Dynamics of Gene Expression in Single Root Cells of Arabidopsis thaliana

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.

Comparative spatial transcriptomics reveals root dryland adaptation mechanism in rice and HMGB1 as a key regulator

Drought severely threatens food security, and its detrimental effects will be exacerbated by climate change in many parts of the world. Rice production is water-consuming and particularly vulnerable to drought stress. Upland rice is a special rice ecotype that specifically adapts to dryland mainly due to its robust root system. However, the molecular and developmental mechanism underlying this adaption has remained elusive. In this study, by comparing the root development between upland and irrigated rice phenotypically and cytologically, we identified key developmental phenotypes that distinguish upland rice from irrigated rice. We further generated spatial transcriptomic atlases for coleoptilar nodes and root tips to explore their molecular differences in crown root formation and development, uncovering promising genes for enhancing rice drought resistance. Among the identified genes, HMGB1, a transcriptional regulator, functions as a key factor that facilitates root elongation and thickening in upland rice and thereby enhances drought resistance. In summary, our study uncovers spatially resolved transcriptomic features in roots of upland rice that contribute to its adaptation to dryland conditions, providing valuable genetic resources for breeding drought-resilient rice.

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.

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.

DNA methylation dynamics play crucial roles in shaping the distinct transcriptomic profiles for different root-type initiation in rice

BACKGROUND

Monocots possess a fibrous root system comprising an embryonic root, crown roots, and lateral roots. The distinct cellular origins highlight the diversity of the initiation mechanism. To date, the distinct initiation mechanisms have been poorly studied. In this study, we conduct a comprehensive transcriptome and DNA methylome assay of these root types during their initiation.

RESULTS

Our findings indicate significant divergence in transcriptome regulation trajectories with apparent transcriptional activation in post-embryonic root initials (crown root and lateral root) contrasted by suppression in embryonic root generation. Additionally, CHH methylation is dynamically and differentially regulated across the initiation stages of the various root types, and is significantly associated with the short transposon element within the promoter regions of functional genes, which plays crucial roles in determining the genes' spatiotemporal transcription. Moreover, our work reveals that the activation of DNA glycosylase 702 (DNG702) and repression of Domains Rearranged Methyltransferase 2 (DRM2) play important roles in the erasure of CHH methylation and activation of functional genes during the processes, such as a novel identified key regulatory bZip65, thus directly impacting the initiation of post-embryonic roots in rice.

CONCLUSIONS

Our extensive analysis delineates the landscapes of spatiotemporal transcriptomes and DNA methylomes during the initiation of the three root types in rice, shedding light on the pivotal role of CHH methylation in the spatiotemporal regulation of various key genes, ensuring the successful initiation of distinct root types in rice.

Damage activates EXG1 and RLP44 to suppress vascular differentiation during regeneration in Arabidopsis

Plants possess remarkable regenerative abilities to form de novo vasculature after damage and in response to pathogens that invade and withdraw nutrients. To identify common factors that affect vascular formation upon stress, we searched for Arabidopsis thaliana genes differentially expressed upon Agrobacterium infection, nematode infection, and plant grafting. One such gene is cell wall-related and highly induced by all three stresses, which we named ENHANCED XYLEM AND GRAFTING1 (EXG1), since its mutations promote ectopic xylem formation in a vascular cell induction system and enhance graft formation. Further observations revealed that exg1 mutants show inhibited cambium development and callus formation but enhanced tissue attachment, syncytium size, phloem reconnection, and xylem formation. Given that brassinosteroids also promote xylem differentiation, we analyzed brassinosteroid-related genes and found that mutations in RLP44 encoding a receptor-like protein cause similar regeneration-related phenotypes as mutations in EXG1. Like EXG1, RLP44 expression is also induced by grafting and wounding. Mutations in EXG1 and RLP44 affect the expression of many genes in common, including those related to cell walls and genes important for vascular regeneration. Our results suggest that EXG1 integrates information from wounding or pathogen stress and functions with RLP44 to suppress vascular differentiation during regeneration and healing.

An Arabidopsis single-nucleus atlas decodes leaf senescence and nutrient allocation

With rapid advancements in single-cell RNA sequencing (scRNA-seq) technologies, exploration of the systemic coordination of critical physiological processes has entered a new era. Here, we generated a comprehensive Arabidopsis single-nucleus transcriptomic atlas using over 1 million nuclei from 20 tissues encompassing multiple developmental stages. Our analyses identified cell types that have not been characterized in previous single-protoplast studies and revealed cell-type conservation and specificity across different organs. Through time-resolved sampling, we revealed highly coordinated onset and progression of senescence among the major leaf cell types. We originally formulated two molecular indexes to quantify the aging state of leaf cells at single-cell resolution. Additionally, facilitated by weighted gene co-expression network analysis, we identified hundreds of promising hub genes that may integratively regulate leaf senescence. Inspired by the functional validation of identified hub genes, we built a systemic scenario of carbon and nitrogen allocation among different cell types from source leaves to sink organs.

