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 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 acylnornicotines, alkaloids predicted to be specific to 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.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10456844PMC
http://dx.doi.org/10.1126/sciadv.ade8984DOI Listing

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