Skip to main content
Download PDF

Genomic characterization of WRKY transcription factors related to secoiridoid biosynthesis in Gentiana macrophylla

BMC Plant Biology volume 24, Article number: 66 (2024) Cite this article

Abstract

Gentiana macrophylla is one of Chinese herbal medicines in which 4 kinds of iridoids or secoiridoids, such as loganic acid, sweroside, swertiamarin, and gentiopicroside, are identified as the dominant medicinal secondary metabolites. WRKY, as a large family of transcription factors (TFs), plays an important role in the synthesis of secondary metabolites in plants. Therefore, WRKY genes involved in the biosynthesis of secoiridoids in G. macrophylla were systematically studied. First, a comprehensive genome-wide analysis was performed, and 42 GmWRKY genes were identified, which were unevenly distributed in 12 chromosomes. Accordingly, gene structure, collinearity, sequence alignment, phylogenetic, conserved motif and promoter analyses were performed, and the GmWRKY proteins were divided into three subfamilies based on phylogenetic and multiple sequence alignment analyses. Moreover, the enzyme-encoding genes of the secoiridoid biosynthesis pathway and their promoters were then analysed, and the contents of the four secoiridoids were determined in different tissues. Accordingly, correlation analysis was performed using Pearson′s correlation coefficient to construct WRKY gene-enzyme-encoding genes and WRKY gene–metabolite networks. Meanwhile, G. macrophylla seedlings were treated with methyl jasmonate (MeJA) to detect the dynamic change trend of GmWRKYs, biosynthetic genes, and medicinal ingredient accumulation. Thus, a total of 12 GmWRKYs were identified to be involved in the biosynthesis of secoiridoids, of which 8 (GmWRKY1, 6, 12, 17, 33, 34, 38 and 39) were found to regulate the synthesis of gentiopicroside, and 4 (GmWRKY7, 14, 26 and 41) were found to regulate the synthesis of loganic acid. Taken together, this study systematically identified WRKY transcription factors related to the biosynthesis of secoiridoids in G. macrophylla, which could be used as a cue for further investigation of WRKY gene functions in secondary metabolite accumulation.

Peer Review reports

Introduction

Gentiana macrophylla Pall, a member of the herbaceous plant in the genus Gentiana of the Gentianaceae family, is found mainly in the Loess Plateau and the eastern part of the Qinghai–Tibet Plateau of China [1]. As one of the famous traditional herbs, the roots of G. macrophylla, called “Qin-jiao” in Chinese, have been used for the therapy of allergic inflammation [2] and antirheumatic [3], anti-inflammatory and pain treatments for rheumatic diseases [4]. In addition, iridoid or secoiridoid glycosides have been identified as the dominant medicinal secondary metabolites, of which loganic acid, seweroside, swertiamarin and gentiopicroside are used as the key characteristic biomarkers for the quality control of G. macrophylla [5, 6]. It is well known that iridoids are synthesized via two pathways: the cytosolic mevalonic acid (MVA) pathway [7] and the plastidial 2C-methyl-D-erythritol 4-phosphate (MEP) pathway [8] in plants. However, the biosynthesis of secoiridoids involved in G. macrophylla is still unclear.

Recent investigations have shown that transcription factors (TFs) are powerful tools to improve the yield and quality of active ingredients by regulating the expression of enzyme-encoding genes involved in biosynthetic pathways [9]. In plants, many TFs (such as MYB, bHLH, bZIP, MADS-box, WRKY and WDR) have been found to participate in the regulation of secondary metabolite biosynthesis [10], among which WRKY, as one of the largest members in higher plants, is also the most studied TF in the regulation of plant function [11]. WRKY proteins have a highly conserved domain containing an almost invariant WRKYGQK sequence at the N-terminus followed by a C2H2 (CX4-5CX22-23HX1H) or C2HC (CX7CX23HXC) zinc-finger motif [12]. Based on both the number of WRKY domains and the features of their zinc-finger motifs, the WRKY proteins can be categorized into three distinct groups. Generally, group I has two WRKY domains and a C2H2 zinc-finger motif; group II has one WRKY domain and a C2H2 zinc-finger motif; and group III has one WRKY domain and a different C2HC zinc-finger motif. Among them, the group II proteins are further divided into 5 subgroups a ~ e, based on additional conserved structural motifs outside the WRKY domain [13, 14].

The WRKY domain can activate or inhibit the transcription of downstream target genes by binding to their DNA element known as the W-box [15, 16], which then plays important roles in responding to plant abiotic stresses [17], participating in plant growth processes, participating in MAPK-mediated signal transduction processes [18], promoting plants to respond to exogenous hormones [19, 20], and ultimately regulating the accumulation of secondary metabolites [21]. For instance, overexpression of CrWRKY1 in hairy roots of Catharanthus roseus upregulated several key TIA pathway genes. CrWRKY1 combined with the W-box element of the tryptophan decarboxylase (TDC) promoter increased TDC activity, thereby promoting the synthesis of terpenoid indole alkaloids [22]. Overexpression of OpWRKY2 in Ophiorrhiza pumila led to a more than threefold increase in camptothecin levels. OpWRKY2 directly binds and activates the central camptothecin pathway gene OpTDC to affect the biosynthesis of camptothecin [23]. Transient overexpression of TcWRKY33 in leaves of Taxus chinensis resulted in increased Taxol and 10-deacetylbaccatin accumulation by 1.20 and 2.16 times compared with the control, respectively [23]. Treating grape berries with ABA decreased the transcription level of VviWRKY40 but increased the transcription level of VviGT14, a monoterpene β-D-glucosyltransferase, indicating that VviWRKY40 is located downstream of the ABA signal transduction network to regulate monoterpenoid glycosylation [24]. All of the above studies indicate that WRKY genes play an important role in regulating the biosynthesis of secondary metabolites in plants. Since the first WRKY gene was identified in sweet potato [25], an increasing number of WRKY family members have been identified, depending on the development of available whole-genome sequences. For example, 50 EcWRKYs in California Poppy [26], 69 SmWRKYs in Salvia milliorrhiza [27], 137 PgWRKYs in Panax ginseng [28], and 39 CasWRKYs in Cannabis sativa [29] have been reported. However, GmWRKYs regulating the biosynthesis of secoiridoid glycosides in G. macrophylla are still unresolved.

In this study, the genome-wide identification and characterization of 42 GmWRKYs in G. macrophylla was performed using available genomic information. A comprehensive analysis of the GmWRKYs, including protein characterization, chromosome location, collinearity analysis, sequence alignment, phylogenetic tree, gene structure, conserved motif and promoter cis-element prediction, was performed. Moreover, based on the function of WRKY transcription factors in regulating enzyme-encoding gene expression to accumulate metabolite production, the enzyme-encoding genes in the biosynthetic pathway of iridoids were mined, and the promoter cis-elements of the enzyme-encoding genes were predicted. Based on the transcriptome data, the expression levels of GmWRKYs and biosynthetic enzyme-encoding genes were analysed. Using HPLC, the contents of the secondary metabolites in different organs (seed, root, leaf, flower and stem) of G. macrophylla were determined. Thus, the correlation between GmWRKYs and metabolic products, as well as the correlation between GmWRKYs and enzyme-encoding genes, were established to elucidate the relationship between GmWRKYs and medicinal ingredients. A previous study reported that treatment with methyl jasmonate (MeJA), an effective elicitor, increased both the expression of WRKY genes and the production of gentiopicroside in G. macrophylla, suggesting that WRKY genes could respond to MeJA elicitation, regulate enzyme-encoding genes in metabolic pathways, and then enhance the production of gentiopicroside [30]. We speculated that some GmWRKYs may act as a bridge between the MeJA signaling pathway and gentiopicroside in G. macrophylla. Based on this hypothesis, the seedlings of G. macrophylla were treated with MeJA, and then, the expression of GmWRKYs and secoiridoid biosynthetic enzyme-encoding genes, as well as the accumulation of secondary metabolites, were investigated. In brief, the aim of the present study was to identify WRKY transcription factors in G. macrophylla and reveal their molecular mechanism involved in secoiridoid biosynthesis.