Spatial omics for accelerating plant research and crop improvement

Plant cells communicate information to regulate developmental processes and respond to environmental stresses. This communication spans various 'omics' layers within a cell and operates through intricate regulatory networks. The emergence of spatial omics presents a promising approach to thoroughly analyze cells, allowing the combined analysis of diverse modalities either in parallel or on the same tissue section. Here, we provide an overview of recent advancements in spatial omics and delineate scientific discoveries in plant research enabled by these technologies. We delve into experimental and computational challenges and outline strategies to navigate these challenges for advancing breeding efforts. With ongoing insightful discoveries and improved accessibility, spatial omics stands on the brink of playing a crucial role in designing future crops.

Comparative single-nucleus RNA-seq analysis revealed localized and cell type-specific pathways governing root-microbiome interactions

Roots can recognize and differentially respond to beneficial and pathogenic microbes, which are fundamental for maintaining root microbiome homeostasis, plasticity, and plant fitness. Meanwhile, roots are highly heterogeneous tissues with complex cell-type compositions and spatially distinct developmental stages. We found that beneficial microbe specifically induces the expression of translation-related genes in the proximal meristem cells, and diverse ribosome proteins and translation regulators are necessary for beneficial microbe-mediated growth promotion. Notably, the root maturation zone can still mount localized immune responses to root pathogens, including genes related to camalexin and triterpene biosynthesis. A triterpene biosynthesis mutant blocked the microbiome reshaping process upon GMI1000 infection. Our results indicate roots may have specialized immune responses in the maturation zone, and provide important insights and vital resources for further elucidating regulators of root-microbe interactions and microbiome reshaping.

Two antagonistic gene regulatory networks drive Arabidopsis root hair growth at low temperature linked to a low-nutrient environment

Root hair (RH) cells can elongate to several hundred times their initial size, and are an ideal model system for investigating cell size control. Their development is influenced by both endogenous and external signals, which are combined to form an integrative response. Surprisingly, a low-temperature condition of 10°C causes increased RH growth in Arabidopsis and in several monocots, even when the development of the rest of the plant is halted. Previously, we demonstrated a strong correlation between RH growth response and a significant decrease in nutrient availability in the growth medium under low-temperature conditions. However, the molecular basis responsible for receiving and transmitting signals related to the availability of nutrients in the soil, and their relation to plant development, remain largely unknown. We have discovered two antagonic gene regulatory networks (GRNs) controlling RH early transcriptome responses to low temperature. One GNR enhances RH growth and it is commanded by the transcription factors (TFs) ROOT HAIR DEFECTIVE 6 (RHD6), HAIR DEFECTIVE 6-LIKE 2 and 4 (RSL2-RSL4) and a member of the homeodomain leucine zipper (HD-Zip I) group I 16 (AtHB16). On the other hand, a second GRN was identified as a negative regulator of RH growth at low temperature and it is composed by the trihelix TF GT2-LIKE1 (GTL1) and the associated DF1, a previously unidentified MYB-like TF (AT2G01060) and several members of HD-Zip I group (AtHB3, AtHB13, AtHB20, AtHB23). Functional analysis of both GRNs highlights a complex regulation of RH growth response to low temperature, and more importantly, these discoveries enhance our comprehension of how plants synchronize RH growth in response to variations in temperature at the cellular level.

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.

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.

Integrating Bulk and Single-Cell Transcriptomic Data to Identify Ferroptosis-Associated Inflammatory Gene in Alzheimer's Disease

Background

Ferroptosis is a form of programmed cell death triggered by iron-dependent lipid peroxidation, characterized by iron accumulation and elevated reactive oxygen species (ROS), leading to cell membrane damage. It is associated with a variety of diseases. However, the cellular and molecular links between ferroptosis, immune inflammation, and the brain-peripheral blood axis in Alzheimer's disease (AD) remain unclear.

Methods

We integrated bulk RNA-seq data from AD brain tissue and peripheral blood and refined the screening of AD candidate genes through differential gene expression analysis, weighted gene co-expression network analysis (WGCNA), and other approaches. Additionally, we analyzed single-cell RNA-seq (scRNA-seq) data from AD patients' brain tissue and peripheral blood, combined with scRNA-seq data from experimental autoimmune encephalomyelitis (EAE) mouse brain tissue. This enabled us to explore AD-related molecular mechanisms from a cell-type-specific perspective. Finally, candidate genes were validated in ferroptosis models using reverse transcription quantitative PCR (RT-qPCR) and immunofluorescence methods.

