Metabolome-genome-wide association study dissects genetic architecture for generating natural variation in rice secondary metabolism

CropMetabolome: a comprehensive metabolome database for major crops cross eight categories

Chemical compositions of crops are of great agronomical importance, as crops serve as resources for nutrition, energy, and medicines for human and livestock. For crop metabolomics research, the lack of crop reference metabolome and high-quality reference compound mass spectra, as well as utilities for metabolic profiling, has hindered the discovery and functional study of phytochemicals in crops. To meet these challenging needs, we have developed the Crop Metabolome database (abbreviated as CropMetabolome) that is dedicated to the construction of crop reference metabolome, repository, and dissemination of crop metabolomic data, and profiling and analytic tools for metabolomics research. CropMetabolome contains a metabolomics database for more than 50 crops (belonging to eight categories) that integrated self-generated raw mass spectral data and public-source datasets. The reference metabolome for 59 crop species was constructed, which have functions that parallel those of reference genome in genomic studies. CropMetabolome also contains 'Standard compound mass spectral library', 'Flavonoids library', 'Pesticide library', and a set of related analytical tools that enable metabolic profiling based on a reference metabolome (CropRefMetaBlast), annotation and identification of new metabolites (CompoundLibBlast), deducing the structure of novel flavonoid derivatives (FlavoDiscover), and detecting possible residual pesticides in crop samples (PesticiDiscover). In addition, CropMetabolome is a repository to share and disseminate metabolomics data and a platform to promote collaborations to develop reference metabolome for more crop species. CropMetabolome is a comprehensive platform that offers important functions in crop metabolomics research and contributes to improve crop breeding, nutrition, and safety. CropMetabolome is freely available at https://www.cropmetabolome.com/.

A Targeted and an Untargeted Metabolomics Approach to Study the Phytochemicals of Tomato Cultivars Grown Under Different Salinity Conditions

In this study, we evaluated the effect of increasing the salinity of irrigation water on the metabolic content and profiles of two tomato cultivars ('Jaune Flamme' (JF) and 'Red Pear' (RP)) using targeted and untargeted metabolomics approaches. Irrigation of tomato plants was performed with four different salt concentrations provided by chloride (treatment 1) and sulfate (treatment 2) salts. Targeted analysis of the methanolic extract resulted in the identification of nine major polyphenols. Among them, chlorogenic acid, rutin, and naringenin were the prominent compounds in both cultivars. In addition, the quantification of 18 free amino acids from both tomato cultivars showed that different salinity treatments significantly enhanced the levels of glutamine, glutamic acid, and γ-aminobutyric acid (GABA). Using the untargeted metabolomic approach, we identified 129 putative metabolites encompassing a diverse array of phytochemicals including polyphenols, organic acids, lipids, sugars, and amino acids. Principal component analysis (PCA) of mass spectral data acquired under positive and negative ionization modes showed a clear separation between the two cultivars. However, only positive ionization showed separation among different salinity treatments. Unsupervised and supervised learning algorithms were applied to mine the generated data and to pinpoint metabolites different from the two cultivars. These findings suggest that different salinity conditions significantly influenced the accumulation of phytochemicals in tomato cultivars. This study will help tomato breeding programs to develop value-added tomato cultivars under varying environmental conditions.

Genome-wide association studies identify loci controlling specialized seed metabolites in Arabidopsis

Plants synthesize specialized metabolites to facilitate environmental and ecological interactions. During evolution, plants diversified in their potential to synthesize these metabolites. Quantitative differences in metabolite levels of natural Arabidopsis (Arabidopsis thaliana) accessions can be employed to unravel the genetic basis for metabolic traits using genome-wide association studies (GWAS). Here, we performed metabolic GWAS on seeds of a panel of 315 A. thaliana natural accessions, including the reference genotypes C24 and Col-0, for polar and semi-polar seed metabolites using untargeted ultra-performance liquid chromatography-mass spectrometry. As a complementary approach, we performed quantitative trait locus (QTL) mapping of near-isogenic introgression lines between C24 and Col-0 for specific seed specialized metabolites. Besides common QTL between seeds and leaves, GWAS revealed seed-specific QTL for specialized metabolites, indicating differences in the genetic architecture of seeds and leaves. In seeds, aliphatic methylsulfinylalkyl and methylthioalkyl glucosinolates associated with the ALKENYL HYDROXYALKYL PRODUCING loci (GS-ALK and GS-OHP) on chromosome 4 containing alkenyl hydroxyalkyl producing 2 (AOP2) and 3 (AOP3) or with the GS-ELONG locus on chromosome 5 containing methylthioalkyl malate synthase (MAM1) and MAM3. We detected two unknown sulfur-containing compounds that were also mapped to these loci. In GWAS, some of the annotated flavonoids (kaempferol 3-O-rhamnoside-7-O-rhamnoside, quercetin 3-O-rhamnoside-7-O-rhamnoside) were mapped to transparent testa 7 (AT5G07990), encoding a cytochrome P450 75B1 monooxygenase. Three additional mass signals corresponding to quercetin-containing flavonols were mapped to UGT78D2 (AT5G17050). The association of the loci and associating metabolic features were functionally verified in knockdown mutant lines. By performing GWAS and QTL mapping, we were able to leverage variation of natural populations and parental lines to study seed specialized metabolism. The GWAS data set generated here is a high-quality resource that can be investigated in further studies.

Omics-driven exploration and mining of key functional genes for the improvement of food and fiber crops

The deployment of omics technologies has obtained an incredible boost over the past few decades with the advances in next-generation sequencing (NGS) technologies, innovative bioinformatics tools, and the deluge of available biological information. The major omics technologies in the limelight are genomics, transcriptomics, proteomics, metabolomics, and phenomics. These biotechnological advances have modernized crop breeding and opened new horizons for developing crop varieties with improved traits. The genomes of several crop species are sequenced, and a huge number of genes associated with crucial economic traits have been identified. These identified genes not only provide insights into the understanding of regulatory mechanisms of crop traits but also decipher practical grounds to assist in the molecular breeding of crops. This review discusses the potential of omics technologies for the acquisition of biological information and mining of the genes associated with important agronomic traits in important food and fiber crops, such as wheat, rice, maize, potato, tomato, cassava, and cotton. Different functional genomics approaches for the validation of these important genes are also highlighted. Furthermore, a list of genes discovered by employing omics approaches is being represented as potential targets for genetic modifications by the latest genome engineering methods for the development of climate-resilient crops that would in turn provide great impetus to secure global food security.

Metabolic GWAS-based dissection of genetic basis underlying nutrient quality variation and domestication of cassava storage root

BACKGROUND

Metabolites play critical roles in regulating nutritional qualities of plants, thereby influencing their consumption and human health. However, the genetic basis underlying the metabolite-based nutrient quality and domestication of root and tuber crops remain largely unknown.

RESULTS

We report a comprehensive study combining metabolic and phenotypic genome-wide association studies to dissect the genetic basis of metabolites in the storage root (SR) of cassava. We quantify 2,980 metabolic features in 299 cultivated cassava accessions. We detect 18,218 significant marker-metabolite associations via metabolic genome-wide association mapping and identify 12 candidate genes responsible for the levels of metabolites that are of potential nutritional importance. Me3GT, MeMYB4, and UGT85K4/UGT85K5, which are involved in flavone, anthocyanin, and cyanogenic glucoside metabolism, respectively, are functionally validated through in vitro enzyme assays and in vivo gene silencing analyses. We identify a cluster of cyanogenic glucoside biosynthesis genes, among which CYP79D1, CYP71E7b, and UGT85K5 are highly co-expressed and their allelic combination contributes to low linamarin content. We find MeMYB4 is responsible for variations in cyanidin 3-O-glucoside and delphinidin 3-O-rutinoside contents, thus controlling SR endothelium color. We find human selection affects quercetin 3-O-glucoside content and SR weight per plant. The candidate gene MeFLS1 is subject to selection during cassava domestication, leading to decreased quercetin 3-O-glucoside content and thus increased SR weight per plant.

CONCLUSIONS

These findings reveal the genetic basis of cassava SR metabolome variation, establish a linkage between metabolites and agronomic traits, and offer useful resources for genetically improving the nutrition of cassava and other root crops.

