Parallel Metabolomic and Transcriptomic Analysis Reveals Key Factors for Quality Improvement of Tea Plants

Depicting the genetic and metabolic panorama of chemical diversity in the tea plant

As a frequently consumed beverage worldwide, tea is rich in naturally important bioactive metabolites. Combining genetic, metabolomic and biochemical methodologies, here, we present a comprehensive study to dissect the chemical diversity in tea plant. A total of 2837 metabolites were identified at high-resolution with 1098 of them being structurally annotated and 63 of them were structurally identified. Metabolite-based genome-wide association mapping identified 6199 and 7823 metabolic quantitative trait loci (mQTL) for 971 and 1254 compounds in young leaves (YL) and the third leaves (TL), respectively. The major mQTL (i.e., P < 1.05 × 10-5, and phenotypic variation explained (PVE) > 25%) were further interrogated. Through extensive annotation of the tea metabolome as well as network-based analysis, this study broadens the understanding of tea metabolism and lays a solid foundation for revealing the natural variations in the chemical composition of the tea plant. Interestingly, we found that galloylations, rather than hydroxylations or glycosylations, were the largest class of conversions within the tea metabolome. The prevalence of galloylations in tea is unusual, as hydroxylations and glycosylations are typically the most prominent conversions of plant specialized metabolism. The biosynthetic pathway of flavonoids, which are one of the most featured metabolites in tea plant, was further refined with the identified metabolites. And we demonstrated the further mining and interpretation of our GWAS results by verifying two identified mQTL (including functional candidate genes CsUGTa, CsUGTb, and CsCCoAOMT) and completing the flavonoid biosynthetic pathway of the tea plant.

Metabonomics Analysis of Stem Extracts from Dalbergia sissoo

Dalbergia sissoo is a woody plant with economic and medicinal value. As the pharmacological qualities and properties of the wood from this plant primarily depend on its extractives, in this study, the metabolomic analysis of extractives from its stems was carried out using UPLC-MS/MS. A total of 735 metabolites were detected from two groups of samples, heartwood and sapwood, with the largest number of terpenoids in type and the largest number of flavonoids in quantity. The PCA and cluster analysis showed significant differences in the metabolite composition between the two groups. The differential metabolites were mainly organic oxygen compounds, flavonoids, and isoflavones. Among the 105 differential metabolites, 26 metabolites were significantly higher in relative content in sapwood than in heartwood, while the other 79 metabolites were significantly higher in relative content in heartwood than in sapwood. KEGG metabolic pathway enrichment analysis showed that these differential metabolites were mainly enriched in three metabolic pathways: Flavonoid biosynthesis, isoflavonoid biosynthesis, and flavonoid and flavonol biosynthesis. This study provides a reference for metabolomics studies in Dalbergia and other woody plants.

Integrating multi-omics data for crop improvement

Our agricultural systems are now in urgent need to secure food for a growing world population. To meet this challenge, we need a better characterization of plant genetic and phenotypic diversity. The combination of genomics, transcriptomics and metabolomics enables a deeper understanding of the mechanisms underlying the complex architecture of many phenotypic traits of agricultural relevance. We review the recent advances in plant genomics to see how these can be integrated with broad molecular profiling approaches to improve our understanding of plant phenotypic variation and inform crop breeding strategies.

Transcriptomic analysis of tea plant (Camellia sinensis) revealed the co-expression network of 4111 paralogous genes and biosynthesis of quality-related key metabolites under multiple stresses

The tea plant is an essential economic plant in many countries. However, its growing season renders them vulnerable to stresses. To understand the transcriptomic influences of these stresses on tea plants, we sequenced and analyzed the transcriptomes under drought, high-temperature, and pest. Paralogs were identified by comparing 14 evolutionarily close genomes. The differentially expressed paralog (DEPs) genes were analyzed regarding single or multiple stresses, and 1075 of the 4111 DEPs were commonly found in all the stresses. The co-expression network of the DEPs and TFs indicated that genes of catechin biosynthesis were associated with most transcription factors specific to each stress. The genes playing a significant role in the late response to drought and pest stress mainly functioned in the early response to high-temperature. This study revealed the relationship between stress and regulation of QRM synthesis and the role of QRMs in response to these (a)biotic stresses.