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Tree Genetics & Genomes

, 14:23 | Cite as

Uncovering tea-specific secondary metabolism using transcriptomic and metabolomic analyses in grafts of Camellia sinensis and C. oleifera

  • Wei-Wei Deng
  • Jieyun Han
  • Yanbing Fan
  • Yuling Tai
  • Biying Zhu
  • Mengqian Lu
  • Rangjian Wang
  • Xiaochun Wan
  • Zheng-Zhu Zhang
Original Article
  • 222 Downloads
Part of the following topical collections:
  1. Gene Expression

Abstract

Camellia sinensis (L.) Kuntze and Camellia oleifera C. Abel (Theaceae) are closely related perennial woody shrubs, but the accumulation of metabolites and gene expression patterns are quite different between these two species. In order to understand the mechanisms behind the accumulation and biosynthesis of tea-specific secondary metabolites and the key genes that regulate their target pathways, 1-year-old clone cuttings of C. sinensis and C. oleifera were grafted in both directions, and self-grafted C. sinensis were used as controls. The transcriptomes and metabolomes of leaves and roots from the grafts were analyzed. We found that 1375 unigenes were up-regulated in the leaves of the CS-CO grafts (C. sinensis scion, C. oleifera stock), while 2437 unigenes were down-regulated. OPLS-DA models established for 7230 and 3223 mass spectra peaks were obtained in the positive and negative modes by LC-MS detection. Association analysis of the secondary metabolism pathways was performed, and the relative gene expressions of 14 genes from the transcriptome screening were verified by qRT-PCR. Among the differential metabolites screened and identified, we found that the relative levels of theanine and caffeine decreased significantly, and that many of the genes in these metabolic pathways were also down-regulated. In contrast, the levels of flavonoids apparently increased, and the expression of related genes in the flavonoid biosynthetic pathway were mostly up-regulated.

Keywords

Camellia sinensis C. oleifera Grafts Metabolome Transcriptome Secondary metabolism 

Notes

Acknowledgments

This study was supported by the Natural Science Foundation of Anhui Province (Grant No.1608085QC60), the National Natural Science Foundation of China (NSFC) (Grant No. 31300576), the Changjiang Scholars and Innovative Research Team in University (Grant No. IRT_15R01), and Tea Plant Germplasm Resources Innovation Team Project of Fujian Academy of Agricultural Science (STIT2017-3-12). We appreciated Chun Liu (Beijing Genome Institute at Shenzhen, China) for technical support and analysis. We were also grateful to the elixigen editing service for the language polishing.

Authors’ contributions

WD, JH, and YF prepared the material for sequencing and analyzed the data.YT, BZ, and ML participated in data analysis. WD, JH, YF, and RW were responsible for drafting and revising the manuscript. ZZ and XW guided this research.

Compliance with ethical standards

The authors declare that they complied with ethical standards.

Competing interests

The authors declare that they have no competing interests.

Data achieving statement

The clean data of grafts of Camellia sinensis and C. oleifera will be available in the NCBI SRA (http://www.ncbi.nlm.nih.gov/Traces/sra_sub/sub.cgi) under project accession number PRJNA429946 if the manuscript is accepted for publication in the tree genetics and genomes prior to publication.

Supplementary material

11295_2018_1237_MOESM1_ESM.docx (625 kb)
ESM 1 (DOCX 624 kb)
11295_2018_1237_MOESM2_ESM.xls (35.2 mb)
ESM 2 (XLS 36019 kb)

