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Single-Cell Omics in Crop Plants: Opportunities and Challenges
CHAPTER 17
Single-Cell Omics in Crop Plants: Opportunities and Challenges Anu Kalia*, Sat Pal Sharma† *Electron Microscopy and Nanoscience Laboratory, Department of Soil Science, Punjab Agricultural University, Ludhiana, India † Department of Vegetable Science, College of Agriculture, Punjab Agricultural University, Ludhiana, India
ABSTRACT Omics studies in plants have helped in the molecular characterization of whole plants or their organs. However, these studies lack information on cellular behavior, cell-to-cell variations, and distinct molecular program(s) operational in individual cells. As an enormous variability exists owing to the type and developmental stage of plant cell/tissue(s), the multidimensionality and complexity of cellular responses in plants towards the environment and growth stages requires descaling to single-cell-type omics technologies to dissect the complex responses to obtain concrete information of components at the ultrastructural, subcellular, or organellar hierarchies of the genome, transcriptome, proteome, and metabolome pathways. Further, single-cell multiomics studies aiming at simultaneous extraction and analysis of different analyte biomolecules in a cell will help in validating the relative changes occurring in a cell to a specific event or elicitor. The integration of the four different omics data and development of an interactome having nodes and edges will then help in designing a comprehensive regulatory system operating in an individual cell. The near complete integrative information on the working and operations of emphatic plant biological systems will furnish us with the ingenuity to design climate-ready resilient crops to cope with the aberrant environmental stresses.
17.1
INTRODUCTION
Plant omics technologies were initiated as genomics studies, which led to development of other omics sciences in an effort to discern the functional dynamics and identification of specific roles of an m-RNA/protein or metabolite in a Single-Cell Omics. https://doi.org/10.1016/B978-0-12-817532-3.00020-7 © 2019 Elsevier Inc. All rights reserved.
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cascade of reaction events for a plant cell (Libault et al., 2017). This paved to almost simultaneous emergence of three different -omes, signifying three hierarchies of cell functioning, viz., transcriptomics, proteomics, and metabolomics. Plants exhibit enormous variability and plasticity at all the four levels of plant -omes (Schiefelbein, 2015) (Fig. 17.1). Likewise, different cells in the whole body of a plant exhibit synthesis of versatile yet complex organic compounds and/or molecules (both macro- and micromolecules) in a series of finely orchestrated events in response to a specific stimulus (Roberts et al., 2018). Therefore, the prediction of the possibility of the events that may occur
FIG. 17.1 The omics hierarchies: Tracing down the plant molecular phenotypic plasticity at four different levels of molecular hierarchy of the cell.
17.1
inside a cell cytoplasm (genomics) will be a reductionist approach (Horgan and Kenny, 2011). Obtaining the critical knowledge of events that may appear to happen (transcriptomics) followed by identification of the key proteinaceous macromolecules that have been responsible for these events or repercussions in a cell (proteomics) and, finally, synthesis of other micro /macromolecules indicating what has occurred in the cell (metabolomics) will help us define the functional relevance and will provide insights into the molecular aspects of the fundamental processes of a plant cell (Van Emon, 2016). Therefore, the omics technologies will allow for discovery of new gene(s) in wild races, elite cultivars, and other related/unrelated genotypes (gene mining) through specific markers, allocation of functional properties to unknown genes, and identification of gene(s) expression cascades and networks. Further, integration of all the omics data obtained at specific hierarchies, systems biology, will validate and complement these different sets of -ome data to provide a universal consolidated bioinformatics platform for plant breeders to discern plant plasticity through identification of uni- and/or multispectral responses to diverse abiotic and biotic alterations (Zhang et al., 2016). This will be critical for the development of novel hybrids and inbred lines of crop plants using gene pyramiding and editing approaches (Schrag et al., 2018). Thus, the whole-plant omics studies have enunciated our understanding of types of adaptation approaches utilized by plants to withstand/combat various abiotic and biotic stresses. These studies have the potential to assist crop breeders to identify and predict the consistency of transfer and performance of various agronomically important traits for development of novel cultivars or hybrids possessing improved yield and productivity under hostile or suboptimal soil, climatic, and other conditions. Moreover, these studies would also speed up the time duration of development of new cultivars or hybrids in a cost-effective manner.
17.1.1
What Are Single-Cell Omics Technologies?
The entire plant omics strategies have improved our understanding of the plant system, its development, and critical responses to environmental variations and stress conditions affecting the growth, development, and yield in plants; in particular, these aspects hold great significance for diverse types of crop plants. However, analysis of several tissue/cell types as a single sample can obscure the useful biological changes that may have occurred in specific individual cells (Fig. 17.2). Therefore, single-cell omics technologies (SCOTs) have been contributing to our know-how concerning the genotypic and phenotypic characteristics of an individual cell. The objectivity of SCOTs involves singularization of specific cells or cell types from a composite sample so as to overcome the heterogeneity issues related to bulk populations (Linnarsson and Teichmann, 2016). SCOTs have equipped plant researchers with adequate technical
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FIG. 17.2 The diversity of the single-cell types derived from vegetative and reproductive organs of above-ground biomass of a potato plant.
