Untargeted metabolic quantitative trait loci analyses reveal a relationship between primary metabolism and potato tuber quality

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.

Plant Metabolomics: Current Initiatives and Future Prospects

Plant metabolomics is a rapidly advancing field of plant sciences and systems biology. It involves comprehensive analyses of small molecules (metabolites) in plant tissues and cells. These metabolites include a wide range of compounds, such as sugars, amino acids, organic acids, secondary metabolites (e.g., alkaloids and flavonoids), lipids, and more. Metabolomics allows an understanding of the functional roles of specific metabolites in plants' physiology, development, and responses to biotic and abiotic stresses. It can lead to the identification of metabolites linked with specific traits or functions. Plant metabolic networks and pathways can be better understood with the help of metabolomics. Researchers can determine how plants react to environmental cues or genetic modifications by examining how metabolite profiles change under various crop stages. Metabolomics plays a major role in crop improvement and biotechnology. Integrating metabolomics data with other omics data (genomics, transcriptomics, and proteomics) provides a more comprehensive perspective of plant biology. This systems biology approach enables researchers to understand the complex interactions within organisms.

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.

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.

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.

Genetic mapping of maize metabolites using high-throughput mass profiling

Plant metabolites are the basis of human nutrition and have biological relevance in ecology. Farmers selected plants with favorable characteristics since prehistoric times and improved the cultivars, but without knowledge of underlying mechanisms. Understanding the genetic basis of metabolite production can facilitate the successful breeding of plants with augmented nutritional value. To identify genetic factors related to the metabolic composition in maize, we generated mass profiles of 198 recombinant inbred lines (RILs) and their parents (B73 and Mo17) using direct-injection electrospray ionization mass spectrometry (DLI-ESI MS). Mass profiling allowed the correct clustering of samples according to genotype. We quantified 71 mass features from grains and 236 mass features from leaf extracts. For the corresponding ions, we identified tissue-specific metabolic 'Quantitative Trait Loci' (mQTLs) distributed across the maize genome. These genetic regions could regulate multiple metabolite biosynthesis pathways. Our findings demonstrate that DLI-ESI MS has sufficient analytical resolution to map mQTLs. These identified genetic loci will be helpful in metabolite-focused maize breeding. Mass profiling is a powerful tool for detecting mQTLs in maize and enables the high-throughput screening of loci responsible for metabolite biosynthesis.

A Role for Allantoate Amidohydrolase (AtAAH) in the Germination of Arabidopsis thaliana Seeds

Seed dormancy is a very complex trait controlled by interactions between genetic and environmental factors. Nitrate is inversely correlated with seed dormancy in Arabidopsis. This is explained by the fact that seed dry storage (after-ripening) reduces the need for nitrogen for germination. When nitrate is absorbed by plants, it is first reduced to nitrite and then to ammonium for incorporation into amino acids, nucleic acids and chlorophyll. Previously, we showed that ALLANTOATE AMIDOHYDROLASE (AtAAH) transcripts are up-regulated in imbibed dormant seeds compared with after-ripened seeds. AAH is an enzyme in the uric acid catabolic pathway which catalyzes the hydrolysis of allantoate to yield CO2, NH3 and S-ureidoglycine. This pathway is the final stage of purine catabolism, and functions in plants and some bacteria to provide nitrogen, particularly when other nitrogen sources are depleted. Ataah mutant seeds are more dormant and accumulate high levels of allantoate, allantoin and urea, whereas energy-related metabolites and several amino acids are lower upon seed imbibition in comparison with Columbia-0. AtAAH expression could be detected during the early stages of seed development, with a transient increase around 8 d after pollination. AtAAH expression is the highest in mature pollen. The application of exogenous potassium nitrate can partly complement the higher dormancy phenotype of the Ataah mutant seeds, whereas other nitrogen sources cannot. Our results indicate that potassium nitrate does not specifically overcome the alleviated dormancy levels in Ataah mutant seeds, but promotes germination in general. Possible pathways by which AtAAH affects seed germination are discussed.

4D genetic networks reveal the genetic basis of metabolites and seed oil-related traits in 398 soybean RILs

Background

The yield and quality of soybean oil are determined by seed oil-related traits, and metabolites/lipids act as bridges between genes and traits. Although there are many studies on the mode of inheritance of metabolites or traits, studies on multi-dimensional genetic network (MDGN) are limited.

Results

In this study, six seed oil-related traits, 59 metabolites, and 107 lipids in 398 recombinant inbred lines, along with their candidate genes and miRNAs, were used to construct an MDGN in soybean. Around 175 quantitative trait loci (QTLs), 36 QTL-by-environment interactions, and 302 metabolic QTL clusters, 70 and 181 candidate genes, including 46 and 70 known homologs, were previously reported to be associated with the traits and metabolites, respectively. Gene regulatory networks were constructed using co-expression, protein–protein interaction, and transcription factor binding site and miRNA target predictions between candidate genes and 26 key miRNAs. Using modern statistical methods, 463 metabolite–lipid, 62 trait–metabolite, and 89 trait–lipid associations were found to be significant. Integrating these associations into the above networks, an MDGN was constructed, and 128 sub-networks were extracted. Among these sub-networks, the gene–trait or gene–metabolite relationships in 38 sub-networks were in agreement with previous studies, e.g., oleic acid (trait)–GmSEI–GmDGAT1a–triacylglycerol (16:0/18:2/18:3), gene and metabolite in each of 64 sub-networks were predicted to be in the same pathway, e.g., oleic acid (trait)–GmPHS–d-glucose, and others were new, e.g., triacylglycerol (16:0/18:1/18:2)–GmbZIP123–GmHD-ZIPIII-10–miR166s–oil content.

