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

Uncovering differences in cadmium accumulation capacity of different Ipomoea aquatica cultivars at the level of root cell types

Water spinach (Ipomoea aquatica) can accumulate cadmium (Cd) even in mildly contaminated soils, but the roles of its root tip cell types in Cd fixation and transport remain unclear. Single-cell RNA sequencing revealed nine cell types in root tips in both the QLQ cultivar (low Cd accumulation) and the T308 cultivar (high Cd accumulation). High expression of LAC2 and PER72 in the QLQ epidermis was associated with enhanced lignin deposition, which may facilitate fixation of Cd and reduce its translocation to the shoot. In T308, PER72 and hormone-related genes (PIN1, ARF8, IAA17, and EIN3) were upregulated, which was hypothesized to promote xylem and trichoblast development, potentially facilitating Cd uptake and transport. Fluorescence assays suggested that the higher pectin demethylation and lignin content in QLQ may limit Cd movement, whereas the more developed tissues in T308 may contribute to increased Cd accumulation in the shoots. These findings clarify the mechanisms by which Cd accumulates in water spinach and offer insights into mitigating Cd uptake in crops.

Single-Cell Transcriptome Reveals the Cellular Response to PEG-Induced Stress in Wheat Leaves

Drought is a major factor limiting the production and yield of wheat bread (Triticum aestivum). Therefore, investigating the wheat drought-related response mechanism is an urgent priority. Here, the single-cell transcriptome of drought-nonsusceptible and susceptible wheat seedlings subjected to PEG-induced stress was systematically analyzed to study the drought-related response at the cellular level. We identified five major cell types using known marker genes and constructed a wheat leaf cell atlas. On this foundation, several potential specific marker genes for each cell type were identified, which provide a reference for further cell type annotation. Moreover, we identified cellular heterogeneity in the drought-related response mechanisms and regulatory networks among cell types. Specifically, the drought response of mesophyll cells was correlated with the photosynthetic pathway. Pseudotime trajectory analysis revealed the transition of epidermal cells from their normal function to a defense response under stress. Moreover, we also characterized the genes associated with the drought response. Notably, we identified two transcription factors (TraesCS1D02G223600 and TraesCS1D02G072900) as master regulators in most cell types. Our study provides detailed insights into the response heterogeneity of cells under PEG-induced stress. The gene resources obtained in our study could be applied to breed better crop plants with improved drought tolerance.

Changes in leaf economic trait relationships across a precipitation gradient are related to differential gene expression in a C4 perennial grass

The leaf economics spectrum (LES) describes a suite of functional traits that consistently covary at large spatial and taxonomic scales. Despite its importance at these larger scales, few studies have examined the major drivers of intraspecific variation in the LES - phenotypic plasticity and standing genetic variation. Using experimental precipitation manipulations, we examined whether covariation among leaf economics traits and selection on leaf economics traits and trait combinations change as diverse genotypes of the widespread perennial grass Panicum virgatum are exposed to differences in precipitation. We also used RNA-Seq to examine whether groups of co-expressed genes that align with leaf economics traits function in processes hypothesized to underlie the LES. Water availability impacted leaf economics trait covariation in important ways - covariation between leaf economics traits and selection on covariation between traits (i.e. correlational selection) tended to be strongest when water availability was high. Additionally, many genes associated with leaf economics traits functioned in processes that may explain how the LES originates, such as chloroplasts, cell walls, and nitrogen metabolism. Water availability is likely an important modulator of selection and evolution of the LES in P. virgatum that can be better understood by examining gene expression.

Dual and spatially resolved drought responses in the Arabidopsis leaf mesophyll revealed by single-cell transcriptomics

Drought stress imposes severe challenges on agriculture by impacting crop performance. Understanding drought responses in plants at a cellular level is a crucial first step toward engineering improved drought resilience. However, the molecular responses to drought are complex as they depend on multiple factors, including the severity of drought, the profiled organ, its developmental stage or even the cell types therein. Thus, deciphering the transcriptional responses to drought is especially challenging. In this study, we investigated tissue-specific responses to mild drought (MD) in young Arabidopsis thaliana (Arabidopsis) leaves using single-cell RNA sequencing (scRNA-seq). To preserve transcriptional integrity during cell isolation, we inhibited RNA synthesis using the transcription inhibitor actinomycin D, and demonstrated the benefits of transcriptome fixation for studying mild stress responses at a single-cell level. We present a curated and validated single-cell atlas, comprising 50 797 high-quality cells from almost all known cell types present in the leaf. All cell type annotations were validated with a new library of reporter lines. The curated data are available to the broad community in an intuitive tool and a browsable single-cell atlas (http://www.single-cell.be/plant/leaf-drought). We show that the mesophyll contains two spatially separated cell populations with distinct responses to drought: one enriched in canonical abscisic acid-related drought-responsive genes, and another one enriched in genes involved in iron starvation responses. Our study thus reveals a dual adaptive mechanism of the leaf mesophyll in response to MD and provides a valuable resource for future research on stress responses.

