METABOLIC AND TRANSCRIPTOME ANALYSIS REVEALS METABOLITE VARIATION AND FLAVONOID REGULATORY NETWORKS IN FRESH SHOOTS OF TEA (<i>CAMELLIA SINENSIS</i>) OVER THREE SEASONS

doi:10.15302/J-FASE-2021382

Front. Agr. Sci. Eng.

2021, Vol. 8

Issue (2) : 215-230 https://doi.org/10.15302/J-FASE-2021382

RESEARCH ARTICLE

METABOLIC AND TRANSCRIPTOME ANALYSIS REVEALS METABOLITE VARIATION AND FLAVONOID REGULATORY NETWORKS IN FRESH SHOOTS OF TEA (CAMELLIA SINENSIS) OVER THREE SEASONS

Chen-Kai JIANG^1,², De-Jiang NI³, Ming-Zhe YAO¹, Jian-Qiang MA¹(

), Liang CHEN¹(

)

¹. Key Laboratory of Tea Biology and Resources Utilization, Ministry of Agriculture and Rural Affairs, Tea Research Institute of the Chinese Academy of Agricultural Sciences, Hangzhou 310008, China.
². State Key Laboratory for Quality and Safety of Agro-products, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China.
³. College of Horticulture and Forestry Science, Huazhong Agricultural University, Wuhan 430070, China.

Download: PDF(2171 KB) HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

Abstract

• Metabolites of fresh tea shoots at harvest were profiled.

• Season-dependent metabolites were identified.

• Key genes responsible for flavonoid metabolism are proposed.

• Regulated relationships among the main compounds were investigated.

Metabolites, especially secondary metabolites, are very important in the adaption of tea plants and the quality of tea products. Here, we focus on the seasonal variation in metabolites of fresh tea shoots and their regulatory mechanism at the transcriptional level. The metabolic profiles of fresh tea shoots of 10 tea accessions collected in spring, summer, and autumn were analyzed using ultra-performance liquid chromatography coupled with quadrupole-obitrap mass spectrometry. We focused on the metabolites and key genes in the phenylpropanoid/flavonoid pathway integrated with transcriptome analysis. Multivariate statistical analysis indicates that metabolites were distinctly different with seasonal alternation. Flavonoids, amino acids, organic acids and alkaloids were the predominant metabolites. Levels of most key genes and downstream compounds in the flavonoid pathway were lowest in spring but the catechin quality index was highest in spring. The regulatory pathway was explored by constructing a metabolite correlation network and a weighted gene co-expression network.

Keywords harvest season metabolites tea shoots transcriptomics untargeted metabolomics

Corresponding Author(s): Jian-Qiang MA,Liang CHEN

Just Accepted Date: 20 January 2021 Online First Date: 02 March 2021 Issue Date: 13 July 2021

Cite this article:

Chen-Kai JIANG,De-Jiang NI,Ming-Zhe YAO, et al. METABOLIC AND TRANSCRIPTOME ANALYSIS REVEALS METABOLITE VARIATION AND FLAVONOID REGULATORY NETWORKS IN FRESH SHOOTS OF TEA (CAMELLIA SINENSIS) OVER THREE SEASONS[J]. Front. Agr. Sci. Eng. , 2021, 8(2): 215-230.

URL:

https://academic.hep.com.cn/fase/EN/10.15302/J-FASE-2021382
https://academic.hep.com.cn/fase/EN/Y2021/V8/I2/215

