Development of a single-cell atlas for woodland strawberry (Fragaria vesca) leaves during early Botrytis cinerea infection using single cell RNA-seq

Spatiotemporal transcriptomic landscape of rice embryonic cells during seed germination

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

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

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

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.

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

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

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.

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.

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.

Single-cell RNA-seq reveals a link of ovule abortion and sugar transport in Camellia oleifera

Camellia oleifera is the most important woody oil crop in China. Seed number per fruit is an important yield trait in C. oleifera. Ovule abortion is generally observed in C. oleifera and significantly decreases the seed number per fruit. However, the mechanisms of ovule abortion remain poorly understood at present. Single-cell RNA sequencing (scRNA-seq) was performed using mature ovaries of two C. oleifera varieties with different ovule abortion rates (OARs). In total, 20,526 high-quality cells were obtained, and 18 putative cell clusters were identified. Six cell types including female gametophyte, protoxylem, protophloem, procambium, epidermis, and parenchyma cells were identified from three main tissue types of ovule, placenta, and pericarp inner layer. A comparative analysis on scRNA-seq data between high- and low-OAR varieties demonstrated that the overall expression of CoSWEET and CoCWINV in procambium cells, and CoSTP in the integument was significantly upregulated in the low-OAR variety. Both the infertile ovule before pollination and the abortion ovule producing after compatible pollination might be attributed to selective abortion caused by low sugar levels in the apoplast around procambium cells and a low capability of hexose uptake in the integument. Here, the first single-cell transcriptional landscape is reported in woody crop ovaries. Our investigation demonstrates that ovule abortion may be related to sugar transport in placenta and ovules and sheds light on further deciphering the mechanism of regulating sugar transport and the improvement of seed yield in C. oleifera.

Single-cell transcriptomic analysis of pea shoot development and cell-type-specific responses to boron deficiency

Understanding how nutrient stress impacts plant growth is fundamentally important to the development of approaches to improve crop production under nutrient limitation. Here we applied single-cell RNA sequencing to shoot apices of Pisum sativum grown under boron (B) deficiency. We identified up to 15 cell clusters based on the clustering of gene expression profiles and verified cell identity with cell-type-specific marker gene expression. Different cell types responded differently to B deficiency. Specifically, the expression of photosynthetic genes in mesophyll cells (MCs) was down-regulated by B deficiency, consistent with impaired photosynthetic rate. Furthermore, the down-regulation of stomatal development genes in guard cells, including homologs of MUTE and TOO MANY MOUTHS, correlated with a decrease in stomatal density under B deficiency. We also constructed the developmental trajectory of the shoot apical meristem (SAM) cells and a transcription factor interaction network. The developmental progression of SAM to MC was characterized by up-regulation of genes encoding histones and chromatin assembly and remodeling proteins including homologs of FASCIATA1 (FAS1) and SWITCH DEFECTIVE/SUCROSE NON-FERMENTABLE (SWI/SNF) complex. However, B deficiency suppressed their expression, which helps to explain impaired SAM development under B deficiency. These results represent a major advance over bulk-tissue RNA-seq analysis in which cell-type-specific responses are lost and hence important physiological responses to B deficiency are missed. The reported findings reveal strategies by which plants adapt to B deficiency thus offering breeders a set of specific targets for genetic improvement. The reported approach and resources have potential applications well beyond P. sativum species and could be applied to various legumes to improve their adaptability to multiple nutrient or abiotic stresses.

The dynamic arms race during the early invasion of woodland strawberry by Botrytis cinerea revealed by dual dense high-resolution RNA-seq analyses

Necrotrophic pathogens replicate massively upon colonizing plants, causing large-scale wilting and death of plant tissues. Understanding both mechanisms of pathogen invasion and host response processes prior to symptom appearance and their key regulatory networks is therefore important for defense against pathogen attack. Here, we investigated the mechanisms of interaction between woodland strawberry (Fragaria vesca) leaves and gray mold pathogen (Botrytis cinerea) at 14 infection time points during the first 12 hours of the infection period using a dense, high-resolution time series dual transcriptomic analysis, characterizing the arms race between strawberry F. vesca and B. cinerea before the appearance of localized lesions. Strawberry leaves rapidly initiated strong systemic defenses at the first sign of external stimulation and showed lower levels of transcriptomic change later in the infection process. Unlike the host plants, B. cinerea showed larger-scale transcriptomic changes that persisted throughout the infection process. Weighted gene co-expression network analysis identified highly correlated genes in 32 gene expression modules between B. cinerea and strawberry. Yeast two-hybrid and bimolecular fluorescence complementation assays revealed that the disease response protein FvRLP2 from woodland strawberry interacted with the cell death inducing proteins BcXYG1 and BcPG3 from B. cinerea. Overexpression of FvRLP2 in both strawberry and Arabidopsis inhibited B. cinerea infection, confirming these genes' respective functions. These findings shed light on the arms race process by which B. cinerea invades host plants and strawberry to defend against pathogen infection.