References

  1. Ashihara H, Sano H, Crozier A (2008) Caffeine and related purine alkaloids: biosynthesis, catabolism, function and genetic engineering. Phytochemistry 69:841–856.  https://doi.org/10.1016/j.phytochem.2007.10.029 CrossRefPubMedGoogle Scholar
  2. Ashihara H (2015) Occurrence, biosynthesis and metabolism of theanine (γ-glutamyl-L-ethylamide) in plants: a comprehensive review. Nat Prod Commun 10:803–810PubMedGoogle Scholar
  3. Ashihara H, Crozier A (1999) Biosynthesis and metabolism of caffeine and related purine alkaloids in plants. Adv Bot Res 30:117–205.  https://doi.org/10.1016/S0065-2296(08)60228-1 CrossRefGoogle Scholar
  4. Audic S, Claverie JM (1997) The significance of digital gene expression profiles. Genome Res 7:986–995.  https://doi.org/10.1101/gr.7.10.986 CrossRefPubMedGoogle Scholar
  5. Bastos DH, Saldanha LA, Catharino RR, Sawaya A, Cunha I, Carvalho P, Eberlin M (2007) Phenolic antioxidants identified by ESI-MS from yerba maté (Ilex paraguariensis) and green tea (Camelia sinensis) extracts. Molecules 12:423–432.  https://doi.org/10.3390/12030423 CrossRefPubMedGoogle Scholar
  6. Bylesjö M, Rantalainen M, Cloarec O, Nicholson JK, Holmes E, Trygg J (2006) OPLS discriminant analysis: combining the strengths of PLS-DA and SIMCA classification. J Chemometrics 20:341–351.  https://doi.org/10.1002/cem.1006 CrossRefGoogle Scholar
  7. Cabrera C, Artacho R, Giménez R (2006) Beneficial effects of green tea—a review. J Am Coll Nutr 25:79–99.  https://doi.org/10.1080/07315724.2006.10719518 CrossRefPubMedGoogle Scholar
  8. Cheng S, Wang Y, Li J et al (2004) Study on the relationship between the endogenous hormones and flavonoids in Ginkgo biloba leaf. Scientia Silvae Sinicae 40:45–49Google Scholar
  9. Conesa A, Götz S, García-Gómez JM et al (2005) Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics 21:3674–3676.  https://doi.org/10.1093/bioinformatics/bti610 CrossRefPubMedGoogle Scholar
  10. Cookson SJ, Clemente Moreno MJ, Hevin C, Nyamba Mendome LZ, Delrot S, Trossat-Magnin C, Ollat N (2013) Graft union formation in grapevine induces transcriptional changes related to cell wall modification, wounding, hormone signalling, and secondary metabolism. J Exper Bot 64:2997–3008.  https://doi.org/10.1093/jxb/ert144 CrossRefGoogle Scholar
  11. Dawson RF (1942) Accumulation of nicotine in reciprocal grafts of tomato and tobacco. Am J Bot 29:66–71CrossRefGoogle Scholar
  12. Deng WW, Ogita S, Ashihara H (2008) Biosynthesis of theanine (γ-ethylamino-l-glutamic acid) in seedlings of Camellia sinensis. Phytochem Lett 1:115–119.  https://doi.org/10.1016/j.phytol.2008.06.002 CrossRefGoogle Scholar
  13. Deng WW, Ogita S, Ashihara H (2009) Ethylamine content and theanine biosynthesis in different organs of Camellia sinensis seedlings. Zeitschrift für Naturforschung C 64:387–390.  https://doi.org/10.1515/znc-2009-5-614 Google Scholar
  14. Deng WW, Li M, Gu CC, Li DX, Ma LL, Jin Y, Wan XC (2015) Low caffeine content in novel grafted tea with Camellia sinensis as scions and Camellia oleifera as stocks. Nat Prod Commun 10:789–792PubMedGoogle Scholar
  15. Deng WW, Fan YB, Gu CC et al (2017) Changes in morphological characters and secondary metabolite contents in leaves of grafting seedlings with Camellia sinensis as scions and C. oleifera as stocks. J Trop Subtrop Bot 25:35–42Google Scholar
