Plant Systems Biology at the Single-Cell Level

ggPlantmap: an open-source R package for the creation of informative and quantitative ggplot maps derived from plant images

As plant research generates an ever-growing volume of spatial quantitative data, the need for decentralized and user-friendly visualization tools to explore large and complex datasets becomes crucial. Existing resources, such as the Plant eFP (electronic Fluorescent Pictograph) viewer, have played a pivotal role on the communication of gene expression data across many plant species. However, although widely used by the plant research community, the Plant eFP viewer lacks open and user-friendly tools for the creation of customized expression maps independently. Plant biologists with less coding experience can often encounter challenges when attempting to explore ways to communicate their own spatial quantitative data. We present 'ggPlantmap' an open-source R package designed to address this challenge by providing an easy and user-friendly method for the creation of ggplot representative maps from plant images. ggPlantmap is built in R, one of the most used languages in biology, to empower plant scientists to create and customize eFP-like viewers tailored to their experimental data. Here, we provide an overview of the package and tutorials that are accessible even to users with minimal R programming experience. We hope that ggPlantmap can assist the plant science community, fostering innovation, and improving our understanding of plant development and function.

Milletomics: a metabolomics centered integrated omics approach toward genetic progression

Producing alternative staple foods like millet will be essential to feeding ten billion people by 2050. The increased demand for millet is driving researchers to improve its genetic variation. Millets include protein, dietary fiber, phenolic substances, and flavonoid components. Its climate resilience makes millet an appealing crop for agronomic sustainability. Integrative omics technologies could potentially identify and develop millets with desirable phenotypes that may have high agronomic value. Millets' salinity and drought tolerance have been enhanced using transcriptomics. In foxtail, finger, and pearl millet, proteomics has discovered salt-tolerant protein, phytohormone-focused protein, and drought tolerance. Metabolomics studies have revealed that certain metabolic pathways including those involving lignin, flavonoids, phenylpropanoid, and lysophospholipids are critical for many processes, including seed germination, photosynthesis, energy metabolism, and the synthesis of bioactive chemicals necessary for drought tolerance. Metabolomics integration with other omics revealed metabolome engineering and trait-specific metabolite creation. Integrated metabolomics and ionomics are still in the development stage, but they could potentially assist in comprehending the pathway of ionomers to control nutrient levels and biofortify millet. Epigenomic analysis has shown alterations in DNA methylation patterns and chromatin structure in foxtail and pearl millets in response to abiotic stress. Whole-genome sequencing utilizing next-generation sequencing is the most proficient method for finding stress-induced phytoconstituent genes. New genome sequencing enables novel biotechnological interventions including genome-wide association, mutation-based research, and other omics approaches. Millets can breed more effectively by employing next-generation sequencing and genotyping by sequencing, which may mitigate climate change. Millet marker-assisted breeding has advanced with high-throughput markers and combined genotyping technologies.

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

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

Single-cell transcriptome landscape elucidates the cellular and developmental responses to tomato chlorosis virus infection in tomato leaf

Plant viral diseases compromise the growth and yield of the crop globally, and they tend to be more serious under extreme temperatures and drought climate changes. Currently, regulatory dynamics during plant development and in response to virus infection at the plant cell level remain largely unknown. In this study, single-cell RNA sequencing on 23 226 individual cells from healthy and tomato chlorosis virus-infected leaves was established. The specific expression and epigenetic landscape of each cell type during the viral infection stage were depicted. Notably, the mesophyll cells showed a rapid function transition in virus-infected leaves, which is consistent with the pathological changes such as thinner leaves and decreased chloroplast lamella in virus-infected samples. Interestingly, the F-box protein SKIP2 was identified to play a pivotal role in chlorophyll maintenance during virus infection in tomato plants. Knockout of the SlSKIP2 showed a greener leaf state before and after virus infection. Moreover, we further demonstrated that SlSKIP2 was located in the cytomembrane and nucleus and directly regulated by ERF4. In conclusion, with detailed insights into the plant responses to viral infections at the cellular level, our study provides a genetic framework and gene reference in plant-virus interaction and breeding in the future research.

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.

Microinjection of the CRISPR/Cas9 editing system through the germ pore of a wheat microspore induces mutations in the target Ms2 gene

BACKGROUND

Microinjection is a direct procedure for delivering various compounds via micropipette into individual cells. Combined with the CRISPR/Cas9 editing technology, it has been used to produce genetically engineered animal cells. However, genetic micromanipulation of intact plant cells has been a relatively unexplored area of research, partly due to the cytological characteristics of these cells. This study aimed to gain insight into the genetic micromanipulation of wheat microspores using microinjection procedures combined with the CRISPR/Cas9 editing system targeting the Ms2 gene.

METHODS AND RESULTS

Microspores were first reprogrammed by starvation and heat shock treatment to make them structurally suitable for microinjection. The large central vacuole was fragmented and the nucleus with cytoplasm was positioned in the center of the cell. This step and an additional maltose gradient provided an adequate source of intact single cells in the three wheat genotypes. The microcapillary was inserted into the cell through the germ pore to deliver a working solution with a fluorescent marker. This procedure was much more efficient and less harmful to the microspore than inserting the microcapillary through the cell wall. The CRISPR/Cas9 binary vectors injected into reprogrammed microspores induced mutations in the target Ms2 gene with deletions ranging from 1 to 16 bp.

CONCLUSIONS

This is the first report of successful genome editing in an intact microspore/wheat cell using the microinjection technique and the CRISPR/Cas9 editing system. The study presented offers a range of molecular and cellular biology tools that can aid in genetic micromanipulation and single-cell analysis.

