Single-Cell Transcriptome Analysis in Plants: Advances and Challenges

Unveiling the toxicological effects and risks of prometryn on red swamp crayfish (Procambarus clarkii): Health assessments, ecological, and molecular insights

Prometryn is commonly used in agricultural and non-agricultural settings. However, possible harm to aquatic organisms remains a persistent concern. Prometryn was also the only one of the 26 triazine herbicides detected in this study. Numerous studies have assessed the harmful effects of prometryn in teleost fish and shrimp. There is a lack of information regarding the ecological and human health risks, as well as the toxic mechanisms affecting crayfish. In this study, human health risk assessment (THQ) and ecological risk assessment (RQ) were conducted on P. clarkii in the rice-crayfish co-culture (IRCC) farming model. The 96 h of exposure to 0.286 mg/L and 1.43 mg/L prometryn was conducted to investigate the potential effects and molecular mechanisms of hepatopancreatic resistance to prometryn in P. clarkii. The original sample analysis revealed that the THQ calculated from the prometryn levels in the muscle and hepatopancreas was below 0.1, suggesting no threat to human health. However, the calculated RQ values were >0.1, indicating a risk to P. clarkii. Histological analysis and biochemical index detection of the experimental samples revealed that the hepatopancreatic injury and oxidative damage in P. clarkii were caused by prometryn. Moreover, transcriptome analysis identified 2512 differentially expressed genes (DEGs) after 96 h of prometryn exposure. Prometryn exposure caused significant changes in metabolic pathways, including oxoacid metabolic processes and cytochrome P450-associated drug metabolism. Further hub gene analysis via PPI indicated that exposure to prometryn may inhibit lipid synthesis, storage, and amino acid transport and affect glucose metabolic pathways and hormone synthesis. Additionally, we hypothesized that prometryn-triggered cell death could be linked to the PI3K-Akt signaling cascade. This study's findings have significant meaning for the efficient and logical application of herbicides in IRCC, ultimately aiding in advancing a highly productive agricultural system.

Integration of CRISPR/Cas9 with multi-omics technologies to engineer secondary metabolite productions in medicinal plant: Challenges and Prospects

Plants acts as living chemical factories that may create a large variety of secondary metabolites, most of which are used in pharmaceutical products. The production of these secondary metabolites is often much lower. Moreover, the primary constraint after discovering potential metabolites is the capacity to manufacture sufficiently for use in industrial and therapeutic contexts. The development of omics technology has brought revolutionary discoveries in various scientific fields, including transcriptomics, metabolomics, and genome sequencing. The metabolic pathways leading to the utilization of new secondary metabolites in the pharmaceutical industry can be identified with the use of these technologies. Genome editing (GEd) is a versatile technology primarily used for site-directed DNA insertions, deletions, replacements, base editing, and activation/repression at the targeted locus. Utilizing GEd techniques such as clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 (CRISPR-associated protein 9), metabolic pathways engineered to synthesize bioactive metabolites optimally. This article will briefly discuss omics and CRISPR/Cas9-based methods to improve secondary metabolite production in medicinal plants.

Single-cell atlases reveal leaf cell-type-specific regulation of metal transporters in the hyperaccumulator Sedum alfredii under cadmium stress

Hyperaccumulation in plants is a complex and dynamic biological process. Sedum alfredii, the most studied Cd hyperaccumulator, can accumulate up to 9000 mg kg-1 Cd in its leaves without suffering toxicity. Although several studies have reported the molecular mechanisms of Cd hyperaccumulation, our understanding of the cell-type-specific transcriptional regulation induced by Cd remains limited. In this study, the first full-length transcriptome of S. alfredii was generated using the PacBio Iso-Seq technology. A total of 18,718,513 subreads (39.90 Gb) were obtained, with an average length of 2133 bp. The single-cell RNA sequencing was employed on leaves of S. alfredii grown under Cd stress. A total of 12,616 high-quality single cells were derived from the control and Cd-treatment samples of S. alfredii leaves. Based on cell heterogeneity and the expression profiles of previously reported marker genes, seven cell types with 12 transcriptionally distinct cell clusters were identified, thereby constructing the first single-cell atlas for S. alfredii leaves. Metal transporters such as CAX5, COPT5, ZIP5, YSL7, and MTP1 were up-regulated in different cell types of S. alfredii leaves under Cd stress. The distinctive gene expression patterns of metal transporters indicate special gene regulatory networks underlying Cd tolerance and hyperaccumulation in S. alfredii. Collectively, our findings are the first observation of the cellular and molecular responses of S. alfredii leaves under Cd stress and lay the cornerstone for future hyperaccumulator scRNA-seq investigations.

Root-specific theanine metabolism and regulation at the single-cell level in tea plants (Camellia sinensis)

Root-synthesized secondary metabolites are critical quality-conferring compounds of foods, plant-derived medicines, and beverages. However, information at a single-cell level on root-specific secondary metabolism remains largely unexplored. L-Theanine, an important quality component of tea, is primarily synthesized in roots, from which it is then transported to new shoots of tea plant. In this study, we present a single-cell RNA sequencing (scRNA-seq)-derived map for the tea plant root, which enabled cell-type-specific analysis of glutamate and ethylamine (two precursors of theanine biosynthesis) metabolism, and theanine biosynthesis, storage, and transport. Our findings support a model in which the theanine biosynthesis pathway occurs via multicellular compartmentation and does not require high co-expression levels of transcription factors and their target genes within the same cell cluster. This study provides novel insights into theanine metabolism and regulation, at the single-cell level, and offers an example for studying root-specific secondary metabolism in other plant systems.

