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Journal of Plant Research

, Volume 132, Issue 3, pp 419–429 | Cite as

Comparative transcriptomic analysis reveal the regulation mechanism underlying MeJA-induced accumulation of alkaloids in Dendrobium officinale

  • Yue Chen
  • Yunzhu Wang
  • Ping Lyu
  • Liping Chen
  • Chenjia Shen
  • Chongbo SunEmail author
Regular Paper

Abstract

Dendrobium officinale is a traditional medicinal herb with a variety of bioactive components. Alkaloid is one of the major active ingredients of Dendrobium plants, and its immune regulatory effects have been well-studied. Although a number of genes involved in the biosynthetic pathway of alkaloids have been elucidated, the regulation mechanism underlying the methyl-jasmonate (MeJA)-induced accumulation of alkaloids in D. officinale is largely unknown. In our study, a total of 4,857 DEGs, including 2,943 up- and 1,932 down-regulated genes, were identified between the control and MeJA-treated groups. Kyoto Encyclopedia of Genes and Genomes annotation showed that a number of DEGs were associated with the putative alkaloid biosynthetic pathway in D. officinale. The main group of Dendrobium alkaloids are sesquiterpene alkaloids, which are the downstream products of mevalonate (MVA) and methylerythritol 4-phosphate (MEP) pathway. Several MVA and MEP pathway genes were significantly up-regulated by the MeJA treatment, suggesting an active precursor supply for the alkaloid biosynthesis under MeJA treatment. A number of MeJA-induced P450 family genes, aminotransferase genes and methyltransferase genes were identified, providing several important candidates to further elucidate the sesquiterpene alkaloid biosynthetic pathway of D. officinale. Furthermore, a large number of MeJA-induced transcript factor encoding genes were identified, suggesting a complex genetic network affecting the sesquiterpene alkaloid metabolism in D. officinale. Our data aids to reveal the regulation mechanism underlying the MeJA-induced accumulation of sesquiterpene alkaloids in D. officinale.

Keywords

Dendrobium Alkaloid Differential expressed genes MVA and MEP pathways P450 family 

Introduction

Orchidaceae is one of the largest families of flowering plants, with over 250,000 species (Leitch et al. 2009). The Dendrobium genus plants are well prized folk medicinal and ornamental gardening herbs with about 1,450 species (Chen et al. 2017; Lu et al. 2012; Wu et al. 2014). Several previous works have provided increasing knowledge on the constituents of various Dendrobium species (Cheng et al. 2013; Ng et al. 2012). The major active ingredients of Dendrobium plants are alkaloids, polysaccharides, phenols, terpenes, flavonoids, coumarins, amino acids, and various trace mineral elements (Zhang et al. 2016).

Among these constituents, alkaloids are the most important medicinal components in Dendrobium plants, and their antipyretic, eye-benefitting and immune regulatory effects have been studied (Li et al. 2011). In the last 50 years, many alkaloids have been isolated and characterized in Dendrobium plants. For example, two alkaloids, N-cis- and N-trans-cinnamoyl-norcuskhygrine, were isolated from D. chrysanthum Wall. (Ekevag et al. 1973). Two novel alkaloids, dendrobine and dendronobiline A, were determined using pressurized liquid extraction and ultra performance liquid chromatography (Xu et al. 2010). (±)-Homocrepidine A, a piperidine derivative, has been isolated from D. crepidatum Lindl. & Paxton (Hu et al. 2016). Although the composition of alkaloids from Dendrobium is very complex, sesquiterpene alkaloid dendrobine has been treated as the quality standard of Dendrobium plants (Kreis and Carreira 2012; Li et al. 2017).

Several previous studies have been focused on the biosynthetic pathway of alkaloids in Dendrobium plants. Transcriptomic analysis of D. officinale Kimura & Migo revealed several putative alkaloid biosynthetic genes and genetic markers, including 25 alkaloid backbone biosynthesis genes, P450 genes, aminotransferase genes, methyltransferase genes, multidrug resistance protein transporter genes and transcription factor genes (Guo et al. 2013). Molecular finger-printings of D. nobile Lindl. along with the estimation of total alkaloid contents were performed using a number of inter-simple sequence repeat and DAMD markers (Bhattacharyya et al. 2015). Taking advantage of transcriptomes from four organs of D. officinale, genes associated with the putative upstream elements of alkaloid biosynthetic pathway were identified (Shen et al. 2017). Recently, a large number of genes involved in the fungus infection-induced alkaloid accumulation also have been identified by transcriptomic analysis (Li et al. 2017).