Recent advances in plant translational genomics for crop improvement

The growing population, climate change, and limited agricultural resources put enormous pressure on agricultural systems. A plateau in crop yields is occurring and extreme weather events and urbanization threaten the livelihood of farmers. It is imperative that immediate attention is paid to addressing the increasing food demand, ensuring resilience against emerging threats, and meeting the demand for more nutritious, safer food. Under uncertain conditions, it is essential to expand genetic diversity and discover novel crop varieties or variations to develop higher and more stable yields. Genomics plays a significant role in developing abundant and nutrient-dense food crops. An alternative to traditional breeding approach, translational genomics is able to improve breeding programs in a more efficient and precise manner by translating genomic concepts into practical tools. Crop breeding based on genomics offers potential solutions to overcome the limitations of conventional breeding methods, including improved crop varieties that provide more nutritional value and are protected from biotic and abiotic stresses. Genetic markers, such as SNPs and ESTs, contribute to the discovery of QTLs controlling agronomic traits and stress tolerance. In order to meet the growing demand for food, there is a need to incorporate QTLs into breeding programs using marker-assisted selection/breeding and transgenic technologies. This chapter primarily focuses on the recent advances that are made in translational genomics for crop improvement and various omics techniques including transcriptomics, metagenomics, pangenomics, single cell omics etc. Numerous genome editing techniques including CRISPR Cas technology and their applications in crop improvement had been discussed.

Introducing single cell stereo-sequencing technology to transform the plant transcriptome landscape

Single cell RNA-sequencing (scRNA-seq) advancements have helped detect transcriptional heterogeneities in biological samples. However, scRNA-seq cannot currently provide high-resolution spatial transcriptome information or identify subcellular organs in biological samples. These limitations have led to the development of spatially enhanced-resolution omics-sequencing (Stereo-seq), which combines spatial information with single cell transcriptomics to address the challenges of scRNA-seq alone. In this review, we discuss the advantages of Stereo-seq technology. We anticipate that the application of such an integrated approach in plant research will advance our understanding of biological process in the plant transcriptomics era. We conclude with an outlook of how such integration will enhance crop improvement.

Single-nucleus transcriptomes reveal spatiotemporal symbiotic perception and early response in Medicago

Establishing legume-rhizobial symbiosis requires precise coordination of complex responses in a time- and cell type-specific manner. Encountering Rhizobium, rapid changes of gene expression levels in host plants occur in the first few hours, which prepare the plants to turn off defence and form a symbiotic relationship with the microbes. Here, we applied single-nucleus RNA sequencing to characterize the roots of Medicago truncatula at 30 min, 6 h and 24 h after nod factor treatment. We found drastic global gene expression reprogramming at 30 min in the epidermis and cortex and most of these changes were restored at 6 h. Moreover, plant defence response genes are activated at 30 min and subsequently suppressed at 6 h in non-meristem cells. Only in the cortical cells but not in other cell types, we found the flavonoid synthase genes required to recruit rhizobia are highly expressed 30 min after inoculation with nod factors. A gene module enriched for symbiotic nitrogen fixation genes showed that MtFER (MtFERONIA) and LYK3 (LysM domain receptor-like kinase 3) share similar responses to symbiotic signals. We further found that MtFER can be phosphorylated by LYK3 and it participates in rhizobial symbiosis. Our results expand our understanding of dynamic spatiotemporal symbiotic responses at the single-cell level.

Analysis of meristems and plant regeneration at single-cell resolution

Rapid development of high-throughput single-cell RNA sequencing (scRNA-seq) technologies offers exciting opportunities to reveal new and rare cell types, previously hidden cell states, and continuous developmental trajectories. In this review, we first illustrate the ways in which scRNA-seq enables researchers to distinguish between distinct plant cell populations, delineate cell cycle continuums, and infer continuous differentiation trajectories of diverse cell types in shoots, roots, and floral and vascular meristems with unprecedented resolution. We then highlight the emerging power of scRNA-seq to dissect cell heterogeneity in regenerating tissues and uncover the cellular basis of cell reprogramming and stem cell commitment during plant regeneration. We conclude by discussing related outstanding questions in the field.

Single-cell profiling of Arabidopsis leaves to Pseudomonas syringae infection

Plant response to pathogen infection varies within a leaf, yet this heterogeneity is not well resolved. We expose Arabidopsis to Pseudomonas syringae or mock treatment and profile >11,000 individual cells using single-cell RNA sequencing. Integrative analysis of cell populations from both treatments identifies distinct pathogen-responsive cell clusters exhibiting transcriptional responses ranging from immunity to susceptibility. Pseudotime analyses through pathogen infection reveals a continuum of disease progression from an immune to a susceptible state. Confocal imaging of promoter-reporter lines for transcripts enriched in immune cell clusters shows expression surrounding substomatal cavities colonized or in close proximity to bacterial colonies, suggesting that cells within immune clusters represent sites of early pathogen invasion. Susceptibility clusters exhibit more general localization and are highly induced at later stages of infection. Overall, our work shows cellular heterogeneity within an infected leaf and provides insight into plant differential response to infection at a single-cell level.

Evaluating and Validating Sunflower Reference Genes for Q-PCR Studies Under High Temperature Condition

Background

Q-PCR is the method of choice for PCR- based transcriptomics and validating microarray-based and RNA-seq results. Proper application of this technology requires proper normalization to correct as much as possible errors propagating during RNA extraction and cDNA synthesis.

Objectives

The investigation was performed to find stable reference genes in sunflower under shifting in ambient temperature.

Materials and Methods

Sequences of five well-known reference genes of Arabidopsis (Actin, Ubiquitin, Elongation factor-1, GAPDH, and SAND) and one well-known reference gene inhuman, Importin, were subjected to BLASTX against sunflower databases and the relevant genes were subjected to primer designing for q-PCR. Two sunflower inbred lines were cultivated at two dates so that anthesis occurred at nearly 30 °C and 40 °C (heat stress). The experiment was repeated for two years. Q-PCR was run on samples taken for two planting date separately at the beginning of anthesis for each genotype from leaf, taproots, receptacle base, immature and mature disc flowers and on pooled samples comprising of the tissues for each genotype, planting dates and also all tissues for both genotypes and both planting dates. Basic statistical properties of each candidate gene across all the samples were calculated. Furthermore, gene expression stability analysis was done for six candidate reference genes on Cq mean of two years using three independent algorithms, geNorm, Bestkeeper, and Refinder.

