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The impact of genetics and environment on the polar fraction metabolome of commercial Brassica napus seeds: a multi-site study

Published online by Cambridge University Press:  05 August 2019

Djawed Bennouna Open the ORCID record for Djawed Bennouna [Opens in a new window] ,
Jean-Christophe Avice ,
Clément Rosique ,
Ljubica Svilar ,
Célia Pontet ,
Jacques Trouverie ,
Frédéric Fine ,
Xavier Pinochet ,
Karl Fraser  and
Jean-Charles Martin
Djawed Bennouna
Affiliation:
Aix Marseille Université, INSERM, INRA, C2VN, BioMeT, Marseille, France
Jean-Christophe Avice
Affiliation:
Normandie Université, UNICAEN, INRA, SFR Normandie Végétal (FED4277), UMR 950 Ecophysiologie Végétale et Agronomie, F-14032 Caen, France
Clément Rosique
Affiliation:
Aix Marseille Université, INSERM, INRA, C2VN, BioMeT, Marseille, France
Ljubica Svilar
Affiliation:
Aix Marseille Université, INSERM, INRA, C2VN, BioMeT, Marseille, France CriBioM, Criblage Biologique Marseille, Faculté de Médecine de la Timone, Marseille, France
Célia Pontet
Affiliation:
Terres Inovia, Paris, France
Jacques Trouverie
Affiliation:
Normandie Université, UNICAEN, INRA, SFR Normandie Végétal (FED4277), UMR 950 Ecophysiologie Végétale et Agronomie, F-14032 Caen, France
Frédéric Fine
Affiliation:
Terres Inovia, Paris, France
Xavier Pinochet
Affiliation:
Terres Inovia, Paris, France
Karl Fraser
Affiliation:
Food Nutrition & Health Team, Food & Bio-Based Products Group, AgResearch Grasslands Research Centre, Palmerston North, New Zealand Riddet Institute, Massey University, Palmerston North 4442, New Zealand
Jean-Charles Martin*
Affiliation:
Aix Marseille Université, INSERM, INRA, C2VN, BioMeT, Marseille, France
*
*Author for correspondence: Jean-Charles Martin, Email: jean-charles.martin@univ-amu.fr
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Abstract

This study was designed to elucidate the biological variation in expression of many metabolites due to environment, genotype, or both, and to investigate the potential utility of metabolomics to supplement compositional analysis for the design of a new resilient cultivar of Brassica napus that can be steady in phytochemicals in different regions in France. Eight rapeseed varieties, grown in eight regions of France, were compared using a non-targeted metabolomics approach. The statistical analysis highlighted the distance and closeness between the samples in terms of both genotypes and geographical regions. A major environmental impact was observed on the polar metabolome, with different trends, depending on the varieties. Some varieties were very sensitive to the environment, while others were quite resilient. The identified secondary metabolites were mapped into the KEGG pathway database to reveal the most sensitive target proteins susceptible to environmental influences. A glucosyl-transferase encoded by the UGT84A1 gene involved in the biosynthesis of phenylpropanoid was identified. This protein could be rate limiting/promoting in this pathway depending on environmental conditions. The metabolomics approach used in this study demonstrated its efficiency to characterize the environmental influence on various cultivars of Brassica napus seeds and may help identify targets for crop improvement.

Keywords

Brassica napusdata processingenvironmentliquid chromatographymass spectrometrymetabolomics

Information

Type
Research Paper
Information
Seed Science Research , Volume 29 , Issue 3 , September 2019 , pp. 167 - 178
Copyright
Copyright © Cambridge University Press 2019 

