A spatiotemporal atlas of organogenesis in the development of orchid flowers

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.

Advances in bamboo genomics: Growth and development, stress tolerance, and genetic engineering

Bamboo is a fast-growing and ecologically significant plant with immense economic value due to its applications in construction, textiles, and bioenergy. However, research on bamboo has been hindered by its long vegetative period, unpredictable flowering cycles, and challenges in genetic transformation. Recent developments in advanced sequencing and genetic engineering technologies have provided new insights into bamboo's evolutionary history, developmental biology, and stress resilience, paving the way for improved conservation and sustainable utilization. This review synthesizes the latest findings on bamboo's genomics, biotechnology, and the molecular mechanisms governing its growth, development, and stress response. Key genes and regulatory pathways controlling its rapid growth, internode elongation, rhizome development, culm lignification, flowering, and abiotic stress responses have been identified through multi-omics and functional studies. Complex interactions among transcription factors, epigenetic regulators, and functionally important genes shape bamboo's unique growth characteristics. Moreover, progress in genetic engineering techniques, including clustered regularly interspaced short palindromic repeats-based genome editing, has opened new avenues for targeted genetic improvements. However, technical challenges, particularly the complexity of polyploid bamboo genomes and inefficient regeneration systems, remain significant barriers to functional studies and large-scale breeding efforts. By integrating recent genomic discoveries with advancements in biotechnology, this review proposes potential strategies to overcome existing technological limitations and to accelerate the development of improved bamboo varieties. Continued efforts in multi-omics research, gene-editing applications, and sustainable cultivation practices will be essential for harnessing bamboo as a resilient and renewable resource for the future. The review presented here not only deepens our understanding of bamboo's genetic architecture but also provides a foundation for future research aimed at optimizing its ecological and industrial potential.

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.

Spatiotemporal transcriptomics reveals key gene regulation for grain yield and quality in wheat

BACKGROUND

Cereal grain size and quality are critical agronomic traits in crop production. Wheat grain development is governed by intricate regulatory networks that require precise spatiotemporal coordination of gene expression to establish functional compartments in different cell types.

RESULTS

Here, we perform a spatial transcriptomics study covering the early stages of wheat grain development, from 4 to 12 days after pollination. We classify the grain into 10 distinct cell types and identify 192 marker genes associated with them. WGCNA analysis reveals that highly expressed genes in different cell types exhibit distinct enrichment patterns, significantly influencing grain development and filling. Through co-expression and motif analyses, we identify a specific group of genes that may regulate wheat grain development, including TaABI3-B1, a transcription factor specifically expressed in the embryo and surrounding endosperm, which negatively affects embryo and grain size.

CONCLUSIONS

This study presents a comprehensive spatiotemporal transcriptional dataset for understanding wheat grain development. Additionally, it identifies key genetic resources with potential applications for improving wheat yield.

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.

The Molecular Mechanism of Interaction Between SEPALLATA3 and APETALA1 in Arabidopsis thaliana

Flower formation has been a primary focus in botanical research, leading to the identification of multiple factors regulating flowering over the past 30 years. The MADS transcription factors SEPALLATA3 (SEP3) and APETALA1 (AP1) are essential for floral meristem development and organ identity. In Arabidopsis, SEP3 functions as a central integrator, combining MADS proteins into a tetrameric complex, with its interaction with AP1 playing a key role in sepal and petal formation. This research explores AtSEP3 and AtAP1, with particular emphasis on the Leu residue in the K1 subfunctional domain of AtSEP3, which is necessary for their interaction. A predicted structural model of AP1 was used, followed by protein docking with SEP3, which indicated that Leu residues at positions 115 and 116 are critical binding sites. Mutations at these position were examined through yeast two-hybrid assays and other techniques, identifying Leu 116 as a significant site. Subsequent purification and EMSA analysis revealed that mutations in the leucine zipper of SEP3 decreased its DNA binding ability. Observations of transgenic plants showed that disruption of AtSEP3 and AtAP1 interaction resulted in extended vegetative growth, increased size and number of rosette leaves, and modifications in floral structures. This study offers new insights into the interaction mechanism between AP1 and SEP3 during flowering.

