Quantitative trait loci analysis of seed‐specialized metabolites reveals seed‐specific flavonols and differential regulation of glycoalkaloid content in tomato. (22nd July 2020) - Alseekh, Saleh; Ofner, Itai; Liu, Zhongyuan; Osorio, Sonia; Vallarino, Jose; Last, Robert L.; Zamir, Dani; Tohge, Takayuki; Fernie, Alisdair R.
SUMMARY: Given the potential health benefits (and adverse effects), of polyphenolic and steroidal glycoalkaloids in the diet there is a growing interest in fully elucidating the genetic control of their levels in foodstuffs. Here we carried out profiling of the specialized metabolites in the seeds of the Solanum pennellii introgression lines identifying 338 putative metabolite quantitative trait loci (mQTL) for flavonoids, steroidal glycoalkaloids and further specialized metabolites. Two putative mQTL for flavonols and one for steroidal glycoalkaloids were cross‐validated by evaluation of the metabolite content of recombinants harboring smaller introgression in the corresponding QTL interval or by analysis of lines from an independently derived backcross inbred line population. The steroidal glycoalkaloid mQTL was localized to a chromosomal region spanning 14 genes, including a previously defined steroidal glycoalkaloid gene cluster. The flavonoid mQTL was further validated via the use of transient and stable overexpression of the Solyc12g098600 and Solyc12g096870 genes, which encode seed‐specific uridine 5′‐diphosphate‐glycosyltransferases. The results are discussed in the context of our understanding of the accumulation of polyphenols and steroidal glycoalkaloids, and how this knowledge may be incorporated into breeding strategies aimed at improving nutritional aspects of plants as well as in fortifying them against abiotic stress. Significance Statement: Here we dissected the genetic architecture of tomato seed specialized metabolism, and we identified metabolic quantitative trait loci for seed‐specific flavonols and steroidal glycoalkaloids. In addition, we combined genetic, transcriptomic and metabolic data to identify cloned genes involved in flavonols and glycoalkaloids biosynthesis. Our data provide information for better understanding of the accumulation of flavonols and glycoalkaloids in tomato, which may be lead to improving nutritional aspects.