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References

Asiago, VM, Hazebroek, J, Harp, T and Zhong, C (2012) Effects of genetics and environment on the metabolome of commercial maize hybrids: a multisite study. Journal of Agricultural and Food Chemistry 60, 11498–11508.Google Scholar
Babst, BA, Chen, HY, Wang, HQ, Payyavula, RS, Thomas, TP, Harding, SA and Tsai, CJ (2014) Stress-responsive hydroxycinnamate glycosyltransferase modulates phenylpropanoid metabolism in Populus. Journal of Experimental Botany 65, 4191–4200.Google Scholar
Baux, A, Hebeisen, T and Pellet, D (2008) Effects of minimal temperatures on low-linolenic rapeseed oil fatty-acid composition. European Journal of Agronomy 29, 102–107.Google Scholar
Caraux, G and Pinloche, S (2005) PermutMatrix: a graphical environment to arrange gene expression profiles in optimal linear order. Bioinformatics 21, 1280–1281.Google Scholar
Cartea, ME, Francisco, M, Soengas, P and Velasco, P (2011) Phenolic compounds in Brassica vegetables. Molecules 16, 251–280.Google Scholar
Cataldi, TRI, Lelario, F, Orlando, D and Bufo, SA (2010) Collision-induced dissociation of the A + 2 isotope ion facilitates glucosinolates structure elucidation by electrospray ionization-tandem mass spectrometry with a linear quadrupole ion trap. Analytical Chemistry 82, 5686–5696.Google Scholar
Dunn, WB, Erban, A, Weber, RJM, Creek, DJ, Brown, M, Breitling, R, Hankemeier, T, Goodacre, R, Neumann, S, Kopka, J and Viant, MR (2013) Mass appeal: metabolite identification in mass spectrometry-focused untargeted metabolomics. Metabolomics 9, 44–66.Google Scholar
Fang, J, Reichelt, M, Hidalgo, W, Agnolet, S and Schneider, B (2012) Tissue-specific distribution of secondary metabolites in rapeseed (Brassica napus L.). PLoS ONE 7, 1–8.Google Scholar
Farag, MA, Sharaf Eldin, MG, Kassem, H and Abou El Fetouh, M (2013) Metabolome classification of Brassica napus L. organs via UPLC-QTOF-PDA-MS and their anti-oxidant potential. Phytochemical Analysis 24, 277–287.Google Scholar
Fenwick, GR and Heaney, RK (1983) Glucosinolates and their breakdown products in cruciferous crops, foods and feedingstuffs. Food Chemistry 11, 249–271.Google Scholar
Fenwick, GR, Spinks, AE, Wilkinson, PA, Heaney, KR and Legoy, AM (1986) Effect of processing on the antinutrient content of rapeseed. Journal of the Science of Food and Agriculture 37, 735–741.Google Scholar
Fiehn, O (2001) Combining geonomics, metabolome analysis, and biochemical modelling to understand metabolic networks. Comparative and Functional Genomics 2, 155–168.Google Scholar
He, F, Pan, QH, Shi, Y and Duan, CQ (2008) Biosynthesis and genetic regulation of proanthocyanidins in plants. Molecules 13, 2674–2703.Google Scholar
Hong, J, Yang, L, Zhang, D and Shi, J (2016) Plant metabolomics: an indispensable system biology tool for plant science. International Journal of Molecular Sciences 17, E767.Google Scholar
Huang, W, Zhang, X and Chen, W (2016) Role of oxidative stress in Alzheimer's disease (review). Biomedical Reports 4, 519–522.Google Scholar
Ivanisevic, J, Benton, HP, Rinehart, D, Epstein, A, Kurczy, ME, Boska, MD, Gendelman, HE and Siuzdak, G (2015) An interactive cluster heat map to visualize and explore multidimensional metabolomic data. Metabolomics 11, 1029–1034.Google Scholar
Jahangir, M, Abdel-Farid, IB, Kim, HK, Choi, YH and Verpoorte, R (2009) Healthy and unhealthy plants: the effect of stress on the metabolism of Brassicaceae. Environmental and Experimental Botany 67, 23–33.Google Scholar
Jankowski, K, Budzynski, W and Szymanowski, A (2008) Effect of sulfur on the quality of winter rape seeds. Journal of Elementology 13, 521–534.Google Scholar
