A multi-omics approach to solving problems in plant disease ecology

Omics approaches in understanding the benefits of plant-microbe interactions

Plant-microbe interactions are pivotal for ecosystem dynamics and sustainable agriculture, and are influenced by various factors, such as host characteristics, environmental conditions, and human activities. Omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, have revolutionized our understanding of these interactions. Genomics elucidates key genes, transcriptomics reveals gene expression dynamics, proteomics identifies essential proteins, and metabolomics profiles small molecules, thereby offering a holistic perspective. This review synthesizes diverse microbial-plant interactions, showcasing the application of omics in understanding mechanisms, such as nitrogen fixation, systemic resistance induction, mycorrhizal association, and pathogen-host interactions. Despite the challenges of data integration and ethical considerations, omics approaches promise advancements in precision intervention and resilient agricultural practices. Future research should address data integration challenges, enhance omics technology resolution, explore epigenomics, and understand plant-microbe dynamics under diverse conditions. In conclusion, omics technologies hold immense promise for optimizing agricultural strategies and fortifying resilient plant-microbe alliances, paving the way for sustainable agriculture and environmental stewardship.

The role of priming and memory in rice environmental stress adaptation: Current knowledge and perspectives

Plant responses to abiotic stresses are dynamic, following the unpredictable changes of physical environmental parameters such as temperature, water and nutrients. Physiological and phenotypical responses to stress are intercalated by periods of recovery. An earlier stress can be remembered as 'stress memory' to mount a response within a generation or transgenerationally. The 'stress priming' phenomenon allows plants to respond quickly and more robustly to stressors to increase survival, and therefore has significant implications for agriculture. Although evidence for stress memory in various plant species is accumulating, understanding of the mechanisms implicated, especially for crops of agricultural interest, is in its infancy. Rice is a major food crop which is susceptible to abiotic stresses causing constraints on its cultivation and yield globally. Advancing the understanding of the stress response network will thus have a significant impact on rice sustainable production and global food security in the face of climate change. Therefore, this review highlights the effects of priming on rice abiotic stress tolerance and focuses on specific aspects of stress memory, its perpetuation and its regulation at epigenetic, transcriptional, metabolic as well as physiological levels. The open questions and future directions in this exciting research field are also laid out.

Twenty Years of 1H NMR Plant Metabolomics: A Way Forward toward Assessment of Plant Metabolites for Constitutive and Inducible Defenses to Biotic Stress

Metabolomics has become an important tool in elucidating the complex relationship between a plant genotype and phenotype. For over 20 years, nuclear magnetic resonance (NMR) spectroscopy has been known for its robustness, quantitative capabilities, simplicity, and cost-efficiency. 1H NMR is the method of choice for analyzing a broad range of relatively abundant metabolites, which can be used for both capturing the plant chemical profile at one point in time and understanding the pathways that underpin plant defense. This systematic Review explores how 1H NMR-based plant metabolomics has contributed to understanding the role of various compounds in plant responses to biotic stress, focusing on both primary and secondary metabolites. It clarifies the challenges and advantages of using 1H NMR in plant metabolomics, interprets common trends observed, and suggests guidelines for method development and establishing standard procedures.

Drought Stress Amelioration Attributes of Plant-Associated Microbiome on Agricultural Plants

The future global food security depends on the availability of water for agriculture. Yet, the ongoing rise in nonagricultural uses for water, such as urban and industrial uses, and growing environmental quality concerns have increased pressure of irrigation water demand and posed danger to food security. Nevertheless, its severity and duration are predicted to rise shortly. Drought pressure causes stunted growth, severe damage to photosynthesis activity, loss in crop yield, reduced seed germination, and reduced nutrient intake by plants. To overcome the effects of a devastating drought on plants, it is essential to think about the causes, mechanisms of action, and long-term agronomy management and genetics. As a result, there is an urgent need for long-term medication to deal with the harmful effects of drought pressure. The review focuses on the adverse impact of drought on the plant, physiological, and biochemical aspects, and management measures to control the severity of drought conditions. This article reviews the role of genome editing (GE) technologies such as CRISPR 9 (CRISPR-Cas9) related spaces and short palindromic relapse between proteins in reducing the effects of phytohormones, osmolytes, external compounds, proteins, microbes (plant growth-promoting microorganism [PGPM]), approach omics, and drought on plants that support plant growth. This research is to examine the potential of using the microbiome associated with plants for drought resistance and sustainable agriculture. Researchers also advocate using a mix of biotechnology, agronomic, and advanced GE technologies to create drought-tolerant plant varieties.