Results

Designed primers for Actin2, SAND, GAPDH, Ubiquitin, EF-1a, and Importin yielded a single peak in melting curve analysis indicating specificity of the PCR reaction. Basic statistical analysis showed that Actin2 and EF-1a had the highest and lowest expression levels across all the samples, respectively. Actin2 appeared to be the most stable reference gene across all the samples based on the three used algorithms. Pairwise variation analysis revealed that for samples taken under ambient temperature of 30 °C, Actin2, EF-1a, SAND and for those taken under ambient temperature of 40 °C, Actin2, EF-1a, Importin and SAND have to be used for normalization in q-PCR studies. Moreover, it is suggested that normalization to be based on Actin2, SAND and EF-1a for vegetative tissues and Actin2, EF-1a, SAND and Importin for reproductive tissues.

Conclusions

In the present research, proper reference genes for normalization of gene expression studies under heat stress conditions were introduced. Moreover, the presence of genotype-by- planting date interaction effects and tissue specific gene expression pattern on the behavior of the most three stable reference genes was indicated.

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.

Emerging trends in genomic and epigenomic regulation of plant specialised metabolism

Regulation of specialised metabolism genes is multilayered and complex, influenced by an array of genomic, epigenetic and epigenomic mechanisms. Here, we review the most recent knowledge in this field, drawing from discoveries in several plant species. Our aim is to improve understanding of how plant genome structure and function influence specialised metabolism. We also highlight key areas for future exploration. Gene regulatory mechanisms influencing specialised metabolism include gene duplication and neo-functionalization, conservation of operon-like clusters of specialised metabolism genes, local chromatin modifications, and the organisation of higher order chromatin structures within the nucleus. Genomic and epigenomic research to-date in the discipline have focused on a relatively small number of plant species, primarily at whole organ or tissue level. This is largely due to the technical demands of the experimental methods needed. However, a high degree of cell-type specificity of function exists in specialised metabolism, driven by similarly specific gene regulation. In this review we focus on the genomic characteristics of genes that are found in different types of clusters within the genome. We propose that acquisition of cell-resolution epigenomic datasets in emerging models, such as the glandular trichomes of Cannabis sativa, will yield important advances. Data such as chromatin accessibility and histone modification profiles can pinpoint which regulatory sequences are active in individual cell types and at specific times in development. These could provide fundamental biological insight as well as novel targets for genetic engineering and crop improvement.

Plant Proteome Dynamics

Proteins are intimately involved in executing and controlling virtually all cellular processes. To understand the molecular mechanisms that underlie plant phenotypes, it is essential to investigate protein expression, interactions, and modifications, to name a few. The proteome is highly dynamic in time and space, and a plethora of protein modifications, protein interactions, and network constellations are at play under specific conditions and developmental stages. Analysis of proteomes aims to characterize the entire protein complement of a particular cell type, tissue, or organism-a challenging task, given the dynamic nature of the proteome. Modern mass spectrometry-based proteomics technology can be used to address this complexity at a system-wide scale by the global identification and quantification of thousands of proteins. In this review, we present current methods and technologies employed in mass spectrometry-based proteomics and provide examples of dynamic changes in the plant proteome elucidated by proteomic approaches.

Machine Learning for Plant Stress Modeling: A Perspective towards Hormesis Management

Plant stress is one of the most significant factors affecting plant fitness and, consequently, food production. However, plant stress may also be profitable since it behaves hormetically; at low doses, it stimulates positive traits in crops, such as the synthesis of specialized metabolites and additional stress tolerance. The controlled exposure of crops to low doses of stressors is therefore called hormesis management, and it is a promising method to increase crop productivity and quality. Nevertheless, hormesis management has severe limitations derived from the complexity of plant physiological responses to stress. Many technological advances assist plant stress science in overcoming such limitations, which results in extensive datasets originating from the multiple layers of the plant defensive response. For that reason, artificial intelligence tools, particularly Machine Learning (ML) and Deep Learning (DL), have become crucial for processing and interpreting data to accurately model plant stress responses such as genomic variation, gene and protein expression, and metabolite biosynthesis. In this review, we discuss the most recent ML and DL applications in plant stress science, focusing on their potential for improving the development of hormesis management protocols.

Single-cell RNA-sequencing of Nicotiana attenuata corolla cells reveals the biosynthetic pathway of a floral scent

High-throughput single-cell RNA sequencing (scRNA-Seq) identifies distinct cell populations based on cell-to-cell heterogeneity in gene expression. By examining the distribution of the density of gene expression profiles, we can observe the metabolic features of each cell population. Here, we employ the scRNA-Seq technique to reveal the entire biosynthetic pathway of a flower volatile. The corolla of the wild tobacco Nicotiana attenuata emits a bouquet of scents that are composed mainly of benzylacetone (BA). Protoplasts from the N. attenuata corolla limbs and throat cups were isolated at three different time points, and the transcript levels of > 16 000 genes were analyzed in 3756 single cells. We performed unsupervised clustering analysis to determine which cell clusters were involved in BA biosynthesis. The biosynthetic pathway of BA was uncovered by analyzing gene co-expression in scRNA-Seq datasets and by silencing candidate genes in the corolla. In conclusion, the high-resolution spatiotemporal atlas of gene expression provided by scRNA-Seq reveals the molecular features underlying cell-type-specific metabolism in a plant.

To the proteome and beyond: advances in single-cell omics profiling for plant systems

Recent advances in single-cell proteomics for animal systems could be adapted for plants to increase our understanding of plant development, response to stimuli, and cell-to-cell signaling.

Cis-regulatory sequences in plants: Their importance, discovery, and future challenges

The identification and characterization of cis-regulatory DNA sequences and how they function to coordinate responses to developmental and environmental cues is of paramount importance to plant biology. Key to these regulatory processes are cis-regulatory modules (CRMs), which include enhancers and silencers. Despite the extraordinary advances in high-quality sequence assemblies and genome annotations, the identification and understanding of CRMs, and how they regulate gene expression, lag significantly behind. This is especially true for their distinguishing characteristics and activity states. Here, we review the current knowledge on CRMs and breakthrough technologies enabling identification, characterization, and validation of CRMs; we compare the genomic distributions of CRMs with respect to their target genes between different plant species, and discuss the role of transposable elements harboring CRMs in the evolution of gene expression. This is an exciting time to study cis-regulomes in plants; however, significant existing challenges need to be overcome to fully understand and appreciate the role of CRMs in plant biology and in crop improvement.