The phytohormone methyl jasmonate (MeJA) was frequently applied to enhance the biosynthesis of secondary metabolites in medical plants (Zhan et al. 2018). MeJA functions as a signaling molecule in elicitor-induced biosynthesis of various secondary metabolites, particular in alkaloids (Zhang et al. 2018). MeJA was also applied to enhance the accumulation of active ingredients in Dendrobium plants (Wang et al. 2016). For example, application of exogenous MeJA could enhance the accumulation of polysaccharides in D. officinale (Yuan et al. 2016). Metabolic profiling of D. officinale showed that protocorm-like bodies with a high-yielding production of alkaloids were obtained by the optimization of precursors and MeJA treatments (Jiao et al. 2018). However, the regulation mechanism underlying MeJA-induced accumulation of sesquiterpene alkaloids in D. officinale is largely unknown. In the present study, a number of differential expressed genes were identified to elucidate the regulation mechanism underlying the MeJA-induced accumulation of sesquiterpene alkaloids in D. officinale.

Materials and methods

Plant materials and total RNA isolation

D. officinale seedlings were obtained from tissue culture. All plants were grown in a greenhouse of Zhejiang Academy of Agriculture Science, Hangzhou, China, at a temperature of 25 ± 1 °C with a light/dark cycle of 12/12 h and 60–70% relative humidity. The leaves of 6-month-old D. officinale sprayed with 100 µM of MeJA (in ethanol solvent) for 24 h were harvested as the treatment group, and the leaves of 6-month-old D. officinale seedlings sprayed with ethanol solvent without MeJA were harvested as the control group. One-half of each sample was frozen at − 80 °C for RNA extraction, and the other half was dried at 40 °C for the determination of alkaloids. There were three biological replicates for each group.

RNA isolation and cDNA libraries construction

Total RNAs were isolated from the leaves using Total RNA Purification Kit, TRK1001 according to the manufacturer’s protocol (LC Science, Houston, TX) and quantified using Bioanalyzer 2100 and RNA 6000 Nano LabChip Kit (Agilent, CA, USA). Approximately 10 µg of total RNAs representing each sample were subjected to isolate Poly (A) mRNA with poly (T) oligo-attached magnetic beads (Invitrogen, CA, USA). After purification, the RNA fractions were fragmented into small pieces using divalent cation under an elevated temperature. Then, the cleaved RNA fragments were reverse-transcribed to create the final cDNA library using mRNA-Seq sample preparation kit in accordance with the protocol (Illumina, San Diego, USA). Then, we performed the paired-end sequencing on an Illumina Hiseq 4000 (LC-bio, Hangzhou, China) following the vendor’s recommended protocol (Yu et al. 2017).

De novo assembly, unigene annotation and functional classification

Firstly, software Cutadapt and perl scripts in house were used to remove the reads containing adaptor contamination, low quality bases and undetermined bases. Then, the sequence quality parameters, including Q20, Q30 and GC content of the clean data, were verified using FastQC program (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). The following analyses were based on the high quality clean data. De novo assembly of the transcriptome was performed with Trinity 2.4.0 (Grabherr et al. 2011). Trinity groups transcripts into clusters based on shared sequences. Such a transcript cluster is very loosely referred to a ‘gene’. The longest transcript in each cluster was chosen as the ‘Unigene’. The raw sequence data has been submitted to the NCBI Short Read Archive with accession number GSE124762.

All assembled Unigenes were aligned against the non-redundant (Nr) (http://www.ncbi.nlm.nih.gov/), Gene Ontology (GO) (http://www.geneontology.org), SwissProt (http://www.expasy.ch/sprot/), Kyoto Encyclopedia of Genes and Genomes (KEGG) (http://www.genome.jp/kegg/) and eggNOG (http://eggnogdb.embl.de/) databases with a threshold of E value < 0.00001.

Differentially expressed gene (DEGs) analysis

Program Salmon was used to analyze the expression level for unigenes by calculating TPM values (Patro et al. 2017). The DEGs were selected with log2 (fold change) > 1 or log2 (fold change) < − 1 and with statistical significance (P value < 0.05) by R package edgeR. Next, GO and KEGG enrichment analysis were again performed on the DEGs by perl scripts in house.