prowess to study the details of their molecular characteristics at mono-omics hierarchies in an integrated manner (Schiefelbein, 2015) at single-cell resolution. These studies maintain the individuality of the cell, thereby overriding the problems of cellular complexity, such as dilution of low-abundant biomolecules and masking of the unique biological response of an individual cell or
17.1
cell type in a heterogeneous sample, as per the Yule-Simpson index (Libault et al., 2017). Further, these techniques provide spatiotemporal information about the gene expression profile, and the extent and adequacy of formation of specific substances in an individual cell pertaining to its developmental stage (Nourbakhsh-Rey and Libault, 2016). Therefore, these studies can also be useful for elucidation of changes occurring at various omic hierarchies individually towards hostile abiotic stress conditions, such as nutrition deprivation (Yan et al., 2011; Menz et al., 2016), drought (Wu et al., 2017), temperature extremes, pH alterations, salinity, water-logging, and deteriorating biotic stresses including pest and pathogenic diseases at the single-cell level (Ahmad et al., 2016). Hence, SCOTs can unleash the unique molecular contributions of individual cells or cell types in response to environmental stress or other variables, which remains obscured if the heterogeneous cell population is utilized for analysis of the response. Under the portfolio of multiomics technologies, a combination of omics techniques can lead to capturing of multiple omes of an individual cell, resolving the complex variability of interaction networks among various omic levels, and their commensurate role in cellular functions (Chappell et al., 2018). The multiome analysis can further help in identification of relationships on associative analysis of the variabilities at each omics level (Kang et al., 2018).
17.1.2 Why Do We Need SCOTs for Plant Tissues? Complexities of Plant System Plant cells exhibit fairly high complexity, due to the occurrence of differentiated cells or cell types leading to formation of specialized plant tissues or organs. This cellular complexity demands identification and isolation of individual cells or specific cell types, such that the cell-omes characteristics can be dissected. In addition, the variabilities among individual omes and relative associations among different omic levels at single-cell resolution can be obtained. However, isolation of the specific individual cells must be performed in a manner such that the isolated cells remain amenable to downstream -ome protocols for accomplishing reproducible data. However, high noise makes it tricky, expensive, and difficult to get reproducible data (Fig. 17.3). The outer cell wall, composed of cellulose biopolymer matrix in plant cells, is quite a rigid structure, which poses a primary and technically challenging problem for isolation of individual cells. Thus, it is easier to collect only a few specialized cell types, such as leaf trichome cells, stomatal guard cells, and root hair cells (Libault et al., 2017). The practical relevance of discerning the individual cell contribution is to obtain improved high-resolution data to better assess the characteristics of the apical/axillary stem cells in plants. Moreover, it will also help in discerning the extent of cellular plasticity for the individual cell types, such that any local molecular alterations in response to changes in the internal/external
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FIG. 17.3 The fundamental problems of plant single-cell omics technologies.
cell environment can be visualized at single-cell resolution. Another fundamental complication of plant SCOTs is that of obtaining crisp and discrete data with high reproducibility. This is further complicated if simultaneously several -ome data sets are to be retrieved from a single set of test cell(s) or cell type.
17.2 SINGLE-CELL OMICS TECHNOLOGIES: STEPS AND TECHNIQUES The prerequisite step for performing plant-omics studies at the four molecular hierarchies begins with isolation of the single cells from the plant tissue samples. As discussed in Section 20.1.2, isolation of single plant cells is a tedious process that can be performed using simple dilution/micropipetting to advanced and high-throughput flow cytometry and laser-based capture/
17.2
Single-Cell Omics Technologies: Steps and Techniques
FIG. 17.4 Techniques for isolation of single-cell types from a composite tissue derived from a plant sample.
dissection techniques, which have already been utilized for isolation of single cells from animal tissues (Hodne and Weltzien, 2015; Efroni and Birnbaum, 2016; Valihrach et al., 2018) (Fig. 17.4). Plant cells require treatment with the cell-wall dissolving enzymes to obtain the protoplasts. These cells when isolated from composite samples can be purified by using an array of techniques, such as density gradient centrifugation (Lu et al., 2015), use of fluorescent (green fluorescent protein, GFP) or magnetic tags to sort cells in flow cytometer (FACS/FANS) or columns (MACS), and substrate tagging [biotinylated nuclear tagging (INTACT)] (Schmid et al., 2015; Libault et al., 2017). There are also set of techniques available now to isolate plant cells of specific types without any prior information about their molecular characteristics, termed laser-enabled or -assisted microdissection techniques. The lasers can be utilized to capture, dissect, and obtain specific cells or cell types in a variety of ways, such as optical,
