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PfERF106, a novel key transcription factor regulating the biosynthesis of floral terpenoids in Primula forbesii Franch

BMC Plant Biology volume 24, Article number: 851 (2024) Cite this article

Abstract

Background

Flowers can be a source of essential oils used in the manufacture of substances with high economic value. The ethylene response factor (ERF) gene family plays a key role in regulating secondary metabolite biosynthesis in plants. However, until now, little has been known about the involvement of ERF transcription factors (TFs) in floral terpenoid biosynthesis.

Results

In this study, an aromatic plant, Primula forbesii Franch., was used as research material to explore the key regulatory effects of PfERF106 on the biosynthesis of terpenoids. PfERF106, which encodes an IXb group ERF transcription factor, exhibited a consistent expression trend in the flowers of P. forbesii and was transcriptionally induced by exogenous ethylene. Transient silencing of PfERF106 in P. forbesii significantly decreased the relative contents of key floral terpenes, including (z)-β-ocimene, sabinene, β-pinene, γ-terpinene, linalool, eremophilene, α-ionone, and α-terpineol. In contrast, constitutive overexpression of PfERF106 in transgenic tobacco significantly increased the relative contents of key floral terpenes, including cis-3-hexen-1-ol, linalool, caryophyllene, cembrene, and sclareol. RNA sequencing of petals of PfERF106-silenced plants and empty-vector control plants revealed 52,711 expressed unigenes and 9,060 differentially expressed genes (DEGs). KEGG annotation analysis revealed that the DEGs were enriched for involvement in secondary metabolic biosynthetic pathways, including monoterpene and diterpene synthesis. Notably, 10 downregulated DEGs were determined to be the downstream target genes of PfERF106 affecting the biosynthesis of terpenoids in P. forbesii.

Conclusion

This study characterized the key positive regulatory effects of PfERF106 on the biosynthesis of terpenoids, indicating high-quality genetic resources for aroma improvement in P. forbesii. Thus, this study advances the artificial and precise directional regulation of metabolic engineering of aromatic substances.

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Background

Plant aromatic ingredients are widely used in the cosmetic, light, and pharmaceutical industries to enhance the economic value of products. Floral fragrances are a complex mixture of volatile secondary metabolites with aromatic properties produced by plants. They play an important role in attracting pollinators as well as preventing natural enemies and the occurrence of diseases and pests [1, 2]. At present, more than 1700 floral components have been identified. These components can be generally divided into three categories based on their biosynthetic pathways: terpenoids, aliphatic compounds and their derivatives, and benzenoids. Notably, the three categories have corresponding metabolic pathways [1, 3, 4]. Terpenoids are the largest group of volatile secondary metabolites and are produced by two biosynthesis pathways [5]. Components of the mevalonate (MVA) pathway are located in the cytosol, where they synthesize sesquiterpenoids and triterpenoids, and the 2-C-methyl-d-erythritol-4-phosphate (MEP) pathway, which occurs in the plastid and mainly synthesizes monoterpenoid and diterpenoid compounds [6,7,8]. Although these two metabolic pathways are isolated in subcellular space and the genes and enzymes in the pathways differ, the two pathways are related to each other and jointly participate in the biosynthesis of isopentenyl diphosphate (IPP), the precursor of terpenoids [9].

Transcription factors (TFs) uniquely exhibit “multi-point regulation,” in which they simultaneously participate in regulating the expression of several key genes in a given metabolic pathway-related gene cluster, leading to the regulation of secondary metabolites. This phenomenon makes up for the insufficient action of a single key enzyme gene and instances in which multiple key enzyme genes may produce constitutive lethal expression, making manipulations of TFs an excellent tool for plant metabolic engineering [10]. In recent years, researchers have cloned and identified some TFs associated with the metabolism regulation of plant terpene floral compounds, such as bHLH [11, 12], WRKY [13], and bZIP [14]. Ethylene-responsive factors (ERF) are a subfamily of the APETALA2/ethylene-responsive factor (AP2/ERF) superfamily of plant-specific transcription factors. The AP2/ERF superfamily is mainly divided into four subfamilies: DREB (dehydration reaction element binding), ERF (ethylene reaction element binding protein), AP2 (APETALA2), and RAV (related to ABI3/VP). There are also a few unclassified factor Soloists subfamilies [15,16,17,18,19,20]. The ERF transcription factor family is widespread and abundant in plants. It plays an important role in regulating plant growth and development [21]. In addition, ERF transcription factors regulate the biosynthesis of volatile secondary metabolites in plants. For example, maize (Zea mays L.) EREB58 promotes the expression of TPS10 by directly binding to the GCC-box of the TPS10 promoter, thus regulating sesquiterpene biosynthesis in leaves [22]. CitERF71 regulates the biosynthesis of geraniol in sweet oranges (Citrus sinensis L.) [23]. In fragrant ornamental plants, such as petunia (Petunia hybrida Hook.), exogenous ethylene upregulates the PhERF6 transcription factor, thereby affecting the expression of ODO1 and several floral-related genes [24]. ERF61 in osmanthus (Osmanthus fragrans Lour.) flower binds to the CCD4 promoter and stimulates CCD4 expression, thereby regulating the synthesis of β-ionone in petals [25]. In Phalaenopsis bellina Rchb.f. (Orchidaceae), PbERF1 regulates the biosynthesis of monoterpenoids in flowers [26].

Primula forbesii Franch., in the family Primulaceae, like most members of its genus, blooms for 3–4 months, beginning in early spring, and has a strong floral scent [27], which can be used as an ideal material for extracting essential oils. Previous studies have posited that there are 10 terpenes, 21 phenylpropane compounds, and 38 fatty acid derivatives among the floral components of P. forbesii. Linalool, β-ocimene, α-terpineol, and other terpenes are the key floral components of P. forbesii, and the change trend of them increases first and then decreases during the flower opening, which gives P. forbesii a unique pleasant aroma [28]. Jia et al. used RNA sequencing to reveal vital gene information regarding the biosynthesis pathway of floral terpenes during P. forbesii floral development, laying an important foundation for understanding the floral metabolism mechanisms of Primula [29]. However, the transcriptional regulation of the metabolism of floral substances in P. forbesii remains unclear, and the regulatory effects of ERF transcription factors on the synthesis of floral substances in P. forbesii have not yet been reported.