  16. Feng C, Chen M, Xu CJ et al (2012) Transcriptomic analysis of Chinese bayberry (Myrica rubra) fruit development and ripening using RNA-Seq. BMC Genomics 13:13–19.  https://doi.org/10.1186/1471-2164-13-19 CrossRefGoogle Scholar
  17. Gismondi A, Di Marco G, Canini A (2017) Detection of plant microRNAs in honey. PLoS One 12(2):e0172981.  https://doi.org/10.1371/journal.pone.0172981 CrossRefPubMedPubMedCentralGoogle Scholar
  18. Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, Adiconis X, Fan L, Raychowdhury R, Zeng Q, Chen Z, Mauceli E, Hacohen N, Gnirke A, Rhind N, di Palma F, Birren BW, Nusbaum C, Lindblad-Toh K, Friedman N, Regev A (2011) Trinity: reconstructing a full-length transcriptome without a genome from RNA-Seq data. Nat Biotechnol 29(7):644–652.  https://doi.org/10.1038/nbt.1883 CrossRefPubMedPubMedCentralGoogle Scholar
  19. Haas BJ, Papanicolaou A, Yassour M, Grabherr M, Blood PD, Bowden J, Couger MB, Eccles D, Li B, Lieber M, MacManes MD, Ott M, Orvis J, Pochet N, Strozzi F, Weeks N, Westerman R, William T, Dewey CN, Henschel R, LeDuc RD, Friedman N, Regev A (2013) De novo transcript sequence reconstruction from RNA-Seq: reference generation and analysis with trinity. Nat Protocol 8(8):1494–1512.  https://doi.org/10.1038/nprot.2013.084 CrossRefGoogle Scholar
  20. Hertog MG, Hollman PC, Katan MB et al (1993) Intake of potentially anticarcinogenic flavonoids and their determinants in adults in The Netherlands. Nutr Cancer 20:21–29.  https://doi.org/10.1080/01635589309514267 CrossRefPubMedGoogle Scholar
  21. Hu Y, Wang HF, Dong SQ et al (2016) Effect of sucrose treatment on flavonoid content and antioxidant activity of Sedum aizoon leaves. Modern Food Sci Tech 32:250–255Google Scholar
  22. Jiang X, Liu Y, Li W, Zhao L, Meng F, Wang Y, Tan H, Yang H, Wei C, Wan X, Gao L, Xia T (2013) Tissue-specific, development-dependent phenolic compounds accumulation profile and gene expression pattern in tea plant [Camellia sinensis]. PLoS One 8(4):e62315.  https://doi.org/10.1371/journal.pone.0062315 CrossRefPubMedPubMedCentralGoogle Scholar
  23. Juneja LR, Chu DC, Okubo T et al (1999) L-theanine—a unique amino acid of green tea and its relaxation effect in humans. Trends Food Sci Tech 10:199–204.  https://doi.org/10.1016/S0924-2244(99)00044-8 CrossRefGoogle Scholar
  24. Kanehisa M, Araki M, Goto S, Hattori M, Hirakawa M, Itoh M, Katayama T, Kawashima S, Okuda S, Tokimatsu T, Yamanishi Y (2008) KEGG for linking genomes to life and the environment. Nucleic Acids Res 36:480–484.  https://doi.org/10.1093/nar/gkm882 CrossRefGoogle Scholar
  25. Kanehisa M, Goto S, Kawashima S et al (2004) The KEGG resource for deciphering the genome. Nucleic Acids Res 32:277–280.  https://doi.org/10.1093/nar/gkh063 CrossRefGoogle Scholar
  26. Kanehisa M, Goto S, Sato Y, Furumichi M, Tanabe M (2012) KEGG for integration and interpretation of large-scale molecular data sets. Nucleic Acids Res 40:109–114.  https://doi.org/10.1093/nar/gkr988 CrossRefGoogle Scholar
  27. Kim D, Langmead B, Salzberg SL (2015) HISAT: a fast spliced aligner with low memory requirements. Nat Meth 12:357–360.  https://doi.org/10.1038/nmeth.3317 CrossRefGoogle Scholar
  28. Koenig D, Jiménez-Gómez JM, Kimura S et al (2013) Comparative transcriptomics reveals patterns of selection in domesticated and wild tomato. PNAS 110:2655–2662.  https://doi.org/10.1073/pnas.1309606110 CrossRefGoogle Scholar
  29. Lea US, Slimestad R, Smedvig P, Lillo C (2007) Nitrogen deficiency enhances expression of specific MYB and bHLH transcription factors and accumulation of end products in the flavonoid pathway. Planta 225:1245–1253.  https://doi.org/10.1007/s00425-006-0414-x CrossRefPubMedGoogle Scholar