Chemical Structure Diversity and Extensive Biological Functions of Specialized Metabolites in Rice

Rice (Oryza sativa L.) is thought to have been domesticated many times independently in China and India, and many modern cultivars are available. All rice tissues are rich in specialized metabolites (SPMs). To date, a total of 181 terpenoids, 199 phenolics, 41 alkaloids, and 26 other types of compounds have been detected in rice. Some volatile sesquiterpenoids released by rice are known to attract the natural enemies of rice herbivores, and play an indirect role in defense. Momilactone, phytocassane, and oryzalic acid are the most common diterpenoids found in rice, and are found at all growth stages. Indolamides, including serotonin, tryptamine, and N-benzoylserotonin, are the main rice alkaloids. The SPMs mainly exhibit defense functions with direct roles in resisting herbivory and pathogenic infections. In addition, phenolics are also important in indirect defense, and enhance wax deposition in leaves and promote the lignification of stems. Meanwhile, rice SPMs also have allelopathic effects and are crucial in the regulation of the relationships between different plants or between plants and microorganisms. In this study, we reviewed the various structures and functions of rice SPMs. This paper will provide useful information and methodological resources to inform the improvement of rice resistance and the promotion of the rice industry.

Plant biochemical genetics in the multiomics era

Our understanding of plant biology has been revolutionized by modern genetics and biochemistry. However, biochemical genetics can be traced back to the foundation of Mendelian genetics; indeed, one of Mendel's milestone discoveries of seven characteristics of pea plants later came to be ascribed to a mutation in a starch branching enzyme. Here, we review both current and historical strategies for the elucidation of plant metabolic pathways and the genes that encode their component enzymes and regulators. We use this historical review to discuss a range of classical genetic phenomena including epistasis, canalization, and heterosis as viewed through the lens of contemporary high-throughput data obtained via the array of approaches currently adopted in multiomics studies.

QT-GWAS: A novel method for unveiling biosynthetic loci affecting qualitative metabolic traits

Although the plant kingdom provides an enormous diversity of metabolites with potentially beneficial applications for humankind, a large fraction of these metabolites and their biosynthetic pathways remain unknown. Resolving metabolite structures and their biosynthetic pathways is key to gaining biological understanding and to allow metabolic engineering. In order to retrieve novel biosynthetic genes involved in specialized metabolism, we developed a novel untargeted method designated as qualitative trait GWAS (QT-GWAS) that subjects qualitative metabolic traits to a genome-wide association study, while the conventional metabolite GWAS (mGWAS) mainly considers the quantitative variation of metabolites. As a proof of the validity of QT-GWAS, 23 and 15 of the retrieved associations identified in Arabidopsis thaliana by QT-GWAS and mGWAS, respectively, were supported by previous research. Furthermore, seven gene-metabolite associations retrieved by QT-GWAS were confirmed in this study through reverse genetics combined with metabolomics and/or in vitro enzyme assays. As such, we established that CYTOCHROME P450 706A5 (CYP706A5) is involved in the biosynthesis of chroman derivatives, UDP-GLYCOSYLTRANSFERASE 76C3 (UGT76C3) is able to hexosylate guanine in vitro and in planta, and SULFOTRANSFERASE 202B1 (SULT202B1) catalyzes the sulfation of neolignans in vitro. Collectively, our study demonstrates that the untargeted QT-GWAS method can retrieve valid gene-metabolite associations at the level of enzyme-encoding genes, even new associations that cannot be found by the conventional mGWAS, providing a new approach for dissecting qualitative metabolic traits.

Characterization of novel loci controlling seed oil content in Brassica napus by marker metabolite-based multi-omics analysis

BACKGROUND

Seed oil content is an important agronomic trait of Brassica napus (B. napus), and metabolites are considered as the bridge between genotype and phenotype for physical traits.

RESULTS

Using a widely targeted metabolomics analysis in a natural population of 388 B. napus inbred lines, we quantify 2172 metabolites in mature seeds by liquid chromatography mass spectrometry, in which 131 marker metabolites are identified to be correlated with seed oil content. These metabolites are then selected for further metabolite genome-wide association study and metabolite transcriptome-wide association study. Combined with weighted correlation network analysis, we construct a triple relationship network, which includes 21,000 edges and 4384 nodes among metabolites, metabolite quantitative trait loci, genes, and co-expression modules. We validate the function of BnaA03.TT4, BnaC02.TT4, and BnaC05.UK, three candidate genes predicted by multi-omics analysis, which show significant impacts on seed oil content through regulating flavonoid metabolism in B. napus.

CONCLUSIONS

This study demonstrates the advantage of utilizing marker metabolites integrated with multi-omics analysis to dissect the genetic basis of agronomic traits in crops.

A metabolome genome-wide association study implicates histidine N-pi-methyltransferase as a key enzyme in N-methylhistidine biosynthesis in Arabidopsis thaliana

A genome-wide association study (GWAS), which uses information on single nucleotide polymorphisms (SNPs) from many accessions, has become a powerful approach to gene identification. A metabolome GWAS (mGWAS), which relies on phenotypic information based on metabolite accumulation, can identify genes that contribute to primary and secondary metabolite contents. In this study, we carried out a mGWAS using seed metabolomic data from Arabidopsis thaliana accessions obtained by liquid chromatography-mass spectrometry to identify SNPs highly associated with the contents of metabolites such as glucosinolates. These SNPs were present in genes known to be involved in glucosinolate biosynthesis, thus confirming the effectiveness of our analysis. We subsequently focused on SNPs detected in an unknown methyltransferase gene associated with N-methylhistidine content. Knockout and overexpression of A. thaliana lines of this gene had significantly decreased and increased N-methylhistidine contents, respectively. We confirmed that the overexpressing line exclusively accumulated histidine methylated at the pi position, not at the tau position. Our findings suggest that the identified methyltransferase gene encodes a key enzyme for N-methylhistidine biosynthesis in A. thaliana.

Natural variation of diterpenoid phytoalexins in rice: Aromatic diterpenoid phytoalexins in specific cultivars

Rice (Oryza sativa L.) plants accumulate antimicrobial compounds known as phytoalexins in response to pathogen attack. To date, more than 20 compounds have been isolated as phytoalexins from rice, mostly diterpenoids. However, the quantitative analysis of diterpenoid phytoalexins in various cultivars has revealed that the cultivar 'Jinguoyin' does not accumulate these compounds at detectable concentrations. Therefore, in this study, we attempted to detect a new class of phytoalexins from Bipolaris oryzae infected leaves of 'Jinguoyin'. We detected five compounds in the leaves of the target cultivar, whereas these compounds were not detected in the leaves of 'Nipponbare' or 'Kasalath', which are representative cultivars of the japonica and indica subspecies. Subsequently, we isolated these compounds from ultraviolet (UV)-light-irradiated leaves and determined their structures by spectroscopic analysis and the crystalline sponge method. All the compounds were diterpenoids containing a benzene ring and were detected from the pathogen-infected rice leaves for the first time. Because the compounds showed antifungal activity against B. oryzae and Pyricularia oryzae, we propose that they function as phytoalexins in rice and named them abietoryzins A-E. The abietoryzins tended to accumulate at high concentrations in cultivars that accumulated low levels of known diterpenoid phytoalexins after UV-light irradiation. Of the total of 69 cultivars in the WRC, 30 cultivars accumulated at least one of the abietoryzins, and, in 15 cultivars, the amounts of some abietoryzins were the highest among those of the analyzed phytoalexins. Therefore, abietoryzins are a major phytoalexin group in rice, although their presence has, to date, been overlooked (252 words).

