Single-Cell Transcriptome Analysis in Plants: Advances and Challenges

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.

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.

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.

Analysis of meristems and plant regeneration at single-cell resolution

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

Whole-mount RNA in situ hybridization technique in Torenia ovules

The expression pattern of an interested gene at a cellular level provides strong evidence for its functions. RNA in situ hybridization has been proved to be a powerful tool in detecting the spatial-temporal expression pattern of a gene in various organisms. However, classical RNA in situ hybridization (ISH) technique is time-consuming and requires sophisticated sectioning skills. Therefore, we developed a method for whole-mount in situ hybridization (WISH) on ovules of Torenia fournieri, which is a model species in the study of plant reproduction. T. fournieri possesses ovules with protruding embryo sacs, making it easy to be observed and imaged through simple manipulation. To determine the effect of classical ISH and our newly established WISH, we detected the expression of a D-class gene, TfSTK3, using both methods. The expression patterns of TfSTK3 are similar in classical ISH and WISH, confirming reliability of the WISH method. Compared with WISH, classical ISH always leads to distorted embryo sacs, hence difficult to distinguish signals within the female gametophyte. To understand whether our WISH protocol also works well in detecting genes expressed within embryo sacs, we further examined the expression of a synergid-enriched candidate, TfPMEI1, and clearly observed specific signals within two synergid cells. To summarize, our WISH technique allows to visualize gene expression patterns in ovules of T. fournieri within one week and will benefit the field of plant reproduction in the future.

Gene expression variations and allele-specific expression of two rice and their hybrid in caryopses at single-nucleus resolution

Seeds are an indispensable part of the flowering plant life cycle and a critical determinant of agricultural production. Distinct differences in the anatomy and morphology of seeds separate monocots and dicots. Although some progress has been made with respect to understanding seed development in Arabidopsis, the transcriptomic features of monocotyledon seeds at the cellular level are much less understood. Since most important cereal crops, such as rice, maize, and wheat, are monocots, it is essential to study transcriptional differentiation and heterogeneity during seed development at a finer scale. Here, we present single-nucleus RNA sequencing (snRNA-seq) results of over three thousand nuclei from caryopses of the rice cultivars Nipponbare and 9311 and their intersubspecies F₁ hybrid. A transcriptomics atlas that covers most of the cell types present during the early developmental stage of rice caryopses was successfully constructed. Additionally, novel specific marker genes were identified for each nuclear cluster in the rice caryopsis. Moreover, with a focus on rice endosperm, the differentiation trajectory of endosperm subclusters was reconstructed to reveal the developmental process. Allele-specific expression (ASE) profiling in endosperm revealed 345 genes with ASE (ASEGs). Further pairwise comparisons of the differentially expressed genes (DEGs) in each endosperm cluster among the three rice samples demonstrated transcriptional divergence. Our research reveals differentiation in rice caryopsis from the single-nucleus perspective and provides valuable resources to facilitate clarification of the molecular mechanism underlying caryopsis development in rice and other monocots.

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

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

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

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

Metabolic profiling reveals altered tryptophan metabolism in patients with kawasaki disease

Kawasaki disease (KD) is a childhood vasculitis disease that is difficult to diagnose, and there is an urgent need for the identification of accurate and specific biomarkers. Here, we aimed to investigate metabolic alterations in patients with KD to determine novel diagnostic and prognostic biomarkers for KD. To this end, we performed untargeted metabolomics and found that several metabolic pathways were significantly enriched, including amino acid, lipid, and tryptophan metabolism, the latter of which we focused on particularly. Tryptophan-targeted metabolomics was conducted to explore the role of tryptophan metabolism in KD. The results showed that Trp and indole acetic acid (IAA) levels markedly decreased, and that l-kynurenine (Kyn) and kynurenic acid (Kyna) levels were considerably higher in patients with KD than in healthy controls. Changes in Trp, IAA, Kyn, and Kyna levels in a KD coronary arteritis mouse model were consistent with those in patients with KD. We further analyzed public single-cell RNA sequencing data of patients with KD and revealed that their peripheral blood mononuclear cells showed Aryl hydrocarbon receptor expression that was remarkably higher than that of healthy children. These results suggest that the Trp metabolic pathway is significantly altered in KD and that metabolic indicators may serve as novel diagnostic and therapeutic biomarkers for KD.

