Metabolomic and genome-wide association studies drive genetic dissection and gene mining in tea plant

Abstract

Abstract As a vital reproductive organ, flowers significantly influence the yield, sensory quality, and breeding efficacy of Camellia sinensis. Many biological characteristics of tea plants are influenced by metabolites; however, our knowledge of metabolites in tea flowers is limited. To investigate the physiological basis and molecular mechanisms underlying tea flower metabolism, we integrated metabolomics and genome-wide association studies (GWAS) to analyze the metabolites present in the flowers of 171 tea genotypes. Untargeted metabolomic analysis detected 581 and 295 metabolites in positive and negative ionization modes, respectively. Twenty-seven distinct metabolites were observed between C. sinensis var. assamica (CSA) and C. sinensis var. sinensis (CSS). GWAS identified 1238 quantitative trait loci (QTL) associated with 505 metabolites. Some structurally related metabolites tended to share common QTL. Integrating GWAS findings with secondary mass spectrometry (MS/MS) fragmentation and haplotype analysis for metabolites (-)-epigallocatechin-3-(3"-O-methyl) gallate (EGCG-3''-O-ME), (-)-Epicatechin-3-(3''-O-methyl) gallate (ECG-3''-O-ME), Pos_1118, and Neg_365 (p-coumaroylquinic acid) resulted in the identification of three candidate genes (W07g015551, W08g018636, and W01g002625). Taken together, our findings provide a foundation for exploring comprehensive metabolic pathways in various tissues of C. sinensis.

Keywords

• Camellia sinensis
• Flower
• Metabolite
• Genome-wide association study
• Candidate genes