Defense-related phenylpropanoid biosynthetic gene clusters in rice

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.

Comprehensive evaluation of the response to aluminum stress in olive tree (Olea europaea L.)

Olive (Olea europaea L.) is an ancient tree species in the Mediterranean, but the lack of knowledge about aluminum-resistant varieties limits its introduction to acidic soil. The objective of this study was to have a comprehensive evaluation of the response to aluminum stress in olive tree at germplasm, metabolome, and transcriptome levels. In this experiment, seedlings of 97 olive germplasm with 1.0-3.0 cm roots and two leaves were treated with 50 μM Al³⁺ (pH = 5.0). By factor analysis of the traits of defoliation rate, rooting rate, length of extended root, and length of new root, 97 germplasm were classified into five different groups according to their diverse responses to aluminum stress: 5 highly resistant (5.15%), 30 moderately resistant (30.93%), 31 general (31.96%), 23 moderately sensitive (23.71%), and 8 highly sensitive (8.25%) germplasm. The three most sensitive and three most resistant germplasm were further used for metabolome and transcriptome analysis. Exposed to aluminum stress, 96 differentially accumulated metabolites (DAMs)/4,845 differentially expressed genes (DEGs) and 66 DAMs/2,752 DEGs were identified in highly sensitive and resistant germplasm, respectively. Using multi-omics technology, the pathways and related DAMs/DEGs involved in cell wall/cytoplasm receptors, reactive oxygen species balance, hormone induction, synthesis of organic acids, Al³⁺ transport, and synthesis of metabolites were identified to mainly regulate the response to aluminum stress in olive. This study provides a theoretical guide and prior germplasm and genes for further genetic improvement of aluminum tolerance in the olive tree.

Gene Co-expression Network Analysis of the Comparative Transcriptome Identifies Hub Genes Associated With Resistance to Aspergillus flavus L. in Cultivated Peanut (Arachis hypogaea L.)

Cultivated peanut (Arachis hypogaea L.), a cosmopolitan oil crop, is susceptible to a variety of pathogens, especially Aspergillus flavus L., which not only vastly reduce the quality of peanut products but also seriously threaten food safety for the contamination of aflatoxin. However, the key genes related to resistance to Aspergillus flavus L. in peanuts remain unclear. This study identifies hub genes positively associated with resistance to A. flavus in two genotypes by comparative transcriptome and weighted gene co-expression network analysis (WGCNA) method. Compared with susceptible genotype (Zhonghua 12, S), the rapid response to A. flavus and quick preparation for the translation of resistance-related genes in the resistant genotype (J-11, R) may be the drivers of its high resistance. WGCNA analysis revealed that 18 genes encoding pathogenesis-related proteins (PR10), 1-aminocyclopropane-1-carboxylate oxidase (ACO1), MAPK kinase, serine/threonine kinase (STK), pattern recognition receptors (PRRs), cytochrome P450, SNARE protein SYP121, pectinesterase, phosphatidylinositol transfer protein, and pentatricopeptide repeat (PPR) protein play major and active roles in peanut resistance to A. flavus. Collectively, this study provides new insight into resistance to A. flavus by employing WGCNA, and the identification of hub resistance-responsive genes may contribute to the development of resistant cultivars by molecular-assisted breeding.