Identification and mode of inheritance of quantitative trait loci for secondary metabolite abundance in tomato

Rewiring of the Fruit Metabolome in Tomato Breeding

Humans heavily rely on dozens of domesticated plant species that have been further improved through intensive breeding. To evaluate how breeding changed the tomato fruit metabolome, we have generated and analyzed a dataset encompassing genomes, transcriptomes, and metabolomes from hundreds of tomato genotypes. The combined results illustrate how breeding globally altered fruit metabolite content. Selection for alleles of genes associated with larger fruits altered metabolite profiles as a consequence of linkage with nearby genes. Selection of five major loci reduced the accumulation of anti-nutritional steroidal glycoalkaloids in ripened fruits, rendering the fruit more edible. Breeding for pink tomatoes modified the content of over 100 metabolites. The introgression of resistance genes from wild relatives in cultivars also resulted in major and unexpected metabolic changes. The study reveals a multi-omics view of the metabolic breeding history of tomato, as well as provides insights into metabolome-assisted breeding and plant biology.

Metabolome Analysis of Multi-Connected Biparental Chromosome Segment Substitution Line Populations

Metabolomic analysis coupled with advanced genetic populations represents a powerful tool with which to investigate the plant metabolome. However, genetic analyses of the rice (Oryza sativa) metabolome have been conducted mainly using natural accessions or a single biparental population. Here, the flag leaves from three interconnected chromosome segment substitution line populations with a common recurrent genetic background were used to dissect rice metabolic diversity. We effectively used multiple interconnected biparental populations, constructed by introducing genomic segments into Zhenshan 97 from ACC10 (A/Z), Minghui 63 (M/Z), and Nipponbare (N/Z), to map metabolic quantitative trait loci (mQTL). A total of 1,587 mQTL were generated, of which 684, 479, and 722 were obtained from the A/Z, M/Z, and N/Z chromosome segment substitution line populations, respectively, and we designated 99 candidate genes for 367 mQTL. In addition, 1,001 mQTL were generated specifically from joint linkage analysis with 25 candidate genes assigned. Several of these candidates were validated, such as LOC_Os07g01020 for the in vivo content of pyridoxine and its derivative and LOC_Os04g25980 for cis-zeatin glucosyltransferase activity. We propose a novel biosynthetic pathway for O-methylapigenin C-pentoside and demonstrated that LOC_Os04g11970 encodes a component of this pathway through fine-mapping. We postulate that the methylated apigenin may confer plant disease resistance. This study demonstrates the power of using multiple interconnected populations to generate a large number of veritable mQTL. The combined results are discussed in the context of functional metabolomics and the possible features of assigned candidates underlying respective metabolites.

Quantitative Trait Loci Analysis Identifies a Prominent Gene Involved in the Production of Fatty Acid-Derived Flavor Volatiles in Tomato

To gain insight into the genetic regulation of lipid metabolism in tomato, we conducted metabolic trait loci (mQTL) analysis following the lipidomic profiling of fruit pericarp and leaf tissue of the Solanum pennellii introgression lines (IL). To enhance mapping resolution for selected fruit-specific mQTL, we profiled the lipids in a subset of independently derived S. pennellii backcross inbred lines, as well as in a near-isogenic sub-IL population. We identified a putative lecithin:cholesterol acyltransferase that controls the levels of several lipids, and two members of the class III lipase family, LIP1 and LIP2, that were associated with decreased levels of diacylglycerols (DAGs) and triacylglycerols (TAGs). Lipases of this class cleave fatty acids from the glycerol backbone of acylglycerols. The released fatty acids serve as precursors of flavor volatiles. We show that LIP1 expression correlates with fatty acid-derived volatile levels. We further confirm the function of LIP1 in TAG and DAG breakdown and volatile synthesis using transgenic plants. Taken together, our study extensively characterized the genetic architecture of lipophilic compounds in tomato and demonstrated at molecular level that release of free fatty acids from the glycerol backbone can have a major impact on downstream volatile synthesis.

Impairment of hormone pathways results in a general disturbance of fruit primary metabolism in tomato

Fruit metabolites are regulated by different phytohormones; however, this needs to be investigated. Dynamic metabolite profiling, based on gas chromatography-mass spectrometry, has been conducted on the fruit of tomato cultivar Micro-Tom and its five hormone mutants: dpy, not, dgt, epi and pro. In total, 48 metabolites were quantified, including sugars, organic acids and amino acids. The results demonstrated that ABA had a greater effect on the regulation of primary metabolism in tomato fruit, while ethylene can play an important role in the transition of primary to secondary metabolism. Besides, results from enzyme activities and transcript abundance involved in primary metabolism suggested that AIV and HXK4 could play key roles in the accumulation of the main sugars. To the best of our knowledge, this is the first comprehensive analysis of the link between hormone and metabolite change during fruit development in a collection of mutants with diverse hormone pathways.

A Highly Specific Genome-Wide Association Study Integrated with Transcriptome Data Reveals the Contribution of Copy Number Variations to Specialized Metabolites in Arabidopsis thaliana Accessions

Lineage-specific gene duplications contribute to a large variation in specialized metabolites among different plant species. There is also considerable variability in the specialized metabolites within a single plant species. However, it is unclear whether copy number variations (CNVs) derived from gene duplication events contribute to the diversity of specialized metabolites within species. We identified metabolome quantitative trait genes (mQTGs) associated with quantitative metabolite variations and examined the relationship between mQTGs and CNVs. We obtained 1,335 specialized metabolite signals from 53 worldwide A. thaliana accessions using liquid chromatography-quadrupole time-of-flight mass spectrometry. In this study, genes associated with specialized metabolites were inferred by either a generally authorized genome-wide association study (GWAS) approach or a novel analysis of the association between gene expression and metabolite accumulation. Genes qualified by both analyses are defined to be mQTGs. The integrated method enabled us to detect mQTGs with a low false positive rate (=5.71 × 10-4). We also identified 5,654 genes associated with 1,335 specialized metabolites. Of these genes, 4.4% were affected by CNVs, which was more than expected (χ2 test: P < 0.01). This result suggests that CNVs contribute to variations in specialized metabolites within a species. To assess the contribution of CNVs to adaptive evolution in A. thaliana, we examined the selective sweeps around the mQTGs. We observed that the mQTGs with CNVs tended to undergo selective sweeps. These observations imply that variations in specialized metabolites caused by CNVs contribute to the adaptive evolution of A. thaliana.

