Applications of Multi-Omics Technologies for Crop Improvement

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.

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.

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.

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.

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.

Deep learning-empowered crop breeding: intelligent, efficient and promising

Crop breeding is one of the main approaches to increase crop yield and improve crop quality. However, the breeding process faces challenges such as complex data, difficulties in data acquisition, and low prediction accuracy, resulting in low breeding efficiency and long cycle. Deep learning-based crop breeding is a strategy that applies deep learning techniques to improve and optimize the breeding process, leading to accelerated crop improvement, enhanced breeding efficiency, and the development of higher-yielding, more adaptive, and disease-resistant varieties for agricultural production. This perspective briefly discusses the mechanisms, key applications, and impact of deep learning in crop breeding. We also highlight the current challenges associated with this topic and provide insights into its future application prospects.

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.

SoyDBean: a database for SNPs reconciliation by multiple versions of soybean reference genomes

Due to the development of sequence technology and decreased cost, many whole genome sequences have been obtained. As a result, extensive genetic variations have been discovered from many populations and germplasms to understand the genetic diversity of soybean (Glycine max [L.] Merr.). However, assessing the quality of variation is essential because the published variants were collected using different bioinformatic methods and parameters. Furthermore, despite the enhanced genome contiguity and more efficient filling of "N" stretches in the new reference genome, there remains a dearth of endeavors to verify the caliber of variations present in it. The primary goal of this research was to discern a dependable set of SNPs that can withstand reconciliation across multiple reference genomes. Additionally, the investigation aimed to reconfirm the variations through the utilization of numerous whole genome sequencing data obtained from publicly available databases. Based on the result, we created datasets that comprised the thoroughly verified SNP coordinates between the reference assemblies. The resulting "SoyDBean" database is now publicly accessible through the following URL: http://soydbean.plantprofile.net/ .

Subcellular Proteomics to Elucidate Soybean Response to Abiotic Stress

Climate change jeopardizes soybean production by declining seed yield and quality. In this review, the morphophysiological alterations of soybean in response to abiotic stress are summarized, followed by illustrations of cellular metabolisms and regulatory mechanisms to organellar stress based on subcellular proteomics. This highlights the communications associated with reactive oxygen species scavenging, molecular chaperones, and phytohormone signals among subcellular compartments. Given the complexity of climate change and the limitations of plants in coping with multiple abiotic stresses, a generic response to environmental constraints is proposed between calcium and abscisic acid signals in subcellular organelles. This review summarizes the findings of subcellular proteomics in stressed soybean and discusses the future prospects of subcellular proteomics for promoting the improvement of climate-tolerant crops.

Integrative time-scale and multi-omics analysis of host responses to viroid infection

Viroids are circular RNAs of minimal complexity compelled to subvert plant-regulatory networks to accomplish their infectious process. Studies focused on the response to viroid-infection have mostly addressed specific regulatory levels and considered specifics infection-times. Thus, much remains to be done to understand the temporal evolution and complex nature of viroid-host interactions. Here we present an integrative analysis of the temporal evolution of the genome-wide alterations in cucumber plants infected with hop stunt viroid (HSVd) by integrating differential host transcriptome, sRNAnome and methylome. Our results support that HSVd promotes the redesign of the cucumber regulatory-pathways predominantly affecting specific regulatory layers at different infection-phases. The initial response was characterised by a reconfiguration of the host-transcriptome by differential exon-usage, followed by a progressive transcriptional downregulation modulated by epigenetic changes. Regarding endogenous small RNAs, the alterations were limited and mainly occurred at the late stage. Significant host-alterations were predominantly related to the downregulation of transcripts involved in plant-defence mechanisms, the restriction of pathogen-movement and the systemic spreading of defence signals. We expect that these data constituting the first comprehensive temporal-map of the plant-regulatory alterations associated with HSVd infection could contribute to elucidate the molecular basis of the yet poorly known host-response to viroid-induced pathogenesis.

Twenty years of mining salt tolerance genes in soybean

Current combined challenges of rising food demand, climate change and farmland degradation exert enormous pressure on agricultural production. Worldwide soil salinization, in particular, necessitates the development of salt-tolerant crops. Soybean, being a globally important produce, has its genetic resources increasingly examined to facilitate crop improvement based on functional genomics. In response to the multifaceted physiological challenge that salt stress imposes, soybean has evolved an array of defences against salinity. These include maintaining cell homeostasis by ion transportation, osmoregulation, and restoring oxidative balance. Other adaptations include cell wall alterations, transcriptomic reprogramming, and efficient signal transduction for detecting and responding to salt stress. Here, we reviewed functionally verified genes that underly different salt tolerance mechanisms employed by soybean in the past two decades, and discussed the strategy in selecting salt tolerance genes for crop improvement. Future studies could adopt an integrated multi-omic approach in characterizing soybean salt tolerance adaptations and put our existing knowledge into practice via omic-assisted breeding and gene editing. This review serves as a guide and inspiration for crop developers in enhancing soybean tolerance against abiotic stresses, thereby fulfilling the role of science in solving real-life problems.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01383-3.