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optoelectronic tweezers, or dissolution of undesirable cells by degradation using intense lasers (Valihrach et al., 2018). Once the cell population is obtained, the downstream processing must be performed for genomics, transcriptomics, proteomics, and metabolomics studies. The single-cell genomics studies reveal the genetic heterogeneity (involves characterization of chromosome structural aberrations and ploidy changes besides recombination in genome), cellular relationships among plant cells of different lineage or origin, evolutionary/diversity analysis, and mosaicism at the genetic level (Libault et al., 2017; Yuan et al., 2018). The genome-wide and newgeneration sequencing techniques that have been initially utilized on bulk cell populations are now being employed to resolve the genetic heterogeneity of individual cells in bulk populations in an unbiased and high-throughput manner (Kolodziejczyk et al., 2015). However, the single-cell transcriptomics involves elucidation of gene regulatory networks via estimation of spatiotemporal variations in gene expression in response to any internal/external stimuli, and the cellular developmental stage through use of single-cell qPCR and single-cell RNA sequencing techniques (scRNA-Seq) (Prakadan et al., 2017). The sc-transcriptomics studies can further discern the subcellular or organellar contributions in a single cell ( Jiang et al., 2017). The single-cell proteomics techniques can unmask the basic genetic heterogeneity among different cell types on the basis of the proteins synthesized in the cell, thereby providing the finely detailed characterization of the cell phenotypes. The fundamental techniques utilized for discerning the single-cell proteome include the two-dimensional gel electrophoresis matrix-assisted laser desorption ionization time-of-flight mass spectrometry (2D-GE-MALDI-TOF MS), electron spray ionization mass spectrometry (MS) or its variants, such as Probe/nanospray SI, tandem MS (MS/MS), liquid chromatography-tandem mass spectrometry (LC-MS/MS), and multidimensional protein identification technology (MudPIT). The spectrometry and MudPIT are the short-gun proteomics approaches that can provide useful qualitative information. Likewise, the relative and absolute quantitative data among different cell types can be obtained through use of isotope-coded affinity/isobaric tags for relative and absolute quantitation (iTRAQs) (Dai and Chen, 2012). The variations occurring at the preceding three omic hierarchies can be validated through identification and isolation of key metabolite(s) in terms of their presence and abundance at the single-cell level using techniques such as GC-MS, LC-ESI-MS, ultrahigh performance liquid chromatography-magnetic resonance (UPLC-MS), nano-high-performance liquid chromatography-magnetic resonance (HPLC-MS), cryogenic nuclear magnetic resonance (NMR), and other variants (Misra et al., 2014). Combined analysis of all -omes can provide a synthetic scenario such that the fundamental functionality and behavior of a specific single cell can be identified (Chappell et al., 2018).
17.3
Elucidation of the Complexity of Plant Responses
17.3 ELUCIDATION OF THE COMPLEXITY OF PLANT RESPONSES: APPLICATIONS OF SCOTs FOR CROP IMPROVEMENT Sections 17.1.1 and 20.1.2 demarcate the ostensible role of SCOTs in overriding the challenges of forward genetics. The sc-genomics studies have led to discovery of genes and their sequence variations in subcellular components of the cell and among different cell types. This information can be critical for plant breeders for development of novel molecular markers, as distinct molecular properties of the individual cells can be discerned by sc-genomics techniques. The gene expression profiling at single-cell resolution can elucidate the effect of altered genetic or environmental conditions on differential expression of specific genes (Table 17.1). These studies have created opportunities for identification and quantification of molecular characteristics with high sensitivity at single-cell resolution to better cognize gene function (Schiefelbein, 2015). Diverse abiotic stresses such as drought, water submergence, salt, heavy metal contamination, and temperature (high or low) negatively affect crop plants across the globe, culminating in plant damage and incurring moderate to high losses of yield, quality, and overall productivity. Abiotic stresschallenged crop plants exhibit stress tolerance and adaptation responses varying from biochemical, physiological, to metabolic, by switching on/off specific genes or sets of genes through intricate and complex signal transduction cascades and pathways to combat/subdue the negative impacts of exposure. The response of a single cell is critical considering the biotic or abiotic stress conditions. Chalkiness of the rice endosperm is a critical quality trait governed by temperature increase, a consequence of the global-warming scenario during the grain-filling stage of the rice. Single-cell on-site analysis studies have revealed enhancement in protein synthesis in endosperm cells in response to N-supply can avoid chalkiness of the grain, even under high temperature conditions (Wada et al., 2017). The biotic characteristics of the plants can either help or thwart their chances for survival. An sc-genomics study of the root microbiome involving endophytic bacteria inhabiting the root tissues of Populus helped in identification of potentially uncultured taxa (Utturkar et al., 2016). Such studies can be beneficial for elucidating the possibility for cultivation of these uncultured microbes, as well as their potential role in imparting growth and immunity to the host plant. Further, integrative single-cell multiomics can pinpoint novel metabolic genes, gene expression profiles, and pathways in crops, unearthing the lineage, course, and repercussions of crop domestication that have led to development of a specific cultivar or hybrid with improved yield and quality characteristics (Zhu et al., 2018).