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.

An integrated multi-layered analysis of the metabolic networks of different tissues uncovers key genetic components of primary metabolism in maize

Primary metabolism plays a pivotal role in normal plant growth, development and reproduction. As maize is a major crop worldwide, the primary metabolites produced by maize plants are of immense importance from both calorific and nutritional perspectives. Here a genome-wide association study (GWAS) of 61 primary metabolites using a maize association panel containing 513 inbred lines identified 153 significant loci associated with the level of these metabolites in four independent tissues. The genome-wide expression level of 760 genes was also linked with metabolite levels within the same tissue. On average, the genetic variants at each locus or transcriptional variance of each gene identified here were estimated to have a minor effect (4.4-7.8%) on primary metabolic variation. Thirty-six loci or genes were prioritized as being worthy of future investigation, either with regard to functional characterization or for their utility for genetic improvement. This target list includes the well-known opaque 2 (O2) and lkr/sdh genes as well as many less well-characterized genes. During our investigation of these 36 loci, we analyzed the genetic components and variations underlying the trehalose, aspartate and aromatic amino acid pathways, thereby functionally characterizing four genes involved in primary metabolism in maize.

Comprehensive Profiling and Inheritance Patterns of Metabolites in Foxtail Millet

Metabolomics aims at determining a sample's metabolites profile and hence provides a straight functional statement of an organism's physiological condition. Here, we investigated comprehensive profiling, natural variation and species-specific accumulation of both primary and secondary metabolites in foxtail millet using LC-MS, and inheritance patterns of metabolome in millet hybrids. The application of a broad target metabolomics method facilitated the simultaneous identification and quantification of more than 300 metabolites. The metabolic analysis of these compounds, such as flavonoids, phenolamides, hydrocinnamoyl derivatives, vitamins and LPCs, revealed their developmentally controlled accumulation, and natural variation in different tissues/varieties. Species-specific accumulation of secondary metabolites was observed based on a comparative metabolic analysis between millet and rice, such as flavonoid O-rutinosides/neohesperidosides and malonylated flavonoid O-glycosides. In analyzing the metabolic variations between hybrid progenies and their parental lines, including a photothermo-sensitive genic male sterility line and five Zhangzagu varieties, metabolic overdominant, and dominant patterns of inheritance could be observed. For example, hydrocinnamoyl derivatives and feruloylated flavonoids were identified as over-parent heterosis (overdominant) metabolites in milet hybrids. Our work paves the way for developing predictors of hybrid performance and the future analysis of the biosynthesis and regulation of relevant metabolic pathways in millet.

Pectic enzymes as potential enhancers of ascorbic acid production through the D-galacturonate pathway in Solanaceae

The increase of L-Ascorbic Acid (AsA) content in tomato (Solanum lycopersicum) is a common goal in breeding programs due to its beneficial effect on human health. To shed light into the regulation of fruit AsA content, we exploited a Solanum pennellii introgression line (IL12-4-SL) harbouring one quantitative trait locus that increases the content of total AsA in the fruit. Biochemical and transcriptomic analyses were carried out in fruits of IL12-4-SL in comparison with the cultivated line M82 at different stages of ripening. AsA content was studied in relation with pectin methylesterase (PME) activity and the degree of pectin methylesterification (DME). Our results indicated that the increase of AsA content in IL12-4-SL fruits was related with pectin de-methylesterification/degradation. Specific PME, polygalacturonase (PG) and UDP-D-glucuronic-acid-4-epimerase (UGlcAE) isoforms were proposed as components of the D-galacturonate pathway leading to AsA biosynthesis. The relationship between AsA content and PME activity was also exploited in PMEI tobacco plants expressing a specific PME inhibitor (PMEI). Here we report that tobacco PMEI plants, altered in PME activity and degree of pectin methylesterification, showed a reduction in low methylesterified pectic domains and exhibited a reduced AsA content. Overall, our results provide novel biochemical and genetic traits for increasing antioxidant content by marker-assisted selection in the Solanaceae family.

Inheritance patterns in metabolism and growth in diallel crosses of Arabidopsis thaliana from a single growth habitat

Metabolism is a key determinant of plant growth and modulates plant adaptive responses. Increased metabolic variation due to heterozygosity may be beneficial for highly homozygous plants if their progeny is to respond to sudden changes in the habitat. Here, we investigate the extent to which heterozygosity contributes to the variation in metabolism and size of hybrids of Arabidopsis thaliana whose parents are from a single growth habitat. We created full diallel crosses among seven parents, originating from Southern Germany, and analysed the inheritance patterns in primary and secondary metabolism as well as in rosette size in situ. In comparison to primary metabolites, compounds from secondary metabolism were more variable and showed more pronounced non-additive inheritance patterns which could be attributed to epistasis. In addition, we showed that glucosinolates, among other secondary metabolites, were positively correlated with a proxy for plant size. Therefore, our study demonstrates that heterozygosity in local A. thaliana population generates metabolic variation and may impact several tasks directly linked to metabolism.

Canalization of Tomato Fruit Metabolism

To explore the genetic robustness (canalization) of metabolism, we examined the levels of fruit metabolites in multiple harvests of a tomato introgression line (IL) population. The IL partitions the whole genome of the wild species Solanum pennellii in the background of the cultivated tomato (Solanum lycopersicum). We identified several metabolite quantitative trait loci that reduce variability for both primary and secondary metabolites, which we named canalization metabolite quantitative trait loci (cmQTL). We validated nine cmQTL using an independent population of backcross inbred lines, derived from the same parents, which allows increased resolution in mapping the QTL previously identified in the ILs. These cmQTL showed little overlap with QTL for the metabolite levels themselves. Moreover, the intervals they mapped to harbored few metabolism-associated genes, suggesting that the canalization of metabolism is largely controlled by regulatory genes.

Integrative field scale phenotyping for investigating metabolic components of water stress within a vineyard

BACKGROUND

There is currently a high requirement for field phenotyping methodologies/technologies to determine quantitative traits related to crop yield and plant stress responses under field conditions.