Single-Cell RNA-Sequencing of Soybean Reveals Transcriptional Changes and Antiviral Functions of GmGSTU23 and GmGSTU24 in Response to Soybean Mosaic Virus

Soybean mosaic virus (SMV) stands as a prominent and widespread threat to soybean (Glycine max L. Merr.), the foremost legume crop globally. Attaining a thorough comprehension of the alterations in the transcriptional network of soybeans in response to SMV infection is imperative for a profound insight into the mechanisms of viral pathogenicity and host resistance. In this investigation, we isolated 50 294 protoplasts from the newly developed leaves of soybean plants subjected to both SMV infection and mock inoculation. Subsequently, we utilized single-cell RNA sequencing (scRNA-seq) to construct the transcriptional landscape at a single-cell resolution. Nineteen distinct cell clusters were identified based on the transcriptomic profiles of scRNA-seq. The annotation of three cell types-epidermal cells, mesophyll cells, and vascular cells-was established based on the expression of orthologs to reported marker genes in Arabidopsis thaliana. The differentially expressed genes between the SMV- and mock-inoculated samples were analyzed for different cell types. Our investigation delved deeper into the tau class of glutathione S-transferases (GSTUs), known for their significant contributions to plant responses against abiotic and biotic stress. A total of 57 GSTU genes were identified by a thorough genome-wide investigation in the soybean genome G. max Wm82.a4.v1. Two specific candidates, GmGSTU23 and GmGSTU24, exhibited distinct upregulation in all three cell types in response to SMV infection, prompting their selection for further research. The transient overexpression of GmGSTU23 or GmGSTU24 in Nicotiana benthamiana resulted in the inhibition of SMV infection, indicating the antiviral function of soybean GSTU proteins.

Single-Cell Transcriptomics Applied in Plants

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

Advances in mass spectrometry imaging for plant metabolomics-Expanding the analytical toolbox

Mass spectrometry imaging (MSI) has become increasingly popular in plant science due to its ability to characterize complex chemical, spatial, and temporal aspects of plant metabolism. Over the past decade, as the emerging and unique features of various MSI techniques have continued to support new discoveries in studies of plant metabolism closely associated with various aspects of plant function and physiology, spatial metabolomics based on MSI techniques has positioned it at the forefront of plant metabolic studies, providing the opportunity for far higher resolution than was previously available. Despite these efforts, profound challenges at the levels of spatial resolution, sensitivity, quantitative ability, chemical confidence, isomer discrimination, and spatial multi-omics integration, undoubtedly remain. In this Perspective, we provide a contemporary overview of the emergent MSI techniques widely used in the plant sciences, with particular emphasis on recent advances in methodological breakthroughs. Having established the detailed context of MSI, we outline both the golden opportunities and key challenges currently facing plant metabolomics, presenting our vision as to how the enormous potential of MSI technologies will contribute to progress in plant science in the coming years.

ScRNA-seq reveals the spatiotemporal distribution of camptothecin pathway and transposon activity in Camptotheca acuminata shoot apexes and leaves

Camptotheca acuminata Decne., a significant natural source of the anticancer drug camptothecin (CPT), synthesizes CPT through the monoterpene indole alkaloid (MIA) pathway. In this study, we used single-cell RNA sequencing (scRNA-seq) to generate datasets encompassing over 60,000 cells from C. acuminata shoot apexes and leaves. After cell clustering and annotation, we identified five major cell types in shoot apexes and four in leaves. Analysis of MIA pathway gene expression revealed that most of them exhibited heightened expression in proliferating cells (PCs) and vascular cells (VCs). In contrast to MIA biosynthesis in Catharanthus roseus, CPT biosynthesis in C. acuminata did not exhibit multicellular compartmentalization. Some putative genes encoding enzymes and transcription factors (TFs) related to the biosynthesis of CPT and its derivatives were identified through co-expression analysis. These include 19 cytochrome P450 genes, 8 O-methyltransferase (OMT) genes, and 62 TFs. Additionally, these pathway genes exhibited dynamic expression patterns during VC and EC development. Furthermore, by integrating gene and transposable element (TE) expression data, we constructed novel single-cell transcriptome atlases for C. acuminata. This approach significantly facilitated the identification of rare cell types, including peripheral zone cells (PZs). Some TE families displayed cell type specific, tissue specific, or developmental stage-specific expression patterns, suggesting crucial roles for these TEs in cell differentiation and development. Overall, this study not only provides novel insights into CPT biosynthesis and spatial-temporal TE expression characteristics in C. acuminata, but also serves as a valuable resource for further comprehensive investigations into the development and physiology of this species.