Network organization of the plant immune system: from pathogen perception to robust defense induction

The plant immune system has been explored essentially through the study of qualitative resistance, a simple form of immunity, and from a reductionist point of view. The recent identification of genes conferring quantitative disease resistance revealed a large array of functions, suggesting more complex mechanisms. In addition, thanks to the advent of high-throughput analyses and system approaches, our view of the immune system has become more integrative, revealing that plant immunity should rather be seen as a distributed and highly connected molecular network including diverse functions to optimize expression of plant defenses to pathogens. Here, we review the recent progress made to understand the network complexity of regulatory pathways leading to plant immunity, from pathogen perception, through signaling pathways and finally to immune responses. We also analyze the topological organization of these networks and their emergent properties, crucial to predict novel immune functions and test them experimentally. Finally, we report how these networks might be regulated by environmental clues. Although system approaches remain extremely scarce in this area of research, a growing body of evidence indicates that the plant response to combined biotic and abiotic stresses cannot be inferred from responses to individual stresses. A view of possible research avenues in this nascent biology domain is finally proposed.

Three-in-one method for high throughput plant multi-omics

Multi-omics has gained momentum over the past few years especially in plant single cell-type analysis as they aim to understand cellular molecular networks across different levels of genetic information flow. For multi-omics sample preparation, molecular extractions performed non-simultaneously create rooms for variation, inaccurate data, waste of limited samples, resources and labor. Here we optimized a protocol for 3-in-1 simultaneous extraction of RNA, metabolites, and proteins from the same single cell-type sample. We adapted a commercially available RNA kit with a few modifications to obtain high quality starting materials for sequencing and LC-MS/MS-based metabolomics and proteomics. RNAs are bound to the column, metabolites were extracted in a polar solvent and proteins are precipitated using acetone. This creates an all-in-one workflow using a standard RNA kit. Little training is required to carry out this protocol as it is simple and easy to use. It may be used with a wide range of plant species and different amounts of starting materials, including single cells.

Current Proteomic and Metabolomic Knowledge of Zygotic and Somatic Embryogenesis in Plants

Embryogenesis is the primary developmental program in plants. The mechanisms that underlie the regulation of embryogenesis are an essential research subject given its potential contribution to mass in vitro propagation of profitable plant species. Somatic embryogenesis (SE) refers to the use of in vitro techniques to mimic the sexual reproduction program known as zygotic embryogenesis (ZE). In this review, we synthesize the current state of research on proteomic and metabolomic studies of SE and ZE in angiosperms (monocots and dicots) and gymnosperms. The most striking finding was the small number of studies addressing ZE. Meanwhile, the research effort focused on SE has been substantial but disjointed. Together, these research gaps may explain why the embryogenic induction stage and the maturation of the somatic embryo continue to be bottlenecks for efficient and large-scale regeneration of plants. Comprehensive and integrative studies of both SE and ZE are needed to provide the molecular foundation of plant embryogenesis, information which is needed to rationally guide experimental strategies to solve SE drawbacks in each species.

Single-cell-type transcriptomic analysis reveals distinct gene expression profiles in wheat guard cells in response to abscisic acid

Stomatal closure, driven by shrinking guard cells in response to the accumulation of abscisic acid (ABA) under drought stress, has a great impact on plant growth and environmental acclimation. However, the molecular regulatory mechanism underlying the turgor alteration of guard cells remains elusive, especially in cereal grasses. Here, we develop a modified enzyme digestion-based approach for the isolation of wheat (Triticum aestivum L.) guard cells. With this approach, we can remove mesophyll, pavement cells and subsidiary cells successively from the epidermis of the trichomeless coleoptile in wheat and preserve guard cells on the cuticle layers in an intact and physiologically active conditions. Using a robust single-cell-type RNA sequencing analysis, we discovered 9829 differentially expressed genes (DEGs) as significantly up- or down-regulated in guard cells in response to ABA treatment. Transcriptome analysis revealed a large percent of DEGs encoding multiple phytohormone signalling pathways, transporters, calcium signalling components, protein kinases and other ABA signalling-related proteins, which are primarily involved in key signalling pathways in ABA-regulated stomatal control and stress response. Our findings provide valuable resource for investigating the transcriptional regulatory mechanism underlying wheat guard cells in response to ABA.

Vision, challenges and opportunities for a Plant Cell Atlas

With growing populations and pressing environmental problems, future economies will be increasingly plant-based. Now is the time to reimagine plant science as a critical component of fundamental science, agriculture, environmental stewardship, energy, technology and healthcare. This effort requires a conceptual and technological framework to identify and map all cell types, and to comprehensively annotate the localization and organization of molecules at cellular and tissue levels. This framework, called the Plant Cell Atlas (PCA), will be critical for understanding and engineering plant development, physiology and environmental responses. A workshop was convened to discuss the purpose and utility of such an initiative, resulting in a roadmap that acknowledges the current knowledge gaps and technical challenges, and underscores how the PCA initiative can help to overcome them.

Systems biology for crop improvement

In recent years, generation of large-scale data from genome, transcriptome, proteome, metabolome, epigenome, and others, has become routine in several plant species. Most of these datasets in different crop species, however, were studied independently and as a result, full insight could not be gained on the molecular basis of complex traits and biological networks. A systems biology approach involving integration of multiple omics data, modeling, and prediction of the cellular functions is required to understand the flow of biological information that underlies complex traits. In this context, systems biology with multiomics data integration is crucial and allows a holistic understanding of the dynamic system with the different levels of biological organization interacting with external environment for a phenotypic expression. Here, we present recent progress made in the area of various omics studies-integrative and systems biology approaches with a special focus on application to crop improvement. We have also discussed the challenges and opportunities in multiomics data integration, modeling, and understanding of the biology of complex traits underpinning yield and stress tolerance in major cereals and legumes.

