Applications of Multi-Omics Technologies for Crop Improvement

CRISPR/Cas9-mediated editing of jasmonic acid pathways to enhance biotic & abiotic stress tolerance: An overview & prospects

Food security is becoming increasingly important as the world's population grows, and the likelihood that climate change could impair agricultural supply complicates matters further. However, plants actively suppress growth as an adaptation strategy to enhance survival under stress conditions. Phytohormone jasmonates (JAs) regulate various physiological processes, including plant growth, development, and senescence. Plant biotic and abiotic stress responses cause dynamic shifts in the metabolism and signaling of JAs, suggesting that JAs response impacts plant development and resistance to various stresses. The JAs-associated responses depend on core components of JAs -signaling, including the transcriptional repressors protein JAZ and the transcription factor MYC2. While traditional breeding has greatly benefited the world, this approach has several disadvantages, such as the emergence of undesirable traits and species barriers. Genome editing technology has revolutionized plant biology research and has significant ramifications for agriculture and global food security, particularly in light of climate change and population growth. CRISPR/Cas9 and its derivative tools have been used for genome editing in numerous crops to improve or alter desired plant phenotypes. This review summarizes JA's role in plant stress and defense and how CRISPR/Cas9-editing technology modifies plant JA's responses, especially against biotic and abiotic stress.

Jasmonic Acid Signaling Pathway Mediates Decabromodiphenyl Ethane (DBDPE) Tolerance by Modulating Photosynthesis and Oxidative Stress in Sugar Beet: Insights from Integrative Physiological and Multiomics Analyses

Decabromodiphenyl ethane (DBDPE), an emerging ubiquitous contaminant, enters the food chain through crop bioaccumulation, threatening food safety. This study investigated the bioaccumulation, toxicity, and tolerance mechanisms of DBDPE in sugar beet. The results showed that DBDPE was absorbed by roots and transported to leaves in a constant proportion, with greater toxicity in leaves than in roots. Physiological analyses revealed that DBDPE induced chloroplastic dysfunction and oxidative stress in a concentration-dependent manner. The antioxidant system in response to DBDPE varied with exposure levels. Integrated transcriptomic, proteomic, and metabolomic analyses revealed that remodeling of jasmonic acid (JA) biosynthesis and consequent activation of JA signaling were critical for DBDPE tolerance. Exogenous JA and JA-Ile (active JA) maintained photosynthetic activity by protecting chloroplasts and mitigated oxidative damage by enhancing antioxidant system activity, thereby improving DBDPE tolerance. This study provides an insight into the development of effective mitigation strategies against DBDPE toxicity in crops.

Low-intensity laser exposure enhances rice (Oryza sativa L.) growth through physio-biochemical regulation, transcriptional modulation, and microbiome alteration

Environmental stressors significantly impact plant growth and agricultural productivity, necessitating innovative approaches to enhance crop resilience and yield. While high-intensity laser applications in agriculture have traditionally been limited to destructive purposes due to their harmful effects on plant growth, the emergence of low-intensity laser technology presents new opportunities for crop improvement. However, the molecular mechanisms underlying the beneficial effects of low-intensity laser treatment remain largely unexplored. This study investigated the effects of low-intensity laser treatment on rice seedling growth, physiological and molecular responses, and rhizosphere microbial communities. Low-intensity laser treatment (2 µmol/m²/s PPFD) significantly enhanced root and shoot growth, enhanced biomass accumulation, and improved yield parameters, with a 16.8% increase in effective panicles and 9.01% higher yield per plant. Physiological analyses revealed elevated antioxidant enzyme activities (POD and SOD) and reduced ROS levels in treated plants. Transmission electron microscopy showed improved chloroplast structure, correlating with enhanced photosynthetic efficiency. Transcriptomic analysis identified 623 differentially expressed genes, with significant enrichment in pathways related to photosynthesis, carbon metabolism, and hormone signaling. Notably upregulation was observed in photosynthesis-related genes (OsPsbB and OsCYF) and hormone signaling genes (OsWRKY114 and OsWRI1). Additionally, 16S rRNA sequencing revealed significant restructuring of rhizosphere bacterial communities in laser-treated plants, with enrichment of beneficial genera including Pseudomonas and Enterobacter. These findings establish low-intensity laser treatment as a promising tool for enhancing rice productivity through coordinated regulation of photosynthetic efficiency, stress responses, and beneficial microbiome interactions.

Machine Learning-Based identification of resistance genes associated with sunflower broomrape

BACKGROUND

Sunflowers (Helianthus annuus L.), a vital oil crop, are facing a severe challenge from broomrape (Orobanche cumana), a parasitic plant that seriously jeopardizes the growth and development of sunflowers, limits global production and leads to substantial economic losses, which urges the development of resistant sunflower varieties.

RESULTS

This study aims to identify resistance genes from a comprehensive transcriptomic profile of 103 sunflower varieties based on gene expression data and then constructs predictive models with the key resistant genes. The least absolute shrinkage and selection operator (LASSO) regression and random forest feature importance ranking method were used to identify resistance genes. These genes were considered as biomarkers in constructing machine learning models with Support Vector Machine (SVM), K-Nearest Neighbours (KNN), Logistic Regression (LR), and Gaussian Naive Bayes (GaussianNB). The SVM model constructed with the 24 key genes selected by the LASSO method demonstrated high classification accuracy (0.9514) and a robust AUC value (0.9865), effectively distinguishing between resistant and susceptible varieties based on gene expression data. Furthermore, we discovered a correlation between key genes and differential metabolites, particularly jasmonic acid (JA).

CONCLUSION

Our study highlights a novel perspective on screening sunflower varieties for broomrape resistance, which is anticipated to guide future biological research and breeding strategies.

Application of proteomics in investigating the responses of plant to abiotic stresses

MAIN CONCLUSION

This review summarizes the application of proteomic techniques in investigating the responses of plant to abiotic stresses. In the natural environment, the plants are exposed to a diverse range of adverse abiotic factors that significantly impact their growth and development. The plants have evolved intricate stress response mechanisms at the genetic, protein, metabolic, and phenotypic levels to mitigate damage caused by unfavorable conditions. Proteomics serves as an effective tool for studying protein changes in plants and provides valuable insights into the physiological mechanisms underlying plant stress resistance. Several proteins involved in abiotic stress responses have been identified in plants, including transcription factors, protein kinases, ATP synthases, heat shock proteins, redox proteins, and enzymes in secondary metabolite pathways. Medicinal plants are a unique category of crops capable of synthesizing secondary metabolites, which play a crucial role in resisting abiotic stress and exhibit changes in content under stress conditions. In this review, we present an overview of proteomic tools employed for investigating the responses of plants to abiotic stresses and summarize alterations observed at the protein level under various abiotic stresses such as signal transduction, oxidative damage, carbohydrate and energy metabolism, protein and amino acid metabolism, cellular homeostasis, and enzyme involvement in secondary metabolism. This work aims to facilitate the application of proteomics techniques in plants research while enhancing our understanding of the response mechanisms exhibited by these plants towards abiotic stresses.

Advancements in multi-omics for nutraceutical enhancement and traits improvement in buckwheat

Buckwheat (Fagopyrum spp.) is a typical pseudocereal, valued for its extensive nutraceutical potential as well as its centuries-old cultivation. Tartary buckwheat and common buckwheat have been used globally and become well-known nutritious foods due to their high quantities of: proteins, flavonoids, and minerals. Moreover, its increasing demand makes it critical to improve nutraceutical, traits and yield. In this review, bioactive compounds accumulated in buckwheat were comprehensively evaluated according to their chemical structure, properties, and physiological function. Biosynthetic pathways of flavonoids, phenolic acids, and fagopyrin were methodically summarized, with the regulation of flavonoid biosynthesis. Although there are classic synthesis pathways presented in the previous research, the metabolic flow of how these certain compounds are being synthesized in buckwheat still remains uncovered. The functional genes involved in the biosynthesis of flavonols, stress response, and plant development were identified based on multi-omics research. Furthermore, it delves into the applications of multi-omics in improving buckwheat's agronomic traits, including: yield, nutritional content, stress resilience, and bioactive compounds biosynthesis. While pangenomics combined with other omics to mine elite genes, the regulatory network and mechanism of specific agronomic traits and biosynthetic of bioactive components, and developing a more efficient genetic transformation system for genetic engineering require further investigation for the execution of breeding designs aimed at enhancing desirable traits in buckwheat. This critical review will provide a comprehensive understanding of multi-omics for nutraceutical enhancement and traits improvement in buckwheat.

