QT–GWAS: A novel method for unveiling biosynthetic loci affecting qualitative metabolic traits

• Published in: Molecular plant 2023-07, Vol.16 (7), p.1212-1227
• Main Authors: Brouckaert, Marlies, Peng, Meng, Höfer, René, El Houari, llias, Darrah, Chiarina, Storme, Véronique, Saeys, Yvan, Vanholme, Ruben, Goeminne, Geert, Timokhin, Vitaliy I., Ralph, John, Morreel, Kris, Boerjan, Wout
• Format: Article
• Language: English
• Subjects: Arabidopsis - genetics; Arabidopsis - metabolism; Genome-Wide Association Study; Metabolomics - methods; Phenotype; Polymorphism, Single Nucleotide; Quantitative Trait Loci - genetics
• ISSN: 1674-2052; 1752-9867
• DOI: 10.1016/j.molp.2023.06.004

Although the plant kingdom provides an enormous diversity of metabolites with potentially beneficial applications for humankind, a large fraction of these metabolites and their biosynthetic pathways remain unknown. Resolving metabolite structures and their biosynthetic pathways is key to gaining biological understanding and to allow metabolic engineering. In order to retrieve novel biosynthetic genes involved in specialized metabolism, we developed a novel untargeted method designated as qualitative trait GWAS (QT–GWAS) that subjects qualitative metabolic traits to a genome-wide association study, while the conventional metabolite GWAS (mGWAS) mainly considers the quantitative variation of metabolites. As a proof of the validity of QT-GWAS, 23 and 15 of the retrieved associations identified in Arabidopsis thaliana by QT-GWAS and mGWAS, respectively, were supported by previous research. Furthermore, seven gene-metabolite associations retrieved by QT–GWAS were confirmed in this study through reverse genetics combined with metabolomics and/or in vitro enzyme assays. As such, we established that CYTOCHROME P450 706A5 (CYP706A5) is involved in the biosynthesis of chroman derivatives, UDP-GLYCOSYLTRANSFERASE 76C3 (UGT76C3) is able to hexosylate guanine in vitro and in planta, and SULFOTRANSFERASE 202B1 (SULT202B1) catalyzes the sulfation of neolignans in vitro. Collectively, our study demonstrates that the untargeted QT–GWAS method can retrieve valid gene–metabolite associations at the level of enzyme-encoding genes, even new associations that cannot be found by the conventional mGWAS, providing a new approach for dissecting qualitative metabolic traits. A novel genome-wide association method to uncover biosynthetic loci underlying qualitative metabolic traits (designated as QT–GWAS) was developed and compared with a conventional quantitative metabolite GWAS (mGWAS). At least 23 of the associations identified by QT-GWAS were supported by previous research, and 7 associations involving three metabolic enzyme-encoding genes (CYP706A5, UGT76C3, and SULT202B1) were newly confirmed, illustrating the power of QT–GWAS.