Materials and methods

Plant materials and treatments

G. macrophylla plant samples grown for 3 years were collected from Fengxian County, Baoji City, Shaanxi Province, P. R. China (33.92′ N, 106.52′ E) and identified by Prof. Wei Wang (Shaanxi University of Chinese Medicine). A voucher specimen (No. GM-20191020) has been deposited in the Herbarium of Shaanxi University of Chinese Medicine (herbarium code: SNTCM). Whole roots, stems (axillary buds and leaves removed), leaves (top-leaves) and whole flowers were collected in mid-June, and immature seeds were collected in late July. All materials were dried in the shade for metabolite extraction, with 9 plants each time.

G. macrophylla seedlings were cultivated under the same conditions in the laboratory. At the four-leaf stage (grown for 3 months), the seedling materials were sprayed using 200 μM MeJA, collected and flash-frozen in liquid nitrogen stored at -80 °C at 0, 6, 12 and 24 h for RNA extraction, 6 plants each time; collected and dried in the shade on 0, 3 and 6 days for the content determination of the secondary metabolites, 30 plants each time. The normal seedlings were collected each time and set up as the blank control.

Identification and protein property analysis of the WRKY gene family in G. macrophylla

The genome of G. macrophylla used in this study at NCBI under accession number PRJNA924980. The raw data of the RNA-seq analysis used in this study were submitted to the Sequence Read Archive (SRA) at NCBI under accession number SRR8438983-SRR8438986. The nucleotide and amino acid sequences of 72 AtWRKYs were downloaded from the Arabidopsis Information Resource (TAIR; available online: http://www.Arabidopsis.org/).

By mining the annotation information of the G. macrophylla transcriptome and alignment screening with known sequences, we initially identified 74 sequences annotated as WRKY transcription factors. First, the amino acid sequences of the 74 putative WRKY genes were isolated from the genome database of G. macrophylla. Next, all of these sequences were searched for sequence similarity by NCBI-Blast alignment, sequence family features were compared with SMART (http://smart.embl-heideberg.de/), and sequence alignment was performed using DNAMAN software. Finally, 42 GmWRKYs with complete WRKY domains were identified in G. macrophylla.

ExPASy (http://ExPASy.org/) [31] was used to investigate the length, molecular weight (MW), isoelectric points (PIs), instability index, and aliphatic index of WRKY proteins in G. macrophylla. Plant-mPLoc (http://www.csbio.sjtu.edu.cn/bioinf/plant-multi/) [32] was used to estimate the subcellular locations of WRKY proteins in the plant.

Phylogenetic, gene structure and conserved motif analyses

The amino acid sequences in the WRKY domain of G. macrophylla and A. thaliana were aligned by MEGA 7.0 software [33] using the ClustalX program, and the phylogenetic analysis was constructed using the neighbour-joining method with 1,000 bootstrap replicates. Based on the genome annotation files of G. macrophylla, the structure of GmWRKYs was visualized using TBtools software [34]. Motifs were identified by the MEME 5.5.1 online program (http://meme-suite.org/tools/meme) [35] with the following parameters: number of repetitions, default; maximum number of motifs, 10; and optimum width of each motif, between 20 and 50 residues.

Chromosomal locations, collinearity analysis and cis-acting regulatory prediction

TBtools software was used to locate all GmWRKYs on the chromosome of G. macrophylla and conduct collinearity analysis.

The 2 kb promoter sequences of GmWRKYs and the related enzyme-encoding genes, upstream of the translation initiation site, were obtained from the G. macrophylla genome. PlantCARE (http://bioinformatics.psb.ugent.be/webtools/plantcare/html/) [36] and PLACE (https://www.dna.affrc.go.jp/PLACE/?Action=newplace) were used to analyse these gene promoters and identify their cis-acting regulatory.

Identification of enzyme-encoding genes related to the biosynthesis of secoiridoids

The biosynthesis pathway of the secoiridoids in G. macrophylla was constructed based on the KEGG pathway database [37] and related literature reports on the secoiridoid biosynthetic pathway [38]. Accordingly, the transcriptome annotation files of the roots, stems, leaves, flowers, and seeds were analysed to retrieve the names of the enzyme-encoding genes in the biosynthesis pathway and screen their numbers and sequences. Meanwhile, a local database was built with BioEidt software to align homologous genes of the metabolic pathway genes with tBlastX. Next, all enzyme-encoding gene sequences were searched for sequence similarity by NCBI-Blast alignment, and the same class of sequence alignment was performed using DNAMAN software to remove the repeat sequences. Finally, 84 enzyme-encoding genes were screened from the roots, stems, leaves, flowers and seeds according to the FPKM values (> 5.0).

Content determination of the secondary metabolites

Source of standard products: loganic acid (purity: 99.12%), swertiamarin (purity: 99.51%), gentiopicroside (purity: 99.90%) and sweroside (purity: 99.16%) were all purchased from Shanghai Yuanye Bio-Technology Co., Ltd.

Each dried sample (50 mg) was extracted in 1 mL methanol under ultrasonic waves 3 times for 40 min each time and centrifuged for 5 min at 12,000 rpm, and the supernatant was collected and filtered through a 0.22 μm filter (Jiangsu Green Union Science Instrument Co., Ltd., Taizhou, China). Repeat 3 times. The contents of four main secondary metabolites, loganic acid, sweroside, swertiamarin and gentiopicroside, were determined via LC-20ADXR HPLC system Shimadzu (Japan) with 4.6 mm × 250 mm, C18 5 μm particles (Welch, USA); UV detector, 254 nm; column temperature, 30 °C; flow rate, 0.8 mL/min, using gradient solvent system ACN (Welch, USA) /H2O as the mobile phase (0—13 min, ACN 11%, 13—16 min, ACN 10%; 16—30 min, ACN 12%). Each injection volume was set at 20 μL.

The standard curve was constructed from the content of metabolite (X, mg/mL) and peak area (Y). The linear regression equation was Y = 9,313,169.91 x + 52,842.65 (linear range 0.004375 mg/mL—1.12 mg/mL) for loganic acid, Y = 19,491,752.98 x + 131,241.49 (linear range, 0.004414063 mg/mL—1.13 mg/mL) for sweroside, Y = 10,348,224.18 x + 124,625.728 (linear range, 0.008007813 mg/mL—2.05 mg/mL) for gentiopicroside, and Y = 40,500,359.78 x + 332,031.12 (linear range, 0.004921875 mg/mL—1.26 mg/mL) for swertiamarin. Each group was repeated 3 times. Excel 2019 was used for data processing, and GraphPad Prism 9.5 software was used for drawing and t test for significance.

Association analysis of WRKY genes with enzyme-encoding genes and secondary metabolites in G. macrophylla

To obtain candidate GmWRKYs for the regulation of secoiridoid biosynthesis, according to the transcriptome data, one Pearson correlation analysis was performed between the expression of GmWRKYs and the genes involved in secoiridoid biosynthesis in different tissues, with a threshold of correlation coefficient 0.75, p < 0.05; the other Pearson correlation analysis was performed between the expression of GmWRKYs and the contents of secondary metabolites (gentiopicroside, sweroside, swertiamarin and loganic acid), with a threshold of correlation coefficient 0.75, p < 0.05.

Gene expression analysis by RT–qPCR

Total RNA was isolated using the polysaccharide polyphenol plant total RNA extraction kit (Bioteke, Beijing). The concentration and purity of RNA were detected by Nanodrop (Thermo Fisher, USA), and its integrity was detected by 1% agarose gel electrophoresis (Solarbio, Beijing). Reverse transcription was then performed according to the manufacturer’s instructions using PrimeScript™ IV 1st strand cDNA Synthesis Mix (TaKaRa, Dalian) and stored at -20 °C until use. RT–qPCR (qTOWER 2.0, Analytik Jena, Germany) was performed under the following conditions: 95 °C for 30 s; 95 °C for 5 s and 60 °C for 20 s, 40 cycles. Relative expression of the genes was calculated by the 2−∆∆Ct method. The SAND1 gene was tested as an internal reference [39]. The primer information is shown in Additional file 13: Table S9. The results are represented by their means ± SDs. GraphPad Prism 9.5 software was used for drawing, and a t test was used for significance.