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.

Protocol to denoise spatially resolved transcriptomics data utilizing optimal transport-based gene filtering algorithm

Spatially resolved transcriptomics (SRT) data contain intricate noise due to the diffusion of transcripts caused by tissue fixation, permeabilization, and cell lysis during the experiment. Here, we present a protocol for denoising SRT data using SpotGF, an optimal transport-based gene filtering algorithm, without modifying the raw gene expression. We describe steps for data preparation, SpotGF score calculation, filtering threshold determination, denoised data generation, and visualization. Our protocol enhances SRT quality and improves the performance of downstream analyses. For complete details on the use and execution of this protocol, please refer to Du et al.1.

Centenary Progress on Orchidaceae Research: A Bibliometric Analysis

BACKGROUND

Research on orchids has experienced substantial growth since the early 20th century, reflecting their ecological and evolutionary significance.

METHODS

This paper provides a comprehensive bibliometric analysis of orchid-related literature published between 1902 and 2024, based on data retrieved from the Web of Science Core Collection™ (WoS).

RESULTS

The primary goal is to assess the global research landscape of orchids by identifying key authors, institutions, and journals, as well as major research themes in the field. A thorough analysis of publication trends, citation frequencies, and keyword co-occurrence networks was conducted to uncover significant research hotspots. The findings indicate that orchid research has evolved from foundational topics such as taxonomy and classification to more intricate subjects, including conservation strategies, orchid-pollinator dynamics, and the role of orchids in ecosystem functions. Additionally, biotechnology-related research is emerging as a dominant trend. This study also highlights that China has the highest publication output, while collaboration between the United States and Europe continues to grow. The co-word analysis of keywords suggests that future research is likely to continue to focus on orchid conservation, the impacts of climate change, pollination biology, and symbiotic relationships with mycorrhizal fungi.

CONCLUSIONS

This review offers valuable insights for researchers and conservationists, helping to identify future research priorities and strategies for the preservation and sustainable use of orchids.

Spatial transcriptome and single-cell RNA sequencing reveal the molecular basis of cotton fiber initiation development

Recent advances in single-cell transcriptomics have greatly expanded our knowledge of plant development and cellular responses. However, analyzing fiber cell differentiation in plants, particularly in cotton, remains a complex challenge. A spatial transcriptomic map of ovule from -1 DPA, 0 DPA, and 1 DPA in cotton was successfully constructed, which helps to explain the important role of sucrose synthesis and lipid metabolism during early fiber development. Additionally, single-cell RNA sequencing (scRNA-seq) further highlighted the cellular heterogeneity and identified clusters of fiber developmental marker genes. Integration of spatial and scRNA-seq data unveiled key genes SVB and SVBL involved in fiber initiation, suggesting functional redundancy between them. These findings provide a detailed molecular landscape of cotton fiber development, offering valuable insights for enhancing lint yield.

Cross-species single-nucleus analysis reveals the potential role of whole-genome duplication in the evolution of maize flower development

BACKGROUND

The evolution and development of flowers are biologically essential and of broad interest. Maize and sorghum have similar morphologies and phylogeny while harboring different inflorescence architecture. The difference in flower architecture between these two species is likely due to spatiotemporal gene expression regulation, and they are a good model for researching the evolution of flower development.

RESULTS

In this study, we generated single nucleus and spatial RNA-seq data for maize ear, tassel, and sorghum inflorescence. By combining single nucleus and spatial transcriptome, we can track the spatial expression of single nucleus cluster marker genes and map single nucleus clusters to spatial positions. This ability provides great power to annotate the single nucleus clusters. Combining the cell cluster resolved transcriptome comparison with genome alignment, our analysis suggested that maize ear and tassel inflorescence diversity is associated with the maize-specific whole genome duplication. Taking sorghum as the outgroup, it is likely that the loss of gene expression profiling contributes to the inflorescence diversity between tassel and ear, resulting in the unisexual flower architecture of maize. The sequence of highly expressed genes in the tassel is more conserved than the highly expressed genes in the ear.