Cell-Type-Specific Proteomics Analysis of a Small Number of Plant Cells by Integrating Laser Capture Microdissection with a Nanodroplet Sample Processing Platform

Plant organs and tissues contain multiple cell types, which are well organized in 3-dimensional structure to efficiently perform physiological functions such as homeostasis and response to environmental perturbation and pathogen infection. It is critically important to perform molecular measurements at the cell-type-specific level to discover mechanisms and unique features of cell populations that govern differentiation and respond to external perturbations. Although mass spectrometry-based proteomics has been demonstrated as an enabling discovery tool for studying plant physiology, conventional approaches require millions of cells to generate robust biological conclusions. Such requirements mask the cell-to-cell heterogeneities and limit the comprehensive profiling of plant proteins at spatially resolved and cell-type-specific resolutions. This article describes a recently developed proteomics workflow for studying a small number of plant cells by integrating laser capture microdissection, microfluidic nanodroplet-based sample preparation, and ultrasensitive liquid chromatography-mass spectrometry. Using poplar as a model tree species, we provide detailed protocols, including plant leaf and root tissue harvest, sample preparation, cryosectioning, laser microdissection, protein digestion, mass spectrometry measurement, and data analysis. We show that the workflow enables the precise identification and quantification of thousands of proteins from hundreds of isolated plant root and leaf cells. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Plant tissue fixation and embedding Support Protocol 1: Preparation of 2.5% CMC solution Support Protocol 2: Slow freezing of CMC blocks to avoid crack development in the block Basic Protocol 2: Preparation of cryosections Alternate Protocol: Using a vacuum manifold to dehydrate the cryosection slides (primarily for root tissues) Basic Protocol 3: Laser capture microdissection of specific types of plant cells Basic Protocol 4: Nanodroplet-based sample preparation for ultrasensitive proteomic analysis Support Protocol 3: Fabrication of nanowell chips Basic Protocol 5: Liquid chromatography and mass spectrometry.

A Sight on Single-Cell Transcriptomics in Plants Through the Prism of Cell-Based Computational Modeling Approaches: Benefits and Challenges for Data Analysis

Single-cell technology is a relatively new and promising way to obtain high-resolution transcriptomic data mostly used for animals during the last decade. However, several scientific groups developed and applied the protocols for some plant tissues. Together with deeply-developed cell-resolution imaging techniques, this achievement opens up new horizons for studying the complex mechanisms of plant tissue architecture formation. While the opportunities for integrating data from transcriptomic to morphogenetic levels in a unified system still present several difficulties, plant tissues have some additional peculiarities. One of the plants' features is that cell-to-cell communication topology through plasmodesmata forms during tissue growth and morphogenesis and results in mutual regulation of expression between neighboring cells affecting internal processes and cell domain development. Undoubtedly, we must take this fact into account when analyzing single-cell transcriptomic data. Cell-based computational modeling approaches successfully used in plant morphogenesis studies promise to be an efficient way to summarize such novel multiscale data. The inverse problem's solutions for these models computed on the real tissue templates can shed light on the restoration of individual cells' spatial localization in the initial plant organ-one of the most ambiguous and challenging stages in single-cell transcriptomic data analysis. This review summarizes new opportunities for advanced plant morphogenesis models, which become possible thanks to single-cell transcriptome data. Besides, we show the prospects of microscopy and cell-resolution imaging techniques to solve several spatial problems in single-cell transcriptomic data analysis and enhance the hybrid modeling framework opportunities.

Advancing crop genomics from lab to field

Crop genomics remains a key element in ensuring scientific progress to secure global food security. It has been two decades since the sequence of the first plant genome, that of Arabidopsis thaliana, was released, and soon after that the draft sequencing of the rice genome was completed. Since then, the genomes of more than 100 crops have been sequenced, plant genome research has expanded across multiple fronts and the next few years promise to bring further advances spurred by the advent of new technologies and approaches. We are likely to see continued innovations in crop genome sequencing, genetic mapping and the acquisition of multiple levels of biological data. There will be exciting opportunities to integrate genome-scale information across multiple scales of biological organization, leading to advances in our mechanistic understanding of crop biological processes, which will, in turn, provide greater impetus for translation of laboratory results to the field.

Membrane dynamics during individual and combined abiotic stresses in plants and tools to study the same

The plasma membrane (PM) is possibly the most diverse biological membrane of plant cells; it separates and guards the cell against its external environment. It has an extremely complex structure comprising a mosaic of lipids and proteins. The PM lipids are responsible for maintaining fluidity, permeability and integrity of the membrane and also influence the functioning of membrane proteins. However, the PM is the primary target of environmental stress, which affects its composition, conformation and properties, thereby disturbing the cellular homeostasis. Maintenance of integrity and fluidity of the PM is a prerequisite for ensuring the survival of plants during adverse environmental conditions. The ability of plants to remodel membrane lipid and protein composition plays a crucial role in adaptation towards varying abiotic environmental cues, including high or low temperature, drought, salinity and heavy metals stress. The dynamic changes in lipid composition affect the functioning of membrane transporters and ultimately regulate the physical properties of the membrane. Plant membrane-transport systems play a significant role in stress adaptation by cooperating with the membrane lipidome to maintain the membrane integrity under stressful conditions. The present review provides a holistic view of stress responses and adaptations in plants, especially the changes in the lipidome and proteome of PM under individual or combined abiotic stresses, which cause alterations in the activity of membrane transporters and modifies the fluidity of the PM. The tools to study the varying lipidome and proteome of the PM are also discussed.

Tissue-specific signatures of metabolites and proteins in asparagus roots and exudates

Comprehensive untargeted and targeted analysis of root exudate composition has advanced our understanding of rhizosphere processes. However, little is known about exudate spatial distribution and regulation. We studied the specific metabolite signatures of asparagus root exudates, root outer (epidermis and exodermis), and root inner tissues (cortex and vasculature). The greatest differences were found between exudates and root tissues. In total, 263 non-redundant metabolites were identified as significantly differentially abundant between the three root fractions, with the majority being enriched in the root exudate and/or outer tissue and annotated as 'lipids and lipid-like molecules' or 'phenylpropanoids and polyketides'. Spatial distribution was verified for three selected compounds using MALDI-TOF mass spectrometry imaging. Tissue-specific proteome analysis related root tissue-specific metabolite distributions and rhizodeposition with underlying biosynthetic pathways and transport mechanisms. The proteomes of root outer and inner tissues were spatially very distinct, in agreement with the fundamental differences between their functions and structures. According to KEGG pathway analysis, the outer tissue proteome was characterized by a high abundance of proteins related to 'lipid metabolism', 'biosynthesis of other secondary metabolites' and 'transport and catabolism', reflecting its main functions of providing a hydrophobic barrier, secreting secondary metabolites, and mediating water and nutrient uptake. Proteins more abundant in the inner tissue related to 'transcription', 'translation' and 'folding, sorting and degradation', in accord with the high activity of cortical and vasculature cell layers in growth- and development-related processes. In summary, asparagus root fractions accumulate specific metabolites. This expands our knowledge of tissue-specific plant cell function.