In this study, a novel ethylene response factor, which was differentially expressed and consistent with the trend in floral terpenoid content in P. forbesii, was selected based on the transcriptome data from different flower development stages of P. forbesii [29]. The gene was cloned and named PfERF106, and it was preliminarily identified as being related to the synthesis of floral terpenes. Further research showed that PfERF106 belongs to the IXb group of the ERF family and responds to induction by exogenous ethylene. Bidirectional verification tests of transient silenced homologously and heterologous overexpression revealed that PfERF106 positively regulates the biosynthesis of floral terpenoid compounds. Transcriptome sequencing revealed the specific pathways and important target genes of PfERF106 in regulating the metabolism and synthesis of terpenoids. This study provided an empirical basis for the genetic improvement of floral characters of P. forbesii.

Results

Sequence analysis of PfERF106

Herein, an AP2/ERF transcription factor exhibiting consistent expression during floral bloom was identified and named PfERF106 (GenBank: PP436709) after cloning analysis based on the transcriptome data of four flowering stages of P. forbesii (Fig. 1). The open reading frame (ORF) of the PfERF106 gene was determined to be 612 bp long and encode 203 amino acids (Supplementary Fig. 1a, b). Amino acid sequence analysis revealed that the PfERF106 gene belongs to a large family of AP2/ERF transcription factors and has an AP2/ERF conserved domain. Notably, the 14th and 19th amino acids of the domain were determined to be alanine and aspartic acid, respectively, which provided additional evidence that PfERF106 is indeed a member of the ERF subfamily of AP2/ERF transcription factors (Supplementary Fig. 1c). Further, the nuclear localization signal prediction tool NLStradamus was used to predict the nuclear localization signal in PfERF106 protein, and the prediction cutoff was set as 0.5. The amino acid sequence “GVRRRPWGKFAAEIR” at positions 99 to 113 of the PfERF106 protein was identified as the nuclear localization signal (Supplementary Fig. 1b). Protein homology retrieval and multiple sequence alignment revealed that ERF106 proteins in many plants have an AP2 domain (including YRG and RAYD elements) shared by the ERF family (Fig. 1a). Phylogenetic analysis revealed that PfERF106 is closely related to potato (Solanum tuberosum L.) StERF106 and tomato (Solanum lycopersicum L.) SpERF106 (Fig. 1b). By comparing the PfERF106 protein sequence with that of the ERF family protein sequence of A. thaliana, it was found that the PfERF106 gene belongs to group IXb of the ERF subfamily (Fig. 1c).

Fig. 1
figure 1

Gene sequence analysis. a ERF106 homologous protein sequence alignment. b Phylogenetic tree of the PfERF106 protein. The accession umbers for these sequences are as follows (CpERF106, XP_021905462.1; StERF106, XP_006365343.1; SpERF106, XP_015074942.1; GhERF106, XP_016744472.1; PeERF106, XP_011022363.1; NtERF106, XP_016481253.1; NsERF106, XP_009771892.1; NaERF106, XP_019257925.1; JcRERF106, XP_012090504.1; PfERF106, WWS35502.1). c Comparison of the PfERF106 protein with ERF family proteins of Arabidopsis thaliana L

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Expression profile of PfERF106 in P. forbesii

The spatiotemporal expression pattern of PfERF106 and its response to ethylene induction were determined (Fig. 2). PfERF106 was expressed in four tissues, namely flowers (full flowering stage), leaves, stems and roots, with the highest expression in leaves, followed by roots and stems (Fig. 2a). The quantitative real-time PCR (qRT-PCR) results revealed that the relative expression level of PfERF106 in the floral organs at the four flowering stages of P. forbesii first increased and then decreased (Fig. 2b). To investigate whether PfERF106 can respond to ethylene induction, this study measured the expression of PfERF106 after ethylene treatment at different concentrations and for different times. The exogenous ethylene treatment test showed that the relative expression of PfERF106 was significantly increased by an ethylene concentration of 10 µL/L (Fig. 2c). Therefore, the petals were subsequently treated with 10 µL/L of ethylene for 0, 2, 4, 8, 12, and 24 h. PfERF106 expression reached its peak after 4 h (Fig. 2d).

Fig. 2
figure 2

Spatiotemporal expression and response hormone of PfERF106. a Expression of PfERF106 in different tissues of P. forbesii (flowers in full flowering stage; leaves; stems; roots). b Expression of PfERF106 at different flowering stages of P. forbesii (L, Petals of the bud stage; C, first flowering stage; S, full flowering stage; M, late flowering stage). c PfERF106 response to ethylene treatment at varying concentrations. d PfERF106 response to 10 µL/L of ethylene treatment at varying timepoints. All the images were drawn using Origin 2021, and SPSS 28.0 was used for data analysis. Data are expressed as mean ± SD of three replicates. Treatments labelled with different lowercase letters were significantly different at a threshold of p < 0.05

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Confocal observation of PfERF106 subcellular localization

In order to analyze the subcellular localization of PfERF106, the plasmid p131-ERF106-YFP was transformed into Agrobacterium GV3101 by the liquid nitrogen freeze-melt method in this study. Agrobacterium was cultured overnight, centrifuged, and then resuspended (10 mmol/L MgCl2, 10 mmol/L MES, and 100 µmol/L Acetosyringone). After standing at room temperature for 3 h, suitable leaves of N. benthamiana were selected for injection, and confocal observation was performed after 3 d injection. As can be seen from Fig. 3, the fusion protein of PfERF106-YFP was localized to the nucleus.

Fig. 3
figure 3

Subcellular localization of PfERF106. Fluorescence signals were visualized using a confocal laser scanning microscope. Yellow fluorescence indicated yellow fluorescent protein (YFP). Red fluorescence indicated nuclei marker fluorescence

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Transient silencing of PfERF106 significantly inhibited terpenoid synthesis in P. forbesii

In this study, mixed infection culture consisting of TRV1 and TRV2-PfERF106, based on tobacco rattle virus (TRV), was injected into the back of the leaves of P. forbesii, and the phytoene desaturase (PDS) gene was used as a marker gene to verify the effectiveness of the system. Notably, new leaves of TRV2-PfPDS-infected plants showed obvious chlorosis; the stems changed from green to white, and the petals exhibited significant faintness of pigmentation at 6 weeks post-injection. TRV2-PfERF106- and TRV2-infected plants grew normally; the leaves and stems were a typical dark green, and the petals were pink-purple (Fig. 4a). Four PfERF106-silencing positive transgenic lines, 106-1, 106-2, 106-3, and 106-5, were identified by agarose gel electrophoresis. Notably, the silencing effect in the three PfERF106-silenced lines 106-1, 106-2, and 106-3 was better (Fig. 4b), exhibiting relative expression levels of 0.17, 0.25, and 0.24 times that of the control line, respectively.

