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Article

CbCBF2 Integrates JA and BR Signaling to Enhance Oleanolic Acid Biosynthesis in Conyza blinii H. Lév Under Cold Stress

by
Ming Yang
1,2,4,†,
Guodong Zhang
1,3,†,
Junjie Deng
2,4,
Tianrun Zheng
5 and
Moyang Liu
1,3,4,*
1
Tropical Horticultural Plant Research Center, Hainan Research Institute, Shanghai Jiao Tong University, Sanya 572000, China
2
Shanghai Collaborative Innovation Center of Agri-Seeds/School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China
3
Institute of Tropical Horticulture Research, Hainan Academy of Agricultural Sciences, Haikou 571100, China
4
Joint Center for Single Cell Biology, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China
5
School of Basic Medical Sciences, Chongqing College of Traditional Chinese Medicine, Chongqing 402760, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agronomy 2025, 15(5), 1001; https://doi.org/10.3390/agronomy15051001
Submission received: 14 March 2025 / Revised: 18 April 2025 / Accepted: 21 April 2025 / Published: 22 April 2025
(This article belongs to the Section Crop Breeding and Genetics)
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Abstract

:
Low temperature significantly contributes to the medicinal quality of Conyza blinii. The CBF/DREB1-dependent cold-responsive signaling pathway is a major contributor to plant cold stress resistance. However, whether the CBF/DREB1 signaling pathway affects the terpenoid metabolism of C. blinii under cold stress remains to be explored. Here, we systematically identified and analyzed the impact of CbCBFs on the terpenoid metabolism of C. blinii. The results showed that three CbCBFs and CbICE1 were identified based on the transcriptome. The functions significantly correlated with CbCBFs encompass plant hormones and stress responses. Co-expression analysis revealed that key genes in BR and JA signaling pathways were correlated with CbCBFs. Among them, CbCBF2 is the predominant factor under low-temperature conditions and is significantly positively correlated with oleanolic acid. Overexpression of CbCBF2 significantly upregulated the catalase gene CbβAS and increased oleanolic acid content in the leaves. These results indicate that CbCBF2 can act as a major regulatory factor to promote the synthesis of oleanolic acid by integrating JA and BR signaling under low temperature conditions.