Transgressive and parental dominant gene expression and cytosine methylation during seed development in Brassica napus hybrids

KEY MESSAGE

Transcriptomic and epigenomic profiling of gene expression and small RNAs during seed and seedling development reveals expression and methylation dominance levels with implications on early stage heterosis in oilseed rape. The enhanced performance of hybrids through heterosis remains a key aspect in plant breeding; however, the underlying mechanisms are still not fully elucidated. To investigate the potential role of transcriptomic and epigenomic patterns in early expression of hybrid vigor, we investigated gene expression, small RNA abundance and genome-wide methylation in hybrids from two distant Brassica napus ecotypes during seed and seedling developmental stages using next-generation sequencing. A total of 31117, 344, 36229 and 7399 differentially expressed genes, microRNAs, small interfering RNAs and differentially methylated regions were identified, respectively. Approximately 70% of the differentially expressed or methylated features displayed parental dominance levels where the hybrid followed the same patterns as the parents. Via gene ontology enrichment and microRNA-target association analyses during seed development, we found copies of reproductive, developmental and meiotic genes with transgressive and paternal dominance patterns. Interestingly, maternal dominance was more prominent in hypermethylated and downregulated features during seed formation, contrasting to the general maternal gamete demethylation reported during gametogenesis in angiosperms. Associations between methylation and gene expression allowed identification of putative epialleles with diverse pivotal biological functions during seed formation. Furthermore, most differentially methylated regions, differentially expressed siRNAs and transposable elements were in regions that flanked genes without differential expression. This suggests that differential expression and methylation of epigenomic features may help maintain expression of pivotal genes in a hybrid context. Differential expression and methylation patterns during seed formation in an F₁ hybrid provide novel insights into genes and mechanisms with potential roles in early heterosis.

BnIR: A multi-omics database with various tools for Brassica napus research and breeding

In the post-genome-wide association study era, multi-omics techniques have shown great power and potential for candidate gene mining and functional genomics research. However, due to the lack of effective data integration and multi-omics analysis platforms, such techniques have not still been applied widely in rapeseed, an important oil crop worldwide. Here, we report a rapeseed multi-omics database (BnIR; http://yanglab.hzau.edu.cn/BnIR), which provides datasets of six omics including genomics, transcriptomics, variomics, epigenetics, phenomics, and metabolomics, as well as numerous "variation-gene expression-phenotype" associations by using multiple statistical methods. In addition, a series of multi-omics search and analysis tools are integrated to facilitate the browsing and application of these datasets. BnIR is the most comprehensive multi-omics database for rapeseed so far, and two case studies demonstrated its power to mine candidate genes associated with specific traits and analyze their potential regulatory mechanisms.

Integrated transcriptome and metabolome analysis reveals that flavonoids function in wheat resistance to powdery mildew

Powdery mildew is a fungal disease devastating to wheat, causing significant quality and yield loss. Flavonoids are important secondary plant metabolites that confer resistance to biotic and abiotic stress. However, whether they play a role in powdery mildew resistance in wheat has yet to be explored. In the present study, we combined transcriptome and metabolome analyses to compare differentially expressed genes (DEGs) and differentially accumulated flavonoids identified in plants with and without powdery mildew inoculation. Transcriptome analysis identified 4,329 DEGs in susceptible wheat cv. Jimai229, and 8,493 in resistant cv. HHG46. The DEGs were functionally enriched using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, revealing the flavonoid synthesis pathway as the most significant in both cultivars. This was consistent with the upregulation of flavonoid synthesis pathway genes observed by quantitative PCR. Metabolome analysis indicated flavone and flavonol biosynthesis pathways as the most significantly enriched following powdery mildew inoculation. An accumulation of total flavonoids content was also found to be induced by powdery mildew infection. Exogenous flavonoids treatment of inoculated plants led to less severe infection, with fewer and smaller powdery mildew spots on the wheat leaves. This reduction is speculated to be regulated through malondialdehyde content and the activities of peroxidase and catalase. Our study provides a fundamental theory for further exploration of the potential of flavonoids as biological prevention and control agents against powdery mildew in wheat.