Holomics - a user-friendly R shiny application for multi-omics data integration and analysis

An organism's observable traits, or phenotype, result from intricate interactions among genes, proteins, metabolites and the environment. External factors, such as associated microorganisms, along with biotic and abiotic stressors, can significantly impact this complex biological system, influencing processes like growth, development and productivity. A comprehensive analysis of the entire biological system and its interactions is thus crucial to identify key components that support adaptation to stressors and to discover biomarkers applicable in breeding programs or disease diagnostics. Since the genomics era, several other 'omics' disciplines have emerged, and recent advances in high-throughput technologies have facilitated the generation of additional omics datasets. While traditionally analyzed individually, the last decade has seen an increase in multi-omics data integration and analysis strategies aimed at achieving a holistic understanding of interactions across different biological layers. Despite these advances, the analysis of multi-omics data is still challenging due to their scale, complexity, high dimensionality and multimodality. To address these challenges, a number of analytical tools and strategies have been developed, including clustering and differential equations, which require advanced knowledge in bioinformatics and statistics. Therefore, this study recognizes the need for user-friendly tools by introducing Holomics, an accessible and easy-to-use R shiny application with multi-omics functions tailored for scientists with limited bioinformatics knowledge. Holomics provides a well-defined workflow, starting with the upload and pre-filtering of single-omics data, which are then further refined by single-omics analysis focusing on key features. Subsequently, these reduced datasets are subjected to multi-omics analyses to unveil correlations between 2-n datasets. This paper concludes with a real-world case study where microbiomics, transcriptomics and metabolomics data from previous studies that elucidate factors associated with improved sugar beet storability are integrated using Holomics. The results are discussed in the context of the biological background, underscoring the importance of multi-omics insights. This example not only highlights the versatility of Holomics in handling different types of omics data, but also validates its consistency by reproducing findings from preceding single-omics studies.

Network Analysis of Publicly Available RNA-seq Provides Insights into the Molecular Mechanisms of Plant Defense against Multiple Fungal Pathogens in Arabidopsis thaliana

Fungal pathogens can have devastating effects on global crop production, leading to annual economic losses ranging from 10% to 23%. In light of climate change-related challenges, researchers anticipate an increase in fungal infections as a result of shifting environmental conditions. However, plants have developed intricate molecular mechanisms for effective defense against fungal attacks. Understanding these mechanisms is essential to the development of new strategies for protecting crops from multiple fungi threats. Public omics databases provide valuable resources for research on plant-pathogen interactions; however, integrating data from different studies can be challenging due to experimental variation. In this study, we aimed to identify the core genes that defend against the pathogenic fungi Colletotrichum higginsianum and Botrytis cinerea in Arabidopsis thaliana. Using a custom framework to control batch effects and construct Gene Co-expression Networks in publicly available RNA-seq dataset from infected A. thaliana plants, we successfully identified a gene module that was responsive to both pathogens. We also performed gene annotation to reveal the roles of previously unknown protein-coding genes in plant defenses against fungal infections. This research demonstrates the potential of publicly available RNA-seq data for identifying the core genes involved in defending against multiple fungal pathogens.

Stress combinations and their interactions in plants database: a one-stop resource on combined stress responses in plants

We have developed a compendium and interactive platform, named Stress Combinations and their Interactions in Plants Database (SCIPDb; http://www.nipgr.ac.in/scipdb.php), which offers information on morpho-physio-biochemical (phenome) and molecular (transcriptome and metabolome) responses of plants to different stress combinations. SCIPDb is a plant stress informatics hub for data mining on phenome, transcriptome, trait-gene ontology, and data-driven research for advancing mechanistic understanding of combined stress biology. We analyzed global phenome data from 939 studies to delineate the effects of various stress combinations on yield in major crops and found that yield was substantially affected under abiotic-abiotic stresses. Transcriptome datasets from 36 studies hosted in SCIPDb identified novel genes, whose roles have not been earlier established in combined stress. Integretome analysis under combined drought-heat stress pinpointed carbohydrate, amino acid, and energy metabolism pathways as the crucial metabolic, proteomic, and transcriptional components in plant tolerance to combined stress. These examples illustrate the application of SCIPDb in identifying novel genes and pathways involved in combined stress tolerance. Further, we showed the application of this database in identifying novel candidate genes and pathways for combined drought and pathogen stress tolerance. To our knowledge, SCIPDb is the only publicly available platform offering combined stress-specific omics big data visualization tools, such as an interactive scrollbar, stress matrix, radial tree, global distribution map, meta-phenome analysis, search, BLAST, transcript expression pattern table, Manhattan plot, and co-expression network. These tools facilitate a better understanding of the mechanisms underlying plant responses to combined stresses.

Deep learning for plant bioinformatics: an explainable gradient-based approach for disease detection

Emerging in the realm of bioinformatics, plant bioinformatics integrates computational and statistical methods to study plant genomes, transcriptomes, and proteomes. With the introduction of high-throughput sequencing technologies and other omics data, the demand for automated methods to analyze and interpret these data has increased. We propose a novel explainable gradient-based approach EG-CNN model for both omics data and hyperspectral images to predict the type of attack on plants in this study. We gathered gene expression, metabolite, and hyperspectral image data from plants afflicted with four prevalent diseases: powdery mildew, rust, leaf spot, and blight. Our proposed EG-CNN model employs a combination of these omics data to learn crucial plant disease detection characteristics. We trained our model with multiple hyperparameters, such as the learning rate, number of hidden layers, and dropout rate, and attained a test set accuracy of 95.5%. We also conducted a sensitivity analysis to determine the model's resistance to hyperparameter variations. Our analysis revealed that our model exhibited a notable degree of resilience in the face of these variations, resulting in only marginal changes in performance. Furthermore, we conducted a comparative examination of the time efficiency of our EG-CNN model in relation to baseline models, including SVM, Random Forest, and Logistic Regression. Although our model necessitates additional time for training and validation due to its intricate architecture, it demonstrates a faster testing time per sample, offering potential advantages in real-world scenarios where speed is paramount. To gain insights into the internal representations of our EG-CNN model, we employed saliency maps for a qualitative analysis. This visualization approach allowed us to ascertain that our model effectively captures crucial aspects of plant disease, encompassing alterations in gene expression, metabolite levels, and spectral discrepancies within plant tissues. Leveraging omics data and hyperspectral images, this study underscores the potential of deep learning methods in the realm of plant disease detection. The proposed EG-CNN model exhibited impressive accuracy and displayed a remarkable degree of insensitivity to hyperparameter variations, which holds promise for future plant bioinformatics applications.