The gas chromatography-mass spectrometry (GC-MS) results indicated that the peak height of key terpenes between the control and treatment group was significantly different; the treatment group exhibited a decreasing trend compared to the control group (Fig. 4c). Further analysis of the relative contents of key floral terpenes revealed a significant decrease in the relative contents of (z)-β-ocimene, sabinene, β-pinene, γ-terpinene, linalool, eremophilene, α-ionone, and α-terpineol in gene-silenced plants compared to control plants (Fig. 4d). The relative contents of sabinene, eremophilene, α-ionone, α-terpineol, and β-pinene were 0.11, 0.04, 0.04, 0.11, and 0.20 times those of the control group, and those of (z)-β-ocimene and γ-terpinene were 0.49 and 0.67 times those of the control group, respectively. The content of linalool, a key floral substance in P. forbesii, in the gene-silenced plants was significantly lower than that in the control group.

Additionally, qRT-PCR results revealed that the relative expression levels of PfLIS (encoding linalool synthase) and PfTPS (encoding α-terpineol synthase) in PfERF106-silenced plants were significantly lower than the corresponding levels in the control group, i.e., by 0.24 and 0.15 times, respectively. Moreover, an analysis of the relative expression of key genes involved in the terpene metabolic pathway of P. forbesii revealed significant downregulation of PfDXS2, PfTPS1, PfHDR3, PfGPPS3, PfHMGR2, and PfHMGR4 in the MEP and MVA pathways relative to the control group. The relative contents of the genes were 0.23, 0.10, 0.44, 0.78, 0.74, and 0.67 times those of the control, respectively (Fig. 4e).

Fig. 4
figure 4

Transient silencing of PfERF106 in P. forbesii. a Phenotypes of the whole plant, flowers, stems, and leaves after the transient silencing of PfERF106 in P. forbesii. b Detection of the relative expression of PfERF106 in different lines. c The floral contents of PfERF106-silenced plants were detected by GC-MS. The variation in floral content was visually demonstrated by using the empty vector plant and the line with the highest gene silencing ratio (i.e., 106-1). d Relative contents of key terpenoids in flowers of control and silenced plants. The silenced lines with three similar levels of silencing (106-1, 106-2, 106-3) were treated as three biological replicates. e Expression of key genes associated with the biosynthesis of floral terpenes. Data are expressed as means ± standard deviations of three replicates (***, p < 0.001; **, p < 0.01; *, p < 0.05)

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Constitutive overexpression of PfERF106 promoted terpenoid biosynthesis in tobacco

Seven transgenic PfERF106 overexpression (OE) lines, OE-2, OE-3, OE-12, OE-13, OE-14, OE-16, and OE-19, were selected to study the effect of stable overexpression of PfERF106 on terpenoid biosynthesis in tobacco. The expression of PfERF106 in these strains was significantly higher than that of the wild type, reaching 22.08, 77.78, 21.05, 61.01, 247.13, 18.76, and 31.55 times that of the wild type, respectively (Fig. 5a). Wild-type plants with healthy growth and two OE transgenic lines with high expression levels of PfERF106 were selected for subsequent experiments. Plant phenotype observations revealed that the OE-14 line, which had the highest PfERF106 expression level, flowered first, while the OE-13 line flowered slightly later. Notably, both lines flowered earlier than wild-type tobacco (Fig. 5b).

GC-MS results revealed that the peak height of key terpenes in OE transgenic tobacco was significantly different from that of wild-type tobacco. Moreover, there was an increasing trend in the treatment group compared to the control group (Fig. 5c). The relative contents of key terpene substances, such as cis-3-hexen-1-ol, linalool, caryophyllene, cembrene, and sclareol, in OE transgenic tobacco petals were significantly increased compared to the control (Fig. 5d). An increase in the relative expression level of PfERF106 significantly increased the relative contents of key terpene substances. Among them, the relative contents of cis-3-hexen-1-ol, caryophyllene, cembrene, and sclareol in OE-13 and OE-14 lines were 1.93 and 5.43 times, 4.84 and 18.23 times, 1.62 and 5.01 times, and 1.11 and 5.16 times those of the control, respectively. Notably, the change of linalool content in OE-13 and OE-14 strains was the most significant, reaching 13.68 and 35.75 times that of the control, respectively.

Fig. 5
figure 5

Constitutive overexpression of PfERF106 in tobacco (WT, wild type; OE, overexpression). a Detection of the relative expression of PfERF106 in different lines. b Phenotypes of the whole plant and flowers after constitutive overexpression of PfERF106 in tobacco. c The floral content of PfERF106-overexpression plants was detected by gas chromatography-mass spectrometry. The variation in floral content was visually demonstrated by using the wild-type plant and the line with the highest gene overexpression ratio (OE-14). d Relative contents of key terpenoids in flowers of control and overexpression plants

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Prediction of downstream PfERF106 gene targets

Data assembly and annotation

RNA-seq was used to establish a transcriptome database of PfERF106-silenced lines and empty-vector control lines of P. forbesii. The total number of transcripts obtained after screening was 114,690, while the total length of the sequences was 153,500,473 bp. The maximum transcript length was 16,868 bp. The N50 value (i.e., the length cutoff for the longest assembled sequences that contain 50% of the total transcriptome length) was 1,904 bp, and the total number of sequences longer than this was 26,124. Similarly, the N90 value was 609 bp, and the total number of longer sequences was 79,431. In addition, the average GC content of all sequences was 39.7%. A total of 52,711 unigenes were obtained after sequence assembly using Trinity (v2.15.1) software. The total sequence length of the unigenes was 60,150,613 bp, with a maximum sequence length of 16,868 bp and an N50 of 1,772 bp. The total number of sequences with a length greater than N50 and N90 were 10,568 and 36,819, respectively. In addition, the average GC content of all the obtained unigene sequences was 39.11% (Table 1).

Table 1 Assembly results of P. forbesii transcriptome
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NR, GO, KEGG, Pfam, eggNOG, and Swiss-Prot databases were used to annotate the functions of the unigenes (Table 2). Notably, 25,960 unigenes were successfully annotated using the NR database, accounting for 49.25% of the total number of unigenes. The unigenes successfully annotated using the GO, KEGG, Pfam, eggNOG, and Swiss-Prot databases were 15,782, 8,566, 16,856, 24,626, and 20,182, accounting for 29.94%, 16.25%, 31.98%, 46.72%, and 38.29% of the total number of the unigenes, respectively. The number of unigenes successfully annotated using every one of the databases was 5,289, accounting for 10.03% of the total number of unigenes.

