十字花科
茶花
亚麻荠
胚乳
代谢组学
生物
转录组
芸苔属
代谢组
硫代葡萄糖苷
拟南芥
植物
拟南芥
蛋白质组学
生物技术
农学
遗传学
生物信息学
基因
作物
基因表达
突变体
作者
Léa Barreda,Céline Brosse,Stéphanie Boutet,Nicolas Klewko,Delphine De Vos,Tracy François,Boris Collet,Damaris Grain,Céline Boulard,Jean Chrisologue Totozafy,Benoı̂t Bernay,François Perreau,Loı̈c Lepiniec,Loïc Rajjou,Massimiliano Corso
摘要
SUMMARY Seeds of Brassicaceae produce a large diversity of beneficial and antinutritional specialized metabolites (SMs) that influence their quality and provide resistance to stresses. While SM distribution has been described in leaves and root tissues, limited information is available about their spatiotemporal accumulation in seeds. Camelina sativa (camelina) is an oilseed Brassicaceae cultivated for human and animal nutrition and for industrial uses. While we previously explored SM diversity and plasticity, no information is available about SM distribution and expression of related proteins and genes in camelina seeds. In this study, we used a multi‐omic approach, integrating untargeted metabolomics, proteomics, and transcriptomics to investigate the synthesis, modification, and degradation of SMs accumulated in camelina seed tissues (seed coat, endosperm, embryo) at six developmental and two germination stages. Metabolomic results showed distinct patterns of SMs and their related pathways, highlighting significant contrasts in seed composition and spatial distribution for the defense‐related and antinutritional glucosinolate (GSL) compounds among camelina, Arabidopsis thaliana , and Brassica napus , three closely related Brassicaceae species. Notably, thanks to metabolomic and proteomic/transcriptomic techniques the variation in GSL spatial distributions was primarily driven by differences in their structure (metabolomics data) and transport (transcriptomic and proteomic data) mechanisms. Long‐chain C8–C11 methylsulfinylalkyl GSLs were predominantly accumulated in the seed coat and endosperm, while mid‐ and short‐chain C3–C7 methylsulfinylalkyl GSLs were accumulated in the embryo. Characterizing the spatial dynamics of seed SMs provides valuable insights that can guide the development of crops with optimized distribution of beneficial and toxic metabolites, improving seed nutritional profiles.
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