An Optimized Method for Profiling Glucosinolate Content in Brassica Enabling Plant Line Selection and Quantitative Trait Locus Mapping
International Journal of Nutrition and Food Sciences
Volume 2, Issue 1, January 2013, Pages: 10-16
Received: Dec. 11, 2012; Published: Jan. 10, 2013
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Reem Issa, Department of Chemistry, University of Warwick, Coventry, CV4 7AL, UK
Guy Barker, School of life sciences, University of Warwick, Coventry, CV4 7AL, UK
Andrew Marsh, Department of Chemistry, University of Warwick, Coventry, CV4 7AL, UK
Susan E. Slade, School of life sciences, University of Warwick, Coventry, CV4 7AL, UK
Paul Taylor, Department of Chemistry, University of Warwick, Coventry, CV4 7AL, UK
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A reproducible and robust enzymatic desulfation reaction utilizing Sulfatase enzyme from Helix pomatia type H1, was developed and used in conjunction with an optimized HPLC-UV/ESI-MS/MS method developed in this study, for complete separation and identification of desulfated glucosinolates, extracted from 89 AGDH mapping population derived from a cross between rapid cycling Brassica oleracea lines; A12DH and GD33DH with high resolution for quantification measurements were used. In addition, we have demonstrated the first use of two internal standards during the preparation of the plant material for analysis, which significantly improved the reproducibility of the quantitative measurements. The quantitative data were then used for the identification of significant Quantitative Trait Loci (QTL) for individual glucosi-nolates and for key points in their biosynthesis, revealed for the presence of major gene effect near the top of B. oleracea linkage group 9 (LG9), associated with aliphatic glucosinolate synthesis. Moreover, a number of novel QTLs were also identified, which control the synthesis of glucosinolates.
Brassicaceae; HPLC-UV/ESI-MS/MS; QTL; Glucosinolates; Sulfatase
To cite this article
Reem Issa, Guy Barker, Andrew Marsh, Susan E. Slade, Paul Taylor, An Optimized Method for Profiling Glucosinolate Content in Brassica Enabling Plant Line Selection and Quantitative Trait Locus Mapping, International Journal of Nutrition and Food Sciences. Vol. 2, No. 1, 2013, pp. 10-16. doi: 10.11648/j.ijnfs.20130201.13
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