Deep transcriptome and metabolome analysis to dissect untapped spatial dynamics of specialized metabolism in Saussurea costus (Falc.) Lipsch.

Saussurea costus (Falc.) is an endangered medicinal plant possessing diverse phytochemical compounds with clinical significance and used to treat numerous human ailments. Despite the source of enriched phytochemicals, molecular insights into spatialized metabolism are poorly understood in S. costus. This study investigated the dynamics of organ-specific secondary metabolite biosynthesis using deep transcriptome sequencing and high-throughput UHPLC-QTOF based untargeted metabolomic profiling. A de novo assembly from quality reads fetched 59,725 transcripts with structural (53.02%) and functional (66.13%) annotations of non-redundant transcripts. Of the 7,683 predicted gene families, 3,211 were categorized as 'single gene families'. Interestingly, out of the 4,664 core gene families within the Asterids, 4,560 families were captured in S. costus. Organ-specific differential gene expression analysis revealed significant variations between leaves vs. stems (23,102 transcripts), leaves vs. roots (30,590 transcripts), and roots vs. stems (21,759 transcripts). Like-wise, putative metabolites (PMs) were recorded with significant differences in leaves vs. roots (250 PMs), leaves vs. stem (350 PMs), and roots vs. stem (107 PMs). The integrative transcriptomic and metabolomic analysis identified organ-specific differences in the accumulation of important metabolites, including secologanin, menthofuran, taraxerol, lupeol, acetyleugenol, scopoletin, costunolide, and dehydrocostus lactone. Furthermore, a global gene co-expression network (GCN) identified putative regulators controlling the expression of key target genes of secondary metabolite pathways including terpenoid, phenylpropanoid, and flavonoid. The comprehensive functionally relevant genomic resource created here provides beneficial insights for upscaling targeted metabolite biosynthesis through genetic engineering, and for expediting association mapping efforts to elucidate the casual genetic elements controlling specific bioactive metabolites.