No.	Name	Formula	Accurate mass	RT	MS² fragments
Alcohols and polyols
1	Xylitol*	C₅H₁₂O₅	152.06841	0.88	69, 57, 99, 73, 73
Alkaloids
2	Betaine*	C₅H₁₁NO₂	117.07897	0.92	118, 59, 58, 119, 60
3	Caffeine*	C₈H₁₀N₄O₂	194.08034	6.28	195, 138, 196, 110, 83
4	Theophylline*	C₇H₈N₄O₂	180.06476	4.84	179, 164, 122, 94, 180
5	Theobromine	C₇H₈N₄O₂	180.06462	4.17	114, 181, 57, 57, 132
Amino acids and their derivatives
6	Glutathione*	C₁₀H₁₇N₃O₆S	307.08375	0.98	76, 179, 84, 162, 308
7	4-Oxoproline	C₅H₇NO₃	129.04261	1.25	128, 88, 85, 129, 129
8	DL-Lysine*	C₆H₁₄N₂O₂	146.10559	0.75	84, 130, 85, 56, 147
9	DL-tyrosine*	C₉H₁₁NO₃	181.07391	0.98	136, 123, 165, 91, 119
10	L-(-)-Serine*	C₃H₇NO₃	105.04257	0.86	74, 72, 104, 105, 75
11	L-Arginine*	C₆H₁₄N₄O₂	174.11166	0.84	70, 175, 60, 116, 130
12	L-Aspartic acid*	C₄H₇NO₄	133.03747	0.86	74, 88, 116, 70, 134
13	L-Glutamic acid*	C₅H₉NO₄	147.05312	0.87	84, 102, 130, 85
14	L-Homoserine*	C₄H₉NO₃	119.05827	0.87	74, 56, 120, 102, 75
15	L-Isoleucine*	C₆H₁₃NO₂	131.09465	1.21	86, 69, 87, 132
16	L-Proline*	C₅H₉NO₂	115.06334	0.91	70, 116, 71, 117
17	L-Theanine*	C₇H₁₄N₂O₃	174.10039	0.97	84, 158, 129, 130, 175
18	β-Alanine*	C₃H₇NO₂	89.04773	0.85	90, 57, 50, 54, 55
19	D-Glutamine	C₅H₁₀N₂O₃	146.06916	0.87	89, 191, 431, 195, 165
20	Glycyl-L-leucine	C₈H₁₆N₂O₃	188.11608	1.24	86, 84, 172, 60, 142
21	L-Glutathione oxidized	C₂₀H₃₂N₆O₁₂S₂	612.15178	1.23	231, 613, 355, 484, 177
22	L-Histidine	C₆H₉N₃O₂	155.06954	0.80	92, 108, 65, 110, 68
23	Dihomomethionine	C₇H₁₅NO₂S	177.08229	1.26	133, 178, 57, 84, 132
24	S-Adenosyl-L-homocysteine (SAH)	C₁₄H₂₀N₆O₅S	384.12194	1.44	167, 85, 219, 69, 115
25	2-Aminoadipic acid	C₆H₁₁NO₄	161.06878	1.24	58, 88, 160, 73, 59
26	L-Phenylalanine*	C₉H₁₁NO₂	165.07901	1.55	120, 103, 121, 131
27	L-Tryptophan*	C₁₁H₁₂N₂O₂	204.08976	2.47	116, 203, 74, 142, 72
Benzoic acid derivatives
28	Theogallin*	C₁₄H₁₆O₁₀	344.07434	2.26	191, 85, 93, 192, 127
29	2,4-Dihydroxybenzoic acid	C₇H₆O₄	154.02658	4.74	109, 153, 135, 65, 111
30	3-Hydroxybenzoic acid	C₇H₆O₃	138.03166	6.56	93, 137
31	4-Hydroxybenzaldehyde	C₇H₆O₂	122.03663	8.22	123, 68, 79, 57, 59
32	4-Hydroxybenzoic acid	C₇H₆O₃	138.0316	6.85	93, 137
Carbohydrates
33	D( + )-Glucuronic Acid*	C₆H₁₀O₇	194.04254	0.90	59, 73, 71, 85, 113
34	D-Fructose*	C₆H₁₂O₆	180.02972	0.87	59, 71, 89, 85, 113