Current Scenario and Future Prospects of Endophytic Microbes: Promising Candidates for Abiotic and Biotic Stress Management for Agricultural and Environmental Sustainability

Globally, substantial research into endophytic microbes is being conducted to increase agricultural and environmental sustainability. Endophytic microbes such as bacteria, actinomycetes, and fungi inhabit ubiquitously within the tissues of all plant species without causing any harm or disease. Endophytes form symbiotic relationships with diverse plant species and can regulate numerous host functions, including resistance to abiotic and biotic stresses, growth and development, and stimulating immune systems. Moreover, plant endophytes play a dominant role in nutrient cycling, biodegradation, and bioremediation, and are widely used in many industries. Endophytes have a stronger predisposition for enhancing mineral and metal solubility by cells through the secretion of organic acids with low molecular weight and metal-specific ligands (such as siderophores) that alter soil pH and boost binding activity. Finally, endophytes synthesize various bioactive compounds with high competence that are promising candidates for new drugs, antibiotics, and medicines. Bioprospecting of endophytic novel secondary metabolites has given momentum to sustainable agriculture for combating environmental stresses. Biotechnological interventions with the aid of endophytes played a pivotal role in crop improvement to mitigate biotic and abiotic stress conditions like drought, salinity, xenobiotic compounds, and heavy metals. Identification of putative genes from endophytes conferring resistance and tolerance to crop diseases, apart from those involved in the accumulation and degradation of contaminants, could open new avenues in agricultural research and development. Furthermore, a detailed molecular and biochemical understanding of endophyte entry and colonization strategy in the host would better help in manipulating crop productivity under changing climatic conditions. Therefore, the present review highlights current research trends based on the SCOPUS database, potential biotechnological interventions of endophytic microorganisms in combating environmental stresses influencing crop productivity, future opportunities of endophytes in improving plant stress tolerance, and their contribution to sustainable remediation of hazardous environmental contaminants.

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

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

Bacterial and Fungal Biocontrol Agents for Plant Disease Protection: Journey from Lab to Field, Current Status, Challenges, and Global Perspectives

Plants are constantly exposed to various phytopathogens such as fungi, Oomycetes, nematodes, bacteria, and viruses. These pathogens can significantly reduce the productivity of important crops worldwide, with annual crop yield losses ranging from 20% to 40% caused by various pathogenic diseases. While the use of chemical pesticides has been effective at controlling multiple diseases in major crops, excessive use of synthetic chemicals has detrimental effects on the environment and human health, which discourages pesticide application in the agriculture sector. As a result, researchers worldwide have shifted their focus towards alternative eco-friendly strategies to prevent plant diseases. Biocontrol of phytopathogens is a less toxic and safer method that reduces the severity of various crop diseases. A variety of biological control agents (BCAs) are available for use, but further research is needed to identify potential microbes and their natural products with a broad-spectrum antagonistic activity to control crop diseases. This review aims to highlight the importance of biocontrol strategies for managing crop diseases. Furthermore, the role of beneficial microbes in controlling plant diseases and the current status of their biocontrol mechanisms will be summarized. The review will also cover the challenges and the need for the future development of biocontrol methods to ensure efficient crop disease management for sustainable agriculture.

Phyto-microbiome to mitigate abiotic stress in crop plants

Plant-associated microbes include taxonomically diverse communities of bacteria, archaebacteria, fungi, and viruses, which establish integral ecological relationships with the host plant and constitute the phyto-microbiome. The phyto-microbiome not only contributes in normal growth and development of plants but also plays a vital role in the maintenance of plant homeostasis during abiotic stress conditions. Owing to its immense metabolic potential, the phyto-microbiome provides the host plant with the capability to mitigate the abiotic stress through various mechanisms like production of antioxidants, plant growth hormones, bioactive compounds, detoxification of harmful chemicals and toxins, sequestration of reactive oxygen species and other free radicals. A deeper understanding of the structure and functions of the phyto-microbiome and the complex mechanisms of phyto-microbiome mediated abiotic stress mitigation would enable its utilization for abiotic stress alleviation of crop plants and development of stress-resistant crops. This review aims at exploring the potential of phyto-microbiome to alleviate drought, heat, salinity and heavy metal stress in crop plants and finding sustainable solutions to enhance the agricultural productivity. The mechanistic insights into the role of phytomicrobiome in imparting abiotic stress tolerance to plants have been summarized, that would be helpful in the development of novel bioinoculants. The high-throughput modern approaches involving candidate gene identification and target gene modification such as genomics, metagenomics, transcriptomics, metabolomics, and phyto-microbiome based genetic engineering have been discussed in wake of the ever-increasing demand of climate resilient crop plants.