1. Introduction

The diversity of secondary metabolites (such as terpenoids, alkaloids, and phenolic compounds) not only endows plants with the ability to resist biotic and abiotic stresses but also constitutes the material basis of their medicinal value. Compared to medicinal plants grown outside their native habitats, those cultivated or harvested in their places of origin often possess superior medicinal properties [1]. The unique environmental conditions of the native habitats ensure optimal growth and development of the medicinal plants, thereby enhancing their medicinal value [2]. Conyza blinii H. Lév. (C. blinii) is a traditional medicinal herb, and the oleanane-type terpenoids (Olas) it contains can effectively prevent and treat gastric ulcers induced by malondialdehyde and inhibit the proliferation of cervical cancer (HeLa) cells and lung cancer (SPC-A1) cells [3,4,5]. The biosynthesis of terpenoids is significantly induced by environmental factors such as low temperature [6,7], UV-B [8], and iron in soil [9].
Environmental stresses (such as low temperature, salinity, and drought) trigger multi-level physiological responses, involving ion homeostasis, membrane system remodeling, and reprogramming of cell signaling and hormone signaling networks. After plant cells are subjected to cold stress, extracellular Ca2+ enters the cell through plasma membrane channel proteins [10,11]. Subsequently, the signal is amplified and transduced to the nucleus by molecular mechanisms such as the MAPK signaling cascade, transcription factors ICE (INDUCER OF CBF EXPRESSION), and CBF (C-REPEAT BINDING FACTOR), activating the expression of downstream COR (COLD REGULATED) genes and transcription factors, including AP2/ERF, MYB, bHLH, ZFP, NAC, WRKY, VOZ, and CAMTA, regulating the balance of primary and secondary metabolism in plants [12,13,14,15,16]. Plant hormones (such as ABA, JA, and BR) regulate the expression of cold-responsive genes and metabolic redirection through synergistic or antagonistic effects, forming an integrated network of “perception-defense-adaptation” [17,18,19].
The ICE-CBF-COR signaling pathway is a core regulatory module for plant cold adaptation and has the potential for metabolic integration. In the model plant Arabidopsis thaliana, ICE1 activates its expression by binding to the CBFs promoter, and CBF proteins further induce the CORs to enhance membrane stability and osmoregulation capacity [20,21,22,23]. The CBF/DREB1 signaling pathway finely regulates plant responses to cold stress through multiple mechanisms such as sensing cold signals, activating the expression of downstream COR genes, and post-translational modification of proteins [24,25,26]. The three CBF/DREB1 genes in Arabidopsis thaliana play a semi-redundant role in cold adaptation [15,27,28,29]. Studies on the ChIP-seq of CBF transcription factors have found that the target genes of CBF are significantly enriched in functions related to hormones, light, and circadian rhythm signaling, indicating that CBFs are key integrators of endogenous and external environmental cues. CBF regulates primary metabolism (such as carbohydrate and lipid metabolism) and also indirectly influences secondary metabolic pathways through plant hormone signaling and transcription factors [30].
The terpenoid metabolic pathway includes the mevalonate (MVA) pathway and the 2-C-methyl-D-erythritol 4-phosphate (MEP) pathway [31]. The MVA pathway occurs in the cytoplasm and peroxisomes, while the MEP pathway takes place in the plastids (chloroplasts) [32]. The two metabolic pathways are closely linked by the isomerization reaction of isoprenoid diphosphate, forming a cross-metabolic pathway in the shape of an “H” [33,34]. Oleanolic acid is a pentacyclic triterpenoid compound, which is mainly accomplished through the MVA pathway [35]. The entire process starts with acetyl-CoA and involves a series of catalytic enzymes, including HMG-CoA reductase (HMGR), plant farnesyl pyrophosphate synthase (FPPS), isoprenoid diphosphate isomerase (IPPI), and β-amyrin synthase (βAS) [36]. Both chloroplast membranes and cytoplasmic membranes are susceptible to damage from cold stress. The antioxidant properties of plant secondary metabolites help maintain membrane stability, enhancing the plant’s stress tolerance [37,38,39,40].
Elucidating the CBF-mediated cold signaling-metabolism coupling mechanism may be the key to improving the quality and stress resistance of medicinal plants. This study, based on the cold-responsive transcriptome data, employed strategies such as phylogenetic tree construction and co-expression analysis, constructing a research framework of “environment-hormone-transcription factor-secondary metabolism” in C. blinii to reveal the molecular evidence of CbCBF regulation of terpenoid metabolism.

2. Materials and Methods

2.1. Plant Material and Growth Conditions

Conyza blinii H. Lév. (C. blinii) was consistent with our previous plant material [7]. Mature seeds were soaked in distilled water overnight to break dormancy. Then, the soaked seeds were placed on moistened filter paper and kept in the dark at 25 ± 2 °C for vernalization for 4–5 days. The germinated seeds were transplanted and cultivated in a soil substrate. The nutrient soil mixture with a ratio of nutrient soil:vermiculite:perlite at 12:12:1. C. blinii was cultivated in a greenhouse (temperature 25 °C ± 2 °C, photoperiod 14 h, light intensity 60 μmol m−2 s−1, humidity 50–70%) until it reached 2 months.

2.2. Nocturnal Low Temperature and Transcriptome

The overall low-temperature treatment protocol at night referred to the vernalization mechanism research protocol of Arabidopsis thaliana [41,42]. The seedlings were cultivated under light (14 h/10 h) during the day, with a cultivation temperature of 25 ± 2 °C, while the low-temperature stress at night was set at 4 °C. One week was considered a cold stress week cycle (SW), with sampling conducted at 2 weeks (SW2), 5 weeks (SW5), and 8 weeks (SW8), respectively. A total of 12 seedlings were used for the nocturnal low-temperature experiments in this study, with three biological replicates set for each cycle for RNA-seq. Samples without night-time low-temperature treatment served as the control check (CK). After the sample treatment was completed, the samples were quickly frozen in liquid nitrogen and stored in a −80 °C freezer. Subsequently, the samples were used for RNA extraction, high-throughput sequencing, and determination of compound content, among other experiments.
The transcriptome data used in this study are from published research [6], which are available for download on NCBI (BioProject ID: PRJNA718965). Due to no reference genome for C. blinii, the transcriptome sequences were annotated by following databases: NCBI (https://www.ncbi.nlm.nih.gov/) (accessed on 15 December 2024), Pfam (http://pfam.sanger.ac.uk/) (accessed on 17 December 2024), KOG/COG (http://www.ncbi.nlm.nih.gov/COG/) (accessed on 17 December 2024), and Swiss-Prot (http://www.ebi.ac.uk/uniprot/) (accessed on 18 December 2024).