Advances in multi-trait genomic prediction approaches: classification, comparative analysis, and perspectives

Traits in any organism are not independent, but show considerable integration, observed in a form of couplings and trade-offs. Therefore, improvement in one trait may affect other traits, often in undesired direction. To account for this problem, crop breeding increasingly relies on multi-trait genomic prediction (MT-GP) approaches that leverage the availability of genetic markers from different populations along with advances in high-throughput precision phenotyping. While significant progress has been made to jointly model multiple traits using a variety of statistical and machine learning approaches, there is no systematic comparison of advantages and shortcomings of the existing classes of MT-GP models. Here, we fill this knowledge gap by first classifying the existing MT-GP models and briefly summarizing their general principles, modeling assumptions, and potential limitations. We then perform an extensive comparative analysis with 10 traits measured in an Oryza sativa diversity panel using cross-validation scenarios relevant in breeding practice. Finally, we discuss directions that can enable the building of next generation MT-GP models in addressing pressing challenges in crop breeding.

Blockchain-Empowered H-CPS Architecture for Smart Agriculture

This study integrates blockchain technology into smart agriculture to enhance its productivity and sustainability. By combining blockchain with remote sensing, artificial intelligence (AI), and the Internet of Things (IoT), a Human-Cyber-Physical System (H-CPS) architecture tailored for agricultural applications is proposed. It supports real-time crop management, data-driven decision-making, and transparent trading of agricultural products. A semantic-based blockchain framework is introduced to address challenges in data management and AI model integration, optimizing production, improving traceability, reducing costs, and enhancing financial security. This framework directly addresses real-world agricultural challenges, such as optimized irrigation, improved crop breeding efficiency, and enhanced supply chain transparency. These innovations provide practical solutions for modern agriculture, contributing to sustainable development and global food security. Further research and collaboration are encouraged to unlock its full potential in transforming agricultural practices.

Multi-omics analyses reveal fecal microbial community and metabolic alterations in finishing cattle fed probiotics-fermented distiller's grains diets

Distiller's grains (DG) are a potential source of animal feeds, and many studies have indicated positive regulatory roles of feeding DG diets in animal breeding. However, there is currently a dearth of research on the actions and underlying mechanisms of probiotics-fermented distiller's grains (FDG)-based diets in cattle breeding. This study aimed to assess the impact of integrating FDG into the diet of finishing cattle on their fecal microbial community and metabolites. Thirty Simmental crossbred cattle (local yellow cattle × Simmental cattle, 8.5 months old, 420.38 ± 68.11 kg) were selected and randomly divided into three dietary treatments, including the basal diet group (CON group), the FDG replacing 10% concentrate (FDG-10%) group, and the FDG replacing 20% concentrate (FDG-20%) group. 16S and ITS sequencing of fecal samples collected from each group on the 30th day of the formal feeding suggested that feeding FDG diets had little effect on the composition and diversity of fecal bacterial and fungal communities in finishing cattle. However, the relative abundance of cellulose-degrading bacteria, including the Christensenellaceae R-7 group and Ruminococcaceae family was significantly higher in both the FDG-20% vs CON comparison and the FDG-20% vs FDG-10% comparison. Besides, the FDG-10% group had a significant drop in the relative abundance of Aspergillus and a noteworthy increase in the relative abundance of Candida when compared to the CON group. Non-targeted metabolomics analysis showed that the addition of FDG modified the levels of organoheterocyclic compounds, lipids and lipid-like molecules, and benzenoids in the feces of finishing cattle and significantly enhanced the metabolic pathway of bile secretion. Further correlation analyses suggested a close association between the significantly differential fecal microbiota and metabolites. In conclusion, these results suggest that FDG supplementation has little effect on the structure and diversity of the fecal microbiota in finishing cattle, but alters intestinal metabolite profiles and influences bile secretion pathways by modulating the relative abundance of genera of fecal bacteria and fungi Christensenellaceae R-7 group, Lachnospiraceae_NK3A20_group, Mucor, and Candida. These findings provide a scientific theoretical basis for the use of FDG in animal feeds.

IMPORTANCE

Probiotics-fermented distiller's grains (FDG) are potential feed sources for livestock. Here, we investigated the effects of partially replacing concentrates with FDG on fecal bacterial and fungal community structure and metabolic profiles in finishing cattle. The results reveal that feeding FDG-based diets alters intestinal metabolite profiles and up-regulates bile secretion pathways through the regulation of relative abundance of certain fecal genera. These findings provide some new insights into clarifying the role and potential mechanisms of FDG diets and also offer a scientific basis for the development of FDG into functional feed resources.

Unlocking the potential of 'Egusi' melon (Colocynthis citrullus L.) as a crop for biotechnological improvement

'Egusi' melon (Colocynthis citrullus L.) plays a critical role in food security and potential biofuel production in West Africa. Its seeds are valued for both their nutritional and potential industrial applications, especially in biodiesel production. However, the crop faces significant challenges, including the impacts of climate change, water scarcity, declining arable land, and increased pressure from pests and diseases. These challenges threaten the stability of 'Egusi' production and may hinder its ability to meet future demand. To address these issues, there is a growing need to complement conventional breeding methods with biotechnological approaches. Molecular approaches; including genomics, transcriptomics, proteomics, and metabolomics; have been utilized for the improvement of several cucurbit species. However, information on molecular breeding of 'Egusi' is very limited. The current review focuses on 'Egusi' melon, its biology, uses, and factors affecting its improvement, and highlights critical knowledge gaps in the molecular breeding of 'Egusi'. The review also examines the potential of omics technologies and outlines the importance of genetic transformation and genome editing methods such as CRISPR that could drive the development of more resilient and high-yielding 'Egusi'varieties that will contribute to sustainability and profitability of 'Egusi' farming.

Accelerating crop improvement via integration of transcriptome-based network biology and genome editing

MAIN CONCLUSION

Big data and network biology infer functional coupling between genes. In combination with machine learning, network biology can dramatically accelerate the pace of gene discovery using modern transcriptomics approaches and be validated via genome editing technology for improving crops to stresses. Unlike other living things, plants are sessile and frequently face various environmental challenges due to climate change. The cumulative effects of combined stresses can significantly influence both plant growth and yields. In navigating the complexities of climate change, ensuring the nourishment of our growing population hinges on implementing precise agricultural systems. Conventional breeding methods have been commonly employed; however, their efficacy has been impeded by limitations in terms of time, cost, and infrastructure. Cutting-edge tools focussing on big data are being championed to usher in a new era in stress biology, aiming to cultivate crops that exhibit enhanced resilience to multifactorial stresses. Transcriptomics, combined with network biology and machine learning, is proving to be a powerful approach for identifying potential genes to target for gene editing, specifically to enhance stress tolerance. The integration of transcriptomic data with genome editing can yield significant benefits, such as gaining insights into gene function by modifying or manipulating of specific genes in the target plant. This review provides valuable insights into the use of transcriptomics platforms and the application of biological network analysis and machine learning in the discovery of novel genes, thereby enhancing the understanding of plant responses to combined or sequential stress. The transcriptomics as a forefront omics platform and how it is employed through biological networks and machine learning that lead to novel gene discoveries for producing multi-stress-tolerant crops, limitations, and future directions have also been discussed.

Targeting PI3K Signaling to Overcome Tumor Immunosuppression: Synergistic Strategies to Enhance Cancer Vaccine Efficacy

Phosphoinositide 3-kinases (PI3Ks), members of the lipid kinase family, play a significant role in modulating immune cell functions, including activation, proliferation, and differentiation. Recent studies have identified the PI3K signaling pathway as a key regulator in tumor biology and the immune microenvironment. This pathway enhances the activity of regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs), contributing to an immunosuppressive tumor microenvironment that impairs the effectiveness of cancer vaccines and immunotherapies. The present study explores PI3K isoforms, particularly p110γ and p110δ, and their associated signaling pathways. The therapeutic potential of selective PI3K inhibitors and their capacity to act synergistically with immunization strategies are analyzed. Targeting the PI3K signaling pathway represents a promising approach to counteract tumor-induced immune suppression and improve the efficacy of immune checkpoint inhibitors and vaccines, ultimately leading to better clinical outcomes.