Direct RNA sequencing in plants: Practical applications and future perspectives

The transcriptome serves as a bridge that links genomic variation to phenotypic diversity. A vast number of studies using next-generation RNA sequencing (RNA-seq) over the last 2 decades have emphasized the essential roles of the plant transcriptome in response to developmental and environmental conditions, providing numerous insights into the dynamic changes, evolutionary traces, and elaborate regulation of the plant transcriptome. With substantial improvement in accuracy and throughput, direct RNA sequencing (DRS) has emerged as a new and powerful sequencing platform for precise detection of native and full-length transcripts, overcoming many limitations such as read length and PCR bias that are inherent to short-read RNA-seq. Here, we review recent advances in dissecting the complexity and diversity of plant transcriptomes using DRS as the main technological approach, covering many aspects of RNA metabolism, including novel isoforms, poly(A) tails, and RNA modification, and we propose a comprehensive workflow for processing of plant DRS data. Many challenges to the application of DRS in plants, such as the need for machine learning tools tailored to plant transcriptomes, remain to be overcome, and together we outline future biological questions that can be addressed by DRS, such as allele-specific RNA modification. This technology provides convenient support on which the connection of distinct RNA features is tightly built, sustainably refining our understanding of the biological functions of the plant transcriptome.

Breaking barriers: improving time and space resolution of arbuscular mycorrhizal symbiosis with single-cell sequencing approaches

The cell and molecular bases of arbuscular mycorrhizal (AM) symbiosis, a crucial plant-fungal interaction for nutrient acquisition, have been extensively investigated by coupling traditional RNA sequencing techniques of roots sampled in bulk, with methods to capture subsets of cells such as laser microdissection. These approaches have revealed central regulators of this complex relationship, yet the requisite level of detail to effectively untangle the intricacies of temporal and spatial development remains elusive.The recent adoption of single-cell RNA sequencing (scRNA-seq) techniques in plant research is revolutionizing our ability to dissect the intricate transcriptional profiles of plant-microbe interactions, offering unparalleled insights into the diversity and dynamics of individual cells during symbiosis. The isolation of plant cells is particularly challenging due to the presence of cell walls, leading plant researchers to widely adopt nuclei isolation methods. Despite the increased resolution that single-cell analyses offer, it also comes at the cost of spatial perspective, hence, it is necessary the integration of these approaches with spatial transcriptomics to obtain a comprehensive overview.To date, few single-cell studies on plant-microbe interactions have been published, most of which provide high-resolution cell atlases that will become crucial for fully deciphering symbiotic interactions and addressing future questions. In AM symbiosis research, key processes such as the mutual recognition of partners during arbuscule development within cortical cells, or arbuscule senescence and degeneration, remain poorly understood, and these advancements are expected to shed light on these processes and contribute to a deeper understanding of this plant-fungal interaction.

A single-cell transcriptome atlas reveals the trajectory of early cell fate transition during callus induction in Arabidopsis

The acquisition of pluripotent callus from somatic cells plays an important role in plant development studies and crop genetic improvement. This developmental process incorporates a series of cell fate transitions and reprogramming. However, our understanding of cell heterogeneity and mechanisms of cell fate transition during callus induction remains quite limited. Here, we report a time-series single-cell transcriptome experiment on Arabidopsis root explants that were induced in callus induction medium for 0, 1, and 4 days, and the construction of a detailed single-cell transcriptional atlas of the callus induction process. We identify the cell types responsible for initiating the early callus: lateral root primordium-initiating (LRPI)-like cells and quiescent center (QC)-like cells. LRPI-like cells are derived from xylem pole pericycle cells and are similar to lateral root primordia. We delineate the developmental trajectory of the dedifferentiation of LRPI-like cells into QC-like cells. QC-like cells are undifferentiated pluripotent acquired cells that appear in the early stages of callus formation and play a critical role in later callus development and organ regeneration. We also identify the transcription factors that regulate QC-like cells and the gene expression signatures that are related to cell fate decisions. Overall, our cell-lineage transcriptome atlas for callus induction provides a distinct perspective on cell fate transitions during callus formation, significantly improving our understanding of callus formation.

Consensus clustering and development of a risk signature based on trajectory differential genes of cancer-associated fibroblast subpopulations in colorectal cancer

BACKGROUND

Cancer-associated fibroblasts (CAFs) play a crucial role in the progression of colorectal cancer (CRC). However, the impact of CAF subpopulation trajectory differentiation on CRC remains unclear.

METHODS

In this study, we first explored the trajectory differences of CAFs subpopulations using bulk and integrated single-cell sequencing data, and then performed consensus clustering of CRC samples based on the trajectory differential genes of CAFs subpopulations. Subsequently, we analyzed the heterogeneity of CRC subtypes using bioinformatics. Finally, we constructed relevant prognostic signature using machine learning and validated them using spatial transcriptomic data.

RESULTS

Based on the differential genes of CAFs subpopulation trajectory differentiation, we identified two CRC subtypes (C1 and C2) in this study. Compared to C1, C2 exhibited worse prognosis, higher immune evasion microenvironment and high CAF characteristics. C1 was primarily associated with metabolism, while C2 was primarily associated with cell metastasis and immune regulation. By combining 101 combinations of 10 machine learning algorithms, we developed a High-CAF risk signatures (HCAFRS) based on the C2 characteristic gene. HCAFRS was an independent prognostic factor for CRC and, when combined with clinical parameters, significantly predicted the overall survival of CRC patients. HCAFRS was closely associated with epithelial-mesenchymal transition, angiogenesis, and hypoxia. Furthermore, the risk score of HCAFRS was mainly derived from CAFs and was validated in the spatial transcriptomic data.

