Plant Cell Identity in the Era of Single-Cell Transcriptomics

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

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

Dynamic patterns of gene expressional and regulatory variations in cotton heterosis

Purpose

Although the application of heterosis has significantly increased crop yield over the past century, the mechanisms underlying this phenomenon still remain obscure. Here, we applied transcriptome sequencing to unravel the impacts of parental expression differences and transcriptomic reprogramming in cotton heterosis.

Methods

A high-quality transcriptomic atlas covering 15 developmental stages and tissues was constructed for XZM2, an elite hybrid of upland cotton (Gossypium hirsutum L.), and its parental lines, CRI12 and J8891. This atlas allowed us to identify gene expression differences between the parents and to characterize the transcriptomic reprogramming that occurs in the hybrid.

Results

Our analysis revealed abundant gene expression differences between the parents, with pronounced tissue specificity; a total of 1,112 genes exhibited single-parent expression in at least one tissue. It also illuminated transcriptomic reprogramming in the hybrid XZM2, which included both additive and non-additive expression patterns. Coexpression networks between parents and hybrid constructed via weighted gene coexpression network analysis identified modules closely associated with fiber development. In particular, key regulatory hub genes involved in fiber development showed high-parent dominant or over dominant patterns in the hybrid, potentially driving the emergence of heterosis. Finally, high-depth resequencing data was generated and allele-specific expression patterns examined in the hybrid, enabling the dissection of cis- and trans-regulation contributions to the observed expression differences.

Conclusion

Parental transcriptional differences and transcriptomic reprogramming in the hybrid, especially the non-additive upregulation of key genes, play an important role in shaping heterosis. Collectively, these findings provide new insights into the molecular basis of heterosis in cotton.

Cellular basis of legume-rhizobium symbiosis

The legume-rhizobium symbiosis represents the most important system for terrestrial biological nitrogen fixation on land. Efficient nitrogen fixation during this symbiosis depends on successful rhizobial infection and complete endosymbiosis, which are achieved by complex cellular events including cell-wall remodeling, cytoskeletal reorganizations, and extensive membrane expansion and trafficking. In this review, we explore the dynamic remodeling of the plant-specific cell wall-membrane system-cytoskeleton (WMC) continuum during symbiotic nitrogen fixation. We focus on key processes linked to efficient nitrogen fixation, including rhizobial uptake, infection thread formation and elongation, rhizobial droplet release, cytoplasmic bridge formation, and rhizobial endosymbiosis. Additionally, we discuss the advanced techniques for investigating the cellular basis of root-nodule symbiosis and provide insights into the unsolved mysteries of robust symbiotic nitrogen fixation.

Integrating omics databases for enhanced crop breeding

Crop plant breeding involves selecting and developing new plant varieties with desirable traits such as increased yield, improved disease resistance, and enhanced nutritional value. With the development of high-throughput technologies, such as genomics, transcriptomics, and metabolomics, crop breeding has entered a new era. However, to effectively use these technologies, integration of multi-omics data from different databases is required. Integration of omics data provides a comprehensive understanding of the biological processes underlying plant traits and their interactions. This review highlights the importance of integrating omics databases in crop plant breeding, discusses available omics data and databases, describes integration challenges, and highlights recent developments and potential benefits. Taken together, the integration of omics databases is a critical step towards enhancing crop plant breeding and improving global food security.

Engineering custom morpho- and chemotypes of Populus for sustainable production of biofuels, bioproducts, and biomaterials