METHODS

We employed an unmanned aerial vehicle equipped with a thermal camera as a high-throughput phenotyping platform to obtain canopy level data of the vines under three irrigation treatments. High-resolution imagery (< 2.5 cm/pixel) was employed to estimate the canopy conductance (gc ) via the leaf energy balance model. In parallel, physiological stress measurements at leaf and stem level as well as leaf sampling for primary and secondary metabolome analysis were performed.

RESULTS

Aerial gc correlated significantly with leaf stomatal conductance (gs ) and stem sap flow, benchmarking the quality of our remote sensing technique. Metabolome profiles were subsequently linked with gc and gs via partial least square modelling. By this approach malate and flavonols, which have previously been implicated to play a role in stomatal function under controlled greenhouse conditions within model species, were demonstrated to also be relevant in field conditions.

CONCLUSIONS

We propose an integrative methodology combining metabolomics, organ-level physiology and UAV-based remote sensing of the whole canopy responses to water stress within a vineyard. Finally, we discuss the general utility of this integrative methodology for broad field phenotyping.

De Novo Assembly of a New Solanum pennellii Accession Using Nanopore Sequencing

Updates in nanopore technology have made it possible to obtain gigabases of sequence data. Prior to this, nanopore sequencing technology was mainly used to analyze microbial samples. Here, we describe the generation of a comprehensive nanopore sequencing data set with a median read length of 11,979 bp for a self-compatible accession of the wild tomato species Solanum pennellii We describe the assembly of its genome to a contig N50 of 2.5 MB. The assembly pipeline comprised initial read correction with Canu and assembly with SMARTdenovo. The resulting raw nanopore-based de novo genome is structurally highly similar to that of the reference S. pennellii LA716 accession but has a high error rate and was rich in homopolymer deletions. After polishing the assembly with Illumina reads, we obtained an error rate of <0.02% when assessed versus the same Illumina data. We obtained a gene completeness of 96.53%, slightly surpassing that of the reference S. pennellii Taken together, our data indicate that such long read sequencing data can be used to affordably sequence and assemble gigabase-sized plant genomes.

Genome-Wide Association Mapping Reveals That Specific and Pleiotropic Regulatory Mechanisms Fine-Tune Central Metabolism and Growth in Arabidopsis

Central metabolism is a coordinated network that is regulated at multiple levels by resource availability and by environmental and developmental cues. Its genetic architecture has been investigated by mapping metabolite quantitative trait loci (QTL). A more direct approach is to identify enzyme activity QTL, which distinguishes between cis-QTL in structural genes encoding enzymes and regulatory trans-QTL. Using genome-wide association studies, we mapped QTL for 24 enzyme activities, nine metabolites, three structural components, and biomass in Arabidopsis thaliana We detected strong cis-QTL for five enzyme activities. A cis-QTL for UDP-glucose pyrophosphorylase activity in the UGP1 promoter is maintained through balancing selection. Variation in acid invertase activity reflects multiple evolutionary events in the promoter and coding region of VAC-INVcis-QTL were also detected for ADP-glucose pyrophosphorylase, fumarase, and phosphoglucose isomerase activity. We detected many trans-QTL, including transcription factors, E3 ligases, protein targeting components, and protein kinases, and validated some by knockout analysis. trans-QTL are more frequent but tend to have smaller individual effects than cis-QTL. We detected many colocalized QTL, including a multitrait QTL on chromosome 4 that affects six enzyme activities, three metabolites, protein, and biomass. These traits are coordinately modified by different ACCELERATED CELL DEATH6 alleles, revealing a trade-off between metabolism and defense against biotic stress.

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.

Current understanding of the pathways of flavonoid biosynthesis in model and crop plants

Flavonoids are a signature class of secondary metabolites formed from a relatively simple collection of scaffolds. They are extensively decorated by chemical reactions including glycosylation, methylation, and acylation. They are present in a wide variety of fruits and vegetables and as such in Western populations it is estimated that 20-50 mg of flavonoids are consumed daily per person. In planta they have demonstrated to contribute to both flower color and UV protection. Their consumption has been suggested to presenta wide range of health benefits. Recent technical advances allowing affordable whole genome sequencing, as well as a better inventory of species-by-species chemical diversity, have greatly advanced our understanding as to how flavonoid biosynthesis pathways vary across species. In parallel, reverse genetics combined with detailed molecular phenotyping is currently allowing us to elucidate the functional importance of individual genes and metabolites and by this means to provide further mechanistic insight into their biological roles. Here we provide an inventory of current knowledge of pathways of flavonoid biosynthesis in both the model plant Arabidopsis thaliana and a range of crop species, including tomato, maize, rice, and bean.

Identification of major loci and genomic regions controlling acid and volatile content in tomato fruit: implications for flavor improvement

Plant metabolites are important to world food security due to their roles in crop yield and nutritional quality. Here we report the metabolic profile of 300 tomato accessions (Solanum lycopersicum and related wild species) by quantifying 60 primary and secondary metabolites, including volatile organic compounds, over a period of 2 yr. Metabolite content and genetic inheritance of metabolites varied broadly, both within and between different genetic groups. Using genotype information gained from 10 000 single nucleotide polymorphism markers, we performed a metabolite genome-wide association mapping (GWAS) study. We identified 79 associations influencing 13 primary and 19 secondary metabolites with large effects at high resolution. Four genome regions were detected, highlighting clusters of associations controlling the variation of several metabolites. Local linkage disequilibrium analysis and allele mining identified possible candidate genes which may modulate the content of metabolites that are of significant importance for human diet and fruit consumption. We precisely characterized two associations involved in fruit acidity and phenylpropanoid volatile production. Taken together, this study reveals complex and distinct metabolite regulation in tomato subspecies and demonstrates that GWAS is a powerful tool for gene-metabolite annotation and identification, pathways elucidation, and further crop improvement.

Leveraging Natural Variance towards Enhanced Understanding of Phytochemical Sunscreens

The dependency of plants on sunlight renders exposure to UV a constant hazard. Light of this wavelength is damaging to proteins, RNA, and DNA, with damage to the latter resulting in a high mutagenic potential. To acclimate to environmental changes in light wavelengths and intensity, plants accumulate the production of UV-B-protectant phytochemicals, such as flavonoids and vitamins. Here, we review current and emerging knowledge concerning the biochemical response of plants to UV-B exposure. We additionally outline our opinion that the adoption of broad natural variance represents a powerful strategy by which to identify both novel UV-B-relevant metabolites and the genes regulating their abundance. Finally, we discuss how such information may guide future metabolic engineering strategies aimed at producing stress-tolerant plants.