Single-Cell RNA Sequencing Reveals the Developmental Landscape of Wheat Roots

Allohexaploid wheat (Triticum aestivum L.) is one of the major crops worldwide, however there is very limited research on the transcriptional programmes of underlying cell type specification. Single-cell RNA sequencing (scRNA-seq) was used to unravel the transcriptome heterogeneity of cells and the composition of cell types in broad-spectrum organisms. Here, we reported the scRNA-seq transcriptomes of single cells from root tips of the wheat Chinese spring (CS) cultivar, defined cell-type-specific marker genes, and identified most of the major cell types. We further profiled the reconstructed developmental trajectories of the stem cell niche (SCN), proximal meristems and meristems, unveiled gene expression signature of water transportation, divulged cell-type-specific asymmetric gene transcription in subgenomes and explored the evolutionary conservation and divergence of wheat cultivar (CS) and rice cultivar (Nip and 93-11, ZH11) cell types through interspecies comparison. Collectively, this work underscored the transcriptional landscape of wheat cultivar (CS) roots and provided a single-cell perspective for differentiation trajectory application, unbalanced gene expression pattern and characteristics of cell types between two plant species, contributing to a better understanding of wheat cultivar (CS) root development at unprecedented resolution.

Single-cell transcriptomics reveal how root tissues adapt to soil stress

Land plants thrive in soils showing vastly different properties and environmental stresses1. Root systems can adapt to contrasting soil conditions and stresses, yet how their responses are programmed at the individual cell scale remains unclear. Using single-cell RNA sequencing and spatial transcriptomic approaches, we showed major expression changes in outer root cell types when comparing the single-cell transcriptomes of rice roots grown in gel versus soil conditions. These tissue-specific transcriptional responses are related to nutrient homeostasis, cell wall integrity and defence in response to heterogeneous soil versus homogeneous gel growth conditions. We also demonstrate how the model soil stress, termed compaction, triggers expression changes in cell wall remodelling and barrier formation in outer and inner root tissues, regulated by abscisic acid released from phloem cells. Our study reveals how root tissues communicate and adapt to contrasting soil conditions at single-cell resolution.

Unveiling the spatiotemporal strategies of plants in response to biotic and abiotic stresses:A comprehensive review

Plant functions are governed by complex regulatory mechanisms that operate across diverse cell types in various tissues. However, the challenge of dissecting plant tissues has hindered the widespread application of single-cell technologies in plant research. Recent advancements in single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) have propelled the field forward. scRNA-seq enables the examination of gene expression at the single-cell level, while ST preserves the spatial context of cellular organization. While previous reviews have discussed the breakthroughs of scRNA-seq and ST in plants, none have comprehensively addressed the use of these technologies to study plant responses to environmental stress at the cellular level. This review provides an in-depth analysis of the development, advantages, and limitations of single-cell and spatial transcriptomics, highlighting their critical role in unraveling plant strategies for coping with biotic and abiotic stresses. We also explore the challenges and future prospects of integrating scRNA-seq and ST in plant research. Understanding cell-specific responses and the complex interactions between cellular entities within the plant under stress is essential for advancing our knowledge of plant biology.

Single-Cell and Spatial Transcriptomics Reveals a Stereoscopic Response of Rice Leaf Cells to Magnaporthe oryzae Infection

Infection by the fungal pathogen Magnaporthe oryzae elicits dynamic responses in rice. Utilizing an integrated approach of single-cell and spatial transcriptomics, a 3D response is uncovered within rice leaf cells to M. oryzae infection. A comprehensive rice leaf atlas is constructed from 236 708 single-cell transcriptomes, revealing heightened expression of immune receptors, namely Pattern Recognition Receptors (PRRs) and Nucleotide-binding site and leucine-rich repeat (NLRs) proteins, within vascular tissues. Diterpene phytoalexins biosynthesis genes are dramatically upregulated in procambium cells, leading to an accumulation of these phytoalexins within vascular bundles. Consistent with these findings, microscopic observations confirmed that M. oryzae is prone to target leaf veins for invasion, yet is unable to colonize further within vascular tissues. Following fungal infection, basal defenses are extensively activated in rice cells, as inferred from trajectory analyses. The spatial transcriptomics reveals that rice leaf tissues toward leaf tips display stronger immunity. Characterization of the polarity gene OsHKT9 suggests that potassium transport plays a critical role in resisting M. oryzae infection by expression along the longitudinal axis, where the immunity is stronger toward leaf tip. This work uncovers that there is a cell-specific and multi-dimensional (local and longitudinal) immune response to a fungal pathogen infection.

Accelerating crop improvement via integration of transcriptome-based network biology and genome editing

MAIN CONCLUSION

Big data and network biology infer functional coupling between genes. In combination with machine learning, network biology can dramatically accelerate the pace of gene discovery using modern transcriptomics approaches and be validated via genome editing technology for improving crops to stresses. Unlike other living things, plants are sessile and frequently face various environmental challenges due to climate change. The cumulative effects of combined stresses can significantly influence both plant growth and yields. In navigating the complexities of climate change, ensuring the nourishment of our growing population hinges on implementing precise agricultural systems. Conventional breeding methods have been commonly employed; however, their efficacy has been impeded by limitations in terms of time, cost, and infrastructure. Cutting-edge tools focussing on big data are being championed to usher in a new era in stress biology, aiming to cultivate crops that exhibit enhanced resilience to multifactorial stresses. Transcriptomics, combined with network biology and machine learning, is proving to be a powerful approach for identifying potential genes to target for gene editing, specifically to enhance stress tolerance. The integration of transcriptomic data with genome editing can yield significant benefits, such as gaining insights into gene function by modifying or manipulating of specific genes in the target plant. This review provides valuable insights into the use of transcriptomics platforms and the application of biological network analysis and machine learning in the discovery of novel genes, thereby enhancing the understanding of plant responses to combined or sequential stress. The transcriptomics as a forefront omics platform and how it is employed through biological networks and machine learning that lead to novel gene discoveries for producing multi-stress-tolerant crops, limitations, and future directions have also been discussed.