Exploring the Potential of Multiomics and Other Integrative Approaches for Improving Waterlogging Tolerance in Plants

Soil flooding has emerged as a serious threat to modern agriculture due to the rapid global warming and climate change, resulting in catastrophic crop damage and yield losses. The most detrimental effects of waterlogging in plants are hypoxia, decreased nutrient uptake, photosynthesis inhibition, energy crisis, and microbiome alterations, all of which result in plant death. Although significant advancement has been made in mitigating waterlogging stress, it remains largely enigmatic how plants perceive flood signals and translate them for their adaptive responses at a molecular level. With the advent of multiomics, there has been significant progress in understanding and decoding the intricacy of how plants respond to different stressors which have paved the way towards the development of climate-resistant smart crops. In this review, we have provided the overview of the effect of waterlogging in plants, signaling (calcium, reactive oxygen species, nitric oxide, hormones), and adaptive responses. Secondly, we discussed an insight into past, present, and future prospects of waterlogging tolerance focusing on conventional breeding, transgenic, multiomics, and gene-editing approaches. In addition, we have also highlighted the importance of panomics for developing waterlogging-tolerant cultivars. Furthermore, we have discussed the role of high-throughput phenotyping in the screening of complex waterlogging-tolerant traits. Finally, we addressed the current challenges and future perspectives of waterlogging signal perception and transduction in plants, which warrants future investigation.

Revitalization of small millets for nutritional and food security by advanced genetics and genomics approaches

Small millets, also known as nutri-cereals, are smart foods that are expected to dominate food industries and diets to achieve nutritional security. Nutri-cereals are climate resilient and nutritious. Small millet-based foods are becoming popular in markets and are preferred for patients with celiac and diabetes. These crops once ruled as food and fodder but were pushed out of mainstream cultivation with shifts in dietary habits to staple crops during the green revolution. Nevertheless, small millets are rich in micronutrients and essential amino acids for regulatory activities. Hence, international and national organizations have recently aimed to restore these lost crops for their desirable traits. The major goal in reviving these crops is to boost the immune system of the upcoming generations to tackle emerging pandemics and disease infestations in crops. Earlier periods of civilization consumed these crops, which had a greater significance in ethnobotanical values. Along with nutrition, these crops also possess therapeutic traits and have shown vast medicinal use in tribal communities for the treatment of diseases like cancer, cardiovascular disease, and gastrointestinal issues. This review highlights the significance of small millets, their values in cultural heritage, and their prospects. Furthermore, this review dissects the nutritional and therapeutic traits of small millets for developing sustainable diets in near future.

Metabolomics-centered mining of plant metabolic diversity and function: Past decade and future perspectives

Plants are natural experts in organic synthesis, being able to generate large numbers of specific metabolites with widely varying structures that help them adapt to variable survival challenges. Metabolomics is a research discipline that integrates the capabilities of several types of research including analytical chemistry, statistics, and biochemistry. Its ongoing development provides strategies for gaining a systematic understanding of quantitative changes in the levels of metabolites. Metabolomics is usually performed by targeting either a specific cell, a specific tissue, or the entire organism. Considerable advances in science and technology over the last three decades have propelled us into the era of multi-omics, in which metabolomics, despite at an earlier developmental stage than genomics, transcriptomics, and proteomics, offers the distinct advantage of studying the cellular entities that have the greatest influence on end phenotype. Here, we summarize the state of the art of metabolite detection and identification, and illustrate these techniques with four case study applications: (i) comparing metabolite composition within and between species, (ii) assessing spatio-temporal metabolic changes during plant development, (iii) mining characteristic metabolites of plants in different ecological environments and upon exposure to various stresses, and (iv) assessing the performance of metabolomics as a means of functional gene identification , metabolic pathway elucidation, and metabolomics-assisted breeding through analyzing plant populations with diverse genetic variations. In addition, we highlight the prominent contributions of joint analyses of plant metabolomics and other omics datasets, including those from genomics, transcriptomics, proteomics, epigenomics, phenomics, microbiomes, and ion-omics studies. Finally, we discuss future directions and challenges exploiting metabolomics-centered approaches in understanding plant metabolic diversity.

Tapping into Plant-Microbiome Interactions through the Lens of Multi-Omics Techniques

This review highlights the pivotal role of root exudates in the rhizosphere, especially the interactions between plants and microbes and between plants and plants. Root exudates determine soil nutrient mobilization, plant nutritional status, and the communication of plant roots with microbes. Root exudates contain diverse specialized signaling metabolites (primary and secondary). The spatial behavior of these metabolites around the root zone strongly influences rhizosphere microorganisms through an intimate compatible interaction, thereby regulating complex biological and ecological mechanisms. In this context, we reviewed the current understanding of the biological phenomenon of allelopathy, which is mediated by phytotoxic compounds (called allelochemicals) released by plants into the soil that affect the growth, survival, development, ecological infestation, and intensification of other plant species and microbes in natural communities or agricultural systems. Advances in next-generation sequencing (NGS), such as metagenomics and metatranscriptomics, have opened the possibility of better understanding the effects of secreted metabolites on the composition and activity of root-associated microbial communities. Nevertheless, understanding the role of secretory metabolites in microbiome manipulation can assist in designing next-generation microbial inoculants for targeted disease mitigation and improved plant growth using the synthetic microbial communities (SynComs) tool. Besides a discussion on different approaches, we highlighted the advantages of conjugation of metabolomic approaches with genetic design (metabolite-based genome-wide association studies) in dissecting metabolome diversity and understanding the genetic components of metabolite accumulation. Recent advances in the field of metabolomics have expedited comprehensive and rapid profiling and discovery of novel bioactive compounds in root exudates. In this context, we discussed the expanding array of metabolomics platforms for metabolome profiling and their integration with multivariate data analysis, which is crucial to explore the biosynthesis pathway, as well as the regulation of associated pathways at the gene, transcript, and protein levels, and finally their role in determining and shaping the rhizomicrobiome.

Non-targeted metabolomic analysis for the comparative evaluation of volatile organic compounds in 20 globally representative cucumber lines

Volatile organic compounds (VOCs) are one of the main fruit-quality determinants in cucumber. Here, we investigated the differences in the VOC and primary metabolite composition among 20 representative cucumber lines. Results of non-targeted metabolomics revealed that the cucumber breeding line of the Korean group showed a unique VOC composition in the fruit peel compared to the other groups. Fruit-flesh VOCs significantly differed among Korean, European, and Thai fruits. The main cucumber flavor components, 2-hexenal, hexanal, 6-nonenal, 2,4-nonadienal, and 2,6-nonadienal, were lower in the Korean cucumber lines than in the others. Conversely, linoleic acid derivatives and α-linolenic acid, which are precursors of these VOCs, were abundant in Korean cucumber line. This suggests that the metabolism related to the characteristic flavor of cucumber are downregulated in Korean cucumber line. This study provides novel insights into the fruit flavor-associated metabolome in various cucumber lines.

Dissecting the genetic basis of bioactive metabolites and fruit quality traits in blueberries (Vaccinium corymbosum L.)

Blueberry is well-recognized as a healthy fruit with functionality derived largely from anthocyanin and chlorogenic acid. Despite their importance, no study to date has evaluated the genetic basis of these bioactives in blueberries and their relationship with fruit quality traits. Hence, to fill this gap, a mapping population including 196 F₁ individuals was phenotyped for anthocyanin and chlorogenic acid concentration and fruit quality traits (titratable acidity, pH, and total soluble solids) over 3 years and data were used for QTL mapping and correlation analysis. Total soluble solids and chlorogenic acid were positively correlated with glycosylated anthocyanin and total anthocyanin, respectively, indicating that parallel selection for these traits is possible. Across all the traits, a total of 188 QTLs were identified on chromosomes 1, 2, 4, 8, 9, 11 and 12. Notably, four major regions with overlapping major-effect QTLs were identified on chromosomes 1, 2, 4 and 8, and were responsible for acylation and glycosylation of anthocyanins in a substrate and sugar donor specific manner. Through comparative transcriptome analysis, multiple candidate genes were identified for these QTLs, including glucosyltransferases and acyltransferases. Overall, the study provides the first insights into the genetic basis controlling anthocyanins accumulation and composition, chlorogenic acid and fruit quality traits, and establishes a framework to advance genetic studies and molecular breeding for anthocyanins in blueberry.

