Large-scale metabolomic landscape of edible maize reveals convergent changes in metabolite differentiation and facilitates its breeding improvement

Edible maize is an important food crop, providing energy and nutrients to meet human health and nutritional requirements. However, how environmental pressures and human activity have shaped the edible maize metabolome remains unclear. In this study, we collected 452 diverse edible maize accessions worldwide, comprising waxy, sweet, and field maize. A total of 3,020 non-redundant metabolites, including 802 annotated metabolites, were identified by a two-step optimized approach, which generated the most comprehensive annotated metabolites dataset in plants to date. Although specific metabolite differentiation was detected in Field-Sweet and Field-Waxy differentiations, convergent metabolite differentiation was the dominant differentiation pattern. We identified hub genes in all metabolite classes by mGWAS hotspot analysis. A total of 17 and 15 hub genes were selected as the key differentiation genes for flavonoids and lipids, respectively. Surprisingly, almost all of these genes were under diversifying selection, which indicated diversifying selection was the main genetic mechanism of convergent metabolic differentiation. Furthermore, the genetic and molecular studies reveal the roles and diversifying selection genetic mechanisms of ZmGPAT11 in convergent metabolite differentiation in lipid pathway. Based on our research, we established the first edible maize metabolome database, EMMDB (www.maizemdb.site/home/). We successfully applied EMMDB for precision improvement of nutritional and flavor traits, and an elite inbred line 6644_2 was bred with greatly improved in contents of flavonoids, lysophosphatidylcholines, lysophosphatidylethanolamines, and vitamins. These findings provide insights into the underlying genetic mechanisms of edible maize metabolite differentiation and provide a database for the breeding improvement of edible maize flavor and nutritional traits by metabolome precision design.