Pathogen Profile of Klebsiella variicola, the Causative Agent of Banana Sheath Rot

Banana (Musa spp.) is an important fruit and food crop worldwide. In recent years, banana sheath rot has become a major problem in banana cultivation, causing plant death and substantial economic losses. Nevertheless, the pathogen profile of this disease has not been fully characterized. Klebsiella variicola is a versatile bacterium capable of colonizing different hosts, such as plants, humans, insects, and animals, and is recognized as an emerging pathogen in various hosts. In this study, we obtained 12 bacterial isolates from 12 different banana samples showing banana sheath rot in Guangdong and Guangxi Provinces, China. Phylogenetic analysis based on 16S rRNA sequences confirmed that all 12 isolates were K. variicola strains. We sequenced the genomes of these strains, performed comparative genomic analysis with other sequenced K. variicola strains, and found a lack of consistency in accessory gene content among these K. variicola strains. However, prediction based on the pan-genome of K. variicola revealed 22 unique virulence factors carried by the 12 pathogenic K. variicola isolates. Microbiome and microbial interaction network analysis of endophytes between the healthy tissues of diseased plants and healthy plants of two cultivars showed that Methanobacterium negatively interacts with Klebsiella in banana plants and that Herbaspirillum might indirectly inhibit Methanobacterium to promote Klebsiella growth. These results suggest that banana sheath rot is caused by the imbalance of plant endophytes and opportunistic pathogenic bacteria, providing an important basis for research and control of this disease.[Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Microbial Consortia for Plant Protection against Diseases: More than the Sum of Its Parts

Biological plant protection presents a promising and exciting alternative to chemical methods for safeguarding plants against the increasing threats posed by plant diseases. This approach revolves around the utilization of biological control agents (BCAs) to suppress the activity of significant plant pathogens. Microbial BCAs have the potential to effectively manage crop disease development by interacting with pathogens or plant hosts, thereby increasing their resistance. However, the current efficacy of biological methods remains unsatisfactory, creating new research opportunities for sustainable plant cultivation management. In this context, microbial consortia, comprising multiple microorganisms with diverse mechanisms of action, hold promise in terms of augmenting the magnitude and stability of the overall antipathogen effect. Despite scientific efforts to identify or construct microbial consortia that can aid in safeguarding vital crops, only a limited number of microbial consortia-based biocontrol formulations are currently available. Therefore, this article aims to present a complex analysis of the microbial consortia-based biocontrol status and explore potential future directions for biological plant protection research with new technological advancements.

Uncovering Phytotoxic Compounds Produced by Colletotrichum spp. Involved in Legume Diseases Using an OSMAC-Metabolomics Approach

Different fungal species belonging to the Colletotrichum genus cause anthracnose disease in a range of major crops, resulting in huge economic losses worldwide. Typical symptoms include dark, sunken lesions on leaves, stems, or fruits. Colletotrichum spp. have synthesized, in vitro, a number of biologically active and structurally unusual metabolites that are involved in their host's infection process. In this study, we applied a one strain many compounds (OSMAC) approach, integrated with targeted and non-targeted metabolomics profiling, to shed light on the secondary phytotoxic metabolite panels produced by pathogenic isolates of Colletotrichum truncatum and Colletotrichum trifolii. The phytotoxicity of the fungal crude extracts was also assessed on their primary hosts and related legumes, and the results correlated with the metabolite profile that arose from the different cultural conditions. To the best of our knowledge, this is the first time that the OSMAC strategy integrated with metabolomics approaches has been applied to Colletotrichum species involved in legume diseases.

Omics Approaches in Invasion Biology: Understanding Mechanisms and Impacts on Ecological Health

Invasive species and rapid climate change are affecting the control of new plant diseases and epidemics. To effectively manage these diseases under changing environmental conditions, a better understanding of pathophysiology with holistic approach is needed. Multiomics approaches can help us to understand the relationship between plants and microbes and construct predictive models for how they respond to environmental stresses. The application of omics methods enables the simultaneous analysis of plant hosts, soil, and microbiota, providing insights into their intricate relationships and the mechanisms underlying plant-microbe interactions. This can help in the development of novel strategies for enhancing plant health and improving soil ecosystem functions. The review proposes the use of omics methods to study the relationship between plant hosts, soil, and microbiota, with the aim of developing a new technique to regulate soil health. This approach can provide a comprehensive understanding of the mechanisms underlying plant-microbe interactions and contribute to the development of effective strategies for managing plant diseases and improving soil ecosystem functions. In conclusion, omics technologies offer an innovative and holistic approach to understanding plant-microbe interactions and their response to changing environmental conditions.