Expanding the Coverage of Metabolic Landscape in Cultivated Rice with Integrated Computational Approaches

Genome-scale metabolomics analysis is increasingly used for pathway and function discovery in the post-genomics era. The great potential offered by developed mass spectrometry (MS)-based technologies has been hindered, since only a small portion of detected metabolites were identifiable so far. To address the critical issue of low identification coverage in metabolomics, we adopted a deep metabolomics analysis strategy by integrating advanced algorithms and expanded reference databases. The experimental reference spectra and in silico reference spectra were adopted to facilitate the structural annotation. To further characterize the structure of metabolites, two approaches were incorporated into our strategy, i.e., structural motif search combined with neutral loss scanning and metabolite association network. Untargeted metabolomics analysis was performed on 150 rice cultivars using ultra-performance liquid chromatography coupled with quadrupole-Orbitrap MS. Consequently, a total of 1939 out of 4491 metabolite features in the MS/MS spectral tag (MS2T) library were annotated, representing an extension of annotation coverage by an order of magnitude in rice. The differential accumulation patterns of flavonoids between indica and japonica cultivars were revealed, especially O-sulfated flavonoids. A series of closely-related flavonolignans were characterized, adding further evidence for the crucial role of tricin-oligolignols in lignification. Our study provides an important protocol for exploring phytochemical diversity in other plant species.

Multi-omics analyses of 398 foxtail millet accessions reveal genomic regions associated with domestication, metabolite traits, and anti-inflammatory effects

Foxtail millet (Setaria italica), which was domesticated from the wild species green foxtail (Setaria viridis), is a rich source of phytonutrients for humans. To evaluate how breeding changed the metabolome of foxtail millet grains, we generated and analyzed the datasets encompassing the genomes, transcriptomes, metabolomes, and anti-inflammatory indices from 398 foxtail millet accessions. We identified hundreds of common variants that influence numerous secondary metabolites. We observed tremendous differences in natural variations of the metabolites and their underlying genetic architectures between distinct sub-groups of foxtail millet. Furthermore, we found that the selection of the gene alleles associated with yellow grains led to altered profiles of metabolites such as carotenoids and endogenous phytohormones. Using CRISPR-mediated genome editing we validated the function of PHYTOENE SYNTHASE 1 (PSY1) gene in affecting millet grain color and quality. Interestingly, our in vitro cell inflammation assays showed that 83 metabolites in millet grains have anti-inflammatory effects. Taken together, our multi-omics study illustrates how the breeding history of foxtail millet has shaped its metabolite profile. The datasets we generated in this study also provide important resources for further understanding how millet grain quality is affected by different metabolites, laying the foundations for future millet genetic research and metabolome-assisted improvement.

A Review of Integrative Omic Approaches for Understanding Rice Salt Response Mechanisms

Soil salinity is one of the most serious environmental challenges, posing a growing threat to agriculture across the world. Soil salinity has a significant impact on rice growth, development, and production. Hence, improving rice varieties’ resistance to salt stress is a viable solution for meeting global food demand. Adaptation to salt stress is a multifaceted process that involves interacting physiological traits, biochemical or metabolic pathways, and molecular mechanisms. The integration of multi-omics approaches contributes to a better understanding of molecular mechanisms as well as the improvement of salt-resistant and tolerant rice varieties. Firstly, we present a thorough review of current knowledge about salt stress effects on rice and mechanisms behind rice salt tolerance and salt stress signalling. This review focuses on the use of multi-omics approaches to improve next-generation rice breeding for salinity resistance and tolerance, including genomics, transcriptomics, proteomics, metabolomics and phenomics. Integrating multi-omics data effectively is critical to gaining a more comprehensive and in-depth understanding of the molecular pathways, enzyme activity and interacting networks of genes controlling salinity tolerance in rice. The key data mining strategies within the artificial intelligence to analyse big and complex data sets that will allow more accurate prediction of outcomes and modernise traditional breeding programmes and also expedite precision rice breeding such as genetic engineering and genome editing.

Applications of Genomic Tools in Plant Breeding: Crop Biofortification

Crop breeding has mainly been focused on increasing productivity, either directly or by decreasing the losses caused by biotic and abiotic stresses (that is, incorporating resistance to diseases and enhancing tolerance to adverse conditions, respectively). Quite the opposite, little attention has been paid to improve the nutritional value of crops. It has not been until recently that crop biofortification has become an objective within breeding programs, through either conventional methods or genetic engineering. There are many steps along this long path, from the initial evaluation of germplasm for the content of nutrients and health-promoting compounds to the development of biofortified varieties, with the available and future genomic tools assisting scientists and breeders in reaching their objectives as well as speeding up the process. This review offers a compendium of the genomic technologies used to explore and create biodiversity, to associate the traits of interest to the genome, and to transfer the genomic regions responsible for the desirable characteristics into potential new varieties. Finally, a glimpse of future perspectives and challenges in this emerging area is offered by taking the present scenario and the slow progress of the regulatory framework as the starting point.

Metabolomics: a systems biology approach for enhancing heat stress tolerance in plants

Comprehensive metabolomic investigations provide a large set of stress-related metabolites and metabolic pathways, advancing crops under heat stress conditions. Metabolomics-assisted breeding, including mQTL and mGWAS boosted our understanding of improving numerous quantitative traits under heat stress. During the past decade, metabolomics has emerged as a fascinating scientific field that includes documentation, evaluation of metabolites, and chemical methods for cell monitoring programs in numerous plant species. A comprehensive metabolome profiling allowed the investigator to handle the comprehensive data groups of metabolites and the equivalent metabolic pathways in an extraordinary manner. Metabolomics, together with transcriptomics, plays an influential role in discovering connections between stress and genes/metabolite, phenotyping, and biomarkers documentation. Further, it helps to decode several metabolic systems connected with heat stress (HS) tolerance in plants. Heat stress is a critical environmental factor that is globally affecting the growth and productivity of plants. Thus, there is an urgent need to exploit modern breeding and biotechnological tools like metabolomics to develop cultivars with improved HS tolerance. Several studies have reported that amino acids, carbohydrates, nitrogen metabolisms, etc. and metabolites involved in the biosynthesis and catalyzing actions play a game-changing role in HS response and help plants to cope with the HS. The use of metabolomics-assisted breeding (MAB) allows a well-organized transmission of higher yield and HS tolerance at the metabolome level with specific properties. Progressive metabolomics systematic techniques have accelerated metabolic profiling. Nonetheless, continuous developments in bioinformatics, statistical tools, and databases are allowing us to produce ever-progressing, comprehensive insights into the biochemical configuration of plants and by what means this is inclined by genetic and environmental cues. Currently, assimilating metabolomics with post-genomic platforms has allowed a significant division of genetic-phenotypic connotation in several plant species. This review highlights the potential of a state-of-the-art plant metabolomics approach for the improvement of crops under HS. The development of plants with specific properties using integrated omics (metabolomics and transcriptomics) and MAB can provide new directions for future research to enhance HS tolerance in plants to achieve a goal of "zero hunger".

Nutritional improvement of cereal crops to combat hidden hunger during COVID-19 pandemic: Progress and prospects

COVID-19 has posed a severe challenge on food security by limiting access to food for the marginally placed population. While access to food is a challenge, access to nutritional food is a greater challenge to the population. The present-day foods are not sufficient to meet the nutritional requirements of the human body. In a pandemic condition, providing nutritious food to the population is imperative to ensure the health and well-being of humankind. Exploiting the existing biodiversity of crop species and deploying classical and modern tools to improve the nutritional potential of these species holds the key to addressing the above challenge. Breeding has been a classical tool of crop improvement that relied predominantly on genetic diversity. Collecting and conserving diverse germplasms and characterizing their diversity using molecular markers is essential to preserve diversity and use them in genetic improvement programs. These markers are also valuable for association mapping analyses to identify the genetic determinants of traits-of-interest in crop species. Association mapping identifies the quantitative trait loci (QTL) underlying the trait-of-interest by exploring marker-trait associations, and these QTLs can further be exploited for the genetic improvement of cultivated species through genomics-assisted breeding. Conventional breeding and genomics approaches are also being applied to develop biofortified cereal crops to reduce nutritional deficiencies in consumers. In this context, chapter explains the prerequisites for association mapping, population structure, genetic diversity, different approaches of performing association mapping to dissect nutritional traits, use the information for genomics-assisted breeding for nutrient-rich cereal crops, and application of genomics strategies in crop biofortification. These approaches will ensure food and nutrition security for all amidst the current COVID-19 crisis.