Humans have been modifying plant traits for thousands of years, first through selection (i.e., domestication) then modern breeding, and in the last 30 years, through biotechnology. These modifications have resulted in increased yield, more efficient agronomic practices, and enhanced quality traits. Precision knowledge of gene regulation and function through high-resolution single-cell omics technologies, coupled with the ability to engineer plant genomes at the DNA sequence, chromatin accessibility, and gene expression levels, can enable engineering of complex and complementary traits at the biosystem level. Populus spp., the primary genetic model system for woody perennials, are among the fastest growing trees in temperate zones and are important for both carbon sequestration and global carbon cycling. Ample genomic and transcriptomic resources for poplar are available including emerging single-cell omics datasets. To expand use of poplar outside of valorization of woody biomass, chassis with novel morphotypes in which stem branching and tree height are modified can be fabricated thereby leading to trees with altered leaf to wood ratios. These morphotypes can then be engineered into customized chemotypes that produce high value biofuels, bioproducts, and biomaterials not only in specific organs but also in a cell-type-specific manner. For example, the recent discovery of triterpene production in poplar leaf trichomes can be exploited using cell-type specific regulatory sequences to synthesize high value terpenes such as the jet fuel precursor bisabolene specifically in the trichomes. By spatially and temporally controlling expression, not only can pools of abundant precursors be exploited but engineered molecules can be sequestered in discrete cell structures in the leaf. The structural diversity of the hemicellulose xylan is a barrier to fully utilizing lignocellulose in biomaterial production and by leveraging cell-type-specific omics data, cell wall composition can be modified in a tailored and targeted specific manner to generate poplar wood with novel chemical features that are amenable for processing or advanced manufacturing. Precision engineering poplar as a multi-purpose sustainable feedstock highlights how genome engineering can be used to re-imagine a crop species.

Cell type-specific cytonuclear coevolution in three allopolyploid plant species

Cytonuclear disruption may accompany allopolyploid evolution as a consequence of the merger of different nuclear genomes in a cellular environment having only one set of progenitor organellar genomes. One path to reconcile potential cytonuclear mismatch is biased expression for maternal gene duplicates (homoeologs) encoding proteins that target to plastids and/or mitochondria. Assessment of this transcriptional form of cytonuclear coevolution at the level of individual cells or cell types remains unexplored. Using single-cell (sc-) and single-nucleus (sn-) RNAseq data from eight tissues in three allopolyploid species, we characterized cell type-specific variations of cytonuclear coevolutionary homoeologous expression and demonstrated the temporal dynamics of expression patterns across development stages during cotton fiber development. Our results provide unique insights into transcriptional cytonuclear coevolution in plant allopolyploids at the single-cell level.

Application of single-cell multi-omics approaches in horticulture research

Cell heterogeneity shapes the morphology and function of various tissues and organs in multicellular organisms. Elucidation of the differences among cells and the mechanism of intercellular regulation is essential for an in-depth understanding of the developmental process. In recent years, the rapid development of high-throughput single-cell transcriptome sequencing technologies has influenced the study of plant developmental biology. Additionally, the accuracy and sensitivity of tools used to study the epigenome and metabolome have significantly increased, thus enabling multi-omics analysis at single-cell resolution. Here, we summarize the currently available single-cell multi-omics approaches and their recent applications in plant research, review the single-cell based studies in fruit, vegetable, and ornamental crops, and discuss the potential of such approaches in future horticulture research.

Single-cell transcriptome atlas reveals spatiotemporal developmental trajectories in the basal roots of moso bamboo (Phyllostachys edulis)

Roots are essential for plant growth and development. Bamboo is a large Poaceae perennial with 1642 species worldwide. However, little is known about the transcriptional atlas that underpins root cell-type differentiation. Here, we set up a modified protocol for protoplast preparation and report single-cell transcriptomes of 14 279 filtered single cells derived from the basal root tips of moso bamboo. We identified four cell types and defined new cell-type-specific marker genes for the basal root. We reconstructed the developmental trajectories of the root cap, epidermis, and ground tissues and elucidated critical factors regulating cell fate determination. According to in situ hybridization and pseudotime trajectory analysis, the root cap and epidermis originated from a common initial cell lineage, revealing the particularity of bamboo basal root development. We further identified key regulatory factors for the differentiation of these cells and indicated divergent root developmental pathways between moso bamboo and rice. Additionally, PheWOX13a and PheWOX13b ectopically expressed in Arabidopsis inhibited primary root and lateral root growth and regulated the growth and development of the root cap, which was different from WOX13 orthologs in Arabidopsis. Taken together, our results offer an important resource for investigating the mechanism of root cell differentiation and root system architecture in perennial woody species of Bambusoideae.