Evaluation of Sustainable Recycled Products to Increase the Production of Nutraceutical and Antibacterial Molecules in Basil Plants by a Combined Metabolomic Approach

BACKGROUND

An important goal of modern medicine is the development of products deriving from natural sources to improve environmental sustainability. In this study, humic substances (HS) and compost teas (CTs) extracted from artichoke (ART) and coffee grounds (COF) as recycled biomasses were employed on Ocimum basilicum plants to optimize the yield of specific metabolites with nutraceutical and antibacterial features by applying sustainable strategies.

METHODS

The molecular characteristics of compost derivates were elucidated by Nuclear Magnetic Resonance spectroscopy to investigate the structure-activity relationship between organic extracts and their bioactive potential. Additionally, combined untargeted and targeted metabolomics workflows were applied to plants treated with different concentrations of compost extracts.

RESULTS

The substances HS-ART and CT-COF improved both antioxidant activity (TEAC values between 39 and 55 μmol g^-1) and the antimicrobial efficacy (MIC value between 3.7 and 1.3 μg mL^-1) of basil metabolites. The metabolomic approach identified about 149 metabolites related to the applied treatments. Targeted metabolite quantification further highlighted the eliciting effect of HS-ART and CT-COF on the synthesis of aromatic amino acids and phenolic compounds for nutraceutical application.

CONCLUSIONS

The combination of molecular characterization, biological assays, and an advanced metabolomic approach, provided innovative insight into the valorization of recycled biomass to increase the availability of natural compounds employed in the medical field.

EASY-FIA: A Readably Usable Standalone Tool for High-Resolution Mass Spectrometry Metabolomics Data Pre-Processing

Flow injection analysis coupled with high-resolution mass spectrometry (FIA-HRMS) is a fair trade-off between resolution and speed. However, free software available for data pre-processing is few, web-based, and often requires advanced user specialization. These tools rarely embedded blank and noise evaluation strategies, and direct feature annotation. We developed EASY-FIA, a free standalone application that can be employed for FIA-HRMS metabolomic data pre-processing by users with no bioinformatics/programming skills. We validated the tool's performance and applicability in two clinical metabolomics case studies. The main functions of our application are blank subtraction, alignment of the metabolites, and direct feature annotation by means of the Human Metabolome Database (HMDB) using a minimum number of mass spectrometry parameters. In a scenario where FIA-HRMS is increasingly recognized as a reliable strategy for fast metabolomics analysis, EASY-FIA could become a standardized and feasible tool easily usable by all scientists dealing with MS-based metabolomics. EASY-FIA was implemented in MATLAB with the App Designer tool and it is freely available for download.

Multi-omics revolution to promote plant breeding efficiency

Crop production is the primary goal of agricultural activities, which is always taken into consideration. However, global agricultural systems are coming under increasing pressure from the rising food demand of the rapidly growing world population and changing climate. To address these issues, improving high-yield and climate-resilient related-traits in crop breeding is an effective strategy. In recent years, advances in omics techniques, including genomics, transcriptomics, proteomics, and metabolomics, paved the way for accelerating plant/crop breeding to cope with the changing climate and enhance food production. Optimized omics and phenotypic plasticity platform integration, exploited by evolving machine learning algorithms will aid in the development of biological interpretations for complex crop traits. The precise and progressive assembly of desire alleles using precise genome editing approaches and enhanced breeding strategies would enable future crops to excel in combating the changing climates. Furthermore, plant breeding and genetic engineering ensures an exclusive approach to developing nutrient sufficient and climate-resilient crops, the productivity of which can sustainably and adequately meet the world's food, nutrition, and energy needs. This review provides an overview of how the integration of omics approaches could be exploited to select crop varieties with desired traits.

Combined transcriptome and metabolome analyses reveal the mechanisms of ultrasonication improvement of brown rice germination

This study investigated the effects of ultrasonication treatment on the germination rate of brown rice. Brown rice grains were subjected to ultrasound (40 kHz/30 min) and then incubated for 36 h at 37 °C to germinate the seeds. Ultrasonic treatment increased the germination rate of brown rice by up to ∼28 % at 30 h. Transcriptomic and metabolomic analyses were performed to explore the mechanisms underlying the effect of ultrasonic treatment on the brown rice germination rate. Comparing the treated and control check samples, 867 differentially expressed genes (DEGs) were identified, including 638 upregulated and 229 downregulated), as well as 498 differentially accumulated metabolites (DAMs), including 422 up accumulated and 76 down accumulated. Multi-omics analysis revealed that the germination rate of brown rice was promoted by increased concentrations of low-molecular metabolites (carbohydrates and carbohydrate conjugates, fatty acids, amino acids, peptides, and analogues), and transcription factors (ARR-B, NAC, bHLH and AP2/EREBP families) as well as increased carbon metabolism. These findings provide new insights into the mechanisms of action of ultrasound in improving the brown rice germination rate and candidate DEGs and DAMs responsible for germination have been identified.