Cell Fate Determination of the Potato Shoot Apex and Stolon Tips Revealed by Single-Cell Transcriptome Analysis

Potato (Solanum tuberosum L.) is a starch-rich crop with two types of meristematic stems: the shoot and stolon. Shoots grow vertically, while stolons grow horizontally underground and produce tubers at their tips. However, transcriptional differences between shoot and stolon cells remain unclear. To address this, we performed single-cell RNA sequencing of the shoot apex and stolon tip, generating a comprehensive transcriptional landscape. We identified 23 distinct cell clusters with high cell heterogeneity, including cell-specific genes and conserved genes with cell-specific expression patterns. Hormone-related genes, particularly those involved in auxin and gibberellin pathways, exhibited distinct patterns among shoot and stolon cells. Meristematic cells were re-clustered based on the expression of StPOTH15, a homolog of SHOOT MERISTEMLESS (STM) in Arabidopsis. Co-expression networks of transcription factors identified the key transcription factors involved in stolon development. We also constructed developmental trajectories for xylem and phloem development using key vascular genes, including MP, XCP1, PP2A1 and SEOR1. Comparative analysis with Arabidopsis highlighted significant differences in cell type-specific transcript profiles. These results provide insights into the transcriptional divergence between potato shoot and stolon, and identify key transcription factors co-expressed with StPOTH15 that can be used to explore their roles in stolon development.

Decoding maize meristems maintenance and differentiation: integrating single-cell and spatial omics

All plant organs are derived from stem cell-containing meristems. In maize, the shoot apical meristem (SAM) is responsible for generating all above-ground structures, including the male and female inflorescence meristems (IMs), which give rise to tassel and ear, respectively. Forward and reverse genetic studies on maize meristem mutants have driven forward our fundamental understanding of meristem maintenance and differentiation mechanisms. However, the high genetic redundancy of the maize genome has impeded progress in functional genomics. This review comprehensively summarizes recent advancements in understanding maize meristem development, with a focus on the integration of single-cell and spatial technologies. We discuss the mechanisms governing stem cell maintenance and differentiation in SAM and IM, emphasizing the roles of gene regulatory networks, hormonal pathways, and cellular omics insights into stress responses and adaptation. Future directions include cross-species comparisons, multi-omics integration, and the application of these technologies to precision breeding and stress adaptation research, with the ultimate goal of translating our understanding of meristem into the development of higher yield varieties.

Cell-Type Specific miRNA Regulatory Network Responses to ABA Stress Revealed by Time Series Transcriptional Atlases in Arabidopsis

In plants, microRNAs (miRNAs) participate in complex gene regulatory networks together with the transcription factors (TFs) in response to biotic and abiotic stresses. To date, analyses of miRNAs-induced transcriptome remodeling are at the whole plant or tissue levels. Here, Arabidopsis's ABA-induced single-cell RNA-seq (scRNA-seq) is performed at different stages of time points-early, middle, and late. Single-cell level primary miRNAs (pri-miRNAs) atlas supported the rapid, dynamic, and cell-type specific miRNA responses under ABA treatment. MiRNAs respond rapidly and prior to target gene expression dynamics, and these rapid response miRNAs are highly cell-type specific, especially in mesophyll and vascular cells. MiRNA-TF-mRNA regulation modules are identified by identifying miRNA-contained feed-forward loops (M-FFLs) in the regulatory network, and regulatory networks with M-FFLs have higher co-expression and clustering coefficient (CC) values than those without M-FFLs, suggesting the hub role of miRNAs in regulatory networks. The cell-type-specific M-FFLs are regulated by these hub miRNAs rather than TFs through sc-RNA-seq network analysis. MiR858a-FBH3-MYB module inhibited the expression of MYB63 and MYB20, which related to the formation of plant secondary wall and the production of lignin, through M-FFL specifically in vascular. These results can provide prominent insights into miRNAs' dynamic and cell-type-specific roles in plant development and stress responses.

Investigating biological nitrogen fixation via single-cell transcriptomics

The extensive use of nitrogen fertilizers has detrimental environmental consequences, and it is essential for society to explore sustainable alternatives. One promising avenue is engineering root nodule symbiosis, a naturally occurring process in certain plant species within the nitrogen-fixing clade, into non-leguminous crops. Advancements in single-cell transcriptomics provide unprecedented opportunities to dissect the molecular mechanisms underlying root nodule symbiosis at the cellular level. This review summarizes key findings from single-cell studies in Medicago truncatula, Lotus japonicus, and Glycine max. We highlight how these studies address fundamental questions about the development of root nodule symbiosis, including the following findings: (i) single-cell transcriptomics has revealed a conserved transcriptional program in root hair and cortical cells during rhizobial infection, suggesting a common infection pathway across legume species; (ii) characterization of determinate and indeterminate nodules using single-cell technologies supports the compartmentalization of nitrogen fixation, assimilation, and transport into distinct cell populations; (iii) single-cell transcriptomics data have enabled the identification of novel root nodule symbiosis genes and provided new approaches for prioritizing candidate genes for functional characterization; and (iv) trajectory inference and RNA velocity analyses of single-cell transcriptomics data have allowed the reconstruction of cellular lineages and dynamic transcriptional states during root nodule symbiosis.

