns among cell types: disease resistance-related genes and gene encoding transcription factors were highly expressed in individual cell types and interacted to trigger plant systemic immunity to B. cinerea. This is the first report to document the of single-cell transcriptional landscape of the plant pathogenic invasion process, it provides new insights into the wholistic dynamics of host-pathogen interactions and can guide the identification of genes and the formulation of strategies for resistant cultivar development.

Reproductive tissue-specific translatome of a rice thermo-sensitive genic male sterile line

Translational regulation, especially tissue- or cell type-specific gene regulation, plays essential roles in plant growth and development. Thermo-sensitive genic male sterile (TGMS) lines have been widely used for hybrid breeding in rice (Oryza sativa). However, little is known about translational regulation during reproductive stage in TGMS rice. Here, we used translating ribosome affinity purification (TRAP) combined with RNA sequencing to investigate the reproductive tissue-specific translatome of TGMS rice expressing FLAG-tagged ribosomal protein L18 (RPL18) from the germline-specific promoter MEIOSIS ARRESTED AT LEPTOTENE1 (MEL1). Differentially expressed genes at the transcriptional and translational levels were enriched in pollen and anther-related formation and development processes. These contained a number of genes reported to be involved in tapetum programmed cell death (PCD) and lipid metabolism during pollen development and anther dehiscence in rice, including several encoding transcription factors and key enzymes, as well as several long non-coding RNAs (lncRNAs) that potentially affect tapetum and pollen-related genes in male sterility. This study represents the first comprehensive reproductive tissue-specific characterization of the translatome in TGMS rice. These results contribute to our understanding of the molecular basis of sterility in TGMS rice and will facilitate further genetic manipulation of TGMS rice in two-line breeding systems.