Conclusions

This study showed the advantages of MGDN in dissecting the genetic relationships between complex traits and metabolites. Using sub-networks in MGDN, 3D genetic sub-networks including pyruvate/threonine/citric acid revealed genetic relationships between carbohydrates, oil, and protein content, and 4D genetic sub-networks including PLDs revealed the relationships between oil-related traits and phospholipid metabolism likely influenced by the environment. This study will be helpful in soybean quality improvement and molecular biological research.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13068-022-02191-1.

The influence of a tomato food matrix on the bioavailability and plasma kinetics of oral gamma-aminobutyric acid (GABA) and its precursor glutamate in healthy men

Gamma-aminobutyric acid (GABA) and its precursor glutamate play signaling roles in a range of tissues. Both function as neurotransmitters in the central nervous system, but they also modulate pancreatic and immune functioning, for example. Besides endogenous production, both compounds are found in food products, reaching relatively high levels in tomatoes. Recent studies in rodents suggest beneficial effects of oral GABA on glucose homeostasis and blood pressure. However, the bioavailability from food remains unknown. We studied the bioavailability of GABA and glutamate from tomatoes relative to a solution in water. After a fasting blood sample was taken, eleven healthy men randomly received 1 liter of 4 different drinks in a cross-over design with a one-week interval. The drinks were a solution of 888 mg L^-1 GABA, a solution of 3673 mg L^-1 glutamate, pureed fresh tomatoes and plain water as the control. Following intake, 18 blood samples were taken at intervals for 24 hours. Plasma GABA and glutamate concentrations were determined by ultra-pressure liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS). Fasting plasma GABA and glutamate concentrations were found to be 16.71 (SD 2.18) ng mL^-1 and 4626 (SD 1666) ng mL^-1, respectively. Fasting GABA levels were constant (5.8 CV%) between individuals, while fasting glutamate levels varied considerably (23.5 CV%). GABA from pureed tomatoes showed similar bioavailability to that of a solution in water. For glutamate, the absorption from pureed tomatoes occurred more slowly as seen from a longer t_max (0.98 ± 0.14 h vs. 0.41 ± 0.04 h, P = 0.003) and lower C_max (7815 ± 627 ng mL^-1vs. 16 420 ± 2778 ng mL^-1, P = 0.006). These data suggest that GABA is bioavailable from tomatoes, and that food products containing GABA could potentially induce health effects similar to those claimed for GABA supplements. The results merit further studies on the bioavailability of GABA from other food products and the health effects of GABA-rich diets. The clinical trial registry number is NCT04086108 (https://clinicaltrials.gov/ct2/show/NCT04303468).

Research Progress and Trends in Metabolomics of Fruit Trees

Metabolomics is an indispensable part of modern systems biotechnology, applied in the diseases' diagnosis, pharmacological mechanism, and quality monitoring of crops, vegetables, fruits, etc. Metabolomics of fruit trees has developed rapidly in recent years, and many important research results have been achieved in combination with transcriptomics, genomics, proteomics, quantitative trait locus (QTL), and genome-wide association study (GWAS). These research results mainly focus on the mechanism of fruit quality formation, metabolite markers of special quality or physiological period, the mechanism of fruit tree's response to biotic/abiotic stress and environment, and the genetics mechanism of fruit trait. According to different experimental purposes, different metabolomic strategies could be selected, such as targeted metabolomics, non-targeted metabolomics, pseudo-targeted metabolomics, and widely targeted metabolomics. This article presents metabolomics strategies, key techniques in metabolomics, main applications in fruit trees, and prospects for the future. With the improvement of instruments, analysis platforms, and metabolite databases and decrease in the cost of the experiment, metabolomics will prompt the fruit tree research to achieve more breakthrough results.

Comparative compositions of metabolites and dietary fibre components in doughs and breads produced from bread wheat, emmer and spelt and using yeast and sourdough processes

Wholemeal flours from blends of bread wheat, emmer and spelt were processed into bread using yeast-based and sourdough fermentation. The bread wheat flour contained significantly higher concentrations of total dietary fibre and fructans than the spelt and emmer flours, the latter having the lowest contents. Breadmaking using sourdough and yeast systems resulted in changes in composition from flour to dough to bread including increases in organic acids and mannitol in the sourdough system and increases in amino acids and sugars (released by hydrolysis of proteins and starch, respectively) in both processing systems. The concentrations of fructans and raffinose (the major endogenous FODMAPs) were reduced by yeast and sourdough fermentation, with yeast having the greater effect. Both systems resulted in greater increases in sugars and glycerol in emmer than in bread wheat and spelt, but the significance of these differences for human health has not been established.

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.

An Eggplant Recombinant Inbred Population Allows the Discovery of Metabolic QTLs Controlling Fruit Nutritional Quality

Eggplant (Solanum melongena L.) represents the third most important crop of the Solanaceae family and is an important component of our daily diet. A population of 164 F6 recombinant inbred lines (RILs), derived from two eggplant lines differing with respect to several key agronomic traits, "305E40" and "67/3," was grown to the commercial maturation stage, and fruits were harvested, separated into peel and flesh, and subjected to liquid chromatography Liquid Chromatography/Mass Spectrometry (LC/MS) analysis. Through a combination of untargeted and targeted metabolomics approaches, a number of metabolites belonging to the glycoalkaloid, anthocyanin, and polyamine classes and showing a differential accumulation in the two parental lines and F1 hybrid were identified. Through metabolic profiling of the RILs, we identified several metabolomic quantitative trait loci (mQTLs) associated with the accumulation of those metabolites. Each of the metabolic traits proved to be controlled by one or more quantitative trait loci (QTLs); for most of the traits, one major mQTL (phenotypic variation explained [PVE] ≥ 10%) was identified. Data on mQTL mapping and dominance-recessivity relationships of measured compounds in the parental lines and F1 hybrid, as well as an analysis of the candidate genes underlying the QTLs and of their sequence differences in the two parental lines, suggested a series of candidate genes underlying the traits under study.