CONCLUSION

This study provides a high-resolution atlas of gene activity during inflorescence development and helps to unravel the potential evolution associated with the differentiation of the ear and tassel in maize.

Unveiling the mechanism of micro-and-nano plastic phytotoxicity on terrestrial plants: A comprehensive review of omics approaches

Micro-and-nano plastics (MNPs) are pervasive in terrestrial ecosystems and represent an increasing threat to plant health; however, the mechanisms underlying their phytotoxicity remain inadequately understood. MNPs can infiltrate plants through roots or leaves, causing a range of toxic effects, including inhibiting water and nutrient uptake, reducing seed germination rates, and impeding photosynthesis, resulting in oxidative damage within the plant system. The effects of MNPs are complex and influenced by various factors including size, shape, functional groups, and concentration. Recent advancements in omics technologies such as proteomics, metabolomics, transcriptomics, and microbiomics, coupled with emerging technologies like 4D omics, phenomics, spatial transcriptomics, and single-cell omics, offer unprecedented insight into the physiological, molecular, and cellular responses of terrestrial plants to MNPs exposure. This literature review synthesizes current findings regarding MNPs-induced phytotoxicity, emphasizing alterations in gene expression, protein synthesis, metabolic pathways, and physiological disruptions as revealed through omics analyses. We summarize how MNPs interact with plant cellular structures, disrupt metabolic processes, and induce oxidative stress, ultimately affecting plant growth and productivity. Furthermore, we have identified critical knowledge gaps and proposed future research directions, highlighting the necessity for integrative omics studies to elucidate the complex pathways of MNPs toxicity in terrestrial plants. In conclusion, this review underscores the potential of omics approaches to elucidate the mechanisms of MNPs-phytotoxicity and to develop strategies for mitigating the environmental impact of MNPs on plant health.

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.

Spatial transcriptome analysis reveals de novo regeneration of poplar roots

Propagation through cuttings is a well-established and effective technique for plant multiplication. This study explores the regeneration of poplar roots using spatial transcriptomics to map a detailed developmental trajectory. Mapping of the time-series transcriptome data revealed notable alterations in gene expression during root development, particularly in the activation of cytokinin-responsive genes. Our analysis identified six distinct clusters during the second and third stages, each corresponding to specific anatomical regions with unique gene expression profiles. Auxin response cis-elements (AuxREs) were prevalent in the promoters of these cytokinin-responsive genes, indicating a regulatory interplay between auxin and cytokinin. Pseudo-temporal trajectory analysis mapped the differentiation from cambium cells to root primordium cells, revealing a complex pattern of cell differentiation. SAC56 and LOS1 emerged as potential novel biomarkers for enhancing root regeneration, with distinct spatial expression patterns confirmed by in situ hybridization. This comprehensive spatial analysis enhances our understanding of the molecular interactions driving root regeneration and provides insights for improving plant propagation techniques.

A signal-diffusion-based unsupervised contrastive representation learning for spatial transcriptomics analysis

MOTIVATION

Spatial transcriptomics allows for the measurement of high-throughput gene expression data while preserving the spatial structure of tissues and histological images. Integrating gene expression, spatial information, and image data to learn discriminative low-dimensional representations is critical for dissecting tissue heterogeneity and analyzing biological functions. However, most existing methods have limitations in effectively utilizing spatial information and high-resolution histological images. We propose a signal-diffusion-based unsupervised contrast learning method (SDUCL) for learning low-dimensional latent embeddings of cells/spots.

RESULTS

SDUCL integrates image features, spatial relationships, and gene expression information. We designed a signal diffusion microenvironment discovery algorithm, which effectively captures and integrates interaction information within the cellular microenvironment by simulating the biological signal diffusion process. By maximizing the mutual information between the local representation and the microenvironment representation of cells/spots, SDUCL learns more discriminative representations. SDUCL was employed to analyze spatial transcriptomics datasets from multiple species, encompassing both normal and tumor tissues. SDUCL performed well in downstream tasks such as clustering, visualization, trajectory inference, and differential gene analysis, thereby enhancing our understanding of tissue structure and tumor microenvironments.