Omics advancements towards exploring arsenic toxicity and tolerance in plants: a review

MAIN CONCLUSION

Omics approaches provide comprehensive insights into plant arsenic stress responses, setting the stage for engineering arsenic-tolerant crops. Understanding arsenic (As) toxicity in plants is crucial for environmental and agricultural sustainability, considering the implications of As in impacting soil productivity and environmental health. Although some articles already examined the detailed molecular mechanisms behind As toxicity and tolerance, a comprehensive review of recent omics advancements in studying plant responses to As exposure is needed. The present review highlights the valuable contribution of omics approaches (genomics, transcriptomics, proteomics, and metabolomics) to characterize the intricate response to As overall, which could empower As-tolerant plant development. Genomic techniques, such as QTL mapping, GWAS, RAPD, and SSH, hold the potential to provide valuable insights into the genetic diversity and expression patterns associated with the plant response to As stress, highlighting also the power of new advanced technology such as CRISPR-Cas9. Transcriptomics approaches (e.g., microarrays and RNA sequencing) revealed gene expression patterns in plants under As stress, emphasizing the role of sulfur metabolism in As tolerance. Proteomics, using 2-DE combined with MALDI-ToF MS or ESI-MS/MS, offers insights into the stress-inducible proteins and their involvement in As toxicity mitigation, while iTRAQ-based proteomics enabled an understanding of cultivar-specific responses under high As concentration. Metabolomics, with LC-MS, GC-MS, (U)HPLC, and NMR, elucidated small molecule alterations and complex metabolic activities occurring under As plant exposure. Compendium of data and evidence-related tools offers a foundation for advancing As-tolerant plant development and promoting environmental and agricultural resilience.

Introducing CHiDO-A No Code Genomic Prediction software implementation for the characterization and integration of driven omics

Climate change represents a significant challenge to global food security by altering environmental conditions critical to crop growth. Plant breeders can play a key role in mitigating these challenges by developing more resilient crop varieties; however, these efforts require significant investments in resources and time. In response, it is imperative to use current technologies that assimilate large biological and environmental datasets into predictive models to accelerate the research, development, and release of new improved varieties that can be more resilient to the increasingly variable climatic conditions. Leveraging large and diverse datasets can improve the characterization of phenotypic responses due to environmental stimuli and genomic pulses. A better characterization of these signals holds the potential to enhance our ability to predict trait performance under changes in weather and/or soil conditions with high precision. This paper introduces characterization and integration of driven omics (CHiDO), an easy-to-use, no-code platform designed to integrate diverse omics datasets and effectively model their interactions. With its flexibility to integrate and process datasets, CHiDO's intuitive interface allows users to explore historical data, formulate hypotheses, and optimize data collection strategies for future scenarios. The platform's mission emphasizes global accessibility, democratizing statistical solutions for situations where professional ability in data processing and data analysis is not available.

Integrated transcriptome and metabolome analyses reveals the mechanisms of function loss of Lr29 leaf rust resistance gene at high temperatures in wheat

Leaf rust (LR) is one of the most common diseases of wheat. The resistance gene Lr29 provides wide resistance to LR, but loses its function under high temperatures. Despite the importance of this gene, the mechanism of resistance is unclear. In this study we investigated the resistance mechanism of the Lr29 gene to LR at the seedling stage, as well as the reasons behind the loss of gene function at high temperatures by using integrated transcriptome and metabolome analyses. Results suggests that the pathways of reactive oxygen species (ROS), which could be due to expression of genes including LOX (lipoxygenase), APX (ascorbate peroxidase) and GST (glutathione S-transferase), play a key role in the resistance of Lr29 to LR, furthermore flavonoids, such as epicatechin, cosmosiin, apiin, vitexin and rutin, were identified as the key metabolites linked to Lr29 resistance. We also found that, at high temperatures, Lr29 downregulated the genes and metabolites associated with glycolysis and the tricarboxylic acid (TCA) cycle, while genes and metabolites related to the shikimic acid pathway were upregulated. This study might provide a valuable theoretical foundation for the cloning of the Lr29 gene, the analysis of its disease resistance mechanism, and the understanding of how temperature affects gene function.

Advancing genetic improvement in the omics era: status and priorities for United States aquaculture

BACKGROUND

The innovations of the "Omics Era" have ushered in significant advancements in genetic improvement of agriculturally important animal species through transforming genetics, genomics and breeding strategies. These advancements were often coordinated, in part, by support provided over 30 years through the 1993-2023 National Research Support Project 8 (NRSP8, National Animal Genome Research Program, NAGRP) and affiliate projects focused on enabling genomic discoveries in livestock, poultry, and aquaculture species. These significant and parallel advances demand strategic planning of future research priorities. This paper, as an output from the May 2023 Aquaculture Genomics, Genetics, and Breeding Workshop, provides an updated status of genomic resources for United States aquaculture species, highlighting major achievements and emerging priorities.

MAIN TEXT

Finfish and shellfish genome and omics resources enhance our understanding of genetic architecture and heritability of performance and production traits. The 2023 Workshop identified present aims for aquaculture genomics/omics research to build on this progress: (1) advancing reference genome assembly quality; (2) integrating multi-omics data to enhance analysis of production and performance traits; (3) developing resources for the collection and integration of phenomics data; (4) creating pathways for applying and integrating genomics information across animal industries; and (5) providing training, extension, and outreach to support the application of genome to phenome. Research focuses should emphasize phenomics data collection, artificial intelligence, identifying causative relationships between genotypes and phenotypes, establishing pathways to apply genomic information and tools across aquaculture industries, and an expansion of training programs for the next-generation workforce to facilitate integration of genomic sciences into aquaculture operations to enhance productivity, competitiveness, and sustainability.

CONCLUSION

This collective vision of applying genomics to aquaculture breeding with focus on the highlighted priorities is intended to facilitate the continued advancement of the United States aquaculture genomics, genetics and breeding research community and industries. Critical challenges ahead include the practical application of genomic tools and analytical frameworks beyond academic and research communities that require collaborative partnerships between academia, government, and industry. The scope of this review encompasses the use of omics tools and applications in the study of aquatic animals cultivated for human consumption in aquaculture settings throughout their life-cycle.

Deciphering nutrient stress in plants: integrative insight from metabolomics and proteomics

To comprehend the responses and resilience of plants under unfavorable environmental conditions, it is crucial to study the metabolomics and proteomic insights into nutrient stress. Nutrient stress substantially challenges agriculture, impacting plant growth, development, and productivity due to a lack or imbalance of essential nutrients, which can happen due to poor soil quality, limited nutrient availability, or unfavorable climatic conditions. Although there has been significant progress in the study of plant nutrient stress using metabolomics and proteomics, several challenges and research gaps still need to be addressed, such as the standardized experimental protocols, data integration strategies, and bioinformatic tools are necessary for comparative analysis and interpretation of omics data. Hence, this review explores the theoretical frameworks of metabolomics and proteomics as powerful tools to decode plant responses to nutrient stress, addressing critical knowledge gaps in the field. This review highlights the advantages of integrative analyses, combining metabolomics, proteomics, and transcriptomics, to uncover the molecular networks governing nutrient stress resilience. Key findings underscore the potential of these techniques to enhance breeding strategies and genetic engineering efforts aimed at developing nutrient-efficient crops. Through metabolomics and proteomic analyses, novel molecular components and regulatory networks have been revealed as responsive to nutrient stress, and this breakthrough has the potential to bolster plant resilience and optimize nutrient utilization. Understanding the synergistic roles of metabolites and proteins in nutrient stress resilience has profound implications for crop improvement and agricultural sustainability. Future research should focus on refining integrative methodologies and exploring their applications across diverse plant species and environmental conditions, paving the way for innovative solutions to nutrient stress challenges.

Using Quantitative Trait Locus Mapping and Genomic Resources to Improve Breeding Precision in Peaches: Current Insights and Future Prospects

Modern breeding technologies and the development of quantitative trait locus (QTL) mapping have brought about a new era in peach breeding. This study examines the complex genetic structure that underlies the morphology of peach fruits, paying special attention to the interaction between genome editing, genomic selection, and marker-assisted selection. Breeders now have access to precise tools that enhance crop resilience, productivity, and quality, facilitated by QTL mapping, which has significantly advanced our understanding of the genetic determinants underlying essential traits such as fruit shape, size, and firmness. New technologies like CRISPR/Cas9 and genomic selection enable the development of cultivars that can withstand climate change and satisfy consumer demands with unprecedented precision in trait modification. Genotype-environment interactions remain a critical challenge for modern breeding efforts, which can be addressed through high-throughput phenotyping and multi-environment trials. This work shows how combining genome-wide association studies and machine learning can improve the synthesis of multi-omics data and result in faster breeding cycles while preserving genetic diversity. This study outlines a roadmap that prioritizes the development of superior cultivars utilizing cutting-edge methods and technologies in order to address evolving agricultural and environmental challenges.