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

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

The Role of Chromatin and Transcriptional Control in the Formation of Sexual Fruiting Bodies in Fungi

Fungal fruiting bodies are complex, three-dimensional structures that arise from a less complex vegetative mycelium. Their formation requires the coordinated action of many genes and their gene products, and fruiting body formation is accompanied by major changes in the transcriptome. In recent years, numerous transcription factor genes as well as chromatin modifier genes that play a role in fruiting body morphogenesis were identified, and through research on several model organisms, the underlying regulatory networks that integrate chromatin structure, gene expression, and cell differentiation are becoming clearer. This review gives a summary of the current state of research on the role of transcriptional control and chromatin structure in fruiting body development. In the first part, insights from transcriptomics analyses are described, with a focus on comparative transcriptomics. In the second part, examples of more detailed functional characterizations of the role of chromatin modifiers and/or transcription factors in several model organisms (Neurospora crassa, Aspergillus nidulans, Sordaria macrospora, Coprinopsis cinerea, and Schizophyllum commune) that have led to a better understanding of regulatory networks at the level of chromatin structure and transcription are discussed.

Single-cell RNA-seq reveals fate determination control of an individual fibre cell initiation in cotton (Gossypium hirsutum)

Cotton fibre is a unicellular seed trichome, and lint fibre initials per seed as a factor determines fibre yield. However, the mechanisms controlling fibre initiation from ovule epidermis are not understood well enough. Here, with single-cell RNA sequencing (scRNA-seq), a total of 14 535 cells were identified from cotton ovule outer integument of Xu142_LF line at four developmental stages (1.5, 1, 0.5 days before anthesis and the day of anthesis). Three major cell types, fibre, non-fibre epidermis and outer pigment layer were identified and then verified by RNA in situ hybridization. A comparative analysis on scRNA-seq data between Xu142 and its fibreless mutant Xu142 fl further confirmed fibre cluster definition. The developmental trajectory of fibre cell was reconstructed, and fibre cell was identified differentiated at 1 day before anthesis. Gene regulatory networks at four stages revealed the spatiotemporal pattern of core transcription factors, and MYB25-like and HOX3 were demonstrated played key roles as commanders in fibre differentiation and tip-biased diffuse growth respectively. A model for early development of a single fibre cell was proposed here, which sheds light on further deciphering mechanism of plant trichome and the improvement of cotton fibre yield.

Single-cell technologies: From research to application

In recent years, more and more single-cell technologies have been developed. A vast amount of single-cell omics data has been generated by large projects, such as the Human Cell Atlas, the Mouse Cell Atlas, the Mouse RNA Atlas, the Mouse ATAC Atlas, and the Plant Cell Atlas. Based on these single-cell big data, thousands of bioinformatics algorithms for quality control, clustering, cell-type annotation, developmental inference, cell-cell transition, cell-cell interaction, and spatial analysis are developed. With powerful experimental single-cell technology and state-of-the-art big data analysis methods based on artificial intelligence, the molecular landscape at the single-cell level can be revealed. With spatial transcriptomics and single-cell multi-omics, even the spatial dynamic multi-level regulatory mechanisms can be deciphered. Such single-cell technologies have many successful applications in oncology, assisted reproduction, embryonic development, and plant breeding. We not only review the experimental and bioinformatics methods for single-cell research, but also discuss their applications in various fields and forecast the future directions for single-cell technologies. We believe that spatial transcriptomics and single-cell multi-omics will become the next booming business for mechanism research and commercial industry.

The egg cell is preferentially fertilized in Arabidopsis double fertilization

In flowering plants (angiosperms), fertilization of the egg cell by one sperm cell produces an embryo, whereas fusion of a second sperm cell with the central cell generates the endosperm. In most angiosperms like Arabidopsis, a pollen grain contains two isomorphic sperm cells required for this double fertilization process. A long-standing unsolved question is whether the two fertilization events have any preference. A tool to address this question is the usage of the cyclin-dependent kinase a1 (cdka;1) mutant pollen, which produces a single sperm-like cell (SLC). Here, we first adopt a complementation-based fluorescence-labeling method to successfully separate and collect cdka;1 mutant pollen containing a single SLC. Single-cell RNA-sequencing analysis revealed that cdka;1 SLCs show a gene expression profile highly similar to that of sperm cells and not to the generative cell, precursor of the two sperm cells. Pollination assays using a limited number of cdka;1 mutant pollen revealed that in 98.2% of the ovules, single fertilization of the egg cell occurred. Pollination of pistils with excessive cdka;1 mutant pollen allowed the delivery of a second SLC via fertilization recovery, which fertilized the central cell, resulting in 20.7% double-fertilized ovules. This indicates that cdka;1 SLCs are able to fertilize both the egg and the central cell. Taken together, our findings have answered a long-standing question and support that preferential fertilization of the egg cell is evident in Arabidopsis.