35	D-Gluconic Acid*	C₆H₁₂O₇	196.05823	0.87	75, 195, 59, 129, 99
36	D-Trehalose*	C₁₂H₂₂O₁₁	342.11651	0.89	59, 71, 89, 341, 101
Coumarins
37	Esculin*	C₁₅H₁₆O₉	340.07951	4.73	177, 133, 178, 105, 339
38	7-Hydroxycoumarine	C₉H₆O₃	162.03157	5.36	163, 147, 135
39	Coumarin	C₉H₆O₂	146.03676	4.61	119, 147, 91, 124, 122
Flavonoids and their derivatives
40	(–)-Epigallocatechin gallate (EGCG)*	C₂₂H₁₈O₁₁	458.08507	6.75	125, 169
41	( + )Catechin (C)*	C₁₅H₁₄O₆	290.07914	4.96	109, 123, 289, 125, 97
42	( + )Epicatechin (EC)*	C₁₅H₁₄O₆	290.07912	5.85	123, 109, 289, 125, 97
43	( + )-Gallocatechin(GC)*	C₁₅H₁₄O₇	306.07401	3.24	125, 137, 139, 109, 305
44	Epicatechin gallate (ECG)*	C₂₂H_{18 O10}	442.09018	8.22	125, 169, 289, 109, 123
45	Epigallocatechin (EGC)*	C₁₅H₁₄O₇	306.07397	4.42	125, 137, 139, 109, 305
46	Epigallocatechin 3-O-(3-O-methyl) gallate	C₂₃H₂₀O₁₁	472.10075	8.56	125, 124, 168, 161, 57
47	Epigallocatechin-(4β→8)-epicatechin-3-O-gallate ester	C₃₇H₃₀O₁₇	746.14908	8.35	127, 123, 139, 287, 179
48	Epigallocatechin-3′-glucuronide	C₂₁H₂₂O₁₃	482.10644	3.29	151, 125, 153, 193, 175
49	Gallocatechin-(4α→8)-epigallocatechin	C₃₀H₂₆O₁₄	610.13233	7.99	127, 139, 287, 305, 179
50	Ideain	C₂₁H₂₀O₁₁	448.10053	8.40	287, 288, 449, 450, 137
51	Phloretin*	C₁₅H₁₄O₅	274.08428	9.50	81, 123, 167, 119, 273
52	Prunin*	C₂₁H₂₂O₁₀	434.12156	8.67	119, 271, 151, 107, 65
53	Cynaroside*	C₂₁H₂₀O₁₁	448.10069	8.67	284, 285, 447, 151, 286
54	Tricetin*	C₁₅H₁₀O₇	302.04269	9.04	149, 301, 151, 107, 302
55	Theasinensin B	C₃₇H₃₀O₁₈	762.14357	5.58	125, 177, 423, 137, 255
56	Kaempferin*	C₂₁H₂₀O₁₀	432.10577	8.99	255, 227, 285, 284, 431
57	Kaempferol*	C₁₅H₁₀O₆	286.04777	9.35	133, 285, 151, 107, 286
58	(–)-Fustin	C₁₅H₁₂O₆	288.06312	5.70	125, 177, 423, 137, 255
59	Avicularin*	C₂₀H₁₈O₁₁	434.08505	8.63	271, 300, 255, 301, 243
60	Baimaside*	C₂₇H₃₀O₁₇	626.14876	7.27	271, 300, 255, 625, 243
61	Isovitexin*	C₂₁H₂₀O₁₀	432.10564	8.37	283, 311, 431, 117, 341
62	Naringenin*	C₁₅H₁₂O₅	272.06862	9.54	119, 151, 271, 107, 65
63	Delphinidin-3-O-rutinoside	C₂₇H₃₀O₁₆	610.15362	8.15	125, 169
64	Eriodictyol*	C₁₅H₁₂O₆	288.06353	9.23	135, 151, 65, 107, 136
65	Myricetin	C₁₅H₁₀O₈	318.03707	7.49	151, 137, 317, 109, 107
66	Naringenin chalcone	C₁₅H₁₂O₅	272.06822	8.22	119, 151, 271, 65, 107