2.3. Phylogenetic Tree

Amino acid sequences of AtICE1 (AT3G26744), AtCBF1 (AT4G25490), AtCBF2 (AT4G25470), AtCBF3 (AT4G25480), AtCBF4 (AT5G51990), AtDDF1 (AT1G12610), and AtDDF2 (AT1G63030) were collected from TAIR (https://www.arabidopsis.org/) (accessed on 20 December 2024). Maximum likelihood phylogenetic analysis was performed using MEGA11 (V11.0.13) software. Motif analysis of amino acid sequences was carried out using the MEME website (https://meme-suite.org/meme/) (accessed on 20 December 2024). Finally, phylogenetic tree and motif visualization analyses were conducted using TBtools (V2.149) software [43].

2.4. Differential Expression and Heatmap Analysis

Differential expression analysis was conducted based on the readcounts of genes using the R package DESeq2 (V1.48.0) [44]. Genes with an adjusted log2FoldChange (Log2FC) > 1.5 and −log10p-value (−Log10pval) > 1.3 were identified as differentially expressed genes (DEGs). The average readcounts of the CBF gene family were normalized using LOG10, and heatmaps were generated using pheatmap (https://github.com/raivokolde/pheatmap) (accessed on 19 December 2024).

2.5. Correlation Analysis

The information on plant hormone signaling pathways is from the KEGG database (https://www.kegg.jp/kegg-bin/show_pathway?ko04075) (accessed on 18 December 2024)., and the gene expression data is from the transcriptome. The correlation (cor) and p-values were calculated using the R package Hmisc (V5.2) (https://hbiostat.org/r/hmisc/) (accessed on 10 December 2024), and the results were visualized using Cytoscape (V3.10.1) [45].

2.6. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) Annotations

GO enrichment of DEGs was performed with agriGO (V2.0) [46]. KEGG annotations was performed with R package clusterProfiler (V4.16) [47].

2.7. Gene Cloning and Vector Construction

The full-length sequence of CbCBF2 was amplified by the primer (Table S1). PCR amplification conditions: 98 °C, 15 s; 58 °C, 15 s; 72 °C, 20 s. The full-length CbCBF2 was inserted into the SalⅠ and SacⅠ restriction sites of pCambia1300 (pC1300) using homologous recombination (Vazyme, Nanjing, China, C115). The recombinant pC1300-CbCBF2 plasmid was transformed into Escherichia coli DH5α competent cells, then plated on kanamycin (50 μg/mL) plates to select for positive transformants. Positive transformants were identified by PCR and final sequencing using the universal primers CaMV 35S promoter (35S)-F and NOS terminator (NOS)-R.

2.8. Transient Transformation of C. blinii Leaves

Transient overexpression was carried out with slight modifications to the previous method [6]. The pC1300-CbCBF2 vector was transformed into Agrobacterium GV3101 competent cells (WeiDi, Shanghai, China) and cultured in LB liquid medium. After removing the supernatant, resuspension buffer (containing 0.1 M MES-KOH, 0.1 M MgCl2, 150 mM acetosyringone) was added to precipitate the bacteria to an OD600 of 0.4. Leaves that had good growth after 2 months were selected to be injected. The mixture was injected into the underside of C. blinii leaves using a 1 mL syringe. After injection, the samples were kept in the dark for 24 hours and then cultured under light for 5 days. Leaves that were cultured in the same manner without injection were used as the blank control group.

2.9. Real-Time Quantitative PCR (RT-qPCR)

The procedures for RNA extraction, cDNA library acquisition, and RT-qPCR were slightly modified from the previous methods [9,48] by using 0.1 g of fresh sample ground in liquid nitrogen for RNA extraction and reverse transcribing 1 µg of total RNA into a cDNA library. The cDNA was diluted 10× before use in RT-qPCR. The housekeeping gene GAPDH (KF027475) in C. blinii was used as the internal standard. The experimental data were processed by the 2−ΔΔCT method, and each RT-qPCR experiment was performed with at least three biological replicates.