Results

Bulk RNA-seq analysis identified SLC11A1, an inflammatory gene associated with AD. Single-cell RNA-seq analysis further revealed that SLC11A1 expression was significantly elevated in the pro-inflammatory (M1-type) microglia and peripheral blood monocytes in AD. Moreover, we identified a microglial subpopulation in AD M1-type microglia that was highly associated with ferroptosis. This subpopulation simultaneously expressed characteristic markers of peripheral blood monocytes, suggesting that these cells may originate from peripheral blood monocytes, thereby triggering neuroinflammation through the ferroptosis pathway. Cell experiments confirmed that SLC11A1 was significantly upregulated in inflammatory microglia induced by ferroptosis.

Conclusion

This study reveals the key role of SLC11A1 in AD, particularly in the context of ferroptosis and immune inflammation. It provides a novel molecular mechanistic perspective and offers potential targets for future therapeutic strategies.

Advancing our understanding of root development: Technologies and insights from diverse studies

Understanding root development is critical for enhancing plant growth and health, and advanced technologies are essential for unraveling the complexities of these processes. In this review, we highlight select technological innovations in the study of root development, with a focus on the transformative impact of single-cell gene expression analysis. We provide a high-level overview of recent advancements, illustrating how single-cell RNA sequencing (scRNA-seq) has become a pivotal tool in plant biology. scRNA-seq has revolutionized root biology by enabling detailed, cell-specific analysis of gene expression. This has allowed researchers to create comprehensive root atlases, predict cell development, and map gene regulatory networks (GRNs) with unprecedented precision. Complementary technologies, such as multimodal profiling and bioinformatics, further enrich our understanding of cellular dynamics and gene interactions. Innovations in imaging and modeling, combined with genetic tools like CRISPR, continue to deepen our knowledge of root formation and function. Moreover, the integration of these technologies with advanced biosensors and microfluidic devices has advanced our ability to study plant-microbe interactions and phytohormone signaling at high resolution. These tools collectively provide a more comprehensive understanding of root system architecture and its regulation by environmental factors. As these technologies evolve, they promise to drive further breakthroughs in plant science, with substantial implications for agriculture and sustainability.

SCEMENT: scalable and memory efficient integration of large-scale single-cell RNA-sequencing data

MOTIVATION

Integrative analysis of large-scale single-cell data collected from diverse cell populations promises an improved understanding of complex biological systems. While several algorithms have been developed for single-cell RNA-sequencing data integration, many lack the scalability to handle large numbers of datasets and/or millions of cells due to their memory and run time requirements. The few tools that can handle large data do so by reducing the computational burden through strategies such as subsampling of the data or selecting a reference dataset to improve computational efficiency and scalability. Such shortcuts, however, hamper the accuracy of downstream analyses, especially those requiring quantitative gene expression information.

RESULTS

We present SCEMENT, a SCalablE and Memory-Efficient iNTegration method, to overcome these limitations. Our new parallel algorithm builds upon and extends the linear regression model previously applied in ComBat to an unsupervised sparse matrix setting to enable accurate integration of diverse and large collections of single-cell RNA-sequencing data. Using tens to hundreds of real single-cell RNA-seq datasets, we show that SCEMENT outperforms ComBat as well as FastIntegration and Scanorama in runtime (upto 214× faster) and memory usage (upto 17.5× less). It not only performs batch correction and integration of millions of cells in under 25 min, but also facilitates the discovery of new rare cell types and more robust reconstruction of gene regulatory networks with full quantitative gene expression information.

AVAILABILITY AND IMPLEMENTATION

Source code freely available for download at https://github.com/AluruLab/scement, implemented in C++ and supported on Linux.

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.

Nucleoporin PNET1 coordinates mitotic nuclear pore complex dynamics for rapid cell division

The nuclear pore complex (NPC) is a cornerstone of eukaryotic cell functionality, orchestrating the nucleocytoplasmic shuttling of macromolecules. Here we report that Plant Nuclear Envelope Transmembrane 1 (PNET1), a transmembrane nucleoporin, is an adaptable NPC component that is mainly expressed in actively dividing cells. PNET1's selective incorporation into the NPC is required for rapid cell growth in highly proliferative meristem and callus tissues in Arabidopsis. We demonstrate that the cell cycle-dependent phosphorylation of PNET1 coordinates mitotic disassembly and post-mitotic reassembly of NPCs during the cell cycle. PNET1 hyperphosphorylation disrupts its interaction with the NPC scaffold, facilitating NPC dismantling and nuclear membrane breakdown to trigger mitosis. In contrast, nascent, unphosphorylated PNET1 is incorporated into the nuclear pore membrane in the daughter cells, where it restores interactions with scaffolding nucleoporins for NPC reassembly. The expression of the human PNET1 homologue is required for and markedly upregulated during cancer cell growth, suggesting that PNET1 plays a conserved role in facilitating rapid cell division during open mitosis in highly proliferative tissues.

