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.

Haploid induction (HI) is an important tool in crop breeding. Phospholipase A1 (ZmPLA1)/NOT LIKE DAD (NLD)/MATRILINEAL (MTL) is a key gene controlling HI in maize; however, the underlying molecular mechanism remains unclear. In this study, to dissect why loss of ZmPLA1 function could mediate HI we performed a comprehensive multiple omics analysis of zmpla1 mutant anthers by integrating transcriptome, metabolome, quantitative proteome, and protein modification data. Functional classes of significantly enriched or differentially abundant molecular entities were found to be associated with the oxidative stress response, suggesting that a reactive oxygen species (ROS) burst plays a critical role in HI. In support of this, we further discovered that a simple chemical treatment of pollen with ROS reagents could lead to HI. Moreover, we identified ZmPOD65, which encodes a sperm-specific peroxidase, as a new gene controlling HI. Taken together, our study revealed a likely mechanism of HI, discovered a new gene controlling HI, and created a new method for HI in maize, indicating the importance of ROS balance in maintaining normal reproduction and providing a potential route to accelerate crop breeding.

Tomato (Solanum lycopersicum) is a major horticultural crop worldwide and has emerged as a preeminent model for metabolic research. Although many research efforts have focused on the analysis of metabolite differences between varieties and species, the dynamics of metabolic changes during the tomato growth cycle and the regulatory networks that underlie these changes are poorly understood. In this study, we integrated high-resolution spatio-temporal metabolome and transcriptome data to systematically explore the metabolic landscape across 20 major tomato tissues and growth stages. In the resulting MicroTom Metabolic Network, the 540 detected metabolites and their co-expressed genes could be divided into 10 distinct clusters based on their biological functions. Using this dataset, we constructed a global map of the major metabolic changes that occur throughout the tomato growth cycle and dissected the underlying regulatory network. In addition to verifying previously well-established regulatory networks for important metabolites, we identified novel transcription factors that regulate the biosynthesis of important secondary metabolites such as steroidal glycoalkaloids and flavonoids. Our findings provide insights into spatio-temporal changes in tomato metabolism and generate a valuable resource for the study of metabolic regulatory processes in model plants.

Metabolic adjustments are a significant, but poorly understood, part of the response of plants to oxidative stress. In a previous study (Baxter et al., 2007), the metabolic response of Arabidopsis cells in culture to induction of oxidative stress by menadione was characterized. An emergency survival strategy was uncovered in which anabolic primary metabolism was largely down-regulated in favour of catabolic and antioxidant metabolism. The response in whole plant tissues may be different and we have therefore investigated the response of Arabidopsis roots to menadione treatment, analyzing the transcriptome, metabolome and key metabolic fluxes with focus on primary as well as secondary metabolism. Using a redox-sensitive GFP, it was also shown that menadione causes redox perturbation, not just in the mitochondrion, but also in the cytosol and plastids of roots. In the first 30 min of treatment, the response was similar to the cell culture: there was a decrease in metabolites of the TCA cycle and amino acid biosynthesis and the transcriptomic response was dominated by up-regulation of DNA regulatory proteins. After 2 and 6 h of treatment, the response of the roots was different to the cell culture. Metabolite levels did not remain depressed, but instead recovered and, in the case of pyruvate, some amino acids and aliphatic glucosinolates showed a steady increase above control levels. However, no major changes in fluxes of central carbon metabolism were observed and metabolic transcripts changed largely independently of the corresponding metabolites. Together, the results suggest that root tissues can recover metabolic activity after oxidative inhibition and highlight potentially important roles for glycolysis and the oxidative pentose phosphate pathway.