3 Biotech

, 8:382 | Cite as

Comparative analysis of glucosinolates and metabolite profiling of green and red mustard (brassica juncea) hairy roots

  • Do Manh Cuong
  • Jae Kwang Kim
  • Sun Ju Bong
  • Seung A Baek
  • Jin Jeon
  • Jong Seok Park
  • Sang Un ParkEmail author
Original Article


Here, accumulation of glucosinolates and expression of glucosinolates biosynthesis genes in green and red mustard hairy roots were identified and quantified by HPLC and qRT-PCR analyses. The total glucosinolates content of green mustard hairy root (10.09 µg/g dry weight) was 3.88 times higher than that of red mustard hairy root. Indolic glucosinolates (glucobrassicin, 4-methoxyglucobrassicin, and neoglucobrassicin) in green mustard were found at 30.92, 6.95, and 5.29 times higher than in red mustard hairy root, respectively. Conversely, levels of glucotropaeolin (aromatic glucosinolate) was significantly higher in red mustard than in green mustard. Accumulation of glucoraphasatin, an aliphatic glucosinolate, was only observed only in red mustard hairy roots. Quantitative real-time PCR analysis showed that the expression level of genes related to aliphatic and aromatic glucosinolate biosynthesis were higher in red mustard, exception BjCYP83B. The expression of BjCYP79B2, which encodes a key enzyme involved in the indolic glucosinolate biosynthetic pathway, was higher in green mustard than in red mustard. Additionally, to further distinguish between green mustard and red mustard hairy roots, hydrophilic and lipophilic compounds were identified by gas chromatography–mass spectrometry and subjected to principal component analysis. The results indicated that core primary metabolites and glucosinolate levels were higher in the hairy roots of green mustard than in those of red mustard.


Glucosinolate Hairy roots Mustard Brassica juncea Metabolite profiling 



This research was supported by the Bio and Medical Technology Development Program of the National Research Foundation (NRF) funded by the Ministry of Science, ICT and Future Planning (2016M3A9A5919548). This work was supported by a grant from the Next-Generation BioGreen 21 Program (SSAC, Project # PJ013328) Rural Development Administration, Republic of Korea.

Author contributions

S.U. Park designed the experiments and analyzed the data. D.M. Cuong, J.K. Kim, S.J. Bong, S.-A Baek, J. Jeon, and J.S. Park wrote the manuscript, performed the experiments, and analyzed the data.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no competing interests.

Supplementary material

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Supplementary material 1 (XLSX 11 KB)
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Supplementary material 2 (XLSX 9 KB)
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Supplementary material 3 (XLSX 9 KB)


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Copyright information

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

Authors and Affiliations

  1. 1.Department of Crop ScienceChungnam National UniversityDaejeonSouth Korea
  2. 2.Division of Life Sciences and Convergence Research Center for Insect VectorsIncheon National UniversityIncheonSouth Korea
  3. 3.Department of Horticultural ScienceChungnam National UniversityDaejeonSouth Korea

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