Identification of EXPA4 as a key gene in cotton salt stress adaptation through transcriptomic and coexpression network analysis of root tip protoplasts

BACKGROUND

Salinity stress impairs cotton growth and fiber quality. Protoplasts enable elucidation of early salt-responsive signaling. Elucidating crop tolerance mechanisms that ameliorate these diverse salinity-induced stresses is key for improving agricultural productivity under saline conditions.

RESULTS

Herein, we performed transcriptome profiling of Gossypium arboreum root tips and root tips-derived protoplasts to uncover salt tolerance genes and mechanisms. Differentially expressed genes (DEGs) were significantly enriched in the plant hormone signal transduction and MAPK signaling pathways. Transcriptome based weighted gene coexpression network analysis (WGCNA) clustered 885 commonly differentially expressed genes into four distinct modules. Black and yellow modules were highly upregulated under salt treatment, containing hub genes integral to signaling and transport, highlighting their importance. Differential expression analysis revealed more dynamic changes in protoplasts, identifying key genes including the Ga-α-expansin 4 (GaEXPA4). Silencing of the GaEXPA4 gene through virus-induced gene silencing heightened cotton's sensitivity to salt stress, leading to increased wilting, elevated lipid peroxidation, and impaired antioxidant activity under salt conditions compared to controls.

CONCLUSION

These findings underscore the functional significance of GaEXPA4 in the salt stress response. Future research should focus on elucidating the precise mechanisms of putative salt tolerance genes like GaEXPA4 and evaluating the potential of signaling pathways, such as MAPK, for engineering enhanced salt resilience in cotton. Integrating multi-omics approaches could further expand the genetic resources available for improving cotton cultivation in saline environments.

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.

Single-cell transcriptomic and cell‑type‑specific regulatory networks in Polima temperature-sensitive cytoplasmic male sterility of Brassica napus L

BACKGROUND

Thermosensitive male sterility (TMS) is a heritable agronomic trait influenced by the interaction between genotype and environment. The anthers of plants are composed of various specialized cells, each of which plays different roles in plant reproduction. In rapeseed (Brassica napus L.), Polima (pol) temperature-sensitive cytoplasmic male sterility (TCMS) is widely used in two-line breeding because its fertility can be partially restored at certain temperatures. The pol-TCMS line exhibits abnormal anther development and pollen abortion at high (restrictive) temperatures (HT, 25 °C) compared to at low (permissive) temperatures (LT, 16 °C). However, the response of different anther cell types to HT and the dynamic regulation of genes under such conditions remain largely unknown.

RESULTS

We present the first single-cell transcriptomic atlas of Brassica napus early developing flower bud tissues in response to HT. We identified 8 cell types and 17 transcriptionally distinct cell clusters via known marker genes under LT and HT treatment conditions. Under HT conditions, changes in the gene expression patterns of different cell clusters were observed, with the number of down-regulated genes in various cell types exceeding that of up-regulated genes. Pseudotime trajectory analysis revealed that HT strongly affected the development of early stamen/anther tissue cells. In combination with the snRNA-seq, WGCNA, and bulk RNA-seq results, we found that many transcription factors play crucial roles in the response to HT, especially heat response family genes.

CONCLUSIONS

Our study revealed the transcriptional regulatory network of floral bud tissue in the pol-TCMS line under HT/LT conditions and increased our understanding of high-temperature-induced anther developmental abnormalities, which may help researchers utilize TCMS in the two-line breeding of Brassica plants.

Filling the gaps on root hair development under salt stress and phosphate starvation using current evidence coupled with a meta-analysis approach

Population expansion is a global issue, especially for food production. Meanwhile, global climate change is damaging our soils, making it difficult for crops to thrive and lowering both production and quality. Poor nutrition and salinity stress affect plant growth and development. Although the impact of individual plant stresses has been studied for decades, the real stress scenario is more complex due to the exposure to multiple stresses at the same time. Here we investigate using existing evidence and a meta-analysis approach to determine molecular linkages between 2 contemporaneous abiotic stimuli, phosphate (Pi) deficiency and salinity, on a single plant cell model, the root hairs (RHs), which is the first plant cell exposed to them. Understanding how these 2 stresses work molecularly in RHs may help us build super-adaptable crops and sustainable agriculture in the face of global climate change.

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.

Unraveling plant-microbe symbioses using single-cell and spatial transcriptomics

Plant-microbe symbioses require intense interaction and genetic coordination to successfully establish in specific cell types of the host and symbiont. Traditional RNA-seq methodologies lack the cellular resolution to fully capture these complexities, but single-cell and spatial transcriptomics (ST) are now allowing scientists to probe symbiotic interactions at an unprecedented level of detail. Here, we discuss the advantages that novel spatial and single-cell transcriptomic technologies provide in studying plant-microbe endosymbioses and highlight key recent studies. Finally, we consider the remaining limitations of applying these approaches to symbiosis research, which are mainly related to the simultaneous capture of both plant and microbial transcripts within the same cells.