Combatting insects mediated biotic stress through plant associated endophytic entomopathogenic fungi in horticultural crops

Horticultural production is a vital catalyst for economic growth, yet insect infestations reduce horticultural crop yield and quality. Pesticides and other pest control methods are used during planting to eliminate pests that cause direct and indirect losses. In such situations, endophytic entomo-pathogenic fungi (EEPF) can act as a potential tools for biological control. They protect plants by boosting growth, nutrition, morpho-physiology and salt or iron tolerance. Antixenosis, antibiosis and plant tolerance change insect performance and preferences. EEPF- plant colonisation slows herbivore development, food consumption, oviposition and larval survival. EEPF changes plant physio-chemical properties like volatile emission profile and secondary metabolite production to regulate insect pest defences. EEPF produces chitinases, laccases, amylases, and cellulases for plant defence. Recent studies focused on EEPF species' significance, isolation, identification and field application. Realizing their full potential is difficult due to insufficient mass production, storage stability and formulation. Genetic-molecular and bioinformatics can help to build EEPF-based biological control systems. Metagenomics helps study microbial EEPF taxonomy and function. Multi-omics and system biology can decode EEPF interactions with host plants and microorganisms. NGS (Next Generation Sequencing), comparative genomics, proteomics, transcriptomics, metabolomics, metatranscriptomics and microarrays are used to evaluate plant-EEPF relationships. IPM requires understanding the abiotic and biotic elements that influence plant-EEPF interaction and the physiological mechanisms of EEPF colonisation. Due to restricted research, there are hundreds of unexplored EEPFs, providing an urgent need to uncover and analyse them.

Phytotoxic Metabolites Produced by Fungi Involved in Grapevine Trunk Diseases: Progress, Challenges, and Opportunities

Grapevine trunk diseases (GTDs), caused by fungal pathogens, are a serious threat to vineyards worldwide, causing significant yield and economic loss. To date, curative methods are not available for GTDs, and the relationship between the pathogen and symptom expression is poorly understood. Several plant pathologists, molecular biologists, and chemists have been investigating different aspects of the pathogenicity, biochemistry, and chemical ecology of the fungal species involved in GTDs. Many studies have been conducted to investigate virulence factors, including the chemical characterization of phytotoxic metabolites (PMs) that assist fungi in invading and colonizing crops such as grapevines. Moreover, multidisciplinary studies on their role in pathogenicity, symptom development, and plant-pathogen interactions have also been carried out. The aim of the present review is to provide an illustrative overview of the biological and chemical characterization of PMs produced by fungi involved in Eutypa dieback, Esca complex, and Botryosphaeria dieback. Moreover, multidisciplinary investigations on host-pathogen interactions, including those using cutting-edge Omics techniques, will also be reviewed and discussed. Finally, challenges and opportunities in the role of PMs for reliable field diagnosis and control of GTDs in vineyards will also be explored.

Multi-Omics Approaches to Study Molecular Mechanisms in Cannabis sativa

Cannabis (Cannabis sativa L.), also known as hemp, is one of the oldest cultivated crops, grown for both its use in textile and cordage production, and its unique chemical properties. However, due to the legislation regulating cannabis cultivation, it is not a well characterized crop, especially regarding molecular and genetic pathways. Only recently have regulations begun to ease enough to allow more widespread cannabis research, which, coupled with the availability of cannabis genome sequences, is fuelling the interest of the scientific community. In this review, we provide a summary of cannabis molecular resources focusing on the most recent and relevant genomics, transcriptomics and metabolomics approaches and investigations. Multi-omics methods are discussed, with this combined approach being a powerful tool to identify correlations between biological processes and metabolic pathways across diverse omics layers, and to better elucidate the relationships between cannabis sub-species. The correlations between genotypes and phenotypes, as well as novel metabolites with therapeutic potential are also explored in the context of cannabis breeding programs. However, further studies are needed to fully elucidate the complex metabolomic matrix of this crop. For this reason, some key points for future research activities are discussed, relying on multi-omics approaches.

Multi-Omics Approaches to Improve Clubroot Resistance in Brassica with a Special Focus on Brassica oleracea L

Brassica oleracea is an agronomically important species of the Brassicaceae family, including several nutrient-rich vegetables grown and consumed across the continents. But its sustainability is heavily constrained by a range of destructive pathogens, among which, clubroot disease, caused by a biotrophic protist Plasmodiophora brassicae, has caused significant yield and economic losses worldwide, thereby threatening global food security. To counter the pathogen attack, it demands a better understanding of the complex phenomenon of Brassica-P. brassicae pathosystem at the physiological, biochemical, molecular, and cellular levels. In recent years, multiple omics technologies with high-throughput techniques have emerged as successful in elucidating the responses to biotic and abiotic stresses. In Brassica spp., omics technologies such as genomics, transcriptomics, ncRNAomics, proteomics, and metabolomics are well documented, allowing us to gain insights into the dynamic changes that transpired during host-pathogen interactions at a deeper level. So, it is critical that we must review the recent advances in omics approaches and discuss how the current knowledge in multi-omics technologies has been able to breed high-quality clubroot-resistant B. oleracea. This review highlights the recent advances made in utilizing various omics approaches to understand the host resistance mechanisms adopted by Brassica crops in response to the P. brassicae attack. Finally, we have discussed the bottlenecks and the way forward to overcome the persisting knowledge gaps in delivering solutions to breed clubroot-resistant Brassica crops in a holistic, targeted, and precise way.