Genetic dissection of metabolite variation in Arabidopsis seeds: evidence for mQTL hotspots and a master regulatory locus of seed metabolism

To gain insight into genetic factors controlling seed metabolic composition and its relationship to major seed properties, an Arabidopsis recombinant inbred line (RIL) population, derived from accessions Col-0 and C24, was studied using an MS-based metabolic profiling approach. Relative intensities of 311 polar primary metabolites were used to identify associated genomic loci and to elucidate their interactions by quantitative trait locus (QTL) mapping. A total of 786 metabolic QTLs (mQTLs) were unequally distributed across the genome, forming several hotspots. For the branched-chain amino acid leucine, mQTLs and candidate genes were elucidated in detail. Correlation studies displayed links between metabolite levels, seed protein content, and seed weight. Principal component analysis revealed a clustering of samples, with PC1 mapping to a region on the short arm of chromosome IV. The overlap of this region with mQTL hotspots indicates the presence of a potential master regulatory locus of seed metabolism. As a result of database queries, a series of candidate regulatory genes, including bZIP10, were identified within this region. Depending on the search conditions, metabolic pathway-derived candidate genes for 40-61% of tested mQTLs could be determined, providing an extensive basis for further identification and characterization of hitherto unknown genes causal for natural variation of Arabidopsis seed metabolism.

Multidimensional Integrative Genomics Approaches to Dissecting Cardiovascular Disease

Elucidating the mechanisms of complex diseases such as cardiovascular disease (CVD) remains a significant challenge due to multidimensional alterations at molecular, cellular, tissue, and organ levels. To better understand CVD and offer insights into the underlying mechanisms and potential therapeutic strategies, data from multiple omics types (genomics, epigenomics, transcriptomics, metabolomics, proteomics, microbiomics) from both humans and model organisms have become available. However, individual omics data types capture only a fraction of the molecular mechanisms. To address this challenge, there have been numerous efforts to develop integrative genomics methods that can leverage multidimensional information from diverse data types to derive comprehensive molecular insights. In this review, we summarize recent methodological advances in multidimensional omics integration, exemplify their applications in cardiovascular research, and pinpoint challenges and future directions in this incipient field.

Integrated genomics-based mapping reveals the genetics underlying maize flavonoid biosynthesis

BACKGROUND

Flavonoids constitute a diverse class of secondary metabolites which exhibit potent bioactivities for human health and have been indicated to play an important role in plant development and defense. However, accumulation and variation of flavonoid content in diverse maize lines and the genes responsible for their biosynthesis in this important crop remain largely unknown. In this study, we combine genetic mapping, metabolite profiling and gene regulatory network analysis to further enhance understanding of the maize flavonoid pathway.

RESULTS

We repeatedly detected 25 QTL corresponding to 23 distinct flavonoids across different environments or populations. In addition, a total of 39 genes were revealed both by an expression based network analysis and genetic mapping. Finally, the function of three candidate genes, including two UDP-glycosyltransferases (UGT) and an oxygenase which belongs to the flavone synthase super family, was revealed via preliminary molecular functional characterization.

CONCLUSION

We explored the genetic influences on the flavonoid biosynthesis based on integrating the genomic, transcriptomic and metabolomic information which provided a rich source of potential candidate genes. The integrated genomics based genetic mapping strategy is highly efficient for defining the complexity of functional genetic variants and their respective regulatory networks as well as in helping to select candidate genes and allelic variance before embarking on laborious transgenic validations.

Metabolomic analysis of tomato seed germination

INTRODUCTION

Seed germination is inherently related to seed metabolism, which changes throughout its maturation, desiccation and germination processes. The metabolite content of a seed and its ability to germinate are determined by underlying genetic architecture and environmental effects during development.

OBJECTIVE

This study aimed to assess an integrative approach to explore genetics modulating seed metabolism in different developmental stages and the link between seed metabolic- and germination traits.

METHODS

We have utilized gas chromatography-time-of-flight/mass spectrometry (GC-TOF/MS) metabolite profiling to characterize tomato seeds during dry and imbibed stages. We describe, for the first time in tomato, the use of a so-called generalized genetical genomics (GGG) model to study the interaction between genetics, environment and seed metabolism using 100 tomato recombinant inbred lines (RILs) derived from a cross between Solanum lycopersicum and Solanum pimpinellifolium.

RESULTS

QTLs were found for over two-thirds of the metabolites within several QTL hotspots. The transition from dry to 6 h imbibed seeds was associated with programmed metabolic switches. Significant correlations varied among individual metabolites and the obtained clusters were significantly enriched for metabolites involved in specific biochemical pathways.

CONCLUSIONS

Extensive genetic variation in metabolite abundance was uncovered. Numerous identified genetic regions that coordinate groups of metabolites were detected and these will contain plausible candidate genes. The combined analysis of germination phenotypes and metabolite profiles provides a strong indication for the hypothesis that metabolic composition is related to germination phenotypes and thus to seed performance.

A naturally occurring promoter polymorphism of the Arabidopsis FUM2 gene causes expression variation, and is associated with metabolic and growth traits

Fumarate and malate are known intermediates of the TCA cycle, a mitochondrial metabolic pathway generating NADH for respiration. Arabidopsis thaliana and other Brassicaceae contain an additional cytosolic fumarase (FUM2) that functions in carbon assimilation and nitrogen use. Here, we report the identification of a hitherto unknown FUM2 promoter insertion/deletion (InDel) polymorphism found between the Col-0 and C24 accessions, which also divides a large number of Arabidopsis accessions carrying either the Col-0 or the C24 allele. The polymorphism consists of two stretches of 2.1 and 3.8 kb, which are both absent from the promotor region of Col-0 FUM2. By analysing mutants as well as mapping and natural populations with contrasting FUM2 alleles, the promotor insertion was linked to reduced FUM2 mRNA expression, reduced fumarase activity and reduced fumarate/malate ratio in leaves. In a large population of 174 natural accessions, the polymorphism was also found to be associated with the fumarate/malate ratio, malate and fumarate levels, and with dry weight at 15 days after sowing (DAS). The association with biomass production was confirmed in an even larger (251) accession population for dry weight at 22 DAS. The dominant Col-0 allele that results in increased fumarate/malate ratios and enhanced biomass production is predominantly found in central/eastern European accessions, whereas the C24 type allele is prevalent on the Iberian Peninsula, west of the Rhine and in the British Isles. Our findings support the role of FUM2 in diurnal carbon storage, and point to a growth advantage of accessions carrying the FUM2 Col-0 allele.