Improving transformation and regeneration efficiency in medicinal plants: insights from other recalcitrant species

Medicinal plants are integral to traditional medicine systems worldwide, being pivotal for human health. Harvesting plant material from natural environments, however, has led to species scarcity, prompting action to develop cultivation solutions that also aid conservation efforts. Biotechnological tools, specifically plant tissue culture and genetic transformation, offer solutions for sustainable, large-scale production and enhanced yield of valuable biomolecules. While these techniques are instrumental to the development of the medicinal plant industry, the challenge of inherent regeneration recalcitrance in some species to in vitro cultivation hampers these efforts. This review examines the strategies for overcoming recalcitrance in medicinal plants using a holistic approach, emphasizing the meticulous choice of explants (e.g. embryonic/meristematic tissues), plant growth regulators (e.g. synthetic cytokinins), and use of novel regeneration-enabling methods to deliver morphogenic genes (e.g. GRF/GIF chimeras and nanoparticles), which have been shown to contribute to overcoming recalcitrance barriers in agriculture crops. Furthermore, it highlights the benefit of cost-effective genomic technologies that enable precise genome editing and the value of integrating data-driven models to address genotype-specific challenges in medicinal plant research. These advances mark a progressive step towards a future where medicinal plant cultivation is not only more efficient and predictable but also inherently sustainable, ensuring the continued availability and exploitation of these important plants for current and future generations.

Mapping proteomic response to salinity stress tolerance in oil crops: Towards enhanced plant resilience

Exposure to saline environments significantly hampers the growth and productivity of oil crops, harmfully affecting their nutritional quality and suitability for biofuel production. This presents a critical challenge, as understanding salt tolerance mechanisms in crops is key to improving their performance in coastal and high-salinity regions. Our content might be read more properly: This review assembles current knowledge on protein-level changes related to salinity resistance in oil crops. From an extensive analysis of proteomic research, featured here are key genes and cellular pathways which react to salt stress. The literature evinces that cutting-edge proteomic approaches - such as 2D-DIGE, IF-MS/MS, and iTRAQ - have been required to reveal protein expression patterns in oil crops under salt conditions. These studies consistently uncover dramatic shifts in protein abundance associated with important physiological activities including antioxidant defence, stress-related signalling pathways, ion homeostasis, and osmotic regulation. Notably, proteins like ion channels (SOS1, NHX), osmolytes (proline, glycine betaine), antioxidant enzymes (SOD, CAT), and stress-related proteins (HSPs, LEA) play central roles in maintaining cellular balance and reducing oxidative stress. These findings underline the complex regulatory networks that govern oil crop salt tolerance. The application of this proteomic information can inform breeding and genetic engineering strategies to enhance salt resistance. Future research should aim to integrate multiple omics data to gain a comprehensive view of salinity responses and identify potential markers for crop improvement.

Physiological, transcriptomic, and metabolomic analyses of the chilling stress response in two melon (Cucumis melo L.) genotypes

BACKGROUND

Chilling stress is a key abiotic stress that severely restricts the growth and quality of melon (Cucumis melo L.). Few studies have investigated the mechanism of response to chilling stress in melon.

RESULTS

We characterized the physiological, transcriptomic, and metabolomic response of melon to chilling stress using two genotypes with different chilling sensitivity ("162" and "13-5A"). "162" showed higher osmotic regulation ability and antioxidant capacity to withstand chilling stress. Transcriptome analysis identified 4395 and 4957 differentially expressed genes (DEGs) in "162" and "13-5A" under chilling stress, respectively. Metabolome analysis identified 615 and 489 differential enriched metabolites (DEMs) were identified in "162" and "13-5A" under chilling stress condition, respectively. Integrated transcriptomic and metabolomic analysis showed enrichment of glutathione metabolism, and arginine (Arg) and proline (Pro) metabolism, with differential expression patterns in the two genotypes. Under chilling stress, glutathione metabolism-related DEGs, 6-phosphogluconate dehydrogenase (G6PDH), glutathione peroxidase (GPX), and glutathione s-transferase (GST) were upregulated in "162," and GSH conjugates (L-gamma-glutamyl-L-amino acid and L-glutamate) were accumulated. Additionally, "162" showed upregulation of DEGs encoding ornithine decarboxylase, Pro dehydrogenase, aspartate aminotransferase, pyrroline-5-carboxylate reductase, and spermidine synthase and increased Arg, ornithine, and Pro. Furthermore, the transcription factors (TFs), MYB, ERF, MADS-box, and bZIP were significantly upregulated, suggesting their crucial role in chilling tolerance of melon.

CONCLUSIONS

These findings elucidate the molecular response mechanism to chilling stress in melon and provide insights for breeding chilling-tolerant melon.

Omics based approaches to decipher the leaf ionome and transcriptome changes in Solanum lycopersicum L. upon Tomato Brown Rugose Fruit Virus (ToBRFV) infection

The Tomato Brown Rugose Fruit Virus (ToBRFV) is a pathogen that mostly affects plants from the Solanaceae family. This virus severely affects the yield of tomato (Solanum lycopersicum L.) plants, thus creating an urgent need to research the basis of resistance to manage the disease. To understand the molecular basis of resistance, we employed omics-based approaches involving leaf ionomics and transcriptomics to help us decipher the interaction between elemental and nutritional composition and investigate its effect on the gene expression profile upon the ToBRFV infection in tomatoes. Ionomics was used to investigate the accumulation of trace elements in leaves, showcasing that the plants resistant to the virus had significantly higher concentrations of iron (p-value = 0.039) and nickel (p-value = 0.042) than the susceptible ones. By correlating these findings with transcriptomics, we identified some key genes involved in iron homeostasis and abscisic acid pathways, potentially responsible for conferring resistance against the pathogen. From the obtained list of differentially expressed genes, a panel of mutation profile was discovered with three important genes-Solyc02g068590.3.1 (K+ transporter), Solyc01g111890.3.1 (LRR), and Solyc02g061770.4.1 (Chitinase) showing persistent missense mutations. We ascertain the role of these genes and establish their association with plant resistance using genotyping assays in various tomato lines. The targeted selection of these genetic determinants can further enhance plant breeding and crop yield management strategies.

Integration of CRISPR/Cas9 with multi-omics technologies to engineer secondary metabolite productions in medicinal plant: Challenges and Prospects

Plants acts as living chemical factories that may create a large variety of secondary metabolites, most of which are used in pharmaceutical products. The production of these secondary metabolites is often much lower. Moreover, the primary constraint after discovering potential metabolites is the capacity to manufacture sufficiently for use in industrial and therapeutic contexts. The development of omics technology has brought revolutionary discoveries in various scientific fields, including transcriptomics, metabolomics, and genome sequencing. The metabolic pathways leading to the utilization of new secondary metabolites in the pharmaceutical industry can be identified with the use of these technologies. Genome editing (GEd) is a versatile technology primarily used for site-directed DNA insertions, deletions, replacements, base editing, and activation/repression at the targeted locus. Utilizing GEd techniques such as clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 (CRISPR-associated protein 9), metabolic pathways engineered to synthesize bioactive metabolites optimally. This article will briefly discuss omics and CRISPR/Cas9-based methods to improve secondary metabolite production in medicinal plants.

Advancing Plant Breeding with Next-Generation Technologies: Insights from Recent Research

Genetic resources are the cornerstone of our food supply and play a pivotal role in developing new crop varieties that ensure sustainable agricultural production amid the challenges of climate change [...].

Exploiting Brassica rapa L. subsp. pekinensis Genome Research

Chinese cabbage, Brassica rapa L. subsp. pekinensis is a crucial and extensively consumed vegetable in the world, especially Eastern Asia. The market demand for this leafy vegetable increases year by year, resulting in multiple challenges for agricultural researchers worldwide. Multi-omic approaches and the integration of functional genomics helps us understand the relationships between Chinese cabbage genomes and phenotypes under specific physiological and environmental conditions. However, challenges exist in integrating multi-omics for the functional analysis of genes and for developing potential traits for Chinese cabbage improvement. However, the panomics platform allows for the integration of complex omics, enhancing our understanding of molecular regulator networks in Chinese cabbage agricultural traits. In addition, the agronomic features of Chinese cabbage are significantly impacted by the environment. The expression of these agricultural features is tightly regulated by a combination of signals from both the internal regulatory network and the external growth environment. To comprehend the molecular process of these characteristics, it is necessary to have a prior understanding of molecular breeding for the objective of enhancing quality. While the use of various approaches in Chinese cabbage is still in its early stages, recent research has shown that it has the potential to uncover new regulators both rapidly and effectively, leading to updated regulatory networks. In addition, the utilization of the efficient transformation technique in conjunction with gene editing using CRISPR/Cas9 will result in a reduction in time requirements and facilitate a more precise understanding of the role of the regulators. Numerous studies about Chinese cabbage have been conducted in the past two decades, but a comprehensive review about its genome still limited. This review provides a concise summary of the latest discoveries in genomic research related to Brassica and explores the potential future developments for this species.