67	Quercetin	C₁₅H₁₀O₇	302.04241	7.78	203, 285, 303, 241, 229
68	Quercetin-3β-D-glucoside	C₂₁H₂₀O₁₂	464.0957	8.37	271, 300, 255, 301, 463
69	Schaftoside	C₂₆H₂₈O₁₄	564.14784	5.67	547, 379, 565, 295, 325
70	Procyanidin B4*	C₃₀H₂₆O₁₂	578.14269	5.68	125, 109, 407, 123, 289
71	Procyanidin B3*	C₃₀H₂₆O₁₂	578.1426	4.74	125, 407, 123, 109, 289
Nucleotides and their derivates
72	7-Methylxanthine*	C₆H₆N₄O₂	166.04908	2.61	85, 167, 124, 103, 57
73	Adenine*	C₅H₅N₅	135.05454	1.24	134, 107, 92, 135, 108
74	Guanine*	C₅H₅N₅O	151.04941	1.61	133, 150, 108, 66, 126
75	Thymine*	C₅H₆N₂O₂	126.04298	1.56	125
76	Xanthine*	C₅H₄N₄O₂	152.03343	1.62	73, 114, 153, 91, 132
77	Guanosine monophosphate	C₁₀H₁₄N₅O₈P	363.05817	1.27	79, 73, 117, 97, 133
78	Uridine monophosphate	C₉H₁₃N₂O₉P	324.03592	0.99	79, 97, 115, 133, 71
79	3′-Adenosine monophosphate	C₁₀H₁₄N₅O₇P	347.06296	1.22	79, 97, 134
80	Adenosine diphosphate	C₁₀H₁₅N₅O₁₀P₂	427.02992	0.96	79, 159, 134
Organic acids
81	p-Coumaric acid	C₉H₈O₃	164.04735	5.44	119, 163, 120, 93, 164
82	2-Hydroxy cinnamic acid*	C₉H₈O₃	164.04717	6.25	119, 120, 117, 163, 93
83	Abscisic acid*	C₁₅H₂₀O₄	264.13619	9.25	204, 219, 203, 151, 122
84	Gallic acid*	C₇H₆O₅	170.02144	1.92	125, 169, 69, 97, 126
85	Malic Acid*	C₄H₆O₅	134.02149	0.99	115, 71, 133, 73, 89
86	Citric acid*	C₆H₈O₇	192.02704	1.21	111, 87, 85, 191
87	Succinic acid*	C₄H₆O₄	118.02661	1.31	73, 117, 99, 117, 74
88	α-Ketoglutaric acid	C₅H₆O₅	146.02147	1.07	101, 102, 128, 57, 73
89	Digallic acid	C₁₄H₁₀O₉	322.0327	5.86	289, 91, 335, 113, 175
90	Malonic acid	C₃H₄O₄	104.01093	1.08	59, 103, 74, 60, 72
91	3-Hydroxy-3-methylglutaric acid	C₆H₁₀O₅	162.05282	1.41	101, 99, 57, 58
92	Ellagic acid	C₁₄H₆O₈	302.0063	5.19	303, 304, 257
93	Ethylmalonic acid	C₅H₈O₄	132.04221	1.84	87, 62, 131, 133
94	Fumaric acid	C₄H₄O₄	116.01091	1.44	71, 73, 69, 117, 115
95	Shikimic acid	C₇H₁₀O₅	174.05253	6.26	93, 73, 83, 137, 111
96	L-Pyroglutamic acid	C₅H₇NO₃	129.04261	0.87	84, 130
Quinates and their derivatives
97	Chlorogenic acid*	C₁₆H₁₈O₉	354.0952	5.36	191, 85, 192, 93, 127
98	Neochlorogenic acid*	C₁₆H₁₈O₉	354.09524	3.62	135, 191, 179, 85, 134
99	Quinic acid	C₇H₁₂O₆	192.06338	6.61	103, 191, 59, 88, 85
Pantothenic acid*
100	Pantothenic acid*	C₉H₁₇NO₅	219.11068	2.05	88, 71, 146, 218, 99