A single-cell and spatial wheat root atlas with cross-species annotations delineates conserved tissue-specific marker genes and regulators

Despite the broad use of single-cell/nucleus RNA sequencing in plant research, accurate cluster annotation in less-studied plant species remains a major challenge due to the lack of validated marker genes. Here, we generated a single-cell RNA sequencing atlas of soil-grown wheat roots and annotated cluster identities by transferring annotations from publicly available datasets in wheat, rice, maize, and Arabidopsis. The predictions from our orthology-based annotation approach were next validated using untargeted spatial transcriptomics. These results allowed us to predict evolutionarily conserved tissue-specific markers and generate cell type-specific gene regulatory networks for root tissues of wheat and the other species used in our analysis. In summary, we generated a single-cell and spatial transcriptomics resource for wheat root apical meristems, including numerous known and uncharacterized cell type-specific marker genes and developmental regulators. These data and analyses will facilitate future cell type annotation in non-model plant species.

Integrative Multi-Omics Approaches for Identifying and Characterizing Biological Elements in Crop Traits: Current Progress and Future Prospects

The advancement of multi-omics tools has revolutionized the study of complex biological systems, providing comprehensive insights into the molecular mechanisms underlying critical traits across various organisms. By integrating data from genomics, transcriptomics, metabolomics, and other omics platforms, researchers can systematically identify and characterize biological elements that contribute to phenotypic traits. This review delves into recent progress in applying multi-omics approaches to elucidate the genetic, epigenetic, and metabolic networks associated with key traits in plants. We emphasize the potential of these integrative strategies to enhance crop improvement, optimize agricultural practices, and promote sustainable environmental management. Furthermore, we explore future prospects in the field, underscoring the importance of cutting-edge technological advancements and the need for interdisciplinary collaboration to address ongoing challenges. By bridging various omics platforms, this review aims to provide a holistic framework for advancing research in plant biology and agriculture.

Opportunities and challenges in the application of single-cell transcriptomics in plant tissue research

Single-cell transcriptomics overcomes the limitations of conventional transcriptome methods by isolating and sequencing RNA from individual cells, thus capturing unique expression values for each cell. This technology allows unprecedented precision in observing the stochasticity and heterogeneity of gene expression within cells. However, single-cell RNA sequencing (scRNA-seq) experiments often fail to capture all cells and genes comprehensively, and single-modality data is insufficient to explain cell states and systemic changes. To address this, the integration of multi-source scRNA-seq and single-cell multi-modality data has emerged, enabling the construction of comprehensive cell atlases. These integration methods also facilitate the exploration of causal relationships and gene regulatory mechanisms across different modalities. This review summarizes the fundamental principles, applications, and value of these integration methods in revealing biological changes, and analyzes the advantages, disadvantages, and future directions of current approaches.

Single-cell transcriptomes reveal spatiotemporal heat stress response in maize roots

Plant roots perceive heat stress (HS) and adapt their architecture accordingly, which in turn influence the yield in crops. Investigating their heterogeneity and cell type-specific response to HS is essential for improving crop resilience. Here, we generate single-cell transcriptional landscape of maize (Zea mays) roots in response to HS. We characterize 15 cell clusters corresponding to 9 major cell types and identify cortex as the main root cell type responsive to HS with the most differentially expressed genes and its trajectory being preferentially affected upon HS. We find that cortex size strongly correlated with heat tolerance that is experimentally validated by using inbred lines and genetic mutation analysis of one candidate gene in maize, providing potential HS tolerance indicator and targets for crop improvement. Moreover, interspecies comparison reveals conserved root cell types and core markers in response to HS in plants, which are experimentally validated. These results provide a universal atlas for unraveling the transcriptional programs that specify and maintain the cell identity of maize roots in response to HS at a cell type-specific level.

Orthologous marker groups reveal broad cell identity conservation across plant single-cell transcriptomes

Single-cell RNA sequencing (scRNA-seq) is widely used in plant biology and is a powerful tool for studying cell identity and differentiation. However, the scarcity of known cell-type marker genes and the divergence of marker expression patterns limit the accuracy of cell-type identification and our capacity to investigate cell-type conservation in many species. To tackle this challenge, we devise a novel computational strategy called Orthologous Marker Gene Groups (OMGs), which can identify cell types in both model and non-model plant species and allows for rapid comparison of cell types across many published single-cell maps. Our method does not require cross-species data integration, while still accurately determining inter-species cellular similarities. We validate the method by analyzing published single-cell data from species with well-annotated single-cell maps, and we show our methods can capture majority of manually annotated cell types. The robustness of our method is further demonstrated by its ability to pertinently map cell clusters from 1 million cells, 268 cell clusters across 15 diverse plant species. We reveal 14 dominant groups with substantial conservation in shared cell-type markers across monocots and dicots. To facilitate the use of this method by the broad research community, we launch a user-friendly web-based tool called the OMG browser, which simplifies the process of cell-type identification in plant datasets for biologists.

Identification of cell-type specificity, trans- and cis-acting functions of plant lincRNAs from single-cell transcriptomes

Long noncoding RNAs, including intergenic lncRNAs (lincRNAs), play a key role in various biological processes throughout the plant life cycle, and the advent of single-cell RNA sequencing (scRNA-seq) technology has opened up a valuable avenue for scrutinizing the intricate roles of lincRNAs in cellular processes. Here, we identified a new batch of lincRNAs using scRNA-seq data from diverse tissues of plants (rice, Arabidopsis, tomato, and maize). Based on well-annotated single-cell transcriptome atlases, plant lincRNAs were found to possess the same level of cell-type specificity as mRNAs and to be involved in the differentiation of certain cell types based on pseudo-time analysis. Many lincRNAs were predicted to play a hub role in the cell-type-specific co-expression networks of lincRNAs and mRNAs, suggesting their trans-acting abilities. Besides, plant lincRNAs were revealed to have potential cis-acting properties based on their genomic distances and expression correlations with the neighboring mRNAs. Furthermore, an online platform, PscLncRNA (http://ibi.zju.edu.cn/psclncrna/), was constructed for searching and visualizing all identified plant lincRNAs with annotated potential functions. Our work provides new insights into plant lincRNAs at single-cell resolution and an important resource for understanding and further investigation of plant lincRNAs.