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.

Antagonistic CLE peptide pathways shape root meristem tissue patterning

Secreted CLAVATA3/EMBRYO SURROUNDING REGION (CLE) peptide ligands dimension the stem cell niche of Arabidopsis shoot meristems by signalling through redundant and cross-compensating CLAVATA1 (CLV1)-type receptor kinases. In the root meristem, the CLV1 homologues BARELY ANY MERISTEM 1 (BAM1) and BAM2 drive CLE13/16-mediated formative divisions that produce the ground tissue layers. Here we report that BAM1/2 are also required to initiate the vascular phloem lineage and that cross-compensation between CLV1-type receptors as observed in the shoot does not operate similarly in the root. Rather, we find that BAM3-mediated CLE45 signalling antagonizes BAM1/2-mediated CLE11/12/13 signalling in the phloem initials but not in the ground tissue. We further observe spatiotemporally contrasting CLE signalling requirements for phloem initiation and differentiation, which are shaped by the SHORT ROOT (SHR) pathway. Our findings thus suggest an intricate quantitative interplay between distinct and antagonistic CLE signalling pathways that organizes tissue layer formation in the Arabidopsis root meristem.

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.

Omics-Driven Strategies for Developing Saline-Smart Lentils: A Comprehensive Review

A number of consequences of climate change, notably salinity, put global food security at risk by impacting the development and production of lentils. Salinity-induced stress alters lentil genetics, resulting in severe developmental issues and eventual phenotypic damage. Lentils have evolved sophisticated signaling networks to combat salinity stress. Lentil genomics and transcriptomics have discovered key genes and pathways that play an important role in mitigating salinity stress. The development of saline-smart cultivars can be further revolutionized by implementing proteomics, metabolomics, miRNAomics, epigenomics, phenomics, ionomics, machine learning, and speed breeding approaches. All these cutting-edge approaches represent a viable path toward creating saline-tolerant lentil cultivars that can withstand climate change and meet the growing demand for high-quality food worldwide. The review emphasizes the gaps that must be filled for future food security in a changing climate while also highlighting the significant discoveries and insights made possible by omics and other state-of-the-art biotechnological techniques.

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

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

Transcriptional landscape of sweetpotato root tip development at the single-cell level

Single-cell transcriptome sequencing (scRNA-seq) is a powerful tool for describing the transcriptome dynamics of plant development but has not yet been utilized to analyze the tissue ontology of sweetpotato. This study established a stable method for isolating single protoplast cells for scRNA-seq to reveal the cell heterogeneity of sweetpotato root tip meristems at the single-cell level. The study analyzed 12,172 single cells and 27,355 genes in the root tips of the sweetpotato variety Guangshu 87, which were distributed into 15 cell clusters. Pseudo-time analysis showed that there were transitional cells in the apical development trajectory of mature cell types from stem cell niches. Furthermore, we identified novel development regulators of sweetpotato tubers via trajectory analysis. The transcription factor IbGATA4 was highly expressed in the adventitious roots during the development of sweetpotato root tips, where it may regulate the development of sweetpotato root tips. In addition, significant differences were observed in the transcriptional profiles of cell types between sweetpotato, Arabidopsis thaliana, and maize. This study mapped the single-cell transcriptome of sweetpotato root tips, laying a foundation for studying the types, functions, differentiation, and development of sweetpotato root tip cells.

Artificial intelligence in plant breeding

Harnessing cutting-edge technologies to enhance crop productivity is a pivotal goal in modern plant breeding. Artificial intelligence (AI) is renowned for its prowess in big data analysis and pattern recognition, and is revolutionizing numerous scientific domains including plant breeding. We explore the wider potential of AI tools in various facets of breeding, including data collection, unlocking genetic diversity within genebanks, and bridging the genotype-phenotype gap to facilitate crop breeding. This will enable the development of crop cultivars tailored to the projected future environments. Moreover, AI tools also hold promise for refining crop traits by improving the precision of gene-editing systems and predicting the potential effects of gene variants on plant phenotypes. Leveraging AI-enabled precision breeding can augment the efficiency of breeding programs and holds promise for optimizing cropping systems at the grassroots level. This entails identifying optimal inter-cropping and crop-rotation models to enhance agricultural sustainability and productivity in the field.

