{"title":"Integration of transcriptome and metabolome analysis reveals the genes and pathways regulating flavonoids biosynthesis in Cinnamomum camphora.","authors":"Huiping Huang, Xinnan Yang, Zerui Yang","doi":"10.1186/s12863-025-01364-9","DOIUrl":null,"url":null,"abstract":"<p><strong>Backgroud: </strong>Although Cinnamomum camphora's metabolic composition has been well studied, flavonoid distribution across its tissues remains poorly understood. This study combined transcriptome and metabolomic analyses on leaf, stem, and root tissues to uncover the synthesis pathway of flavonoids and to identify key regulatory genes.</p><p><strong>Results: </strong>Metabolomic analysis revealed 2,893 metabolites, which can be divided into secondary metabolite 1,213(41.93%), primary metabolite: 622 (21.50%) and others: 1,058 (36.57%). As for the secondary metabolite, flavonoids were the most abundant (28%), followed by terpenoids (27%) and phenolic acids (12%). Differential metabolites were identified using VIP > 1, |log2 fold change|≥ 1, and p < 0.05 criteria, showing tissue-specific flavonoids distribution. For example, rutin, quercetin 3-o-alpha-l-rhamnoside, and quercetin were abundant in leaves and stems, while 2-hydroxyisoflavanone naringenin, fustin, and catechin were predominant in roots. Transcriptome analysis indicated that a total of 2,043 differentially expressed genes (DEGs) were identified, with the most considerable number found in the leaf-to-root comparison. The KEGG enrichment analysis of DEGs showed significant changes in pathways related to flavonoid and phenylpropanoid biosynthesis. Correlation analysis indicated that key enzyme genes including CcPAL_1, CcF3H_1, CcF3_H, CcCHS_1, CcC4H_2, CcANR_1, Cc4CL_9, Cc4CL_7 and Cc4CL_1 play positive regulatory roles in the accumulation of downstream metabolites, whereas CcPAL_4, CcPAL_2 and CcC4H_1 exert negative regulation on downstream metabolites. In addition, we have identified several bHLH and MYB transcription factors that may regulate flavonoid biosynthesis. Finally, qRT-PCR validation confirmed the RNA sequencing results.</p><p><strong>Conclusions: </strong>This research elucidates the spatial variations in the accumulation profiles of flavonoid metabolites across different tissues and offers crucial insights into the regulatory mechanisms of flavonoid metabolism in C. camphora. Consequently, it laid a foundation for further research on the flavonoid biosynthetic pathway of C. camphora.</p>","PeriodicalId":72427,"journal":{"name":"BMC genomic data","volume":"26 1","pages":"71"},"PeriodicalIF":2.5000,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12482126/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC genomic data","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/s12863-025-01364-9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 0
Abstract
Backgroud: Although Cinnamomum camphora's metabolic composition has been well studied, flavonoid distribution across its tissues remains poorly understood. This study combined transcriptome and metabolomic analyses on leaf, stem, and root tissues to uncover the synthesis pathway of flavonoids and to identify key regulatory genes.
Results: Metabolomic analysis revealed 2,893 metabolites, which can be divided into secondary metabolite 1,213(41.93%), primary metabolite: 622 (21.50%) and others: 1,058 (36.57%). As for the secondary metabolite, flavonoids were the most abundant (28%), followed by terpenoids (27%) and phenolic acids (12%). Differential metabolites were identified using VIP > 1, |log2 fold change|≥ 1, and p < 0.05 criteria, showing tissue-specific flavonoids distribution. For example, rutin, quercetin 3-o-alpha-l-rhamnoside, and quercetin were abundant in leaves and stems, while 2-hydroxyisoflavanone naringenin, fustin, and catechin were predominant in roots. Transcriptome analysis indicated that a total of 2,043 differentially expressed genes (DEGs) were identified, with the most considerable number found in the leaf-to-root comparison. The KEGG enrichment analysis of DEGs showed significant changes in pathways related to flavonoid and phenylpropanoid biosynthesis. Correlation analysis indicated that key enzyme genes including CcPAL_1, CcF3H_1, CcF3_H, CcCHS_1, CcC4H_2, CcANR_1, Cc4CL_9, Cc4CL_7 and Cc4CL_1 play positive regulatory roles in the accumulation of downstream metabolites, whereas CcPAL_4, CcPAL_2 and CcC4H_1 exert negative regulation on downstream metabolites. In addition, we have identified several bHLH and MYB transcription factors that may regulate flavonoid biosynthesis. Finally, qRT-PCR validation confirmed the RNA sequencing results.
Conclusions: This research elucidates the spatial variations in the accumulation profiles of flavonoid metabolites across different tissues and offers crucial insights into the regulatory mechanisms of flavonoid metabolism in C. camphora. Consequently, it laid a foundation for further research on the flavonoid biosynthetic pathway of C. camphora.