A Comprehensive Targeted Metabolomics Assay for Crop Plant Sample Analysis

Metabolomics plays an important role in various fields from health to agriculture. However, the comprehensive quantitative metabolomic analysis of plants and plant metabolites has not been widely performed. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS)-based plant metabolomics offers the sensitivity and breadth of coverage for both phenotyping and disease diagnosis of plants. Here, we report a high-coverage and quantitative MS-based assay for plant metabolite analysis. The assay detects and quantifies 206 primary and secondary plant metabolites, including many key plant hormones. In total, it measures 28 amino acids and derivatives, 27 organic acids, 20 biogenic amines and derivatives, 40 acylcarnitines, 90 phospholipids and C-6 sugars. All the analysis methods in this assay are based on LC-MS/MS techniques using both positive and negative-mode multiple reaction monitoring (MRM). The recovery rates of spiked plant samples at three different concentration levels (low, medium and high) ranged from 80% to 120%, with satisfactory precision values of less than 20%. This targeted plant metabolomic assay has been successfully applied to the analysis of large numbers of pine and spruce needle samples, canola root samples, as well as cannabis samples. Moreover, the assay was specifically developed in a 96-well plate format, which enables automated, high-throughput sample analysis. This assay has already been used to analyze over 1500 crop plant samples in less than two months.

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.

Metabolomics of Photosynthetically Active Tissues in White Grapes: Effects of Light Microclimate and Stress Mitigation Strategies

The effects of climate change are becoming a real concern for the viticulture sector, with impacts on both grapevine physiology and the quality of the fresh berries and wine. Short-term mitigation strategies, like foliar kaolin application and smart irrigation regimes, have been implemented to overcome these problems. We previously showed that these strategies also influence the photosynthetic activity of the berries themselves, specifically in the exocarp and seed. In the present work, we assessed the modulating effects of both canopy-light microclimate, kaolin and irrigation treatments on the metabolic profiles of the exocarp and seed, as well as the potential role of berry photosynthesis herein. Berries from the white variety Alvarinho were collected at two contrasting light microclimate positions within the vine canopy (HL—high light and LL—low light) from both irrigated and kaolin-treated plants, and their respective controls, at three fruit developmental stages (green, véraison and mature). Untargeted liquid chromatography mass spectrometry (LCMS) profiling of semi-polar extracts followed by multivariate statistical analysis indicate that both the light microclimate and irrigation influenced the level of a series of phenolic compounds, depending on the ripening stage of the berries. Moreover, untargeted gas chromatography mass spectrometry (GCMS) profiling of polar extracts show that amino acid and sugar levels were influenced mainly by the interaction of irrigation and kaolin treatments. The results reveal that both photosynthetically active berry tissues had a distinct metabolic profile in response to the local light microclimate, which suggests a specific role of photosynthesis in these tissues. A higher light intensity within the canopy mainly increased the supply of carbon precursors to the phenylpropanoid/flavonoid pathway, resulting in increased levels of phenolic compounds in the exocarp, while in seeds, light mostly influenced compounds related to carbon storage and seed development. In addition, our work provides new insights into the influence of abiotic stress mitigation strategies on the composition of exocarps and seeds, which are both important tissues for the quality of grape-derived products.

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.

Impact of root-associated strains of three Paraburkholderia species on primary and secondary metabolism of Brassica oleracea

Several root-colonizing bacterial species can simultaneously promote plant growth and induce systemic resistance. How these rhizobacteria modulate plant metabolism to accommodate the carbon and energy demand from these two competing processes is largely unknown. Here, we show that strains of three Paraburkholderia species, P. graminis PHS1 (Pbg), P. hospita mHSR1 (Pbh), and P. terricola mHS1 (Pbt), upon colonization of the roots of two Broccoli cultivars led to cultivar-dependent increases in biomass, changes in primary and secondary metabolism and induced resistance against the bacterial leaf pathogen Xanthomonas campestris. Strains that promoted growth led to greater accumulation of soluble sugars in the shoot and particularly fructose levels showed an increase of up to 280-fold relative to the non-treated control plants. Similarly, a number of secondary metabolites constituting chemical and structural defense, including flavonoids, hydroxycinnamates, stilbenoids, coumarins and lignins, showed greater accumulation while other resource-competing metabolite pathways were depleted. High soluble sugar generation, efficient sugar utilization, and suppression or remobilization of resource-competing metabolites potentially contributed to curb the tradeoff between the carbon and energy demanding processes induced by Paraburkholderia-Broccoli interaction. Collectively, our results provide a comprehensive and integrated view of the temporal changes in plant metabolome associated with rhizobacteria-mediated plant growth promotion and induced resistance.

Comparative Metabolomic Profiling of Citrullus spp. Fruits Provides Evidence for Metabolomic Divergence during Domestication

Watermelon (Citrullus lanatus) is one of the most nutritional fruits that is widely distributed in the whole world. The nutritional compositions are mainly influenced by the genotype and environment. However, the metabolomics of different domestication status and different flesh colors watermelon types is not fully understood. In this study, we reported an extensive assessment of metabolomic divergence in the fruit flesh among Citrullus sp. and within Citrullus sp. We demonstrate that metabolic profiling was significantly different between the wild and cultivated watermelons, the apigenin 6-C-glucoside, luteolin 6-C-glucoside, chrysoeriol C-hexoside, naringenin C-hexoside, C-pentosyl-chrysoeriol O-hexoside, and sucrose are the main divergent metabolites. Correlation analysis results revealed that flavonoids were present in one tight metabolite cluster. The main divergent metabolites in different flesh-colored cultivated watermelon fruits are p-coumaric acid, 2,3-dihydroflavone, catechin, N-(3-indolylacetyl)-l-alanine, 3,4-dihydroxycinnamic acid, and pelargonidin o-hexoside. A total of 431 differentially accumulated metabolites were identified from pairwise comparative analyses. C. lanatus edible-seed watermelon (cultivars) and C. mucosospermus (wild) have similar fruit metabolic profiles and phenotypic traits, indicating that edible-seed watermelon may be a relative of wild species and a relatively primitive differentiation type of cultivated watermelon. Our data provide extensive knowledge for metabolomics-based watermelon improvement of Citrullus fruits meet their enhanced nutritive properties or upgraded germplasm utility values.

