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. 2016 Aug 3;11(8):e0160338.
doi: 10.1371/journal.pone.0160338. eCollection 2016.

Transcriptome Analysis of Storage Roots and Fibrous Roots of the Traditional Medicinal Herb Callerya speciosa (Champ.) ScHot

Li Xu  1   2 , Jiabin Wang  1   2 , Ming Lei  1   2 , Li Li  1   2 , Yunliu Fu  1   2 , Zhunian Wang  1   2 , Mengfei Ao  1   2 , Zhiying Li  1   2
Affiliations

Transcriptome Analysis of Storage Roots and Fibrous Roots of the Traditional Medicinal Herb Callerya speciosa (Champ.) ScHot

Li Xu et al. PLoS One. .

Abstract

Callerya speciosa (Champ.) ScHot is a woody perennial plant in Fabaceae, the roots of which are used medicinally. The storage roots of C. speciosa are derived from fibrous roots, but not all fibrous roots can develop into storage roots. To detect key genes involved in storage roots formation, we performed Illumina sequencing of the C. speciosa storage roots and fibrous roots. De novo assembly resulted in 161,926 unigenes, which were subsequently annotated by BLAST, GO and KEGG analyses. After expression profiling, 4538 differentially expressed genes were identified. The KEGG pathway enrichment analysis revealed changes in the biosynthesis of cytokinin, phenylpropanoid, starch, sucrose, flavone and other secondary metabolites. Transcription factor-related differentially expressed genes (DEGs) were also identified, including such gene families as GRAS, COL, MIKC, ERF, LBD, and NAC. The DEGs related to light signaling, starch, sugar, photohormones and cell wall-loosening might be involved in the formation of storage roots. This study provides the first transcriptome profiling of C. speciosa roots, data that will facilitate future research of root development and metabolites with medicinal value as well as the breeding of C. speciosa.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Summary of BLASTx results for the NR database.
(A) E-value distribution of unigenes with BLAST hits in NR; (B) Species-based distribution of unigenes with BLAST hits in NR.
Fig 2
Fig 2. GO classification of unigenes.
The number and percent of unigenes assigned to each GO category were provided in vertical axis.
Fig 3
Fig 3. Summary of KEGG annotation of unigenes.
(A) Number of unigenes involved in sub-pathways of carbohydrate metabolism. (B) Number of unigenes involved in sub-pathways of metabolism of other metabolites. (C) Number of unigenes involved in sub-pathways of metabolic pathway.
Fig 4
Fig 4. KEGG enrichment analysis of DEGs.
The enriched kEGG pathways were with a q-value≤0.05. Enrichment factor: the ratio between the number of DEGs and all unigenes enriched in a particular pathway.
Fig 5
Fig 5. Summary of DEGs related to transcription factors.
(A) Up-regulated unigenes related to transcription factors. (B) Down-regulated unigenes related to transcription factors.
Fig 6
Fig 6. qRT-PCR validation of selected DEGs.
SR, relative expression level of SR DEGs; FR, relative expression level of FR DEGs.
See this image and copyright information in PMC

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