Potential Regulatory Networks and Heterosis for Flavonoid and Terpenoid Contents in Pak Choi: Metabolomic and Transcriptome Analyses

小白菜中黄酮类和萜类化合物含量的潜在调控网络和杂种优势:代谢组学和转录组学分析

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Abstract

Pak choi exhibits a diverse color range and serves as a rich source of flavonoids and terpenoids. However, the mechanisms underlying the heterosis and coordinated regulation of these compounds-particularly isorhamnetin-remain unclear. This study involved three hybrid combinations and the detection of 528 metabolites from all combinations, including 26 flavonoids and 88 terpenoids, through untargeted metabolomics. Analysis of differential metabolites indicated that the heterosis for the flavonoid and terpenoid contents was parent-dependent, and positive heterosis was observed for isorhamnetin in the two hybrid combinations (SZQ, 002 and HMG, ZMG). Moreover, there was a high transcription level of flavone 3'-O-methyltransferase, which is involved in isorhamnetin biosynthesis. The third group was considered the ideal hybrid combination for investigating the heterosis of flavonoid and terpenoid contents. Transcriptome analysis identified a total of 12,652 DEGs (TPM > 1) in various groups that were used for comparison, and DEGs encoding enzymes involved in various categories, including "carotenoid bio-synthesis" and "anthocyanin biosynthesis", were enriched in the hybrid combination (SZQ, 002). Moreover, the category of anthocyanin biosynthesis also was enriched in the hybrid combination (HMG, ZMG). The flavonoid pathway demonstrated more differential metabolites than the terpenoid pathway did. The WGCNA demonstrated notable positive correlations between the dark-green modules and many flavonoids and terpenoids. Moreover, there were 23 ERF genes in the co-expression network (r ≥ 0.90 and p < 0.05). Thus, ERF genes may play a significant role in regulating flavonoid and terpenoid biosynthesis. These findings enhance our understanding of the heterosis and coordinated regulation of flavonoid and terpenoid biosynthesis in pak choi, offering insights for genomics-based breeding improvements.

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