Statistical analysis

All data are expressed as the mean ± SD of three independent biological replicates. Statistical analysis was performed using GraphPad Prism 9.5 software. A t test was used for statistical analysis, followed by an unpaired t test. P < 0.05 was considered to indicate a statistically significant difference.

Results

Identification and protein characterization of WRKY in G. macrophylla

To extensively identify the potential WRKY genes, according to the annotated genome data, a total of 74 putative WRKY gene family members were obtained using “WRKY” as the search term. The redundant sequences and the incomplete sequences without the zinc finger structure were expurgated, according to the results of NCBI-Blast alignment and SMART database comparison. Thus, a total of 42 WRKY genes were eventually identified and named GmWRKY1—GmWRKY42 (Additional file 5: Table S1). The sequence analysis results showed that the protein length of these GmWRKYs ranged from 207 (GmWRKY24) to 707 (GmWRKY40) amino acids (aa), the protein relative molecular mass varied from 23.38 (GmWRKY24) to 77.37 (GmWRKY40) kDa, and the protein PI was distributed in a wide range from acidic 5.32 (GmWRKY2 and GmWRKY20) to very basic 9.9 (GmWRKY19). The instability index results showed that most GmWRKY proteins were greater than 40, belonging to the unstable proteins, except GmWRKY35 (38.39). The aliphatic index results showed that the proteins ranged from 35.69 (GmWRKY13) to 75.17 (GmWRKY14). The GRAVY scores of GmWRKY proteins were all below 0, indicating their hydrophilic characteristics. Furthermore, all 42 proteins were located in the nucleus.

Classification of the WRKY proteins and phylogenetic analysis in G. macrophylla

Sequence analysis revealed that all GmWRKY proteins have the conserved “WRKYGQK” motif, except GmWRKY9, which possesses “WRKYGKK” (Additional file 1: Fig. S1). To understand the evolutionary relationship of GmWRKY proteins, a total of 42 GmWRKYs in G. macrophylla and 68 AtWRKYs in A. thaliana were used to build a phylogenetic tree constructed by the NJ method (Additional file 2: Fig. S2). Thus, 42 GmWRKY proteins were divided into three main groups, similar to other plants, in which group I included 12 GmWRKY proteins (GmWRKY 3, 8, 10, 12, 16, 17, 21, 25, 27, 38, 40, and 41); group II included 25 GmWRKY proteins, further refined into five subgroups: IIa (GmWRKY1), IIb (GmWRKY 5, 15, 32 and 39), IIc (GmWRKY 4, 9, 11, 13, 18, 24, 28, 34, 35 and 37), IId (GmWRKY 19, 22, 23, 26, 29, 31 and 36), and IIe (GmWRKY6, 33 and 42); and group III included 5 GmWRKY proteins (GmWRKY2, 7, 14, 20 and 30).

Gene structure and conserved motifs of WRKY genes in G. macrophylla

The conserved motif and intron/exon distribution were visualized using TBtools software to clarify the structural characteristics of GmWRKYs. The gene structure map (Additional file 3: Fig. S3B) showed that among the 42 identified GmWRKYs, 2 contained one exon belonging to group IId; 1 contained two exons belonging to group IIc; 17 had three exons belonging mainly to groups II and III; 9 had four exons belonging only to group I; and 6 had five exons and 7 had six exons belonging mainly to group I, suggesting that GmWRKY members from the same WRKY group tended to share a similar gene structure in terms of intron/exon organization. The gene conserved motif map showed that a total of 10 motif patterns were obtained (Additional file 3: Fig. S3C and Additional file 6: Table S2). All family members of GmWRKYs contained motifs 1 and 2, whereas motifs 3, 7 and 10 were found only in groups I, IIb and IId, respectively; motifs 4 and 6 were mainly present in group I; motif 9 was found in groups I and IIc; motif 5 was mainly found in groups IId and IIe; and motif 8 was present in most genes in groups I and IId (Additional file 3: Fig. S3A). As expected, most of the GmWRKYs observed in the same group or subgroup usually shared highly similar motif compositions, further validating the phylogenetic relationship of GmWRKYs and suggesting that they might have a similar regulatory function in the same group.

Chromosome locations and collinearity analysis of WRKY genes in G. macrophylla

To determine the genomic distribution of WRKY genes, the physical map positions of 42 GmWRKYs were identified by TBtools based on annotation information of G. macrophylla (Fig. 1 and Additional file 7: Table S3), in which 40 GmWRKYs were distributed across 12 chromosomes, except GmWRKY10 and GmWRKY18. Among these chromosomes, Chr3 had the most WRKY genes (8 genes, 19.5% of the total), followed by Chr5 (5 genes, 11.9% of the total), while Chr1, 7 and 8 contained 4 genes; Chr6, 11 and 12 contained 3 genes; Chr9 and 10 contained 2 genes; and Chr2 and 13 contained only one. Subsequently, TBtools was used to investigate their duplication events to illustrate the expansion patterns of GmWRKYs (Fig. 2). The results showed that 14 duplication pairs were identified, concentrated in groups I, IIc, IId, IIe and III. Two or more homologous genes within a 200 kb range on the same chromosome are defined as tandem repeat events [40]. In this study, two sets of tandem repeat events were found in 42 WRKYs, namely GmWRKY33 and GmWRKY6 located on chromosome 3, and GmWRKY24, GmWRKY2, and GmWRKY20 located on chromosome (Additional file 8: Table S4).

Fig. 1
figure 1

Distribution of GmWRKYs across the chromosomes of G. macrophylla. The chromosome numbers are shown at the top of each chromosome (black bars). The location of each WRKY gene is indicated by a line. Groups and subgroups are distinguished by different colors (groups: I-red; IIa-blue; IIb-purple; IIc-green; IId-yellow; IIe-brown; III-pink)

Full size image
Fig. 2
figure 2

Synteny analyses of GmWRKYs in G. macrophylla. The yellow blocks indicate the parts of G. macrophylla chromosomes. The coloured lines indicate duplicated GmWRKY gene pairs. The scale bar on the top-right corner shows the different colors to represent the gene distribution density values. Low and high values are indicated in blue and red, respectively. Darker blue indicates less gene distribution, while darker red indicates more gene distribution

Full size image

Cis-Acting regulatory elements in the promoter region of WRKY genes in G. macrophylla

The cis-acting elements in the 2.0 kb upstream promoter region of all GmWRKYs were predicted and analysed by PlantCARE (Fig. 3). The results showed that many types of cis-acting elements were present. Among them, light responsive elements were found in the promoter region of 42 GmWRKYs, accounting for the largest proportion, followed by MeJA-responsive elements (34 GmWRKYs). Abscisic acid- and auxin-responsive elements were found in 30 and 20 promoters of GmWRKYs, respectively. Gibberellin- and salicylic acid-responsive elements were found in the promoter regions of 20 and 15 genes, respectively. In addition, some elements related to abiotic stresses were found, such as low temperature (19 GmWRKYs), defense (17 GmWRKYs), and drought (19 GmWRKYs). Moreover, some elements were found to regulate plant growth and development, such as zein metabolism regulation, circadian control, endosperm expression and meristem expression.

Fig. 3
figure 3

Prediction of cis-regulatory elements in the promoter regions of GmWRKYs. (A) Phylogenetic tree of GmWRKY proteins. (B) The distribution of cis-regulatory elements within each GmWRKY promoter

Full size image

Expression analysis of WRKY genes in different tissues of G. macrophylla

It is well known that tissue-specific expression patterns of genes can provide invaluable information for understanding the biological function of genes. According to the transcriptome data, the expression profiles of GmWRKYs were generated, and the results showed that all 42 GmWRKYs were ubiquitously expressed in different tissues but with different expression patterns in the roots, stems, leaves, flowers and seeds (Fig. 4). Among them, 7 (GmWRKY6, 15, 21, 29, 31, 33 and 39), 6 (GmWRKY7, 14, 20, 26, 30 and 41) and 7 (GmWRKY4, 13, 16, 24, 25, 28 and 37) showed the highest levels expression in the roots, leaves and stems, respectively. In addition, some GmWRKYs were expressed in two tissues at high levels, such as GmWRKY1, GmWRKY9, GmWRKY12 and GmWRKY34 in roots and leaves, GmWRKY19 and GmWRKY27 in roots and stems, GmWRKY42 in roots and flowers, and GmWRKY3 in stems and flowers. The results indicated that these genes might be important for plant growth and organ development in G. macrophylla.

