Exploring metabolic responses upon harvesting via untargeted metabolomics coupled with machine learning algorithm in rubber tree

Rubber tree ( Hevea brasiliensis ) is important for modern life due to its commercial product, natural rubber, which is indispensable for many important sectors. Unlike cereal crops, rubber trees can be harvested by tapping every several days for up to 40 years. In unharvested virgin trees, tapping stimulates rubber production. However, the underlying molecular basis of tapping-induced rubber production still remains elusive. To identify core tapping-responsive metabolic pathways and key marker metabolites for optimal rubber yield, we used three field-grown elite rubber tree cultivars with contrasting yields, and investigated their latex chemistry among 15 successive tappings by untargeted metabolomics coupled with random forest machine learning algorithm. A total of 367 metabolites were annotated. The metabolite profiles clearly mirrored the yielding traits of the three cultivars prior to and post the tapping treatment. Exploration of tapping-responsive differentially accumulated metabolites (DAMs) underlined the roles of sugar metabolism, amino acid and nucleotide metabolism and stress responses in tapping-induced rubber production in a cultivar-independent manner. Further analysis revealed the significance of energy production primed by sugar metabolism, stress-associated amino acid synthesis, and oxidative homeostasis in cultivar-dependent rubber production. Finally, 19 potential marker compounds were screened using the random forest regression model, in which 6 metabolites including fructose-6-phosphate and raffinose were identified as positive markers, whilst 13 metabolites including citric acid and fumaric acid were revealed as negative markers to predict high-yield cultivars. The specialized metabolites and pathways identified in this work will aid targeted rubber tree breeding in the future. • Metabolic analysis was performed in latex from three rubber tree cultivars. • 27 cultivar-dependent and 18 cultivar-independent metabolites were identified. • 19 marker compounds for predicting rubber yield were revealed via modeling. • Sugar metabolism-primed energy production is essential to optimum rubber yield.

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Publication Details

Journal
Industrial Crops and Products
Published
2025-11-20
DOI
https://doi.org/10.1016/j.indcrop.2025.122300
Primary Topic
Plant biochemistry and biosynthesis
Type
article
Field-Weighted Citation Impact
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article

Exploring metabolic responses upon harvesting via untargeted metabolomics coupled with machine learning algorithm in rubber tree

Yun Xiong, Yunxia Qin, Jiang Wang, Xiaohu Xiao et al.
Industrial Crops and Products
Plant biochemistry and biosynthesis
article

Exploring metabolic responses upon harvesting via untargeted metabolomics coupled with machine learning algorithm in rubber tree

Yun Xiong, Yunxia Qin, Jiang Wang, Xiaohu Xiao, Binhui Zhou, Yacheng Huang, Chuang Wang, Yongjun Fang, Jinheng Zhu
article en

Abstract

Rubber tree ( Hevea brasiliensis ) is important for modern life due to its commercial product, natural rubber, which is indispensable for many important sectors. Unlike cereal crops, rubber trees can be harvested by tapping every several days for up to 40 years. In unharvested virgin trees, tapping stimulates rubber production. However, the underlying molecular basis of tapping-induced rubber production still remains elusive. To identify core tapping-responsive metabolic pathways and key marker metabolites for optimal rubber yield, we used three field-grown elite rubber tree cultivars with contrasting yields, and investigated their latex chemistry among 15 successive tappings by untargeted metabolomics coupled with random forest machine learning algorithm. A total of 367 metabolites were annotated. The metabolite profiles clearly mirrored the yielding traits of the three cultivars prior to and post the tapping treatment. Exploration of tapping-responsive differentially accumulated metabolites (DAMs) underlined the roles of sugar metabolism, amino acid and nucleotide metabolism and stress responses in tapping-induced rubber production in a cultivar-independent manner. Further analysis revealed the significance of energy production primed by sugar metabolism, stress-associated amino acid synthesis, and oxidative homeostasis in cultivar-dependent rubber production. Finally, 19 potential marker compounds were screened using the random forest regression model, in which 6 metabolites including fructose-6-phosphate and raffinose were identified as positive markers, whilst 13 metabolites including citric acid and fumaric acid were revealed as negative markers to predict high-yield cultivars. The specialized metabolites and pathways identified in this work will aid targeted rubber tree breeding in the future. • Metabolic analysis was performed in latex from three rubber tree cultivars. • 27 cultivar-dependent and 18 cultivar-independent metabolites were identified. • 19 marker compounds for predicting rubber yield were revealed via modeling. • Sugar metabolism-primed energy production is essential to optimum rubber yield.

Industrial Crops and ProductsVol. 237
Chinese Academy of Tropical Agricultural Sciences (CN), Hainan University (CN), Tropical Crops Genetic Resources Institute (CN), Rubber Research Institute (CN), Hainan Tropical Ocean University (CN)
Openalex Percentile: Top 68%
Plant biochemistry and biosynthesis
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