Plant multiscale networks: charting plant connectivity by multi-level analysis and imaging techniques

In multicellular and even single-celled organisms, individual components are interconnected at multiscale levels to produce enormously complex biological networks that help these systems maintain homeostasis for development and environmental adaptation. Systems biology studies initially adopted network analysis to explore how relationships between individual components give rise to complex biological processes. Network analysis has been applied to dissect the complex connectivity of mammalian brains across different scales in time and space in The Human Brain Project. In plant science, network analysis has similarly been applied to study the connectivity of plant components at the molecular, subcellular, cellular, organic, and organism levels. Analysis of these multiscale networks contributes to our understanding of how genotype determines phenotype. In this review, we summarized the theoretical framework of plant multiscale networks and introduced studies investigating plant networks by various experimental and computational modalities. We next discussed the currently available analytic methodologies and multi-level imaging techniques used to map multiscale networks in plants. Finally, we highlighted some of the technical challenges and key questions remaining to be addressed in this emerging field.

The Landscape of RNA-Protein Interactions in Plants: Approaches and Current Status

RNAs transmit information from DNA to encode proteins that perform all cellular processes and regulate gene expression in multiple ways. From the time of synthesis to degradation, RNA molecules are associated with proteins called RNA-binding proteins (RBPs). The RBPs play diverse roles in many aspects of gene expression including pre-mRNA processing and post-transcriptional and translational regulation. In the last decade, the application of modern techniques to identify RNA-protein interactions with individual proteins, RNAs, and the whole transcriptome has led to the discovery of a hidden landscape of these interactions in plants. Global approaches such as RNA interactome capture (RIC) to identify proteins that bind protein-coding transcripts have led to the identification of close to 2000 putative RBPs in plants. Interestingly, many of these were found to be metabolic enzymes with no known canonical RNA-binding domains. Here, we review the methods used to analyze RNA-protein interactions in plants thus far and highlight the understanding of plant RNA-protein interactions these techniques have provided us. We also review some recent protein-centric, RNA-centric, and global approaches developed with non-plant systems and discuss their potential application to plants. We also provide an overview of results from classical studies of RNA-protein interaction in plants and discuss the significance of the increasingly evident ubiquity of RNA-protein interactions for the study of gene regulation and RNA biology in plants.

Laser Microdissection of Specific Stem-Base Tissue Types from Olive Microcuttings for Isolation of High-Quality RNA

Simple Summary

Only a small portion of the stem cells participate in the process of adventitious root formation and the cells/tissues types involved in this process is species-dependent. In olive, it is still unclear which type of cells acquire competence for rooting. Regardless, the entire stem nodal segment (containing a mixture of distinct cell types) continues to be used in studies related to the molecular mechanisms underlying this process. Laser microdissection (LM) technology has been applied to isolate specific tissue and cell types. However, it is difficult to find a standard LM protocol suitable for all plant species and cell types and, thus, LM procedures must be developed and optimized for each particular tissue. In this study, we aimed to evaluate the efficiency of a LM protocol in olive microcuttings stem-base samples. This work presents a simple, rapid and efficient LM procedure for harvesting specific tissue types used for further high-quality RNA isolation. This will encourage future cell type-specific transcriptomic studies, contributing at deciphering rooting-competent cells in olive stems and to better understand the molecular mechanisms underlying the process of adventitious root formation.

Abstract

Higher plants are composed of different tissue and cell types. Distinct cells host different biochemical and physiological processes which is reflected in differences in gene expression profiles, protein and metabolite levels. When omics are to be carried out, the information provided by a specific cell type can be diluted and/or masked when using a mixture of distinct cells. Thus, studies performed at the cell- and tissue-type level are gaining increasing interest. Laser microdissection (LM) technology has been used to isolate specific tissue and cell types. However, this technology faces some challenges depending on the plant species and tissue type under analysis. Here, we show for the first time a LM protocol that proved to be efficient for harvesting specific tissue types (phloem, cortex and epidermis) from olive stem nodal segments and obtaining RNA of high quality. This is important for future transcriptomic studies to identify rooting-competent cells. Here, nodal segments were flash-frozen in liquid nitrogen-cooled isopentane and cryosectioned. Albeit the lack of any fixatives used to preserve samples’ anatomy, cryosectioned sections showed tissues with high morphological integrity which was comparable with that obtained with the paraffin-embedding method. Cells from the phloem, cortex and epidermis could be easily distinguished and efficiently harvested by LM. Total RNA isolated from these tissues exhibited high quality with RNA Quality Numbers (determined by a Fragment Analyzer System) ranging between 8.1 and 9.9. This work presents a simple, rapid and efficient LM procedure for harvesting specific tissue types of olive stems and obtaining high-quality RNA.

Developmental genetics of maize vegetative shoot architecture

More than 1.1 billion tonnes of maize grain were harvested across 197 million hectares in 2019 (FAOSTAT 2020). The vast global productivity of maize is largely driven by denser planting practices, higher yield potential per area of land, and increased yield potential per plant. Shoot architecture, the three-dimensional structural arrangement of the above-ground plant body, is critical to maize grain yield and biomass. Structure of the shoot is integral to all aspects of modern agronomic practices. Here, the developmental genetics of the maize vegetative shoot is reviewed. Plant architecture is ultimately determined by meristem activity, developmental patterning, and growth. The following topics are discussed: shoot apical meristem, leaf architecture, axillary meristem and shoot branching, and intercalary meristem and stem activity. Where possible, classical and current studies in maize developmental genetics, as well as recent advances leveraged by "-omics" analyses, are highlighted within these sections.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01208-1.