Dynamics of alternative polyadenylation in single root cells of Arabidopsis thaliana

Introduction

Single-cell RNA-seq (scRNA-seq) technologies have been widely used to reveal the diversity and complexity of cells, and pioneering studies on scRNA-seq in plants began to emerge since 2019. However, existing studies on plants utilized scRNA-seq focused only on the gene expression regulation. As an essential post-transcriptional mechanism for regulating gene expression, alternative polyadenylation (APA) generates diverse mRNA isoforms with distinct 3' ends through the selective use of different polyadenylation sites in a gene. APA plays important roles in regulating multiple developmental processes in plants, such as flowering time and stress response.

Methods

In this study, we developed a pipeline to identify and integrate APA sites from different scRNA-seq data and analyze APA dynamics in single cells. First, high-confidence poly(A) sites in single root cells were identified and quantified. Second, three kinds of APA markers were identified for exploring APA dynamics in single cells, including differentially expressed poly(A) sites based on APA site expression, APA markers based on APA usages, and APA switching genes based on 3' UTR (untranslated region) length change. Moreover, cell type annotations of single root cells were refined by integrating both the APA information and the gene expression profile.

Results

We comprehensively compiled a single-cell APA atlas from five scRNA-seq studies, covering over 150,000 cells spanning four major tissue branches, twelve cell types, and three developmental stages. Moreover, we quantified the dynamic APA usages in single cells and identified APA markers across tissues and cell types. Further, we integrated complementary information of gene expression and APA profiles to annotate cell types and reveal subtle differences between cell types.

Discussion

This study reveals that APA provides an additional layer of information for determining cell identity and provides a landscape of APA dynamics during Arabidopsis root development.

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.

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.

Lost in space: what single-cell RNA sequencing cannot tell you

Plant scientists are rapidly integrating single-cell RNA sequencing (scRNA-seq) into their workflows. Maximizing the potential of scRNA-seq requires a proper understanding of the spatiotemporal context of cells. However, positional information is inherently lost during scRNA-seq, limiting its potential to characterize complex biological systems. In this review we highlight how current single-cell analysis pipelines cannot completely recover spatial information, which confounds biological interpretation. Various strategies exist to identify the location of RNA, from classical RNA in situ hybridization to spatial transcriptomics. Herein we discuss the possibility of utilizing this spatial information to supervise single-cell analyses. An integrative approach will maximize the potential of each technology, and lead to insights which go beyond the capability of each individual technology.

Streamlined spatial and environmental expression signatures characterize the minimalist duckweed Wolffia australiana

Single-cell genomics permits a new resolution in the examination of molecular and cellular dynamics, allowing global, parallel assessments of cell types and cellular behaviors through development and in response to environmental circumstances, such as interaction with water and the light-dark cycle of the Earth. Here, we leverage the smallest, and possibly most structurally reduced, plant, the semiaquatic Wolffia australiana, to understand dynamics of cell expression in these contexts at the whole-plant level. We examined single-cell-resolution RNA-sequencing data and found Wolffia cells divide into four principal clusters representing the above- and below-water-situated parenchyma and epidermis. Although these tissues share transcriptomic similarity with model plants, they display distinct adaptations that Wolffia has made for the aquatic environment. Within this broad classification, discrete subspecializations are evident, with select cells showing unique transcriptomic signatures associated with developmental maturation and specialized physiologies. Assessing this simplified biological system temporally at two key time-of-day (TOD) transitions, we identify additional TOD-responsive genes previously overlooked in whole-plant transcriptomic approaches and demonstrate that the core circadian clock machinery and its downstream responses can vary in cell-specific manners, even in this simplified system. Distinctions between cell types and their responses to submergence and/or TOD are driven by expression changes of unexpectedly few genes, characterizing Wolffia as a highly streamlined organism with the majority of genes dedicated to fundamental cellular processes. Wolffia provides a unique opportunity to apply reductionist biology to elucidate signaling functions at the organismal level, for which this work provides a powerful resource.

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

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

Full-length RNA sequencing and single-nucleus sequencing deciphers programmed cell death and developmental trajectories in laticiferous canals of Decaisnea insignis fruits

Introduction

Programmed cell death (PCD) is a fundamental biological process crucial for plant development. Despite recent advancements in our understanding of PCD's molecular mechanisms, the intricate orchestration of this process within plant cells remains enigmatic. To address this knowledge gap, the present study focuses on Decaisnea insignis, a plant species renowned for its unique fruit anatomy, including laticiferous canals that secrete latex. While extensive anatomical studies have elucidated the structural features of these canals,molecular insights into their developmental regulation, particularly the involvement of PCD, are lacking.

Methods

In this study, we sequenced the single-cell transcriptomes at two developmental stage of Decaisnea insignis fruit using the technology known as 10x Genomics (S1, S2). Using sequencing technology combining full- length RNA sequencing and single-nucleus RNA sequencing (snRNA-seq) in combination with ultrastructural analyses, our study revealed a cellular map of Decaisnea insignis fruit at the single-cell level and identified different cell types.