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Table 17.1 Single-Cell Omics Studies Performed With Different Plant Cells Omics Hierarchy
Study/ Biomolecule(s) Studied
Key Findings
Reference
Dilution-based/flowsorting of single-cell single-chromosome sequencing/haplotyping
Plant developmental biology/DNA
• Identification of genetic mosaicisms, haplotypes, gene markers
Dolezˇel et al. (2014)
Fruit tissues (pericarp, septum, locular tissue, placenta, columella, and seeds)
Laser capture microdissection, RNA-Seq
Plant developmental biology/RNA
Shinozaki et al. (2018)
Arabidopsis
Root tip cells
scRNA-Seq
Plant physiology/ RNA
Solanum lycopersicum
Fruit cells and cell types
Plant physiology/ RNA
Cotton (Gossypium barbadense L. cv 3–79)
Cotton fiber cells
Laser microdissectiontranscriptome profiling, cryo-sectioning followed by laser microdissection and scRNA-Seq Total RNA-Seq and QRT-PCR
• Tomato ripening involves gene expression gradients that start in internal tissues radiating outward, and basipetally along a latitudinal axis • Spatial variations in the epigenetic control patterns during ripening • Regeneration of root follows the embryonic developmental stages • Complementary hormone domains guide the spatial information • Identification of differentially expressed genes among cell or tissue types
• Cotton fiber cells exhibited greater DNA methylation • Integrated multiomics study revealed • dynamic DNA methylation regulates lipid biosynthesis • spatiotemporal modulation of ROS during differentiation in fiber cells
Wang et al. (2016)
Crop/Plant
Cell Type/Cell Studied
Technique(s) Utilized
Cereal and other crops
Different cell types
Solanum lycopersicum cv M82
Genomics
Transcriptomics
Plant physiology/ DNA, RNA
Efroni et al. (2016)
Martin et al. (2016)
Table 17.1 Single-Cell Omics Studies Performed With Different Plant Cells—Continued Omics Hierarchy
Crop/Plant
Cell Type/Cell Studied
Technique(s) Utilized
Oryza sativa L. cv. Nipponbare
Rice egg, sperm, callus cells
Manual isolation, RNA extraction, cDNA preparation and Q-PCR
Solanum lycopersicum cv. Micro-Tom
Root-tip tissues
Arabidopsis thaliana
Leaf epidermal, vascular, and mesophyll cells
Oryza sativa L. cv. Nipponbare
Study/ Biomolecule(s) Studied
Key Findings
Reference
Plant developmental biology/RNA and proteins
• Preferential expression of specific and global genes expressed in gamete cells
Abiko et al. (2013)
Laser capture microdissection followed by nanoLC-MS/MS Meselect-based sorting of leaf cells, western blotting, affinity enrichment and mass spectrometry
Plant metal toxicity/Proteins of root epidermal and other cells Plant physiology/ Proteins (Ubiquitin-26S proteasome targets)
Zhu et al. (2016)
Rice egg, sperm, callus cells
SDS-PAGE followed by LC-MS/MS
Plant developmental biology/Proteins
• Varying effects of Al toxicity on various layers of root cells can be studied through sc-proteomics • Overall number and types of proteins vary in specific leaf tissues Ubiquitin-26S proteasome targets and functioning varies among different cell types • Preferential occurrence of specific proteins expressed in gamete cells
Brassica napus var. Global
Leaf guard cells
GC-MS, UPLC-MS and MRM HPLC-MS
Plant stress response/ Phytohormones
Geng et al. (2017)
Allium cepa
Epidermal single-cell of bulbs
Probe ESI-MS
Vicia faba
Water and wound-stressed single cells from leaf tissue
Nanospray IonizationTandem MS using stable isotope labelling followed by LC-MS/MS
Plant biochemistry/ Specialized metabolites, oligosaccharides Plant developmental biology/ Jasmonoylisoleucine and Abscisic acid hormones
• Low CO2 promotes increased stomatal opening controlled through multiple hormones • A complex cross-talk of various phytohormones mediated low CO2 response • Continuous monitoring of a live single-cell can be achieved by using specialized miniaturized probes • Stress-induced accumulation of ABA and JA-Ile in single cells
Proteomics
Svozil et al. (2015)
Abiko et al. (2013)
Metabolomics
Gong et al. (2014)
Shimizu et al. (2015)
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17.4
CONCLUSIONS AND FUTURE PROSPECTS
Single-cell omics technologies have definitely improved our understanding of individual cell contributions at the four -ome hierarchies. The SCOTs for the isolation, extraction, amplification, and analysis of the various biomolecules (DNA, RNA, proteins, and metabolites) are improving with new advances that have led to the collection of improved, unbiased, high-throughput, and highresolution data sets. However, presently the prime technological problems faced by SCOTs involve enhancing the accuracy and sensitivity, besides the overall throughput of the analytical systems (Libault et al., 2017). Novel cell-capture, isolation, and extraction techniques have to be identified and evaluated for collection of an ample number of uniform individual cells from tissues situated deeper than the epidermis of plant cells in thick samples (Efroni et al., 2015). Currently, the plant structural rigidity and complexity of tissue organization have constrained most of the single-cell omics studies to specialized epidermal cells such as leaf/stem trichomes, stomatal guard cells, root hairs, or certain male/female gamete cells (Schiefelbein, 2015; Schmid et al., 2015; Libault et al., 2017). Multiplexed extraction and quantification of the individual -ome information from a single-cell simultaneously is the other shortcoming that has to be addressed effectively for present-day single-cell plant omics studies. Further, integration of individual -ome information, single-cell multiomics strategies, can provide detailed spatiotemporally resolved data on complex and integrated network responses, such as senescence or aging involving the signal transduction communications among different plant cell types (Großkinsky et al., 2017) and other complex networked responses to various stress conditions (Barkla et al., 2016). Moreover, a combination of two or more kinds of -ome information will provide next-level data orthogonal to the primary -ome data individually, particularly suitable for identification of the transcriptome- and epigenomecontrolled traits in a cell (Kolodziejczyk and L€ onnberg, 2017).
Acknowledgments The authors graciously thank the Head, Department of Soil Science, Punjab Agricultural University, Ludhiana, Punjab for providing the necessary facilities for the research work.