Fig. 4
figure 4

Heatmap representing the expression profiles of GmWRKYs in leaves, roots, stems, flowers and seeds. Different color blocks represent the normalized gene expression levels (log2 (FPKM)) of all genes in different tissues. Within each row, low and high values are indicated in light blue and red, respectively. The scale represents the signal intensity of FPKM values

Full size image

Identification of the enzyme-encoding genes involved in secoiridoid biosynthesis

In simple terms, the secoiridoid biosynthesis pathway in plants can be divided into three main parts: the initial MEP and MVA pathways and the characteristic secoiridoid pathway [38]. Accordingly, the putative secoiridoid biosynthetic pathway in G. macrophylla was reconstructed based on the KEGG database. Thus, a total of 84 enzyme-encoding genes were classified into 27 enzyme categories related to the pathway (Fig. 5 and Additional file 9: Table S5). Among them, 19, 13 and 52 enzyme-encoding genes encoding 6, 7 and 14 enzymes were involved in the MVA, MEP and secoiridoid pathways, respectively. Furthermore, the enzyme-encoding genes of the MVA pathway were mainly present with the highest expression in roots but the lowest expression in seeds; the enzyme-encoding genes of the MEP pathway were mainly present with the highest expression in leaves but the lowest expression in seeds; and the enzyme-encoding genes of the characteristic secoiridoid pathway were mainly present with high expression in roots, stems and leaves but low expression in flowers and seeds.

Fig. 5
figure 5

Analysis of gene expression involved in the secoiridoid biosynthesis of G. macrophylla. Different color blocks represent the normalized gene expression levels (log2 (FPKM)) of all genes in different tissues. The yellow ellipse represents the MVA pathway, the light blue ellipse represents the MEP pathway, and the green ellipse represents the characteristic secoiridoid pathway. GmAACT, acetoacetyl-CoA thiolase; GmHMGS, 3-hydroxy-3-methylglutaryl-CoA synthase; GmHMGR, 3-hydroxy-3-methylglutaryl-CoA reductase; GmMK, mevalonate kinase; GmPMK, phosphomevalonate kinase; GmMDC, mevalonate-5-pyrophosphate decarboxylase; GmDXS, deoxyd-xylulose-5-phosphate synthase; GmDXR, deoxy-D-xylulose-5-phosphate reductoisomerase; GmCMS, 4-(cytidine 5’-diphospho)-2-C-methyl-D-erythritol synthase; GmCMK, 4-(cytidine 5’-diphospho)-2-C-methyl-D-erythritol kinase; GmMCS, 2-C-methyld-erythritol2,4-cyclodiphosphate synthase; GmHDS, 4-hydroxy-3-methylbut-2-enyl diphosphate synthase; GmHDR, 4-hydroxy-3-methylbut-2-enyl diphosphate reductase; GmIDI, isopentenyl diphosphate isomerase; GmGPPS, geranyl diphosphate synthase; GmFPPS, farnesyl diphosphate synthase; GmGGPPS, geranylgeranyl diphosphate synthases; GmGES, geraniol synthase; GmG10H geraniol 10-hydroxylase; Gm8-HGO, 8-hydroxy-geraniol oxidoreductase; GmIS, iridoid synthase; GmNS, nepetalactol synthase; GmIO, iridoid oxidase; Gm7-DLGT, 7-deoxyloganetic acid glucosyltransferase; Gm7-DLNGT, 7-deoxyloganetic glucosyltransferase; Gm7-DLH, 7-deoxyloganate 7-hydroxylase; and GmSLS, secologanin synthase; were recorded as the key enzymes in the pathway

Full size image

Correlation analysis of WRKY genes and the enzyme-encoding genes involved in secoiridoid biosynthesis in G. macrophylla

Pearson correlation analysis was performed to identify the WRKY genes involved in the regulation of secoiridoid biosynthesis in G. macrophylla (Fig. 6 and Additional file 10: Table S6). The results showed that 32 GmWRKYs were significantly correlated with 49 enzyme-encoding genes (encoding 23 enzymes). Among them, significant correlations were observed between 5 enzymes of the MVA pathway (GmAACT, GmHMGS, GmHMGR, GmMK and GmPMK) and 21 GmWRKYs (GmWRKY1, 6, 12, 13, 14, 17, 18, 21, 22, 23, 25, 27, 28, 29, 30, 32, 33, 36, 38, 40 and 41), between 7 enzymes of the MEP pathway (GmDXS, GmDXR, GmCMS, GmCMK, GmMCS, GmHDS and GmHDR) and 21 GmWRKYs (GmWRKY1, 6, 7, 9, 13, 14, 17, 18, 19, 20, 22, 23, 27, 28, 30, 32, 33, 36, 38, 40 and 41), between 11 enzymes of the characteristic secoiridoids pathway (GmIDI, GmFDPS, GmGGPS, GmGES, GmG10H, Gm8-HGO, GmIS, GmNS, Gm7-DLGT, Gm7-DLH and GmSLS) and 31 GmWRKYs (GmWRKY1, 3, 6, 7, 8, 9, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 25, 27, 28, 29, 30, 32, 33, 34, 37, 38, 39, 40 and 41).

Fig. 6
figure 6

Pearson correlation analysis of GmWRKYs and the enzyme-encoding genes involved in secoiridoid biosynthesis in G. macrophylla. The scale bar on the top-right corner shows the different colors to represent the correlation coefficient values. The deeper the red is, the stronger the positive correlation. The deeper the blue is, the stronger the negative correlation

Full size image

Promoter analysis of the enzyme-encoding genes involved in secoiridoid biosynthesis in G. macrophylla

The mechanism of WRKY transcription factor regulation in activating or inhibiting gene expression involves binding to the W-box element in the target gene promoter. According to the above results that 49 enzyme-encoding genes were significantly related to 32 GmWRKYs in secoiridoid biosynthesis of G. macrophylla, these enzyme-encoding gene promoters were analysed (Additional file 11: Table S7). The results showed that eight types of W-boxes (ELRECOREPCRP1, WBBOXPCWRKY1, WBOXATNPR1, WBOXHVISO1, WBOXNTERF3, WBOXNTCHN48, TGACGTVMAMY and WRKY71OS) were present in the promoters. Each enzyme-encoding gene contained at least two kinds of W-boxes, one of which was WRKY71OS. Each enzyme-encoding gene contained at least two kinds of W-boxes, one of which was WRKY71OS. These results implied that 32 GmWRKYs might directly bind to W-box elements in regulating the expression of the key enzyme-encoding genes in G. macrophylla and thereby affecting secoiridoid biosynthesis.

Correlation analysis of WRKY gene expression with the content of secondary metabolites in G. macrophylla

HPLC was used to determine the contents of four representative components, namely, loganic acid, swertiamarin, sweroside, and gentiopicroside, in different tissues. The results (Fig. 7A and Additional file 12: Table S8) showed that gentiopicroside was present at the highest level in roots at 217.98 ± 2.87 mg/g (dry weight), while loganic acid, swertiamarin, and sweroside were present at the highest levels in seeds at 20.69 ± 0.63 mg/g, 5.13 ± 0.10 mg/g and 2.58 ± 0.06 mg/g, respectively. The correlation of the expression of 32 GmWRKYs with the contents of these components was then analysed. The results showed (Fig. 7B) that 16 GmWRKYs displayed a significant correlation with the components, of which 8 (GmWRKY1, 6, 12, 17, 33, 34, 38 and 39) presented a positive correlation with gentiopicroside, while 4 (GmWRKY7, 14, 26 and 41), 3 (GmWRKY14, 27 and 30) and 8 (GmWRKY1, 7, 14, 16, 20, 27, 38 and 41) were negatively correlated with loganic acid, swertiamarin and sweroside, respectively.