Single-cell transcriptome analyses reveal cellular and molecular responses to low nitrogen in burley tobacco leaves

Tobacco (Nicotiana tabacum) is cultivated and consumed worldwide. It requires great amounts of nitrogen (N) to achieve the best yield and quality. With a view to sustainable and environmentally friendly agriculture, developing new genotypes with high productivity under low N conditions is an important approach. It is unclear how genes in tobacco are expressed at the cellular level and the precise mechanisms by which cells respond to environmental stress, especially in the case of low N. Here, we characterized the transcriptomes in tobacco leaves grown in normal and low-N conditions by performing scRNA-seq. We identified 10 cell types with 17 transcriptionally distinct cell clusters with the assistance of marker genes and constructed the first single-cell atlas of tobacco leaves. Distinct gene expression patterns of cell clusters were observed under low-N conditions, and the mesophyll cells were the most important responsive cell type and displayed heterogene responses among its three subtypes. Pseudo-time trajectory analysis revealed low-N stress decelerates the differentiation towards mesophyll cells. In combination with scRNA-seq, WGCNA, and bulk RNA-seq results, we found that genes involved in porphyrin metabolism, nitrogen metabolism, carbon fixation, photosynthesis, and photosynthesis-antenna pathway play an essential role in response to low N. Moreover, we identified COL16, GATA24, MYB73, and GLK1 as key TFs in the regulation of N-responsive genes. Collectively, our findings are the first observation of the cellular and molecular responses of tobacco leaves under low N stress and lay the cornerstone for future tobacco scRNA-seq investigations.

OmicsSuite: a customized and pipelined suite for analysis and visualization of multi-omics big data

With the advancements in high-throughput sequencing technologies such as Illumina, PacBio, and 10X Genomics platforms, and gas/liquid chromatography-mass spectrometry, large volumes of biological data in multiple formats can now be obtained through multi-omics analysis. Bioinformatics is constantly evolving and seeking breakthroughs to solve multi-omics problems; however, it is challenging for most experimental biologists to analyse data using command-line interfaces, coding, and scripting. Based on experience with multi-omics, we have developed OmicsSuite, a desktop suite that comprehensively integrates statistics and multi-omics analysis and visualization. The suite has 175 sub-applications in 12 categories, including Sequence, Statistics, Algorithm, Genomics, Transcriptomics, Enrichment, Proteomics, Metabolomics, Clinical, Microorganism, Single Cell, and Table Operation. We created the user interface with Sequence View, Table View, and intelligent components based on JavaFX and the popular Shiny framework. The multi-omics analysis functions were developed based on BioJava and 300+ packages provided by the R CRAN and Bioconductor communities, and it encompasses over 3000 adjustable parameter interfaces. OmicsSuite can directly read multi-omics raw data in FastA, FastQ, Mutation Annotation Format, mzML, Matrix, and HDF5 formats, and the programs emphasize data transfer directions and pipeline analysis functions. OmicsSuite can produce pre-publication images and tables, allowing users to focus on biological aspects. OmicsSuite offers multi-omics step-by-step workflows that can be easily applied to horticultural plant breeding and molecular mechanism studies in plants. It enables researchers to freely explore the molecular information contained in multi-omics big data (Source: https://github.com/OmicsSuite/, Website: https://omicssuite.github.io, v1.3.9).

An Integrated Multi-Omics and Artificial Intelligence Framework for Advance Plant Phenotyping in Horticulture

This review discusses the transformative potential of integrating multi-omics data and artificial intelligence (AI) in advancing horticultural research, specifically plant phenotyping. The traditional methods of plant phenotyping, while valuable, are limited in their ability to capture the complexity of plant biology. The advent of (meta-)genomics, (meta-)transcriptomics, proteomics, and metabolomics has provided an opportunity for a more comprehensive analysis. AI and machine learning (ML) techniques can effectively handle the complexity and volume of multi-omics data, providing meaningful interpretations and predictions. Reflecting the multidisciplinary nature of this area of research, in this review, readers will find a collection of state-of-the-art solutions that are key to the integration of multi-omics data and AI for phenotyping experiments in horticulture, including experimental design considerations with several technical and non-technical challenges, which are discussed along with potential solutions. The future prospects of this integration include precision horticulture, predictive breeding, improved disease and stress response management, sustainable crop management, and exploration of plant biodiversity. The integration of multi-omics and AI holds immense promise for revolutionizing horticultural research and applications, heralding a new era in plant phenotyping.

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.

Understanding plant pathogen interactions using spatial and single-cell technologies

Plants are in contact with diverse pathogens and microorganisms. Intense investigation over the last 30 years has resulted in the identification of multiple immune receptors in model and crop species as well as signaling overlap in surface-localized and intracellular immune receptors. However, scientists still have a limited understanding of how plants respond to diverse pathogens with spatial and cellular resolution. Recent advancements in single-cell, single-nucleus and spatial technologies can now be applied to plant-pathogen interactions. Here, we outline the current state of these technologies and highlight outstanding biological questions that can be addressed in the future.