  30. Lee CP, Shih PH, Hsu CL, Yen GC (2007) Hepatoprotection of tea seed oil (Camellia oleifera Abel.) against CCl4-induced oxidative damage in rats. Food Chem Toxicol 45:888–895.  https://doi.org/10.1016/j.fct.2006.11.007 CrossRefPubMedGoogle Scholar
  31. Lee CP, Yen GC (2006) Antioxidant activity and bioactive compounds of tea seed (Camellia oleifera Abel.) oil. J Agr Food Chem 54:779–784.  https://doi.org/10.1021/jf052325a CrossRefGoogle Scholar
  32. Li CF, Zhu Y, Yu Y, Zhao QY, Wang SJ, Wang XC, Yao MZ, Luo D, Li X, Chen L, Yang YJ (2015) Global transcriptome and gene regulation network for secondary metabolite biosynthesis of tea plant (Camellia sinensis). BMC Genomics 16:560.  https://doi.org/10.1186/s12864-015-1773-0 CrossRefPubMedPubMedCentralGoogle Scholar
  33. Li M, Li Y, Guo L, Gong N, Pang Y, Jiang W, Liu Y, Jiang X, Zhao L, Wang Y, Xie DY, Gao L, Xia T (2017) Functional characterization of tea (Camellia sinensis) MYB4a transcription factor using an integrative approach. Front Plant Sci 8:943.  https://doi.org/10.3389/fpls.2017.00943 CrossRefPubMedPubMedCentralGoogle Scholar
  34. Mahadevan S, Shah SL, Marrie TJ, Slupsky CM (2008) Analysis of metabolomic data using support vector machines. Analytical Chem 80:7562–7570.  https://doi.org/10.1021/ac800954c CrossRefGoogle Scholar
  35. McCombie G, Browning LM, Titman CM, Song M, Shockcor J, Jebb SA, Griffin JL (2009) ω-3 oil intake during weight loss in obese women results in remodelling of plasma triglyceride and fatty acids. Metabolomics 5:363–374.  https://doi.org/10.1007/s11306-009-0161-7 CrossRefPubMedPubMedCentralGoogle Scholar
  36. McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, Garimella K, Altshuler D, Gabriel S, Daly M, DePristo MA (2010) The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 20:1297–1303.  https://doi.org/10.1101/gr.107524.110 CrossRefPubMedPubMedCentralGoogle Scholar
  37. Mistry J, Finn RD, Eddy SR, Bateman A, Punta M (2013) Challenges in homology search: HMMER3 and convergent evolution of coiled-coil regions. Nucleic Acids Res 41:e121.  https://doi.org/10.1093/nar/gkt263 CrossRefPubMedPubMedCentralGoogle Scholar
  38. Pertea G, Huang X, Liang F, Antonescu V, Sultana R, Karamycheva S, Lee Y, White J, Cheung F, Parvizi B, Tsai J, Quackenbush J (2003) TIGR gene indices clustering tools (TGICL): a software system for fast clustering of large EST datasets. Bioinformatics 19(5):651–652.  https://doi.org/10.1093/bioinformatics/btg034 CrossRefPubMedGoogle Scholar
  39. Quevillon E, Silventoinen V, Pillai S et al (2005) InterProScan: protein domains identifier. Nucl Acids Res 33:116–120.  https://doi.org/10.1093/nar/gki442 CrossRefGoogle Scholar
  40. Ranjith K, Ilango R, Victor J (2017) Impact of grafting methods, scion materials and number of scions on graft success, vigour and flowering of top worked plants in tea (Camellia spp.) Sci Hortic 220:139–146.  https://doi.org/10.1016/j.scienta.2017.03.039 CrossRefGoogle Scholar
  41. Rice P, Longden I, Bleasby A (2000) EMBOSS: the European molecular biology open software suite. Trends Genet 16:276–277CrossRefPubMedGoogle Scholar
  42. Ruan CJ, Mopper S (2017) High-crown grafting to increase low yields in Camellia oleifera. J Hortic Sci Biotechnol 92(4):439–444.  https://doi.org/10.1080/14620316.2017.1283969 Google Scholar