Combined Use of Genome-Wide Association Data and Correlation Networks Unravels Key Regulators of Primary Metabolism in Arabidopsis thaliana

Plant primary metabolism is a highly coordinated, central, and complex network of biochemical processes regulated at both the genetic and post-translational levels. The genetic basis of this network can be explored by analyzing the metabolic composition of genetically diverse genotypes in a given plant species. Here, we report an integrative strategy combining quantitative genetic mapping and metabolite‒transcript correlation networks to identify functional associations between genes and primary metabolites in Arabidopsis thaliana. Genome-wide association study (GWAS) was used to identify metabolic quantitative trait loci (mQTL). Correlation networks built using metabolite and transcript data derived from a previously published time-course stress study yielded metabolite‒transcript correlations identified by covariation. Finally, results obtained in this study were compared with mQTL previously described. We applied a statistical framework to test and compare the performance of different single methods (network approach and quantitative genetics methods, representing the two orthogonal approaches combined in our strategy) with that of the combined strategy. We show that the combined strategy has improved performance manifested by increased sensitivity and accuracy. This combined strategy allowed the identification of 92 candidate associations between structural genes and primary metabolites, which not only included previously well-characterized gene‒metabolite associations, but also revealed novel associations. Using loss-of-function mutants, we validated two of the novel associations with genes involved in tyrosine degradation and in β-alanine metabolism. In conclusion, we demonstrate that applying our integrative strategy to the largely untapped resource of metabolite-transcript associations can facilitate the discovery of novel metabolite-related genes. This integrative strategy is not limited to A. thaliana, but generally applicable to other plant species.

Comparative and parallel genome-wide association studies for metabolic and agronomic traits in cereals

The plant metabolome is characterized by extensive diversity and is often regarded as a bridge between genome and phenome. Here we report metabolic and phenotypic genome-wide studies (mGWAS and pGWAS) in rice grain that, in addition to previous metabolic GWAS in rice leaf and maize kernel, show both distinct and overlapping aspects of genetic control of metabolism within and between species. We identify new candidate genes potentially influencing important metabolic and/or morphological traits. We show that the differential genetic architecture of rice metabolism between different tissues is in part determined by tissue specific expression. Using parallel mGWAS and pGWAS we identify new candidate genes potentially responsible for variation in traits such as grain colour and size, and provide evidence of metabotype-phenotype linkage. Our study demonstrates a powerful strategy for interactive functional genomics and metabolomics in plants, especially the cloning of minor QTLs for complex phenotypic traits.

Ultrahigh resolution metabolomics for S-containing metabolites

The advent of the genome-editing era greatly increases the opportunities for synthetic biology research that aims to enhance production of potentially useful bioactive metabolites in heterologous hosts. A wide variety of sulfur (S)-containing metabolites (S-metabolites) are known to possess bioactivities and health-promoting properties, but finding them and their chemical assignment using mass spectrometry-based metabolomics has been difficult. In this review, we highlight recent advances on the targeted metabolomic analysis of S-metabolites (S-omics) in plants using ultrahigh resolution mass spectrometry. The use of exact mass and signal intensity differences between ³²S-containing monoisotopic ions and counterpart ³⁴S isotopic ions exploits an entirely new method to characterize S-metabolites. Finally, we discuss the availability of S-omics for synthetic biology.

Plant Metabolomics: An Indispensable System Biology Tool for Plant Science

As genomes of many plant species have been sequenced, demand for functional genomics has dramatically accelerated the improvement of other omics including metabolomics. Despite a large amount of metabolites still remaining to be identified, metabolomics has contributed significantly not only to the understanding of plant physiology and biology from the view of small chemical molecules that reflect the end point of biological activities, but also in past decades to the attempts to improve plant behavior under both normal and stressed conditions. Hereby, we summarize the current knowledge on the genetic and biochemical mechanisms underlying plant growth, development, and stress responses, focusing further on the contributions of metabolomics to practical applications in crop quality improvement and food safety assessment, as well as plant metabolic engineering. We also highlight the current challenges and future perspectives in this inspiring area, with the aim to stimulate further studies leading to better crop improvement of yield and quality.

Plant secondary metabolism linked glycosyltransferases: An update on expanding knowledge and scopes

The multigene family of enzymes known as glycosyltransferases or popularly known as GTs catalyze the addition of carbohydrate moiety to a variety of synthetic as well as natural compounds. Glycosylation of plant secondary metabolites is an emerging area of research in drug designing and development. The unsurpassing complexity and diversity among natural products arising due to glycosylation type of alterations including glycodiversification and glycorandomization are emerging as the promising approaches in pharmacological studies. While, some GTs with broad spectrum of substrate specificity are promising candidates for glycoengineering while others with stringent specificity pose limitations in accepting molecules and performing catalysis. With the rising trends in diseases and the efficacy/potential of natural products in their treatment, glycosylation of plant secondary metabolites constitutes a key mechanism in biogeneration of their glycoconjugates possessing medicinal properties. The present review highlights the role of glycosyltransferases in plant secondary metabolism with an overview of their identification strategies, catalytic mechanism and structural studies on plant GTs. Furthermore, the article discusses the biotechnological and biomedical application of GTs ranging from detoxification of xenobiotics and hormone homeostasis to the synthesis of glycoconjugates and crop engineering. The future directions in glycosyltransferase research should focus on the synthesis of bioactive glycoconjugates via metabolic engineering and manipulation of enzyme's active site leading to improved/desirable catalytic properties. The multiple advantages of glycosylation in plant secondary metabolomics highlight the increasing significance of the GTs, and in near future, the enzyme superfamily may serve as promising path for progress in expanding drug targets for pharmacophore discovery and development.