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Single-Cell Omics in Crop Plants: Opportunities and Challenges Anu Kalia*, Sat Pal Sharma† *Electron Microscopy and Nanoscience Laboratory, Department of Soil Science, Punjab Agricultural University, Ludhiana, India † Department of Vegetable Science, College of Agriculture, Punjab Agricultural University, Ludhiana, India
ABSTRACT Omics studies in plants have helped in the molecular characterization of whole plants or their organs. However, these studies lack information on cellular behavior, cell-to-cell variations, and distinct molecular program(s) operational in individual cells. As an enormous variability exists owing to the type and developmental stage of plant cell/tissue(s), the multidimensionality and complexity of cellular responses in plants towards the environment and growth stages requires descaling to single-cell-type omics technologies to dissect the complex responses to obtain concrete information of components at the ultrastructural, subcellular, or organellar hierarchies of the genome, transcriptome, proteome, and metabolome pathways. Further, single-cell multiomics studies aiming at simultaneous extraction and analysis of different analyte biomolecules in a cell will help in validating the relative changes occurring in a cell to a specific event or elicitor. The integration of the four different omics data and development of an interactome having nodes and edges will then help in designing a comprehensive regulatory system operating in an individual cell. The near complete integrative information on the working and operations of emphatic plant biological systems will furnish us with the ingenuity to design climate-ready resilient crops to cope with the aberrant environmental stresses.
17.1
INTRODUCTION
Plant omics technologies were initiated as genomics studies, which led to development of other omics sciences in an effort to discern the functional dynamics and identification of specific roles of an m-RNA/protein or metabolite in a Single-Cell Omics. https://doi.org/10.1016/B978-0-12-817532-3.00020-7 © 2019 Elsevier Inc. All rights reserved.
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cascade of reaction events for a plant cell (Libault et al., 2017). This paved to almost simultaneous emergence of three different -omes, signifying three hierarchies of cell functioning, viz., transcriptomics, proteomics, and metabolomics. Plants exhibit enormous variability and plasticity at all the four levels of plant -omes (Schiefelbein, 2015) (Fig. 17.1). Likewise, different cells in the whole body of a plant exhibit synthesis of versatile yet complex organic compounds and/or molecules (both macro- and micromolecules) in a series of finely orchestrated events in response to a specific stimulus (Roberts et al., 2018). Therefore, the prediction of the possibility of the events that may occur
FIG. 17.1 The omics hierarchies: Tracing down the plant molecular phenotypic plasticity at four different levels of molecular hierarchy of the cell.
17.1
inside a cell cytoplasm (genomics) will be a reductionist approach (Horgan and Kenny, 2011). Obtaining the critical knowledge of events that may appear to happen (transcriptomics) followed by identification of the key proteinaceous macromolecules that have been responsible for these events or repercussions in a cell (proteomics) and, finally, synthesis of other micro /macromolecules indicating what has occurred in the cell (metabolomics) will help us define the functional relevance and will provide insights into the molecular aspects of the fundamental processes of a plant cell (Van Emon, 2016). Therefore, the omics technologies will allow for discovery of new gene(s) in wild races, elite cultivars, and other related/unrelated genotypes (gene mining) through specific markers, allocation of functional properties to unknown genes, and identification of gene(s) expression cascades and networks. Further, integration of all the omics data obtained at specific hierarchies, systems biology, will validate and complement these different sets of -ome data to provide a universal consolidated bioinformatics platform for plant breeders to discern plant plasticity through identification of uni- and/or multispectral responses to diverse abiotic and biotic alterations (Zhang et al., 2016). This will be critical for the development of novel hybrids and inbred lines of crop plants using gene pyramiding and editing approaches (Schrag et al., 2018). Thus, the whole-plant omics studies have enunciated our understanding of types of adaptation approaches utilized by plants to withstand/combat various abiotic and biotic stresses. These studies have the potential to assist crop breeders to identify and predict the consistency of transfer and performance of various agronomically important traits for development of novel cultivars or hybrids possessing improved yield and productivity under hostile or suboptimal soil, climatic, and other conditions. Moreover, these studies would also speed up the time duration of development of new cultivars or hybrids in a cost-effective manner.
17.1.1
What Are Single-Cell Omics Technologies?
The entire plant omics strategies have improved our understanding of the plant system, its development, and critical responses to environmental variations and stress conditions affecting the growth, development, and yield in plants; in particular, these aspects hold great significance for diverse types of crop plants. However, analysis of several tissue/cell types as a single sample can obscure the useful biological changes that may have occurred in specific individual cells (Fig. 17.2). Therefore, single-cell omics technologies (SCOTs) have been contributing to our know-how concerning the genotypic and phenotypic characteristics of an individual cell. The objectivity of SCOTs involves singularization of specific cells or cell types from a composite sample so as to overcome the heterogeneity issues related to bulk populations (Linnarsson and Teichmann, 2016). SCOTs have equipped plant researchers with adequate technical
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FIG. 17.2 The diversity of the single-cell types derived from vegetative and reproductive organs of above-ground biomass of a potato plant.