2.10. Determination of Terpenoid Content

High-performance liquid chromatography (HPLC) was used to determine the content of blinin and oleanolic acid, while a colorimetric method was employed to measure the total saponin content [7,9]. HPLC analysis was performed using the Agilent (Santa Clara, CA, USA) 1220 Infinity II liquid chromatography system. The blinin detection wavelength was 210 nm, the column temperature was 25 °C, and the mobile phase was methanol: water: acetonitrile = 40:45:15 with a flow rate of 1 mL/min. The retention time was approximately 7 min. The Ola detection wavelength was 210 nm. Gradient of the mobile phase was as follows: 0 min, water: acetonitrile = 50:50; 8 min, water: acetonitrile = 0:100; 10 min, water: acetonitrile = 0:100. The flow rate was 1 mL/min, and the column temperature was 30 °C. The whole program ran for 15 min. The content of total saponins was detected by the vanillin-perchloric acid method, with an absorbance at 544 nm [49].

3. Results

3.1. CbCBF2 Is the Most Active CBF Transcription Factor

Based on the transcriptome annotation information, a total of 17 DREB transcription factors and two ICE transcription factors were identified (Table S1). The phylogenetic analysis results indicated that cluster-16989.11183, cluster-16989.13001, cluster-16989.35637, cluster-16989.9105, and cluster-16989.4695 clustered with the AtCBFs. Cluster-16989.10930 clustered with the AtICE1/2. Amino acid motif analysis revealed that cluster-16989.11183, cluster-16989.13001, cluster-16989.35637, cluster-16989.4695, and cluster-16989.10930 shared similar motifs (Figure 1). Based on these findings, cluster-16989.11183 was named CbCBF1, cluster-16989.35637 was named CbCBF2, cluster-16989.13001 was named CbCBF3, cluster-16989.4695 was named CbCBF4, and cluster-16989.10930 was named CbICE1.
In S2W, there were a total of 1301 DEGs, of which 802 were significantly upregulated and 117 were significantly downregulated (Figure 2A, Table S2). In S5W, there were a total of 2188 DEGs, of which 1170 were significantly upregulated and 318 were significantly downregulated (Figure 2B, Table S3). In S8W, there were a total of 567 DEGs, of which 299 were significantly upregulated and 112 were significantly downregulated (Figure 2C, Table S4). Differential expression in SW2, SW5, and SW8 indicated that CBF2 was significantly upregulated in SW2 (p ≈ 0.0182) and SW5 (p ≈ 0.0049) among all CBFs (Figure 2A–C). The expression trends of all CbDREBs and CbICE were upregulated in SW2 and SW5, and relatively decreased in SW8 (Figure 2D). The normalized FPKM showed that only CbCBF2 was significantly up-regulated under cold conditions. In summary, based on the differential gene expression and normalized FPKM data, it is inferred that CbCBF2 may be the most effective cold-responsive factor among the CbCBFs.

3.2. CBF2 Is More Significantly Associated with DEGs Under Low Temperature

To verify whether CBF2 plays a more dominant regulatory role in SW2 and SW5, we first conducted an overlap analysis of DEGs in SW2 and SW5. The results showed 787 overlapping genes among the DEGs in SW2 and SW5 (Table S5). The types of these genes are mainly transcription factors, protein kinases, protein receptors, and transporters. A co-expression analysis of these genes, together with CbCBF1/2/3, revealed that CBF1/2 had a more significant correlation with the vast majority of the DEGs (Figure 3A). Subsequently, these shared DEGs with a correlation coefficient |cor| > 0.5, and p < 0.05 were further defined as high-confidence associated genes (HAGs). Finally, after screening out 391 HAGs (Table S6), GO and KEGG annotations were used to infer biological functions that highly correlated with CbCBFs. It was discovered that “plant-pathogen interaction”, “plant hormone signal transduction”, and “phenylpropanoid biosynthesis” were significantly enriched in HAGs (Figure 3B). After GO enrichment analysis, all HAGs were classified into three categories: biological process (BP), cellular component (CC), and molecular function (MF). In biological processes, “phosphorylation”, “cellular protein modification process”, and “phosphorus metabolic process” were more enriched. In the cellular component, the “proteinaceous extracellular matrix” was more enriched. In molecular function, “ion binding” and “kinase activity” were more enriched (Figure 3C). In summary, through co-expression, GO and KEGG annotation analysis, it was found that CbCBF2 may be the most active regulatory factor among the three CbCBFs, with potential regulatory functions possibly involving kinase activity, plant hormone signal transduction, and stress defense.