Jankowski, KJ, Sokólski, M, Dubis, B, Krzebietke, S, Żarczyński, P, Hulanicki, P and Hulanicki, PS (2016) Yield and quality of winter oilseed rape (Brassica napus L.) seeds in response to foliar application of boron. Agricultural and Food Science 25, 164–176.Google Scholar
Jensen, CR, Mogensen, VO, Mortensen, G, Fieldsend, JK, Milford, GFJ, Andersen, MN and Thage, JH (1996) Seed glucosinolate, oil and protein contents of field-grown rape (Brassica napus L.) affected by soil drying and evaporative demand. Field Crops Research 47, 93–105.Google Scholar
Jervis, J, Kastl, C, Hildreth, SB, Biyashev, R, Grabau, EA, Saghai-Maroof, MA and Helm, RF (2015) Metabolite profiling of soybean seed extracts from near-isogenic low and normal phytate lines using orthogonal separation strategies. Journal of Agricultural and Food Chemistry 63, 9879–9887.Google Scholar
Kanehisa, M, Furumichi, M, Tanabe, M, Sato, Y and Morishima, K (2017) KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Research 45, D353–361.Google Scholar
Keum, YS, Jeong, WS and Kong, AN (2004) Chemoprevention by isothiocyanates and their underlying molecular signaling mechanisms. Mutation Research – Fundamental and Molecular Mechanisms of Mutagenesis 555, 191–202.Google Scholar
Khattab, R, Eskin, M, Aliani, M and Thiyam, U (2010) Determination of sinapic acid derivatives in Canola extracts using high-performance liquid chromatography. Journal of the American Oil Chemists’ Society 87, 147–155.Google Scholar
Kim, JK, Chu, SM, Kim, SJ, Lee, DJ, Lee, SY, Lim, SH, Ha, SH, Kweon, SJ and Cho, HS (2010) Variation of glucosinolates in vegetable crops of Brassica rapa L. ssp. pekinensis. Food Chemistry 119, 423–428.Google Scholar
Lattanzio, V, Lattanzio, VMT, Cardinali, A and Amendola, V (2006) Role of phenolics in the resistance mechanisms of plants against fungal pathogens and insects. Available at: https://www.researchgate.net/publication/303270594_Role_of_phenolics_in_the_resistance_mechanisms_of_plants_against_fungal_pathogens_and_insectsGoogle Scholar
Lehfeldt, C, Shirley, AM, Meyer, K, Ruegger, MO, Cusumano, JC, Viitanen, PV, Strack, D and Chapple, C (2000) Cloning of the SNG1 gene of Arabidopsis reveals a role for a serine carboxypeptidase-like protein as an acyltransferase in secondary metabolism. The Plant Cell 12, 1295.Google Scholar
Lehmann, MM, Rinne, KT, Blessing, C, Siegwolf, RTW, Buchmann, N and Werner, RA (2015) Malate as a key carbon source of leaf dark-respired CO2 across different environmental conditions in potato plants. Journal of Experimental Botany 66, 5769–5781.Google Scholar
Lelario, F, Bianco, G, Bufo, SA and Cataldi, TRI (2012) Establishing the occurrence of major and minor glucosinolates in Brassicaceae by LC-ESI-hybrid linear ion-trap and Fourier-transform ion cyclotron resonance mass spectrometry. Phytochemistry 73, 74–83.Google Scholar
Lohani, UC, Fallahi, P and Muthukumarappan, K (2015) Comparison of ethyl acetate with hexane for oil extraction from various oilseeds. Journal of the American Oil Chemists’ Society 92, 743–754.Google Scholar
Martin, JC, Maillot, M, Mazerolles, G, Verdu, A, Lyan, B, Migné, C, Defoort, C, Canlet, C, Junot, C, Guillou, C, Manach, C, Jabob, D, Bouveresse, DJR, Paris, E, Pujos-Guillot, E, Jourdan, F, Giacomoni, F, Courant, F, Favé, G, Le Gall, G, Chassaigne, H, Tabet, JC, Martin, JF, Antignac, JP, Shintu, L, Defernez, M, Philo, M, Alexandre-Gouaubau, MC, Amiot-Carlin, MJ, Bossis, M, Triba, MN, Stojilkovic, N, Banzet, N, Molinié, R, Bott, R, Goulitquer, S, Caldarelli, S and Rutledge, DN (2015) Can we trust untargeted metabolomics? Results of the metabo-ring initiative, a large-scale, multi-instrument inter-laboratory study. Metabolomics 11, 807–821.Google Scholar
Mawson, R and Heaney, RK (1994) Rapeseed meal-glucosinolates and their antinutritional effects. Part 5. Animal reproduction. Die Nahrung 38, 588–598.Google Scholar