Genome-wide analysis and prediction of chloroplast and mitochondrial RNA editing sites of AGC gene family in cotton (Gossypium hirsutum L.) for abiotic stress tolerance

BACKGROUND

Cotton is one of the topmost fiber crops throughout the globe. During the last decade, abrupt changes in the climate resulted in drought, heat, and salinity. These stresses have seriously affected cotton production and significant losses all over the textile industry. The GhAGC kinase, a subfamily of AGC group and member of serine/threonine (Ser/Thr) protein kinases group and is highly conserved among eukaryotic organisms. The AGC kinases are compulsory elements of cell development, metabolic processes, and cell death in mammalian systems. The investigation of RNA editing sites within the organelle genomes of multicellular vascular plants, such as Gossypium hirsutum holds significant importance in understanding the regulation of gene expression at the post-transcriptional level.

METHODS

In present work, we characterized twenty-eight GhAGC genes in cotton and constructed phylogenetic tree using nine different species from the most primitive to the most recent.

RESULTS

In sequence logos analyses, highly conserved amino acid residues were found in G. hirsutum, G. arboretum, G. raimondii and A. thaliana. The occurrence of cis-acting growth and stress-related elements in the promoter regions of GhAGCs highlight the significance of these factors in plant development and abiotic stress tolerance. Ka/Ks levels demonstrated that purifying selection pressure resulting from segmental events was applied to GhAGC with little functional divergence. We focused on identifying RNA editing sites in G. hirsutum organelles, specifically in the chloroplast and mitochondria, across all 28 AGC genes.

CONCLUSION

The positive role of GhAGCs was explored by quantifying the expression in the plant tissues under abiotic stress. These findings help in understanding the role of GhAGC genes under abiotic stresses which may further be used in cotton breeding for the development of climate smart varieties in abruptly changing climate.

Harnessing Multi-Omics Strategies and Bioinformatics Innovations for Advancing Soybean Improvement: A Comprehensive Review

Soybean improvement has entered a new era with the advent of multi-omics strategies and bioinformatics innovations, enabling more precise and efficient breeding practices. This comprehensive review examines the application of multi-omics approaches in soybean-encompassing genomics, transcriptomics, proteomics, metabolomics, epigenomics, and phenomics. We first explore pre-breeding and genomic selection as tools that have laid the groundwork for advanced trait improvement. Subsequently, we dig into the specific contributions of each -omics field, highlighting how bioinformatics tools and resources have facilitated the generation and integration of multifaceted data. The review emphasizes the power of integrating multi-omics datasets to elucidate complex traits and drive the development of superior soybean cultivars. Emerging trends, including novel computational techniques and high-throughput technologies, are discussed in the context of their potential to revolutionize soybean breeding. Finally, we address the challenges associated with multi-omics integration and propose future directions to overcome these hurdles, aiming to accelerate the pace of soybean improvement. This review serves as a crucial resource for researchers and breeders seeking to leverage multi-omics strategies for enhanced soybean productivity and resilience.

Metabolic imaging in living plants: A promising field for chemical exchange saturation transfer (CEST) MRI

Magnetic resonance imaging (MRI) is a versatile technique in the biomedical field, but its application to the study of plant metabolism in vivo remains challenging because of magnetic susceptibility problems. In this study, we report the establishment of chemical exchange saturation transfer (CEST) for plant MRI. This method enables noninvasive access to the metabolism of sugars and amino acids in complex sink organs (seeds, fruits, taproots, and tubers) of major crops (maize, barley, pea, potato, sugar beet, and sugarcane). Because of its high signal detection sensitivity and low susceptibility to magnetic field inhomogeneities, CEST analyzes heterogeneous botanical samples inaccessible to conventional magnetic resonance spectroscopy. The approach provides unprecedented insight into the dynamics and distribution of sugars and amino acids in intact, living plant tissue. The method is validated by chemical shift imaging, infrared microscopy, chromatography, and mass spectrometry. CEST is a versatile and promising tool for studying plant metabolism in vivo, with many applications in plant science and crop improvement.

Calcium signaling regulates the accumulation of phenolic acids in response to UV-B stress in Rhododendron chrysanthum Pall

KEY MESSAGE

This study, using multi-omics combined with physiologic assays, found that calcium-ion signaling can regulate phenolic acid accumulation in R. chrysanthum leaves in response to UV-B stress. UV-B stress is a severe abiotic stress capable of destroying cellular structures and affecting plant growth. Rhododendron chrysanthum Pall. (R. chrysanthum) is a plant that has been exposed to high levels of UV-B radiation for an extended period, leading to the development of adaptive responses to mitigate UV-B stress. As such, it serves as a valuable experimental material for studying plant resilience to UV-B stress. We utilized R. chrysanthum as the experimental material and subjected it to UV-B stress. We conducted a comprehensive analysis of the changes in R. chrysanthum under both control and UV-B stress conditions using multi-omic and physiologic assays. Our aim was to investigate the molecular mechanism underlying R. chrysanthum's resistance to UV-B stress, with a focus on calcium-ion signaling. UV-B stress was found to impact the photosynthesis of R. chrysanthum by decreasing the maximum photosynthetic efficiency of photosystem II, reducing Fm, and increasing F0. In addition, the composition of numerous phenolic acid compounds was significantly altered. Genes and proteins related to calcium signaling showed significant differences, with some proteins (CML, CPK1, CRK3, ATP2C, ERG3, CAR7) being modified by acetylation. The correlation between genes and proteins involved in calcium signaling and phenolic compounds suggested that calcium signaling may play a role in regulating the accumulation of phenolic compounds under UV-B stress to help R. chrysanthum adapt. This study examines the impact of calcium-ion signaling on the accumulation of phenolic acid compounds, offering insights for future research on the molecular mechanisms underlying plant resilience to UV-B stress.

Phenomics in Livestock Research: Bottlenecks and Promises of Digital Phenotyping and Other Quantification Techniques on a Global Scale

Bottlenecks in moving genomics to real-life applications also include phenomics. This is true not only for genomics medicine and public health genomics but also in ecology and livestock phenomics. This expert narrative review explores the intricate relationship between genetic makeup and observable phenotypic traits across various biological levels in the context of livestock research. We unpack and emphasize the significance of precise phenotypic data in selective breeding outcomes and examine the multifaceted applications of phenomics, ranging from improvement to assessing welfare, reproductive traits, and environmental adaptation in livestock. As phenotypic traits exhibit strong correlations, their measurement alongside specific biological outcomes provides insights into performance, overall health, and clinical endpoints like morbidity and disease. In addition, automated assessment of livestock holds potential for monitoring the dynamic phenotypic traits across various species, facilitating a deeper comprehension of how they adapt to their environment and attendant stressors. A key challenge in genetic improvement in livestock is predicting individuals with optimal fitness without direct measurement. Temporal predictions from unmanned aerial systems can surpass genomic predictions, offering in-depth data on livestock. In the near future, digital phenotyping and digital biomarkers may further unravel the genetic intricacies of stress tolerance, adaptation and welfare aspects of animals enabling the selection of climate-resilient and productive livestock. This expert review thus delves into challenges associated with phenotyping and discusses technological advancements shaping the future of biological research concerning livestock.

