Single-cell RNA-sequencing of Nicotiana attenuata corolla cells reveals the biosynthetic pathway of a floral scent

The transcriptional integration of environmental cues with root cell type development

Plant roots navigate the soil ecosystem with each cell type uniquely responding to environmental stimuli. Below ground, the plant's response to its surroundings is orchestrated at the cellular level, including morphological and molecular adaptations that shape root system architecture as well as tissue and organ functionality. Our understanding of the transcriptional responses at cell type resolution has been profoundly enhanced by studies of the model plant Arabidopsis thaliana. However, both a comprehensive view of the transcriptional basis of these cellular responses to single and combinatorial environmental cues in diverse plant species remains elusive. In this review, we highlight the ability of root cell types to undergo specific anatomical or morphological changes in response to abiotic and biotic stresses or cues and how they collectively contribute to the plant's overall physiology. We further explore interconnections between stress and the temporal nature of developmental pathways and discuss examples of how this transcriptional reprogramming influences cell type identity and function. Finally, we highlight the power of single-cell and spatial transcriptomic approaches to refine our understanding of how environmental factors fine tune root spatiotemporal development. These complex root system responses underscore the importance of spatiotemporal transcriptional mapping, with significant implications for enhanced agricultural resilience.

Specialized metabolism in St John's wort

The specialized metabolism of St. John's wort, Hypericum perforatum L., is a key focus in medicinal plant research due to its hallmark bioactive compounds hyperforin and hypericin. Known for its traditional medicinal uses dating back to ancient times, St. John's wort is currently used for mild depression therapy. Recent research works have shed light on the biosynthesis of various metabolites in this plant, such as flavonoids, xanthones, hyperforin, and hypericin. The elucidation of these pathways, along with the discovery of novel enzymes like hyperforin synthase, support the pharmaceutical research by enabling scalable production of bioactive compounds for the development of new drugs. Elucidation of the hyperforin biosynthesis based on single-cell RNA-seq is an approach that will be expanded and accelerate the gene discovery and full pathway reconstitution of plant specialized metabolites.

Single-cell RNA sequencing facilitates the elucidation of the complete biosynthesis of the antidepressant hyperforin in St. John's wort

Hyperforin is the compound responsible for the effectiveness of St. John's wort (Hypericum perforatum) as an antidepressant, but its complete biosynthetic pathway remains unknown. Gene discovery based on co-expression analysis of bulk RNA-sequencing data or genome mining failed to discover the missing steps in hyperforin biosynthesis. In this study, we sequenced the 1.54-Gb tetraploid H. perforatum genome assembled into 32 chromosomes with the scaffold N50 value of 42.44 Mb. By single-cell RNA sequencing, we identified a type of cell, "Hyper cells", wherein hyperforin biosynthesis de novo takes place in both the leaves and flowers. Through pathway reconstitution in yeast and tobacco, we identified and characterized four transmembrane prenyltransferases (HpPT1-4) that are localized at the plastid envelope and complete the hyperforin biosynthetic pathway. The hyperforin polycyclic scaffold is created by a reaction cascade involving an irregular isoprenoid coupling and a tandem cyclization. Our findings reveal how and where hyperforin is biosynthesized, enabling synthetic-biology reconstitution of the complete pathway. Thus, this study not only deepens our comprehension of specialized metabolism at the cellular level but also provides strategic guidance for elucidation of the biosynthetic pathways of other specializied metabolites in plants.

Single-cell RNA sequencing reveals a high-resolution cell atlas of petals in Prunus mume at different flowering development stages

