Weighted Gene Co-expression Network Analysis of the Dioscin Rich Medicinal Plant Dioscorea nipponica

Abstract

Dioscorea contains critically important species which can be used as staple foods or sources of bioactive substances, including Dioscorea nipponica, which has been used to develop highly successful drugs to treat cardiovascular disease. Its major active ingredients are thought to be sterol compounds such as diosgenin, which has been called “medicinal gold” because of its valuable properties. However, reliance on naturally growing plants as a production system limits the potential use of D. nipponica, raising interest in engineering metabolic pathways to enhance the production of secondary metabolites. However, the biosynthetic pathway of diosgenin is still poorly understood, and D. nipponica is poorly characterized at a molecular level, hindering in-depth investigation. In the present work, the RNAs from five organs and seven methyl jasmonate treated D. nipponica rhizomes were sequenced using the Illumina high-throughput sequencing platform, yielding 52 gigabases of data, which were pooled and assembled into a reference transcriptome. Four hundred and eighty two genes were found to be highly expressed in the rhizomes, and these genes are mainly involved in stress response and transcriptional regulation. Based on their expression patterns, 36 genes were selected for further investigation as candidate genes involved in dioscin biosynthesis. Constructing co-expression networks based on significant changes in gene expression revealed 15 gene modules. Of these, four modules with properties correlating to dioscin regulation and biosynthesis, consisting of 4,665 genes in total, were selected for further functional investigation. These results improve our understanding of dioscin biosynthesis in this important medicinal plant and will help guide more intensive investigations.

A Novel AP2/ERF Transcription Factor CR1 Regulates the Accumulation of Vindoline and Serpentine in Catharanthus roseus

“…Therefore, it is critical to find new ways which could greatly facilitate TIAs production, such as genetic engineering. Nowadays, bioinformatics has been widely used in many medicinal plants such as Dioscorea nipponica ( Sun et al, 2017 ), Panax ginseng C. A. Meyer ( Zhang et al, 2017 ), Taxus chinensis ( Li et al, 2012 ; Meng et al, 2017 ), and Ginkgo biloba ( Lin et al, 2011 ; He et al, 2015 ). High-throughput data such as transcriptome, proteome and metabolome could help us to gain an insight into the process of secondary metabolism in many non-model plants.…”

Transcriptome analysis reveals the molecular mechanisms of the defense response to gray leaf spot disease in maize

“…Weighted Gene Co-expression Network Analysis (WGCNA) is a statistical tool for clustering transcripts that have a similar expression pattern across a group of samples [ 33 , 34 ]. WGCNA was originally developed to analyze microarray data but can also be used to examine RNA-Seq data [ 35 ]. The input data for the WGCNA were the normalized values for each transcript.…”

Proteomic Contributions to Medicinal Plant Research: From Plant Metabolism to Pharmacological Action

“…Genome sequences have been provided for some species [ 83 , 84 ], but as the basis for secondary metabolism studies, transcriptomic analysis is of growing importance ( Figure 1 ) [ 85 ]. RNA sequencing-based transcriptomic data are now available for medicinal plants such as Dendrobium officinale [ 86 ], Dioscorea nipponica [ 87 ], Ephedra sinica [ 88 ], L. japonica [ 89 ], and Polygonum minus [ 90 ]. Not only medicinal plants, but also other tropical plants, were studied by RNA sequencing-based transcriptomic analysis with an eye for understanding the unique characteristics of diverse plants such as pitcher plants [ 91 , 92 ].…”