AVAILABILITY AND IMPLEMENTATION

https://github.com/WeiMin-Li-visual/SDUCL.

A history-dependent integrase recorder of plant gene expression with single-cell resolution

During development, most cells experience a progressive restriction of fate that ultimately results in a fully differentiated mature state. Understanding more about the gene expression patterns that underlie developmental programs can inform engineering efforts for new or optimized forms. Here, we present a four-state integrase-based recorder of gene expression history and demonstrate its use in tracking gene expression events in Arabidopsis thaliana in two developmental contexts: lateral root initiation and stomatal differentiation. The recorder uses two serine integrases to mediate sequential DNA recombination events, resulting in step-wise, history-dependent switching between expression of fluorescent reporters. By using promoters that express at different times along each of the two differentiation pathways to drive integrase expression, we tie fluorescent status to an ordered progression of gene expression along the developmental trajectory. In one snapshot of a mature tissue, our recorder is able to reveal past gene expression with single cell resolution. In this way, we are able to capture heterogeneity in stomatal development, confirming the existence of two alternate paths of differentiation.

Spatial transcriptomics of a parasitic flatworm provides a molecular map of drug targets and drug resistance genes

The spatial organization of gene expression dictates tissue functions in multicellular parasites. Here, we present the spatial transcriptome of a parasitic flatworm, the common liver fluke Fasciola hepatica. We identify gene expression profiles and marker genes for eight distinct tissues and validate the latter by in situ hybridization. To demonstrate the power of our spatial atlas, we focus on genes with substantial medical importance, including vaccine candidates (Ly6 proteins) and drug resistance genes (glutathione S-transferases, ABC transporters). Several of these genes exhibit unique expression patterns, indicating tissue-specific biological functions. Notably, the prioritization of tegumental protein kinases identifies a PKCβ, for which small-molecule targeting causes parasite death. Our comprehensive gene expression map provides unprecedented molecular insights into the organ systems of this complex parasitic organism, serving as a valuable tool for both basic and applied research.

SpotGF: Denoising spatially resolved transcriptomics data using an optimal transport-based gene filtering algorithm

Spatially resolved transcriptomics (SRT) combines gene expression profiles with the physical locations of cells in their native states but suffers from unpredictable spatial noise due to cell damage during cryosectioning and exposure to reagents for staining and mRNA release. To address this noise, we developed SpotGF, an algorithm for denoising SRT data using optimal transport-based gene filtering. SpotGF quantifies diffusion patterns numerically, distinguishing widespread expression genes from aggregated expression genes and filtering out the former as noise. Unlike conventional denoising methods, SpotGF preserves raw sequencing data, thereby avoiding false positives that can arise from imputation. Additionally, SpotGF demonstrates superior performance in cell clustering, identifying potential marker genes, and annotating cell types. Overall, SpotGF has the potential to become a crucial preprocessing step in the downstream analysis of SRT data. The SpotGF software is freely available at GitHub. A record of this paper's transparent peer review process is included in the supplemental information.

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.

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.

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

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

Molecular and genetic regulation of petal number variation

Floral forms with an increased number of petals, also known as double-flower phenotypes, have been selected and conserved in many domesticated plants, particularly in ornamentals, because of their great economic value. The molecular and genetic mechanisms that control this trait are therefore of great interest, not only for scientists, but also for breeders. In this review, we summarize current knowledge of the gene regulatory networks of flower initiation and development and known mutations that lead to variation of petal number in many species. In addition to the well-accepted miR172/AP2-like module, for which many questions remain unanswered, we also discuss other pathways in which mutations also lead to the formation of extra petals, such as those involved in meristem maintenance, hormone signalling, epigenetic regulation, and responses to environmental signals. We discuss how the concept of 'natural mutants' and recent advances in genomics and genome editing make it possible to explore the molecular mechanisms underlying double-flower formation, and how such knowledge could contribute to the future breeding and selection of this trait in more crops.