Multi-Omics Analysis Reveals a Regulatory Network of ZmCCT During Maize Resistance to Gibberella Stalk Rot at the Early Stage

Gibberella stalk rot (GSR) caused by Fusarium graminearum is one of the most devastating diseases in maize; however, the regulatory mechanism of resistance to GSR remains largely unknown. We performed a comparative multi-omics analysis to reveal the early-stage resistance of maize to GSR. We inoculated F. graminearum to the roots of susceptible (Y331) and resistant (Y331-ΔTE) near-isogenic lines containing GSR-resistant gene ZmCCT for multi-omics analysis. Transcriptome detected a rapid reaction that confers resistance at 1-3 hpi as pattern-triggered immunity (PTI) response to GSR. Many key properties were involved in GSR resistance, including genes in photoperiod and hormone pathways of salicylic acid and auxin. The activation of programmed cell death-related genes and a number of metabolic pathways at 6 hpi might be important to prevent further colonization. This is consistent with an integrative analysis of transcriptomics and proteomics that resistant-mediated gene expression reprogramming exhibited a dynamic pattern from 3 to 6 hpi. Further metabolomics analysis revealed that the amount of many chemical compounds was altered in pathways associated with the phenylpropanoid biosynthesis and the phenylalanine metabolism, which may play key roles to confer the GSR resistance. Taken together, we generated a valuable resource to interpret the defense mechanism during early GSR resistance.

Transcriptome and metabolome analyses reveal new insights into chlorophyll, photosynthesis, metal ion and phenylpropanoids related pathways during sugarcane ratoon chlorosis

BACKGROUND

Ratoon sugarcane is susceptible to chlorosis, characterized by chlorophyll loss, poor growth, and a multitude of nutritional deficiency mainly occurring at young stage. Chlorosis would significantly reduce the cane production. The molecular mechanism underlying this phenomenon remains unknown. We analyzed the transcriptome and metabolome of chlorotic and non-chlorotic sugarcane leaves of the same age from the same field to gain molecular insights into this phenomenon.

RESULTS

The agronomic traits, such as plant height and the number of leaf, stalk node, and tillers declined in chlorotic sugarcane. Chlorotic leaves had substantially lower chlorophyll content than green leaves. A total of 11,776 differentially expressed genes (DEGs) were discovered in transcriptome analysis. In the KEGG enriched chlorophyll metabolism pathway, sixteen DEGs were found, eleven of which were down-regulated. Two photosynthesis pathways were also enriched with 32 genes downregulated and four genes up-regulated. Among the 81 enriched GO biological processes, there were four categories related to metal ion homeostasis and three related to metal ion transport. Approximately 400 metabolites were identified in metabolome analysis. The thirteen differentially expressed metabolites (DEMs) were all found down-regulated. The phenylpropanoid biosynthesis pathway was enriched in DEGs and DEMs, indicating a potentially vital role for phenylpropanoids in chlorosis.

CONCLUSIONS

Chlorophyll production, metal ion metabolism, photosynthesis, and some metabolites in the phenylpropanoid biosynthesis pathway were considerably altered in chlorotic ratoon sugarcane leaves. Our finding revealed the relation between chlorosis and these pathways, which will help expand our mechanistic understanding of ratoon sugarcane chlorosis.

Applications of cell- and tissue-specific 'omics to improve plant productivity

The individual tissues and cell types of plants each have characteristic properties that contribute to the function of the plant as a whole. These are reflected by unique patterns of gene expression, protein and metabolite content, which enable cell-type-specific patterns of growth, development and physiology. Gene regulatory networks act within the cell types to govern the production and activity of these components. For the broader organism to grow and reproduce successfully, cell-type-specific activity must also function within the context of surrounding cell types, which is achieved by coordination of signalling pathways. We can investigate how gene regulatory networks are constructed and function using integrative ‘omics technologies. Historically such experiments in plant biological research have been performed at the bulk tissue level, to organ resolution at best. In this review, we describe recent advances in cell- and tissue-specific ‘omics technologies that allow investigation at much improved resolution. We discuss the advantages of these approaches for fundamental and translational plant biology, illustrated through the examples of specialised metabolism in medicinal plants and seed germination. We also discuss the challenges that must be overcome for such approaches to be adopted widely by the community.