Integrative Omics Analysis of Three Oil Palm Varieties Reveals (Tanzania × Ekona) TE as a Cold-Resistant Variety in Response to Low-Temperature Stress

Oil palm (Elaeis guineensis Jacq.) is an economically important tropical oil crop widely cultivated in tropical zones worldwide. Being a tropical crop, low-temperature stress adversely affects the oil palm. However, integrative leaf transcriptomic and proteomic analyses have not yet been conducted on an oil palm crop under cold stress. In this study, integrative omics transcriptomic and iTRAQ-based proteomic approaches were employed for three oil palm varieties, i.e., B × E (Bamenda × Ekona), O × G (E. oleifera × Elaeis guineensis), and T × E (Tanzania × Ekona), in response to low-temperature stress. In response to low-temperature stress at (8 °C) for 5 days, a total of 5175 up- and 2941 downregulated DEGs in BE-0_VS_BE-5, and a total of 3468 up- and 2443 downregulated DEGs for OG-0_VS_OG-5, and 3667 up- and 2151 downregulated DEGs for TE-0_VS_TE-5 were identified. iTRAQ-based proteomic analysis showed 349 up- and 657 downregulated DEPs for BE-0_VS_BE-5, 372 up- and 264 downregulated DEPs for OG-0_VS_OG-5, and 500 up- and 321 downregulated DEPs for TE-0_VS_TE-5 compared to control samples treated at 28 °C and 8 °C, respectively. The KEGG pathway correlation of oil palm has shown that the metabolic synthesis and biosynthesis of secondary metabolites pathways were significantly enriched in the transcriptome and proteome of the oil palm varieties. The correlation expression pattern revealed that TE-0_VS_TE-5 is highly expressed and BE-0_VS_BE-5 is suppressed in both the transcriptome and proteome in response to low temperature. Furthermore, numerous transcription factors (TFs) were found that may regulate cold acclimation in three oil palm varieties at low temperatures. Moreover, this study identified proteins involved in stresses (abiotic, biotic, oxidative, and heat shock), photosynthesis, and respiration in iTRAQ-based proteomic analysis of three oil palm varieties. The increased abundance of stress-responsive proteins and decreased abundance of photosynthesis-related proteins suggest that the TE variety may become cold-resistant in response to low-temperature stress. This study may provide a basis for understanding the molecular mechanism for the adaptation of oil palm varieties in response to low-temperature stress in China.

From single- to multi-omics: future research trends in medicinal plants

Medicinal plants are the main source of natural metabolites with specialised pharmacological activities and have been widely examined by plant researchers. Numerous omics studies of medicinal plants have been performed to identify molecular markers of species and functional genes controlling key biological traits, as well as to understand biosynthetic pathways of bioactive metabolites and the regulatory mechanisms of environmental responses. Omics technologies have been widely applied to medicinal plants, including as taxonomics, transcriptomics, metabolomics, proteomics, genomics, pangenomics, epigenomics and mutagenomics. However, because of the complex biological regulation network, single omics usually fail to explain the specific biological phenomena. In recent years, reports of integrated multi-omics studies of medicinal plants have increased. Until now, there have few assessments of recent developments and upcoming trends in omics studies of medicinal plants. We highlight recent developments in omics research of medicinal plants, summarise the typical bioinformatics resources available for analysing omics datasets, and discuss related future directions and challenges. This information facilitates further studies of medicinal plants, refinement of current approaches and leads to new ideas.

Molecular Breeding and Drought Tolerance in Chickpea

Cicer arietinum L. is the third greatest widely planted imperative pulse crop worldwide, and it belongs to the Leguminosae family. Drought is the utmost common abiotic factor on plants, distressing their water status and limiting their growth and development. Chickpea genotypes have the natural ability to fight drought stress using certain strategies viz., escape, avoidance and tolerance. Assorted breeding methods, including hybridization, mutation, and marker-aided breeding, genome sequencing along with omics approaches, could be used to improve the chickpea germplasm lines(s) against drought stress. Root features, for instance depth and root biomass, have been recognized as the greatest beneficial morphological factors for managing terminal drought tolerance in the chickpea. Marker-aided selection, for example, is a genomics-assisted breeding (GAB) strategy that can considerably increase crop breeding accuracy and competence. These breeding technologies, notably marker-assisted breeding, omics, and plant physiology knowledge, underlined the importance of chickpea breeding and can be used in future crop improvement programmes to generate drought-tolerant cultivars(s).