Prunus mume (mei), a traditional ornamental plant in China, is renowned for its fragrant flowers, primarily emitted by its petals. However, the cell types of mei petals and where floral volatile synthesis occurs are rarely reported. The study used single-cell RNA sequencing to characterize the gene expression landscape in petals of P. mume 'Fenhong Zhusha' at budding stage (BS) and full-blooming stage (FS). Six major cell types of petals were identified: epidermal cells (ECs), parenchyma cells (PCs), xylem parenchyma cells, phloem parenchyma cells, xylem vessels and fibers, and sieve elements and companion cells complex. Cell-specific marker genes in each cell type were provided. Floral volatiles from mei petals were measured at four flowering development stages, and their emissions increased from BS to FS, and decreased at the withering stage. Fifty-eight differentially expressed genes (DEGs) in benzenoid/phenylpropanoid pathway were screened using bulk RNA-seq data. Twenty-eight DEGs expression increased from BS to FS, indicating that they might play roles in floral volatile synthesis in P. mume, among which PmBAHD3 would participate in benzyl acetate synthesis. ScRNA-seq data showed that 27 DEGs mentioned above were expressed variously in different cell types. In situ hybridization confirmed that PmPAL2, PmCAD1, PmBAHD3,5, and PmEGS1 involved in floral volatile synthesis in mei petals are mainly expressed in EC, PC, and most vascular tissues, consistent with scRNA-seq data. The result indicates that benzyl acetate and eugenol, the characteristic volatiles in mei, are mostly synthesized in these cell types. The first petal single-cell atlas was constructed, offering new insights into the molecular mechanism of floral volatile synthesis.

READRetro: natural product biosynthesis predicting with retrieval-augmented dual-view retrosynthesis

Plants, as a sessile organism, produce various secondary metabolites to interact with the environment. These chemicals have fascinated the plant science community because of their ecological significance and notable biological activity. However, predicting the complete biosynthetic pathways from target molecules to metabolic building blocks remains a challenge. Here, we propose retrieval-augmented dual-view retrosynthesis (READRetro) as a practical bio-retrosynthesis tool to predict the biosynthetic pathways of plant natural products. Conventional bio-retrosynthesis models have been limited in their ability to predict biosynthetic pathways for natural products. READRetro was optimized for the prediction of complex metabolic pathways by incorporating cutting-edge deep learning architectures, an ensemble approach, and two retrievers. Evaluation of single- and multi-step retrosynthesis showed that each component of READRetro significantly improved its ability to predict biosynthetic pathways. READRetro was also able to propose the known pathways of secondary metabolites such as monoterpene indole alkaloids and the unknown pathway of menisdaurilide, demonstrating its applicability to real-world bio-retrosynthesis of plant natural products. For researchers interested in the biosynthesis and production of secondary metabolites, a user-friendly website (https://readretro.net) and the open-source code of READRetro have been made available.

Quantitative Single-Cell Mass Spectrometry Provides a Highly Resolved Analysis of Natural Product Biosynthesis Partitioning in Plants

Plants produce an extraordinary array of natural products (specialized metabolites). Notably, these structurally complex molecules are not evenly distributed throughout plant tissues but are instead synthesized and stored in specific cell types. Elucidating both the biosynthesis and function of natural products would be greatly facilitated by tracking the location of these metabolites at the cell-level resolution. However, detection, identification, and quantification of metabolites in single cells, particularly from plants, have remained challenging. Here, we show that we can definitively identify and quantify the concentrations of 16 molecules from four classes of natural products in individual cells of leaf, root, and petal of the medicinal plant Catharanthus roseus using a plate-based single-cell mass spectrometry method. We show that identical natural products show substantially different patterns of cell-type localization in different tissues. Moreover, we show that natural products are often found in a wide range of concentrations across a population of cells, with some natural products at concentrations of over 100 mM per cell. This single-cell mass spectrometry method provides a highly resolved picture of plant natural product biosynthesis partitioning at a cell-specific resolution.

Genome assembly of Hibiscus sabdariffa L. provides insights into metabolisms of medicinal natural products

Hibiscus sabdariffa L. is a widely cultivated herbaceous plant with diverse applications in food, tea, fiber, and medicine. In this study, we present a high-quality genome assembly of H. sabdariffa using more than 33 Gb of high-fidelity (HiFi) long-read sequencing data, corresponding to ∼20× depth of the genome. We obtained 3 genome assemblies of H. sabdariffa: 1 primary and 2 partially haplotype-resolved genome assemblies. These genome assemblies exhibit N50 contig lengths of 26.25, 11.96, and 14.50 Mb, with genome coverage of 141.3, 86.0, and 88.6%, respectively. We also utilized 26 Gb of total RNA sequencing data to predict 154k, 79k, and 87k genes in the respective assemblies. The completeness of the primary genome assembly and its predicted genes was confirmed by the benchmarking universal single-copy ortholog analysis with a completeness rate of 99.3%. Based on our high-quality genomic resources, we constructed genetic networks for phenylpropanoid and flavonoid metabolism and identified candidate biosynthetic genes, which are responsible for producing key intermediates of roselle-specific medicinal natural products. Our comprehensive genomic and functional analysis opens avenues for further exploration and application of valuable natural products in H. sabdariffa.