prowess to study the details of their molecular characteristics at mono-omics hierarchies in an integrated manner (Schiefelbein, 2015) at single-cell resolution. These studies maintain the individuality of the cell, thereby overriding the problems of cellular complexity, such as dilution of low-abundant biomolecules and masking of the unique biological response of an individual cell or
17.1
cell type in a heterogeneous sample, as per the Yule-Simpson index (Libault et al., 2017). Further, these techniques provide spatiotemporal information about the gene expression profile, and the extent and adequacy of formation of specific substances in an individual cell pertaining to its developmental stage (Nourbakhsh-Rey and Libault, 2016). Therefore, these studies can also be useful for elucidation of changes occurring at various omic hierarchies individually towards hostile abiotic stress conditions, such as nutrition deprivation (Yan et al., 2011; Menz et al., 2016), drought (Wu et al., 2017), temperature extremes, pH alterations, salinity, water-logging, and deteriorating biotic stresses including pest and pathogenic diseases at the single-cell level (Ahmad et al., 2016). Hence, SCOTs can unleash the unique molecular contributions of individual cells or cell types in response to environmental stress or other variables, which remains obscured if the heterogeneous cell population is utilized for analysis of the response. Under the portfolio of multiomics technologies, a combination of omics techniques can lead to capturing of multiple omes of an individual cell, resolving the complex variability of interaction networks among various omic levels, and their commensurate role in cellular functions (Chappell et al., 2018). The multiome analysis can further help in identification of relationships on associative analysis of the variabilities at each omics level (Kang et al., 2018).
17.1.2 Why Do We Need SCOTs for Plant Tissues? Complexities of Plant System Plant cells exhibit fairly high complexity, due to the occurrence of differentiated cells or cell types leading to formation of specialized plant tissues or organs. This cellular complexity demands identification and isolation of individual cells or specific cell types, such that the cell-omes characteristics can be dissected. In addition, the variabilities among individual omes and relative associations among different omic levels at single-cell resolution can be obtained. However, isolation of the specific individual cells must be performed in a manner such that the isolated cells remain amenable to downstream -ome protocols for accomplishing reproducible data. However, high noise makes it tricky, expensive, and difficult to get reproducible data (Fig. 17.3). The outer cell wall, composed of cellulose biopolymer matrix in plant cells, is quite a rigid structure, which poses a primary and technically challenging problem for isolation of individual cells. Thus, it is easier to collect only a few specialized cell types, such as leaf trichome cells, stomatal guard cells, and root hair cells (Libault et al., 2017). The practical relevance of discerning the individual cell contribution is to obtain improved high-resolution data to better assess the characteristics of the apical/axillary stem cells in plants. Moreover, it will also help in discerning the extent of cellular plasticity for the individual cell types, such that any local molecular alterations in response to changes in the internal/external
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FIG. 17.3 The fundamental problems of plant single-cell omics technologies.
cell environment can be visualized at single-cell resolution. Another fundamental complication of plant SCOTs is that of obtaining crisp and discrete data with high reproducibility. This is further complicated if simultaneously several -ome data sets are to be retrieved from a single set of test cell(s) or cell type.
17.2 SINGLE-CELL OMICS TECHNOLOGIES: STEPS AND TECHNIQUES The prerequisite step for performing plant-omics studies at the four molecular hierarchies begins with isolation of the single cells from the plant tissue samples. As discussed in Section 20.1.2, isolation of single plant cells is a tedious process that can be performed using simple dilution/micropipetting to advanced and high-throughput flow cytometry and laser-based capture/
17.2
Single-Cell Omics Technologies: Steps and Techniques
FIG. 17.4 Techniques for isolation of single-cell types from a composite tissue derived from a plant sample.
dissection techniques, which have already been utilized for isolation of single cells from animal tissues (Hodne and Weltzien, 2015; Efroni and Birnbaum, 2016; Valihrach et al., 2018) (Fig. 17.4). Plant cells require treatment with the cell-wall dissolving enzymes to obtain the protoplasts. These cells when isolated from composite samples can be purified by using an array of techniques, such as density gradient centrifugation (Lu et al., 2015), use of fluorescent (green fluorescent protein, GFP) or magnetic tags to sort cells in flow cytometer (FACS/FANS) or columns (MACS), and substrate tagging [biotinylated nuclear tagging (INTACT)] (Schmid et al., 2015; Libault et al., 2017). There are also set of techniques available now to isolate plant cells of specific types without any prior information about their molecular characteristics, termed laser-enabled or -assisted microdissection techniques. The lasers can be utilized to capture, dissect, and obtain specific cells or cell types in a variety of ways, such as optical,