CONCLUSION

In conclusion, HCAFRS has the potential to serve as a promising prognostic indicator for CRC, improving the quality of life for CRC patients.

Developing a simple and rapid method for cell-specific transcriptome analysis through laser microdissection: insights from citrus rind with broader implications

BACKGROUND

With the rapid development of single-cell sequencing technology, histological studies are no longer limited to conventional homogenized tissues. Laser microdissection enables the accurate isolation of specific tissues or cells, and when combined with next-generation sequencing, it can reveal important biological processes at the cellular level. However, traditional laser microdissection techniques have often been complicated and time-consuming, and the quality of the RNA extracted from the collected samples has been inconsistent, limiting follow-up studies. Therefore, an improved, simple, and efficient laser microdissection method is urgently needed.

RESULTS

We omitted the sample fixation and cryoprotectant addition steps. Instead, fresh samples were embedded in Optimal Cutting Temperature medium within 1.5 ml centrifuge tube caps, rapidly frozen with liquid nitrogen, and immediately subjected to cryosectioning. A series of section thicknesses of citrus rind were tested for RNA extraction, which showed that 18 μm thickness yielded the highest quality RNA. By shortening the dehydration time to one minute per ethanol gradient and omitting the tissue clearing step, the resulting efficient dehydration and preserved morphology ensured high-quality RNA extraction. We also propose a set of laser microdissection parameters by adjusting the laser power to optimal values, reducing the aperture size, and lowering the pulse frequency. Both the epidermal and subepidermal cells from the citrus rind were collected, and RNA extraction was completed within nine hours. Using this efficient method, the transcriptome sequencing of the isolated tissues generated high-quality data with average Q30 values and mapping rates exceeding 91%. Moreover, the transcriptome analysis revealed significant differences between the cell layers, further confirming the effectiveness of our isolation approach.

CONCLUSIONS

We developed a simple and rapid laser microdissection method and demonstrated its effectiveness through a study based on citrus rind, from which we generated high-quality transcriptomic data. This fast and efficient method of cell isolation, combined with transcriptome sequencing not only contributes to precise histological studies at the cellular level in citrus but also provides a promising approach for cell-specific transcriptome analysis in a broader range of other plant tissues.

Multi-Omics Approaches in Oil Palm Research: A Comprehensive Review of Metabolomics, Proteomics, and Transcriptomics Based on Low-Temperature Stress

Oil palm (Elaeis guineensis Jacq.) is a typical tropical oil crop with a temperature of 26-28 °C, providing approximately 35% of the total world's vegetable oil. Growth and productivity are significantly affected by low-temperature stress, resulting in inhibited growth and substantial yield losses. To comprehend the intricate molecular mechanisms underlying the response and acclimation of oil palm under low-temperature stress, multi-omics approaches, including metabolomics, proteomics, and transcriptomics, have emerged as powerful tools. This comprehensive review aims to provide an in-depth analysis of recent advancements in multi-omics studies on oil palm under low-temperature stress, including the key findings from omics-based research, highlighting changes in metabolite profiles, protein expression, and gene transcription, as well as including the potential of integrating multi-omics data to reveal novel insights into the molecular networks and regulatory pathways involved in the response to low-temperature stress. This review also emphasizes the challenges and prospects of multi-omics approaches in oil palm research, providing a roadmap for future investigations. Overall, a better understanding of the molecular basis of the response of oil palm to low-temperature stress will facilitate the development of effective breeding and biotechnological strategies to improve the crop's resilience and productivity in changing climate scenarios.

Crosstalk between Rho of Plants GTPase signalling and plant hormones

Rho of Plants (ROPs) constitute a plant-specific subset of small guanine nucleotide-binding proteins within the Cdc42/Rho/Rac family. These versatile proteins regulate diverse cellular processes, including cell growth, cell division, cell morphogenesis, organ development, and stress responses. In recent years, the dynamic cellular and subcellular behaviours orchestrated by ROPs have unveiled a notable connection to hormone-mediated organ development and physiological responses, thereby expanding our knowledge of the functions and regulatory mechanisms of this signalling pathway. This review delineates advancements in understanding the interplay between plant hormones and the ROP signalling cascade, focusing primarily on the connections with auxin and abscisic acid pathways, alongside preliminary discoveries in cytokinin, brassinosteroid, and salicylic acid responses. It endeavours to shed light on the intricate, coordinated mechanisms bridging cell- and tissue-level signals that underlie plant cell behaviour, organ development, and physiological processes, and highlights future research prospects and challenges in this rapidly developing field.

A spatially resolved multiomic single-cell atlas of soybean development

Cis-regulatory elements (CREs) precisely control spatiotemporal gene expression in cells. Using a spatially resolved single-cell atlas of gene expression with chromatin accessibility across ten soybean tissues, we identified 103 distinct cell types and 303,199 accessible chromatin regions (ACRs). Nearly 40% of the ACRs showed cell-type-specific patterns and were enriched for transcription factor (TF) motifs defining diverse cell identities. We identified de novo enriched TF motifs and explored conservation of gene regulatory networks underpinning legume symbiotic nitrogen fixation. With comprehensive developmental trajectories for endosperm and embryo, we uncovered the functional transition of the three sub-cell types of endosperm, identified 13 sucrose transporters sharing the DOF11 motif that were co-up-regulated in late peripheral endosperm and identified key embryo cell-type specification regulators during embryogenesis, including a homeobox TF that promotes cotyledon parenchyma identity. This resource provides a valuable foundation for analyzing gene regulatory programs in soybean cell types across tissues and life stages.