Metabolite Diversity and Metabolic Genome-Wide Marker Association Studies (Mgwas) for Health Benefiting Nutritional Traits in Pearl Millet Grains

As efforts are made to increase food security, millets are gaining increasing importance due to their excellent nutritional credentials. Among the millets, pearl millet is the predominant species possessing several health benefiting nutritional traits in its grain that are helpful in mitigating chronic illnesses such as type−2 diabetes and obesity. In this paper, we conducted metabolomic fingerprinting of 197 pearl millet inbred lines drawn randomly from within the world collection of pearl millet germplasm and report the extent of genetic variation for health benefitting metabolites in these genotypes. Metabolites were extracted from seeds and assessed using flow infusion high-resolution mass spectrometry (FIE-HRMS). Metabolite features (m/z), whose levels significantly differed among the germplasm inbred lines, were identified by ANOVA corrected for FDR and subjected to functional pathway analysis. A number of health-benefiting metabolites linked to dietary starch, antioxidants, vitamins, and lipid metabolism-related compounds were identified. Metabolic genome-wide association analysis (mGWAS) performed using the 396 m/z as phenotypic traits and the 76 K SNP as genotypic variants identified a total of 897 SNPs associated with health benefiting nutritional metabolite at the -log p-value ≤ 4.0. From these associations, 738 probable candidate genes were predicted to have an important role in starch, antioxidants, vitamins, and lipid metabolism. The mGWAS analysis focused on genes involved in starch branching (α-amylase, β-amylase), vitamin-K reductase, UDP-glucuronosyl, and UDP-glucosyl transferase (UGTs), L-ascorbate oxidase, and isoflavone 2′-monooxygenase genes, which are known to be linked to increases in human health benefiting metabolites. We demonstrate how metabolomic, genomic, and statistical approaches can be utilized to pinpoint genetic variations and their functions linked to key nutritional properties in pearl millet, which in turn can be bred into millets and other cereals crops using plant breeding methods.

Metabolomics and complementary techniques to investigate the plant phytochemical cosmos

Covering: up to 2021Plants and their associated microbial communities are known to produce millions of metabolites, a majority of which are still not characterized and are speculated to possess novel bioactive properties. In addition to their role in plant physiology, these metabolites are also relevant as existing and next-generation medicine candidates. Elucidation of the plant metabolite diversity is thus valuable for the successful exploitation of natural resources for humankind. Herein, we present a comprehensive review on recent metabolomics approaches to illuminate molecular networks in plants, including chemical isolation and enzymatic production as well as the modern metabolomics approaches such as stable isotope labeling, ultrahigh-resolution mass spectrometry, metabolome imaging (spatial metabolomics), single-cell analysis, cheminformatics, and computational mass spectrometry. Mass spectrometry-based strategies to characterize plant metabolomes through metabolite identification and annotation are described in detail. We also highlight the use of phytochemical genomics to mine genes associated with specialized metabolites' biosynthesis. Understanding the metabolic diversity through biotechnological advances is fundamental to elucidate the functions of the plant-derived specialized metabolome.

Exploring the genic resources underlying metabolites through mGWAS and mQTL in wheat: From large-scale gene identification and pathway elucidation to crop improvement

Common wheat (Triticum aestivum L.) is a leading cereal crop, but has lagged behind with respect to the interpretation of the molecular mechanisms of phenotypes compared with other major cereal crops such as rice and maize. The recently available genome sequence of wheat affords the pre-requisite information for efficiently exploiting the potential molecular resources for decoding the genetic architecture of complex traits and identifying valuable breeding targets. Meanwhile, the successful application of metabolomics as an emergent large-scale profiling methodology in several species has demonstrated this approach to be accessible for reaching the above goals. One such productive avenue is combining metabolomics approaches with genetic designs. However, this trial is not as widespread as that for sequencing technologies, especially when the acquisition, understanding, and application of metabolic approaches in wheat populations remain more difficult and even arguably underutilized. In this review, we briefly introduce the techniques used in the acquisition of metabolomics data and their utility in large-scale identification of functional candidate genes. Considerable progress has been made in delivering improved varieties, suggesting that the inclusion of information concerning these metabolites and genes and metabolic pathways enables a more explicit understanding of phenotypic traits and, as such, this procedure could serve as an -omics-informed roadmap for executing similar improvement strategies in wheat and other species.

Genome-wide association studies: assessing trait characteristics in model and crop plants

GWAS involves testing genetic variants across the genomes of many individuals of a population to identify genotype–phenotype association. It was initially developed and has proven highly successful in human disease genetics. In plants genome-wide association studies (GWAS) initially focused on single feature polymorphism and recombination and linkage disequilibrium but has now been embraced by a plethora of different disciplines with several thousand studies being published in model and crop species within the last decade or so. Here we will provide a comprehensive review of these studies providing cases studies on biotic resistance, abiotic tolerance, yield associated traits, and metabolic composition. We also detail current strategies of candidate gene validation as well as the functional study of haplotypes. Furthermore, we provide a critical evaluation of the GWAS strategy and its alternatives as well as future perspectives that are emerging with the emergence of pan-genomic datasets.

Toward the identification of molecular markers associated with phytochemical traits in the Iranian sumac (Rhus coriaria L.) population

Sumac (Rhus coriaria L.) is one of the important forest species dispersed in the northwest of Iran. It is one of the important spice in Iran and the Middle East because of active components containing organic acids, phenolic acids, flavonoids, anthocyanins, tannins and terpenoids. This study aimed to investigate population structure and linkage disequilibrium (LD) extent within Rhus coriaria L. genotypes using ISSR markers and identify molecular markers associated with phytochemical traits using association analysis. In the molecular part of the experiment, the genetic diversity of 75 sumac genotypes from five different areas of northwest Iran was assessed by 18 ISSR primers. In the phenotypic assessment, the fruits of the sumac genotypes were analyzed using HPLC-LC/MSMS for determining phytochemical components including maleic acid, ellagic acid, maleic acid hexoside, gallic acid, coumaric acid, quercetin, caftaric acid, and linoleic acid. The phenotypic data analysis revealed the great phenotypic diversity among and within Iranian sumac populations for the studied phytochemical traits. The studied sumac genotypes were divided into two subpopulations based on molecular marker-based structure analysis. A significant level of LD was observed in 11.64% of the ISSR marker pairs (p < .05). The mixed linear model procedure showed that 12 loci had a significant association with investigated traits. The ISSR loci identified in this study can be potentially used in marker-assisted selection in sumac breeding programs.

Positive selective sweeps of epigenetic mutations regulating specialized metabolites in plants

DNA methylation is an important factor regulating gene expression in organisms. However, whether DNA methylation plays a key role in adaptive evolution is unknown. Here, we show evidence of naturally selected DNA methylation in Arabidopsis thaliana. In comparison with single nucleotide polymorphisms, three types of methylation—methylated CGs (mCGs), mCHGs, and mCHHs—contributed highly to variable gene expression levels among an A. thaliana population. Such variably expressed genes largely affect a large variation of specialized metabolic quantities. Among the three types of methylations, only mCGs located in promoter regions of genes associated with specialized metabolites show a selective sweep signature in the A. thaliana population. Thus, naturally selected mCGs appear to be key mutations that cause the expressional diversity associated with specialized metabolites during plant evolution.

Comparing Metabolites and Functional Properties of Various Tomatoes Using Mass Spectrometry-Based Metabolomics Approach

Tomato is one of the world's most consumed vegetables, and thus, various cultivars have been developed. Therefore, metabolic differences and nutrient contents of various tomatoes need to be discovered. To do so, we performed metabolite profiling along with evaluation of morphological and physicochemical properties of five representative tomato types. Common tomato cultivars, bigger and heavier than other tomatoes, contained higher levels of amino acids, organic acids, and lipids. On the contrary, cherry tomato cultivars contained a higher proportion of phenylpropanoids, lycopene, β-carotene, and α-carotene than the other tomatoes. Also, the highest antioxidant activity and total phenolic and flavonoid contents were observed in cherry tomato cultivars. Furthermore, to understand metabolic distributions in various tomato cultivars, we constructed a metabolic pathway map. The higher metabolic flux distribution of most primary metabolite synthetic pathways was observed in common tomatoes, while cherry tomato cultivars showed a significantly elevated flux in secondary metabolite synthetic pathways. Accordingly, these results provide valuable information of different characteristics in various tomatoes, which can be considered while purchasing and improving tomato cultivars.