Beyond co-expression: pathway discovery for plant pharmaceuticals

Plant natural products have been an important source of medicinal molecules since ancient times. To gain access to the whole diversity of these molecules for pharmaceutical applications, it is important to understand their biosynthetic origins. Whilst co-expression is a reliable tool for identifying gene candidates, a variety of complementary methods can aid in screening or refining candidate selection. Here, we review recently employed plant biosynthetic pathway discovery approaches, and highlight future directions in the field.

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

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

Advances in Single-Cell Transcriptome Sequencing and Spatial Transcriptome Sequencing in Plants

"Omics" typically involves exploration of the structure and function of the entire composition of a biological system at a specific level using high-throughput analytical methods to probe and analyze large amounts of data, including genomics, transcriptomics, proteomics, and metabolomics, among other types. Genomics characterizes and quantifies all genes of an organism collectively, studying their interrelationships and their impacts on the organism. However, conventional transcriptomic sequencing techniques target population cells, and their results only reflect the average expression levels of genes in population cells, as they are unable to reveal the gene expression heterogeneity and spatial heterogeneity among individual cells, thus masking the expression specificity between different cells. Single-cell transcriptomic sequencing and spatial transcriptomic sequencing techniques analyze the transcriptome of individual cells in plant or animal tissues, enabling the understanding of each cell's metabolites and expressed genes. Consequently, statistical analysis of the corresponding tissues can be performed, with the purpose of achieving cell classification, evolutionary growth, and physiological and pathological analyses. This article provides an overview of the research progress in plant single-cell and spatial transcriptomics, as well as their applications and challenges in plants. Furthermore, prospects for the development of single-cell and spatial transcriptomics are proposed.

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.

Single-cell RNA-seq reveals a link of ovule abortion and sugar transport in Camellia oleifera

Camellia oleifera is the most important woody oil crop in China. Seed number per fruit is an important yield trait in C. oleifera. Ovule abortion is generally observed in C. oleifera and significantly decreases the seed number per fruit. However, the mechanisms of ovule abortion remain poorly understood at present. Single-cell RNA sequencing (scRNA-seq) was performed using mature ovaries of two C. oleifera varieties with different ovule abortion rates (OARs). In total, 20,526 high-quality cells were obtained, and 18 putative cell clusters were identified. Six cell types including female gametophyte, protoxylem, protophloem, procambium, epidermis, and parenchyma cells were identified from three main tissue types of ovule, placenta, and pericarp inner layer. A comparative analysis on scRNA-seq data between high- and low-OAR varieties demonstrated that the overall expression of CoSWEET and CoCWINV in procambium cells, and CoSTP in the integument was significantly upregulated in the low-OAR variety. Both the infertile ovule before pollination and the abortion ovule producing after compatible pollination might be attributed to selective abortion caused by low sugar levels in the apoplast around procambium cells and a low capability of hexose uptake in the integument. Here, the first single-cell transcriptional landscape is reported in woody crop ovaries. Our investigation demonstrates that ovule abortion may be related to sugar transport in placenta and ovules and sheds light on further deciphering the mechanism of regulating sugar transport and the improvement of seed yield in C. oleifera.

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.

Ameliorating the effects of multiple stresses on agronomic traits in crops: modern biotechnological and omics approaches

While global climate change poses a significant environmental threat to agriculture, the increasing population is another big challenge to food security. To address this, developing crop varieties with increased productivity and tolerance to biotic and abiotic stresses is crucial. Breeders must identify traits to ensure higher and consistent yields under inconsistent environmental challenges, possess resilience against emerging biotic and abiotic stresses and satisfy customer demands for safer and more nutritious meals. With the advent of omics-based technologies, molecular tools are now integrated with breeding to understand the molecular genetics of genotype-based traits and develop better climate-smart crops. The rapid development of omics technologies offers an opportunity to generate novel datasets for crop species. Identifying genes and pathways responsible for significant agronomic traits has been made possible by integrating omics data with genetic and phenotypic information. This paper discusses the importance and use of omics-based strategies, including genomics, transcriptomics, proteomics and phenomics, for agricultural and horticultural crop improvement, which aligns with developing better adaptability in these crop species to the changing climate conditions.