Single-cell transcriptome landscape elucidates the cellular and developmental responses to tomato chlorosis virus infection in tomato leaf

Plant viral diseases compromise the growth and yield of the crop globally, and they tend to be more serious under extreme temperatures and drought climate changes. Currently, regulatory dynamics during plant development and in response to virus infection at the plant cell level remain largely unknown. In this study, single-cell RNA sequencing on 23 226 individual cells from healthy and tomato chlorosis virus-infected leaves was established. The specific expression and epigenetic landscape of each cell type during the viral infection stage were depicted. Notably, the mesophyll cells showed a rapid function transition in virus-infected leaves, which is consistent with the pathological changes such as thinner leaves and decreased chloroplast lamella in virus-infected samples. Interestingly, the F-box protein SKIP2 was identified to play a pivotal role in chlorophyll maintenance during virus infection in tomato plants. Knockout of the SlSKIP2 showed a greener leaf state before and after virus infection. Moreover, we further demonstrated that SlSKIP2 was located in the cytomembrane and nucleus and directly regulated by ERF4. In conclusion, with detailed insights into the plant responses to viral infections at the cellular level, our study provides a genetic framework and gene reference in plant-virus interaction and breeding in the future research.

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

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

Combining enzyme and metabolic engineering for microbial supply of therapeutic phytochemicals

The history of pharmacology is deeply intertwined with plant-derived compounds, which continue to be crucial in drug development. However, their complex structures and limited availability in plants challenge drug discovery, optimization, development, and industrial production via chemical synthesis or natural extraction. This review delves into the integration of metabolic and enzyme engineering to leverage micro-organisms as platforms for the sustainable and reliable production of therapeutic phytochemicals. We argue that engineered microbes can serve a triple role in this paradigm: facilitating pathway discovery, acting as cell factories for scalable manufacturing, and functioning as platforms for chemical derivatization. Analyzing recent progress and outlining future directions, the review highlights microbial biotechnology's transformative potential in expanding plant-derived human therapeutics' discovery and supply chains.

Chromosome-Scale, De Novo, Phased Genome Assemblies of Three Australian Limes: Citrus australasica, C. inodora, and C. glauca

Huanglongbing (HLB) is a severe citrus disease worldwide. Wild Australian limes like Citrus australasica, C. inodora, and C. glauca possess beneficial HLB resistance traits. Individual trees of the three taxa were extensively used in a breeding program for over a decade to introgress resistance traits into commercial-quality citrus germplasm. We generated high-quality, phased, de novo genome assemblies of the three Australian limes using PacBio long-read sequencing. The genome assembly sizes of the primary and alternate haplotypes were determined for C. australasica (337 Mb/335 Mb), C. inodora (304 Mb/299 Mb), and C. glauca (376 Mb/379 Mb). The nine chromosome-scale scaffolds included 86-91% of the genome sequences generated. The integrity and completeness of the assembled genomes were estimated to be at 97.2-98.8%. Gene annotation studies identified 25,461 genes in C. australasica, 27,665 in C. inodora, and 30,067 in C. glauca. Genes belonging to 118 orthogroups were specific to Australian lime genomes compared to other citrus genomes analyzed. Significantly fewer canonical resistance (R) genes were found in C. inodora and C. glauca (319 and 449, respectively) compared to C. australasica (576), C. clementina (579), and C. sinensis (651). Similar patterns were observed for other gene families associated with potential HLB resistance, including Phloem protein 2 (PP2) and Callose synthase (CalS) genes predicted in the Australian lime genomes. The genomic information on Australian limes developed in the present study will help understand the genetic basis of HLB resistance.

Single-cell transcriptome profiling reveals the spatiotemporal distribution of triterpenoid saponin biosynthesis and transposable element activity in Gynostemma pentaphyllum shoot apexes and leaves

Gynostemma pentaphyllum (Thunb.) Makino is an important producer of dammarene-type triterpenoid saponins. These saponins (gypenosides) exhibit diverse pharmacological benefits such as anticancer, antidiabetic, and immunomodulatory effects, and have major potential in the pharmaceutical and health care industries. Here, we employed single-cell RNA sequencing (scRNA-seq) to profile the transcriptomes of more than 50,000 cells derived from G. pentaphyllum shoot apexes and leaves. Following cell clustering and annotation, we identified five major cell types in shoot apexes and four in leaves. Each cell type displayed substantial transcriptomic heterogeneity both within and between tissues. Examining gene expression patterns across various cell types revealed that gypenoside biosynthesis predominantly occurred in mesophyll cells, with heightened activity observed in shoot apexes compared to leaves. Furthermore, we explored the impact of transposable elements (TEs) on G. pentaphyllum transcriptomic landscapes. Our findings the highlighted the unbalanced expression of certain TE families across different cell types in shoot apexes and leaves, marking the first investigation of TE expression at the single-cell level in plants. Additionally, we observed dynamic expression of genes involved in gypenoside biosynthesis and specific TE families during epidermal and vascular cell development. The involvement of TE expression in regulating cell differentiation and gypenoside biosynthesis warrant further exploration. Overall, this study not only provides new insights into the spatiotemporal organization of gypenoside biosynthesis and TE activity in G. pentaphyllum shoot apexes and leaves but also offers valuable cellular and genetic resources for a deeper understanding of developmental and physiological processes at single-cell resolution in this species.