3.3. CBF2 Is the Main Effector Linking Plant Hormones and Terpenoids

The results from GO and KEGG also show that CbCBF2 is closely linked to plant hormone signaling pathways and protein kinases (Figure 3B,C). We explored the potential connections between key genes in plant hormone signaling pathways and CbCBF2, and further inferred the impact of CbCBF2 on the metabolism of downstream terpenoids. Based on the transcriptome annotation information of C. blinii, a total of 4 ABA, 2 JA, 3 GA, and 4 BR signaling key genes were identified (Table S7). Co-expression analysis with CBF1/2/3 revealed that ABA signaling, JA signaling, and BR signaling are positively correlated with CBFs. Among them, BRI1 (BRASSIONSTEROID INSENSITIVE 1) and BIN2 (BRASSIONSTEROID INSENSITIVE 2) showed the highest correlation with CbCBF2 (Figure 4A). Combining the previously published oleanolic acid and blinin data, it was found that among the three candidate CbCBFs, CbCBF2 is significantly positively correlated with oleanolic acid and blinin (Figure 4B). Based on the above results, it is speculated that CbCBF2 is a regulatory factor in C. blinii that integrates hormone signals under low temperatures and affects downstream terpenoid metabolism.

3.4. Overexpression of CbCBF2 Enhances the Activity of MVA Pathway

To verify the effect of CbCBF2 on terpenoid metabolism in C. blinii, the gene expression levels and terpenoid contents of leaves with transient overexpression of CbCBF2 were detected. The results showed that after overexpression of CbCBF2, there were no significant changes in the expression levels of the MEP pathway genes CbDXS (1-deoxy-D-xylulose-5-phosphate synthase), CbDXR (1-deoxy-D-xylulose-5-phosphate reductoisomerase), and CbGGPPS (Geranylgeranyl diphosphate synthase) (Figure 5A). The activity of the MVA pathway was increased, with the expression levels of the key rate-limiting enzyme genes CbHMGR (3-hydroxy-3-methylglutaryl-CoA reductase) and CbβAS (beta-amyrin synthase) being significantly upregulated (Figure 5B). Upon detection, the content of the MEP pathway metabolite blinin showed no significant change (Figure 5C). In contrast, the content of the MVA pathway metabolite oleanolic acid was significantly increased (Figure 5E). A similar upward trend was also observed in the detection of total saponins (Figure 5D).

4. Discussion

We artificially divide the cold acclimation process into three stages: the cold response phase, the signal amplification phase, and the cold acclimation phase [6]. During the cold response phase, the expression of CbCBF1 and CbCBF2 is significantly upregulated, indicating their important roles in perceiving low-temperature signals and initiating downstream defense mechanisms (Figure 2D). The expression level of CbCBF2 was more significant during the rapid response and signal amplification stages (Figure 2E), and at the same time, CbCBF2 had more significant correlations with more differentially expressed genes (DEGs). These results suggested that CbCBF2 may play a dominant role in the early stages of cold adaptation in C. blinii.
The CBFs are functionally redundant, yet specific. Some studies have shown that the three CBF genes in Arabidopsis thaliana exhibit functional redundancy in regulating cold-responsive genes [12]. Another study has indicated that CBF2 acts as a regulator of CBF1/3 [28,29]. Moreover, CBF1 can independently regulate the phyB-PIF4/PIF5 signaling module under ambient temperatures, separate from CBF2 and CBF3, to promote the elongation of the hypocotyl [20]. CBF2 and CBF3 possess various forms of functionally null mutations in wild Arabidopsis thaliana populations, whereas CBF1 almost lacks such mutations, suggesting that CBF1 may harbor unique and significant functions [12]. AtCBF4 is involved in response to drought stress and abscisic acid treatment, but not to low temperatures [50]. In this experiment, the differential expression of CBF2 was more pronounced, and its correlation with plant hormone pathway genes was stronger, indicating that CBF2 may interact more extensively with the plant hormone pathways to influence other downstream biological functions.
AtCBF target genes are significantly enriched in functions related to hormones, light, and circadian clock signals, indicating that CBF plays a key role in integrating internal and external environmental signals [30]. The HAGs annotated by GO and KEGG are also significantly enriched in functions such as plant hormones and stress defense (Figure 3A). Among them, there are 44 annotated transcription factors, including NAC, WRKY, and ERF/AP2 (Table S5). These transcription factors may serve as potential target genes of CBF, assisting CBF in amplifying cold signals and thereby enhancing the plant’s cold resistance. CBF2 possesses a greater number of target genes (2482), surpassing those of CBF1 (1945) and CBF3 (1267), suggesting that CBF2 may play a more dominant role in cold response [30]. In this experiment, CbCBF2 also exhibited similar characteristics. CBF proteins bind to genes related to lipid metabolism and sugar metabolism, such as PLC1, DGK1/2, AMY3, BAM1, TPS8, TPS11, SUS1, and STP1 [30]. The expression of these genes may play an important role in the establishment of acquired freezing tolerance in plants. CBF may indirectly affect secondary metabolism by regulating other transcription factors or by enhancing the stability of the plasma membrane through the regulation of COR gene expression.
BR and JA serve as negative regulatory signals for CBF. BIN2 induces the ubiquitination and degradation of ICE1 through phosphorylation, thereby initiating the expression of CBF [51,52]. JAZ1 and JAZ4 can also inhibit the transcriptional activity of ICE1, thus suppressing the expression of CBF under cold stress [53,54]. Downstream of CBF, CBF target genes are significantly enriched in the ABA and JA signaling pathways (Figure 4B), indicating that CBF may influence the plant’s cold response by regulating ABA-related genes. For example, CBF binds to the promoters of ABA biosynthesis enzymes (such as NCED2, NCED3, NCED5) and ABA metabolism enzymes (such as CYP707A3, CYP707A4) [30]. CBF possesses mechanisms to integrate the regulation of multiple hormones at different signal transduction positions, enabling plants to finely regulate their physiological processes under adverse conditions, thereby enhancing their survival and adaptability [26].