Phylogenetic tree building

Multiple sequence alignments were performed with the predicted protein sequences of P450 family using the ClustalW software with default parameters. The alignments were visualized subsequently by GeneDoc (http://www.nrbsc.org/gfx/genedoc/), and a phylogenetic tree constructed with aligned 59 P450 protein sequences using MEGA6.1 (http://www.megasoftware.net/) employing the neighbor-joining method.

Determination of the alkaloids in D. officinale

For alkaloids extraction, three samples from two groups were soaked five times with 90% ethanol for 12 h, and then were heated to boiling for 2 h. The alcohol extract was concentrated with nonalcoholic, and then was dissolved with 5% hydrochloric acid. After leaching, aqueous acid solution was extracted three times by petroleum, and the pH value was adjusted to 10 using strong aqueous ammonia. The alkaline solution was extracted twice with chloroform, concentrated, and the total alkaloids were obtained.

Real-time PCR validation

To confirm the expression changes of MeJA responsive genes, a DoACTIN gene was used as an internal reference to calculate relative fold changes basing on the comparative cycle threshold (2−ΔΔCt) values. The qRT-PCR procedure was as follows: 1 µL of a 1/10 dilution of cDNA was added to 5 µL of 2 × SYBR® Green buffer, 0.1 µM of each primer and ddH2O to a final volume of 10 µL.

Statistical analysis

Differences between values were calculated using one-way analysis of variance (ANOVA) with Student’s t test at P < 0.05 in Excel software. All expression analysis was performed for three biological repeats and figures show the average values of three repeats.

Results

Determination of total alkaloids in D. officinale

To provide a scientific basis for the MeJA induced accumulation of total alkaloids in D. officinale, contents of total alkaloids were determined under both the control and MeJA treatments. The content of alkaloids was significantly induced from 0.55 to 1.22 mg L−1 by the MeJA treatment (Fig. 1), suggesting an efficient role of MeJA in the accumulation of alkaloids in D. officinale.

Fig. 1

Determination of total alkaloid contents in D. officinale under the control and MeJA treatments. The significantly changes in total alkaloid contents between the MeJA and control treatments were indicated by “*”. The scale bars indicated standard deviation

Sequencing and unigene annotation

Three independent RNA-seq libraries were constructed using the RNA samples from the control and MeJA treated groups, respectively. In our study, a large number of raw reads, 97.96% of which were valid reads, were obtained. A total of 269,267,462 clean reads were integrated and assembled into 148,692 transcripts with a mean length of 754 bp and into 60,597 genes with a mean length of 527 bp (Table S1). The size distributions of transcripts and genes were analyzed. For transcripts, 14.44% of the transcripts were > 2,000 bp in length, half of the transcripts (49.8%) were between 500 ~ 2,000 bp in length and 35.7% of the transcripts were < 500 bp in length. For genes, 11.72% of the genes were > 2,000 bp in length, 40.2% of the genes were between 500 ~ 2,000 bp in length and 48.1% of the genes were < 500 bp in length (Fig. S2).

For annotation, all identified genes were searched against various databases. In detail, 22,933 genes were identified in the GO database, 12,877 genes were identified in the KEGG database, 21,527 genes were identified in the Pfam database, 18,804 genes were identified in the Swissprot database, 27,906 genes were identified in the eggNOG database, and 29,229 genes were annotated in the NR database (Fig. S3).

GO and KEGG classification of the genes in D. officinale

In D. officinale, most of the genes could be assigned into a large number of GO functional terms belonging to three major categories: biological process, cellular component and molecular function (Table S2). For the biological process category, ‘biological process’, ‘regulation of transcription’, and ‘transcription’ were the dominant terms; for the cellular component category, the largest terms were ‘nucleus’, ‘cytoplasm’ and ‘plasma membrane’; and for the molecular function category, a large percentage of genes were related to ‘molecular function’, ‘protein binding’ and ‘ATP binding’ (Fig. S3).

Some of the genes could be mapped onto canonical KEGG pathways. In total, 12,877 genes were grouped into 19 secondary level KEGG pathways (Table S3). Most of the pathways were grouped into the ‘Metabolism’ category. For example, 1,838 genes were classified into the ‘carbohydrate metabolism’ pathway, 989 genes were classified into the ‘lipid metabolism’ pathway, 876 genes were classified into the ‘amino acid metabolism’ pathway, and 716 genes were classified into the ‘biosynthesis of other secondary metabolism’ pathway (Fig. 2).