Fig. 7
figure 7

Correlation analysis of WRKY expression with the content of secondary metabolites in G. macrophylla. (A) Content determination of four representative components (loganic acid, swertiamarin, gentiopicroside and sweroside) in different tissues. The roots were used as a blank control. The asterisks (*) represent significant differences (*, P < 0.05; **, P < 0.01; ***, P < 0.001; and ****, P < 0.0001). (B) Correlation analysis of GmWRKY expression with the content of the four components

Full size image

Analysis of WRKY gene expression, biosynthetic enzyme-encoding gene expression, and component content determination in MeJA-treated G. macrophylla seedlings

Under the cognition that MeJA treatment could induce the expression of GmWRKYs in a previous study, to further verify the above experimental results that GmWRKYs were involved in the regulation of secoiridoid biosynthesis, seedlings of G. macrophylla treated with MeJA at the four-leaf stage were cultivated and collected; thus, GmWRKY expression, enzyme-encoding gene expression, and the content of the components in them were analysed. The results of the content determination (Fig. 8, Additional file 4: Fig. S4 and Additional file 14: Table S10) showed that the gentiopicroside content was significantly increased, and the sweroside content was gently increased, while the swertiamarin content showed no great change, whereas the loganic acid content was sharply decreased. The results of the RT–qPCR (Fig. 9 and Fig. 10) showed that the expression levels of 16 GmWRKYs were upregulated by MeJA treatment, of which 11 (GmWRKY1, 6, 7, 12, 14, 16, 17, 20, 30, 38 and 41) presented significant upregulation at 12 h but downregulation at 24 h; 5 (GmWRKY26, 27 33 34 39) presented significant upregulation at 24 h. Meanwhile, some genes involved in secoiridoid biosynthesis shared a similar expression pattern with GmWRKYs, such as the genes GmHMGS, GmMK and GmPMK in the MVA pathway, the genes GmCMS, GmMCS and GmHDS in the MEP pathway, and the genes GmIDI, GmGES, GmFPPS, GmIS, GmIO, Gm7-DLGT and GmSLS in the characteristic secoiridoid pathway, presenting significant upregulation at 12 h but downregulation at 24 h; and 6 genes (GmDXR, GmCMK, GmHDR, GmGGPS, GmG10H, GmNS) involved in secoiridoid biosynthesis presented significant upregulation at 24 h, suggesting the same regulatory mechanism by MeJA between the GmWRKYs and the pathway biosynthetic genes.

Fig. 8
figure 8

(A) The determination of the content of the four compounds (loganic acid, sweroside, gentiopicroside and swertiamarin) in the seedlings of G. macrophylla treated with MeJA. The red columns represent the content determination results of G. macrophylla seedlings treated with MeJA. The blue columns represent the content determination results of G. macrophylla seedlings without MeJA treatment (Control). The asterisks (*) represent significant differences (*, P < 0.05; **, P < 0.01; ***, P < 0.001; and ****, P < 0.0001). (B) Chromatograms for the determination of the content of four compounds in G. macrophylla seedlings for 3 days. The red chromatogram shows the content determination chromatogram of G. macrophylla seedlings treated with MeJA. The blue chromatogram shows the content determination of G. macrophylla seedlings without MeJA treatment (Control). 1: Loganic acid, 2: Swertiamarin, 3: Gentiopicroside, 4: Sweroside

Full size image
Fig. 9
figure 9

Analysis of GmWRKY expression in MeJA-treated seedlings of G. macrophylla (0 h, 6 h, 12 h and 24 h) tested by RT–qPCR. The CK (the seedling of G. macrophylla not treated with MeJA) was used as the blank control. The asterisks (*) represent significant differences (*, P < 0.05; **, P < 0.01; ***, P < 0.001; and ****, P < 0.0001)

Full size image
Fig. 10
figure 10

Analysis of the gene expression involved in secoiridoid biosynthesis in MeJA-treated seedlings of G. macrophylla (0 h, 6 h, 12 h and 24 h) tested by RT–qPCR. The CK (the seedling of G. macrophylla not treated with MeJA) was used as the blank control. The asterisks (*) represent significant differences (*, P < 0.05; **, P < 0.01; ***, P < 0.001; and ****, P < 0.0001)

Full size image

Discussion

G. macrophylla, the flowers of which are used as Tibetan medicine [41], while the roots of which are used as traditional Chinese medicine, is widely used in the pharmaceutical industry. Secoiridoids, as the main bioactive components, exhibit many therapeutic activities [42], with swertiamarin and gentiopicroside being regarded as two promising new natural drugs [43, 44]. Bioengineering studies to increase yields of swertiamarin [45] or gentiopicroside [46] have been carried out in recent years. Transcription factors are powerful tools to regulate the expression of synthetic pathway genes and improve the yield and quality of bioactive compounds [47]. Due to rare research on G. macrophylla, WRKY transcription factors in the regulation of secoiridoid biosynthesis were studied in this paper.

Herein, a total of 42 GmWRKYs were obtained from the G. macrophylla genome by bioinformatics analysis and divided into 3 groups (12 in Group I, 25 in Group II, and 5 in Group III). Obviously, group II was the largest group in G. macrophylla, which was similar to the results of Panax ginseng [28], Eucommia ulmoides [48], Taraxacum kok-saghyz [49] and Bupleurum chinense [50]. Considering that the distribution discrepancy of the groups implied different evolutionary processes in plant development [48, 51], the above data indicated that GmWRKYs in group II underwent more gene duplications during the process of evolution. Moreover, the typical characteristics of the WRKYs were conserved in structure but versatile in function. Some genes, such as ApWRKYs (Andrographis paniculata) [52] or GmWRKY (Soybean) [53] with similar protein sequence structures, showed similar expression patterns and performed similar biological functions, while others, such as MnWRKY (Mulberry) [54], SiWRKY (Sesame) [55] and GmWRKYs (Gentiana macrophylla), in the same group or subgroup shared highly similar motif compositions and gene structures but different expression patterns and functions.

In addition to AtWRKYs in A. thaliana [56] and TkWRKYs in Taraxacum kok-saghyz [49], most GmWRKYs contained a WRKY domain prominent feature composed of 60 amino acids with a conserved WRKYGQK heptapeptide sequence at the N-terminus. In most cases, the WRKY domain was very conserved; however, variant motifs such as WRKYGEK, WRKYGKK, WRICGQK, WSKYEQK and WRKYSEK were also found [57]. GmWRKY9 sequence variations occurred and were replaced by the WRKYGKK motif. As reported that the variants might change the DNA binding specificities in the interactions of WRKY genes with downstream target genes [58, 59], the nature of GmWRKY9 needs to be further explored in the future.

As shown in Catharanthus roseus [22] and Salvia miltiorrhiza [27], WRKY transcription factors always play important regulatory roles in the synthesis of secondary metabolites, while the expression patterns of enzyme-encoding genes involved in the formation of secondary metabolites in plants were significantly related to the distribution of metabolites. Thus, correlation analysis was conducted on the expression of GmWRKYs, the enzyme-encoding genes in the secoiridoid biosynthesis pathway, and the contents of loganinic acid, swertiamarin, gentiopicroside, and sweroside. As shown in Fig. 6, 32 GmWRKYs were significantly correlated with 23 enzymes. As shown in Figs. 7B and 8 GmWRKYs were positively correlated with gentiopicroside, while 4, 3 and 8 GmWRKYs were negatively correlated with loganic acid, swertiamarin and sweroside, respectively. In addition, the mechanism for GmWRKYs to regulate these metabolites was determined as the WRKY sequence initially binding to W-box elements [60], observed in the promoters of metabolic pathway enzyme-encoding genes, interacting with the target genes, and finally affecting the accumulation of secondary metabolites in G. macrophylla.