Fecal microbiota transplantation: current challenges and future landscapes

SUMMARYGiven the importance of gut microbial homeostasis in maintaining health, there has been considerable interest in developing innovative therapeutic strategies for restoring gut microbiota. One such approach, fecal microbiota transplantation (FMT), is the main "whole gut microbiome replacement" strategy and has been integrated into clinical practice guidelines for treating recurrent Clostridioides difficile infection (rCDI). Furthermore, the potential application of FMT in other indications such as inflammatory bowel disease (IBD), metabolic syndrome, and solid tumor malignancies is an area of intense interest and active research. However, the complex and variable nature of FMT makes it challenging to address its precise functionality and to assess clinical efficacy and safety in different disease contexts. In this review, we outline clinical applications, efficacy, durability, and safety of FMT and provide a comprehensive assessment of its procedural and administration aspects. The clinical applications of FMT in children and cancer immunotherapy are also described. We focus on data from human studies in IBD in contrast with rCDI to delineate the putative mechanisms of this treatment in IBD as a model, including colonization resistance and functional restoration through bacterial engraftment, modulating effects of virome/phageome, gut metabolome and host interactions, and immunoregulatory actions of FMT. Furthermore, we comprehensively review omics technologies, metagenomic approaches, and bioinformatics pipelines to characterize complex microbial communities and discuss their limitations. FMT regulatory challenges, ethical considerations, and pharmacomicrobiomics are also highlighted to shed light on future development of tailored microbiome-based therapeutics.

Unraveling the genetic and molecular basis of heat stress in cotton

Human activities and climate change have resulted in frequent and intense weather fluctuations, leading to diverse abiotic stresses on crops which hampers greatly their metabolic activities. Heat stress, a prevalent abiotic factor, significantly influences cotton plant biological activities resulting in reducing yield and production. We must deepen our understanding of how plants respond to heat stress across various dimensions, encompassing genes, RNAs, proteins, metabolites for effective cotton breeding. Multi-omics methods, primarily genomics, transcriptomics, proteomics, metabolomics, and phenomics, proves instrumental in studying cotton's responses to abiotic stresses. Integrating genomics, transcriptomics, proteomics, and metabolomic is imperative for our better understanding regarding genetics and molecular basis of heat tolerance in cotton. The current review explores fundamental omics techniques, covering genomics, transcriptomics, proteomics, and metabolomics, to highlight the progress made in cotton omics research.

Visualizing set relationships: EVenn's comprehensive approach to Venn diagrams

Venn diagrams serve as invaluable tools for visualizing set relationships due to their ease of interpretation. Widely applied across diverse disciplines such as metabolomics, genomics, transcriptomics, and proteomics, their utility is undeniable. However, the operational complexity has been compounded by the absence of standardized data formats and the need to switch between various platforms for generating different Venn diagrams. To address these challenges, we introduce the EVenn platform, a versatile tool offering a unified interface for efficient data exploration and visualization of diverse Venn diagrams. EVenn (http://www.ehbio.com/test/venn) streamlines the data upload process with a standardized format, enhancing the capabilities for multimodule analysis. This comprehensive protocol outlines various applications of EVenn, featuring representative results of multiple Venn diagrams, data uploads in the centralized data center, and step-by-step case demonstrations. Through these functionalities, EVenn emerges as a valuable and user-friendly tool for the in-depth exploration of multiomics data.

Metabolomic Profiling Reveals the Anti-Herbivore Mechanisms of Rice (Oryza sativa)

The use of secondary metabolites of rice to control pests has become a research hotspot, but little is known about the mechanism of rice self-resistance. In this study, metabolomics analysis was performed on two groups of rice (T1, with insect pests; T2, without pests), indicating that fatty acids, alkaloids, and phenolic acids were significantly up-regulated in T1. The up-regulated metabolites (p-value < 0.1) were enriched in linoleic acid metabolism, terpene, piperidine, and pyridine alkaloid biosynthesis, α-linolenic acid metabolism, and tryptophan metabolism. Six significantly up-regulated differential metabolites in T1 were screened out: N-trans-feruloyl-3-methoxytyramine (1), N-trans-feruloyltyramine (2), N-trans-p-coumaroyltyramine (3), N-cis-feruloyltyramine (4), N-phenylacetyl-L-glutamine (5), and benzamide (6). The insect growth inhibitory activities of these six different metabolites were determined, and the results show that compound 1 had the highest activity, which significantly inhibited the growth of Chilo suppressalis by 59.63%. Compounds 2-4 also showed a good inhibitory effect on the growth of Chilo suppressalis, while the other compounds had no significant effect. RNA-seq analyses showed that larval exposure to compound 1 up-regulated the genes that were significantly enriched in ribosome biogenesis in eukaryotes, the cell cycle, ribosomes, and other pathways. The down-regulated genes were significantly enriched in metabolic pathways, oxidative phosphorylation, the citrate cycle (TCA cycle), and other pathways. Eighteen up-regulated genes and fifteen down-regulated genes from the above significantly enriched pathways were screened out and verified by real-time quantitative PCR. The activities of detoxification enzymes (glutathione S-transferase (GST); UDP-glucuronosyltransferase (UGT); and carboxylesterase (CarE)) under larval exposure to compound 1 were measured, which indicated that the activity of GST was significantly inhibited by compound 1, while the activities of the UGT and CarE enzymes did not significantly change. As determined by UPLC-MS, the contents of compound 1 in the T1 and T2 groups were 8.55 ng/g and 0.53 ng/g, respectively, which indicated that pest insects significantly induced the synthesis of compound 1. Compound 1 may enhance rice insect resistance by inhibiting the detoxification enzyme activity and metabolism of Chilo suppressalis, as well as promoting cell proliferation to affect its normal growth and development process. The chemical-ecological mechanism of the insect resistance of rice is preliminarily clarified in this paper.

Integration of targeted metabolome and transcript profiling of Pseudomonas syringae-triggered changes in defence-related phytochemicals in oat plants

MAIN CONCLUSION

A gene-to-metabolite approach afforded new insights regarding defence mechanisms in oat plants that can be incorporated into plant breeding programmes for the selection of markers and genes related to disease resistance. Monitoring metabolite levels and changes therein can complement and corroborate transcriptome (mRNA) data on plant-pathogen interactions, thus revealing mechanisms involved in pathogen attack and host defence. A multi-omics approach thus adds new layers of information such as identifying metabolites with antimicrobial properties, elucidating metabolomic profiles of infected and non-infected plants, and reveals pathogenic requirements for infection and colonisation. In this study, two oat cultivars (Dunnart and SWK001) were inoculated with Pseudomonas syringae pathovars, pathogenic and non-pathogenic on oat. Following inoculation, metabolites were extracted with methanol from leaf tissues at 2, 4 and 6 days post-infection and analysed by multiple reaction monitoring (MRM) on a triple quadrupole mass spectrometer system. Relatedly, mRNA was isolated at the same time points, and the cDNA analysed by quantitative PCR (RT-qPCR) for expression levels of selected gene transcripts associated with avenanthramide (Avn) biosynthesis. The targeted amino acids, hydroxycinnamic acids and Avns were successfully quantified. Distinct cultivar-specific differences in the metabolite responses were observed in response to pathogenic and non-pathogenic strains. Trends in aromatic amino acids and hydroxycinnamic acids seem to indicate stronger activation and flux through these pathways in Dunnart as compared to SWK001. A positive correlation between hydroxycinnamoyl-CoA:hydroxyanthranilate N-hydroxycinnamoyl transferase (HHT) gene expression and the abundance of Avn A in both cultivars was documented. However, transcript profiling of selected genes involved in Avn synthesis did not reveal a clear pattern to distinguish between the tolerant and susceptible cultivars.

Latest Review Papers in Molecular Plant Sciences 2023

Success in sustaining food security in the face of global climate change depends on the multi-disciplinary efforts of plant science, physics, mathematics, and computer sciences, whereby each discipline contributes specific concepts, information, and tools [...].

Deleterious Effects of Heat Stress on the Tomato, Its Innate Responses, and Potential Preventive Strategies in the Realm of Emerging Technologies

The tomato is a fruit vegetable rich in nutritional and medicinal value grown in greenhouses and fields worldwide. It is severely sensitive to heat stress, which frequently occurs with rising global warming. Predictions indicate a 0.2 °C increase in average surface temperatures per decade for the next three decades, which underlines the threat of austere heat stress in the future. Previous studies have reported that heat stress adversely affects tomato growth, limits nutrient availability, hammers photosynthesis, disrupts reproduction, denatures proteins, upsets signaling pathways, and damages cell membranes. The overproduction of reactive oxygen species in response to heat stress is toxic to tomato plants. The negative consequences of heat stress on the tomato have been the focus of much investigation, resulting in the emergence of several therapeutic interventions. However, a considerable distance remains to be covered to develop tomato varieties that are tolerant to current heat stress and durable in the perspective of increasing global warming. This current review provides a critical analysis of the heat stress consequences on the tomato in the context of global warming, its innate response to heat stress, and the elucidation of domains characterized by a scarcity of knowledge, along with potential avenues for enhancing sustainable tolerance against heat stress through the involvement of diverse advanced technologies. The particular mechanism underlying thermotolerance remains indeterminate and requires further elucidatory investigation. The precise roles and interplay of signaling pathways in response to heat stress remain unresolved. The etiology of tomato plants' physiological and molecular responses against heat stress remains unexplained. Utilizing modern functional genomics techniques, including transcriptomics, proteomics, and metabolomics, can assist in identifying potential candidate proteins, metabolites, genes, gene networks, and signaling pathways contributing to tomato stress tolerance. Improving tomato tolerance against heat stress urges a comprehensive and combined strategy including modern techniques, the latest apparatuses, speedy breeding, physiology, and molecular markers to regulate their physiological, molecular, and biochemical reactions.