Fig. 2

Illumina sequencing and unigene annotation. The number of unigenes annotated by the KEGG database were showed. All the unigenes were classified into five major categories, including ‘Environmental Information Processing’, ‘Metabolism’, ‘Cellular Processes’, ‘Genetic Information processing’ and ‘Organismal Systems’

Identification and classification of the DEGs between the control and MeJA treated groups

To screen the DEGs between the control and MeJA treated groups, the read density for each gene was calculated. A significance analysis of the DEGs was performed and visualized using a volcano plot (Fig. 3a). A total of 4,857 DEGs, including 2,943 up- and 1,932 down-regulated genes, were identified between the control and MeJA treated groups (Figs. 3b, 4).

Fig. 3

Transcriptional variation between the control and MeJA treated samples of D. officinale. a Significance analysis of all DEGs between the control and MeJA treated samples by a volcanoplot. b The numbers of up-regulated genes and down-regulated genes under MeJA treatment compared to the control. c KEGG enrichment analysis of the DEGs variation between the control and MeJA treated samples of D. officinale

Fig. 4

Transcript abundance changes of the MVA and MEP pathway-related genes. a Overview of MVA and MEP pathways in D. officinale. Enzyme abbreviations are as follows. AACT acetyl CoA acetyltransferase, HMGS hydroxymethylglutaryl-CoA synthase, HMGR 3-hydroxy-3-methylglutaryl CoA reductase, MK mevalonate kinase, PMK phosphomevalonate kinase, MPDC mevalonate diphosphosphate decarboxylase, DXS 1-deoxy-d-xylulose-5-phosphate synthase, DXR 1-deoxy-d-xylulose-5-phosphate reductoisomerase, MCT 2-C-methyl-d-erythritol4-phosphate cytidylyl transferase, CMK 4-diphosphocytidyl-2-C-methyl-d-erythritol kinase, MDS 2-C-methyl-d-erythritol 2,4-cyclodiphosphate synthase, HDS (E)-4-hydroxy-3-methylbut-2-enyl-diphosphate synthase, HDR 4-hydroxy-3-methylbut-2-enyl diphosphate reductase; and FPPS famesyl diphosphase synthase. b Expression changes of the genes associated with MVA and MEP pathway under MeJA treatment. Red indicates up-regulated genes and blue indicates down-regulated genes

GO enrichment analysis showed that 2,876 genes were assigned into at least one GO term (Table S4). The most enriched GO terms were the ‘transcription factor activity’ term (237 genes), the ‘extracellular region’ term (205 genes), the ‘cell wall’ term (95 genes), the ‘sequence-specific DNA binding’ term (93 genes), the ‘dioxygenase activity’ term (70 genes) and the ‘response to wounding’ term (63 genes) (Fig. S4). Furthermore, 1,672 genes were assigned into various KEGG metabolic pathways (Table S5). Enrichment analysis showed that the significantly enriched KEGG pathways were ‘phenylpropanoid biosynthesis’ (map00940), ‘flavonoid biosynthesis’ (map00941), ‘stilbenoid, diarylheptanoid and gingerol biosynthesis’ (map00945), ‘plant hormone signal transduction’ (map04075) and ‘glutathione metabolism’ (map00480) (Fig. 3c).

Putative alkaloid biosynthetic pathway in D. officinale

According to their structural features, dendrobine might be of sesquiterpene origin (Li et al. 2017; Lynch et al. 1988). In plants, the upstream biosynthetic pathways for the sesquiterpene intermediate products were well-studied and conserved (Li et al. 2017). The main group of dendrobium alkaloids are sesquiterpene alkaloids, which are the downstream products of MVA. In our study, most of the key enzymes involved in the MVA pathway were identified. In total, 11 genes encoding six enzymes were mapped onto the MVA pathway, including acetyl CoA acetyltransferase (AACT), hydroxymethylglutaryl-CoA synthase (HMGS), 3-hydroxy-3-methylglutaryl CoA reductase (HMGR), mevalonate kinase (MK), phosphomevalonate kinase (PMK), and mevalonate diphosphosphate decarboxylase (MPDC). In addition, the MEP pathway would be a supplemental provider of isoprene units in the biosynthesis of dendrobine. In total, 11 genes encoding nine enzymes were mapped onto the MEP pathway, including: 1-deoxy-d-xylulose-5-phosphate synthase (DXS), 1-deoxy-d-xylulose-5-phosphate reductoisomerase (DXR), 2-C-methyl-d-erythritol4-phosphate cytidylyl transferase (MCT), 4-diphosphocytidyl-2-C-methyl-d-erythritol kinase (CMK),: 2-C-methyl-d-erythritol 2,4-cyclodiphosphate synthase (MDS), (E)-4-hydroxy-3-methylbut-2-enyl-diphosphate synthase (HDS), and 4-hydroxy-3-methylbut-2-enyl diphosphate reductase (HDR) (Fig. 3a). The expression levels of these genes are shown in Fig. 3b.