The Expression Profile of Genes Related to Carotenoid Biosynthesis in Pepper Under Abiotic Stress Reveals a Positive Correlation with Plant Tolerance

In light of the increasingly adverse environmental conditions and the concomitant challenges to the survival of important crops, there is a pressing need to enhance the resilience of pepper seedlings to extreme weather. Carotenoid plays an important role in plants' resistance to abiotic stress. Nevertheless, the relationship between carotenoid biosynthesis and sweet pepper seedlings' resistance to different abiotic stresses remains uncertain. In this study, the carotenoid content in abiotic-stressed sweet pepper seedling roots was determined, revealing that carotenoid content was extremely significantly elevated by more than 16-fold under salt stress, followed by drought stress (8-fold), and slightly elevated by only about 1-fold under waterlogging stress. After that, serine/threonine-protein phosphatase 2A (PP2A) was found to be the suitable reference gene (RG) in sweet pepper seedling roots under different abiotic stresses by using RT-qPCR and RefFinder analysis. Subsequently, using PP2A as the RG, RT-qPCR analysis showed that the expression level of most genes associated with carotenoid biosynthesis was extremely significantly up-regulated in sweet pepper seedlings under salt and drought stress. Specifically, violoxanthin deepoxidase (VDE) was significantly up-regulated by more than 481- and 36-fold under salt and drought stress, respectively; lycopene epsilon cyclase (LCYE) was significantly up-regulated by more than 840- and 23-fold under salt and drought stress, respectively. This study contributes to a more comprehensive understanding of the carotenoid biosynthesis pathway serving as a major source of retrograde signals in pepper subjected to different abiotic stresses.

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.

The transcriptional integration of environmental cues with root cell type development

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

Gene regulatory networks in abiotic stress responses via single-cell sequencing and spatial technologies: Advances and opportunities

Understanding intricate gene regulatory networks (GRNs) orchestrating responses to abiotic stresses is crucial for enhancing climate resilience in crop plants. Recent advancements in single-cell and spatial technologies have revolutionized our ability to dissect the GRNs at unprecedented resolution. Here, we explore the progress, challenges, and opportunities these state-of-the-art technologies offer in delineating the cellular intricacies of plant responses to abiotic stress. Using scRNA-seq, the transcriptome landscape of individual plant cells along with their lineages and regulatory interactions can be unraveled. Moreover, coupling scRNA-seq with spatial transcriptomics provides spatially resolved gene expression and insights into cell-to-cell interactions. In addition, the chromatin accessibility assays can discover the regulatory regions governing abiotic stress responses. An integrated multi-omics approach can facilitate discovery of cell-type-specific GRNs to reveal the key components that coordinate adaptive responses to different stresses. These potential regulatory factors can be harnessed for genetic engineering to enhance stress resilience in crop plants.

Single-cell transcriptomics: a new frontier in plant biotechnology research

Single-cell transcriptomic techniques have ushered in a new era in plant biology, enabling detailed analysis of gene expression at the resolution of individual cells. This review delves into the transformative impact of these technologies on our understanding of plant development and their far-reaching implications for plant biotechnology. We present a comprehensive overview of the latest advancements in single-cell transcriptomics, emphasizing their application in elucidating complex cellular processes and developmental pathways in plants. By dissecting the heterogeneity of cell populations, single-cell technologies offer unparalleled insights into the intricate regulatory networks governing plant growth, differentiation, and response to environmental stimuli. This review covers the spectrum of single-cell approaches, from pioneering techniques such as single-cell RNA sequencing (scRNA-seq) to emerging methodologies that enhance resolution and accuracy. In addition to showcasing the technological innovations, we address the challenges and limitations associated with single-cell transcriptomics in plants. These include issues related to sample preparation, cell isolation, data complexity, and computational analysis. We propose strategies to mitigate these challenges, such as optimizing protocols for protoplast isolation, improving computational tools for data integration, and developing robust pipelines for data interpretation. Furthermore, we explore the practical applications of single-cell transcriptomics in plant biotechnology. These applications span from improving crop traits through precise genetic modifications to enhancing our understanding of plant-microbe interactions. The review also touches on the potential for single-cell approaches to accelerate breeding programs and contribute to sustainable agriculture. This review concludes with a forward-looking perspective on the future impact of single-cell technologies in plant research. We foresee these tools becoming essential in plant biotechnology, spurring innovations that tackle global challenges in food security and environmental sustainability. This review serves as a valuable resource for researchers, providing a roadmap from sample preparation to data analysis and highlighting the transformative potential of single-cell transcriptomics in plant biotechnology.