Table 2 Unigene functional annotation results among different databases
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The similarities between the gene sequences of P. forbesii and those of related species as well as the functional annotation of P. forbesii genes were obtained by comparing and annotating them using the NR database (Fig. 6a). The E-value distribution map showed that 53.95% of the annotated sequences had strong homology (0 < E-value < 10−45). The most unigene sequences were most similar to tea (Camellia sinensis L.), followed by Actinidia chinensis var. chinensis, Actinidia rufa Planch., Nyssa sinensis Oliver., and Rhododendron griersonianum Balf. f. et Forrest, Rhododendron simsii Planch., and Vitis vinifera L., in that order, accounting for 26.22%, 14.44%, 5.23%, 4.99%, 3.96%, 3.66%, and 2.19% of unigenes, respectively. The number of genes annotated for their biological process, cellular component, and molecular function in the GO database were 53,989, 17,846, and 24,397, accounting for 56.10%, 18.54%, and 25.35% of unigenes, respectively (Fig. 6b). The top five KEGG functions were metabolism, genetic information processing, environmental information processing, cellular processes, and organismal systems (Fig. 6c). Notably, the metabolism (based on KEGG annotation) of terpenoids and polyketides and biosynthesis of other secondary metabolites corresponded to 160 and 237 functional annotation results, respectively. The eggNOG database was used to annotate 2,113 unigenes as signal transduction mechanisms and 2,087 unigenes as associated with posttranslational modification, protein turnover, and chaperones. Notably, 880 unigenes were classified as involved in secondary metabolite biosynthesis, transport, and catabolism (Fig. 6d).

Fig. 6
figure 6

Annotation of the unigene functions according to different databases. a E-value and species distribution of the top BLAST hits for each unique sequence. b The annotation results of the GO database. c The annotation results of the KEGG database. d The annotation results of the eggNOG database. e A principal component analysis of the gene expression level. f Correlation analysis of the samples. GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes

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Principal component analysis and correlation analysis revealed a strong correlation between the performance of samples in silenced (M) and control plants (CK). Notably, there was high similarity in the expression patterns among the samples (Fig. 6e, f). In this study, after transcriptome sequencing of PfERF106-silenced lines and empty-vector control lines of P. forbesii, a large number of genes related to terpene synthesis were obtained by KEGG annotation analysis. To verify the reliability of transcriptome data after PfERF106-silencing, 12 differentially expressed genes, especially those related to terpenoid metabolism, were randomly selected for quantification to verify the reliability of gene expression estimates based on RNA-Seq. Notably, the qRT-PCR data for these genes was highly consistent with the fragments per kilobase of transcript per million mapped reads (FPKM) values of the RNA-seq transcriptome data (Fig. 7a). Linear regression analysis revealed a correlation of 87.58% between RNA-seq and qRT-PCR data (Fig. 7b), indicating that the transcriptome data were indeed reliable.

Fig. 7
figure 7

The qRT-PCR validation of 12 differentially expressed genes (DEGs). a The qRT-PCR analysis of 12 terpene biosynthesis-associated genes. The bar chart shows the relative gene expression based on qRT-PCR (left y-axis), while the line chart shows the fragments per kilobase of transcript per million mapped reads (FPKM) value of RNA-Seq (right y-axis). The error bar represents the standard deviation of three independent replicates. b Correlation analysis of fold-change values obtained from RNA-seq and qRT-PCR analyses. qRT-PCR, real-time quantitative reverse transcription PCR

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Analysis of genes associated with differential gene expression and terpenoid synthesis

Differential gene expression analysis identified 9,060 differentially expressed genes (DEGs): 4,534 upregulated and 4,526 downregulated genes. GO enrichment analysis of DEGs showed that secondary metabolite synthesis processes were enriched in the first 10 GO term entries among biological processes (Fig. 8a). The metabolism pathway was the most enriched KEGG pathway among the 30 pathways and had the lowest p-value. There were two types of metabolic pathways identified: diterpenoid biosynthesis and monoterpenoid biosynthesis (Fig. 8b). Notably, the top 20 KEGG pathways with the lowest false discovery rate (FDR) value had these two types of metabolic pathways (Fig. 8c). These biological processes are potentially vital to the synthesis of terpenoid floral compounds. In addition, a total of 1,236 transcription factors were differentially expressed in this study (Fig. 8d) including 60, 37, and 21 downregulated members of the ERF, bHLH, and MYB transcription factor families, respectively.

Fig. 8
figure 8

Analysis of the differentially expressed genes (DEGs). a The top 10 GO terms with the lowest p-value in each GO classification in the GO enrichment analysis of DEGs. b The top 30 pathways with the lowest p-value in KEGG annotation results of DEGs. c The top 20 pathways with the lowest false discovery rate (FDR) in the KEGG annotation results of DEGs. d Statistics of the differential expression of transcription factors. GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes

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Changes in the DEGs associated with terpenoid synthesis associated with PfERF106 silencing were further analyzed utilizing the transcriptome data to explore the regulatory effect of PfERF106 on the synthesis of floral terpenoids in P. forbesii (Table 3). Notably, 60 DEGs were annotated as participating in the synthesis of terpenoids. Among them, seven were associated with diterpenoid biosynthesis, while three were associated with monoterpenoid biosynthesis. Similarly, there were three DEGs, nine DEGs, another nine DEGs, and one DEG associated with sesquiterpenoid and triterpenoid biosynthesis, ubiquinone and other terpenoid-quinone biosynthesis, terpenoid backbone biosynthesis, and limonene and pinene degradation, respectively. In addition, there were 7, 13, and 8 DEGs associated with the terpenoid and polyketones metabolic pathways, including brassinosteroid biosynthesis, carotenoid biosynthesis, and zeatin synthesis, respectively. The DEGs were classified into MEP and MVA metabolic pathways based on the annotation information and metabolic pathways. One unigene was predicted to encode DXS in the MEP pathway, while the other unigenes were predicted to encode 4-hydroxy-3-methylbut 2-enyl diphosphate reductase (HDR), geranyl diphosphate synthase (GDPS), and nerolidol synthase (NES). In the MVA pathway, one unigene was predicted to participate in the expression of hydroxymethylglutaryl-CoA reductase (HMGR) and acetyl-CoA C-acetyltransferase (AACT) (Table 4).

