Metabolomic Profiling in Combination with Data Association Analysis Provide Insights about Potential Metabolic Regulation Networks among Non-Volatile and Volatile Metabolites in Camellia sinensis cv Baijiguan
Abstract
:1. Introduction
2. Results
2.1. Non-Volatile Contents of the Albino Half-Sibs and the Green Half-Sibs of Baijiguan
2.2. Volatile Contents of the Albino Half-Sibs and the Green Half-Sibs of Baijiguan
2.3. Correlations among Non-Volatile Metabolites of Baijiguan Half-Sibs
2.4. Correlations among the Four Volatile Synthesis Pathways in Baijiguan Half-Sibs
2.5. Correlations between Volatile Synthesis Pathways and Non-Volatile Metabolites in Baijiguan Half-Sibs
2.6. Correlations among the Volatiles Derived from MVA Pathway in Baijiguan Half-Sibs
2.7. Correlations among the Volatiles Derived from MEP Pathway in Baijiguan Half-Sibs
2.8. Correlations among the Volatiles Derived from the Shikimate–Phenylpropanoid Pathway and Fatty Acid-Derivative Pathway
3. Discussion
3.1. The Synthesis of Total Amino Acids, Caffeine, and Catechins Likely Is Independently Regulated in Tender Tea Leaves
3.2. Volatile Synthesis Pathways Were Metabolically Connected with Catechins or Amino Acid Metabolism
3.3. Potential Opportunities to Alter Volatile Contents and Compositions in Tender Tea Leaves
4. Materials and Methods
4.1. Plant Material
4.2. Tea Sample Preparation
4.3. Free Amino Acid Measurement
4.4. Caffeine Quantification
4.5. Catechin Measurement
4.6. Tea Volatile Isolation and Quantification
4.7. Correlation Analysis
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Leaf Type | Germplasm Name | Phenylpropanoids | Monoterpenes/ Diterpenes | Sesquiterpenes | Fatty Acid Derivatives |
---|---|---|---|---|---|
Albino half-sibs | 0306C | 19.56 ± 1.54 | 12.18 ± 0.43 | 0.91 ± 0.12 | 0.19 ± 0.01 |
0306D | 21.18 ± 1.55 | 9.02 ± 0.38 | 1.27 ± 0.17 | 0.36 ± 0.02 | |
0306F | 9.53 ± 0.88 | 13.21 ± 1.73 | 1.57 ± 0.70 | 0.40 ± 0.05 | |
0306I | 14.53 ± 0.76 | 14.01 ± 0.45 | 1.26 ± 0.12 | 0.36 ± 0.04 | |
0317L | 23.72 ± 1.41 | 11.24 ± 0.52 | 1.28 ± 0.09 | 0.23 ± 0.01 | |
0317N | 4.35 ± 0.11 | 3.06 ± 0.12 | 0.75 ± 0.03 | 0.15 ± 0.01 | |
Green half-sibs | 0306A | 11.48 ± 0.61 | 10.24 ± 0.57 | 1.14 ± 0.06 | 0.26 ± 0.01 |
0306B | 17.58 ± 0.58 | 8.79 ± 0.78 | 3.19 ± 0.32 | 0.72 ± 0.05 | |
0306H | 23.06 ± 0.59 | 18.53 ± 0.67 | 1.11 ± 0.09 | 0.39 ± 0.02 | |
0306L | 22.72 ± 1.61 | 7.24 ± 0.60 | 0.89 ± 0.04 | 0.15 ± 0.00 | |
0309A | 37.24 ± 0.56 | 14.57 ± 0.39 | 1.71 ± 0.15 | 0.27 ± 0.02 | |
0317D | 28.26 ± 1.35 | 31.00 ± 1.82 | 1.33 ± 0.33 | 0.06 ± 0.00 |
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Chen, M.; Kong, X.; Zhang, Y.; Wang, S.; Zhou, H.; Fang, D.; Yue, W.; Chen, C. Metabolomic Profiling in Combination with Data Association Analysis Provide Insights about Potential Metabolic Regulation Networks among Non-Volatile and Volatile Metabolites in Camellia sinensis cv Baijiguan. Plants 2022, 11, 2557. https://doi.org/10.3390/plants11192557
Chen M, Kong X, Zhang Y, Wang S, Zhou H, Fang D, Yue W, Chen C. Metabolomic Profiling in Combination with Data Association Analysis Provide Insights about Potential Metabolic Regulation Networks among Non-Volatile and Volatile Metabolites in Camellia sinensis cv Baijiguan. Plants. 2022; 11(19):2557. https://doi.org/10.3390/plants11192557
Chicago/Turabian StyleChen, Mingjie, Xiangrui Kong, Yi Zhang, Shiya Wang, Huiwen Zhou, Dongsheng Fang, Wenjie Yue, and Changsong Chen. 2022. "Metabolomic Profiling in Combination with Data Association Analysis Provide Insights about Potential Metabolic Regulation Networks among Non-Volatile and Volatile Metabolites in Camellia sinensis cv Baijiguan" Plants 11, no. 19: 2557. https://doi.org/10.3390/plants11192557