Conserved features and diversity attributes of chimeric RNAs across accessions in four plants

As a non-collinear expression form of genetic information, chimeric RNAs increase the complexity of transcriptome in diverse organisms. Although chimeric RNAs have been identified in plants, few common features have been revealed. Here, we systemically explored the landscape of chimeric RNAs across multi-accession and multi-tissue using pan-genome and transcriptome data of four plants: rice, maize, soybean, and Arabidopsis. Among the four species, conserved characteristics of breakpoints and parental genes were discovered. In each species, chimeric RNAs displayed a high level of diversity among accessions, and the clustering of accessions using chimeric events was generally concordant with clustering based on genomic variants, implying a general relationship between genetic variations and chimeric RNAs. Through mass spectrometry, we confirmed a fusion protein OsNDC1-OsGID1L2 and observed its subcellular localization, which differed from the original proteins. Phenotypic cues in transgenic rice suggest the potential functions of OsNDC1-OsGID1L2. Moreover, an intriguing chimeric event Os01g0216500-Os01g0216900, generated by a large deletion in basmati rice, also exists in another accession without the deletion, demonstrating its convergence in evolution. Our results illuminate the characteristics and hint at the evolutionary implications of plant chimeric RNAs, which serve as a supplement to genetic variations, thus expanding our understanding of genetic diversity.

Leveraging multi-omics tools to comprehend responses and tolerance mechanisms of heavy metals in crop plants

Extreme anthropogenic activities and current farming techniques exacerbate the effects of water and soil impurity by hazardous heavy metals (HMs), severely reducing agricultural output and threatening food safety. In the upcoming years, plants that undergo exposure to HM might cause a considerable decline in the development as well as production. Hence, plants have developed sophisticated defensive systems to evade or withstand the harmful consequences of HM. These mechanisms comprise the uptake as well as storage of HMs in organelles, their immobilization via chemical formation by organic chelates, and their removal using many ion channels, transporters, signaling networks, and TFs, amid other approaches. Among various cutting-edge methodologies, omics, most notably genomics, transcriptomics, proteomics, metabolomics, miRNAomics, phenomics, and epigenomics have become game-changing approaches, revealing information about the genes, proteins, critical metabolites as well as microRNAs that govern HM responses and resistance systems. With the help of integrated omics approaches, we will be able to fully understand the molecular processes behind plant defense, enabling the development of more effective crop protection techniques in the face of climate change. Therefore, this review comprehensively presented omics advancements that will allow resilient and sustainable crop plants to flourish in areas contaminated with HMs.

From single cell to spatial multi-omics: unveiling molecular mechanisms in dynamic and heterogeneous systems

Single-cell multi-omics and spatial technology have been widely applied to biomedical studies and recently to environmental studies. The cell size detected by single-cell omics ranges from ∼2 µm (e.g., Bacillus subtilis) to ∼120 µm (e.g., human oocytes). Simultaneous detection of single-cell multi-omics is available to human and plant tissues while limited to microbial samples. Spatial technology enables mapping the detected biomolecules in situ. The recent advances in Matrix-Assisted Laser Desorption/Ionization-Mass Spectrometry Imaging and Micro/Nanodroplet Processing in One Pot for Trace Samples for the first time allow the application of spatial multi-omics in highly heterogeneous environmental samples composed of plants, fungi, and bacteria. We envision that these technologies will continue to advance our understanding of unique cell types, their developmental trajectory, and the intercellular signaling and interaction within biological samples.

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.

Single-cell transcriptomics reveals heterogeneity in plant responses to the environment: a focus on biotic and abiotic interactions

Biotic and abiotic environmental cues are major factors influencing plant growth and productivity. Interactions with biotic (e.g. symbionts and pathogens) and abiotic (e.g. changes in temperature, water, or nutrient availability) factors trigger signaling and downstream transcriptome adjustments in plants. While bulk RNA-sequencing technologies have traditionally been used to profile these transcriptional changes, tissue homogenization may mask heterogeneity of responses resulting from the cellular complexity of organs. Thus, whether different cell types respond equally to environmental fluctuations, or whether subsets of the responses are cell-type specific, are long-lasting questions in plant biology. The recent breakthrough of single-cell transcriptomics in plant research offers an unprecedented view of cellular responses under changing environmental conditions. In this review, we discuss the contribution of single-cell transcriptomics to the understanding of cell-type-specific plant responses to biotic and abiotic environmental interactions. Besides major biological findings, we present some technical challenges coupled to single-cell studies of plant-environment interactions, proposing possible solutions and exciting paths for future research.

Spatiotemporal transcriptomic landscape of rice embryonic cells during seed germination

Characterizing cellular features during seed germination is crucial for understanding the complex biological functions of different embryonic cells in regulating seed vigor and seedling establishment. We performed spatially enhanced resolution omics sequencing (Stereo-seq) and single-cell RNA sequencing (scRNA-seq) to capture spatially resolved single-cell transcriptomes of germinating rice embryos. An automated cell-segmentation model, employing deep learning, was developed to accommodate the analysis requirements. The spatial transcriptomes of 6, 24, 36, and 48 h after imbibition unveiled both known and previously unreported embryo cell types, including two unreported scutellum cell types, corroborated by in situ hybridization and functional exploration of marker genes. Temporal transcriptomic profiling delineated gene expression dynamics in distinct embryonic cell types during seed germination, highlighting key genes involved in nutrient metabolism, biosynthesis, and signaling of phytohormones, reprogrammed in a cell-type-specific manner. Our study provides a detailed spatiotemporal transcriptome of rice embryo and presents a previously undescribed methodology for exploring the roles of different embryonic cells in seed germination.