Tab.1 Identification of metabolites of fresh tea shoots

Fig.1 Multivariate statistical analysis of metabolites in tea samples from three harvest seasons. (a) PCA score plot; (b) PLS-DA score plot; and (c) 10-fold cross-validation bar of PLS-DA model with 100 permutation tests.

Fig.2 Heat map of the concentrations of the top 25 metabolites over the three seasons.

Fig.3 Metabolic pathway changes in flavonoids over three harvest seasons. Peak areas of metabolites in spring, summer and autumn are shown in green, pink and blue bars, respectively; low, medium and high expression levels of genes are shown in blue, yellow and red blocks, respectively; bars with the same lowercase letters are not significantly different by LSD test; PAL, phenylalanine ammonia-lyase; C4H, cinnamate 4-hydroxylase; 4CL, 4-coumarate–CoA ligase; CHI, chalcone isomerase; CHS, chalcone synthase; F3′5′H, flavonoid 3′,5′-hydroxylase; F3H, flavanone 3-hydroxylase; F3′H, flavonoid 3′-monooxygenase; FLS, flavonol synthase; DFR, dihydroflavonol-4-reductase; ANS, anthocyanidin synthase; ANR, anthocyanidin reductase; and LAR, leucoanthocyanidin reductase.

Fig.4 Comparison of catechin concentrations in three harvest seasons. (a) Catechin quality indices; (b) mean value of catechin quality index. Bars with the same lowercase letters are not significantly different by LSD test.

Fig.5 The metabolic correlated network and weighted gene co-expression network. (a) Metabolic correlated network among metabolites with PCC > 0.6 (Nodes were colored based on term weight value. Positive and negative correlation are indicated with pink and blue connectors, respectively); (b) weighted gene co-expression network in flavonoid metabolism with weighted correlation coefficient > 0.5. (Edge width reflects weighted correlation coefficient. Node size reflects the degree value. Nodes were colored based on the group of hub-gene).