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 analyses reveal cellular and molecular patterns of rubber tree response to early powdery mildew infection

As a perennial woody plant, the rubber tree (Hevea brasiliensis) must adapt to various environmental challenges through gene expression in multiple cell types. It is still unclear how genes in this species are expressed at the cellular level and the precise mechanisms by which cells respond transcriptionally to environmental stimuli, especially in the case of pathogen infection. Here, we characterized the transcriptomes in Hevea leaves during early powdery mildew infection using single-cell RNA sequencing. We identified 10 cell types and constructed the first single-cell atlas of Hevea leaves. Distinct gene expression patterns of the cell clusters were observed under powdery mildew infection, which was especially significant in the epidermal cells. Most of the genes involved in host-pathogen interactions in epidermal cells exhibited a pattern of dramatically increased expression with increasing pseudotime. Interestingly, we found that the HbCNL2 gene, encoding a nucleotide-binding leucine-rich repeat protein, positively modulated the defence of rubber leaves against powdery mildew. Overexpression of the HbCNL2 gene triggered a typical cell death phenotype in tobacco leaves and a higher level of reactive oxygen species in the protoplasts of Hevea leaves. The HbCNL2 protein was located in the cytomembrane and nucleus, and its leucine-rich repeat domain interacted with the histidine kinase-like ATPase domain of the molecular chaperone HbHSP90 in the nucleus. Collectively, our results provide the first observation of the cellular and molecular responses of Hevea leaves to biotrophic pathogen infection and can guide the identification of disease-resistance genes in this important tree species.

Characterization of Arbuscular Mycorrhizal Effector Proteins

Plants are colonized by various fungi with both pathogenic and beneficial lifestyles. One type of colonization strategy is through the secretion of effector proteins that alter the plant's physiology to accommodate the fungus. The oldest plant symbionts, the arbuscular mycorrhizal fungi (AMF), may exploit effectors to their benefit. Genome analysis coupled with transcriptomic studies in different AMFs has intensified research on the effector function, evolution, and diversification of AMF. However, of the current 338 predicted effector proteins from the AM fungus Rhizophagus irregularis, only five have been characterized, of which merely two have been studied in detail to understand which plant proteins they associate with to affect the host physiology. Here, we review the most recent findings in AMF effector research and discuss the techniques used for the functional characterization of effector proteins, from their in silico prediction to their mode of action, with an emphasis on high-throughput approaches for the identification of plant targets of the effectors through which they manipulate their hosts.

Going broad and deep: sequencing-driven insights into plant physiology, evolution, and crop domestication

Deep sequencing is a term that has become embedded in the plant genomic literature in recent years and with good reason. A torrent of (largely) high-quality genomic and transcriptomic data has been collected and most of this has been publicly released. Indeed, almost 1000 plant genomes have been reported (www.plabipd.de) and the 2000 Plant Transcriptomes Project has long been completed. The EarthBioGenome project will dwarf even these milestones. That said, massive progress in understanding plant physiology, evolution, and crop domestication has been made by sequencing broadly (across a species) as well as deeply (within a single individual). We will outline the current state of the art in genome and transcriptome sequencing before we briefly review the most visible of these broad approaches, namely genome-wide association and transcriptome-wide association studies, as well as the compilation of pangenomes. This will include both (i) the most commonly used methods reliant on single nucleotide polymorphisms and short InDels and (ii) more recent examples which consider structural variants. We will subsequently present case studies exemplifying how their application has brought insight into either plant physiology or evolution and crop domestication. Finally, we will provide conclusions and an outlook as to the perspective for the extension of such approaches to different species, tissues, and biological processes.

Single-cell transcriptome atlas reveals developmental trajectories and a novel metabolic pathway of catechin esters in tea leaves

The tea plant is an economically important woody beverage crop. The unique taste of tea is evoked by certain metabolites, especially catechin esters, whereas their precise formation mechanism in different cell types remains unclear. Here, a fast protoplast isolation method was established and the transcriptional profiles of 16 977 single cells from 1st and 3rd leaves were investigated. We first identified 79 marker genes based on six isolated tissues and constructed a transcriptome atlas, mapped developmental trajectories and further delineated the distribution of different cell types during leaf differentiation and genes associated with cell fate transformation. Interestingly, eight differently expressed genes were found to co-exist at four branch points. Genes involved in the biosynthesis of certain metabolites showed cell- and development-specific characteristics. An unexpected catechin ester glycosyltransferase was characterized for the first time in plants by a gene co-expression network in mesophyll cells. Thus, the first single-cell transcriptional landscape in woody crop leave was reported and a novel metabolism pathway of catechin esters in plants was discovered.