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

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

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

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

Regulatory networks in plant responses to drought and cold stress

Drought and cold represent distinct types of abiotic stress, each initiating unique primary signaling pathways in response to dehydration and temperature changes, respectively. However, a convergence at the gene regulatory level is observed where a common set of stress-responsive genes is activated to mitigate the impacts of both stresses. In this review, we explore these intricate regulatory networks, illustrating how plants coordinate distinct stress signals into a collective transcriptional strategy. We delve into the molecular mechanisms of stress perception, stress signaling, and the activation of gene regulatory pathways, with a focus on insights gained from model species. By elucidating both the shared and distinct aspects of plant responses to drought and cold, we provide insight into the adaptive strategies of plants, paving the way for the engineering of stress-resilient crop varieties that can withstand a changing climate.

Engineering Plant Cell Fates and Functions for Agriculture and Industry

Many plant species are grown to enable access to specific organs or tissues, such as seeds, fruits, or stems. In some cases, a value is associated with a molecule that accumulates in a single type of cell. Domestication and subsequent breeding have often increased the yields of these target products by increasing the size, number, and quality of harvested organs and tissues but also via changes to overall plant growth architecture to suit large-scale cultivation. Many of the mutations that underlie these changes have been identified in key regulators of cellular identity and function. As key determinants of yield, these regulators are key targets for synthetic biology approaches to engineer new forms and functions. However, our understanding of many plant developmental programs and cell-type specific functions is still incomplete. In this Perspective, we discuss how advances in cellular genomics together with synthetic biology tools such as biosensors and DNA-recording devices are advancing our understanding of cell-specific programs and cell fates. We then discuss advances and emerging opportunities for cell-type-specific engineering to optimize plant morphology, responses to the environment, and the production of valuable compounds.

Spatial co-transcriptomics reveals discrete stages of the arbuscular mycorrhizal symbiosis

The symbiotic interaction of plants with arbuscular mycorrhizal (AM) fungi is ancient and widespread. Plants provide AM fungi with carbon in exchange for nutrients and water, making this interaction a prime target for crop improvement. However, plant-fungal interactions are restricted to a small subset of root cells, precluding the application of most conventional functional genomic techniques to study the molecular bases of these interactions. Here we used single-nucleus and spatial RNA sequencing to explore both Medicago truncatula and Rhizophagus irregularis transcriptomes in AM symbiosis at cellular and spatial resolution. Integrated, spatially registered single-cell maps revealed infected and uninfected plant root cell types. We observed that cortex cells exhibit distinct transcriptome profiles during different stages of colonization by AM fungi, indicating dynamic interplay between both organisms during establishment of the cellular interface enabling successful symbiosis. Our study provides insight into a symbiotic relationship of major agricultural and environmental importance and demonstrates a paradigm combining single-cell and spatial transcriptomics for the analysis of complex organismal interactions.

Comparative Metabolomics and Transcriptome Studies of Two Forms of Rhododendron chrysanthum Pall. under UV-B Stress

Rhododendron chrysanthum Pall. (R. chrysanthum), a plant with UV-B resistance mechanisms that can adapt to alpine environments, has gained attention as an important plant resource with the ability to cope with UV-B stress. In this experiment, R. chrysanthums derived from the same origin were migrated to different culture environments (artificial climate chamber and intelligent artificial incubator) to obtain two forms of R. chrysanthum. After UV-B irradiation, 404 metabolites and 93,034 unigenes were detected. Twenty-six of these different metabolites were classified as UV-B-responsive metabolites. Glyceric acid is used as a potential UV-B stress biomarker. The domesticated Rhododendron chrysanthum Pall. had high amino acid and SOD contents. The study shows that the domesticated Rhododendron chrysanthum Pall. has significant UV-B resistance. The transcriptomics results show that the trends of DEGs after UV-B radiation were similar for both forms of R. chrysanthum: cellular process and metabolic process accounted for a higher proportion in biological processes, cellular anatomical entity accounted for the highest proportion in the cellular component, and catalytic activity and binding accounted for the highest proportion in the molecular function category. Through comparative study, the forms of metabolites resistant to UV-B stress in plants can be reflected, and UV-B radiation absorption complexes can be screened for application in future specific practices. Moreover, by comparing the differences in response to UV-B stress between the two forms of R. chrysanthum, references can be provided for cultivating domesticated plants with UV-B stress resistance characteristics. Research on the complex mechanism of plant adaptation to UV-B will be aided by these results.

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

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

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

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

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

KEY MESSAGE

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

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

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

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

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

Towards high-throughput parallel imaging and single-cell transcriptomics of microbial eukaryotic plankton

Single-cell transcriptomics has the potential to provide novel insights into poorly studied microbial eukaryotes. Although several such technologies are available and benchmarked on mammalian cells, few have been tested on protists. Here, we applied a microarray single-cell sequencing (MASC-seq) technology, that generates microscope images of cells in parallel with capturing their transcriptomes, on three species representing important plankton groups with different cell structures; the ciliate Tetrahymena thermophila, the diatom Phaeodactylum tricornutum, and the dinoflagellate Heterocapsa sp. Both the cell fixation and permeabilization steps were adjusted. For the ciliate and dinoflagellate, the number of transcripts of microarray spots with single cells were significantly higher than for background spots, and the overall expression patterns were correlated with that of bulk RNA, while for the much smaller diatom cells, it was not possible to separate single-cell transcripts from background. The MASC-seq method holds promise for investigating "microbial dark matter", although further optimizations are necessary to increase the signal-to-noise ratio.