1	N Sanlier, B B Gokcen, M Altuğ. Tea consumption and disease correlations. Trends in Food Science & Technology, 2018, 78: 95–106 https://doi.org/10.1016/j.tifs.2018.05.026
2	H G Ji, Y R Lee, M S Lee, K H Hwang, E H Kim, J S Park, Y S Hong. Metabolic phenotyping of various tea (Camellia sinensis L.) cultivars and understanding of their intrinsic metabolism. Food Chemistry, 2017, 233: 321–330 https://doi.org/10.1016/j.foodchem.2017.04.079 pmid: 28530581
3	R Fang, S P Redfern, D Kirkup, E A Porter, G C Kite, L A Terry, M J Berry, M S J Simmonds. Variation of theanine, phenolic, and methylxanthine compounds in 21 cultivars of Camellia sinensis harvested in different seasons. Food Chemistry, 2017, 220: 517–526 https://doi.org/10.1016/j.foodchem.2016.09.047 pmid: 27855934
4	H Li, Z W Liu, Z J Wu, Y X Wang, R M Teng, J Zhuang. Differentially expressed protein and gene analysis revealed the effects of temperature on changes in ascorbic acid metabolism in harvested tea leaves. Horticulture Research, 2018, 5(1): 65 https://doi.org/10.1038/s41438-018-0070-x pmid: 30302261
5	S Jayasekera, L Kaur, A L Molan, M L Garg, P J Moughan. Effects of season and plantation on phenolic content of unfermented and fermented Sri Lankan tea. Food Chemistry, 2014, 152: 546–551 https://doi.org/10.1016/j.foodchem.2013.12.005 pmid: 24444973
6	W Dai, D Qi, T Yang, H Lv, L Guo, Y Zhang, Y Zhu, Q Peng, D Xie, J Tan, Z Lin. Nontargeted analysis using ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry uncovers the effects of harvest season on the metabolites and taste quality of tea (Camellia sinensis L.). Journal of Agricultural and Food Chemistry, 2015, 63(44): 9869–9878 https://doi.org/10.1021/acs.jafc.5b03967 pmid: 26494158
7	P Zhou, O Hu, H Fu, L Ouyang, X Gong, P Meng, Z Wang, M Dai, X Guo, Y Wang. UPLC-Q-TOF/MS-based untargeted metabolomics coupled with chemometrics approach for Tieguanyin tea with seasonal and year variations. Food Chemistry, 2019, 283: 73–82 https://doi.org/10.1016/j.foodchem.2019.01.050 pmid: 30722928
8	Q Zhang, M Liu, J Ruan. Metabolomics analysis reveals the metabolic and functional roles of flavonoids in light-sensitive tea leaves. BMC Plant Biology, 2017, 17(1): 64 https://doi.org/10.1186/s12870-017-1012-8 pmid: 28320327
9	J Zhu, Q Xu, S Zhao, X Xia, X Yan, Y An, X Mi, L Guo, L Samarina, C Wei. Comprehensive co-expression analysis provides novel insights into temporal variation of flavonoids in fresh leaves of the tea plant (Camellia sinensis). Plant Science, 2020, 290: 110306 pmid: 31779914
10	J Xu, Q F Zhang, J Zheng, B F Yuan, Y Q Feng. Mass spectrometry-based fecal metabolome analysis. Trends in Analytical Chemistry, 2019, 112: 161–174
11	W Xu, Q Song, D Li, X Wan. Discrimination of the production season of Chinese green tea by chemical analysis in combination with supervised pattern recognition. Journal of Agricultural and Food Chemistry, 2012, 60(28): 7064–7070 pmid: 22720840
12	D Qi, J Li, X Qiao, M Lu, W Chen, A Miao, W Guo, C Ma. Non-targeted metabolomic analysis based on ultra-high-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry reveals the effects of grafting on non-volatile metabolites in fresh tea leaves (Camellia sinensis L.). Journal of Agricultural and Food Chemistry, 2019, 67(23): 6672–6682 pmid: 31117493
13	X Guo, C T Ho, W Schwab, C Song, X Wan. Aroma compositions of large-leaf yellow tea and potential effect of theanine on volatile formation in tea. Food Chemistry, 2019, 280: 73–82 https://doi.org/10.1016/j.foodchem.2018.12.066 pmid: 30642509
14	M Kito, H Kokura, J Izaki, K Sasaoka. Theanine, a precursor of the phloroglucinol nucleus of catechins in tea plants. Phytochemistry, 1968, 7(4): 599–603 https://doi.org/10.1016/S0031-9422(00)88234-5
15	D N Barua. Seasonal dormancy in tea (Camellia sinensis L.). Nature, 1969, 224(5218): 514 https://doi.org/10.1038/224514a0
16	C Yue, H Cao, X Hao, J Zeng, W Qian, Y Guo, N Ye, Y Yang, X Wang. Differential expression of gibberellin- and abscisic acid-related genes implies their roles in the bud activity-dormancy transition of tea plants. Plant Cell Reports, 2018, 37(3): 425–441 https://doi.org/10.1007/s00299-017-2238-5 pmid: 29214380
17	T Tohge, L P de Souza, A R Fernie. Current understanding of the pathways of flavonoid biosynthesis in model and crop plants. Journal of Experimental Botany, 2017, 68(15): 4013–4028 https://doi.org/10.1093/jxb/erx177 pmid: 28922752
18	S Kaneko, K Kumazawa, H Masuda, A Henze, T Hofmann. Molecular and sensory studies on the umami taste of Japanese green tea. Journal of Agricultural and Food Chemistry, 2006, 54(7): 2688–2694 https://doi.org/10.1021/jf0525232 pmid: 16569062
19	Q Q Cao, C Zou, Y H Zhang, Q Z Du, J F Yin, J Shi, S Xue, Y Q Xu. Improving the taste of autumn green tea with tannase. Food Chemistry, 2019, 277: 432–437 https://doi.org/10.1016/j.foodchem.2018.10.146 pmid: 30502167