Reprogramming of Tomato Leaf Metabolome by the Activity of Heat Stress Transcription Factor HsfB1

Plants respond to high temperatures with global changes of the transcriptome, proteome, and metabolome. Heat stress transcription factors (Hsfs) are the core regulators of transcriptome responses as they control the reprogramming of expression of hundreds of genes. The thermotolerance-related function of Hsfs is mainly based on the regulation of many heat shock proteins (HSPs). Instead, the Hsf-dependent reprogramming of metabolic pathways and their contribution to thermotolerance are not well described. In tomato (Solanum lycopersicum), manipulation of HsfB1, either by suppression or overexpression (OE) leads to enhanced thermotolerance and coincides with distinct profile of metabolic routes based on a metabolome profiling of wild-type (WT) and HsfB1 transgenic plants. Leaves of HsfB1 knock-down plants show an accumulation of metabolites with a positive effect on thermotolerance such as the sugars sucrose and glucose and the polyamine putrescine. OE of HsfB1 leads to the accumulation of products of the phenylpropanoid and flavonoid pathways, including several caffeoyl quinic acid isomers. The latter is due to the enhanced transcription of genes coding key enzymes in both pathways, in some cases in both non-stressed and stressed plants. Our results show that beyond the control of the expression of Hsfs and HSPs, HsfB1 has a wider activity range by regulating important metabolic pathways providing an important link between stress response and physiological tomato development.

Genetic loci determining potato starch yield and granule morphology revealed by genome-wide association study (GWAS)

Background

It is well-documented that (bio)chemical reaction capacity of raw potato starch depends on crystallinity, morphology and other chemical and physical properties of starch granules, and these properties are closely related to gene functions. Preparative yield, amylose/amylopectin content, and phosphorylation of potato tuber starch are starch-related traits studied at the genetic level. In this paper, we perform a genome-wide association study using a 22K SNP potato array to identify for the first time genomic regions associated with starch granule morphology and to increase number of known genome loci associated with potato starch yield.

Methods

A set of 90 potato (Solanum tuberosum L.) varieties from the ICG “GenAgro” collection (Novosibirsk, Russia) was harvested, 90 samples of raw tuber starch were obtained, and DNA samples were isolated from the skin of the tubers. Morphology of potato tuber starch granules was evaluated by optical microscopy and subsequent computer image analysis. A set of 15,214 scorable SNPs was used for the genome-wide analysis. In total, 53 SNPs were found to be significantly associated with potato starch morphology traits (aspect ratio, roundness, circularity, and the first bicomponent) and starch yield-related traits.

Results

A total of 53 novel SNPs was identified on potato chromosomes 1, 2, 4, 5, 6, 7, 9, 11 and 12; these SNPs are associated with tuber starch preparative yield and granule morphology. Eight SNPs are situated close to each other on the chromosome 1 and 19 SNPs—on the chromosome 2, forming two DNA regions—potential QTLs, regulating aspect ratio and roundness of the starch granules. Thirty-seven of 53 SNPs are located in protein-coding regions. There are indications that granule shape may depend on starch phosphorylation processes. The GWD gene, which is known to regulate starch phosphorylation—dephosphorylation, participates in the regulation of a number of morphological traits, rather than one specific trait. Some significant SNPs are associated with membrane and plastid proteins, as well as DNA transcription and binding regulators. Other SNPs are related to low-molecular-weight metabolite synthesis, and may be associated with flavonoid biosynthesis and circadian rhythm-related metabolic processes. The preparative yield of tuber starch is a polygenic trait that is associated with a number of SNPs from various regions and chromosomes in the potato genome.

The genetic and functional analysis of flavor in commercial tomato: the FLORAL4 gene underlies a QTL for floral aroma volatiles in tomato fruit

Tomato (Solanum lycopersicum L.) has become a popular model for genetic studies of fruit flavor in the last two decades. In this article we present a study of tomato fruit flavor, including an analysis of the genetic, metabolic and sensorial variation of a collection of contemporary commercial glasshouse tomato cultivars, followed by a validation of the associations found by quantitative trait locus (QTL) analysis of representative biparental segregating populations. This led to the identification of the major sensorial and chemical components determining fruit flavor variation and detection of the underlying QTLs. The high representation of QTL haplotypes in the breeders' germplasm suggests that there is great potential for applying these QTLs in current breeding programs aimed at improving tomato flavor. A QTL on chromosome 4 was found to affect the levels of the phenylalanine-derived volatiles (PHEVs) 2-phenylethanol, phenylacetaldehyde and 1-nitro-2-phenylethane. Fruits of near-isogenic lines contrasting for this locus and in the composition of PHEVs significantly differed in the perception of fruity and rose-hip-like aroma. The PHEV locus was fine mapped, which allowed for the identification of FLORAL4 as a candidate gene for PHEV regulation. Using a gene-editing-based (CRISPR-CAS9) reverse-genetics approach, FLORAL4 was demonstrated to be the key factor in this QTL affecting PHEV accumulation in tomato fruit.