Table 3 Annotation analysis and quantitative statistics of differentially expressed genes related to floral terpenoid synthesis in P. forbesii
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Table 4 Key downregulated genes of floral terpenoids involved in biosynthesis in P. forbesii
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Discussion

PfERF106 is a potential regulator of terpenoid metabolism

Plants produce special metabolites with diverse structures, such as alkaloids and terpenes, in response to biological and abiotic environmental stresses. This process is dynamically regulated by metabolic genes associated with specific pathways and usually occurs at the transcription level, mediated by transcription factors (TFs) [30,31,32]. TFs coordinate the transcription of multiple metabolic pathways and affect gene expression within the same metabolic pathway [33,34,35]. Studies have postulated that AP2/ERF is widely involved in plant biological processes and plays a vital role in regulating the biosynthesis of primary and secondary metabolites of plants, including Catharanthus roseus L [36]. and Artemisia annua L [37]. These previous results indicate that PfERF106, a member of the AP2/ERF transcription factor family, is highly likely to participate in the biosynthesis of plant secondary metabolites. Nakano et al. divided the ERF family genes of A. thaliana into 12 groups, Group I to Group X, Group VI-L, and Group Xb-L, based on their gene structure and conserved motifs [17]. Further analysis revealed that genes in Group IX of the ERF family are typically involved in the expression of defense genes in response to pathogen infection. For example, overexpression of ERF1 in A. thaliana and of Pti4 in tomato (S. lycopersicum) has been shown to enhance resistance to necrotic fungi, bacteria, and biotrophic fungi [38, 39]. In addition, relevant studies have postulated that genes in this group participate in the control of secondary metabolite synthesis by interacting with the GCC-box region in the promoter [40]. For example, Litsea cubeba Lour. LcERF19, a member of the IXb group of the ERF family, positively regulates the production of geranial and neral by binding to the LcTPS42 promoter [41]. The transcription factor CitERF71 of sweet orange (C. sinensis) belongs to Group IXa of the ERF gene family and activates the terpene synthase gene involved in (E)-geraniol synthesis [23]. These reports strongly suggest that PfERF106, a member of the IXb group of the ERF family, is highly likely to participate in the biosynthesis of floral volatiles, especially terpenes.

In this study, PfERF106 was highly expressed in the roots and leaves but expressed at a low level in stems and flowers, consistent with the observed trend of the transcription factor LcERF19, which is associated with the metabolism of geranial and neral [41]. Similarly, PhERF6 is associated with floral biosynthesis in petunias (P. hybrida) and is highly expressed in the roots and stems but expressed at a low level in the corolla [24]. These reports suggest that gene function of homologous genes in different plants often exhibit different levels of expression in different tissues, as TFs have more diverse and complex regulatory roles than key functional genes in metabolic pathways and can bind to various suitable DNA contact sites and recruit other proteins for the regulation of different functions [42].

It has been posited that AP2/ERF transcription factor members, especially members of the ERF subfamily, are involved in growth, development, stress, and various responses and can be induced by defense-related plant hormones, such as ethylene, jasmonic acid, and salicylic acid [43, 44]. For example, PhERF genes in petunias are highly expressed after 4 h and 8 h of treatment with exogenous ethylene [16]. Similarly, the present study showed that PfERF106, an ethylene response factor, can respond to exogenous ethylene treatment. Ethylene is a gaseous plant hormone involved in many physiological and biochemical reactions throughout the life processes of plants and is closely associated with the synthesis and release of plant aroma. It can affect the release of terpenoids and the expression and transcription levels of related genes in Antirrhinum majus L [45]. , P. hybrida [46, 47], and Lathyrus odoratus [48]. These results suggest that PfERF106, as a factor downstream of ethylene, may be involved in floral release in response to ethylene signals during flower development.

Transcription factors typically play a transcriptional regulatory function in the nucleus [49]. In this study, the protein encoded by PfERF106 was located in the nucleus. In addition, some proteins encoded by terpene synthase genes are usually localized to chloroplasts or cytoplasm, such as Stevia rebaudiana SrTPS1-5, which can affect monoterpenoids or sesquiterpenoids biosynthesis [50]. These results suggest that PfERF106 may be involved in the regulation of nuclear gene transcription, and then affect the expression of downstream genes such as terpene synthase genes in cytoplasm, thus affecting the biosynthesis of terpenoids.

PfERF106 positively regulated the biosynthesis of terpenoids

Virus-induced gene silencing (VIGS) is a technique that uses RNA-mediated antiviral immunity and can thus be utilized in all plants as a post-transcriptional gene silencing (PTGS) mechanism [51]. Gene silencing (TRV-VIGs) induced by tobacco rattle virus (TRV) has many advantages, such as its high silencing efficiency and long duration. It is widely used in various plants, including tomato (S. lycopersicum) [52], tobacco (Nicotiana tabacum L.) [53], and P. hybrida [54, 55].

In this study, TRV induced the silencing of PfERF106 and reduced the relative content of floral terpenoids in plants. These results are similar to those of O. fragrans OfERF61 [25] and Z. mays EREB58 [22], which also regulate the synthesis of volatile terpenoids. Similarly, SmERF128 [56] and SmERF6 [57] from Salvia miltiorrhiza Bunge and CsERF061 [58] from C. sinensis participate in the regulation of non-volatile terpenoid synthesis. These results strongly suggested that PfERF106 is positively involved in regulating the synthesis of terpene floral substances in P. forbesii.

Notably, this study found that the silencing of PfERF106 significantly reduced linalool content and PfLIS gene expression. This finding is consistent with that of Wei et al. [59], who found that transient overexpression of PpERF61 in peach (Prunus persica L.) fruit significantly increased linalool content and the expression levels of the linalool synthase genes PpTPS1 and PpTPS3, suggesting that PfERF106 affects the synthesis of linalool by upregulating the expression of the linalool synthase gene PfLIS. Although the content of linalool in the silenced strain was significantly lower than that in the control group, the decline factor was slightly lower, indicating that linalool, as the floral component with the largest relative content in P. forbesii [28], had an abundance of its substrate. The inhibited expression of a single transcription factor cannot completely block the synthesis of downstream secondary metabolites.

In addition, we found that the trend of gene expression in the terpenoid synthesis pathway was consistent with that of PfERF106 expression. This finding is consistent with that of Wang et al. [41], who showed that transient overexpression of LcERF19 in C. chinensis increased the expression levels of LcDXS, LcHMGR, and other terpenoid biosynthetic pathway genes. Similarly, transcriptomic sequencing conducted by Wan et al. [60] after treating A. annua with different forms of phosphorus revealed that several artemisinin biosynthesis genes, such as DXS, GPPS, and GGPS, were co-upregulated with 21 transcription factor family genes, including the ERF family. This finding suggested that ERF transcription factors are strongly correlated with key genes associated with terpenoid metabolic pathways and PfERF106 potentially affects the synthesis of terpene floral substances by affecting key genes in the terpene metabolic pathway of P. forbesii.

