Abstract
Specialized metabolite (SM) diversification is a core process to plants' adaptation to diverse ecological niches. Here, we implemented a computational mass spectrometry-based metabolomics approach to exploring SM diversification in tissues of 20 species covering Nicotiana phylogenetics sections. To markedly increase metabolite annotation, we created a large in silico fragmentation database, comprising >1 million structures, and scripts for connecting class prediction to consensus substructures. Together, the approach provides an unprecedented cartography of SM diversity and section-specific innovations in this genus. As a case study and in combination with nuclear magnetic resonance and mass spectrometry imaging, we explored the distribution of N-acylnornicotines, alkaloids predicted to be specific to Repandae allopolyploids, and revealed their prevalence in the genus, albeit at much lower magnitude, as well as a greater structural diversity than previously thought. Together, the data integration approaches provided here should act as a resource for future research in plant SM evolution.