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.

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

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

Applications of some advanced sequencing, analytical, and computational approaches in medicinal plant research: a review

The potential active chemicals found in medicinal plants, which have long been employed as natural medicines, are abundant. Exploring the genes responsible for producing these compounds has given new insights into medicinal plant research. Previously, the authentication of medicinal plants was done via DNA marker sequencing. With the advancement of sequencing technology, several new techniques like next-generation sequencing, single molecule sequencing, and fourth-generation sequencing have emerged. These techniques enshrined the role of molecular approaches for medicinal plants because all the genes involved in the biosynthesis of medicinal compound(s) could be identified through RNA-seq analysis. In several research insights, transcriptome data have also been used for the identification of biosynthesis pathways. miRNAs in several medicinal plants and their role in the biosynthesis pathway as well as regulation of the disease-causing genes were also identified. In several research articles, an in silico study was also found to be effective in identifying the inhibitory effect of medicinal plant-based compounds against virus' gene(s). The use of advanced analytical methods like spectroscopy and chromatography in metabolite proofing of secondary metabolites has also been reported in several recent research findings. Furthermore, advancement in molecular and analytic methods will give new insight into studying the traditionally important medicinal plants that are still unexplored.

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.

Proteogenomics-based functional genome research: approaches, applications, and perspectives in plants

Proteogenomics (PG) integrates the proteome with the genome and transcriptome to refine gene models and annotation. Coupled with single-cell (SC) assays, PG effectively distinguishes heterogeneity among cell groups. Affiliating spatial information to PG reveals the high-resolution circuitry within SC atlases. Additionally, PG can investigate dynamic changes in protein-coding genes in plants across growth and development as well as stress and external stimulation, significantly contributing to the functional genome. Here we summarize existing PG research in plants and introduce the technical features of various methods. Combining PG with other omics, such as metabolomics and peptidomics, can offer even deeper insights into gene functions. We argue that the application of PG will represent an important font of foundational knowledge for plants.

Spatial transcriptomics drives a new era in plant research

The plant community lags far behind the animal and human fields concerning the application of single‐cell methodologies. This is primarily due to the challenges associated with plant tissue dissection and the limitations of the available technologies. However, recent advances in spatial transcriptomics enable the study of single‐cells derived from plant tissues from a spatial perspective. This technology is already successfully used to identify cell types, reconstruct cell‐fate lineages, and reveal cell‐to‐cell interactions. Future technological advancements will overcome the challenges in sample processing, data analysis, and the integration of multiple‐omics technologies. Thanks to spatial transcriptomics, we anticipate several plant research projects to significantly advance our understanding of critical aspects of plant biology.

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

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

A rapid and sensitive, multiplex, whole mount RNA fluorescence in situ hybridization and immunohistochemistry protocol

BACKGROUND

In the past few years, there has been an explosion in single-cell transcriptomics datasets, yet in vivo confirmation of these datasets is hampered in plants due to lack of robust validation methods. Likewise, modeling of plant development is hampered by paucity of spatial gene expression data. RNA fluorescence in situ hybridization (FISH) enables investigation of gene expression in the context of tissue type. Despite development of FISH methods for plants, easy and reliable whole mount FISH protocols have not yet been reported.

RESULTS

We adapt a 3-day whole mount RNA-FISH method for plant species based on a combination of prior protocols that employs hybridization chain reaction (HCR), which amplifies the probe signal in an antibody-free manner. Our whole mount HCR RNA-FISH method shows expected spatial signals with low background for gene transcripts with known spatial expression patterns in Arabidopsis inflorescences and monocot roots. It allows simultaneous detection of three transcripts in 3D. We also show that HCR RNA-FISH can be combined with endogenous fluorescent protein detection and with our improved immunohistochemistry (IHC) protocol.

CONCLUSIONS

The whole mount HCR RNA-FISH and IHC methods allow easy investigation of 3D spatial gene expression patterns in entire plant tissues.

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.

NRTPredictor: identifying rice root cell state in single-cell RNA-seq via ensemble learning

BACKGROUND

Single-cell RNA sequencing (scRNA-seq) measurements of gene expression show great promise for studying the cellular heterogeneity of rice roots. How precisely annotating cell identity is a major unresolved problem in plant scRNA-seq analysis due to the inherent high dimensionality and sparsity.

RESULTS

To address this challenge, we present NRTPredictor, an ensemble-learning system, to predict rice root cell stage and mine biomarkers through complete model interpretability. The performance of NRTPredictor was evaluated using a test dataset, with 98.01% accuracy and 95.45% recall. With the power of interpretability provided by NRTPredictor, our model recognizes 110 marker genes partially involved in phenylpropanoid biosynthesis. Expression patterns of rice root could be mapped by the above-mentioned candidate genes, showing the superiority of NRTPredictor. Integrated analysis of scRNA and bulk RNA-seq data revealed aberrant expression of Epidermis cell subpopulations in flooding, Pi, and salt stresses.