The role of phenomics and genomics in delineating the genetic basis of complex traits in millets

Millets, comprising a diverse group of small-seeded grains, have emerged as vital crops with immense nutritional, environmental, and economic significance. The comprehension of complex traits in millets, influenced by multifaceted genetic determinants, presents a compelling challenge and opportunity in agricultural research. This review delves into the transformative roles of phenomics and genomics in deciphering these intricate genetic architectures. On the phenomics front, high-throughput platforms generate rich datasets on plant morphology, physiology, and performance in diverse environments. This data, coupled with field trials and controlled conditions, helps to interpret how the environment interacts with genetics. Genomics provides the underlying blueprint for these complex traits. Genome sequencing and genotyping technologies have illuminated the millet genome landscape, revealing diverse gene pools and evolutionary relationships. Additionally, different omics approaches unveil the intricate information of gene expression, protein function, and metabolite accumulation driving phenotypic expression. This multi-omics approach is crucial for identifying candidate genes and unfolding the intricate pathways governing complex traits. The review highlights the synergy between phenomics and genomics. Genomically informed phenotyping targets specific traits, reducing the breeding size and cost. Conversely, phenomics identifies promising germplasm for genomic analysis, prioritizing variants with superior performance. This dynamic interplay accelerates breeding programs and facilitates the development of climate-smart, nutrient-rich millet varieties and hybrids. In conclusion, this review emphasizes the crucial roles of phenomics and genomics in unlocking the genetic enigma of millets.

The complex transcriptional regulation of heat stress response in maize

As one of the most important food and feed crops worldwide, maize suffers much more tremendous damages under heat stress compared to other plants, which seriously inhibits plant growth and reduces productivity. To mitigate the heat-induced damages and adapt to high temperature environment, plants have evolved a series of molecular mechanisms to sense, respond and adapt high temperatures and heat stress. In this review, we summarized recent advances in molecular regulations underlying high temperature sensing, heat stress response and memory in maize, especially focusing on several important pathways and signals in high temperature sensing, and the complex transcriptional regulation of ZmHSFs (Heat Shock Factors) in heat stress response. In addition, we highlighted interactions between ZmHSFs and several epigenetic regulation factors in coordinately regulating heat stress response and memory. Finally, we laid out strategies to systematically elucidate the regulatory network of maize heat stress response, and discussed approaches for breeding future heat-tolerance maize.

Mapping and Omics Integration: Towards Precise Rice Disease Resistance Breeding

Rice (Oryza sativa), as a staple crop feeding a significant portion of the global population, particularly in Asian countries, faces constant threats from various diseases jeopardizing global food security. A precise understanding of disease resistance mechanisms is crucial for developing resilient rice varieties. Traditional genetic mapping methods, such as QTL mapping, provide valuable insights into the genetic basis of diseases. However, the complex nature of rice diseases demands a holistic approach to gain an accurate knowledge of it. Omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, enable a comprehensive analysis of biological molecules, uncovering intricate molecular interactions within the rice plant. The integration of various mapping techniques using multi-omics data has revolutionized our understanding of rice disease resistance. By overlaying genetic maps with high-throughput omics datasets, researchers can pinpoint specific genes, proteins, or metabolites associated with disease resistance. This integration enhances the precision of disease-related biomarkers with a better understanding of their functional roles in disease resistance. The improvement of rice breeding for disease resistance through this integration represents a significant stride in agricultural science because a better understanding of the molecular intricacies and interactions underlying disease resistance architecture leads to a more precise and efficient development of resilient and productive rice varieties. In this review, we explore how the integration of mapping and omics data can result in a transformative impact on rice breeding for enhancing disease resistance.

StCoExpNet: a global co-expression network analysis facilitates identifying genes underlying agronomic traits in potatoes

KEY MESSAGE

We constructed a gene expression atlas and co-expression network for potatoes and identified several novel genes associated with various agronomic traits. This resource will accelerate potato genetics and genomics research. Potato (Solanum tuberosum L.) is the world's most crucial non-cereal food crop and ranks third in food production after wheat and rice. Despite the availability of several potato transcriptome datasets at public databases like NCBI SRA, an effort has yet to be put into developing a global transcriptome atlas and a co-expression network for potatoes. The objectives of our study were to construct a global expression atlas for potatoes using publicly available transcriptome datasets, identify housekeeping and tissue-specific genes, construct a global co-expression network and identify co-expression clusters, investigate the transcriptional complexity of genes involved in various essential biological processes related to agronomic traits, and provide a web server (StCoExpNet) to easily access the newly constructed expression atlas and co-expression network to investigate the expression and co-expression of genes of interest. In this study, we used data from 2299 publicly available potato transcriptome samples obtained from 15 different tissues to construct a global transcriptome atlas. We found that roughly 87% of the annotated genes exhibited detectable expression in at least one sample. Among these, we identified 281 genes with consistent and stable expression levels, indicating their role as housekeeping genes. Conversely, 308 genes exhibited marked tissue-specific expression patterns. We exemplarily linked some co-expression clusters to important agronomic traits of potatoes, such as self-incompatibility, anthocyanin biosynthesis, tuberization, and defense responses against multiple pathogens. The dataset compiled here constitutes a new resource (StCoExpNet), which can be accessed at https://stcoexpnet.julius-kuehn.de . This transcriptome atlas and the co-expression network will accelerate potato genetics and genomics research.

Advances in the Application of Single-Cell Transcriptomics in Plant Systems and Synthetic Biology

Plants are complex systems hierarchically organized and composed of various cell types. To understand the molecular underpinnings of complex plant systems, single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for revealing high resolution of gene expression patterns at the cellular level and investigating the cell-type heterogeneity. Furthermore, scRNA-seq analysis of plant biosystems has great potential for generating new knowledge to inform plant biosystems design and synthetic biology, which aims to modify plants genetically/epigenetically through genome editing, engineering, or re-writing based on rational design for increasing crop yield and quality, promoting the bioeconomy and enhancing environmental sustainability. In particular, data from scRNA-seq studies can be utilized to facilitate the development of high-precision Build-Design-Test-Learn capabilities for maximizing the targeted performance of engineered plant biosystems while minimizing unintended side effects. To date, scRNA-seq has been demonstrated in a limited number of plant species, including model plants (e.g., Arabidopsis thaliana), agricultural crops (e.g., Oryza sativa), and bioenergy crops (e.g., Populus spp.). It is expected that future technical advancements will reduce the cost of scRNA-seq and consequently accelerate the application of this emerging technology in plants. In this review, we summarize current technical advancements in plant scRNA-seq, including sample preparation, sequencing, and data analysis, to provide guidance on how to choose the appropriate scRNA-seq methods for different types of plant samples. We then highlight various applications of scRNA-seq in both plant systems biology and plant synthetic biology research. Finally, we discuss the challenges and opportunities for the application of scRNA-seq in plants.

Transcriptomics, proteomics, and metabolomics interventions prompt crop improvement against metal(loid) toxicity

The escalating challenges posed by metal(loid) toxicity in agricultural ecosystems, exacerbated by rapid climate change and anthropogenic pressures, demand urgent attention. Soil contamination is a critical issue because it significantly impacts crop productivity. The widespread threat of metal(loid) toxicity can jeopardize global food security due to contaminated food supplies and pose environmental risks, contributing to soil and water pollution and thus impacting the whole ecosystem. In this context, plants have evolved complex mechanisms to combat metal(loid) stress. Amid the array of innovative approaches, omics, notably transcriptomics, proteomics, and metabolomics, have emerged as transformative tools, shedding light on the genes, proteins, and key metabolites involved in metal(loid) stress responses and tolerance mechanisms. These identified candidates hold promise for developing high-yielding crops with desirable agronomic traits. Computational biology tools like bioinformatics, biological databases, and analytical pipelines support these omics approaches by harnessing diverse information and facilitating the mapping of genotype-to-phenotype relationships under stress conditions. This review explores: (1) the multifaceted strategies that plants use to adapt to metal(loid) toxicity in their environment; (2) the latest findings in metal(loid)-mediated transcriptomics, proteomics, and metabolomics studies across various plant species; (3) the integration of omics data with artificial intelligence and high-throughput phenotyping; (4) the latest bioinformatics databases, tools and pipelines for single and/or multi-omics data integration; (5) the latest insights into stress adaptations and tolerance mechanisms for future outlooks; and (6) the capacity of omics advances for creating sustainable and resilient crop plants that can thrive in metal(loid)-contaminated environments.

