Abstract
The genetic basis of the wide variation for nutritional traits in Brassica rapa is largely unknown. A new Recombinant Inbred Line (RIL) population was profiled using High Performance Liquid Chromatography (HPLC) and Nuclear Magnetic Resonance (NMR) analysis to detect quantitative trait loci (QTLs) controlling seed tocopherol and seedling metabolite concentrations. RIL population parent L58 had a higher level of glucosinolates and phenylpropanoids, whereas levels of sucrose, glucose and glutamate were higher in the other RIL population parent, R-o-18. QTL related to seed tocopherol (α-, β-, γ-, δ-, α-/γ- and total tocopherol) concentrations were detected on chromosomes A3, A6, A9 and A10, explaining 11%–35% of the respective variation. The locus on A3 co-locates with the BrVTE1gene, encoding tocopherol cyclase. NMR spectroscopy identified the presence of organic/amino acid, sugar/glucosinolate and aromatic compounds in seedlings. QTL positions were obtained for most of the identified compounds. Compared to previous studies, novel loci were found for glucosinolate concentrations. This work can be used to design markers for marker-assisted selection of nutritional compounds in B. rapa.
Highlights
Brassica rapa is a valuable source of health-promoting metabolites, like antioxidants, vitamins or glucosinolates
Transgression beyond the parental values was observed for all measured tocopherols, except δ-tocopherol (Figure 1), suggesting both parents to contain both positive and negative alleles of genes involved in tocopherol biosynthesis
H-Nuclear Magnetic Resonance (NMR) data of Recombinant Inbred Line (RIL) seedling metabolites were subjected to principal component analysis (PCA)
Summary
Brassica rapa is a valuable source of health-promoting metabolites, like antioxidants, vitamins or glucosinolates. B. rapa is related to the reference plant species, Arabidopsis thaliana, in which fourteen QTLs affecting seed tocopherol content and composition have been identified, in two recombinant inbred line (RIL) populations [4]. Different cultivars could be distinguished by elucidated metabolites, for instance, several organic and amino acids, carbohydrates, adenine, indole acetic acid (IAA), phenylpropanoids, flavonoids and glucosinolates [44]. We have used this technique to analyze the genetic variation for a range of (secondary) metabolites in B. rapa seedlings of a recently developed RIL population [45]. As the complete genome sequence of B. rapa is available [46], our analysis will simplify the identification of candidate genes that can be used for genetic modification or marker-assisted breeding for improved nutritional quality of B. rapa
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