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.

Modulation of the Tomato Fruit Metabolome by LED Light

Metabolic profiles of tomatoes change during ripening and light can modulate the activity of relevant biochemical pathways. We investigated the effects of light directly supplied to the fruits on the metabolome of the fruit pericarp during ripening. Mature green tomatoes were exposed to well-controlled conditions with light as the only varying factor; control fruits were kept in darkness. In experiment 1 the fruits were exposed to either white light or darkness for 15 days. In experiment 2, fruits were exposed to different light spectra (blue, green, red, far-red, white) added to white background light for seven days. Changes in the global metabolome of the fruit pericarp were monitored using LCMS and GCMS (554 compounds in total). Health-beneficial compounds (carotenoids, flavonoids, tocopherols and phenolic acids) accumulated faster under white light compared to darkness, while alkaloids and chlorophylls decreased faster. Light also changed the levels of taste-related metabolites including glutamate and malate. The light spectrum treatments indicated that the addition of blue light was the most effective treatment in altering the fruit metabolome. We conclude that light during ripening of tomatoes can have various effects on the metabolome and may help with shaping the levels of key compounds involved in various fruit quality characteristics.

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.

Cold storage reveals distinct metabolic perturbations in processing and non-processing cultivars of potato (Solanum tuberosum L.)

Cold-induced sweetening (CIS) causes considerable losses to the potato processing industry wherein the selection of potato genotypes using biochemical information has found to be advantageous. Here, ¹H NMR spectroscopy was performed to identify metabolic perturbations from tubers of five potato cultivars (Atlantic, Frito Lay-1533, Kufri Jyoti, Kufri Pukhraj, and PU1) differing in their CIS ability and processing characteristics at harvest and after cold storage (4 °C). Thirty-nine water-soluble metabolites were detected wherein significantly affected metabolites after cold storage were categorized into sugars, sugar alcohols, amino acids, and organic acids. Multivariate statistical analysis indicated significant differences in the metabolic profiles among the potato cultivars. Pathway enrichment analysis revealed that carbohydrates, amino acids, and organic acids are the key players in CIS. Interestingly, one of the processing cultivars, FL-1533, exhibited a unique combination of metabolites represented by low levels of glucose, fructose, and asparagine accompanied by high citrate levels. Conversely, non-processing cultivars (Kufri Pukhraj and Kufri Jyoti) showed elevated glucose, fructose, and malate levels. Our results indicate that metabolites such as glucose, fructose, sucrose, asparagine, glutamine, citrate, malate, proline, 4-aminobutyrate can be potentially utilized for the prediction, selection, and development of potato cultivars for long-term storage, nutritional, as well as processing attributes.

Network Analysis Provides Insight into Tomato Lipid Metabolism

Metabolic correlation networks have been used in several instances to obtain a deeper insight into the complexity of plant metabolism as a whole. In tomato (Solanum lycopersicum), metabolites have a major influence on taste and overall fruit quality traits. Previously a broad spectrum of metabolic and phenotypic traits has been described using a Solanum pennellii introgression-lines (ILs) population. To obtain insights into tomato fruit metabolism, we performed metabolic network analysis from existing data, covering a wide range of metabolic traits, including lipophilic and volatile compounds, for the first time. We provide a comprehensive fruit correlation network and show how primary, secondary, lipophilic, and volatile compounds connect to each other and how the individual metabolic classes are linked to yield-related phenotypic traits. Results revealed a high connectivity within and between different classes of lipophilic compounds, as well as between lipophilic and secondary metabolites. We focused on lipid metabolism and generated a gene-expression network with lipophilic metabolites to identify new putative lipid-related genes. Metabolite–transcript correlation analysis revealed key putative genes involved in lipid biosynthesis pathways. The overall results will help to deepen our understanding of tomato metabolism and provide candidate genes for transgenic approaches toward improving nutritional qualities in tomato.

Biomarkers for grain yield stability in rice under drought stress

Crop yield stability requires an attenuation of the reduction of yield losses caused by environmental stresses such as drought. Using a combination of metabolomics and high-throughput colorimetric assays, we analysed central metabolism and oxidative stress status in the flag leaf of 292 indica rice (Oryza sativa) accessions. Plants were grown in the field and were, at the reproductive stage, exposed to either well-watered or drought conditions to identify the metabolic processes associated with drought-induced grain yield loss. Photorespiration, protein degradation, and nitrogen recycling were the main processes involved in the drought-induced leaf metabolic reprogramming. Molecular markers of drought tolerance and sensitivity in terms of grain yield were identified using a multivariate model based on the values of the metabolites and enzyme activities across the population. The model highlights the central role of the ascorbate-glutathione cycle, particularly dehydroascorbate reductase, in minimizing drought-induced grain yield loss. In contrast, malondialdehyde was an accurate biomarker for grain yield loss, suggesting that drought-induced lipid peroxidation is the major constraint under these conditions. These findings highlight new breeding targets for improved rice grain yield stability under drought.

Reciprocal cybrids reveal how organellar genomes affect plant phenotypes

Assessment of the impact of variation in chloroplast and mitochondrial DNA (collectively termed the plasmotype) on plant phenotypes is challenging due to the difficulty in separating their effect from nuclear-derived variation (the nucleotype). Haploid-inducer lines can be used as efficient plasmotype donors to generate new plasmotype-nucleotype combinations (cybrids)¹. We generated a panel comprising all possible cybrids of seven Arabidopsis thaliana accessions and extensively phenotyped these lines for 1,859 phenotypes under both stable and fluctuating conditions. We show that natural variation in the plasmotype results in both additive and epistatic effects across all phenotypic categories. Plasmotypes that induce more additive phenotypic changes also cause more epistatic effects, suggesting a possible common basis for both additive and epistatic effects. On average, epistatic interactions explained twice as much of the variance in phenotypes as additive plasmotype effects. The impact of plasmotypic variation was also more pronounced under fluctuating and stressful environmental conditions. Thus, the phenotypic impact of variation in plasmotypes is the outcome of multi-level nucleotype-plasmotype-environment interactions and, as such, the plasmotype is likely to serve as a reservoir of variation that is predominantly exposed under certain conditions. The production of cybrids using haploid inducers is a rapid and precise method for assessment of the phenotypic effects of natural variation in organellar genomes. It will facilitate efficient screening of unique nucleotype-plasmotype combinations to both improve our understanding of natural variation in these combinations and identify favourable combinations to enhance plant performance.