Understanding Omics Driven Plant Improvement and de novo Crop Domestication: Some Examples

In the current era, one of biggest challenges is to shorten the breeding cycle for rapid generation of a new crop variety having high yield capacity, disease resistance, high nutrient content, etc. Advances in the "-omics" technology have revolutionized the discovery of genes and bio-molecules with remarkable precision, resulting in significant development of plant-focused metabolic databases and resources. Metabolomics has been widely used in several model plants and crop species to examine metabolic drift and changes in metabolic composition during various developmental stages and in response to stimuli. Over the last few decades, these efforts have resulted in a significantly improved understanding of the metabolic pathways of plants through identification of several unknown intermediates. This has assisted in developing several new metabolically engineered important crops with desirable agronomic traits, and has facilitated the de novo domestication of new crops for sustainable agriculture and food security. In this review, we discuss how "omics" technologies, particularly metabolomics, has enhanced our understanding of important traits and allowed speedy domestication of novel crop plants.

Translating insights from the seed metabolome into improved prediction for lipid-composition traits in oat (Avena sativa L.)

Oat (Avena sativa L.) seed is a rich resource of beneficial lipids, soluble fiber, protein, and antioxidants, and is considered a healthful food for humans. Little is known regarding the genetic controllers of variation for these compounds in oat seed. We characterized natural variation in the mature seed metabolome using untargeted metabolomics on 367 diverse lines and leveraged this information to improve prediction for seed quality traits. We used a latent factor approach to define unobserved variables that may drive covariance among metabolites. One hundred latent factors were identified, of which 21% were enriched for compounds associated with lipid metabolism. Through a combination of whole-genome regression and association mapping, we show that latent factors that generate covariance for many metabolites tend to have a complex genetic architecture. Nonetheless, we recovered significant associations for 23% of the latent factors. These associations were used to inform a multi-kernel genomic prediction model, which was used to predict seed lipid and protein traits in two independent studies. Predictions for 8 of the 12 traits were significantly improved compared to genomic best linear unbiased prediction when this prediction model was informed using associations from lipid-enriched factors. This study provides new insights into variation in the oat seed metabolome and provides genomic resources for breeders to improve selection for health-promoting seed quality traits. More broadly, we outline an approach to distill high-dimensional "omics" data to a set of biologically meaningful variables and translate inferences on these data into improved breeding decisions.

Mass spectrometry based untargeted metabolomics for plant systems biology

Untargeted metabolomics enables the identification of key changes to standard pathways, but also aids in revealing other important and possibly novel metabolites or pathways for further analysis. Much progress has been made in this field over the past decade and yet plant metabolomics seems to still be an emerging approach because of the high complexity of plant metabolites and the number one challenge of untargeted metabolomics, metabolite identification. This final and critical stage remains the focus of current research. The intention of this review is to give a brief current state of LC–MS based untargeted metabolomics approaches for plant specific samples and to review the emerging solutions in mass spectrometer hardware and computational tools that can help predict a compound's molecular structure to improve the identification rate.

Metabolomics Intervention Towards Better Understanding of Plant Traits

The majority of the most economically important plant and crop species are enriched with the availability of high-quality reference genome sequences forming the basis of gene discovery which control the important biochemical pathways. The transcriptomics and proteomics resources have also been made available for many of these plant species that intensify the understanding at expression levels. However, still we lack integrated studies spanning genomics–transcriptomics–proteomics, connected to metabolomics, the most complicated phase in phenotype expression. Nevertheless, for the past few decades, emphasis has been more on metabolome which plays a crucial role in defining the phenotype (trait) during crop improvement. The emergence of modern high throughput metabolome analyzing platforms have accelerated the discovery of a wide variety of biochemical types of metabolites and new pathways, also helped in improving the understanding of known existing pathways. Pinpointing the causal gene(s) and elucidation of metabolic pathways are very important for development of improved lines with high precision in crop breeding. Along with other-omics sciences, metabolomics studies have helped in characterization and annotation of a new gene(s) function. Hereby, we summarize several areas in the field of crop development where metabolomics studies have made its remarkable impact. We also assess the recent research on metabolomics, together with other omics, contributing toward genetic engineering to target traits and key pathway(s).

Applications of Multi-Omics Technologies for Crop Improvement

Multiple "omics" approaches have emerged as successful technologies for plant systems over the last few decades. Advances in next-generation sequencing (NGS) have paved a way for a new generation of different omics, such as genomics, transcriptomics, and proteomics. However, metabolomics, ionomics, and phenomics have also been well-documented in crop science. Multi-omics approaches with high throughput techniques have played an important role in elucidating growth, senescence, yield, and the responses to biotic and abiotic stress in numerous crops. These omics approaches have been implemented in some important crops including wheat (Triticum aestivum L.), soybean (Glycine max), tomato (Solanum lycopersicum), barley (Hordeum vulgare L.), maize (Zea mays L.), millet (Setaria italica L.), cotton (Gossypium hirsutum L.), Medicago truncatula, and rice (Oryza sativa L.). The integration of functional genomics with other omics highlights the relationships between crop genomes and phenotypes under specific physiological and environmental conditions. The purpose of this review is to dissect the role and integration of multi-omics technologies for crop breeding science. We highlight the applications of various omics approaches, such as genomics, transcriptomics, proteomics, metabolomics, phenomics, and ionomics, and the implementation of robust methods to improve crop genetics and breeding science. Potential challenges that confront the integration of multi-omics with regard to the functional analysis of genes and their networks as well as the development of potential traits for crop improvement are discussed. The panomics platform allows for the integration of complex omics to construct models that can be used to predict complex traits. Systems biology integration with multi-omics datasets can enhance our understanding of molecular regulator networks for crop improvement. In this context, we suggest the integration of entire omics by employing the "phenotype to genotype" and "genotype to phenotype" concept. Hence, top-down (phenotype to genotype) and bottom-up (genotype to phenotype) model through integration of multi-omics with systems biology may be beneficial for crop breeding improvement under conditions of environmental stresses.

Using Metabolomics to Assist Plant Breeding

Recent methodological advances in both gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) have provided a deep understanding of metabolic regulation occurring in plant cells. The application of these techniques to agricultural systems is, however, subject to more complex interactions. Here we summarize a step-by-step modern metabolomics methodology that generates metabolome data toward the implementation of metabolomics in crop breeding. We describe a metabolic workflow, and provide guidelines for handling large sample numbers for the specific purpose of metabolic quantitative trait loci approaches.

Promoting Human Nutrition and Health through Plant Metabolomics: Current Status and Challenges

Simple Summary

This review summarizes the status, applications, and challenges of plant metabolomics in the context of crop breeding, food quality and safety, and human nutrition and health. It also highlights the importance of plant metabolomics in elucidating biochemical and genetic bases of traits associated with nutritive and healthy beneficial foods and other plant products to secure food supply, to ensure food quality, to protect humans from malnutrition and other diseases. Meanwhile, this review calls for comprehensive collaborations to accelerate relevant researches and applications in the context of human nutrition and health.

Abstract

Plant metabolomics plays important roles in both basic and applied studies regarding all aspects of plant development and stress responses. With the improvement of living standards, people need high quality and safe food supplies. Thus, understanding the pathways involved in the biosynthesis of nutritionally and healthily associated metabolites in plants and the responses to plant-derived biohazards in humans is of equal importance to meet people’s needs. For each, metabolomics has a vital role to play, which is discussed in detail in this review. In addition, the core elements of plant metabolomics are highlighted, researches on metabolomics-based crop improvement for nutrition and safety are summarized, metabolomics studies on plant natural products including traditional Chinese medicine (TCM) for health promotion are briefly presented. Challenges are discussed and future perspectives of metabolomics as one of the most important tools to promote human nutrition and health are proposed.

