Characterization of metabolite quantitative trait loci and metabolic networks that control glucosinolate concentration in the seeds and leaves of Brassica napus
Article first published online: 4 OCT 2011
© 2011 The Authors. New Phytologist © 2011 New Phytologist Trust
Volume 193, Issue 1, pages 96–108, January 2012
How to Cite
Feng, J., Long, Y., Shi, L., Shi, J., Barker, G. and Meng, J. (2012), Characterization of metabolite quantitative trait loci and metabolic networks that control glucosinolate concentration in the seeds and leaves of Brassica napus. New Phytologist, 193: 96–108. doi: 10.1111/j.1469-8137.2011.03890.x
- Issue published online: 2 DEC 2011
- Article first published online: 4 OCT 2011
- Received: 7 July 2011, Accepted: 15 August 2011
- Brassica napus;
- epistatic interaction;
- metabolic networks;
- quantitative trait loci (QTL);
- regulatory relationships
- •Glucosinolates are a major class of secondary metabolites found in the Brassicaceae, whose degradation products are proving to be increasingly important for human health and in crop protection.
- •The genetic and metabolic basis of glucosinolate accumulation was dissected through analysis of total glucosinolate concentration and its individual components in both leaves and seeds of a doubled-haploid (DH) mapping population of oilseed rape/canola (Brassica napus).
- •The quantitative trait loci (QTL) that had an effect on glucosinolate concentration in either or both of the organs were integrated, resulting in 105 metabolite QTL (mQTL). Pairwise correlations between individual glucosinolates and prior knowledge of the metabolic pathways involved in the biosynthesis of different glucosinolates allowed us to predict the function of genes underlying the mQTL. Moreover, this information allowed us to construct an advanced metabolic network and associated epistatic interactions responsible for the glucosinolate composition in both leaves and seeds of B. napus.
- •A number of previously unknown potential regulatory relationships involved in glucosinolate synthesis were identified and this study illustrates how genetic variation can affect a biochemical pathway.