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.

The interaction between genotype and maternal nutritional environments affects tomato seed and seedling quality

Seed and seedling traits are affected by the conditions of the maternal environment, such as light, temperature, and nutrient availability. In this study, we have investigated whether different maternally applied nitrate and phosphate concentrations affect the seed and seedling performance of two closely related tomato species: Solanum lycopersicum cv. Money maker and Solanum pimpinellifolium accession CGN14498. We observed large differences for seed and seedling traits between the two species. Additionally, we have shown that for nitrate most of the seed and seedling traits were significantly affected by genotype-environment interactions (G×E). The effect of the maternal environment was clearly visible in the primary metabolites of the dry seeds. For example, we could show that the amount of γ-aminobutyric acid (GABA) in Money maker seeds was affected by the differences in the maternal environments and was positively correlated with seed germination under high temperature. Overall, compared with phosphate, nitrate had a larger effect on seed and seedling performance in tomato. In general, the different responses to the maternal environments of the two tomato species showed a major role for G×E in shaping seed and seedling traits.

Metabolomic profiles differ among unique genotypes of a threatened Caribbean coral

Global threats to reefs require urgent efforts to resolve coral attributes that affect survival in a changing environment. Genetically different individuals of the same coral species are known to exhibit different responses to the same environmental conditions. New information on coral physiology, particularly as it relates to genotype, could aid in unraveling mechanisms that facilitate coral survival in the face of stressors. Metabolomic profiling detects a large subset of metabolites in an organism, and, when linked to metabolic pathways, can provide a snapshot of an organism’s physiological state. Identifying metabolites associated with desirable, genotype-specific traits could improve coral selection for restoration and other interventions. A key step toward this goal is determining whether intraspecific variation in coral metabolite profiles can be detected for species of interest, however little information exists to illustrate such differences. To address this gap, we applied untargeted ¹H-NMR and LC-MS metabolomic profiling to three genotypes of the threatened coral Acropora cervicornis. Both methods revealed distinct metabolite “fingerprints” for each genotype examined. A number of metabolites driving separation among genotypes were identified or putatively annotated. Pathway analysis suggested differences in protein synthesis among genotypes. For the first time, these data illustrate intraspecific variation in metabolomic profiles for corals in a common garden. Our results contribute to the growing body of work on coral metabolomics and suggest future work could identify specific links between phenotype and metabolite profile in corals.

Metabolic Analysis of Four Cultivars of Liriope platyphylla

Liriope platyphylla (Liliaceae), a medical plant distributed mainly in China, Taiwan, and Korea, has been used traditionally for the treatment of cough, sputum, asthma, and neurodegenerative diseases. The present study involved the metabolic profiling of this plant and reports spicatoside A accumulation in four different varieties of L. platyphylla (Cheongyangjaerae, Seongsoo, Cheongsim, and Liriope Tuber No. 1) using HPLC and gas chromatography time-of-flight mass spectrometry (GC⁻TOFMS). A total of 47 metabolites were detected in the different cultivars using GC⁻TOFMS-based metabolic profiling. The resulting data were subjected to principal component analysis (PCA) for determining the whole experimental variation, and the different cultivars were separated by score plots. Furthermore, hierarchical clustering, Pearson's correlation, and partial least-squares discriminant analyses (PLS-DA) were subsequently performed to determine significant differences in the various metabolites of the cultivars. The HPLC data revealed that the presence of spicatoside A was detected in all four cultivars, with the amount of spicatoside A varying among them. Among the cultivars, Liriope Tuber No. 1 contained the highest amount of spicatoside A (1.83 ± 0.13 mg/g dry weight), followed by Cheongyangjaerae (1.25 ± 0.01 mg/g dry weight), Cheongsim (1.09 ± 0.04 mg/g dry weight), and Seongsoo (1.01 ± 0.02 mg/g dry weight). The identification of spicatoside A was confirmed by comparing the retention time of the sample with the retention time of the standard. Moreover, the Cheongsim cultivar contained higher levels of phenolic compounds-including vanillic acid, quinic acid, gallic acid, chlorogenic acid, caffeic acid, and benzoic acid-than those of the other two cultivars. On the other hand, the levels of amino acids were higher in the Seongsoo cultivar. Therefore, this study may help breeders produce new varieties with improved nutraceutical and nutritional qualities.

Starch phosphorylation associated SNPs found by genome-wide association studies in the potato (Solanum tuberosum L.)

Background

The natural variation of starch phosphate content in potatoes has been previously reported. It is known that, in contrast to raw starch, commercially phosphorylated starch is more stable at high temperatures and shear rates and has higher water capacity. The genetic improvement of phosphate content in potato starch by selection or engineering would allow the production of phosphorylated starch in a natural, environmentally friendly way without chemicals. The aim of the current research is to identify genomic SNPs associated with starch phosphorylation by carrying out a genome-wide association study in potatoes.