Identification of a lipase gene with a role in tomato fruit short-chain fatty acid-derived flavor volatiles by genome-wide association

Fatty acid-derived volatile organic compounds (FA-VOCs) make significant contributions to tomato (Solanum lycopersicum) fruit flavor and human preferences. Short-chain FA-VOCs (C5 and C6) are among the most abundant and important volatile compounds in tomato fruits. The precursors of these volatiles, linoleic acid (18:2) and linolenic acid (18:3), are derived from cleavage of glycerolipids. However, the initial step in synthesis of these FA-VOCs has not been established. A metabolite-based genome-wide association study combined with genetic mapping and functional analysis identified a gene encoding a novel class III lipase family member, Sl-LIP8, that is associated with accumulation of short-chain FA-VOCs in tomato fruit. In vitro assays indicated that Sl-LIP8 can cleave 18:2 and 18:3 acyl groups from glycerolipids. A CRISPR/Cas9 gene edited Sl-LIP8 mutant had much lower content of multiple fruit short-chain FA-VOCs, validating an important role for this enzyme in the pathway. Sl-LIP8 RNA abundance was correlated with FA-VOC content, consistent with transcriptional regulation of the first step in the pathway. Taken together, our work indicates that glycerolipid turnover by Sl-LIP8 is an important early step in the synthesis of multiple short-chain FA-VOCs.

Quantitative trait loci analysis of seed-specialized metabolites reveals seed-specific flavonols and differential regulation of glycoalkaloid content in tomato

Given the potential health benefits (and adverse effects), of polyphenolic and steroidal glycoalkaloids in the diet there is a growing interest in fully elucidating the genetic control of their levels in foodstuffs. Here we carried out profiling of the specialized metabolites in the seeds of the Solanum pennellii introgression lines identifying 338 putative metabolite quantitative trait loci (mQTL) for flavonoids, steroidal glycoalkaloids and further specialized metabolites. Two putative mQTL for flavonols and one for steroidal glycoalkaloids were cross-validated by evaluation of the metabolite content of recombinants harboring smaller introgression in the corresponding QTL interval or by analysis of lines from an independently derived backcross inbred line population. The steroidal glycoalkaloid mQTL was localized to a chromosomal region spanning 14 genes, including a previously defined steroidal glycoalkaloid gene cluster. The flavonoid mQTL was further validated via the use of transient and stable overexpression of the Solyc12g098600 and Solyc12g096870 genes, which encode seed-specific uridine 5'-diphosphate-glycosyltransferases. The results are discussed in the context of our understanding of the accumulation of polyphenols and steroidal glycoalkaloids, and how this knowledge may be incorporated into breeding strategies aimed at improving nutritional aspects of plants as well as in fortifying them against abiotic stress.

Comparative Metabolome and Transcriptome Analyses of Susceptible Asparagus officinalis and Resistant Wild A. kiusianus Reveal Insights into Stem Blight Disease Resistance

Phomopsis asparagi is one of the most serious fungal pathogens, which causes stem blight disease in Asparagus officinalis (AO), adversely affecting its production worldwide. Recently, the development of novel asparagus varieties using wild Asparagus genetic resources with natural P. asparagi resistance has become a priority in Japan due to the lack of resistant commercial AO cultivars. In this study, comparative metabolome and transcriptome analyses of susceptible AO and resistant wild Asparagus kiusianus (AK) 24 and 48 h postinoculated (AOI_24 hpi, AOI_48 hpi, AKI_24 hpi and AKI_48 hpi, respectively) with P. asparagi were conducted to gain insights into metabolic and expression changes associated with AK species. Following infection, the resistant wild AK showed rapid metabolic changes with increased levels of flavonoids and steroidal saponins and decreased asparagusic acid glucose ester content, compared with the susceptible AO plants. Transcriptome data revealed a total of 21  differentially expressed genes (DEGs) as the core gene set that displayed upregulation in the resistant AK versus susceptible AO after infection with P. asparagi. Kyoto Encyclopedia of Genes and Genomes pathway analysis of these DEGs identified 11 significantly enriched pathways, including flavonoid biosynthesis and primary metabolite metabolism, in addition to plant signaling and defense-related pathways. In addition, comparative single-nucleotide polymorphism and Indel distributions in susceptible AO and resistant AK plants were evaluated using the latest AO reference genome Aspof.V1. The data generated in this study are important resources for advancing Asparagus breeding programs and for investigations of genetic linkage mapping, phylogenetic diversity and plant defense-related genes.

Metabolomics analysis reveals differences in evolution between maize and rice

Metabolites are the intermediate and final products of metabolism, which play essential roles in plant growth, evolution and adaptation to changing climates. However, it is unclear how evolution contributes to metabolic variation in plants. Here, we investigated the metabolomics data from leaf and seed tissues in maize and rice. Using principal components analysis based on leaf metabolites but not seed metabolites, metabolomics data could be clearly separated for rice Indica and Japonica accessions, while two maize subgroups, temperate and tropical, showed more visible admixture. Rice and maize seed exhibited significant interspecific differences in metabolic variation, while within rice, leaf and seed displayed similar metabolic variations. Among 10 metabolic categories, flavonoids had higher variation in maize than rice, indicating flavonoids are a key constituent of interspecific metabolic divergence. Interestingly, metabolic regulation was also found to be reshaped dramatically from positive to negative correlations, indicative of the differential evolutionary processes in maize and rice. Moreover, perhaps due to this divergence significantly more metabolic interactions were identified in rice than maize. Furthermore, in rice, the leaf was found to harbor much more intense metabolic interactions than the seed. Our result suggests that metabolomes are valuable for tracking evolutionary history, thereby complementing and extending genomic insights concerning which features are responsible for interspecific differentiation in maize and rice.

Metabolomics analysis and metabolite-agronomic trait associations using kernels of wheat (Triticum aestivum) recombinant inbred lines

Plants produce numerous metabolites that are important for their development and growth. However, the genetic architecture of the wheat metabolome has not been well studied. Here, utilizing a high-density genetic map, we conducted a comprehensive metabolome study via widely targeted LC-MS/MS to analyze the wheat kernel metabolism. We further combined agronomic traits and dissected the genetic relationship between metabolites and agronomic traits. In total, 1260 metabolic features were detected. Using linkage analysis, 1005 metabolic quantitative trait loci (mQTLs) were found distributed unevenly across the genome. Twenty-four candidate genes were found to modulate the levels of different metabolites, of which two were functionally annotated by in vitro analysis to be involved in the synthesis and modification of flavonoids. Combining the correlation analysis of metabolite-agronomic traits with the co-localization of methylation quantitative trait locus (mQTL) and phenotypic QTL (pQTL), genetic relationships between the metabolites and agronomic traits were uncovered. For example, a candidate was identified using correlation and co-localization analysis that may manage auxin accumulation, thereby affecting number of grains per spike (NGPS). Furthermore, metabolomics data were used to predict the performance of wheat agronomic traits, with metabolites being found that provide strong predictive power for NGPS and plant height. This study used metabolomics and association analysis to better understand the genetic basis of the wheat metabolism which will ultimately assist in wheat breeding.

Network-based strategies in metabolomics data analysis and interpretation: from molecular networking to biological interpretation

INTRODUCTION

Metabolomics has become a crucial part of systems biology; however, data analysis is still often undertaken in a reductionist way focusing on changes in individual metabolites. Whilst such approaches indeed provide relevant insights into the metabolic phenotype of an organism, the intricate nature of metabolic relationships may be better explored when considering the whole system.

AREAS COVERED

This review highlights multiple network strategies that can be applied for metabolomics data analysis from different perspectives including: association networks based on quantitative information, mass spectra similarity networks to assist metabolite annotation and biochemical networks for systematic data interpretation. We also highlight some relevant insights into metabolic organization obtained through the exploration of such approaches.

EXPERT OPINION

Network based analysis is an established method that allows the identification of non-intuitive metabolic relationships as well as the identification of unknown compounds in mass spectrometry. Additionally, the representation of data from metabolomics within the context of metabolic networks is intuitive and allows for the use of statistical analysis that can better summarize relevant metabolic changes from a systematic perspective.