CONCLUSION

Taken together, our results demonstrate that NRTPredictor is a useful tool for automated prediction of rice root cell stage and provides a valuable resource for deciphering the rice root cellular heterogeneity and the molecular mechanisms of flooding, Pi, and salt stresses. Based on the proposed model, a free webserver has been established, which is available at https://www.cgris.net/nrtp .

Harnessing the Genetic Basis of Sorghum Biomass-Related Traits to Facilitate Bioenergy Applications

The extensive use of fossil fuels and global climate change have raised ever-increasing attention to sustainable development, global food security and the replacement of fossil fuels by renewable energy. Several C4 monocot grasses have excellent photosynthetic ability, stress tolerance and may rapidly produce biomass in marginal lands with low agronomic inputs, thus representing an important source of bioenergy. Among these grasses, Sorghum bicolor has been recognized as not only a promising bioenergy crop but also a research model due to its diploidy, simple genome, genetic diversity and clear orthologous relationship with other grass genomes, allowing sorghum research to be easily translated to other grasses. Although sorghum molecular genetic studies have lagged far behind those of major crops (e.g., rice and maize), recent advances have been made in a number of biomass-related traits to dissect the genetic loci and candidate genes, and to discover the functions of key genes. However, molecular and/or targeted breeding toward biomass-related traits in sorghum have not fully benefited from these pieces of genetic knowledge. Thus, to facilitate the breeding and bioenergy applications of sorghum, this perspective summarizes the bioenergy applications of different types of sorghum and outlines the genetic control of the biomass-related traits, ranging from flowering/maturity, plant height, internode morphological traits and metabolic compositions. In particular, we describe the dynamic changes of carbohydrate metabolism in sorghum internodes and highlight the molecular regulators involved in the different stages of internode carbohydrate metabolism, which affects the bioenergy utilization of sorghum biomass. We argue the way forward is to further enhance our understanding of the genetic mechanisms of these biomass-related traits with new technologies, which will lead to future directions toward tailored designing sorghum biomass traits suitable for different bioenergy applications.

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.

Analysis of the response mechanisms of Pinellia ternata to terahertz wave stresses using transcriptome and metabolic data

Pinellia ternata (Thunb.) Breit. (Araceae), a significant medicinal plant, has been used to treat various diseases for centuries. Terahertz radiation (THZ) is located between microwaves and infrared rays on the electromagnetic spectrum. THZ possesses low single-photon energy and a spectral fingerprint, but its effects on plant growth have not yet been investigated. The study's primary objective was to examine the transcriptome and metabolome databases of the SY line to provide a new perspective for identifying genes associated with resistance and growth promotion and comprehending the underlying molecular mechanism. Variations in the biological characteristics of P. ternata grown under control and experimental conditions were analyzed to determine the effect of THZ. Compared with the control group, phenotypic variables such as leaf length, petiole length, number of leaves, leaf petiole diameter, and proliferation coefficient exhibited significant differences. P. ternata response to THZ was analyzed regarding the effects of various coercions on root exudation. The experimental group contained considerably more sugar alcohol than the control group. The transcriptome analysis revealed 1,695 differentially expressed genes (DEGs), including 509 upregulated and 1,186 downregulated genes. In the KEGG-enriched plant hormone signaling pathway, there were 19 differentially expressed genes, 13 of which were downregulated and six of which were upregulated. In the metabolomic analysis, approximately 416 metabolites were uncovered. There were 112 DEMs that were downregulated, whereas 148 were upregulated. The P. ternata leaves displayed significant differences in phytohormone metabolites, specifically in brassinolide (BR) and abscisic acid (ABA). The rise in BR triggers alterations in internal plant hormones, resulting in faster growth and development of P. ternata. Our findings demonstrated a link between THZ and several metabolic pathway processes, which will enhance our understanding of P. ternata mechanisms.

Highlighter: An optogenetic system for high-resolution gene expression control in plants

Optogenetic actuators have revolutionized the resolution at which biological processes can be controlled. In plants, deployment of optogenetics is challenging due to the need for these light-responsive systems to function in the context of horticultural light environments. Furthermore, many available optogenetic actuators are based on plant photoreceptors that might crosstalk with endogenous signaling processes, while others depend on exogenously supplied cofactors. To overcome such challenges, we have developed Highlighter, a synthetic, light-gated gene expression system tailored for in planta function. Highlighter is based on the photoswitchable CcaS-CcaR system from cyanobacteria and is repurposed for plants as a fully genetically encoded system. Analysis of a re-engineered CcaS in Escherichia coli demonstrated green/red photoswitching with phytochromobilin, a chromophore endogenous to plants, but also revealed a blue light response likely derived from a flavin-binding LOV-like domain. We deployed Highlighter in transiently transformed Nicotiana benthamiana for optogenetic control of fluorescent protein expression. Using light to guide differential fluorescent protein expression in nuclei of neighboring cells, we demonstrate unprecedented spatiotemporal control of target gene expression. We implemented the system to demonstrate optogenetic control over plant immunity and pigment production through modulation of the spectral composition of broadband visible (white) light. Highlighter is a step forward for optogenetics in plants and a technology for high-resolution gene induction that will advance fundamental plant biology and provide new opportunities for crop improvement.

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

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

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

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