Spatiotemporal transcriptomic atlas of rhizome formation in Oryza longistaminata

Rhizomes are modified stems that grow underground and produce new individuals genetically identical to the mother plant. Recently, a breakthrough has been made in efforts to convert annual grains into perennial ones by utilizing wild rhizomatous species as donors, yet the developmental biology of this organ is rarely studied. Oryza longistaminata, a wild rice species featuring strong rhizomes, provides a valuable model for exploration of rhizome development. Here, we first assembled a double-haplotype genome of O. longistaminata, which displays a 48-fold improvement in contiguity compared to the previously published assembly. Furthermore, spatiotemporal transcriptomics was performed to obtain the expression profiles of different tissues in O. longistaminata rhizomes and tillers. Two spatially reciprocal cell clusters, the vascular bundle 2 cluster and the parenchyma 2 cluster, were determined to be the primary distinctions between the rhizomes and tillers. We also captured meristem initiation cells in the sunken area of parenchyma located at the base of internodes, which is the starting point for rhizome initiation. Trajectory analysis further indicated that the rhizome is regenerated through de novo generation. Collectively, these analyses revealed a spatiotemporal transcriptional transition underlying the rhizome initiation, providing a valuable resource for future perennial crop breeding.

Single-cell and spatial RNA sequencing reveal the spatiotemporal trajectories of fruit senescence

The senescence of fruit is a complex physiological process, with various cell types within the pericarp, making it highly challenging to elucidate their individual roles in fruit senescence. In this study, a single-cell expression atlas of the pericarp of pitaya (Hylocereus undatus) is constructed, revealing exocarp and mesocarp cells undergoing the most significant changes during the fruit senescence process. Pseudotime analysis establishes cellular differentiation and gene expression trajectories during senescence. Early-stage oxidative stress imbalance is followed by the activation of resistance in exocarp cells, subsequently senescence-associated proteins accumulate in the mesocarp cells at late-stage senescence. The central role of the early response factor HuCMB1 is unveiled in the senescence regulatory network. This study provides a spatiotemporal perspective for a deeper understanding of the dynamic senescence process in plants.

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.

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.

Research advances on the gene regulation of floral development and color in orchids

Orchidaceae is one of the largest monocotyledon families and contributes significantly to worldwide biodiversity, with value in the fields of landscaping, medicine, and ecology. The diverse phenotypes and vibrant colors of orchid floral organs make them excellent research objects for investigating flower development and pigmentation. In recent years, a number of orchid genomes have been published, laying the molecular foundation for revealing flower development and color presentation. In this article, we review transcription factors, the structural genes responsible for the floral pigment synthesis pathways, the molecular mechanisms of flower morphogenesis, and the potential relationship between flower type and flower color. This study provides a theoretical reference for the research on molecular mechanisms related to flower morphogenesis and color presentation, genetic improvement, and new variety creation in orchids.

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

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

Spatial transcriptomics drives a new era in plant research

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

Resolving plant development in space and time with single-cell genomics

Single-cell genomics technologies are ushering in a new research era. In this review, we summarize the benefits and current challenges of using these technologies to probe the transcriptional regulation of plant development. In addition to profiling cells at a single snapshot in time, researchers have recently produced time-resolved datasets to map cell responses to stimuli. Live-imaging and spatial transcriptomic techniques are rapidly being adopted to link a cell's transcriptional profile with its spatial location within a tissue. Combining these technologies is a powerful spatiotemporal approach to investigate cell plasticity and developmental responses that contribute to plant resilience. Although there are hurdles to overcome, we conclude by discussing how single-cell genomics is poised to address developmental questions in the coming years.

Spatial transcriptomics reveals light-induced chlorenchyma cells involved in promoting shoot regeneration in tomato callus

Callus is a reprogrammed cell mass involved in plant regeneration and gene transformation in crop engineering. Pluripotent callus cells develop into fertile shoots through shoot regeneration. The molecular basis of the shoot regeneration process in crop callus remains largely elusive. This study pioneers the exploration of the spatial transcriptome of tomato callus during shoot regeneration. The findings reveal the presence of highly heterogeneous cell populations within the callus, including epidermis, vascular tissue, shoot primordia, inner callus, and outgrowth shoots. By characterizing the spatially resolved molecular features of shoot primordia and surrounding cells, specific factors essential for shoot primordia formation are identified. Notably, chlorenchyma cells, enriched in photosynthesis-related processes, play a crucial role in promoting shoot primordia formation and subsequent shoot regeneration. Light is shown to promote shoot regeneration by inducing chlorenchyma cell development and coordinating sugar signaling. These findings significantly advance our understanding of the cellular and molecular aspects of shoot regeneration in tomato callus and demonstrate the immense potential of spatial transcriptomics in plant biology.