Genome-Phenome Wide Association in Maize and Arabidopsis Identifies a Common Molecular and Evolutionary Signature

Linking natural genetic variation to trait variation can help determine the functional roles ofdifferent genes. Variations of one or several traits are often assessed separately. High-throughput phenotyping and data mining can capture dozens or hundreds of traits from the same individuals. Here, we test the association between markers within a gene and many traits simultaneously. This genome-phenome wide association study (GPWAS) is both a multi-marker and multi-trait test. Genes identified using GPWAS with 260 phenotypic traits in maize were enriched for genes independently linked to phenotypic variation. Traits associated with classical mutants were consistent with reported phenotypes for mutant alleles. Genes linked to phenomic variation in maize using GPWAS shared molecular, population genetic, and evolutionary features with classical mutants in maize. Genes linked to phenomic variation in Arabidopsis using GPWAS are significantly enriched in genes with known loss-of-function phenotypes. GPWAS may be an effective strategy to identify genes in which loss-of-function alleles produce mutant phenotypes. The shared signatures present in classical mutants and genes identified using GPWAS may be markers for genes with a role in specifying plant phenotypes generally or pleiotropy specifically.

The style and substance of plant flavonoid decoration; towards defining both structure and function

Over 8000 different flavonoids have been described and a considerable number of new flavonoid structures are being elucidated every year. The advent of metabolomics alongside the development of phytochemical genetics - wherein the genetic basis underlying the regulation of the levels of plant metabolites is determined - has provided a massive boost to such efforts. That said our understanding of the individual function(s) of the vast majority of the metabolites that constitute this important class of phytochemicals remains unknown. Here we review what is known concerning the major decorative modifications of flavonoids in plants, namely hydroxylation, glycosylation, methylation and acylation. Our major focus is with regard to the in planta function of these modified compounds, however, we also highlight the demonstrated bioactive roles which they possess. We additionally performed a comprehensive survey of the flavonoids listed in the KNApSAcK database in order to assess the frequency of occurrence of each type of flavonoid modification. We conclude that whilst considerable research has been carried out regarding the biological roles of flavonoids most studies to date have merely provided information on the compound class or sub-classes thereof as a whole with too little currently known on the specific role of individual metabolites. We, therefore, finally suggest a framework based on currently available tools by which the relative importance of the individual compounds can be assessed under various biological conditions in order to fill this knowledge-gap.

Diversity in Metabolites and Fruit Quality Traits in Blueberry Enables Ploidy and Species Differentiation and Establishes a Strategy for Future Genetic Studies

Blueberry is well recognized as a rich source of health promoting phytochemicals such as flavonoids and phenolic acids. Multiple studies in blueberry and other crops indicated that flavonoids and phenolic acids function as bioactive compounds in the human body promoting multiple health effects. Despite their importance, information is limited about the levels of variation in bioactive compounds within and between ploidy level and species, and their association with fruit quality traits. Such information is crucial to define a strategy to study the genetic mechanisms controlling these traits and to select for these traits in blueberry breeding programs. Here we evaluated 33 health related phytochemicals belonging to four major groups of flavonoids and phenolic acids across 128 blueberry accessions over two years together with fruit quality traits, including fruit weight, titratable acidity, total soluble acids and pH. Highly significant variation between accessions, years, and accession by year interaction were identified for most of the traits. Cluster analysis grouped phytochemicals by their functional structure (e.g., anthocyanins, flavanols, flavonols, and phenolic acids). Multivariate analysis of the traits resulted in separation of diploid, tetraploid and hexaploid accessions. Broad sense heritability of the traits estimated in 100 tetraploid accessions, ranged from 20 to 90%, with most traits revealing moderate to high broad sense heritability (H² > 40%), suggesting that strong genetic factors control these traits. Fruit size can be estimated as a proxy of fruit weight or volume and vice versa, and it was negatively correlated with content of most of phytochemicals evaluated here. However, size-independent variation for anthocyanin content and profile (e.g., acylated vs. non-acylated anthocyanin) exists in the tetraploid accessions and can be explored to identify other factors such as genes related to the biosynthetic pathway that control this trait. This result also suggests that metabolite concentrations and fruit size, to a certain degree can be improved simultaneously in breeding programs. Overall, the results of this study provide a framework to uncover the genetic basis of bioactive compounds and fruit quality traits and will be useful to advance blueberry-breeding programs focusing on integrating these traits.

The Genetic Basis and Nutritional Benefits of Pigmented Rice Grain

Improving the nutritional quality of rice grains through modulation of bioactive compounds and micronutrients represents an efficient means of addressing nutritional security in societies which depend heavily on rice as a staple food. White rice makes a major contribution to the calorific intake of Asian and African populations, but its nutritional quality is poor compared to that of pigmented (black, purple, red orange, or brown) variants. The compounds responsible for these color variations are the flavonoids anthocyanin and proanthocyanidin, which are known to have nutritional value. The rapid progress made in the technologies underlying genome sequencing, the analysis of gene expression and the acquisition of global 'omics data, genetics of grain pigmentation has created novel opportunities for applying molecular breeding to improve the nutritional value and productivity of pigmented rice. This review provides an update on the nutritional value and health benefits of pigmented rice grain, taking advantage of both indigenous and modern knowledge, while also describing the current approaches taken to deciphering the genetic basis of pigmentation.

Pathway-specific enzymes from bamboo and crop leaves biosynthesize anti-nociceptive C-glycosylated flavones

C-glycosylated flavones (CGFs) are promising candidates as anti-nociceptive compounds. The leaves of bamboo and related crops in the grass family are a largely unexploited bioresource with a wide array of CGFs. We report here pathway-specific enzymes including C-glycosyltransferases (CGTs) and P450 hydroxylases from cereal crops and bamboo species accumulating abundant CGFs. Mining of CGTs and engineering of P450s that decorate the flavonoid skeleton allowed the production of desired CGFs (with yield of 20–40 mg/L) in an Escherichia coli cell factory. We further explored the antinociceptive activity of major CGFs in mice models and identified isoorientin as the most potent, with both neuroanalgesic and anti-inflammatory effects superior to clinical drugs such as rotundine and aspirin. Our discovery of the pain-alleviating flavonoids elicited from bamboo and crop leaves establishes this previously underutilized source, and sheds light on the pathway and pharmacological mechanisms of the compounds.

Yuwei Sun, Zhuo Chen, Jingya Yang et al. identify bamboo as a rich source of C-glycosylated flavonoids that reduces pain and inflammation. They identify isoorientin as the most potent C-glycosylated flavonoid, superior to aspirin, and report new enzymes that synthesize pain-alleviating C-glycosylated flavonoids.

Metabolomics: A Way Forward for Crop Improvement

Metabolomics is an emerging branch of "omics" and it involves identification and quantification of metabolites and chemical footprints of cellular regulatory processes in different biological species. The metabolome is the total metabolite pool in an organism, which can be measured to characterize genetic or environmental variations. Metabolomics plays a significant role in exploring environment-gene interactions, mutant characterization, phenotyping, identification of biomarkers, and drug discovery. Metabolomics is a promising approach to decipher various metabolic networks that are linked with biotic and abiotic stress tolerance in plants. In this context, metabolomics-assisted breeding enables efficient screening for yield and stress tolerance of crops at the metabolic level. Advanced metabolomics analytical tools, like non-destructive nuclear magnetic resonance spectroscopy (NMR), liquid chromatography mass-spectroscopy (LC-MS), gas chromatography-mass spectrometry (GC-MS), high performance liquid chromatography (HPLC), and direct flow injection (DFI) mass spectrometry, have sped up metabolic profiling. Presently, integrating metabolomics with post-genomics tools has enabled efficient dissection of genetic and phenotypic association in crop plants. This review provides insight into the state-of-the-art plant metabolomics tools for crop improvement. Here, we describe the workflow of plant metabolomics research focusing on the elucidation of biotic and abiotic stress tolerance mechanisms in plants. Furthermore, the potential of metabolomics-assisted breeding for crop improvement and its future applications in speed breeding are also discussed. Mention has also been made of possible bottlenecks and future prospects of plant metabolomics.