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optoelectronic tweezers, or dissolution of undesirable cells by degradation using intense lasers (Valihrach et al., 2018). Once the cell population is obtained, the downstream processing must be performed for genomics, transcriptomics, proteomics, and metabolomics studies. The single-cell genomics studies reveal the genetic heterogeneity (involves characterization of chromosome structural aberrations and ploidy changes besides recombination in genome), cellular relationships among plant cells of different lineage or origin, evolutionary/diversity analysis, and mosaicism at the genetic level (Libault et al., 2017; Yuan et al., 2018). The genome-wide and newgeneration sequencing techniques that have been initially utilized on bulk cell populations are now being employed to resolve the genetic heterogeneity of individual cells in bulk populations in an unbiased and high-throughput manner (Kolodziejczyk et al., 2015). However, the single-cell transcriptomics involves elucidation of gene regulatory networks via estimation of spatiotemporal variations in gene expression in response to any internal/external stimuli, and the cellular developmental stage through use of single-cell qPCR and single-cell RNA sequencing techniques (scRNA-Seq) (Prakadan et al., 2017). The sc-transcriptomics studies can further discern the subcellular or organellar contributions in a single cell ( Jiang et al., 2017). The single-cell proteomics techniques can unmask the basic genetic heterogeneity among different cell types on the basis of the proteins synthesized in the cell, thereby providing the finely detailed characterization of the cell phenotypes. The fundamental techniques utilized for discerning the single-cell proteome include the two-dimensional gel electrophoresis matrix-assisted laser desorption ionization time-of-flight mass spectrometry (2D-GE-MALDI-TOF MS), electron spray ionization mass spectrometry (MS) or its variants, such as Probe/nanospray SI, tandem MS (MS/MS), liquid chromatography-tandem mass spectrometry (LC-MS/MS), and multidimensional protein identification technology (MudPIT). The spectrometry and MudPIT are the short-gun proteomics approaches that can provide useful qualitative information. Likewise, the relative and absolute quantitative data among different cell types can be obtained through use of isotope-coded affinity/isobaric tags for relative and absolute quantitation (iTRAQs) (Dai and Chen, 2012). The variations occurring at the preceding three omic hierarchies can be validated through identification and isolation of key metabolite(s) in terms of their presence and abundance at the single-cell level using techniques such as GC-MS, LC-ESI-MS, ultrahigh performance liquid chromatography-magnetic resonance (UPLC-MS), nano-high-performance liquid chromatography-magnetic resonance (HPLC-MS), cryogenic nuclear magnetic resonance (NMR), and other variants (Misra et al., 2014). Combined analysis of all -omes can provide a synthetic scenario such that the fundamental functionality and behavior of a specific single cell can be identified (Chappell et al., 2018).
17.3
Elucidation of the Complexity of Plant Responses
17.3 ELUCIDATION OF THE COMPLEXITY OF PLANT RESPONSES: APPLICATIONS OF SCOTs FOR CROP IMPROVEMENT Sections 17.1.1 and 20.1.2 demarcate the ostensible role of SCOTs in overriding the challenges of forward genetics. The sc-genomics studies have led to discovery of genes and their sequence variations in subcellular components of the cell and among different cell types. This information can be critical for plant breeders for development of novel molecular markers, as distinct molecular properties of the individual cells can be discerned by sc-genomics techniques. The gene expression profiling at single-cell resolution can elucidate the effect of altered genetic or environmental conditions on differential expression of specific genes (Table 17.1). These studies have created opportunities for identification and quantification of molecular characteristics with high sensitivity at single-cell resolution to better cognize gene function (Schiefelbein, 2015). Diverse abiotic stresses such as drought, water submergence, salt, heavy metal contamination, and temperature (high or low) negatively affect crop plants across the globe, culminating in plant damage and incurring moderate to high losses of yield, quality, and overall productivity. Abiotic stresschallenged crop plants exhibit stress tolerance and adaptation responses varying from biochemical, physiological, to metabolic, by switching on/off specific genes or sets of genes through intricate and complex signal transduction cascades and pathways to combat/subdue the negative impacts of exposure. The response of a single cell is critical considering the biotic or abiotic stress conditions. Chalkiness of the rice endosperm is a critical quality trait governed by temperature increase, a consequence of the global-warming scenario during the grain-filling stage of the rice. Single-cell on-site analysis studies have revealed enhancement in protein synthesis in endosperm cells in response to N-supply can avoid chalkiness of the grain, even under high temperature conditions (Wada et al., 2017). The biotic characteristics of the plants can either help or thwart their chances for survival. An sc-genomics study of the root microbiome involving endophytic bacteria inhabiting the root tissues of Populus helped in identification of potentially uncultured taxa (Utturkar et al., 2016). Such studies can be beneficial for elucidating the possibility for cultivation of these uncultured microbes, as well as their potential role in imparting growth and immunity to the host plant. Further, integrative single-cell multiomics can pinpoint novel metabolic genes, gene expression profiles, and pathways in crops, unearthing the lineage, course, and repercussions of crop domestication that have led to development of a specific cultivar or hybrid with improved yield and quality characteristics (Zhu et al., 2018).
