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An untargeted metabolomics analysis of the components of heartwood and sapwood in 4 fast-growing Chinese fir (Cunninghamia lanceolata (Lamb.) Hook) clones

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Abstract

Wood color is a crucial factor influencing the overall quality of wood products. In this study, we investigated color differences between sapwood (SW) and heartwood (HW) in 4 Chinese fir clones of the same age, using the CIE L*a*b* system. Our results revealed distinct color variations between SW and HW within the same clone, with notable discrepancies observed among different clones. Interestingly, these variation in wood color correlated with wood density, consistent with previous research. Metabolite analysis using an untargeted metabolomics approach was conducted, employing ultra-performance liquid chromatography in conjunction with a quadrupole time-of-flight tandem mass spectrometer (UPLC/Q-TOF–MS/MS), identifying a total of 938 metabolites spanning 12 superclasses. Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) revealed distinct metabolic differences between SW and HW in various Chinese fir clones, with significant variations in abundance patterns and species-specific differences observed in the HW group. Further analysis, through Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA), pinpointed specific metabolites responsible for these distinctions. Among these metabolites, flavonoids, recognized for their role in color formation, stood out prominently. Metabolomic pathway enrichment analysis (MPEA) indicated the involvement of these differential metabolites in various pathways, including flavonoid biosynthesis. The study underscores the intricate relationship between metabolites and wood color variation in Chinese fir clones, accentuating potential applications in enhancing wood quality and decay to resistance.

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Data availability

The data are available from the corresponding author on reasonable request.

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Acknowledgements

The authors acknowledge the National Key Research & Development Program of China (No. 2017YFD0600205), Young and Middle-aged Academic and Technological Leaders of Yunnan Province (No. 202205AC160049), Scientific Research Fund Project of Yunnan Education Department (No. 2019J0193), and Xingdian talent support program of Yunnan Province (Junming Xu) for financial support.

Funding

National Key Research & Development Program of China, 2017YFD0600205, Ping Zhao; Young and Middle-aged Academic and Technological Leaders of Yunnan Province, 202205AC160049, Xiao-Qin Yang; Postdoctoral Research Station in Forestry of Southwest Forestry University, ynbh2021058, Xiao-Qin Yang; Scientific Research Fund Project of Yunnan Education Department, 2019J0193, Ping Zhao; Xingdian Talent Support Program of Yunnan Province.

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Author notes

  1. Xiaoqin Yang and Liping Li have contributed equally to this work and should be considered co-first authors.

Authors and Affiliations

  1. Key Laboratory of National Forestry and Grassland Administration on Highly-Efficient Utilization of Forestry Biomass Resources in Southwest China, Southwest Forestry University, Kunming, 650224, Yunnan, China

    Xiaoqin Yang, Liping Li, Sida Xie, Guolei Zhu & Ping Zhao

  2. Key Laboratory of Ministry of Education for Forest Resources Conservation and Utilization in the Southwest Mountains of China, Southwest Forestry University, Kunming, 650224, Yunnan, China

    Xiaoqin Yang, Xiaorui Yu, Yun Liu & Ping Zhao

  3. Institute of Chemical Industry of Forest Products, Chinese Academy of Forestry, Nanjing, 210042, Jiangsu, China

    Junming Xu

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  1. Xiaoqin Yang
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The manuscript was written with the contributions of all authors. All authors have given approval for the final version of the manuscript.

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Correspondence to Xiaoqin Yang or Ping Zhao.

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We declare that we have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper, there is no part of this paper has published or submitted elsewhere, and no conflict of interest exits in the submission of this manuscript.

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Associated content

Associated content

A list of the total 827 identified metabolites with the untargeted metabolomics approach (Table S4) (XLS).

A list of candidate differential metabolites obtained from the comparison groups of SW (Table S5), include Candidate differential metabolites obtained from the comparison groups of CF-3-SW and CF-8-SW (Table S5A), CF-3-SW and CF-13-SW (Table S5B), CF-3-SW and CF-24-SW (Table S5C) (XLS).

A list of candidate differential metabolites obtained from the comparison groups of HW (Table S6), includes Candidate differential metabolites obtained from the comparison group of CF-3-HW and CF-8-HW (Table S6A), CF-3-HW and CF-13-HW (Table S6B), CF-3-HW and CF-24-HW (Table S6C) (XLS).

Sample preparation, UPLC/Q-TOF–MS/MS analysis, detailed information for 4 Chinese fir clones (Table S1), classification of 4 Chinese fir clones wood samples (Table S2), statistics of identified metabolites (Table S3), differential metabolite analysis between the comparison groups of CF-3-SW and CF-3-HW using OPLS-DA (Figure S1), differential metabolite analysis between the comparison groups of CF-8-SW and CF-8-HW using OPLS-DA (Figure S2), differential metabolite analysis between the comparison groups of CF-13-SW and CF-13-HW using OPLS-DA (Figure S3), differential metabolite analysis between the comparison groups of CF-24-SW and CF-24-HW using OPLS-DA (Figure S4), differential metabolite analysis among the comparison group of CF-3-SW, CF-8-SW, CF-13-SW, and CF-24-SW using OPLS-DA (Figure S5), differential metabolite analysis among the comparison group of CF-3-HW, CF-8-HW, CF-13-HW, and CF-24-HW using OPLS-DA (Figure S6) (PDF).

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Yang, X., Li, L., Yu, X. et al. An untargeted metabolomics analysis of the components of heartwood and sapwood in 4 fast-growing Chinese fir (Cunninghamia lanceolata (Lamb.) Hook) clones. Trees 38, 339–356 (2024). https://doi.org/10.1007/s00468-023-02486-2

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