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Abstract
Plant-specialized metabolites, such as glyceollins and soyasaponins, play vital roles in adapting to dynamic environments and promoting human health. Glyceollins, induced phytoalexins derived from the isoflavonoid branch of the phenylpropanoid pathway, and soyasaponins, triterpenoid class compounds naturally abundant in legume species, have particular importance in responding to environmental stresses and contributing to sustainable human nutrition. However, the genetic basis of glyceollin induction and soyasaponin production, especially in wild crop species like wild soybean (G. soja), remains poorly studied. To bridge these knowledge gaps, our study focused on G. soja, which has abundant genetic diversity. Our objective was to unravel the genetic basis of glyceollin induction as well as phytochemical diversity with respect to soyasaponin variation. For insights into glyceollin induction, we employed a targeted metabolite-based genome-wide association (mGWA) approach utilizing 264 G. soja ecotypes and identified eight significant SNPs associated with glyceollin induction on chromosomes 3, 9, 13, 15, and 20. Among these, six genes near a significant SNP (ss715603454) on chromosome 9 formed two clusters, encoding enzymes of the glycosyltransferase class. We also discovered transcription factor genes, including MYB and WRKY, within the linkage disequilibrium of the significant SNPs on chromosome 9. Epistasis and strong selection signals were detected for four of the significant SNPs on chromosome 9, indicating their major evolutionary influence on glyceollin induction. For the genetic basis of phytochemical diversity with respect to soyasaponin biosynthesis, we utilized an untargeted metabolomics approach in an association panel of 190 G. soja ecotypes from diverse natural environments. Among the 874 detected metabolite peaks, we annotated 485 metabolites and identified 1155 SNPs significantly associated with 359 metabolites through a genome-wide association study. Clustering analysis revealed eight QTLs, named QTL-multiple metabolite clusters. Mining data within the linkage disequilibrium blocks of these QTLs led to the identification of 612 annotated genes. From this set, we selected 16 candidate genes relevant to the triterpenoid and phenylpropanoid-derived isoflavonoid biosynthetic pathways, with UDP-dependent glycosyltransferase (UGT) emerging as a promising candidate gene on chromosome 15. Sequence analysis of the UGT gene in 46 different wild soybean ecotypes revealed two haplotypes with three SNPs on exon-1 for 29 ecotypes, resulting in amino acid changes. These haplotypes were significantly associated with varying soyasaponin-producing ecotypes and exhibited notable expression level differences. We also observed the same two haplotypes in different cultivated G. max ecotypes. Incidentally, there was a higher frequency of the haplotype associated with relatively low soyasaponin II accumulation in 29 out of 34 G. max ecotypes. Our findings provide valuable insights into the genetic basis of glyceollin induction and phytochemical diversity, with a focus on soyasaponin variation. This knowledge will be a good resource for developing phytochemicals-fortified climate-resilient, high-value soybean crops employing metabolic engineering, ultimately benefiting plant and human health.