Identification of the P450 superfamily, methyltransferase and aminotransferase genes in D. officinale

In our study, 59 putative P450 superfamily members with full-length cDNA sequences were identified (Table S6). Phylogenetic analysis showed that all the identified P450 genes were grouped into 12 subfamilies basing on the nomenclature of the P450 superfamily. In detail, the biggest subfamily (subfamily 72) consisted of 11 P450 genes, the second largest subfamily (subfamilies 81) consisted of nine P450 genes, and the smallest subfamilies (subfamilies 734, 97 and 736) consisted of only two P450 genes (Fig. 5a). The expression pattern of these P450 genes was also analyzed. Most of the P450 genes belonging to the subfamilies 88 and 94 (Class I) and the subfamily 81 (Class II) were up-regulated by the MeJA treatment (Fig. 5b).

Fig. 5

Expression pattern of the genes involved in the biosynthesis of alkaloids. a Phylogenetic analysis of all P450 genes identified from the D. officinale transcriptomes. Branches in different background colors indicated different subfamilies. b Expression pattern of the P450 family genes under MeJA treatment. c Expression pattern of the methyltransferase genes under MeJA treatment. d Expression pattern of the aminotransferase genes under MeJA treatment. Red indicates up-regulated genes and blue indicates down-regulated genes

A putative pathway up to dendrobine together with P450s, aminotransferases, and methyltransferases has been provided by Li et al. (Li et al. 2017). Based on the putative pathway, a number of methyltransferase genes and aminotransferase genes were also identified in D. officinale. Clustering analysis showed that about half of the methyltransferase genes and most of the aminotransferase genes were induced by the MeJA treatment (Fig. 5c, d).

Identification of transcription factors (TFs) in D. officinale

Various TFs were reported to participate in the biosynthesis of secondary metabolites in plants. In our study, 570 putative TF genes belonging to 18 major TF families were identified in D. officinale (Table 1). The largest number of TFs were included in the NAC family (61 genes), the MYB family (95 genes), and the bHLH family (93 genes). Among these TF genes, a large number of TF genes, such as 14 NAC genes, 26 WRKY genes, 16 bHLH genes, 17 MYB genes and 8 MYB-like genes, were up-regulated under the MeJA treatment.

Table 1

Transcription factor families identified in the D. officinale stem transcriptome dataset

putative transcription factor family

No. of nuique transcripts

Up-regulated

Down-regulated

putative transcription factor family

No. of nuique transcripts

Up-regulated

Down-regulated

C2H2

3

0

0

MYB-related

31

8

6

C3H

1

0

0

SBP

9

0

1

BHLH

93

16

7

GRAS

15

1

1

Homeobox

69

8

3

HSF

7

6

0

bZIP

23

0

8

MADS

25

1

0

WRKY

71

26

2

PHD

15

0

0

ARF

13

1

3

TCP

25

0

4

MYB

95

17

7

G2-like

11

0

0

NAC

61

14

0

GBF

3

0

0

Validation of the expression changes of several key genes

A qRT-PCR assay with independent samples from the control and MeJA treatments was applied to verify the expression changes of several key genes involved in the alkaloid biosynthetic pathway. In total, 24 genes, including five MVA pathway genes, three MEP pathway genes, four P450 family genes, four methyltransferase genes, four aminotransferase genes, and four TF gens, were selected to confirm the RNA-seq data. The expression levels of these selected genes were basically consistent with the RNA-seq results (Fig. 6, Table S7).

Fig. 6

The related expression levels of the key genes involved in the MeJA-induced accumulation of alkaloids in D. officinale. The significantly changes in expression levels between the MeJA and control treatments were indicated by “*”. The scale bars indicated standard deviation

Discussion

As an important traditional herb in China, the soluble extraction from D. officinale displayed strong immune modulatory activities (Guo et al. 2013). Alkaloids are the major active ingredients of D. officinale with strong anti-oxidative effects (Xu et al. 2017b). However, the regulation mechanism underlying the MeJA-induced accumulation of alkaloids in D. officinale is largely unknown.