Results

A total of 90 S. tuberosum L. varieties were used for phenotyping and genotyping. The phosphorus content of starch in 90 potato cultivars was measured and then statistically analysed. Principal component analysis (PCA) revealed that the third and eighth principal components appeared to be sensitive to variation in phosphorus content (p = 0.0005 and p = 0.002, respectively). PC3 showed the correlation of starch phosphorus content with allelic variations responsible for higher phosphorylation levels, found in four varieties. Similarly, PC8 indicated that hybrid 785/8–5 carried an allele associated with high phosphorus content, while the Impala and Red Scarlet varieties carried alleles for low phosphorus content. Genotyping was carried out using an Illumina 22 K SNP potato array. A total of 15,214 scorable SNPs (71.7% success rate) was revealed. GWAS mapping plots were obtained using TASSEL based on several statistical models, including general linear models (GLMs), with and without accounting for population structure, as well as MLM. A total of 17 significant SNPs was identified for phosphorus content in potato starch, 14 of which are assigned to 8 genomic regions on chromosomes 1, 4, 5, 7, 8, 10, and 11. Most of the SNPs identified belong to protein coding regions; however, their allelic variation was not associated with changes in protein structure or function.

Conclusions

A total of 8 novel genomic regions possibly associated with starch phosphorylation on potato chromosomes 1, 4, 5, 7, 8, 10, and 11 was revealed. Further validation of the SNPs identified and the analysis of the surrounding genomic regions for candidate genes will allow better understanding of starch phosphorylation biochemistry. The most indicative SNPs may be useful for developing diagnostic markers to accelerate the breeding of potatoes with predetermined levels of starch phosphorylation.

Electronic supplementary material

The online version of this article (10.1186/s12863-019-0729-9) contains supplementary material, which is available to authorized users.

Metabotyping as a Stopover in Genome-to-Phenome Mapping

Predicting phenotypic expression from genomic and environmental information is arguably the greatest challenge in today's biology. Being able to survey genomic content, e.g., as single-nucleotide polymorphism data, within a diverse population and predict the phenotypes of external traits, represents the holy grail across genome-informed disciplines, from personal medicine and nutrition to plant breeding. In the present study, we propose a two-step procedure in bridging the genome to phenome gap where external phenotypes are viewed as emergent properties of internal phenotypes, such as molecular profiles, in interaction with the environment. Using biomass accumulation and shoot-root allometry as external traits in diverse genotypes of the model grass Brachypodium distachyon, we established correlative models between genotypes and metabolite profiles (metabotypes) as internal phenotypes, and between metabotypes and external phenotypes under two contrasting watering regimes. Our results demonstrate the potential for employing metabotypes as an integrator in predicting external phenotypes from genomic information.

QTL mapping of insect resistance components of Solanum galapagense

QTLs for insect resistance parameters, trichome type IV development, and more than 200 non-volatile metabolites, including 76 acyl sugars, all co-locate at the end of Chromosome 2 of Solanum galapagense. Host plant resistance is gaining importance as more and more insecticides are being banned due to environmental concerns. In tomato, resistance towards insects is found in wild relatives and has been attributed to the presence of glandular trichomes and their specific phytochemical composition. In this paper, we describe the results from a large-scale QTL mapping of data from whitefly resistance tests, trichome phenotyping and a comprehensive metabolomics analysis in a recombinant inbred line population derived from a cross between the cultivated Solanum lycopersicum and the wild relative S. galapagense, which is resistant to a range of pest insects. One major QTL (Wf-1) was found to govern the resistance against two different whitefly species. This QTL co-localizes with QTLs for the presence of trichomes type IV and V, as well as all 76 acyl sugars detected and about 150 other non-volatile phytochemicals, including methyl esters of the flavonols myricetin and quercetin. Based on these results, we hypothesize that Wf-1 is regulating the formation of glandular trichome type IV on the leaf epidermis, enabling the production and accumulation of bioactive metabolites in this type of trichomes.

The effect of isolation methods of tomato pollen on the results of metabolic profiling

INTRODUCTION

Untargeted metabolomics is a powerful tool to detect hundreds of metabolites within a given tissue and to compare the metabolite composition of samples in a comprehensive manner. However, with regard to pollen research such comprehensive metabolomics approaches are yet not well developed. To enable isolation of pollen that is tightly enclosed within the anthers of the flower, such as immature pollen, the current pollen isolation protocols require the use of a watery solution. These protocols raise a number of concerns for their suitability in metabolomics analyses, in view of possible metabolic activities in the pollen and contamination with anther metabolites.

OBJECTIVES

We assessed the effect of different sample preparation procedures currently used for pollen isolation for their suitability to perform metabolomics of tomato pollen.

METHODS

Pollen were isolated using different methods and the metabolic profiles were analysed by liquid chromatography-mass spectrometry (LC-MS).

RESULTS

Our results demonstrated that pollen isolation in a watery solution led to (i) rehydration of the pollen grains, inducing marked metabolic changes in flavonoids, phenylpropanoids and amino acids and thus resulting in a metabolite profile that did not reflect the one of mature dry pollen, (ii) hydrolysis of sucrose into glucose and fructose during subsequent metabolite extraction, unless the isolated and rehydrated pollen were lyophilized prior to extraction, and (iii) contamination with anther-specific metabolites, such as alkaloids, thus compromising the metabolic purity of the pollen fraction.

CONCLUSION

We conclude that the current practices used to isolate pollen are suboptimal for metabolomics analyses and provide recommendations on how to improve the pollen isolation protocol, in order to obtain the most reliable metabolic profile from pollen tissue.

Exploring the Diversity of Plant Metabolism

Plants produce a huge array of metabolites, far more than those produced by most other organisms. Unraveling this diversity and its underlying genetic variation has attracted increasing research attention. Post-genomic profiling platforms have enabled the marriage and mining of the enormous amount of phenotypic and genetic diversity. We review here achievements to date and challenges remaining that are associated with plant metabolic research using multi-omic strategies. We focus mainly on strategies adopted in investigating the diversity of plant metabolism and its underlying features. Recent advances in linking metabotypes with phenotypic and genotypic traits are also discussed. Taken together, we conclude that exploring the diversity of metabolism could provide new insights into plant evolution and domestication.