Results

In particular, we identified a possible PCD-mediated cluster of Decaisnea insignis fruit lactiferous canals in epidermal cells and clarified the expression patterns of DiRD21A (a hydrolase) and DiLSD1 (a transcription factor), which may be closely related to the development of laticiferous canals in Decaisnea insignis fruits.

Discussion

By integrating high-resolution gene expression profiling with visual insights into cellular transformations, we sought to more precisely characterize the regulatory role of PCD during the developmental formation of lactiferous canals in Decaisnea insignis fruit.

Single-cell transcriptome atlases of soybean root and mature nodule reveal new regulatory programs that control the nodulation process

The soybean root system is complex. In addition to being composed of various cell types, the soybean root system includes the primary root, the lateral roots, and the nodule, an organ in which mutualistic symbiosis with N-fixing rhizobia occurs. A mature soybean root nodule is characterized by a central infection zone where atmospheric nitrogen is fixed and assimilated by the symbiont, resulting from the close cooperation between the plant cell and the bacteria. To date, the transcriptome of individual cells isolated from developing soybean nodules has been established, but the transcriptomic signatures of cells from the mature soybean nodule have not yet been characterized. Using single-nucleus RNA-seq and Molecular Cartography technologies, we precisely characterized the transcriptomic signature of soybean root and mature nodule cell types and revealed the co-existence of different sub-populations of B. diazoefficiens-infected cells in the mature soybean nodule, including those actively involved in nitrogen fixation and those engaged in senescence. Mining of the single-cell-resolution nodule transcriptome atlas and the associated gene co-expression network confirmed the role of known nodulation-related genes and identified new genes that control the nodulation process. For instance, we functionally characterized the role of GmFWL3, a plasma membrane microdomain-associated protein that controls rhizobial infection. Our study reveals the unique cellular complexity of the mature soybean nodule and helps redefine the concept of cell types when considering the infection zone of the soybean nodule.

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.

Single-cell network analysis reveals gene expression programs for Arabidopsis root development and metabolism

Single-cell RNA-sequencing datasets of Arabidopsis roots have been generated, but related comprehensive gene co-expression network analyses are lacking. We conducted a single-cell gene co-expression network analysis with publicly available scRNA-seq datasets of Arabidopsis roots using a SingleCellGGM algorithm. The analysis identified 149 gene co-expression modules, which we considered to be gene expression programs (GEPs). By examining their spatiotemporal expression, we identified GEPs specifically expressed in major root cell types along their developmental trajectories. These GEPs define gene programs regulating root cell development at different stages and are enriched with relevant developmental regulators. As examples, a GEP specific for the quiescent center (QC) contains 20 genes regulating QC and stem cell niche homeostasis, and four GEPs are expressed in sieve elements (SEs) from early to late developmental stages, with the early-stage GEP containing 17 known SE developmental regulators. We also identified GEPs for metabolic pathways with cell-type-specific expression, suggesting the existence of cell-type-specific metabolism in roots. Using the GEPs, we discovered and verified a columella-specific gene, NRL27, as a regulator of the auxin-related root gravitropism response. Our analysis thus systematically reveals GEPs that regulate Arabidopsis root development and metabolism and provides ample resources for root biology studies.

Single-nucleus RNA and ATAC sequencing analyses provide molecular insights into early pod development of peanut fruit

Peanut (Arachis hypogaea L.) is an important leguminous oil and economic crop that produces flowers aboveground and fruits belowground. Subterranean fruit-pod development, which significantly affects peanut production, involves complex molecular mechanisms that likely require the coordinated regulation of multiple genes in different tissues. To investigate the molecular mechanisms that underlie peanut fruit-pod development, we characterized the anatomical features of early fruit-pod development and integrated single-nucleus RNA-sequencing (snRNA-seq) and single-nucleus assay for transposase-accessible chromatin with sequencing (snATAC-seq) data at the single-cell level. We identified distinct cell types, such as meristem, embryo, vascular tissue, cuticular layer, and stele cells within the shell wall. These specific cell types were used to examine potential molecular changes unique to each cell type during pivotal stages of fruit-pod development. snRNA-seq analyses of differentially expressed genes revealed cell-type-specific insights that were not previously obtainable from transcriptome analyses of bulk RNA. For instance, we identified MADS-box genes that contributes to the formation of parenchyma cells and gravity-related genes that are present in the vascular cells, indicating an essential role for the vascular cells in peg gravitropism. Overall, our single-nucleus analysis provides comprehensive and novel information on specific cell types, gene expression, and chromatin accessibility during the early stages of fruit-pod development. This information will enhance our understanding of the mechanisms that underlie fruit-pod development in peanut and contribute to efforts aimed at improving peanut production.

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.

