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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.

As one of the most important crops in the world, rice (Oryza sativa) is a model plant for metabolome research. Although many studies have focused on the analysis of specific tissues, the changes in metabolite abundance across the entire life cycle have not yet been determined. In this study, combining both targeted and nontargeted metabolite profiling methods, a total of 825 annotated metabolites were quantified in rice samples from different tissues covering the entire life cycle. The contents of metabolites in different tissues of rice were significantly different, with various metabolites accumulating in the plumule and radicle during seed germination. Combining these data with transcriptome data obtained from the same time period, we constructed the Rice Metabolic Regulation Network. The metabolites and co-expressed genes were further divided into 12 clusters according to their accumulation patterns, with members within each cluster displaying a uniform and clear pattern of abundance across development. Using this dataset, we established a comprehensive metabolic profile of the rice life cycle and used two independent strategies to identify novel transcription factors—namely the use of known regulatory genes as bait to screen for new networks underlying lignin metabolism and the unbiased identification of new glycerophospholipid metabolism regulators on the basis of tissue specificity. This study thus demonstrates how guilt-by-association analysis of metabolome and transcriptome data spanning the entire life cycle in cereal crops provides novel resources and tools to aid in understanding the mechanisms underlying important agronomic traits.

Phenolamides (PAs), a diverse group of specialized metabolites, including hydroxycinnamoylputrescine (HP), hydroxycinnamoylagmatine, and hydroxycinnamoyltryptamine, are important in plant resistance to biotic stress. However, the genes involved in the biosynthesis and modulation of PAs have not been fully elucidated. This study identified an HP biosynthetic gene cluster in rice (Oryza sativa) comprising one gene (OsODC) encoding a decarboxylase and two tandem-duplicated genes (OsPHT3 and OsPHT4) encoding putrescine hydroxycinnamoyl acyltransferases coexpressed in different tissues. OsODC catalyzes the conversion of ornithine to putrescine, which is used in HP biosynthesis involving OsPHT3 and OsPHT4. OsPHT3 or OsPHT4 overexpression causes HP accumulation and cell death and putrescine hydroxycinnamoyl acyltransferases (PHT) activity-dependent resistance against the fungal pathogen Magnaporthe oryzae. OsODC overexpression plants also confer enhanced resistance to M. oryzae. Notably, the basic leucine zipper transcription factor APIP5, a negative regulator of cell death, directly binds to the OsPHT4 promoter, repressing its transcription. Moreover, APIP5 suppression induces OsPHT4 expression and HP accumulation. Comparative genomic analysis revealed that the HP biosynthetic gene cluster is conserved in monocots. These results characterized a previously unidentified monocot-specific gene cluster that is involved in HP biosynthesis and contributes to defense and cell death in rice.

Secondary metabolism in plants gives rise to a vast array of small-molecule natural products. The discovery of operon-like gene clusters in plants has provided a new perspective on the evolution of specialized metabolism and the opportunity to rapidly advance the metabolic engineering of natural product production. Here, we review historical aspects of the study of plant metabolic gene clusters as well as general strategies for identifying plant metabolic gene clusters in the multi-omics era. We also emphasize the exploration of their natural variation and evolution, as well as new strategies for the prospecting of plant metabolic gene clusters and a deeper understanding of how their structure influences their function.

Plants produce specialized metabolites to adapt to the ever-changing environments. Flavonoids are antioxidants essential for growth, development, and breeding with increased stress resistance in crops. However, the mechanism of the involvement of flavonoids in ultraviolet-B (UV-B) stress in rice (Oryza sativa) is largely unknown. In this study, we cloned and functionally identified a receptor-like kinase (OsRLCK160) and a bZIP transcription factor (OsbZIP48) positively regulating flavonoid accumulation through metabolite-based genome-wide association study of the flavonoid content in rice. Meanwhile, OsRLCK160 interacted with and phosphorylated OsbZIP48 to regulate the flavonoid accumulation and participate in UV-B tolerance in rice. Our study indicates the importance of applying OsRLCK160 and OsbZIP48 to advance the fundamental understanding of stable rice production and breed UV-B-tolerant rice varieties, which may contribute to breeding high-yield rice varieties.

Diterpenoids are the major group of antimicrobial phytoalexins in rice1,2. Here, we report the discovery of a rice diterpenoid gene cluster on chromosome 7 (DGC7) encoding the entire biosynthetic pathway to 5,10-diketo-casbene, a member of the monocyclic casbene-derived diterpenoids. We revealed that DGC7 is regulated directly by JMJ705 through methyl jasmonate-mediated epigenetic control3. Functional characterization of pathway genes revealed OsCYP71Z21 to encode a casbene C10 oxidase, sought after for the biosynthesis of an array of medicinally important diterpenoids. We further show that DGC7 arose relatively recently in the Oryza genus, and that it was partly formed in Oryza rufipogon and positively selected for in japonica during domestication. Casbene-synthesizing enzymes that are functionally equivalent to OsTPS28 are present in several species of Euphorbiaceae but gene tree analysis shows that these and other casbene-modifying enzymes have evolved independently. As such, combining casbene-modifying enzymes from these different families of plants may prove effective in producing a diverse array of bioactive diterpenoid natural products. A rice diterpenoid gene cluster is reported that controls the biosynthesis of 5,10-diketo-casbene, a phytoalexin that confers resistance to rice bacterial blight and blast fungus. It recently evolved in the japonica subspecies under artificial selection.

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.