To further verify the positive regulatory effect of PfERF106 on the synthesis of terpenoids, this study found that the contents of key terpenoids were significantly increased by overexpression of PfERF106. This identification of floral gene function by both knockout and overexpression of function has also been accomplished in various plants, including P. hybrida [24] and Lilium ‘Siberia’ [61]. Notably, PfERF106 plays a role in both homologous and heterologous plants. In contrast, Zhao et al. reported transient overexpression of LcERF134 in L. cubeba increased monoterpene content, while its overexpression in tomatoes did not cause an increase in monoterpene content [62]. These contrasting results suggest that LcERF134 is a specific transcription factor, while PfERF106 is conserved in its control of the synthesis of terpenoid substances in P. forbesii. In addition, it was found that overexpression of PfERF106 could advance the flowering stage of plants. This finding is consistent with the findings of Xing et al., who found that constitutive expression of CmERF110 from Chrysanthemum morifolium Ramat. in A. thaliana accelerated plant flowering [21]. Moreover, A. thaliana AtERF110 is regulated by ethylene and participates in modulating the bolting time of flowers through protein phosphorylation [63]. Yan et al. performed transcriptome sequencing analysis on Camellia oleifera Abel. and thus identified CoERF106, a key pivotal gene closely associated with photoperiod-sensitive differential genes [64]. This finding suggests that PfERF106 overexpression in P. forbesii potentially affects the expression level of photoperiodic pathway-related genes, thereby accelerating the flowering time of tobacco.

PfERF106 is involved in several terpenoid metabolic pathways

RNA sequencing (RNA-seq) is a reliable and versatile technology widely used in biosynthesis regulation studies of plant aromatic substances, including in Prunus mume Siebold & Zucc [65]. , Hedychium coronarium J [66]. , and Cymbidium goeringii Rchb. F [67].

In the present study, through transcriptome sequencing analysis of PfERF106-silenced plants and control plants, it was found that PfERF106 affected the synthesis of various terpenoids, including both primary terpene metabolites, such as sterols, carotenoids, and hormones, and secondary or specialized terpene metabolites [68]. The present study focused on identifying downregulated DEGs that may be the downstream target genes of PfERF106 in the MEP and MVA terpenoid synthesis pathways, including DXS, HDR, GDPS, HMGR, and NES, among others. DXS genes are divided into three types, each of which exhibits different expression patterns and functions in the specific development process and organs of plants in which they are involved [69]. Type I DXS genes include the DXS1 (CLA1) gene from A. thaliana, which has been posited to have a major housekeeping function [70]. Type II DXS genes include MtDXS2 from Medicago truncatula Gaertn. and dxs2 from maize (Z. mays), whose expression is crucial to the accumulation of carotenoids in the process of plant mycorrhizalization [71, 72]. Type III DXS genes include OsDXS3 in rice (Oryza sativa L.) and PaDXS2A and PaDXS2B in Picea abies L., which are mainly involved in defense responses and the generation of secondary metabolites [73, 74]. These results indicate that the DXS gene, as the first key enzyme gene in the MEP metabolic pathway, plays an important role in the synthesis of secondary metabolites. Notably, biological processes, such as photosystem and photosynthesis GO terms, were significantly enriched in the DEG pathways. This phenomenon was attributed to the regulation of the expression of PfDXS2, a key gene that encodes proteins localized to chloroplasts in the MEP metabolic pathway of P. forbesii [29], as determined by silencing the PfERF106 gene, which affected the synthesis of volatile terpenes in flowers and plant photosynthesis.

One unigene annotated as the HDR gene was identified in the terpenoid backbone biosynthesis pathway. HDR, a key enzyme involved in the last step of the MEP pathway, synthesizes isopentenyl pyrophosphate (IPP) and dimethylallyl diphosphate (DMAPP) and plays an important role in isoprene biosynthesis [75]. Ma et al. found that overexpression of AaHDR1 in A. annua significantly increased the contents of seven sesquiterpenoids, including artemisinin and artemisinin B, and eight monoterpenoids, including α-pinene, cineol, and sabinene [76]. Similarly, a unigene annotated as the GDPS gene was identified in the MEP pathway. The PbGDPS gene in P. bellina plays a crucial role in the release of monoterpene [77], suggesting that PfGDPS may also affect the release of monoterpene in P. forbesii. Beyond the MEP pathway, two unigenes annotated as HMGR and AACT were obtained from the MVA pathway. The two unigenes play important functions in terpenoid synthesis as key rate-limiting enzymes in the MVA metabolic pathway. For example, overexpression of HMGR in N. tabacum can lead to a 3- to 10-fold increase in total sterol level [78].

One NES gene in the monoterpenoid biosynthesis pathway was identified in this study. The NES annotation in the Swiss-Prot database was obtained from strawberry (Fragaria × ananassa) FaNES1. The NES gene encodes a bifunctional monoterpene and sesquiterpene synthase, which catalyzes the production of linalool by geranyl diphosphate (GDP) and nerolidol by farnesyl diphosphate (FDP). It is thus also called linalool/nerolidol synthase (LIS/NES) [79]. Overexpression of strawberry (Fragaria × ananassa) FaNES1 in A. thaliana leaves produced free, hydroxylated, and glycosylated linalool derivatives [80, 81]. Similarly, Nagegowda et al. showed that the protein encoded by AmNES/LIS-2 in A. majus was localized to plastids, but could catalyze the formation of linalool in plastids and nerolidol in cytoplasmic pathways at the same time, and sesquiterpene synthase activity was detected in white bodies [82]. Similarly, in N. tabacum and S. tuberosum, a small amount of the sesquiterpenoid precursor FDP was found in the plastid, and monoterpenoid precursor substances were found in the cytoplasm in metabolically engineered A. thaliana [80, 83, 84]. These results collectively suggest that there is a special relationship between linalool and nerolidol synthesis and the synthesis of downstream metabolites dependent on the content and proportion of precursor substances. The NES1 gene identified in this study potentially participates in linalool synthesis, a key floral monoterpenoid in P. forbesii. The above studies indicate that the significantly downregulated terpenoid synthesis genes identified in PfERF106-silenced plants are highly likely to participate in the regulation of floral terpenoids biosynthesis of P. forbesii as key downstream target genes of PfERF106. In the future, yeast one-hybrid and dual-luciferase assays will be further used to explore which TPS gene is regulated by this transcription factor and thus affects the change in terpene content.