Special Issue "State-of-the-Art Molecular Plant Sciences in Japan"

Food shortages are one of the most serious problems caused by global warming and population growth in this century [...].

Plant biomarkers as early detection tools in stress management in food crops: a review

MAIN CONCLUSION

Plant Biomarkers are objective indicators of a plant's cellular state in response to abiotic and biotic stress factors. They can be explored in crop breeding and engineering to produce stress-tolerant crop species. Global food production safely and sustainably remains a top priority to feed the ever-growing human population, expected to reach 10 billion by 2050. However, abiotic and biotic stress factors negatively impact food production systems, causing between 70 and 100% reduction in crop yield. Understanding the plant stress responses is critical for developing novel crops that can adapt better to various adverse environmental conditions. Using plant biomarkers as measurable indicators of a plant's cellular response to external stimuli could serve as early warning signals to detect stresses before severe damage occurs. Plant biomarkers have received considerable attention in the last decade as pre-stress indicators for various economically important food crops. This review discusses some biomarkers associated with abiotic and biotic stress conditions and highlights their importance in developing stress-resilient crops. In addition, we highlighted some factors influencing the expression of biomarkers in crop plants under stress. The information presented in this review would educate plant researchers, breeders, and agronomists on the significance of plant biomarkers in stress biology research, which is essential for improving plant growth and yield toward sustainable food production.

Drought stress in Lens culinaris: effects, tolerance mechanism, and its smart reprogramming by using modern biotechnological approaches

Among legumes, lentil serves as an imperative source of dietary proteins and are considered an important pillar of global food and nutritional security. The crop is majorly cultivated in arid and semi-arid regions and exposed to different abiotic stresses. Drought stress is a polygenic stress that poses a major threat to the crop productivity of lentils. It negatively influenced the seed emergence, water relations traits, photosynthetic machinery, metabolites, seed development, quality, and yield in lentil. Plants develop several complex physiological and molecular protective mechanisms for tolerance against drought stress. These complicated networks are enabled to enhance the cellular potential to survive under extreme water-scarce conditions. As a result, proper drought stress-mitigating novel and modern approaches are required to improve lentil productivity. The currently existing biotechnological techniques such as transcriptomics, genomics, proteomics, metabolomics, CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/cas9), and detection of QTLs (quantitative trait loci), proteins, and genes responsible for drought tolerance have gained appreciation among plant breeders for developing climate-resilient lentil varieties. In this review, we critically elaborate the impact of drought on lentil, mechanisms employed by plants to tolerate drought, and the contribution of omics approaches in lentils for dealing with drought, providing deep insights to enhance lentil productivity and improve resistance against abiotic stresses. We hope this updated review will directly help the lentil breeders to develop resistance against drought stress.

Graphical Abstract

TCOD: an integrated resource for tropical crops

Tropical crops are vital for tropical agriculture, with resource scarcity, functional diversity and extensive market demand, providing considerable economic benefits for the world's tropical agriculture-producing countries. The rapid development of sequencing technology has promoted a milestone in tropical crop research, resulting in the generation of massive amount of data, which urgently needs an effective platform for data integration and sharing. However, the existing databases cannot fully satisfy researchers' requirements due to the relatively limited integration level and untimely update. Here, we present the Tropical Crop Omics Database (TCOD, https://ngdc.cncb.ac.cn/tcod), a comprehensive multi-omics data platform for tropical crops. TCOD integrates diverse omics data from 15 species, encompassing 34 chromosome-level de novo assemblies, 1 255 004 genes with functional annotations, 282 436 992 unique variants from 2048 WGS samples, 88 transcriptomic profiles from 1997 RNA-Seq samples and 13 381 germplasm items. Additionally, TCOD not only employs genes as a bridge to interconnect multi-omics data, enabling cross-species comparisons based on homology relationships, but also offers user-friendly online tools for efficient data mining and visualization. In short, TCOD integrates multi-species, multi-omics data and online tools, which will facilitate the research on genomic selective breeding and trait biology of tropical crops.

Germplasm Resources and Metabolite Marker Screening of High-Flavonoid Tartary Buckwheat (Fagopyrum tataricum)

Tartary buckwheat is an annual minor cereal crop with a variety of secondary metabolites, endowing it with a high nutritional and medicinal value. Flavonoids constitute the primary compounds of Tartary buckwheat. Recently, metabolomics, as an adjunct breeding method, has been increasingly employed in crop research. This study explores the correlation between the total flavonoid content (TFC) and antioxidant capacity in 167 Tartary buckwheat varieties. Ten Tartary buckwheat varieties with significant differences in flavonoid content and antioxidant capacity were selected by cluster analysis. With the use of liquid chromatography-mass spectrometry, 58 flavonoid compounds were identified, namely, 42 flavonols, 10 flavanols, 3 flavanones, 1 isoflavone, 1 anthocyanidin, and 1 proanthocyanidin. Different samples were clearly separated by employing principal component analysis and partial least-squares discriminant analysis. Eight differential flavonoid compounds were further selected through volcano plots and variable importance in projection. Differential metabolites were highly correlated with TFC and antioxidant capacity. Finally, metabolic markers of kaempferol-3-O-hexoside, kaempferol-7-O-glucoside, and naringenin-O-hexoside were determined by the random forest model. The findings provide a basis for the selection and identification of Tartary buckwheat varieties with high flavonoid content and strong antioxidant activity.

Unveiling changes in rhizosphere-associated bacteria linked to the genotype and water stress in quinoa

Drought is among the main abiotic factors causing agronomical losses worldwide. To minimize its impact, several strategies have been proposed, including the use of plant growth-promoting bacteria (PGPBs), as they have demonstrated roles in counteracting abiotic stress. This aspect has been little explored in emergent crops such as quinoa, which has the potential to contribute to reducing food insecurity. Thus, here we hypothesize that the genotype, water environment and the type of inoculant are determining factors in shaping quinoa rhizosphere bacterial communities, affecting plant performance. To address this, two different quinoa cultivars (with contrasting water stress tolerance), two water conditions (optimal and limiting water conditions) and different soil infusions were used to define the relevance of these factors. Different bacterial families that vary among genotypes and water conditions were identified. Certain families were enriched under water stress conditions, such as the Nocardioidaceae, highly present in the water-sensitive cultivar F15, or the Pseudomonadaceae, Burkholderiaceae and Sphingomonadaceae, more abundant in the tolerant cultivar F16, which also showed larger total polyphenol content. These changes demonstrate that the genotype and environment highly contribute to shaping the root-inhabiting bacteria in quinoa, and they suggest that this plant species is a great source of PGPBs for utilization under water-liming conditions.

Stressing the importance of plant specialized metabolites: omics-based approaches for discovering specialized metabolism in plant stress responses

Plants produce a diverse range of specialized metabolites that play pivotal roles in mediating environmental interactions and stress adaptation. These unique chemical compounds also hold significant agricultural, medicinal, and industrial values. Despite the expanding knowledge of their functions in plant stress interactions, understanding the intricate biosynthetic pathways of these natural products remains challenging due to gene and pathway redundancy, multifunctionality of proteins, and the activity of enzymes with broad substrate specificity. In the past decade, substantial progress in genomics, transcriptomics, metabolomics, and proteomics has made the exploration of plant specialized metabolism more feasible than ever before. Notably, recent advances in integrative multi-omics and computational approaches, along with other technologies, are accelerating the discovery of plant specialized metabolism. In this review, we present a summary of the recent progress in the discovery of plant stress-related specialized metabolites. Emphasis is placed on the application of advanced omics-based approaches and other techniques in studying plant stress-related specialized metabolism. Additionally, we discuss the high-throughput methods for gene functional characterization. These advances hold great promise for harnessing the potential of specialized metabolites to enhance plant stress resilience in the future.