  43. Savoi S, Wong DC, Arapitsas P et al (2016) Transcriptome and metabolite profiling reveals that prolonged drought modulates the phenylpropanoid and terpenoid pathway in white grapes (Vitis vinifera L.) BMC Plant Biol 16:67.  https://doi.org/10.1186/s12870-016-0760-1 CrossRefPubMedPubMedCentralGoogle Scholar
  44. Stulen I (1986) Interactions between nitrogen and carbon metabolism in a whole plant context. Developments in Plant and Soil Sciences, vol 19. Springer, Dordrecht, pp 261-278Google Scholar
  45. Sun B, Zhu Z, Cao P, Chen H, Chen C, Zhou X, Mao Y, Lei J, Jiang Y, Meng W, Wang Y, Liu S (2016) Purple foliage coloration in tea (Camellia sinensis L.) arises from activation of the R2R3-MYB transcription factor CsAN1. Sci Rep 6(32534).  https://doi.org/10.1038/srep32534
  46. Tai Y, Wei C, Yang H, Zhang L, Chen Q, Deng W, Wei S, Zhang J, Fang C, Ho C, Wan X (2015) Transcriptomic and phytochemical analysis of the biosynthesis of characteristic constituents in tea (Camellia sinensis) compared with oil tea (Camellia oleifera). BMC Plant Biol 15:190.  https://doi.org/10.1186/s12870-015-0574-6 CrossRefPubMedPubMedCentralGoogle Scholar
  47. Takeo T (1974) L-alanine as a precursor of ethylamine in Camellia sinensis. Phytochemistry 13:1401–1406.  https://doi.org/10.1016/0031-9422(74)80299-2 CrossRefGoogle Scholar
  48. Tautenhahn R, Cho K, Uritboonthai W, Zhu Z, Patti GJ, Siuzdak G (2012) An accelerated workflow for untargeted metabolomics using the METLIN database. Nat Biotech 30:826–828.  https://doi.org/10.1038/nbt.2348 CrossRefGoogle Scholar
  49. Trapnell C, Hendrickson DG, Sauvageau M, Goff L, Rinn JL, Pachter L (2013) Differential analysis of gene regulation at transcript resolution with RNA-seq. Nat Biotech 31:46–53.  https://doi.org/10.1038/nbt.2450 CrossRefGoogle Scholar
  50. Weisburger JH, Hosey JR, Larios E, Pittman B, Zang E, Hara Y, Kuts-Cheraux G (2001) Investigation of commercial mitolife as an antioxidant and antimutagen. Nutrition 17:322–325.  https://doi.org/10.1016/S0899-9007(00)00557-8 CrossRefPubMedGoogle Scholar
  51. Wiklund S, Johansson E, Sjöström L, Mellerowicz EJ, Edlund U, Shockcor JP, Gottfries J, Moritz T, Trygg J (2008) Visualization of GC/TOF-MS-based metabolomics data for identification of biochemically interesting compounds using OPLS class models. Anal Chem 80:115–122.  https://doi.org/10.1021/ac0713510 CrossRefPubMedGoogle Scholar
  52. Wu ZJ, Tian C, Jiang Q, Li XH, Zhuang J (2016) Selection of suitable reference genes for qRT-PCR normalization during leaf development and hormonal stimuli in tea plant (Camellia sinensis). Sci Rep 6(19748).  https://doi.org/10.1038/srep19748
  53. Xia EH, Jiang JJ, Huang H, Zhang LP, Zhang HB, Gao LZ (2014) Transcriptome analysis of the oil-rich tea plant, Camellia oleifera, reveals candidate genes related to lipid metabolism. PLoS One 9:e104150.  https://doi.org/10.1371/journal.pone.0104150 CrossRefPubMedPubMedCentralGoogle Scholar
  54. Zhao Y, Chen P, Lin L, Harnly JM, Yu L(L), Li Z (2011) Tentative identification, quantitation, and principal component analysis of green pu-erh, green, and white teas using UPLC/DAD/MS. Food Chem 126:1269–1277.  https://doi.org/10.1016/j.foodchem.2010.11.055 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.State Key Laboratory of Tea Plant Biology and UtilizationAnhui Agricultural UniversityHefeiChina
  2. 2.Tea Research InstituteFujian Academy of Agricultural ScienceFuanChina

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