In addition, key differentially expressed transcription factors, such as MYB and bHLH, were also identified in this study. MYB family genes participate in the biosynthesis of floral terpenoids. For example, Guo et al. identified the Lilium ‘Siberia’ transcription factors LiMYB1, LiMYB305, and LiMYB330 as regulating terpenoid synthesis [61]. Abbas et al. found that five HcMYB genes in H. coronarium participated in the regulation of terpenoid and phenylpropane biosynthesis by activating genes involved in the biosynthesis of volatile compounds at the base of the bottom floral structure [85]. Xia et al. identified six TwMYB genes potentially involved in the regulation of terpenoid biosynthesis following a whole-genome analysis of the MYB gene family in Tripterygium wilfordii Hook. f [86]. Members of the bHLH family of transcription factors are also key regulators of plant-specific metabolites, such as the synthesis and regulation of terpenoid indole alkaloids (TIAs) in C. roseus [87]. In this study, a MYC transcription factor in the large bHLH transcription factor family was identified, suggesting the involvement of MYC family members in terpenoid synthesis in plants. For example, overexpression of the LaMYC4 gene of lavender (Lavandula angustifolia Mill.) in Arabidopsis thaliana and tobacco (N. tabacum) increased the metabolism of sesquiterpenes, including caryophyllenes, in transgenic plants [88]. CpMYC2 from Chimonanthus praecox L. is potentially involved in the positive regulation and biosynthesis of monoterpenes (linalool) and sesquiterpenes (β-caryophyllene) in transgenic plants [89]. These reports collectively suggest that the biosynthesis of linalool, a key floral component of P. forbesii, is potentially associated with MYC-class transcription factors. The TFs associated with the release of volatile compounds are strong candidates for future research.

Conclusion

In this study, PfERF106, an ethylene response factor with differential expression that consistently matched trends of floral components of terpenes in the aromatic plant P. forbesii, was identified and cloned. Bioinformatics and expression analyses were performed on the PfERF106 gene to determine its spatiotemporal expression, response to exogenous ethylene treatment, and subcellular localization. Homologous instantaneous silencing and heterologous overexpression were used to verify the function of the PfERF106 gene in the synthesis of floral terpenoids. The downstream target genes of PfERF106 were screened and predicted by RNA sequencing, laying a molecular foundation for the future improvement of floral traits in P. forbesii through genetic engineering. The molecular data generated also provide high-quality genetic resources for aroma improvement in plants. Notably, the selected functional genes and transcription factors were not functionally verified. These genes, which are primarily associated with the release of volatile compounds, will be a key focus of future research.

Materials and methods

Plant materials and growth conditions

Primula forbesii was planted in the greenhouse facilities of the College of Landscape Architecture, Sichuan Agricultural University (30◦42′N, 103◦51′E) under a daytime temperature of 18 ± 2℃, nighttime temperature of 10 ± 2℃, and photocycle of 12/12 h (day/night). Petals from the bud stage, initial flowering stage, full flowering stage, and late flowering stage, as well as leaves, stem, and roots, were used as experimental materials for tissue-specific expression and flower development stage expression experiments. Samples were placed in a pre-cooled 1.5-mL centrifuge tube, immediately frozen in liquid nitrogen, and stored at -80℃ in an ultra-low temperature freezer prior to subsequent tests. The ethylene treatment experiment was applied following the method of Liu et al. [16]. Briefly, the flowers of P. forbesii in the full flowering stage were sampled and placed in a closed environment, incubated with ethylene at different concentrations (0, 5, 10, 15, and 20 µL/L) for 10 h, and then treated with ethylene at test concentrations for 0, 2, 4, 8, 12, and 24 h. The flower organs of 8 to 10 flowers were collected at each time point, immediately frozen in liquid nitrogen, and stored at -80℃ for easy RNA extraction. Nicotiana benthamiana Domin and Nicotiana tabacum cv. ‘Samsun’ grow under an average temperature of 24℃ and a photoperiod of 12/12 h (day/night).

Gene isolation and sequence comparison analysis

The full-length coding sequence (CDS) of PfERF106 was amplified by PCR and sequenced after being cloned into a T vector. The primers that were used are listed in Supplementary Table 1 (Table S1). The NCBI database was used to predict the conserved domains of proteins encoded by PfERF106. The NLStradamus web tool (http://www.moseslab.csb.utoronto.ca/NLStradamus/) was used to predict nuclear localization signal of PfERF106. The sequences of ERF106 homologous proteins were downloaded from the GenBank. The ERF family protein sequences of Arabidopsis thaliana L. were downloaded from PlantTFDB 5.0. Amino acid sequence alignment was performed using DNAMAN 8.0, followed by the construction of a phylogenetic tree using MEGA-X, with reference to the ERF family subgroup classification of A. thaliana [17].

RNA extraction, cDNA synthesis, and qRT-PCR

Total RNA was extracted using the RNAprep Pure Plant Plus Kit (TIANGEN, Beijing, China) following the manufacturer’s instructions. The purity, concentration, and integrity of the RNA samples were detected using a NanoDrop spectrophotometer (Thermo Scientific, Waltham, MA, USA) and Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). The RNA samples were subsequently synthesized into cDNA using the Evo M-MLV reverse transcription premix kit (ACCURATE, Changsha, China). The qRT-PCR assay was performed using the SYBR Green Pro Taq HS premixed qPCR kit (ACCURATE, Changsha, China) on a Real-time quantitative PCR instrument (CFX Connect Bio-Rad, Hercules, CA, USA). Each qRT-PCR was replicated thrice, and the relative gene expression was analyzed using the 2−∆∆CT method [90]. The qRT-PCR primers are listed in Table S2, Table S6, Table S7, and Table S8, respectively.

Subcellular localization

The target gene PfERF106 was inserted into the EcoRI/SpeI site of p131-35 S-YFP using a seamless cloning method, followed by the transformation of the fusion plasmid into Agrobacterium strain GV3101. The primers for the construction of subcellular localization vectors are listed in Table S3. The Agrobacterium was prepared for injection by culturing it overnight, followed by centrifuge-mediated suspension in a solution containing 10 mmol/L MgCl2, 10 mmol/L MES, and 100 µmol/L Acetosyringone. The Agrobacterium culture was allowed to stand for 3 h in the suspension solution at room temperature and was then injected into the leaves of N. benthamiana at the 4–5-leaf stage. The tobacco leaves were sampled 3 days after injection and observed under a confocal laser microscope (TCS SP8, Leica, Wetzlar, Germany). The excitation and emission wavelengths of yellow fluorescent protein (YFP) were 514 nm and 525–575 nm, while those of mCherry were 587 nm and 600–650 nm, respectively.