In D. officinale, a number of transcriptomic analyses have been performed for different goals, such as prediction of putative metabolic pathway (Guo et al. 2013), identification of functional genes (Chen et al. 2017; He et al. 2015; Zhang et al. 2016), uncovering environmental responses, and development of genetic markers (Xu et al. 2017a). In our study, 60,597 D. officinale genes were identified and annotated. The number of genes identified by our transcriptome was greater than what was identified by Guo’s study (36,407 unigenes), and similar to what was identified by Wu’s study (79,256 unigenes) (Guo et al. 2013; Wu et al. 2016). KEGG analysis revealed that a large number of genes were associated with primary and secondary metabolisms, which allowed us to explore the regulation mechanism involved in the alkaloid biosynthesis in D. officinale.

Sesquiterpenes are generally derived from farnesyl diphospate (FPP) that is provided by the MVA and MEP pathway in plants (Schwab and Wust 2015). Previous studies have identified a number of genes involved in the putative dendrobine biosynthetic pathway (Li et al. 2017; Rai et al. 2013; Yuan et al. 2018). Most of the MVA and MEP pathway genes were significantly up-regulated by the MeJA treatment. In Salvia sclarea, high correlations between the contents of bioactive abietane diterpenes and the transcripts of DXS and DXR were observed (Vaccaro et al. 2017). Several terpenoids, such as linalool, geraniol, and phenylethyl alcohol, were increased in MeJA-treated tea leaves, and the expression levels of DXS and HDR genes were also largely induced by the MeJA treatment (Shi et al. 2015). In Hevea brasiliensis, a key gene (HMGR) involved in 2-C-methyl-d-erythritol 4-phosphate in MVA pathway was up-regulated by MeJA treatment (Liu et al. 2018).

Our data suggested that well supplied precursors for dendrobine biosynthesis provided a reasonable explanation for the MeJA induced accumulation of alkaloids in D. officinale.

Recently, several RNA-seq analyses have been performed by different research groups. By Shen’s group, a tissue-specific transcriptomic analysis identified 49 full-length P450 genes (Shen et al. 2017). In our study, 59 P450 genes were identified, providing more candidates involved in the dendrobine biosynthesis. In 2017, another transcriptome analysis showed that a number of MVA and MEP pathway genes were involved in fungus-induced dendrobine biosynthesis in D. nobile (Li et al. 2017). In D. officinale, half of the MVA and MEP pathway genes were significantly up-regulated by the MeJA treatment.

So far, a putative pathway to dendrobine, involving a series of cytochrome P450s, methyltransferase, and aminotransferases, has been investigated by Li et al. (Li et al. 2017). Screening MeJA-induced P450 genes is an effective method to identify the novel candidates involved in the active ingredients biosynthesis. In D. huoshanense, 229 unigenes were identified as putative P450 superfamily members, and the majority were CYP71 family members, followed by CYP3A family members and CYP4 family members (Yuan et al. 2018). In our study, only 59 putative P450 genes belonging to 12 subfamilies were identified, and the majority were CYP72 and CYP81 families. CYP71 family is likely to be involved in hydroxylation steps of alkaloid biosynthesis in D. huoshanense (Yuan et al. 2018). However, most CYP71 members in D. officinale were down-regulated by the MeJA treatment. Previous studies showed that P450 family CYP81 was involved in fenoxaprop-P-ethyl resistance in Alopecurus japonicus (Chen et al. 2018). Our data might suggest a novel role of CYP81 family in accumulation of alkaloids. Interestingly, the biosynthesis of the plant hormone jasmonate-isoleucine, which is inactivated JA, was mediated by CYP94 family enzymes (Aubert et al. 2015). Moreover, CYP94-enzymes might play an essential role for JA response under various stresses (Bruckhoff et al. 2016; Kurotani et al. 2015). In our study, most of the P450 genes belonging to the subfamilies 94 were largely up-regulated by the MeJA treatment, suggesting their important roles in the MeJA-induced accumulation of alkaloids. Moreover, aminotransferases and methyltransferases might be required for the consummating chemical structure of alkaloids (Bedewitz et al. 2014; Li et al. 2017). In our study, several MeJA-induced aminotransferase genes and methyltransferase genes were identified. These genes might be important candidates for further identification of the enzymes in alkaloid biosynthetic pathway of D. officinale.

