Comprehensive characterization of a time-course transcriptional response induced by autotoxins in Panax ginseng using RNA-Seq

Abstract

Background: As a valuable medicinal plant, the yield of Panax ginseng is seriously affected by autotoxicity, which is a common phenomenon due to continuous cropping. However, the mechanism of autotoxicity in P. ginseng is still unknown.

Results: In total, high throughput sequencing of 18 RNA-Seq libraries produced 996,000,000 100-nt reads that were assembled into 72,732 contigs. Compared with control, 3697 and 2828 genes were significantly up- and down-regulated across different tissues and time points, respectively. Gene Ontology enrichment analysis showed that 'enzyme inhibitor activity', 'carboxylesterase activity', 'pectinesterase activity', 'centrosome cycle and duplication' and 'mitotic spindle elongation' were enriched for the up-regulated genes. Transcription factors including AP2s/ERFs, MYBs, and WRKYs were up-regulated in roots after benzoic acid treatment. Moreover, reactive oxygen species, peroxidases and superoxide dismutase contigs were up-regulated in roots after benzoic acid treatment. Physiological and biochemical indexes showed that the proline and malondialdehyde content were restored to lower levels at a later stage after benzoic acid treatment. Benzoic acid inhibited the root hair development in a dose-dependent manner, and several differential expressed genes potentially involved in hair development were identified. Several key contigs in the flavonoid and ginsenoside biosynthesis pathways were repressed. Finally, 58,518 alternative splicing (AS) events from 12,950 genes were found after benzoic acid treatment. Interestingly, contigs in the ginsenoside biosynthetic pathway underwent AS, providing useful information about post-transcriptional regulation in P. ginseng.

Conclusions: This study revealed the stress-response molecular mechanisms in P. ginseng induced by benzoic acid.

Fig. 1

Expression patterns of 28 randomly selected DEGs by qRT-PCR and the correlation between qRT-PCR and RNA-Seq. Fold changes of the transcript levels at different time points are shown. The average expression level in 0 DPT was set to 1. Error bars represent standard error. L, S and R represent leaves, stems and roots, respectively. The X-axis represents log2 fold change of the qRT-PCR. The Y-axis indicates the log2 value of the fold change from RNA-Seq. The size of each point is proportional to the log2 (FPKM) in 0 DPT. Leaves, stems and roots were represented by points with different color

Fig. 2

Representative time-course profile clusters. Representative profile clusters for roots, stems and leaves. For each time point and each gene, the log2 (FPKM + 1) is shown for the mean expression profile for each cluster

Fig. 3

Venn diagram illustrating the overlap of the DEGs

Fig. 4

Most significantly enriched GO terms (P < 0.05) of the DEGs. The most significant GO terms (P < 0.01) are presented graphically. The X-axis represents the log10 of the enrichment P value. The Y-axis indicates the number of DEGs in log2 value. The size of each point is proportional to the percentage (DEGs associated with GO terms/all genes associated with GO terms). a and b presents the enriched GO term for up-regulation genes based on biological procession and molecular function, respectively. c and d presents the enriched GO term for Down-regulation genes based on biological procession and molecular function, respectively

Fig. 5

Measurement of physiological and biochemical indexes of proline (a) and malondialdehyde (b)

Fig. 6

Plot of the 41 root hair related genes according to FPKM values

Fig. 7

Hierarchical clustering of differentially expressed TFs from 18 libraries. Hierarchical clustering of the DEGs among roots, stems and leaves at 0 DPT, 1 DPT, 3 DPT, 5 DPT, 7 DPT and 9 DPT using FPKM expression values from RNA-Seq. Each column represents an RNA-Seq library and each row represents a DEG. Different colors shown different expression levels, with green representing low expression levels and red representing high expression levels

Fig. 8

Validation of randomly selected AS events by RT-PCR