Establishment of single-cell transcriptional states during seed germination

Germination involves highly dynamic transcriptional programs as the cells of seeds reactivate and express the functions necessary for establishment in the environment. Individual cell types have distinct roles within the embryo, so must therefore have cell type-specific gene expression and gene regulatory networks. We can better understand how the functions of different cell types are established and contribute to the embryo by determining how cell type-specific transcription begins and changes through germination. Here we describe a temporal analysis of the germinating Arabidopsis thaliana embryo at single-cell resolution. We define the highly dynamic cell type-specific patterns of gene expression and how these relate to changing cellular function as germination progresses. Underlying these are unique gene regulatory networks and transcription factor activity. We unexpectedly discover that most embryo cells transition through the same initial transcriptional state early in germination, even though cell identity has already been established during embryogenesis. Cells later transition to cell type-specific gene expression patterns. Furthermore, our analyses support previous findings that the earliest events leading to the induction of seed germination take place in the vasculature. Overall, our study constitutes a general framework with which to characterize Arabidopsis cell transcriptional states through seed germination, allowing investigation of different genotypes and other plant species whose seed strategies may differ.

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

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

Single-cell RNA-sequencing provides new insights into the cell-specific expression patterns and transcriptional regulation of photosynthetic genes in bermudagrass leaf blades

As an important warm-season turfgrass species, bermudagrass (Cynodon dactylon L.) flourishes in warm areas around the world due to the existence of the C4 photosynthetic pathway. However, how C4 photosynthesis operates in bermudagrass leaves is still poorly understood. In this study, we performed single-cell RNA-sequencing on 5296 cells from bermudagrass leaf blades. Eight cell clusters corresponding to mesophyll, bundle sheath, epidermis and vascular bundle cells were successfully identified using known cell marker genes. Expression profiling indicated that genes encoding NADP-dependent malic enzymes (NADP-MEs) were highly expressed in bundle sheath cells, whereas NAD-ME genes were weakly expressed in all cell types, suggesting C4 photosynthesis of bermudagrass leaf blades might be NADP-ME type rather than NAD-ME type. The results also indicated that starch synthesis-related genes showed preferential expression in bundle sheath cells, whereas starch degradation-related genes were highly expressed in mesophyll cells, which agrees with the observed accumulation of starch-filled chloroplasts in bundle sheath cells. Gene co-expression analysis further revealed that different families of transcription factors were co-expressed with multiple C4 photosynthesis-related genes, suggesting a complex transcription regulatory network of C4 photosynthesis might exist in bermudagrass leaf blades. These findings collectively provided new insights into the cell-specific expression patterns and transcriptional regulation of photosynthetic genes in bermudagrass.

Engineering the future cereal crops with big biological data: toward intelligence-driven breeding by design

How to feed 10 billion human populations is one of the challenges that need to be addressed in the following decades, especially under an unpredicted climate change. Crop breeding, initiating from the phenotype-based selection by local farmers and developing into current biotechnology-based breeding, has played a critical role in securing the global food supply. However, regarding the changing environment and ever-increasing human population, can we breed outstanding crop varieties fast enough to achieve high productivity, good quality, and widespread adaptability? This review outlines the recent achievements in understanding cereal crop breeding, including the current knowledge about crop agronomic traits, newly developed techniques, crop big biological data research, and the possibility of integrating them for intelligence-driven breeding by design, which ushers in a new era of crop breeding practice and shapes the novel architecture of future crops. This review focuses on the major cereal crops, including rice, maize, and wheat, to explain how intelligence-driven breeding by design is becoming a reality.

Genome-Wide Identification and Bioinformatics Analysis of the FK506 Binding Protein Family in Rice

The FK506 Binding Protein (FKBP), ubiquitously present across diverse species, is characterized by its evolutionarily conserved FK506 binding domain (FKBd). In plants, evidence suggests that this gene family plays integral roles in regulating growth, development, and responses to environmental stresses. Notably, research on the identification and functionality of FKBP genes in rice remains limited. Therefore, this study utilized bioinformatic tools to identify 30 FKBP-encoding genes in rice. It provides a detailed analysis of their chromosomal locations, evolutionary relationships with the Arabidopsis thaliana FKBP family, and gene structures. Further analysis of the promoter elements of these rice FKBP genes revealed a high presence of stress-responsive elements. Quantitative PCR assays under drought and heat stress conditions demonstrated that genes OsFKBP15-2, OsFKBP15-3, OsFKBP16-3, OsFKBP18, and OsFKBP42b are inducible by these adverse conditions. These findings suggest a significant role for the rice FKBP gene family in stress adaptation. This research establishes a critical foundation for deeper explorations of the functional roles of the OsFKBP genes in rice.

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

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

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.

AraLeTA: An Arabidopsis leaf expression atlas across diurnal and developmental scales

Mature plant leaves are a composite of distinct cell types, including epidermal, mesophyll, and vascular cells. Notably, the proportion of these cells and the relative transcript concentrations within different cell types may change over time. While gene expression data at a single-cell level can provide cell-type-specific expression values, it is often too expensive to obtain these data for high-resolution time series. Although bulk RNA-seq can be performed in a high-resolution time series, RNA-seq using whole leaves measures average gene expression values across all cell types in each sample. In this study, we combined single-cell RNA-seq data with time-series data from whole leaves to assemble an atlas of cell-type-specific changes in gene expression over time for Arabidopsis (Arabidopsis thaliana). We inferred how the relative transcript concentrations of different cell types vary across diurnal and developmental timescales. Importantly, this analysis revealed 3 subgroups of mesophyll cells with distinct temporal profiles of expression. Finally, we developed tissue-specific gene networks that form a community resource: an Arabidopsis Leaf Time-dependent Atlas (AraLeTa). This allows users to extract gene networks that are confirmed by transcription factor-binding data and specific to certain cell types at certain times of day and at certain developmental stages. AraLeTa is available at https://regulatorynet.shinyapps.io/araleta/.