Research strategies for single-cell transcriptome analysis in plant leaves

The recent and continuous improvement in single-cell RNA sequencing (scRNA-seq) technology has led to its emergence as an efficient experimental approach in plant research. However, compared with single-cell research in animals and humans, the application of scRNA-seq in plant research is limited by several challenges, including cell separation, cell type annotation, cellular function analysis, and cell-cell communication networks. In addition, the unavailability of corresponding reliable and stable analysis methods and standards has resulted in the relative decentralization of plant single-cell research. Considering these shortcomings, this review summarizes the research progress in plant leaf using scRNA-seq. In addition, it describes the corresponding feasible analytical methods and associated difficulties and problems encountered in the current research. In the end, we provide a speculative overview of the development of plant single-cell transcriptome research in the future.

Investigation of Brassica and its relative genomes in the post-genomics era

The Brassicaceae family includes many economically important crop species, as well as cosmopolitan agricultural weed species. In addition, Arabidopsis thaliana, a member of this family, is used as a molecular model plant species. The genus Brassica is mesopolyploid, and the genus comprises comparatively recently originated tetrapolyploid species. With these characteristics, Brassicas have achieved the commonly accepted status of model organisms for genomic studies. This paper reviews the rapid research progress in the Brassicaceae family from diverse omics studies, including genomics, transcriptomics, epigenomics, and three-dimensional (3D) genomics, with a focus on cultivated crops. The morphological plasticity of Brassicaceae crops is largely due to their highly variable genomes. The origin of several important Brassicaceae crops has been established. Genes or loci domesticated or contributing to important traits are summarized. Epigenetic alterations and 3D structures have been found to play roles in subgenome dominance, either in tetraploid Brassica species or their diploid ancestors. Based on this progress, we propose future directions and prospects for the genomic investigation of Brassicaceae crops.

Molecular mechanisms underlying leaf development, morphological diversification, and beyond

The basic mechanisms of leaf development have been revealed through a combination of genetics and intense analyses in select model species. The genetic basis for diversity in leaf morphology seen in nature is also being unraveled through recent advances in techniques and technologies related to genomics and transcriptomics, which have had a major impact on these comparative studies. However, this has led to the emergence of new unresolved questions about the mechanisms that generate the diversity of leaf form. Here, we provide a review of the current knowledge of the fundamental molecular genetic mechanisms underlying leaf development with an emphasis on natural variation and conserved gene regulatory networks involved in leaf development. Beyond that, we discuss open questions/enigmas in the area of leaf development, how recent technologies can best be deployed to generate a unified understanding of leaf diversity and its evolution, and what untapped fields lie ahead.

Identification of new marker genes from plant single-cell RNA-seq data using interpretable machine learning methods

An essential step in the analysis of single-cell RNA sequencing data is to classify cells into specific cell types using marker genes. In this study, we have developed a machine learning pipeline called single-cell predictive marker (SPmarker) to identify novel cell-type marker genes in the Arabidopsis root. Unlike traditional approaches, our method uses interpretable machine learning models to select marker genes. We have demonstrated that our method can: assign cell types based on cells that were labelled using published methods; project cell types identified by trajectory analysis from one data set to other data sets; and assign cell types based on internal GFP markers. Using SPmarker, we have identified hundreds of new marker genes that were not identified before. As compared to known marker genes, the new marker genes have more orthologous genes identifiable in the corresponding rice single-cell clusters. The new root hair marker genes also include 172 genes with orthologs expressed in root hair cells in five non-Arabidopsis species, which expands the number of marker genes for this cell type by 35-154%. Our results represent a new approach to identifying cell-type marker genes from scRNA-seq data and pave the way for cross-species mapping of scRNA-seq data in plants.