The Regulation of Essential Amino Acid Synthesis and Accumulation in Plants

Although amino acids are critical for all forms of life, only proteogenic amino acids that humans and animals cannot synthesize de novo and therefore must acquire in their diets are classified as essential. Nine amino acids-lysine, methionine, threonine, phenylalanine, tryptophan, valine, isoleucine, leucine, and histidine-fit this definition. Despite their nutritional importance, several of these amino acids are present in limiting quantities in many of the world's major crops. In recent years, a combination of reverse genetic and biochemical approaches has been used to define the genes encoding the enzymes responsible for synthesizing, degrading, and regulating these amino acids. In this review, we describe recent advances in our understanding of the metabolism of the essential amino acids, discuss approaches for enhancing their levels in plants, and appraise efforts toward their biofortification in crop plants.

Molecular control of crop shade avoidance

The shade avoidance response (SAR) in crops can be detrimental to yield, as precious carbon resources are redirected to stem or petiole elongation at the expense of biomass production. While breeding efforts have inadvertently attenuated this response in staple crops through correlated selection for yield at high density, it has not been eliminated. The extensive work done in Arabidopsis has provided a detailed understanding of the SAR and can be used as a framework for understanding the SAR in crop species. Recent crop SAR works point to auxin as a key factor in regulating the SAR in several crop species. These works also clearly demonstrate that one model for crop SAR will not fit all, and thus we need to move forward with studying the genetic players of the SAR in several model crop species. In this review, we provide the current knowledge of the SAR as reported at the physiological and molecular levels.

Beyond the Canon: Within-Plant and Population-Level Heterogeneity in Jasmonate Signaling Engaged by Plant-Insect Interactions

Plants have evolved sophisticated communication and defense systems with which they interact with insects. Jasmonates are synthesized from the oxylipin pathway and act as pivotal cellular orchestrators of many of the metabolic and physiological processes that mediate these interactions. Many of these jasmonate-dependent responses are tissue-specific and translate from modulations of the canonical jasmonate signaling pathway. Here we provide a short overview of within-plant heterogeneities in jasmonate signaling and dependent responses in the context of plant-insect interactions as illuminated by examples from recent work with the ecological model, Nicotiana attenuata. We then discuss means of manipulating jasmonate signaling by creating tissue-specific jasmonate sinks, and the micrografting of different transgenic plants. The metabolic phenotyping of these manipulations provides an integrative understanding of the functional significance of deviations from the canonical model of this hormonal pathway. Additionally, natural variation in jasmonate biosynthesis and signaling both among and within species can explain polymorphisms in resistance to insects in nature. In this respect, insect-guided explorations of population-level variations in jasmonate metabolism have revealed more complexity than previously realized and we discuss how different "omic" techniques can be used to exploit the natural variation that occurs in this important signaling pathway.

Hydrophilic antioxidants from Andean tomato landraces assessed by their bioactivities in vitro and in vivo

Potential nutraceutical properties of hydrophilic antioxidants in fruits of tomato landraces collected in Andean valleys were characterised. Antioxidant metabolites were measured by HPLC-DAD-MS/MS in mature fruits and their biological activities were assessed by in vitro and in vivo methods. In vitro antioxidant capacities were established by TEAC and FRAP methods. For in vivo biological activities we used a procedure based on Caenorhabditis elegans subjected to thermal stress. In addition, Saccharomyces cerevisiae was also used as a rapid screening system to evaluate tomato antioxidant capacity. All tomato accessions displayed significant differences regarding metabolic composition, biological activity and antioxidant capacity. Metabolite composition was associated with geographical origin and fruit size. Antioxidant activities showed significant association with phenolic compounds, such as caffeoylquinic acids, ferulic acid-O-hexosides and rutin. Combination of in vitro and in vivo methods applied here allowed evaluation of the variability in nutraceutical properties of tomato landraces, which could be applied to other fruits or food products.

Genomics-based strategies for the use of natural variation in the improvement of crop metabolism

Next-generation genomics holds great potential in the study of plant phenotypic variation. With several crop reference genomes now available, the affordable costs of de novo genome assembly or target resequencing offer the opportunity to mine the enormous amount of genetic diversity hidden in crop wild relatives. Wide introgressions from these wild ancestors species or land races represent a possible strategy to improve cultivated varieties. In this review, we discuss the mechanisms underlying metabolic diversity within plant species and the possible strategies (and barriers) to introgress novel metabolic traits into cultivated varieties. We show how deep genomic surveys uncover various types of structural variants from extended gene pools of major crops and highlight how this variation may be used for the improvement of crop metabolism.

Identification of a Solanum pennellii Chromosome 4 Fruit Flavor and Nutritional Quality-Associated Metabolite QTL

A major resource for tomato quality improvement and gene discovery is the collection of introgression lines (ILs) of cultivated Solanum lycopersicum that contain different, defined chromosomal segments derived from the wild tomato relative, S. pennellii. Among these lines, IL4-4, in which the bottom of S. lycopersicum (cv. M82) chromosome 4 is replaced by the corresponding S. pennellii segment, is altered in many primary and secondary metabolites, including many related to fruit flavor and nutritional quality. Here, we provide a comprehensive profile of IL4-4 ripe fruit metabolites, the transcriptome and fine mapping of sub-ILs. Remarkably, out of 327 quantified metabolites, 185 were significantly changed in IL4-4 fruit, compared to the control. These altered metabolites include volatile organic compounds, primary and secondary metabolites. Partial least squares enhanced discriminant analysis of the metabolite levels among sub-ILs indicated that a genome region encompassing 20 putative open reading frames is responsible for most of the metabolic changes in IL4-4 fruit. This work provides comprehensive insights into IL4-4 fruit biochemistry, identifying a small region of the genome that has major effects on a large and diverse set of metabolites.