Abiotic Stress and Belowground Microbiome: The Potential of Omics Approaches

Nowadays, the worldwide agriculture is experiencing a transition process toward more sustainable production, which requires the reduction of chemical inputs and the preservation of microbiomes’ richness and biodiversity. Plants are no longer considered as standalone entities, and the future of agriculture should be grounded on the study of plant-associated microorganisms and all their potentiality. Moreover, due to the climate change scenario and the resulting rising incidence of abiotic stresses, an innovative and environmentally friendly technique in agroecosystem management is required to support plants in facing hostile environments. Plant-associated microorganisms have shown a great attitude as a promising tool to improve agriculture sustainability and to deal with harsh environments. Several studies were carried out in recent years looking for some beneficial plant-associated microbes and, on the basis of them, it is evident that Actinomycetes and arbuscular mycorrhizal fungi (AMF) have shown a considerable number of positive effects on plants’ fitness and health. Given the potential of these microorganisms and the effects of climate change, this review will be focused on their ability to support the plant during the interaction with abiotic stresses and on multi-omics techniques which can support researchers in unearthing the hidden world of plant–microbiome interactions. These associated microorganisms can increase plants’ endurance of abiotic stresses through several mechanisms, such as growth-promoting traits or priming-mediated stress tolerance. Using a multi-omics approach, it will be possible to deepen these mechanisms and the dynamic of belowground microbiomes, gaining fundamental information to exploit them as staunch allies and innovative weapons against crop abiotic enemies threatening crops in the ongoing global climate change context.

Omics Path to Increasing Productivity in Less-Studied Crops Under Changing Climate-Lentil a Case Study

Conventional breeding techniques for crop improvement have reached their full potential, and hence, alternative routes are required to ensure a sustained genetic gain in lentils. Although high-throughput omics technologies have been effectively employed in major crops, less-studied crops such as lentils have primarily relied on conventional breeding. Application of genomics and transcriptomics in lentils has resulted in linkage maps and identification of QTLs and candidate genes related to agronomically relevant traits and biotic and abiotic stress tolerance. Next-generation sequencing (NGS) complemented with high-throughput phenotyping (HTP) technologies is shown to provide new opportunities to identify genomic regions and marker-trait associations to increase lentil breeding efficiency. Recent introduction of image-based phenotyping has facilitated to discern lentil responses undergoing biotic and abiotic stresses. In lentil, proteomics has been performed using conventional methods such as 2-D gel electrophoresis, leading to the identification of seed-specific proteome. Metabolomic studies have led to identifying key metabolites that help differentiate genotypic responses to drought and salinity stresses. Independent analysis of differentially expressed genes from publicly available transcriptomic studies in lentils identified 329 common transcripts between heat and biotic stresses. Similarly, 19 metabolites were common across legumes, while 31 were common in genotypes exposed to drought and salinity stress. These common but differentially expressed genes/proteins/metabolites provide the starting point for developing high-yielding multi-stress-tolerant lentils. Finally, the review summarizes the current findings from omic studies in lentils and provides directions for integrating these findings into a systems approach to increase lentil productivity and enhance resilience to biotic and abiotic stresses under changing climate.

Plant Disease Sensing: Studying Plant-Pathogen Interactions at Scale

Plant disease threatens the environmental and financial sustainability of crop production, causing $220 billion in annual losses. The dire threat disease poses to modern agriculture demands tools for better detection and monitoring to prevent crop loss and input waste. The nascent discipline of plant disease sensing, or the science of using proximal and/or remote sensing to detect and diagnose disease, offers great promise to extend monitoring to previously unachievable resolutions, a basis to construct multiscale surveillance networks for early warning, alert, and response at low latency, an opportunity to mitigate loss while optimizing protection, and a dynamic new dimension to agricultural systems biology. Despite its revolutionary potential, plant disease sensing remains an underdeveloped discipline, with challenges facing both fundamental study and field application. This article offers a perspective on the current state and future of plant disease sensing, highlights remaining gaps to be filled, and presents a bold vision for the future of global agriculture.

Advances in Multi-Omics Approaches for Molecular Breeding of Black Rot Resistance in Brassica oleracea L

Brassica oleracea is one of the most important species of the Brassicaceae family encompassing several economically important vegetables produced and consumed worldwide. But its sustainability is challenged by a range of pathogens, among which black rot, caused by Xanthomonas campestris pv. campestris (Xcc), is the most serious and destructive seed borne bacterial disease, causing huge yield losses. Host-plant resistance could act as the most effective and efficient solution to curb black rot disease for sustainable production of B. oleracea. Recently, 'omics' technologies have emerged as promising tools to understand the host-pathogen interactions, thereby gaining a deeper insight into the resistance mechanisms. In this review, we have summarized the recent achievements made in the emerging omics technologies to tackle the black rot challenge in B. oleracea. With an integrated approach of the omics technologies such as genomics, proteomics, transcriptomics, and metabolomics, it would allow better understanding of the complex molecular mechanisms underlying black rot resistance. Due to the availability of sequencing data, genomics and transcriptomics have progressed as expected for black rot resistance, however, other omics approaches like proteomics and metabolomics are lagging behind, necessitating a holistic and targeted approach to address the complex questions of Xcc-Brassica interactions. Genomic studies revealed that the black rot resistance is a complex trait and is mostly controlled by quantitative trait locus (QTL) with minor effects. Transcriptomic analysis divulged the genes related to photosynthesis, glucosinolate biosynthesis and catabolism, phenylpropanoid biosynthesis pathway, ROS scavenging, calcium signalling, hormonal synthesis and signalling pathway are being differentially expressed upon Xcc infection. Comparative proteomic analysis in relation to susceptible and/or resistance interactions with Xcc identified the involvement of proteins related to photosynthesis, protein biosynthesis, processing and degradation, energy metabolism, innate immunity, redox homeostasis, and defence response and signalling pathways in Xcc-Brassica interaction. Specifically, most of the studies focused on the regulation of the photosynthesis-related proteins as a resistance response in both early and later stages of infection. Metabolomic studies suggested that glucosinolates (GSLs), especially aliphatic and indolic GSLs, its subsequent hydrolysis products, and defensive metabolites synthesized by jasmonic acid (JA)-mediated phenylpropanoid biosynthesis pathway are involved in disease resistance mechanisms against Xcc in Brassica species. Multi-omics analysis showed that JA signalling pathway is regulating resistance against hemibiotrophic pathogen like Xcc. So, the bonhomie between omics technologies and plant breeding is going to trigger major breakthroughs in the field of crop improvement by developing superior cultivars with broad-spectrum resistance. If multi-omics tools are implemented at the right scale, we may be able to achieve the maximum benefits from the minimum. In this review, we have also discussed the challenges, future prospects, and the way forward in the application of omics technologies to accelerate the breeding of B. oleracea for disease resistance. A deeper insight about the current knowledge on omics can offer promising results in the breeding of high-quality disease-resistant crops.