AaGSW1 could be directly regulated by the jasmonic acid (JA) positive regulator AaMYC2 in Artemisia annua, and overexpression of AaGSW1 significantly increased the content of artemisinin and dihydroartemisinin [61]; TcWRKY1 increased after JA induction in suspension cells of Taxus chinensis, and overexpression of TcWRKY1 increased the expression of the DBAT gene, while RNA interference reduced the transcription level of the DBAT gene, a key rate-limiting enzyme in the Taxol biosynthesis pathway [62]. These studies revealed that WRKY transcription factors were involved in the response to JA signals, thus directly or indirectly affecting the accumulation of various plant secondary metabolites. Because GmWRKYs had hormone MeJA responsive elements in the promoter region, G. macrophylla seedlings were treated with MeJA. However, studies have not reached a consensus on the selection of time points for studying the correlation between genes and metabolites. The main reason is that the regulatory relationship between metabolites and genes is complex. The response of gene expression to exogenous inducer treatment occurs earlier than the accumulation of secondary metabolites; however, the front-to-back effect between them needs to consider their different rates and durations of changes in different plants or in the same plants with different test objectives; thus, measuring gene expression and metabolite content at different time points can better capture their correlation. For G. macrophylla, after MeJA treatment, changes in gene expression appeared within 24 h, but the contents of the metabolites changed from 3 to 6 days. Thus, they were chosen as the time points for this study. As shown in Fig. 8, the content of gentiopicroside was significantly increased after MeJA treatment, while the loganic acid content was sharply decreased, whereas sweroside and swertiamarin content showed no significant change. As shown in Figs. 9 and 10, the expression of 16 GmWRKYs and 22 enzyme-encoding genes were significantly increased after MeJA treatment, in which the expression of 8 GmWRKYs and 13 enzymes were significantly increased as well as the content of gentiopicroside, verifying the positive correlation indicated in the results of different tissues, while the expression of 4 GmWRKYs and 14 enzymes were significantly increased in contrast to the reduction of loganic acid content, verifying the negative correlation indicated in different tissues. In addition, after treatment with MeJA, the expression of GmWRKYs and the enzyme-encoding genes related to swertiamarin and sweroside were also increased; however, their contents showed no significant change. Thus, 8 GmWRKYs (GmWRKY1, 6, 12, 17, 33, 34, 38 and 39) regulating the synthesis of gentiopicroside and 4 GmWRKYs (GmWRKY7, 14, 26 and 41) regulating the synthesis of loganic acid were identified in G. macrophylla. These results indicated that WRKY transcription factors were most likely involved in secoiridoid biosynthesis in G. macrophylla. This study provides a theoretical basis for further exploring the mechanism of WRKY transcription factors in the regulation of secondary metabolites in G. macrophylla.

Conclusion

In this study, 42 WRKY genes were identified in the G. macrophylla genome and divided into 3 groups (12 in Group I, 25 in Group IIa-e, and 5 in Group III) by sequence alignment, phylogenetic analysis, gene structure analysis and conserved motif analysis. Based on the study of the relationship of WRKY genes with the enzyme-encoding genes in the secondary metabolism pathway and the secondary metabolites and the experiment in which seedlings were treated with MeJA, 8 GmWRKYs (GmWRKY1, 6, 12, 17, 33, 34, 38 and 39) regulating the synthesis of gentiopicroside and 4 GmWRKYs (GmWRKY7, 14, 26 and 41) regulating the synthesis of loganic acid were found (Fig. 11). Our study has generated an important resource for further studies of WRKY transcription factors in G. macrophylla and provided a clue for further investigating WRKY gene function in secondary metabolite accumulation.

Fig. 11
figure 11

Predicted network diagram of GmWRKY pathway genes and secondary metabolites. The yellow ellipse presents the secondary metabolites, the light blue ellipse presents the GmWRKYs, and the green rectangle presents the pathway genes. The red arrow indicates positive regulation, and the blue arrow indicates negative regulation

Full size image

Availability of data and materials

All data included in this study are available upon request by contact with the corresponding author.

References

  1. Lu YY, Yang YM, Ma XH, Zhang XB, Zhu SD, Jin L. Ecology suitability study of Chinese materia medica Gentianae Macrophyllae Radix. China J Chin Materia Med. 2016;41(17):3176–80.

    Google Scholar 

  2. Wang YM, Xu M, Wang D, Yang CR, Zeng Y, Zhang YJ. Anti-inflammatory compounds of “Qin-Jiao”, the roots of Gentiana dahurica (Gentianaceae). J Ethnopharmacol. 2013;147(2):341–8.

    Article  CAS  PubMed  Google Scholar 

  3. Yu F, Yu F, Li R, Wang R. Inhibitory effects of the Gentiana macrophylla (Gentianaceae) extract on rheumatoid arthritis of rats. J Ethnopharmacol. 2004;95(1):77–81.

    Article  PubMed  Google Scholar 

  4. Jia N, Chu W, Li Y, Ding L, Duan J, Cui J, Cao S, Zhao C, Wu Y, Wen A. Iridoid glycosides from the flowers of Gentiana macrophylla Pall. ameliorate collagen-induced arthritis in rats. Journal of Ethnopharmacology. 2016;189:1–9.

    Article  PubMed  Google Scholar 

  5. Wang Y, Ahmad B, Duan B, Zeng R, Huang L. Chemical and genetic comparative analysis of Gentiana crassicaulis and Gentiana macrophylla. Chem Biodivers. 2016;13(6):776–81.

    Article  CAS  PubMed  Google Scholar 

  6. Kou Y, Yi X, Li Z, Ai Y, Ma S, Chen Q. A comparative transcriptomic with UPLC-Q-Exactive MS reveals differences in gene expression and components of iridoid biosynthesis in various parts of Gentiana macrophylla. Genes. 2022;13:2372.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Liao P, Hemmerlin A, Bach TJ, Chye M-L. The potential of the mevalonate pathway for enhanced isoprenoid production. Biotechnol Adv. 2016;34(5):697–713.

    Article  CAS  PubMed  Google Scholar 

  8. Zeng L, Dehesh K. The eukaryotic MEP-pathway genes are evolutionarily conserved and originated from Chlaymidia and cyanobacteria. BMC Genomics. 2021;22(1):137.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Patra B, Schluttenhofer C, Wu Y, Pattanaik S, Yuan L. Transcriptional regulation of secondary metabolite biosynthesis in plants. Gene Regul Mechan. 2013;1829(11):1236–47.

    CAS  Google Scholar 

  10. Yang CQ, Fang X, Wu XM, Mao YB, Wang LJ, Chen XY. Transcriptional regulation of plant secondary metabolism. J Integr Plant Biol. 2012;54(10):703–12.

    Article  CAS  PubMed  Google Scholar 

  11. Rushton PJ, Somssich IE, Ringler P, Shen QJ. WRKY transcription factors. Trends Plant Sci. 2010;15(5):247–58.

    Article  CAS  PubMed  Google Scholar 

  12. Grzechowiak M, Ruszkowska A, Sliwiak J, Urbanowicz A, Jaskolski M, Ruszkowski M. New aspects of DNA recognition by group II WRKY transcription factor revealed by structural and functional study of AtWRKY18 DNA binding domain. Int J Biol Macromol. 2022;213:589–601.

    Article  CAS  PubMed  Google Scholar 

  13. Jing C, Wang D, Liu Z, Chen X, Dong H, Wu X. Identification of the WRKY gene family in apricot and its response to drought stress. Hortic Environ Biotechnol. 2023;64(2):269–82.

    Article  CAS  Google Scholar 

  14. Du P, Wu Q, Liu Y, Cao X, Yi W, Jiao T, Hu M, Huang Y. WRKY transcription factor family in lettuce plant (Lactuca sativa): Genome-wide characterization, chromosome location, phylogeny structures, and expression patterns. PeerJ. 2022;10:e14136.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Eulgem T, Rushton PJ, Robatzek S, Somssich IE. The WRKY superfamily of plant transcription factors. Trends in PlantScience. 2000;5(5):199–206.

    Article  CAS  Google Scholar 

  16. Ulker B, Somssich IE. WRKY transcription factors: from DNA binding towards biological function. Curr Opin Plant Biol. 2004;7(5):491–8.

    Article  PubMed  Google Scholar 

  17. Chen L, Song Y, Li S, Zhang L, Zou C, Yu D. The role of WRKY transcription factors in plant abiotic stresses. Biochem Biophys Acta. 2012;1819(2):120–8.

    CAS  PubMed  Google Scholar 

  18. Liang W, Yang B, Yu B-J, Zhou Z, Li C, Jia M, Sun Y, Zhang Y, Wu F, Zhang H, et al. Identification and analysis of MKK and MPK gene families in canola (Brassica napus L.). BMC Genom. 2013;14(1):392.