Genetic dissection of the (poly)phenol profile of diploid strawberry (Fragaria vesca) fruits using a NIL collection

Over the last few years, diploid strawberry (Fragaria vesca) has been recognized as a model species for applied research of cultivated strawberry (Fragaria × ananassa) that is one of the most economically important crops. Berries, particularly strawberries, are known for their high antioxidant capacity due to a high concentration of (poly) phenolic compounds. Studies have already characterized the phenolic composition of fruits from sets of cultivated strawberries but the quantification of phenolics in a Fragaria mapping population has not been reported, yet. The metabolite profiling of a F. vesca near isogenic line (NIL) collection by LC-MS allowed the unambiguous identification of 22 (poly)-phenols, including anthocyanins, flavonols, flavan-3-ols, flavanones, hydroxycinnamic acid derivatives, and ellagic acid in the diploid strawberry fruit. The variability in the collection revealed that the genetic factor was more decisive than the environmental factor for the accumulation of 18 of the 24 compounds. Genotyping the NIL collection with the Axiom® IStraw90® SNPs array, we were able to map 76 stable QTLs controlling accumulation of the (poly)-phenolic compounds. They provide a powerful new tool to characterise candidate genes to increase the antioxidant capacity of fruits and produce healthier strawberries for consumers.

Identification of Loci Affecting Accumulation of Secondary Metabolites in Tomato Fruit of a Solanum lycopersicum × Solanum chmielewskii Introgression Line Population

Semi-polar metabolites such as flavonoids, phenolic acids, and alkaloids are very important health-related compounds in tomato. As a first step to identify genes responsible for the synthesis of semi-polar metabolites, quantitative trait loci (QTLs) that influence the semi-polar metabolite content in red-ripe tomato fruit were identified, by characterizing fruits of a population of introgression lines (ILs) derived from a cross between the cultivated tomato Solanum lycopersicum and the wild species Solanum chmielewskii. By analyzing fruits of plants grown at two different locations, we were able to identify robust metabolite QTLs for changes in phenylpropanoid glycoconjugation on chromosome 9, for accumulation of flavonol glycosides on chromosome 5, and for alkaloids on chromosome 7. To further characterize the QTLs we used a combination of genome sequencing, transcriptomics and targeted metabolomics to identify candidate key genes underlying the observed metabolic variation.

Combining Quantitative Genetics Approaches with Regulatory Network Analysis to Dissect the Complex Metabolism of the Maize Kernel

Metabolic quantitative trait locus (QTL) studies have allowed us to better understand the genetic architecture underlying naturally occurring plant metabolic variance. Here, we use two recombinant inbred line (RIL) populations to dissect the genetic architecture of natural variation of 155 metabolites measured in the mature maize (Zea mays) kernel. Overall, linkage mapping identified 882 metabolic QTLs in both RIL populations across two environments, with an average of 2.1 QTLs per metabolite. A large number of metabolic QTLs (more than 65%) were identified with moderate effects (r(2) = 2.1%-10%), while a small portion (less than 35%) showed major effects (r(2) > 10%). Epistatic interactions between these identified loci were detected for more than 30% of metabolites (with the proportion of phenotypic variance ranging from 1.6% to 37.8%), implying that genetic epistasis is not negligible in determining metabolic variation. In total, 57 QTLs were validated by our previous genome-wide association study on the same metabolites that provided clues for exploring the underlying genes. A gene regulatory network associated with the flavonoid metabolic pathway was constructed based on the transcriptional variations of 28,769 genes in kernels (15 d after pollination) of 368 maize inbred lines. A large number of genes (34 of 58) in this network overlapped with previously defined genes controlled by maize PERICARP COLOR1, while three of them were identified here within QTL intervals for multiple flavonoids. The deeply characterized RIL populations, elucidation of metabolic phenotypes, and identification of candidate genes lay the foundation for maize quality improvement.

Metabolite Profiling of Italian Tomato Landraces with Different Fruit Types

Increased interest toward traditional tomato varieties is fueled by the need to rescue desirable organoleptic traits and to improve the quality of fresh and processed tomatoes in the market. In addition, the phenotypic and genetic variation preserved in tomato landraces represents a means to understand the genetic basis of traits related to health and organoleptic aspects and improve them in modern varieties. To establish a framework for this approach, we studied the content of several metabolites in a panel of Italian tomato landraces categorized into three broad fruit type classes (flattened/ribbed, pear/oxheart, round/elongate). Three modern hybrids, corresponding to the three fruit shape typologies, were included as reference. Red ripe fruits were morphologically characterized and biochemically analyzed for their content in glycoalkaloids, phenols, amino acids, and Amadori products. The round/elongate types showed a higher content in glycoalkaloids, whereas flattened types had higher levels of phenolic compounds. Flattened tomatoes were also rich in total amino acids and in particular in glutamic acid. Multivariate analysis of amino acid content clearly separated the three classes of fruit types. Making allowance of the very low number of genotypes, phenotype-marker relationships were analyzed after retrieving single nucleotide polymorphisms (SNPs) among the landraces available in the literature. Sixty-six markers were significantly associated with the studied traits. The positions of several of these SNPs showed correspondence with already described genomic regions and QTLs supporting the reliability of the association. Overall the data indicated that significant changes in quality-related metabolites occur depending on the genetic background in traditional tomato germplasm, frequently according to specific fruit shape categories. Such a variability is suitable to harness association mapping for metabolic quality traits using this germplasm as an experimental population, paving the way for investigating their genetic/molecular basis, and facilitating breeding for quality-related compounds in tomato fruits.

Natural Variation of Plant Metabolism: Genetic Mechanisms, Interpretive Caveats, and Evolutionary and Mechanistic Insights

Combining quantitative genetics studies with metabolomics/metabolic profiling platforms, genomics, and transcriptomics is creating significant progress in identifying the causal genes controlling natural variation in metabolite accumulations and profiles. In this review, we discuss key mechanistic and evolutionary insights that are arising from these studies. This includes the potential role of transport and other processes in leading to a separation of the site of mechanistic causation and metabolic consequence. A reilluminated observation is the potential for genomic variation in the organelle to alter phenotypic variation alone and in epistatic interaction with the nuclear genetic variation. These studies are also highlighting new aspects of metabolic pleiotropy both in terms of the breadth of loci altering metabolic variation as well as the potential for broader effects on plant defense regulation of the metabolic variation than has previously been predicted. We also illustrate caveats that can be overlooked when translating quantitative genetics descriptors such as heritability and per-locus r(2) to mechanistic or evolutionary interpretations.