Transient silencing of PfERF106 in P. forbesii

The PfERF106-silenced line of P. forbesii was obtained as described by Fu et al. using tobacco rattle virus (TRV) as a VIGS vector [91]. The primer sequences used for TRV vector construction are listed in Table S4. The infection solution prepared in advance (sterile water containing 10 mmol/L MES, 10 mmol/L MgCl2, and 200 µmol/L Acetosyringone) was mixed with the Agrobacterium obtained after centrifugation to obtain a bacterial solution with a concentration of OD600 = 1.0. The bacterial solution containing TRV2-PfPDS and TRV2-PfERF106 was left to stand for 3–4 h at room temperature. It was then mixed with the bacterial solution containing TRV1 at a ratio of 1:1 (V:V), and the mixture was subsequently slowly injected into the back of the leaves of P. forbesii until the leaves showed signs of impregnation. PCR-positive identification and expression level detection of transgenic strains were conducted after flowering (40 d post-infection). The primers used are listed in Table S5 and Table S2. Fresh petal samples (0.3 g) were placed in a 20-mL headspace bottle, followed by the addition of 5 µL of 0.5% ethyl caprate (anhydrous ethanol dissolved) as the internal standard. The volatile floral components were extracted following the method of Jia et al. [29] and determined by solid phase microextraction-gas chromatography-mass spectrometry (SPME-GC-MS). Each strain was measured thrice, and the relative content of each floral component was subsequently calculated using the method of Sheng et al. [92]. The mass fraction of each component was calculated using the following formula: Relative content of each component (µg/g, FW) = (peak area of each component/internal standard peak area) × (internal standard concentration × internal standard volume/sample mass). The key genes for terpenoid synthesis in P. forbesii were selected for expression detection, and the primer sequences are shown in Table S7.

Constitutive overexpression of PfERF106 in tobacco

The transformation vector containing PfERF106 (pCAMBIA2301-PfERF106) was transformed into Agrobacterium strain GV3101 using the leaf disk transformation method to overexpress PfERF106 in N. tabacum constitutively. Leaves were infected with the Agrobacterium and kept in the dark for 24 h. Callus growth was subsequently induced in a medium supplemented with 50 mg/L kanamycin B and 400 mg/L cephalosporin. The callus was transferred to the screening and differentiation medium 30–45 d later to induce bud formation. The buds were then placed in Murashige and Skoog medium to induce root formation, after which the well-rooted seedlings were planted in soil in a greenhouse. The transformed plants were identified by PCR and analyzed by qRT-PCR to verify the relative expression of PfERF106 in positive transgenic plants. The primers used are listed in Table S6. Fresh petal samples of wild-type tobacco and two independent transgenic tobacco lines with high PfERF106 expression were harvested at the full flowering stage for volatile component analysis and quantification.

Transcriptome sequencing analysis

RNA was extracted from PfERF106-silenced transgenic lines and empty-vector control lines, synthesized into cDNA using the cDNA Synthesis kit following the manufacturer’s protocol (Illumina, San Diego, CA, USA), and used to construct six libraries. The library quality was tested using the Agilent 2100 Bioanalyzer (Agilent, 2100) and Agilent High Sensitivity DNA Kit (Agilent, 5067 − 4626). The cDNA libraries were paired-end (PE) sequenced on a NovaSeq 6000 platform (Illumina). The raw sequence data were filtered using fastp (0.22.0) software to obtain high-quality sequences (Clean Reads). Unigene sequences were subsequently obtained by assembling the clean reads using Trinity (v2.15.1) software.

The obtained Unigenes were annotated for gene function using the NR (NCBI non-redundant protein sequences), GO (Gene Ontology), KEGG (Kyoto Encyclopedia of Genes and Genome), eggNOG (evolutionary genealogy of genes: Non-supervised Orthologous Groups), Swiss-Prot, and Pfam databases. RNA-seq by expectation maximization (RSEM v2.15) statistics were used to compare the reading values of each gene to the original expression level of each gene, while FPKM values were used to standardize the expression level. The DESeq (v1.38.3) software was used to analyze the differential gene expression based on fold change > 1.5 and p-value < 0.05 thresholds.

GO enrichment analysis was conducted with topGO (v2.50.0). The p-value was calculated using the hypergeometric distribution method (the criterion for significant enrichment was a p-value < 0.05 threshold) to identify the significantly enriched GO terms of the DEGs (among all, upregulated, and downregulated DEGs, respectively). This calculation was conducted to determine the main biological functions of the DEGs. The Cluster Profiler (v4.6.0) tool was used for the enrichment analysis of KEGG channels. Pathways exceeding a threshold of p-value < 0.05 were significantly enriched. Downregulated terpenoid synthetic genes were randomly selected for expression detection for RNA-seq data validation; the primer sequences used are shown in Table S8.

Availability of data and materials

The datasets generated for this study are available in the NCBI Sequence Read Archive ( SRA ) under bioproject No. PRJNA1083092.

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This work was supported by the National Natural Science Foundation of China (32001356).

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Authors and Affiliations

  1. College of Landscape Architecture, Sichuan Agricultural University, Chengdu, 611130, China

    Xiancai Yin, Hongchen Yang, Keying Ding, Yuanzhi Luo, Wanqing Deng, Jianwei Liao, Yuanzhi Pan, Beibei Jiang, Xue Yong & Yin Jia

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  1. Xiancai Yin
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  2. Hongchen Yang
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  4. Yuanzhi Luo
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Contributions

Y J (Yin Jia), XC Y (Xiancai Yin), and HC Y (Hongchen Yang) designed experiments; XC Y (Xiancai Yin), KY D (Keying Ding) and YZ L (Yuanzhi Luo) performed experiments; XC Y (Xiancai Yin) and HC Y (Hongchen Yang) wrote the manuscript; WQ D (Wanqing Deng) and JW L (Jianwei Liao) analyzed data; YZ P (Yuanzhi Pan), BB J (Beibei Jiang), X Y (Xue Yong) and Y J (Yin Jia) reviewed and edited the original version of the manuscript. All authors read and approved the manuscript.

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All our experiments have complied with relevant institutional, national, and international guidelines and legislation. Plant samples used in this study were cultivated by Professor Yin Jia from the College of Landscape Architecture, Sichuan Agricultural University, and have independent intellectual property rights. All methods and materials were in compliance with relevant institutional, national, and international guidelines and legislation. The plant materials don’t include any wild species at risk of extinction. We comply with relevant institutional, national, and international guidelines and legislation for plant study.

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Yin, X., Yang, H., Ding, K. et al. PfERF106, a novel key transcription factor regulating the biosynthesis of floral terpenoids in Primula forbesii Franch. BMC Plant Biol 24, 851 (2024). https://doi.org/10.1186/s12870-024-05567-7

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BMC Plant Biology

ISSN: 1471-2229

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