Identification of Terpene-Related Biosynthetic Gene Clusters in Tobacco through Computational-Based Genomic, Transcriptomic, and Metabolic Analyses

Terpenes and terpenoids contribute aroma flavor that influence consumer preferences in selecting plant-based products. Computational identification of biosynthetic gene clusters (BGCs) plants can pave the way for future genetic engineering. Using integrative genomic, transcriptomic, metabolic pathway annotation analyses, 35 BGCs were identified tobacco with high confidence. Among identified, 7 classified as terpene biosynthesis-related BGCs. Two found on C13 C14 chromosomes belonged to saccharide-terpene classes only 93 Mb 189 Kb apart, respectively. Other have lengths ranging from 120 (Cluster 9) 1.6 18). Each cluster contained five 21) twenty genes 32), number synthase present also varied one (Clusters 18 eight 32). Gene expression profiling using diurnal topping transcriptome datasets co-expressing within modules varying levels among represented by normalized enrichment score measured each module. The positions pinpointed these computational analyses will allow more efficient modifications specific development tobacco-based products improved flavor.