Integrative Approaches to Enhance Understanding of Plant Metabolic Pathway Structure and Regulation

Huge insight into molecular mechanisms and biological network coordination have been achieved following the application of various profiling technologies. Our knowledge of how the different molecular entities of the cell interact with one another suggests that, nevertheless, integration of data from different techniques could drive a more comprehensive understanding of the data emanating from different techniques. Here, we provide an overview of how such data integration is being used to aid the understanding of metabolic pathway structure and regulation. We choose to focus on the pairwise integration of large-scale metabolite data with that of the transcriptomic, proteomics, whole-genome sequence, growth- and yield-associated phenotypes, and archival functional genomic data sets. In doing so, we attempt to provide an update on approaches that integrate data obtained at different levels to reach a better understanding of either single gene function or metabolic pathway structure and regulation within the context of a broader biological process.

Metabolomics-Inspired Insight into Developmental, Environmental and Genetic Aspects of Tomato Fruit Chemical Composition and Quality

Tomato was one of the first plant species to be evaluated using metabolomics and remains one of the best characterized, with tomato fruit being both an important source of nutrition in the human diet and a valuable model system for the development of fleshy fruits. Additionally, given the broad habitat range of members of the tomato clade and the extensive use of exotic germplasm in tomato genetic research, it represents an excellent genetic model system for understanding both metabolism per se and the importance of various metabolites in conferring stress tolerance. This review summarizes technical approaches used to characterize the tomato metabolome to date and details insights into metabolic pathway structure and regulation that have been obtained via analysis of tissue samples taken under different developmental or environmental circumstance as well as following genetic perturbation. Particular attention is paid to compounds of importance for nutrition or the shelf-life of tomatoes. We propose furthermore how metabolomics information can be coupled to the burgeoning wealth of genome sequence data from the tomato clade to enhance further our understanding of (i) the shifts in metabolic regulation occurring during development and (ii) specialization of metabolism within the tomato clade as a consequence of either adaptive evolution or domestication.

Ectopic expression of snapdragon transcription factors facilitates the identification of genes encoding enzymes of anthocyanin decoration in tomato

Given the potential health benefits of polyphenolic compounds in the diet, there is a growing interest in the generation of food crops enriched with health-protective flavonoids. We undertook a series of metabolite analyses of tomatoes ectopically expressing the Delila and Rosea1 transcription factor genes from snapdragon (Antirrhinum majus), paying particular attention to changes in phenylpropanoids compared to controls. These analyses revealed multiple changes, including depletion of rutin and naringenin chalcone, and enhanced levels of anthocyanins and phenylacylated flavonol derivatives. We isolated and characterized the chemical structures of the two most abundant anthocyanins, which were shown by NMR spectroscopy to be delphinidin-3-(4'''-O-trans-p-coumaroyl)-rutinoside-5-O-glucoside and petunidin-3-(4'''-O-trans-p-coumaroyl)-rutinoside-5-O-glucoside. By performing RNA sequencing on both purple fruit and wild-type fruit, we obtained important information concerning the relative expression of both structural and transcription factor genes. Integrative analysis of the transcript and metabolite datasets provided compelling evidence of the nature of all anthocyanin biosynthetic genes, including those encoding species-specific anthocyanin decoration enzymes. One gene, SlFdAT1 (Solyc12g088170), predicted to encode a flavonoid-3-O-rutinoside-4'''-phenylacyltransferase, was characterized by assays of recombinant protein and over-expression assays in tobacco. The combined data are discussed in the context of both our current understanding of phenylpropanoid metabolism in Solanaceous species, and evolution of flavonoid decorating enzymes and their transcriptional networks in various plant species.

Genetic Determinants of the Network of Primary Metabolism and Their Relationships to Plant Performance in a Maize Recombinant Inbred Line Population

Deciphering the influence of genetics on primary metabolism in plants will provide insights useful for genetic improvement and enhance our fundamental understanding of plant growth and development. Although maize (Zea mays) is a major crop for food and feed worldwide, the genetic architecture of its primary metabolism is largely unknown. Here, we use high-density linkage mapping to dissect large-scale metabolic traits measured in three different tissues (leaf at seedling stage, leaf at reproductive stage, and kernel at 15 d after pollination [DAP]) of a maize recombinant inbred line population. We identify 297 quantitative trait loci (QTLs) with moderate (86.2% of the mapped QTL, R(2) = 2.4 to 15%) to major effects (13.8% of the mapped QTL, R(2) >15%) for 79 primary metabolites across three tissues. Pairwise epistatic interactions between these identified loci are detected for more than 25.9% metabolites explaining 6.6% of the phenotypic variance on average (ranging between 1.7 and 16.6%), which implies that epistasis may play an important role for some metabolites. Key candidate genes are highlighted and mapped to carbohydrate metabolism, the tricarboxylic acid cycle, and several important amino acid biosynthetic and catabolic pathways, with two of them being further validated using candidate gene association and expression profiling analysis. Our results reveal a metabolite-metabolite-agronomic trait network that, together with the genetic determinants of maize primary metabolism identified herein, promotes efficient utilization of metabolites in maize improvement.

Boosting Sensitivity in Liquid Chromatography-Fourier Transform Ion Cyclotron Resonance-Tandem Mass Spectrometry for Product Ion Analysis of Monoterpene Indole Alkaloids

In metabolomics, the analysis of product ions in tandem mass spectrometry (MS/MS) is noteworthy to chemically assign structural information. However, the development of relevant analytical methods are less advanced. Here, we developed a method to boost sensitivity in liquid chromatography-Fourier transform ion cyclotron resonance-tandem mass spectrometry analysis (MS/MS boost analysis). To verify the MS/MS boost analysis, both quercetin and uniformly labeled (13)C quercetin were analyzed, revealing that the origin of the product ions is not the instrument, but the analyzed compounds resulting in sensitive product ions. Next, we applied this method to the analysis of monoterpene indole alkaloids (MIAs). The comparative analyses of MIAs having indole basic skeleton (ajmalicine, catharanthine, hirsuteine, and hirsutine) and oxindole skeleton (formosanine, isoformosanine, pteropodine, isopteropodine, rhynchophylline, isorhynchophylline, and mitraphylline) identified 86 and 73 common monoisotopic ions, respectively. The comparative analyses of the three pairs of stereoisomers showed more than 170 common monoisotopic ions in each pair. This method was also applied to the targeted analysis of MIAs in Catharanthus roseus and Uncaria rhynchophylla to profile indole and oxindole compounds using the product ions. This analysis is suitable for chemically assigning features of the metabolite groups, which contributes to targeted metabolome analysis.