Artificial Intelligence as Accelerator for Genomic Medicine and Planetary Health

Genomic medicine has made important strides over the past several decades, but as new insights and technologies emerge, the applications of genomics in medicine and planetary health continue to evolve and expand. An important grand challenge is harnessing and making sense of the genomic big data in ways that best serve public and planetary health. Because human health is inextricably intertwined with the health of planetary ecosystems and nonhuman animals, genomic medicine is in need of high throughput bioinformatics analyses to harness and integrate human and ecological multiomics big data. It is in this overarching context that artificial intelligence (AI), particularly machine learning and deep learning, offers enormous potentials to advance genomic medicine in a spirit of One Health. This expert review offers an analysis of the rapidly emerging role of AI in genomic medicine, including its current drivers, levers, opportunities, and challenges. The scope of AI applications in genomic medicine is broad, ranging from efficient and automated data analysis to drug repurposing and precision medicine, as with its challenges such as veracity of the big data that AI sorely depends on, social biases that the AI-driven algorithms can introduce, and how best to incorporate AI with human intelligence. The road ahead for AI in genomic medicine is complex and arduous and yet worthy of cautious optimism as we face future pandemics and ecological crises in the 21st century. Now is a good time to think about the role of AI in genomic medicine and planetary health.

Network biology to uncover functional and structural properties of the plant immune system

In the last two decades, advances in network science have facilitated the discovery of important systems' entities in diverse biological networks. This graph-based technique has revealed numerous emergent properties of a system that enable us to understand several complex biological processes including plant immune systems. With the accumulation of multiomics data sets, the comprehensive understanding of plant-pathogen interactions can be achieved through the analyses and efficacious integration of multidimensional qualitative and quantitative relationships among the components of hosts and their microbes. This review highlights comparative network topology analyses in plant-pathogen co-expression networks and interactomes, outlines dynamic network modeling for cell-specific immune regulatory networks, and discusses the new frontiers of single-cell sequencing as well as multiomics data integration that are necessary for unraveling the intricacies of plant immune systems.

How to Unravel the Key Functions of Cryptic Oomycete Elicitin Proteins and Their Role in Plant Disease

Pathogens and plants are in a constant battle with one another, the result of which is either the restriction of pathogen growth via constitutive or induced plant defense responses or the pathogen colonization of plant cells and tissues that cause disease. Elicitins are a group of highly conserved proteins produced by certain oomycete species, and their sterol binding ability is recognized as an important feature in sterol–auxotrophic oomycetes. Elicitins also orchestrate other aspects of the interactions of oomycetes with their plant hosts. The function of elicitins as avirulence or virulence factors is controversial and is dependent on the host species, and despite several decades of research, the function of these proteins remains elusive. We summarize here our current understanding of elicitins as either defense-promoting or defense-suppressing agents and propose that more recent approaches such as the use of ‘omics’ and gene editing can be used to unravel the role of elicitins in host–pathogen interactions. A better understanding of the role of elicitins is required and deciphering their role in host–pathogen interactions will expand the strategies that can be adopted to improve disease resistance and reduce crop losses.

Endophytic Fungi: Biological Control and Induced Resistance to Phytopathogens and Abiotic Stresses

Plant diseases cause losses of approximately 16% globally. Thus, management measures must be implemented to mitigate losses and guarantee food production. In addition to traditional management measures, induced resistance and biological control have gained ground in agriculture due to their enormous potential. Endophytic fungi internally colonize plant tissues and have the potential to act as control agents, such as biological agents or elicitors in the process of induced resistance and in attenuating abiotic stresses. In this review, we list the mode of action of this group of microorganisms which can act in controlling plant diseases and describe several examples in which endophytes were able to reduce the damage caused by pathogens and adverse conditions. This is due to their arsenal of molecules generated during the interaction by which they form a kind of biological shield in the plant. Furthermore, considering that endophytic fungi can be an important tool in managing for biotic and abiotic stresses due to the large amount of biologically active substances produced, bioprospecting this class of microorganisms is tending to increase and generate valuable products for agriculture.