Root and shoot metabolic profiles of Arabidopsis and White cabbage: Predictive value for intra-specific variation?

In Brassicaceae metabolic profiles in aerial parts are known to vary intraspecifically, due to genotypic differences and environmental variation. However, it is unknown whether there is similar intraspecific variation in metabolic profiles of roots. We examined if metabolic profiles of roots of Arabidopsis and white cabbage showed similar intraspecific and environmental variation patterns as aerial parts. Second, we evaluate if genetic diversity becomes expressed in both shoots and roots. To address these questions we analyzed glucosinolate profiles from four white cabbage cultivars grown in three environments, as well as untargeted metabolomics profiles measured by LC-MS and GC-MS of nine Arabidopsis accessions grown in four environments. To assess genetic diversity we used an existing dataset with 149 single nucleotide polymorphism markers of the nine Arabidopsis accessions. Root glucosinolate profiles in white cabbage showed significant intraspecific variation; however, this variation was unrelated to that recorded in shoots. Root profiles were generally comparable between environments, whereas shoot profiles were highly plastic and responsive to changes in environmental conditions. Also for Arabidopsis, metabolic profiles of roots showed significant intraspecific variation that was unrelated to the variation in shoots. Shoot profiles in Arabidopsis also responded to changes in environment, although variation between accessions was larger than between environments. Shoot profiles among accessions have a small but significant correlation with genetic variation. Root profiles however were uncorrelated with genetic variation. We conclude that among Brassicaceae variation in shoot metabolic profiles is not indicative of metabolic variation in roots. Cabbage shoots and roots also differed in their responsiveness to environmental conditions. Metabolic differences cannot be used consistently as a reliable predictor for genetic variation between accessions