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DC Field | Value | Language |
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dc.contributor.author | Priya, Piyush | - |
dc.contributor.author | Kumari, Sangita | - |
dc.contributor.author | Yadav, Gitanjali | - |
dc.date.accessioned | 2017-01-06T09:38:05Z | - |
dc.date.available | 2017-01-06T09:38:05Z | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | Indian J. Plant Physiol., 21(4): 569-575 | en_US |
dc.identifier.issn | 0974-0252 | - |
dc.identifier.uri | http://59.163.192.83:8080/jspui/handle/123456789/712 | - |
dc.description | Accepted date: 19 October 2016 | en_US |
dc.description.abstract | Plant essential oils are complex mixtures of volatile organic compounds, which play indispensable roles in communication, defense, and adaptive evolution. The complete chemical library produced by a plant is referred to as its terpenome. The potential biological information stored in essential oil composition data can provide an insight into the silent language of plants, as well as roles of terpene emissions in direct and indirect defense, and for playing a crucial role in adaptive evolution. In this work, we have attempted to measure the plant terpenome from a global perspective. One way of measuring the terpenome is to observe and record actual emissions in natural conditions, and this has been in practice for over a century through variously evolving methods of comprehensive GC–MS and HPLC. An alternative method is a knowledge-based prediction of the terpenome, and this method has gained popularity in recent years, with the advent of large-scale genome sequencing technologies. Over the past decade, our laboratory has been involved in compilation and investigation of the plant terpenome using both these methods and this has offered us the opportunity to compare and contrast data from actual and potential emissions, in order to better understand the terpenome and its roles in primary, secondary and adaptive metabolism. We have used emission data in conjunction with genomic data in order to understand how a plant creates the so-called final terpenome, specific to itself, and whether or not plants tap the complete potential for terpene biosynthesis at their disposal according to their genomes. For measuring actual emissions, we have used EssOilDB (the ESSential OIL DataBase), the largest contextual web resource for phytochemicals and for measuring the total plant potential for emissions, we have used TERZYME, an automated algorithm for identification and analysis of genes and proteins involved in isoprenoid biosynthesis. | en_US |
dc.description.sponsorship | Authors’ thanks are due to Director, NIPGR for encouragement, the SERB Women’s Excellence Award Grant of DBT, Govt of India, to GY for financial support, the Biotechnology Information System Network (BTISNET) program of Dept of Biotechnology (DBT), Govt of India, for computational resources, and the Council of Scientific and Industrial Research (CSIR) for Senior Research Fellowship (SRF) to SK and PP. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Springer | en_US |
dc.subject | Terpenome | en_US |
dc.subject | Phytochemicals | en_US |
dc.subject | EssOilDB | en_US |
dc.subject | Terzyme | en_US |
dc.subject | Essential oil emission | en_US |
dc.title | Quantification of the plant terpenome: predicted versus actual emission potentials | en_US |
dc.type | Article | en_US |
dc.identifier.officialurl | http://link.springer.com/article/10.1007/s40502-016-0256-x | en_US |
dc.identifier.doi | 10.1007/s40502-016-0256-x | en_US |
Appears in Collections: | Institutional Publications |
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Yadav G_2016_2.pdf Restricted Access | 954.69 kB | Adobe PDF | View/Open Request a copy |
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