Miller-Cebert, RL, Sistani, NA and Cebert, E (2009) Comparative mineral composition among canola cultivars and other cruciferous leafy greens. Journal of Food Composition and Analysis 22, 112–116.Google Scholar
Misra, BB (2016) Cataloging the Brassica napus seed metabolome. Cogent Food & Agriculture 2, 1–16.Google Scholar
Nicholson, JK, Holmes, E and Lindon, JC (1999) ‘Metabonomics’: understanding the metabolic responses of living systems to path physiological stimul via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica 29, 1181–1189.Google Scholar
Pandey, K and Rizv, S (2009) Plant polyphenols as dietary antioxidants in human health and disease. Oxidative Medicine and Cellular Longevity 2, 270–278.Google Scholar
Petersen, BL, Chen, S, Hansen, CH, Olsen, CE and Halkier, BA (2002) Composition and content of glucosinolates in developing Arabidopsis thaliana. Planta 214, 562–571.Google Scholar
Scott, JK, Vitou, J and Jourdan, M (1999) Review of the potential for biological control of wild radish (Raphanus raphanistrum) based on surveys in the Mediterranean region. 377–380.Google Scholar
Shannon, P, Markiel, A, Ozier, O, Baliga, NS, Wang, JT, Ramage, D, Amin, N, Schwikowski, B and Ideker, T (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Research 2498–2504.Google Scholar
Shao, Y, Jiang, J, Ran, L, Lu, C, Wei, C and Wang, Y (2014) Analysis of flavonoids and hydroxycinnamic acid derivatives in rapeseeds (Brassica napus L. var. napus) by HPLC-PDA-ESI(–)-MSn/HRMS. Journal of Agricultural and Food Chemistry 62, 2935–2945.Google Scholar
Sinlapadech, T, Stout, J, Ruegger, MO, Deak, M and Chapple, C (2007) The hyper-fluorescent trichome phenotype of the brt1 mutant of Arabidopsis is the result of a defect in a sinapic acid:UDPG glucosyltransferase. Plant Journal 49, 655–668.Google Scholar
Smith, CA, Want, EJ, O'Maille, G, Abagyan, R and Siuzdak, G (2006) XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. Analytical Chemistry 78, 779–787.Google Scholar
Sumner, LW, Lei, Z, Nikolau, BJ, Saito, K, Roessner, U and Trengove, R (2014) Proposed quantitative and alphanumeric metabolite identification metrics. Metabolomics 10, 1047–1049.Google Scholar
Tautenhahn, R, Bottcher, C and Neumann, S (2008) Highly sensitive feature detection for high resolution LC/MS. BMC Bioinformatics 9, 1–16.Google Scholar
Van Der Kloet, FM, Bobeldijk, I, Verheij, ER and Jellema, RH (2009) Analytical error reduction using single point calibration for accurate and precise metabolomic phenotyping research articles. Journal of Proteome Research 8, 5132–5141.Google Scholar
Vermorel, M, Heaney, RK and Fenwick, GR (1988) Antinutritional effects of the rapeseed meals, Darmor and Jet Neuf, and progoitrin together with myrosinase in the growing rat. Journal of the Science of Food and Agriculture 44, 321–334.Google Scholar
Westerhuis, JA, Hoefsloot, HCJ, Smit, S, Vis, DJ, Smilde, AK, Velzen, EJJ, Duijnhoven, JPM and Dorsten, FA (2008) Assessment of PLSDA cross validation. Metabolomics 4, 81–89.Google Scholar
Widodo, , Patterson, JH, Newbigin, E, Tester, M, Bacic, A and Roessner, U (2009) Metabolic responses to salt stress of barley (Hordeum vulgare L.) cultivars, Sahara and Clipper, which differ in salinity tolerance. Journal of Experimental Botany 60, 4089–4103.Google Scholar
Xia, J, Psychogios, N, Young, N and Wishart, D S (2009) MetaboAnalyst: a web server for metabolomic data analysis and interpretation. Nucleic Acids Research 37, 652–660.Google Scholar
Yang, S, Arasu, MV, Chun, J, Jang, Y, Lee, Y, Kim, IH, Lee, K, Hong, S and Kim, S (2015) Identification and determination of phenolic compounds in rapeseed meals (Brassica napus L.). Journal of Agricultural Chemistry and Environment 4, 14–23.Google Scholar
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