Single-cell transcriptome sequencing of plant leaf expressing anti-HER2 VHH-FcK cancer therapeutic protein

The transgenic plant is a promising strategy for the production of highly valuable biotherapeutic proteins such as recombinant vaccines and antibodies. To achieve an efficient level of protein production, codon sequences and expression cassette elements need to be optimized. However, the systematical expression of recombinant proteins in plant biomass can generally be controlled for the production of therapeutic proteins after the generation of transgenic plants. Without understanding the transgene expression patterns in plant tissue, it is difficult to enhance further production levels. In this study, single-cell RNA-sequencing (scRNA-seq) analysis of transgenic tobacco (Nicotiana tabacum) leaf, expressing an immunotherapeutic llama antibody against breast cancer, anti-HER2 VHH-Fc, was conducted to obtain data on the expression pattern of tissue-specific cells. These high-quality scRNA-seq data enabled the identification of gene expression patterns by cell types, which can be applied to select the best cell types or tissues for the high production of these recombinant antibodies. These data provide a foundation to elucidate the mechanisms that regulate the biosynthesis of recombinant proteins in N. tabacum.

Chemistry, biosynthesis and biology of floral volatiles: roles in pollination and other functions

Covering: 2010 to 2023Floral volatiles are a chemically diverse group of plant metabolites that serve multiple functions. Their composition is shaped by environmental, ecological and evolutionary factors. This review will summarize recent advances in floral scent research from chemical, molecular and ecological perspectives. It will focus on the major chemical classes of floral volatiles, on notable new structures, and on recent discoveries regarding the biosynthesis and the regulation of volatile emission. Special attention will be devoted to the various functions of floral volatiles, not only as attractants for different types of pollinators, but also as defenses of flowers against enemies. We will also summarize recent findings on how floral volatiles are affected by abiotic stressors, such as increased temperatures and drought, and by other organisms, such as herbivores and flower-dwelling microbes. Finally, this review will indicate current research gaps, such as the very limited knowledge of the isomeric pattern of chiral compounds and its importance in interspecific interactions.

Single-cell RNA sequencing reveals a hierarchical transcriptional regulatory network of terpenoid biosynthesis in cotton secretory glandular cells

Plants can synthesize a wide range of terpenoids in response to various environmental cues. However, the specific regulatory mechanisms governing terpenoid biosynthesis at the cellular level remain largely elusive. In this study, we employed single-cell RNA sequencing to comprehensively characterize the transcriptome profile of cotton leaves and established a hierarchical transcriptional network regulating cell-specific terpenoid production. We observed substantial expression levels of genes associated with the biosynthesis of both volatile terpenes (such as β-caryophyllene and β-myrcene) and non-volatile gossypol-type terpenoids in secretory glandular cells. Moreover, two novel transcription factors, namely GoHSFA4a and GoNAC42, are identified to function downstream of the Gossypium PIGMENT GLAND FORMATION genes. Both transcription factors could directly regulate the expression of terpenoid biosynthetic genes in secretory glandular cells in response to developmental and environmental stimuli. For convenient retrieval of the single-cell RNA sequencing data generated in this study, we developed a user-friendly web server . Our findings not only offer valuable insights into the precise regulation of terpenoid biosynthesis genes in cotton leaves but also provide potential targets for cotton breeding endeavors.

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.

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.

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.

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.

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.

Many different flowers make a bouquet: Lessons from specialized metabolite diversity in plant-pollinator interactions

Flowering plants have evolved extraordinarily diverse metabolites that underpin the floral visual and olfactory signals enabling plant-pollinator interactions. In some cases, these metabolites also provide unusual rewards that specific pollinators depend on. While some metabolites are shared by most flowering plants, many have evolved in restricted lineages in response to the specific selection pressures encountered within different niches. The latter are designated as specialized metabolites. Recent investigations continue to uncover a growing repertoire of unusual specialized metabolites. Increased accessibility to cutting-edge multi-omics technologies (e.g. genome, transcriptome, proteome, metabolome) is now opening new doors to simultaneously uncover the molecular basis of their synthesis and their evolution across diverse plant lineages. Drawing upon the recent literature, this perspective discusses these aspects and, where known, their ecological and evolutionary relevance. A primer on omics-guided approaches to discover the genetic and biochemical basis of functional specialized metabolites is also provided.