    Article  CAS  Google Scholar 

  19. Yang B, Jiang Y, Rahman MH, Deyholos MK, Kav NNV. Identification and expression analysis of WRKY transcription factor genes in canola (Brassica napus L.) in response to fungal pathogens and hormone treatments. BMC Plant Biol. 2009;9(1):68.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Li W, Pang S, Lu Z, Jin B. Function and mechanism of WRKY transcription factors in abiotic stress responses of plants. Plants. 2020;9(11):1515.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Fu X, Peng B, Hassani D, Xie L, Liu H, Li Y, Chen T, Liu P, Tang Y, Li L, et al. AaWRKY9 contributes to light- and jasmonate-mediated to regulate the biosynthesis of artemisinin in Artemisia annua. New Phytol. 2021;231(5):1858–74.

    Article  CAS  PubMed  Google Scholar 

  22. Suttipanta N, Pattanaik S, Kulshrestha M, Patra B, Singh SK, Yuan L. The transcription factor CrWRKY1 positively regulates the terpenoid indole alkaloid biosynthesis in Catharanthus roseus. Plant Physiol. 2011;157(4):2081–93.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Chen Y, Zhang H, Zhang M, Zhang W, Ou Z, Peng Z, Fu C, Zhao C, Yu L. Salicylic acid-responsive factor TcWRKY33 positively regulates taxol biosynthesis in Taxus chinensis in direct and indirect ways. Front Plant Sci. 2021;12:697476.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Li X, He L, An X, Yu K, Meng N, Duan C, Pan Q-H. VviWRKY40, a WRKY transcription factor, regulates glycosylated monoterpenoid production by VviGT14 in grape berry. Genes. 2020;11:485.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Ishiguro S, Nakamura K. Characterization of a cDNA encoding a novel DNA-binding protein, SPF1, that recognizes SP8 sequences in the 5’ upstream regions of genes coding for sporamin and beta-amylase from sweet potato. Mol Gen Genet. 1994;244(6):563–71.

    Article  CAS  PubMed  Google Scholar 

  26. Yamada Y, Nishida S, Shitan N, Sato F. Genome-Wide Profiling of WRKY Genes Involved in Benzylisoquinoline Alkaloid Biosynthesis in California Poppy (Eschscholzia californica). Front Plant Sci. 2021;12:699326.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Yu H, Guo W, Yang D, Hou Z, Liang Z. Transcriptional profiles of SmWRKY family genes and their putative roles in the biosynthesis of tanshinone and phenolic acids in Salvia miltiorrhiza. Int J Mol Sci. 2018;19:1593.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Di P, Wang P, Yan M, Han P, Huang X, Yin L, Yan Y, Xu Y, Wang Y. Genome-wide characterization and analysis of WRKY transcription factors in Panax ginseng. BMC Genomics. 2021;22(1):834.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Wei H, Chen S, Niyitanga S, Liu T, Qi J, Zhang L. Genome-wide identification and expression analysis response to GA3 stresses of WRKY gene family in seed hemp (Cannabis sativa L). Gene. 2022;822:146290.

    Article  CAS  PubMed  Google Scholar 

  30. Cao X, Guo X, Yang X, Wang H, Hua W, He Y, Kang J, Wang Z. Transcriptional responses and gentiopicroside biosynthesis in methyl Jasmonate-treated Gentiana macrophylla seedlings. PLoS ONE. 2016;11(11):e0166493.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Duvaud S, Gabella C, Lisacek F, Stockinger H, Ioannidis V, Durinx C. Expasy, the Swiss bioinformatics resource portal, as designed by its users. Nucleic Acids Res. 2021;49(W1):W216–27.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Chou KC, Shen HB. Plant-mPLoc: a top-down strategy to augment the power for predicting plant protein subcellular localization. PLoS ONE. 2010;5(6):e11335.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Kumar S, Stecher G, Tamura K. MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol Biol Evol. 2016;33(7):1870–4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Chen C, Chen H, Zhang Y, Thomas HR, Frank MH, He Y, Xia R. TBtools: an integrative toolkit developed for interactive analyses of big biological data. Mol Plant. 2020;13(8):1194–202.

    Article  CAS  PubMed  Google Scholar 

  35. Bailey TL, Boden M, Buske FA, Frith M, Grant CE, Clementi L, Ren J, Li WW, Noble WS. MEME SUITE: tools for motif discovery and searching. Nucleic Acids Res. 2009;37(suppl_2):W202–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Lescot M, Déhais P, Thijs G, Marchal K, Moreau Y, Van de Peer Y, Rouzé P, Rombauts S. PlantCARE, a database of plant cis-acting regulatory elements and a portal to tools for in silico analysis of promoter sequences. Nucleic Acids Res. 2002;30(1):325–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Minoru K, Miho F, Yoko S, Masayuki K, Mari I-W. KEGG for taxonomy-based analysis of pathways and genomes. Nucleic Acids Res. 2023;51(D1):D587–92.

    Article  Google Scholar 

  38. Zhou T, Bai G, Hu Y, Ruhsam M, Yang Y, Zhao Y. De novo genome assembly of the medicinal plant Gentiana macrophylla provides insights into the genomic evolution and biosynthesis of iridoids. DNA Res. 2022;29(6):dsac034.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Yihan H, Hailing Y, Wenping H, Yaya H, Zhezhi W. Selection and validation of reference genes for quantitative real-time PCR in Gentiana macrophylla. Front Plant Sci. 2016;7:945.

    Google Scholar 

  40. Holub EB. The arms race is ancient history in Arabidopsis, the wildflower. Nat Rev Genet. 2001;2(7):516–27.

    Article  CAS  PubMed  Google Scholar 

  41. Zhao L, Ye J, Wu G-T, Peng X-J, Xia P-F, Ren Y. Gentiopicroside prevents interleukin-1 beta induced inflammation response in rat articular chondrocyte. J Ethnopharmacol. 2015;172:100–7.

    Article  CAS  PubMed  Google Scholar 

  42. Dinda B, Debnath S, Harigaya Y. Naturally occurring secoiridoids and bioactivity of naturally occurring iridoids and secoiridoids. A review, part 2. Cheminform. 2007;55(5):689–728.

    CAS  Google Scholar 

  43. Muhamad Fadzil NS, Sekar M, Gan SH, Bonam SR, Wu YS, Vaijanathappa J, Ravi S, Lum PT, Dhadde SB. Chemistry, pharmacology and therapeutic potential of Swertiamarin - a promising natural lead for new drug discovery and development. Drug Des Dev Ther. 2021;15:2721–46.

    Article  Google Scholar 

  44. Wu S, Ning Y, Zhao Y, Sun W, Thorimbert S, Dechoux L, Sollogoub M, Zhang Y. Research progress of natural product Gentiopicroside - a Secoiridoid compound. Mini-Rev Med Chem. 2017;17(1):62–77.

    Article  CAS  PubMed  Google Scholar 

  45. Wang J, Liu Y, Cai Y, Zhang F, Xia G, Xiang F. Cloning and functional analysis of geraniol 10-hydroxylase, a cytochrome P450 from Swertia mussotii Franch. Biosci Biotechnol Biochem. 2010;74(8):1583–90.

    Article  CAS  PubMed  Google Scholar 

  46. Cai Y, Yanling L, Zhenhua Z, Feng X, Fengning X, Guangmin X. High-frequency embryogenesis and regeneration of plants with high content of gentiopicroside from the Chinese medicinal plant Gentiana straminea Maxim. In Vitro Cell Dev Biol Plant: J Tissue Cult Assoc. 2009;45(6):730–9.

    Article  CAS  Google Scholar 

  47. Vom Endt D, Kijne JW, Memelink J. Transcription factors controlling plant secondary metabolism: what regulates the regulators? Phytochemistry. 2002;61(2):107–14.

    Article  Google Scholar 

  48. Liu J, Wang X, Chen Y, Liu Y, Wu Y, Ren S, Li L. Identification, evolution and expression analysis of WRKY gene family in Eucommia ulmoides. Genomics. 2021;113(5):3294–309.