Authentication of Single Herbal Powders Enabled by Microscopy-Guided In Situ Auto-sampling Combined with Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry

In the long history of investigation of herbal products, microscopic examination has greatly contributed to the authentication of herbs in a powder form. However, it cannot provide the chemical profiles of herbal powders and thus is limited to morphological identification. In this work, we present a label-free and automatic approach for the characterization and identification of single herbal powders and their adulterants, enabled through the combination of microscopy-guided auto-sampling and matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS). To meet the demand for automatic and highly efficient in situ extraction, the glass slide was coated with gelatin to immobilize dried herbal powders that cannot stick to the glass slide like fresh and hydrated cells. The gelatin coating also facilitated the pump-out of chemical components and prevented diffusion across the interface enabled by the formation of a tight contact at the probe tip and surface. Optical microscopy was applied to acquire the microstructure and position of the herbal powders immobilized on the gelatin-coated slide. The candidate single herbal powders were picked out by a software for subsequent auto-sampling and MALDI MS identification. The combination of microstructure features and chemical profiles significantly improved the authentication capability of microscopic examination.

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

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

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

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

BarleyExpDB: an integrative gene expression database for barley

BACKGROUND

RNA-sequencing (RNA-seq) has been widely used to study the dynamic expression patterns of transcribed genes, which can lead to new biological insights. However, processing and analyzing these huge amounts of histological data remains a great challenge for wet labs and field researchers who lack bioinformatics experience and computational resources.

RESULTS

We present BarleyExpDB, an easy-to-operate, free, and web-accessible database that integrates transcriptional profiles of barley at different growth and developmental stages, tissues, and stress conditions, as well as differential expression of mutants and populations to build a platform for barley expression and visualization. The expression of a gene of interest can be easily queried by searching by known gene ID or sequence similarity. Expression data can be displayed as a heat map, along with functional descriptions as well as Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, Proteins Families Database, and Simple Modular Architecture Research Tool annotations.

CONCLUSIONS

BarleyExpDB will serve as a valuable resource for the barley research community to leverage the vast publicly available RNA-seq datasets for functional genomics research and crop molecular breeding.

scTransSort: Transformers for Intelligent Annotation of Cell Types by Gene Embeddings

Single-cell transcriptomics is rapidly advancing our understanding of the composition of complex tissues and biological cells, and single-cell RNA sequencing (scRNA-seq) holds great potential for identifying and characterizing the cell composition of complex tissues. Cell type identification by analyzing scRNA-seq data is mostly limited by time-consuming and irreproducible manual annotation. As scRNA-seq technology scales to thousands of cells per experiment, the exponential increase in the number of cell samples makes manual annotation more difficult. On the other hand, the sparsity of gene transcriptome data remains a major challenge. This paper applied the idea of the transformer to single-cell classification tasks based on scRNA-seq data. We propose scTransSort, a cell-type annotation method pretrained with single-cell transcriptomics data. The scTransSort incorporates a method of representing genes as gene expression embedding blocks to reduce the sparsity of data used for cell type identification and reduce the computational complexity. The feature of scTransSort is that its implementation of intelligent information extraction for unordered data, automatically extracting valid features of cell types without the need for manually labeled features and additional references. In experiments on cells from 35 human and 26 mouse tissues, scTransSort successfully elucidated its high accuracy and high performance for cell type identification, and demonstrated its own high robustness and generalization ability.