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Table 17.1 Single-Cell Omics Studies Performed With Different Plant Cells Omics Hierarchy
Study/ Biomolecule(s) Studied
Key Findings
Reference
Dilution-based/flowsorting of single-cell single-chromosome sequencing/haplotyping
Plant developmental biology/DNA
• Identification of genetic mosaicisms, haplotypes, gene markers
Dolezˇel et al. (2014)
Fruit tissues (pericarp, septum, locular tissue, placenta, columella, and seeds)
Laser capture microdissection, RNA-Seq
Plant developmental biology/RNA
Shinozaki et al. (2018)
Arabidopsis
Root tip cells
scRNA-Seq
Plant physiology/ RNA
Solanum lycopersicum
Fruit cells and cell types
Plant physiology/ RNA
Cotton (Gossypium barbadense L. cv 3–79)
Cotton fiber cells
Laser microdissectiontranscriptome profiling, cryo-sectioning followed by laser microdissection and scRNA-Seq Total RNA-Seq and QRT-PCR
• Tomato ripening involves gene expression gradients that start in internal tissues radiating outward, and basipetally along a latitudinal axis • Spatial variations in the epigenetic control patterns during ripening • Regeneration of root follows the embryonic developmental stages • Complementary hormone domains guide the spatial information • Identification of differentially expressed genes among cell or tissue types
• Cotton fiber cells exhibited greater DNA methylation • Integrated multiomics study revealed • dynamic DNA methylation regulates lipid biosynthesis • spatiotemporal modulation of ROS during differentiation in fiber cells
Wang et al. (2016)
Crop/Plant
Cell Type/Cell Studied
Technique(s) Utilized
Cereal and other crops
Different cell types
Solanum lycopersicum cv M82
Genomics
Transcriptomics
Plant physiology/ DNA, RNA
Efroni et al. (2016)
Martin et al. (2016)
Table 17.1 Single-Cell Omics Studies Performed With Different Plant Cells—Continued Omics Hierarchy
Crop/Plant
Cell Type/Cell Studied
Technique(s) Utilized
Oryza sativa L. cv. Nipponbare
Rice egg, sperm, callus cells
Manual isolation, RNA extraction, cDNA preparation and Q-PCR
Solanum lycopersicum cv. Micro-Tom
Root-tip tissues
Arabidopsis thaliana
Leaf epidermal, vascular, and mesophyll cells
Oryza sativa L. cv. Nipponbare
Study/ Biomolecule(s) Studied
Key Findings
Reference
Plant developmental biology/RNA and proteins
• Preferential expression of specific and global genes expressed in gamete cells
Abiko et al. (2013)
Laser capture microdissection followed by nanoLC-MS/MS Meselect-based sorting of leaf cells, western blotting, affinity enrichment and mass spectrometry
Plant metal toxicity/Proteins of root epidermal and other cells Plant physiology/ Proteins (Ubiquitin-26S proteasome targets)
Zhu et al. (2016)
Rice egg, sperm, callus cells
SDS-PAGE followed by LC-MS/MS
Plant developmental biology/Proteins
• Varying effects of Al toxicity on various layers of root cells can be studied through sc-proteomics • Overall number and types of proteins vary in specific leaf tissues Ubiquitin-26S proteasome targets and functioning varies among different cell types • Preferential occurrence of specific proteins expressed in gamete cells
Brassica napus var. Global
Leaf guard cells
GC-MS, UPLC-MS and MRM HPLC-MS
Plant stress response/ Phytohormones
Geng et al. (2017)
Allium cepa
Epidermal single-cell of bulbs
Probe ESI-MS
Vicia faba
Water and wound-stressed single cells from leaf tissue
Nanospray IonizationTandem MS using stable isotope labelling followed by LC-MS/MS
Plant biochemistry/ Specialized metabolites, oligosaccharides Plant developmental biology/ Jasmonoylisoleucine and Abscisic acid hormones
• Low CO2 promotes increased stomatal opening controlled through multiple hormones • A complex cross-talk of various phytohormones mediated low CO2 response • Continuous monitoring of a live single-cell can be achieved by using specialized miniaturized probes • Stress-induced accumulation of ABA and JA-Ile in single cells
Proteomics
Svozil et al. (2015)
Abiko et al. (2013)
Metabolomics
Gong et al. (2014)
Shimizu et al. (2015)
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17.4
CONCLUSIONS AND FUTURE PROSPECTS
Single-cell omics technologies have definitely improved our understanding of individual cell contributions at the four -ome hierarchies. The SCOTs for the isolation, extraction, amplification, and analysis of the various biomolecules (DNA, RNA, proteins, and metabolites) are improving with new advances that have led to the collection of improved, unbiased, high-throughput, and highresolution data sets. However, presently the prime technological problems faced by SCOTs involve enhancing the accuracy and sensitivity, besides the overall throughput of the analytical systems (Libault et al., 2017). Novel cell-capture, isolation, and extraction techniques have to be identified and evaluated for collection of an ample number of uniform individual cells from tissues situated deeper than the epidermis of plant cells in thick samples (Efroni et al., 2015). Currently, the plant structural rigidity and complexity of tissue organization have constrained most of the single-cell omics studies to specialized epidermal cells such as leaf/stem trichomes, stomatal guard cells, root hairs, or certain male/female gamete cells (Schiefelbein, 2015; Schmid et al., 2015; Libault et al., 2017). Multiplexed extraction and quantification of the individual -ome information from a single-cell simultaneously is the other shortcoming that has to be addressed effectively for present-day single-cell plant omics studies. Further, integration of individual -ome information, single-cell multiomics strategies, can provide detailed spatiotemporally resolved data on complex and integrated network responses, such as senescence or aging involving the signal transduction communications among different plant cell types (Großkinsky et al., 2017) and other complex networked responses to various stress conditions (Barkla et al., 2016). Moreover, a combination of two or more kinds of -ome information will provide next-level data orthogonal to the primary -ome data individually, particularly suitable for identification of the transcriptome- and epigenomecontrolled traits in a cell (Kolodziejczyk and L€ onnberg, 2017).
Acknowledgments The authors graciously thank the Head, Department of Soil Science, Punjab Agricultural University, Ludhiana, Punjab for providing the necessary facilities for the research work.
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