DIscBIO: A User-Friendly Pipeline for Biomarker Discovery in Single-Cell Transcriptomics

The growing attention toward the benefits of single-cell RNA sequencing (scRNA-seq) is leading to a myriad of computational packages for the analysis of different aspects of scRNA-seq data. For researchers without advanced programing skills, it is very challenging to combine several packages in order to perform the desired analysis in a simple and reproducible way. Here we present DIscBIO, an open-source, multi-algorithmic pipeline for easy, efficient and reproducible analysis of cellular sub-populations at the transcriptomic level. The pipeline integrates multiple scRNA-seq packages and allows biomarker discovery with decision trees and gene enrichment analysis in a network context using single-cell sequencing read counts through clustering and differential analysis. DIscBIO is freely available as an R package. It can be run either in command-line mode or through a user-friendly computational pipeline using Jupyter notebooks. We showcase all pipeline features using two scRNA-seq datasets. The first dataset consists of circulating tumor cells from patients with breast cancer. The second one is a cell cycle regulation dataset in myxoid liposarcoma. All analyses are available as notebooks that integrate in a sequential narrative R code with explanatory text and output data and images. R users can use the notebooks to understand the different steps of the pipeline and will guide them to explore their scRNA-seq data. We also provide a cloud version using Binder that allows the execution of the pipeline without the need of downloading R, Jupyter or any of the packages used by the pipeline. The cloud version can serve as a tutorial for training purposes, especially for those that are not R users or have limited programing skills. However, in order to do meaningful scRNA-seq analyses, all users will need to understand the implemented methods and their possible options and limitations.

Single-Cell Transcriptome Analysis in Plants: Advances and Challenges

The rapid and enthusiastic adoption of single-cell RNA sequencing (scRNA-seq) has demonstrated that this technology is far more than just another way to perform transcriptome analysis. It is not an exaggeration to say that the advent of scRNA-seq is revolutionizing the details of whole-transcriptome snapshots from a tissue to a cell. With this disruptive technology, it is now possible to mine heterogeneity between tissue types and within cells like never before. This enables more rapid identification of rare and novel cell types, simultaneous characterization of multiple different cell types and states, more accurate and integrated understanding of their roles in life processes, and more. However, we are only at the beginning of unlocking the full potential of scRNA-seq applications. This is particularly true for plant sciences, where single-cell transcriptome profiling is in its early stage and has many exciting challenges to overcome. In this review, we compare and evaluate recent pioneering studies using the Arabidopsis root model, which has established new paradigms for scRNA-seq studies in plants. We also explore several new and promising single-cell analysis tools that are available to those wishing to study plant development and physiology at unprecedented resolution and scale. In addition, we propose some future directions on the use of scRNA-seq technology to tackle some of the critical challenges in plant research and breeding.

Decoding Heavy Metal Stress Signalling in Plants: Towards Improved Food Security and Safety

The mining of heavy metals from the environment leads to an increase in soil pollution, leading to the uptake of heavy metals into plant tissue. The build-up of toxic metals in plant cells often leads to cellular damage and senescence. Therefore, it is of utmost importance to produce plants with improved tolerance to heavy metals for food security, as well as to limit heavy metal uptake for improved food safety purposes. To achieve this goal, our understanding of the signaling mechanisms which regulate toxic heavy metal uptake and tolerance in plants requires extensive improvement. In this review, we summarize recent literature and data on heavy metal toxicity (oral reference doses) and the impact of the metals on food safety and food security. Furthermore, we discuss some of the key events (reception, transduction, and response) in the heavy metal signaling cascades in the cell wall, plasma membrane, and cytoplasm. Our future perspectives provide an outlook of the exciting advances that will shape the plant heavy metal signaling field in the near future.

Expression Partitioning of Duplicate Genes at Single Cell Resolution in Arabidopsis Roots

Gene duplication is a key evolutionary phenomenon, prevalent in all organisms but particularly so in plants, where whole genome duplication (WGD; polyploidy) is a major force in genome evolution. Much effort has been expended in attempting to understand the evolution of duplicate genes, addressing such questions as why some paralog pairs rapidly return to single copy status whereas, in other pairs, both paralogs are retained and may diverge in expression pattern or function. The effect of a gene - its site of expression and thus the initial locus of its function - occurs at the level of a cell comprising a single cell type at a given state of the cell's development. Using Arabidopsis thaliana single cell transcriptomic data we categorized patterns of expression for 11,470 duplicate gene pairs across 36 cell clusters comprising nine cell types and their developmental states. Among these 11,470 pairs, 10,187 (88.8%) had at least one copy expressed in at least one of the 36 cell clusters. Pairs produced by WGD more often had both paralogs expressed in root cells than did pairs produced by small scale duplications. Three quarters of gene pairs expressed in the 36 cell clusters (7,608/10,187) showed extreme expression bias in at least one cluster, including 352 cases of reciprocal bias, a pattern consistent with expression subfunctionalization. More than twice as many pairs showed reciprocal expression bias between cell states than between cell types or between roots and leaves. A group of 33 gene pairs with reciprocal expression bias showed evidence of concerted divergence of gene networks in stele vs. epidermis. Pairs with both paralogs expressed without bias were less likely to have paralogs with divergent mutant phenotypes; such bias-free pairs showed evidence of preservation by maintenance of dosage balance. Overall, we found considerable evidence of shifts in gene expression following duplication, including in >80% of pairs encoding 7,653 genes expressed ubiquitously in all root cell types and states for which we inferred the polarity of change.

Single-Cell Genomics and Epigenomics: Technologies and Applications in Plants

The development of genomics and epigenomics has allowed rapid advances in our understanding of plant biology. However, conventional bulk analysis dilutes cell-specific information by providing only average information, thereby limiting the resolution of genomic and functional genomic studies. Recent advances in single-cell sequencing technology concerning genomics and epigenomics open new avenues to dissect cell heterogeneity in multiple biological processes. Recent applications of these approaches to plants have provided exciting insights into diverse biological questions. We highlight the methodologies underlying the current techniques of single-cell genomics and epigenomics before covering their recent applications, potential significance, and future perspectives in plant biology.

Does Gene Expression Noise Play a Functional Role in Plants?

Gene expression in individual cells can be surprisingly noisy. In unicellular organisms this noise can be functional; for example, by allowing a subfraction of the population to prepare for environmental stress. The role of gene expression noise in multicellular organisms has, however, remained unclear. In this review, we discuss how new techniques are revealing an unexpected level of variability in gene expression between and within genetically identical plants. We describe recent progress as well as speculate on the function of transcriptional noise as a mechanism for generating functional phenotypic diversity in plants.