Coexpression enhances cross-species integration of single-cell RNA sequencing across diverse plant species

Single-cell RNA sequencing is increasingly used to investigate cross-species differences driven by gene expression and cell-type composition in plants. However, the frequent expansion of plant gene families due to whole-genome duplications makes identification of one-to-one orthologues difficult, complicating integration. Here we demonstrate that coexpression can be used to trim many-to-many orthology families down to identify one-to-one gene pairs with proxy expression profiles, improving the performance of traditional integration methods and reducing barriers to integration across a diverse array of plant species.

Genomic characteristics of adipose-derived stromal cells induced into neurons based on single-cell RNA sequencing

Adipose-derived stromal cells (ADSCs) can be induced to differentiate into neurons, representing the most promising avenue for cell therapy. However, the molecular mechanism and genomic characteristics of the differentiation of ADSCs into neurons remain poorly understood. In this study, cells from the adult ADSCs group, induction 1h, 3h, 5h, 6h, and 8h groups were selected for single-cell RNA sequencing (scRNA-Seq). Samples from these seven-time points were sequenced and analyzed. The expression of neuron marker genes, including NES, MAP2, TMEM59L, PTK2B, CHN1, DNM1, NRSN2, FBLN2, SCAMP1, SLC1A1, DLG4, CDK5, and ENO2, was found to be low in the ADSCs group, but highly expressed in differentiated cell clusters. The expression of stem cell marker genes, including CCND1, IL1B, MMP1, MMP3, MYO10, and BMP2, was the highest in the ADSCs cluster. This expression decreased significantly with the extension of induction time. Gene ontology (GO) enrichment analysis of upregulated genes in the induced samples showed that the biological processes related to neuronal differentiation and development, such as neuronal differentiation, projection, and apoptosis, were significantly upregulated with a longer induction time during cell cluster differentiation. The results of the cell communication analysis demonstrated the gradual formation of complex neural network connections between ADSC-derived neurons through receptor and ligand pairs at 5h after the induction of differentiation.

Global dynamics and cytokinin participation of salt gland development trajectory in recretohalophyte Limonium bicolor

Salt gland is an epidermal Na+ secretory structure that enhances salt resistance in the recretohalophyte sea lavender (Limonium bicolor). To elucidate the salt gland development trajectory and related molecular mechanisms, we performed single-cell RNA sequencing of L. bicolor protoplasts from young leaves at salt gland initiation and differentiation stages. Dimensionality reduction analyses defined 19 transcriptionally distinct cell clusters, which were assigned into 4 broad populations-promeristem, epidermis, mesophyll, and vascular tissue-verified by in situ hybridization. Cytokinin was further proposed to participate in salt gland development by the expression patterns of related genes and cytological evidence. By comparison analyses of Single-cell RNA sequencing with exogenous application of 6-benzylaminopurine, we delineated 5 salt gland development-associated subclusters and defined salt gland-specific differentiation trajectories from Subclusters 8, 4, and 6 to Subcluster 3 and 1. Additionally, we validated the participation of TRIPTYCHON and the interacting protein Lb7G34824 in salt gland development, which regulated the expression of cytokinin metabolism and signaling-related genes such as GLABROUS INFLORESCENCE STEMS 2 to maintain cytokinin homeostasis during salt gland development. Our results generated a gene expression map of young leaves at single-cell resolution for the comprehensive investigation of salt gland determinants and cytokinin participation that helps elucidate cell fate determination during epidermis formation and evolution in recretohalophytes.

Multiome in the Same Cell Reveals the Impact of Osmotic Stress on Arabidopsis Root Tip Development at Single-Cell Level

Cell-specific transcriptional regulatory networks (TRNs) play vital roles in plant development and response to environmental stresses. However, traditional single-cell mono-omics techniques are unable to directly capture the relationships and dynamics between different layers of molecular information within the same cells. While advanced algorithm facilitates merging scRNA-seq and scATAC-seq datasets, accurate data integration remains a challenge, particularly when investigating cell-type-specific TRNs. By examining gene expression and chromatin accessibility simultaneously in 16,670 Arabidopsis root tip nuclei, the TRNs are reconstructed that govern root tip development under osmotic stress. In contrast to commonly used computational integration at cell-type level, 12,968 peak-to-gene linkage is captured at the bona fide single-cell level and construct TRNs at an unprecedented resolution. Furthermore, the unprecedented datasets allow to more accurately reconstruct the coordinated changes of gene expression and chromatin states during cellular state transition. During root tip development, chromatin accessibility of initial cells precedes gene expression, suggesting that changes in chromatin accessibility may prime cells for subsequent differentiation steps. Pseudo-time trajectory analysis reveal that osmotic stress can shift the functional differentiation of trichoblast. Candidate stress-related gene-linked cis-regulatory elements (gl-cCREs) as well as potential target genes are also identified, and uncovered large cellular heterogeneity under osmotic stress.