Identification of Terpene-Related Biosynthetic Gene Clusters in Tobacco through Computational-Based Genomic, Transcriptomic, and Metabolic Analyses
Terpenes and terpenoids contribute aroma and flavor that influence consumer preferences in selecting plant-based products. Computational identification of biosynthetic gene clusters (BGCs) in plants can pave the way for future biosynthetic genetic engineering. Using integrative genomic, transcriptom...
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MDPI AG
2023-06-01
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Series: | Agronomy |
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Online Access: | https://www.mdpi.com/2073-4395/13/6/1632 |
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author | Roel C. Rabara Chengalrayan Kudithipudi Michael P. Timko |
author_facet | Roel C. Rabara Chengalrayan Kudithipudi Michael P. Timko |
author_sort | Roel C. Rabara |
collection | DOAJ |
description | Terpenes and terpenoids contribute aroma and flavor that influence consumer preferences in selecting plant-based products. Computational identification of biosynthetic gene clusters (BGCs) in plants can pave the way for future biosynthetic genetic engineering. Using integrative genomic, transcriptomic, and metabolic pathway annotation analyses, 35 BGCs were identified in tobacco with high confidence. Among the 35 BGCs identified, 7 were classified as terpene biosynthesis-related BGCs. Two BGCs found on C13 and C14 chromosomes belonged to terpene and saccharide-terpene biosynthetic classes that were only 93 Mb and 189 Kb apart, respectively. Other clusters have lengths ranging from 120 Kb (Cluster 9) to 1.6 Mb (Cluster 18). Each cluster contained five (Cluster 21) to twenty genes (Cluster 32), and the number of terpene synthase genes present in the clusters also varied from one (Clusters 18 and 21) to eight (Cluster 32). Gene expression profiling using diurnal and topping transcriptome datasets identified co-expressing genes within modules and varying levels of expression among modules as represented by the normalized enrichment score measured in each module. The positions pinpointed from these computational analyses will allow for the more efficient modifications of specific genes and BGCs for the development of tobacco-based products with improved aroma and flavor. |
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institution | Directory Open Access Journal |
issn | 2073-4395 |
language | English |
last_indexed | 2024-03-11T02:52:10Z |
publishDate | 2023-06-01 |
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spelling | doaj.art-d93f09159d704b3c989407acac5ecc142023-11-18T08:55:55ZengMDPI AGAgronomy2073-43952023-06-01136163210.3390/agronomy13061632Identification of Terpene-Related Biosynthetic Gene Clusters in Tobacco through Computational-Based Genomic, Transcriptomic, and Metabolic AnalysesRoel C. Rabara0Chengalrayan Kudithipudi1Michael P. Timko2Department of Biology, University of Virginia, Charlottesville, VA 22903, USAAltria Client Services, Center for Research and Technology, Richmond, VA 23219, USADepartment of Biology, University of Virginia, Charlottesville, VA 22903, USATerpenes and terpenoids contribute aroma and flavor that influence consumer preferences in selecting plant-based products. Computational identification of biosynthetic gene clusters (BGCs) in plants can pave the way for future biosynthetic genetic engineering. Using integrative genomic, transcriptomic, and metabolic pathway annotation analyses, 35 BGCs were identified in tobacco with high confidence. Among the 35 BGCs identified, 7 were classified as terpene biosynthesis-related BGCs. Two BGCs found on C13 and C14 chromosomes belonged to terpene and saccharide-terpene biosynthetic classes that were only 93 Mb and 189 Kb apart, respectively. Other clusters have lengths ranging from 120 Kb (Cluster 9) to 1.6 Mb (Cluster 18). Each cluster contained five (Cluster 21) to twenty genes (Cluster 32), and the number of terpene synthase genes present in the clusters also varied from one (Clusters 18 and 21) to eight (Cluster 32). Gene expression profiling using diurnal and topping transcriptome datasets identified co-expressing genes within modules and varying levels of expression among modules as represented by the normalized enrichment score measured in each module. The positions pinpointed from these computational analyses will allow for the more efficient modifications of specific genes and BGCs for the development of tobacco-based products with improved aroma and flavor.https://www.mdpi.com/2073-4395/13/6/1632biosynthetic gene clusteringspecialized metabolitesterpene synthaseco-expressing genesspecialized metabolic pathwaystobacco |
spellingShingle | Roel C. Rabara Chengalrayan Kudithipudi Michael P. Timko Identification of Terpene-Related Biosynthetic Gene Clusters in Tobacco through Computational-Based Genomic, Transcriptomic, and Metabolic Analyses Agronomy biosynthetic gene clustering specialized metabolites terpene synthase co-expressing genes specialized metabolic pathways tobacco |
title | Identification of Terpene-Related Biosynthetic Gene Clusters in Tobacco through Computational-Based Genomic, Transcriptomic, and Metabolic Analyses |
title_full | Identification of Terpene-Related Biosynthetic Gene Clusters in Tobacco through Computational-Based Genomic, Transcriptomic, and Metabolic Analyses |
title_fullStr | Identification of Terpene-Related Biosynthetic Gene Clusters in Tobacco through Computational-Based Genomic, Transcriptomic, and Metabolic Analyses |
title_full_unstemmed | Identification of Terpene-Related Biosynthetic Gene Clusters in Tobacco through Computational-Based Genomic, Transcriptomic, and Metabolic Analyses |
title_short | Identification of Terpene-Related Biosynthetic Gene Clusters in Tobacco through Computational-Based Genomic, Transcriptomic, and Metabolic Analyses |
title_sort | identification of terpene related biosynthetic gene clusters in tobacco through computational based genomic transcriptomic and metabolic analyses |
topic | biosynthetic gene clustering specialized metabolites terpene synthase co-expressing genes specialized metabolic pathways tobacco |
url | https://www.mdpi.com/2073-4395/13/6/1632 |
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