Metabolic diversity in tuber tissues of native Chiloé potatoes and commercial cultivars of Solanum tuberosum ssp. tuberosum L

INTRODUCTION

The native potatoes (Solanum tuberosum ssp. tuberosum L.) cultivated on Chiloé Island in southern Chile have great variability in terms of tuber shape, size, color and flavor. These traits have been preserved throughout generations due to the geographical position of Chiloé, as well as the different uses given by local farmers.

OBJECTIVES

The present study aimed to investigate the diversity of metabolites in skin and pulp tissues of eleven native accessions of potatoes from Chile, and evaluate the metabolite associations between tuber tissues.

METHODS

For a deeper characterization of these accessions, we performed a comprehensive metabolic study in skin and pulp tissues of tubers, 3 months after harvesting. Specific targeted quantification of metabolites using 96 well microplates, and high-performance liquid chromatography combined with non-targeted metabolite profiling by gas chromatography time-of-flight mass spectrometry were used in this study.

RESULTS

We observed differential levels of antioxidant activity and phenolic compounds between skin and pulp compared to a common commercial cultivar (Desireé). In addition, we uncovered considerable metabolite variability between different tuber tissues and between native potatoes. Network correlation analysis revealed different metabolite associations among tuber tissues that indicate distinct associations between primary metabolite and anthocyanin levels, and antioxidant activity in skin and pulp tissues. Moreover, multivariate analysis lead to the grouping of native and commercial cultivars based on metabolites from both skin and pulp tissues.

CONCLUSIONS

As well as providing important information to potato producers and breeding programs on the levels of health relevant phytochemicals and other abundant metabolites such as starch, proteins and amino acids, this study highlights the associations of different metabolites in tuber skins and pulp, indicating the need for distinct strategies for metabolic engineering in these tissues. Furthermore, this study shows that native Chilean potato accessions have great potential as a natural source of phytochemicals.

Functional Metabolomics—A Useful Tool to Characterize Stress-Induced Metabolome Alterations Opening New Avenues towards Tailoring Food Crop Quality

The breeding of stress-tolerant cultivated plants that would allow for a reduction in harvest losses and undesirable decrease in quality attributes requires a new quality of knowledge on molecular markers associated with relevant agronomic traits, on quantitative metabolic responses of plants to stress challenges, and on the mechanisms controlling the biosynthesis of these molecules. By combining metabolomics with genomics, transcriptomics and proteomics datasets a more comprehensive knowledge of the composition of crop plants used for food or animal feed is possible. In order to optimize crop trait developments, to enhance crop yields and quality, as well as to guarantee nutritional and health factors that provide the possibility to create functional food or feedstuffs, knowledge about the plants’ metabolome is crucial. Next to classical metabolomics studies, this review focuses on several metabolomics-based working techniques, such as sensomics, lipidomics, hormonomics and phytometabolomics, which were used to characterize metabolome alterations during abiotic and biotic stress in order to find resistant food crops with a preferred quality or at least to produce functional food crops.

Metabolomics 20 years on: what have we learned and what hurdles remain?

The term metabolome was coined in 1998, by analogy to genome, transcriptome and proteome. The first research papers using the terms metabolomics, metabonomics, metabolic profiling or metabolite profiling were published shortly thereafter. In this short review we reflect on the major achievements brought about by the use of these approaches, and document the knowledge and technology gaps that are currently constraining its further development. Finally, we detail why we think that the time is ripe to refocus our efforts on the understanding of metabolic function.

Metabolic responses of Eucalyptus species to different temperature regimes

Species and hybrids of Eucalyptus are the world's most widely planted hardwood trees. They are cultivated across a wide range of latitudes and therefore environmental conditions. In this context, comprehensive metabolomics approaches have been used to assess how different temperature regimes may affect the metabolism of three species of Eucalyptus, E. dunnii, E. grandis and E. pellita. Young plants were grown for 53 d in the greenhouse and then transferred to growth chambers at 10°C, 20°C or 30°C for another 7 d. In all three species the leaf chlorophyll content was positively correlated to temperature, and in E. pellita the highest temperature also resulted in a significant increase in stem biomass. Comprehensive metabolomics was performed using untargeted gas chromatography mass spectrometry (GC-MS) and liquid chromatography (LC)-MS. This approach enabled the comparison of the relative abundance of 88 polar primary metabolites from GC-MS and 625 semi-polar secondary metabolites from LC-MS. Using principal components analysis, a major effect of temperature was observed in each species which was larger than that resulting from the genetic background. Compounds mostly affected by temperature treatment were subsequently selected using partial least squares discriminant analysis and were further identified. These putative annotations indicated that soluble sugars and several polyphenols, including tannins, triterpenes and alkaloids were mostly influenced.

The Genetics of Plant Metabolism

Plant metabolic studies have traditionally focused on the role and regulation of the enzymes catalyzing key reactions within specific pathways. Within the past 20 years, reverse genetic approaches have allowed direct determination of the effects of the deficiency, or surplus, of a given protein on the biochemistry of a plant. In parallel, top-down approaches have also been taken, which rely on screening broad, natural genetic diversity for metabolic diversity. Here, we compare and contrast the various strategies that have been adopted to enhance our understanding of the natural diversity of metabolism. We also detail how these approaches have enhanced our understanding of both specific and global aspects of the genetic regulation of metabolism. Finally, we discuss how such approaches are providing important insights into the evolution of plant secondary metabolism.