Multi-level gene regulatory network models to understand complex mechanisms underlying plant development

Patterning in plant development is the emergent outcome of the feedback-based interplay between tissue-coupled intracellular regulatory networks and physicochemical fields. This interplay gives rise to dynamics that evolve on a wide spectrum of spatiotemporal scales. This imposes important challenges for computational approaches to model the dynamics of plant development. These challenges are being tackled in recent times by computational and mathematical advances that have made progress in the modelling of regulatory networks, as well as in approaches to couple the latter to physicochemical fields. Efforts in this direction are fundamental to identify the dynamical constraints that emerge from non-cellular autonomous activity in cell-fate decisions and patterning, and requires an understanding of how multi-level and multi-scale processes are coupled. Here, we discuss the use of multi-level modeling and simulation tools for the study of multicellular systems, with emphasis on plants. As illustrative examples, we discuss recent works elucidating the mechanisms that underlie patterning in the root meristem of Arabidopsis thaliana, and in plant responses to environmental conditions.

Demystifying biotrophs: FISHing for mRNAs to decipher plant and algal pathogen-host interaction at the single cell level

Plant-pathogen interactions follow spatial and temporal developmental dynamics where gene expression in pathogen and host undergo crucial changes. Therefore, it is of great interest to detect, quantify and localise where and when key genes are active to understand these processes. Many pathosystems are not accessible for genetic amendments or other spatially-resolved gene expression monitoring methods. Here, we adapt single molecule FISH techniques to demonstrate the presence and activity of mRNAs at the single-cell level using phytomyxids in their plant and algal host in lab and field material. This allowed us to monitor and quantify the expression of genes from the clubroot pathogen Plasmodiophora brassicae, several species of its Brassica hosts, and of several brown algae, including the genome model Ectocarpus siliculosus, infected with the phytomyxid Maullinia ectocarpii. We show that mRNAs are localised along a spatiotemporal gradient, thus providing a proof-of-concept of the usefulness of single-molecule FISH to increase knowledge about the interactions between plants, algae and phytomyxids. The methods used are easily applicable to any interaction between microbes and their algal or plant host, and have therefore the potential to rapidly increase our understanding of key, spatially- and temporally-resolved processes underpinning complex plant-microbe interactions.

Impact of genome duplication on secondary metabolite composition in non-cultivated species: a systematic meta-analysis

BACKGROUND AND AIMS

Whole-genome duplication is known to influence ecological interactions and plant physiology; however, despite abundant case studies, much is still unknown about the typical impact of genome duplication on plant secondary metabolites (PSMs). In this study, we assessed the impact of polyploidy events on PSM characteristics in non-cultivated plants.

METHODS

We conducted a systematic review and meta-analysis to compare composition and concentration of PSMs among closely related plant species or species complexes differing in ploidy level.

KEY RESULTS

We assessed 53 studies that focus on PSMs among multiple cytotypes, of which only 14 studies compared concentration quantitatively among cytotypes. We found that whole-genome duplication can have a significant effect on PSM concentration; however, these effects are highly inconsistent.

CONCLUSION

Overall, there was no consistent effect of whole-genome duplication on PSM concentrations or profiles.

Single-cell RNA-seq analysis reveals ploidy-dependent and cell-specific transcriptome changes in Arabidopsis female gametophytes

BACKGROUND

Polyploidy provides new genetic material that facilitates evolutionary novelty, species adaptation, and crop domestication. Polyploidy often leads to an increase in cell or organism size, which may affect transcript abundance or transcriptome size, but the relationship between polyploidy and transcriptome changes remains poorly understood. Plant cells often undergo endoreduplication, confounding the polyploid effect.

RESULTS

To mitigate these effects, we select female gametic cells that are developmentally stable and void of endoreduplication. Using single-cell RNA sequencing (scRNA-seq) in Arabidopsis thaliana tetraploid lines and isogenic diploids, we show that transcriptome abundance doubles in the egg cell and increases approximately 1.6-fold in the central cell, consistent with cell size changes. In the central cell of tetraploid plants, DEMETER (DME) is upregulated, which can activate PRC2 family members FIS2 and MEA, and may suppress the expression of other genes. Upregulation of cell size regulators in tetraploids, including TOR and OSR2, may increase the size of reproductive cells. In diploids, the order of transcriptome abundance is central cell, synergid cell, and egg cell, consistent with their cell size variation. Remarkably, we uncover new sets of female gametophytic cell-specific transcripts with predicted biological roles; the most abundant transcripts encode families of cysteine-rich peptides, implying roles in cell-cell recognition during double fertilization.

CONCLUSIONS

Transcriptome in single cells doubles in tetraploid plants compared to diploid, while the degree of change and relationship to the cell size depends on cell types. These scRNA-seq resources are free of cross-contamination and are uniquely valuable for advancing plant hybridization, reproductive biology, and polyploid genomics.

Biotechnological Perspectives of Omics and Genetic Engineering Methods in Alfalfa

For several decades, researchers are working to develop improved major crops with better adaptability and tolerance to environmental stresses. Forage legumes have been widely spread in the world due to their great ecological and economic values. Abiotic and biotic stresses are main factors limiting legume production, however, alfalfa (Medicago sativa L.) shows relatively high level of tolerance to drought and salt stress. Efforts focused on alfalfa improvements have led to the release of cultivars with new traits of agronomic importance such as high yield, better stress tolerance or forage quality. Alfalfa has very high nutritional value due to its efficient symbiotic association with nitrogen-fixing bacteria, while deep root system can help to prevent soil water loss in dry lands. The use of modern biotechnology tools is challenging in alfalfa since full genome, unlike to its close relative barrel medic (Medicago truncatula Gaertn.), was not released yet. Identification, isolation, and improvement of genes involved in abiotic or biotic stress response significantly contributed to the progress of our understanding how crop plants cope with these environmental challenges. In this review, we provide an overview of the progress that has been made in high-throughput sequencing, characterization of genes for abiotic or biotic stress tolerance, gene editing, as well as proteomic and metabolomics techniques bearing biotechnological potential for alfalfa improvement.