Increasing evidences showed that various TF families, such as the bHLH, ERF, and WRKY families, are involved in different steps of the alkaloid biosynthesis pathways (Yamada and Sato 2013). For example, MeJA-induced alkaloid biosynthesis in C. Roseus cultures was controlled by the expressions of various TF genes, including ORCA, ZCT, GBF, MYC2, and WRKY1 (Goklany et al. 2013). However, no ORCA or ZCT genes have been identified in our study. This difference may reflect the presence of species-specific regulations of alkaloids in plants. To date, the roles of NAC family TFs in alkaloid biosynthesis are largely unknown. However, increasing studies revealed the roles of NAC family members in other secondary metabolisms. For example, overexpression of NAC03 in Norway spruce leads to reduced flavonol biosynthesis (Dalman et al. 2017). In Arabidopsis, a NAC domain protein, XND1, negatively regulates lignocelluloses synthesis in xylem (Zhao et al. 2008). In our study, 14 NAC genes were significantly up-regulated by the MeJA treatment, suggesting their potential roles in the MeJA-induced alkaloid biosynthesis in D. officinale. Additionally, several bHLH family TFs, such as CjbHLH1, play central roles in the regulation of alkaloid biosynthesis (Yamada et al. 2011). Two bZIP TFs, CrGBF1 and CrGBF2, take part in the expression regulation of several key genes involved in secologanin biosynthesis (Siberil et al. 2001). In D. officinale, 93 bHLH, 23 bZIP and 3 GBF TF genes were identified, of which 23 bHLH and 8 bZIP genes were responsive to the MeJA treatment. No differential expressed GBF genes were identified. Differential expressions of these TF genes under the MeJA treatment suggested a complex genetic network affecting the biosynthesis of alkaloids in D. officinale.

Conclusions

In our study, a total of 4,857 DEGs were identified, some of which were associated with the putative alkaloid biosynthetic pathway in D. officinale. Several the MVA and MEP pathway genes were significantly up-regulated, suggesting an active precursor supply for the alkaloid biosynthesis under MeJA treatment. Furthermore, a number of MeJA-induced P450 family genes, aminotransferase genes and methyltransferase genes were identified, providing many important candidates to elucidate the potential alkaloid biosynthetic pathway of D. officinale. Our data aids to reveal the regulation mechanism underlying the MeJA-induced accumulation of alkaloids in D. officinale.

Notes

Acknowledgements

This study was supported by the Natural Science Foundation of Zhejiang Province, China (LQ17C150002 and LY19C160001), the Tree Breeding Project of Zhejiang Province, China (2016C02065) and the Project of Excellent Scientist Fund in Zhejiang Academy of Agricultural Sciences, China (2016R05R08E03).

Author contributions

YC and YW conceived and designed the study. YC and PL collected and took care of the plant samples. YC, YW, LC, and CS (Chongbo Sun) performed the experiments. PL and CS (Chongbo Sun) analyzed the data. CS (Chenjia Shen) wrote the manuscript.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no competing interests.

Supplementary material

10265_2019_1099_MOESM1_ESM.pdf (363 kb)
Supplementary material 1 (PDF 363 KB)
10265_2019_1099_MOESM2_ESM.xlsx (157 kb)
Supplementary material 2 (XLSX 157 KB)
10265_2019_1099_MOESM3_ESM.pdf (546 kb)
Supplementary material 3 (PDF 546 KB)

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Copyright information

© The Botanical Society of Japan and Springer Japan KK, part of Springer Nature 2019

Authors and Affiliations

  • Yue Chen
    • 1
    • 2
  • Yunzhu Wang
    • 1
    • 2
  • Ping Lyu
    • 3
  • Liping Chen
    • 1
    • 2
  • Chenjia Shen
    • 4
  • Chongbo Sun
    • 1
    • 2
    Email author
  1. 1.Institute of HorticultureZhejiang Academy of Agriculture ScienceHangzhouPeople’s Republic of China
  2. 2.Key Laboratory of Creative AgricultureMinistry of AgricultureHangzhouPeople’s Republic of China
  3. 3.Lin’an Agricultural and Forestry Technology Extension CenterHangzhouPeople’s Republic of China
  4. 4.College of Life and Environmental SciencesHangzhou Normal UniversityHangzhouPeople’s Republic of China

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