Cell-type-specific transcriptomics uncovers spatial regulatory networks in bioenergy sorghum stems

Bioenergy sorghum is a low-input, drought-resilient, deep-rooting annual crop that has high biomass yield potential enabling the sustainable production of biofuels, biopower, and bioproducts. Bioenergy sorghum's 4-5 m stems account for ~80% of the harvested biomass. Stems accumulate high levels of sucrose that could be used to synthesize bioethanol and useful biopolymers if information about cell-type gene expression and regulation in stems was available to enable engineering. To obtain this information, laser capture microdissection was used to isolate and collect transcriptome profiles from five major cell types that are present in stems of the sweet sorghum Wray. Transcriptome analysis identified genes with cell-type-specific and cell-preferred expression patterns that reflect the distinct metabolic, transport, and regulatory functions of each cell type. Analysis of cell-type-specific gene regulatory networks (GRNs) revealed that unique transcription factor families contribute to distinct regulatory landscapes, where regulation is organized through various modes and identifiable network motifs. Cell-specific transcriptome data was combined with known secondary cell wall (SCW) networks to identify the GRNs that differentially activate SCW formation in vascular sclerenchyma and epidermal cells. The spatial transcriptomic dataset provides a valuable source of information about the function of different sorghum cell types and GRNs that will enable the engineering of bioenergy sorghum stems, and an interactive web application developed during this project will allow easy access and exploration of the data (https://mc-lab.shinyapps.io/lcm-dataset/).

Nitrogen sensing and regulatory networks: it's about time and space

A plant's response to external and internal nitrogen signals/status relies on sensing and signaling mechanisms that operate across spatial and temporal dimensions. From a comprehensive systems biology perspective, this involves integrating nitrogen responses in different cell types and over long distances to ensure organ coordination in real time and yield practical applications. In this prospective review, we focus on novel aspects of nitrogen (N) sensing/signaling uncovered using temporal and spatial systems biology approaches, largely in the model Arabidopsis. The temporal aspects span: transcriptional responses to N-dose mediated by Michaelis-Menten kinetics, the role of the master NLP7 transcription factor as a nitrate sensor, its nitrate-dependent TF nuclear retention, its "hit-and-run" mode of target gene regulation, and temporal transcriptional cascade identified by "network walking." Spatial aspects of N-sensing/signaling have been uncovered in cell type-specific studies in roots and in root-to-shoot communication. We explore new approaches using single-cell sequencing data, trajectory inference, and pseudotime analysis as well as machine learning and artificial intelligence approaches. Finally, unveiling the mechanisms underlying the spatial dynamics of nitrogen sensing/signaling networks across species from model to crop could pave the way for translational studies to improve nitrogen-use efficiency in crops. Such outcomes could potentially reduce the detrimental effects of excessive fertilizer usage on groundwater pollution and greenhouse gas emissions.

Progress in Rice Breeding Based on Genomic Research

The role of rice genomics in breeding progress is becoming increasingly important. Deeper research into the rice genome will contribute to the identification and utilization of outstanding functional genes, enriching the diversity and genetic basis of breeding materials and meeting the diverse demands for various improvements. Here, we review the significant contributions of rice genomics research to breeding progress over the last 25 years, discussing the profound impact of genomics on rice genome sequencing, functional gene exploration, and novel breeding methods, and we provide valuable insights for future research and breeding practices.

Weed biology and management in the multi-omics era: Progress and perspectives

Weeds pose a significant threat to crop production, resulting in substantial yield reduction. In addition, they possess robust weedy traits that enable them to survive in extreme environments and evade human control. In recent years, the application of multi-omics biotechnologies has helped to reveal the molecular mechanisms underlying these weedy traits. In this review, we systematically describe diverse applications of multi-omics platforms for characterizing key aspects of weed biology, including the origins of weed species, weed classification, and the underlying genetic and molecular bases of important weedy traits such as crop-weed interactions, adaptability to different environments, photoperiodic flowering responses, and herbicide resistance. In addition, we discuss limitations to the application of multi-omics techniques in weed science, particularly compared with their extensive use in model plants and crops. In this regard, we provide a forward-looking perspective on the future application of multi-omics technologies to weed science research. These powerful tools hold great promise for comprehensively and efficiently unraveling the intricate molecular genetic mechanisms that underlie weedy traits. The resulting advances will facilitate the development of sustainable and highly effective weed management strategies, promoting greener practices in agriculture.

Best practices for the execution, analysis, and data storage of plant single-cell/nucleus transcriptomics

Single-cell and single-nucleus RNA-sequencing technologies capture the expression of plant genes at an unprecedented resolution. Therefore, these technologies are gaining traction in plant molecular and developmental biology for elucidating the transcriptional changes across cell types in a specific tissue or organ, upon treatments, in response to biotic and abiotic stresses, or between genotypes. Despite the rapidly accelerating use of these technologies, collective and standardized experimental and analytical procedures to support the acquisition of high-quality data sets are still missing. In this commentary, we discuss common challenges associated with the use of single-cell transcriptomics in plants and propose general guidelines to improve reproducibility, quality, comparability, and interpretation and to make the data readily available to the community in this fast-developing field of research.

Unraveling the molecular mechanisms governing axillary meristem initiation in plants

MAIN CONCLUSION

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

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.