ORIGINAL RESEARCH article
Front. Plant Sci.
Sec. Plant Metabolism and Chemodiversity
Machine Learning Integrates Metabolomics and Proteomics to Identify Key Regulators of Anthocyanin Biosynthesis in Edible Rose Petals
Dannuo Fu 1
Shuang Liang 2
Hongwei Fu 1
1. Zhejiang Sci-Tech University, Hangzhou, China
2. Beijing University of Chinese Medicine, Beijing, China
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Abstract
Edible rose petals represent a promising source of anthocyanins, natural pigments with health-promoting properties suitable for functional food applications. However, the molecular mechanisms regulating anthocyanin biosynthesis in roses remain incompletely understood. Here, we employed an integrated metabolomic and proteomic approach to investigate anthocyanin profiles and their regulatory networks in three edible rose varieties: Rosa alba (RA), Rosa damascena (RD), and Rosa centifolia (RC). We identified a total of 13 anthocyanins, with RC exhibiting the highest total anthocyanin content—6.9% higher than RD and fivefold greater than RA. Compositional analysis revealed variety-specific accumulation patterns: RD was rich in delphinidin and peonidin derivatives, while RA predominantly accumulated pelargonidin-3-O-rutinoside. Proteomic analysis identified 9,924 proteins, and weighted gene co-expression network analysis (WGCNA) highlighted the MEblue module as strongly correlated with anthocyanin accumulation. By integrating a KNN-based machine learning model, we identified ten key structural proteins (e.g., RhUFGT, F3H, DFR) and several transcription factors (e.g., NAC, bZIP_2, C3H) as central regulators. Our findings elucidate the molecular basis of anthocyanin biosynthesis in edible roses and provide potential targets for breeding strategies aimed at enhancing their value as functional food ingredients.
Summary
Keywords
Anthocyanin, edible roses, Functional Food, Metabolomics, Proteomics, Transcriptionfactor
Received
22 November 2025
Accepted
17 February 2026
Copyright
© 2026 Fu, Liang and Fu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Hongwei Fu
Disclaimer
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