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Plant Cell Physiol. 2013 May;54(5):697-710. doi: 10.1093/pcp/pct057. Epub 2013 Apr 14.

Glycyrrhiza uralensis transcriptome landscape and study of phytochemicals.

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RIKEN Center for Life Science Technologies (Division of Genomic Technologies), RIKEN Yokohama Institute, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama City, Kanagawa, 230-0045 Japan.


Medicinal and industrial properties of phytochemicals (e.g. glycyrrhizin) from the root of Glycyrrhiza uralensis (licorice plant) made it an attractive, multimillion-dollar trade item. Bioengineering is one of the solutions to overcome such high market demand and to protect plants from extinction. Unfortunately, limited genomic information on medicinal plants restricts their research and thus biosynthetic mechanisms of many important phytochemicals are still poorly understood. In this work we utilized the de novo (no reference genome sequence available) assembly of Illumina RNA-Seq data to study the transcriptome of the licorice plant. Our analysis is based on sequencing results of libraries constructed from samples belonging to different tissues (root and leaf) and collected in different seasons and from two distinct strains (low and high glycyrrhizin producers). We provide functional annotations and the expression profile of 43,882 assembled unigenes, which are suitable for various further studies. Here, we searched for G. uralensis-specific enzymes involved in isoflavonoid biosynthesis as well as elucidated putative cytochrome P450 enzymes and putative vacuolar saponin transporters involved in glycyrrhizin production in the licorice root. To disseminate the data and the analysis results, we constructed a publicly available G. uralensis database. This work will contribute to a better understanding of the biosynthetic pathways of secondary metabolites in licorice plants, and possibly in other medicinal plants, and will provide an important resource to further advance transcriptomic studies in legumes.


Database; De novo assembly; Glycyrrhiza uralensis; Phytochemicals; RNA-Seq; Transcriptome profiling

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