20	Y S Zhen, Z M Chen, S J Cheng, M L Chen. Tea: Bioactivity and Therapeutic Potential. London, UK: CRC Press, 2002
21	S Kallithraka, J Bakker, M N Clifford. Evaluation of bitterness and astringency of (+)-catechin and (–)-epicatechin in red wine and in model solution. Journal of Sensory Studies, 1997, 12(1): 25–37 https://doi.org/10.1111/j.1745-459X.1997.tb00051.x
22	H Peleg, K Gacon, P Schlich, A C Noble. Bitterness and astringency of flavan-3-ol monomers, dimers and trimers. Journal of the Science of Food and Agriculture, 1999, 79(8): 1123–1128 https://doi.org/10.1002/(SICI)1097-0010(199906)79:8<1123::AID-JSFA336>3.0.CO;2-D
23	C Liu, X Wang, V Shulaev, R A Dixon. A role for leucoanthocyanidin reductase in the extension of proanthocyanidins. Nature Plants, 2016, 2(12): 16182 https://doi.org/10.1038/nplants.2016.182 pmid: 27869786
24	R Stracke, H Ishihara, G Huep, A Barsch, F Mehrtens, K Niehaus, B Weisshaar. Differential regulation of closely related R2R3-MYB transcription factors controls flavonol accumulation in different parts of the Arabidopsis thaliana seedling. Plant Journal, 2007, 50(4): 660–677 https://doi.org/10.1111/j.1365-313X.2007.03078.x pmid: 17419845
25	S Chen, F Wu, Y Li, Y Qian, X Pan, F Li, Y Wang, Z Wu, C Fu, H Lin, A Yang. NtMYB4 and NtCHS1 are critical factors in the regulation of flavonoid biosynthesis and are involved in salinity responsiveness. Frontiers in Plant Science, 2019, 10: 178 https://doi.org/10.3389/fpls.2019.00178 pmid: 30846995
26	J I Kim, X Zhang, P E Pascuzzi, C J Liu, C Chapple. Glucosinolate and phenylpropanoid biosynthesis are linked by proteasome-dependent degradation of PAL. New Phytologist, 2020, 225(1): 154–168 https://doi.org/10.1111/nph.16108 pmid: 31408530
27	C Pastore, S Dal Santo, S Zenoni, N Movahed, G Allegro, G Valentini, I Filippetti, G B Tornielli. Whole plant temperature manipulation affects flavonoid metabolism and the transcriptome of grapevine berries. Frontiers in Plant Science, 2017, 8: 929 https://doi.org/10.3389/fpls.2017.00929 pmid: 28634482
28	Y Lu, Y Liu, X Niu, Q Yang, X Hu, H Y Zhang, J Xia. Systems genetic validation of the SNP-metabolite association in rice via metabolite-pathway-based phenome-wide association scans. Frontiers in Plant Science, 2015, 6: 1027 https://doi.org/10.3389/fpls.2015.01027 pmid: 26640468
29	Y C Ruan, Q K Cheng. The relation between the components of tea catechins and the quality of green tea. Acta Horticulturae Sinica, 1964, 3: 287–300 (in Chinese)
30	Y R Liang, J L Lu, L Y Zhang. Comparative study of cream in infusions of black tea and green tea (Camellia sinensis (L.) O. Kuntze). International Journal of Food Science & Technology, 2002, 37(6): 627–634 https://doi.org/10.1046/j.1365-2621.2002.00589.x
31	G A A R Perera, A M T Amarakoon, D C K Illeperuma, P K P Muthukumarana. Effects of raw material on the chemical composition, organoleptic properties, antioxidant activity, physical properties and the yield of instant black tea. Lebensmittel-Wissenschaft+Technologie, 2015, 63(1): 745–750 https://doi.org/10.1016/j.lwt.2015.03.060
32	B S Moore, C Hertweck, J N Hopke, M Izumikawa, J A Kalaitzis, G Nilsen, T O’Hare, J Piel, P R Shipley, L Xiang, M B Austin, J P Noel. Plant-like biosynthetic pathways in bacteria: from benzoic acid to chalcone. Journal of Natural Products, 2002, 65(12): 1956–1962 https://doi.org/10.1021/np020230m pmid: 12502351
33	C Zheng, J Q Ma, J D Chen, C L Ma, W Chen, M Z Yao, L Chen. Gene co-expression networks reveal key drivers of flavonoid variation in eleven tea cultivars (Camellia sinensis). Journal of Agricultural and Food Chemistry, 2019, 67(35): 9967–9978 https://doi.org/10.1021/acs.jafc.9b04422 pmid: 31403784
34	M Nemesio-Gorriz, P B Blair, K Dalman, A Hammerbacher, J Arnerup, J Stenlid, S M Mukhtar, M Elfstrand. Identification of norway spruce MYB-bHLH-WDR transcription factor complex members linked to regulation of the flavonoid pathway. Frontiers in Plant Science, 2017, 8: 305 https://doi.org/10.3389/fpls.2017.00305 pmid: 28337212

[1]	FASE-21382-OF-JCK_suppl_1	Download
[2]	FASE-21382-OF-JCK_suppl_2	Download

[1]	Zhiqiang XIA,Xin CHEN,Cheng LU,Meiling ZOU,Shujuan WANG,Yang ZHANG,Kun PAN,Xincheng ZHOU,Haiyan WANG,Wenquan WANG. *Comparative transcriptomics revealed enhanced light responses, energy transport and storage in domestication of cassava (Manihot esculenta)*[J]. Front. Agr. Sci. Eng. , 2016, 3(4): 295-307.
[2]	Fengxia YIN,Hui LIU,Shorgan BOU,Guangpeng LI. Oocyte-associated transcription factors in reprogramming after somatic cell nuclear transfer: a review[J]. Front. Agr. Sci. Eng. , 2014, 1(2): 104-113.

Viewed

Full text

Abstract

Cited

Shared

Discussed