Black Poplar (Populus nigra L.) Root Extracellular Trap, Structural and Molecular Remodeling in Response to Osmotic Stress

The root extracellular trap (RET) consists of root-associated, cap-derived cells (root AC-DCs) and their mucilaginous secretions, and forms a structure around the root tip that protects against biotic and abiotic stresses. However, there is little information concerning the changes undergone by the RET during droughts, especially for tree species. Morphological and immunocytochemical approaches were used to study the RET of black poplar (Populus nigra L.) seedlings grown in vitro under optimal conditions (on agar-gelled medium) or when polyethylene glycol-mediated (PEG6000—infused agar-gelled medium) was used to mimic drought conditions through osmotic stress. Under optimal conditions, the root cap released three populations of individual AC-DC morphotypes, with a very low proportion of spherical morphotypes, and equivalent proportions of intermediate and elongated morphotypes. Immunolabeling experiments using anti-glycan antibodies specific to cell wall polysaccharide and arabinogalactan protein (AGP) epitopes revealed the presence of homogalacturonan (HG), galactan chains of rhamnogalacturonan-I (RG-I), and AGPs in root AC-DC cell walls. The data also showed the presence of xylogalacturonan (XGA), xylan, AGPs, and low levels of arabinans in the mucilage. The findings also showed that under osmotic stress conditions, both the number of AC-DCs (spherical and intermediate morphotypes) and the total quantity of mucilage per root tip increased, whereas the mucilage was devoid of the epitopes associated with the polysaccharides RG-I, XGA, xylan, and AGPs. Osmotic stress also led to reduced root growth and increased root expression of the P5CS2 gene, which is involved in proline biosynthesis and cellular osmolarity maintenance (or preservation) in aerial parts. Together, our findings show that the RET is a dynamic structure that undergoes pronounced structural and molecular remodeling, which might contribute to the survival of the root tip under osmotic conditions.

Growth-regulating factors: conserved and divergent roles in plant growth and development and potential value for crop improvement

High yield and stress resistance are the major prerequisites for successful crop cultivation, and can be achieved by modifying plant architecture. Evolutionarily conserved growth-regulating factors (GRFs) control the growth of different tissues and organs of plants. Here, we provide a systematic overview of the expression patterns of GRF genes and the structural features of GRF proteins in different plant species. Moreover, we illustrate the conserved and divergent roles of GRFs, microRNA396 (miR396), and GRF-interacting factors (GIFs) in leaf, root, and flower development. We also describe the molecular networks involving the miR396-GRF-GIF module, and illustrate how this module coordinates with different signaling molecules and transcriptional regulators to control development of different plant species. GRFs promote leaf growth, accelerate grain filling, and increase grain size and weight. We also provide some molecular insight into how coordination between GRFs and other signaling modules enhances crop productivity; for instance, how the GRF-DELLA interaction confers yield-enhancing dwarfism while increasing grain yield. Finally, we discuss how the GRF-GIF chimera substantially improves plant transformation efficiency by accelerating shoot formation. Overall, we systematically review the conserved and divergent roles of GRFs and the miR396-GRF-GIF module in growth regulation, and also provide insights into how GRFs can be utilized to improve the productivity and nutrient content of crop plants.

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

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

Protoplast Preparation for Algal Single-Cell Omics Sequencing

Single-cell sequencing (SCS) is an evolutionary technique for conducting life science research, providing the highest genome-sale throughput and single-cell resolution and unprecedented capabilities in addressing mechanistic and operational questions. Unfortunately, the current SCS pipeline cannot be directly applied to algal research as algal cells have cell walls, which makes RNA extraction hard for the current SCS platforms. Fortunately, effective methods are available for producing algal protoplasts (cells without cell walls), which can be directly fed into current SCS pipelines. In this review, we first summarize the cell wall structure and chemical composition of algal cell walls, particularly in Chlorophyta, then summarize the advances made in preparing algal protoplasts using physical, chemical, and biological methods, followed by specific cases of algal protoplast production in some commonly used eukaryotic algae. This review provides a timely primer to those interested in applying SCS in eukaryotic algal research.