    Article  CAS  PubMed  Google Scholar 

  49. Cheng Y, Luo J, Li H, Wei F, Zhang Y, Jiang H, Peng X. Identification of the WRKY gene family and characterization of stress-responsive genes in Taraxacum kok-saghyz Rodin. Int J Mol Sci. 2022;23(18):10270.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Wu SR, Gao K, Liu X, Xu J, Wei JH, Sui C. Identification of WRKY transcription factors related to Saikosaponin biosynthesis in adventitious roots of Bupleurum chinense. Chin Herb Med. 2017;9(2):8.

    Google Scholar 

  51. Ayadi M, Hanana M, Kharrat N, Merchaoui H, Marzoug RB, Lauvergeat V, Rebaï A, Mzid R. The WRKY transcription factor family in citrus: valuable and useful candidate genes for citrus breeding. Appl Biochem Biotechnol. 2016;180(3):516–43.

    Article  CAS  PubMed  Google Scholar 

  52. Zhang R, Chen Z, Zhang L, Yao W, Ji A. Genomic characterization of WRKY transcription factors related to andrographolide biosynthesis in Andrographis paniculata. Front Genet. 2021;11:601689.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Kurt F, Filiz E. Biological network analyses of WRKY transcription factor family in soybean (Glycine max) under low phosphorus treatment. J Crop Sci Biotechnol. 2020;23(2):127–36.

    Article  Google Scholar 

  54. Baranwal VK, Negi N, Khurana P. Genome-wide identification and structural, functional and evolutionary analysis of WRKY components of mulberry. Sci Rep. 2016;6:30794.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Li D, Liu P, Yu J, Wang L, Dossa K, Zhang Y, Zhou R, Wei X, Zhang X. Genome-wide analysis of WRKY gene family in the sesame genome and identification of the WRKY genes involved in responses to abiotic stresses. BMC Plant Biol. 2017;17(1):1–19.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Yamasaki K. Structural basis for sequence-specific DNA recognition by an Arabidopsis WRKY transcription factor. J Biol Chem. 2012;287(10):7683–91.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Sáenz-Mata J, Salazar-Badillo FB, Jiménez-Bremont JF. Transcriptional regulation of Arabidopsis thaliana WRKY genes under interaction with beneficial fungus Trichoderma atroviride. Acta Physiol Plant. 2014;36(5):1085–93.

    Article  Google Scholar 

  58. Van Verk MC, Pappaioannou D, Neeleman L, Bol JF, Linthorst HJM. A novel WRKY transcription factor is required for induction of PR-1a gene expression by salicylic acid and bacterial elicitors. Plant Physiol. 2008;146(4):1983–95.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Zhou QY, Tian AG, Zou HF, Xie ZM, Lei G, Huang J, Wang CM, Wang HW, Zhang JS, Chen SY. Soybean WRKY-type transcription factor genes, GmWRKY13, GmWRKY21, and GmWRKY54, confer differential tolerance to abiotic stresses in transgenic Arabidopsis plants. Plant Biotechnol J. 2008;6(5):486–503.

    Article  CAS  PubMed  Google Scholar 

  60. Schluttenhofer C, Yuan L. Regulation of specialized metabolism by WRKY transcription factors. Plant Physiol. 2015;167(2):295–306.

    Article  CAS  PubMed  Google Scholar 

  61. Chen M, Yan T, Shen Q, Lu X, Tang K. GLANDULAR TRICHOME-SPECIFIC WRKY 1 promotes artemisinin biosynthesis in Artemisia annua. New Phytol. 2017;214(1):304.

    Article  CAS  PubMed  Google Scholar 

  62. Zhang M, Chen Y, Nie L, Jin X, Liao W, Zhao S, Fu C, Yu L. Transcriptome-wide identification and screening of WRKY factors involved in the regulation of taxol biosynthesis in Taxus chinensis. Sci Rep. 2018;8(1):5197.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We would like to express our gratitude to Tao Zhou from Xi'an Jiaotong University for providing support in obtaining the genome data of G. macrophylla.

Funding

This study was partially supported by the Natural Science Foundation of China (No. 81903753, 81503237), the Key Industry Innovation Chain (Group) of Shaanxi Province (No. 2023-ZDLSF-58), the Key Research and Development Program of Shaanxi Province (No. 2022SF-089), the Natural Science Foundation of Qinghai (No. 2022-ZJ-917), the Project on Collaborative Innovation of Shaanxi Provincial Department of Education (No. 21JY011), the Key Program (A) of Shaanxi Provincial Health Commission (No. 2021A008), the Fundamental Research Funds for the Shaanxi University of Chinese Medicine (No.2017PY06), and the Subject Innovation Team of Shaanxi University of Chinese Medicine (No. 2019 YS01).

Author information

Authors and Affiliations

  1. State Key Laboratory of Research & Development of Characteristic Qin Medicine Resources (Cultivation), Coconstruction Collaborative Innovation Center for Chinese Medicinal Resources Industrialization By Shaanxi & Education Ministry, Shaanxi Innovative Drug Research Center, School of Pharmacy, Shaanxi University of Chinese Medicine, Xianyang, 712046, People’s Republic of China

    Yangyang Yin, Huanhuan Fu, Ye Yang, Yaomin Wang, Zhe Li, Yihan He & Zhenggang Yue

  2. College of Life Science, Qinghai Normal University, Xining, 810016, People’s Republic of China

    Fakai Mi & Zhenggang Yue

Authors
  1. Yangyang Yin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Huanhuan Fu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Fakai Mi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ye Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yaomin Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Zhe Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Yihan He
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Zhenggang Yue
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Y.Y.Y. conceived, designed, and performed the experiment, as well as wrote and revised the paper. H.H.F. conducted RT-qPCR analysis and analyzed the data. F.K.M. performed bioinformatics analyses. Y.Y. detected metabolites. Y.M.W. collected and processed the samples. Z.L. revised the paper. H.Y.H. conceived the experiment and revised the paper. Z.G.Y. wrote and revised the paper. All authors have read and approved the final manuscript.

Corresponding authors

Correspondence to Yihan He or Zhenggang Yue.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1: Figure S1.

Multiple sequences alignment of the conserved domain of WRKY transcription factors in G. macrophylla.

Additional file 2: Figure S2.

Phylogenetic tree of WRKYs from G. macrophylla and A. thaliana.

Additional file 3: Figure S3.

The gene structure and the distribution of conserved motifs within each GmWRKYs in G. macrophylla.

Additional file 4: Figure S4.

Chromatograms for the determination of four kinds of standards.

Additional file 5: Table S1.

Identification and protein characterization of the GmWRKY genes.

Additional file 6: Table S2.

Conserved motifs identified in WRKY transcription factors from G. macrophylla by MEME analysis.

Additional file 7: Table S3.

Gene locus number of GmWRKYs across the chromosomes of G. macrophylla.

Additional file 8: Table S4.

Tandem duplication events have been observed in the 42GmWRKY genes.

Additional file 9: Table S5.

Enzyme genes involved in the biosynthesis of secoiridoids.

Additional file 10: Table S6.

Correlation analysis results of GmWRKYs and the enzyme genes involved in secoiridoids biosynthesis.

Additional file 11: Table S7.

Regulatory elements targeted by WRKY transcription factors in the promoters of the enzyme-coding genes of the secoiridoids biosynthesis pathway.

Additional file 12: Table S8.

The contents of four representative components (loganic acid, swertiamarin, gentiopicroside and swerosides) in different tissues.

Additional file 13: Table S9.

Primer sequences of the candidate WRKYs and enzyme genes used for RT-qPCR analyses.

Additional file 14: Table S10.

The contents of the four compounds (loganic acid, swertiamarin gentiopicroside and sweroside) in G. macrophylla seedlings treated by MeJA.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yin, Y., Fu, H., Mi, F. et al. Genomic characterization of WRKY transcription factors related to secoiridoid biosynthesis in Gentiana macrophylla. BMC Plant Biol 24, 66 (2024). https://doi.org/10.1186/s12870-024-04727-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12870-024-04727-z

Keywords

BMC Plant Biology

ISSN: 1471-2229

Contact us