Combining single-cell RNA sequencing with spatial transcriptome analysis reveals dynamic molecular maps of cambium differentiation in the primary and secondary growth of trees

Primary and secondary growth of the tree stem are responsible for corresponding increases in trunk height and diameter. However, our molecular understanding of the biological processes that underlie these two types of growth is incomplete. In this study, we used single-cell RNA sequencing and spatial transcriptome sequencing to reveal the transcriptional landscapes of primary and secondary growth tissues in the Populus stem. Comparison between the cell atlas and differentiation trajectory of primary and secondary growth revealed different regulatory networks involved in cell differentiation from cambium to xylem precursors and phloem precursors. These regulatory networks may be controlled by auxin accumulation and distribution. Analysis of cell differentiation trajectories suggested that vessel and fiber development followed a sequential pattern of progressive transcriptional regulation. This research provides new insights into the processes of cell identity and differentiation that occur throughout primary and secondary growth of tree stems, increasing our understanding of the cellular differentiation dynamics that occur during stem growth in trees.

Spatially resolved transcriptomic analysis of the germinating barley grain

Seeds are a vital source of calories for humans and a unique stage in the life cycle of flowering plants. During seed germination, the embryo undergoes major developmental transitions to become a seedling. Studying gene expression in individual seed cell types has been challenging due to the lack of spatial information or low throughput of existing methods. To overcome these limitations, a spatial transcriptomics workflow was developed for germinating barley grain. This approach enabled high-throughput analysis of spatial gene expression, revealing specific spatial expression patterns of various functional gene categories at a sub-tissue level. This study revealed over 14 000 genes differentially regulated during the first 24 h after imbibition. Individual genes, such as the aquaporin gene family, starch degradation, cell wall modification, transport processes, ribosomal proteins and transcription factors, were found to have specific spatial expression patterns over time. Using spatial autocorrelation algorithms, we identified auxin transport genes that had increasingly focused expression within subdomains of the embryo over time, suggesting their role in establishing the embryo axis. Overall, our study provides an unprecedented spatially resolved cellular map for barley germination and identifies specific functional genomics targets to better understand cellular restricted processes during germination. The data can be viewed at https://spatial.latrobe.edu.au/.

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

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

Deciphering plant cell-cell communications using single-cell omics data

Plants have various cell types that respond to different environmental factors, and cell-cell communication is the fundamental process that controls these plant responses. The emergence of single-cell techniques provides opportunities to explore features unique to each cell type and construct a comprehensive cell-cell communication (CCC) network. Although the most current successes of CCC inference were achieved in animal research, computational methods can also be directly applied to plants. This review describes the current major models for cell-cell communication inference and summarizes the computational tools based on single-cell omics datasets. In addition, we discuss the limitations of plant cell-cell communication research and propose new directions to expand the field in meaningful ways.

Characterization of Gene Regulatory Networks in Plants Using New Methods and Data Types

A major question in plant biology is to understand how plant growth, development, and environmental responses are controlled and coordinated by the activities of regulatory factors. Gene regulatory network (GRN) analyses require integrated approaches that combine experimental approaches with computational analyses. A wide range of experimental approaches and tools are now available, such as targeted perturbation of gene activities, quantitative and cell-type specific measurements of dynamic gene activities, and systematic analysis of the molecular 'hard-wiring' of the systems. At the computational level, different tools and databases are available to study regulatory sequences, including intuitive visualizations to explore data-driven gene regulatory networks in different plant species. Furthermore, advanced data integration approaches have recently been developed to efficiently leverage complementary regulatory data types and learn context-specific networks.