Single-cell multi-omics in the medicinal plant Catharanthus roseus

Advances in omics technologies now permit the generation of highly contiguous genome assemblies, detection of transcripts and metabolites at the level of single cells and high-resolution determination of gene regulatory features. Here, using a complementary, multi-omics approach, we interrogated the monoterpene indole alkaloid (MIA) biosynthetic pathway in Catharanthus roseus, a source of leading anticancer drugs. We identified clusters of genes involved in MIA biosynthesis on the eight C. roseus chromosomes and extensive gene duplication of MIA pathway genes. Clustering was not limited to the linear genome, and through chromatin interaction data, MIA pathway genes were present within the same topologically associated domain, permitting the identification of a secologanin transporter. Single-cell RNA-sequencing revealed sequential cell-type-specific partitioning of the leaf MIA biosynthetic pathway that, when coupled with a single-cell metabolomics approach, permitted the identification of a reductase that yields the bis-indole alkaloid anhydrovinblastine. We also revealed cell-type-specific expression in the root MIA pathway.

A novel physiological function of pheromone biosynthesis-activating neuropeptide in production of aggregation pheromone

The western flower thrips, Frankliniella occidentalis, is an insect pest, and its aggregation pheromone (AP) plays a crucial role in the recruitment of both sexes. A novel pheromone biosynthesis-activating neuropeptide (PBAN)-like gene is encoded in F. occidentalis genome, but its physiological function has yet to be elucidated. This study hypothesized the physiological role played by PBAN in mediating AP production. AP has been known to be produced only by male adults in F. occidentalis. Surprisingly, our extraction of headspace volatiles contained two AP components in females as well as in males with similar composition. PBAN injection elevated the AP production whereas RNA interference (RNAi) of the gene expression suppressed the AP production in both sexes. A biosynthetic pathway to produce AP components were predicted and the enzymes catalyzing the main steps were confirmed in their expressions. Individual RNAi treatments of these genes significantly suppressed AP production. RNAi of PBAN gene downregulated the expressions of these biosynthesis-associated genes in both sexes. These results suggest that the novel neuropeptide acts as PBAN mediating AP production through stimulating its biosynthetic machinery in F. occidentalis.

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

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

Single-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.

Reproductive Performance of Zi-Goose Promoted by Red Color Illumination

The color of light affects the reproductive performance of poultry, but it is not clear what efficient illumination strategy could be adopted to improve the reproductive performance of Zi-goose. Red light can increase the average weekly egg production rate, egg production, and qualified production. It can increase the serum GnRH level and decrease the serum PRL, MT, and T4 levels. In our study, red light for 12 h increased the average weekly laying rate, average qualified egg production, and hatching rate of Zi-goose eggs, and increased the serum levels of FSH, LH, P4, E2, MT, T3, and T4. Blue light at 14 h improved the average weekly egg production rate, average egg production, and average qualified egg production, and reduce serum PRL and MT levels to ensure the improvement of reproductive performance of goose. A total of 705,714 overlapping group sequences, 471,145 transcript sequences, and 268,609 single gene sequences were obtained from 18 sequencing samples, with a total length of 323.04, 668.53, and 247.88 M, respectively. About 176,416 unigenes were annotated successfully in six databases, accounting for 65.68% of the total unigenes obtained. 2,106, 2,142, and 8,892 unigenes were identified in the hypothalamus, pituitary gland, and ovary of the birds respectively, with different expressions of light regulation. The hypothalamus, ovary, and pituitary were involved in 279, 327, and 275 KEGG (Kyoto Encyclopedia of Genes and Genomes) metabolic pathways in response to light, respectively. Through further significance analysis and differential discovery rate control, a total of five metabolic pathways were obtained which were closely related to the reproductive hormones of goose. Ten candidate genes related to the reproductive performance of goslings were selected according to the identification results of differentially expressed genes of goslings under red light and white light conditions and the genes involved in metabolic pathways significantly related to the reproductive hormones of goslings. The expression levels of GnRh-1 in the hypothalamus, GnRH-R, FSH β and LH β in the pituitary gland, and FSH-R and LH-R candidate genes in the ovary were higher under the 12 h red light treatment than white light. However, the expression levels of VIP, PRL, and PRL-R candidate genes in the hypothalamus, pituitary and ovary were lower under 12 h red light than under 12 h white light.

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.