5. Conclusions

This study indicates that under low-temperature stress, CbCBF2 acts as a principal regulatory factor, integrating jasmonic acid and brassinosteroid signaling to promote the biosynthesis of oleanolic acid, which helps C. blinii adapt to low-temperature environments.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy15051001/s1, Table S1: Phylogenetic gene ID; Table S2: DEGs in SW2; Table S3: DEGs in SW5; Table S4: DEGs in SW8; Table S5: Overlap genes in SW2 and SW5; Table S6: Correlation coefficients and p-values of HAGs; Table S7: Plant hormones pathway genes in C. blinii.

Author Contributions

Data curation, T.Z.; Funding acquisition, M.L.; Supervision, M.L.; Writing—original draft, M.Y.; Writing—review and editing, G.Z. and J.D. All authors will be updated at each stage of manuscript processing, including submission, revision, and revision reminder, via emails from our system or the assigned Assistant Editor. All authors have read and agreed to the published version of the manuscript.

Funding

This research was sponsored by the National Natural Science Foundation of China (grant ID 32101682; 32170333; 32360414; 32122076), the Scientific and technological innovation team of Hainan Academy of Agricultural Sciences (grant ID HAAS2023TDYD05), the Hainan Province science and technology talent innovation project (grant ID KJRC2023C24), and the Basic scientific research business expenses of HAAS (grant ID ITH2024ZD02).

Data Availability Statement

The original contributions presented in this study are included in the article/Supplementary Materials. Further inquiries can be directed to the corresponding author(s).

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Phylogenetic analysis. (A) Transcriptome analysis of the DREB family transcription factors in C. blinii and evolutionary analysis with AtCBFs and AtCIE1/2. AtDDF1 and AtDDF2, annotated by TAIR as members of the CBFs. Initial trees for the heuristic search were obtained automatically by applying the maximum parsimony method. (B) Motifs of all genes in the phylogenetic tree. Different colors show different motifs.
Figure 1. Phylogenetic analysis. (A) Transcriptome analysis of the DREB family transcription factors in C. blinii and evolutionary analysis with AtCBFs and AtCIE1/2. AtDDF1 and AtDDF2, annotated by TAIR as members of the CBFs. Initial trees for the heuristic search were obtained automatically by applying the maximum parsimony method. (B) Motifs of all genes in the phylogenetic tree. Different colors show different motifs.
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Figure 2. The expression analysis of CbCBFs during cold stress weeks. (A–C) DEGs in SW2, SW5, and SW8. Genes with a log2FoldChange (Log2FC) > 1.5 and −log10p-value (−Log10pval) > 1.3 were defined as DEGs. Red dots represent significantly upregulated genes, green dots represent significantly downregulated genes, and blue dots represent genes with no significant change. (D) Heatmap analyzed the expression trends DREB family genes. The colors represent the readcounts of each gene after log10 normalization. Genes with similar expression trends are clustered in adjacent areas. (E) Categorized statistics of the normalized FPKM for each gene. Asterisk indicates a significant difference between the experimental and control groups (p < 0.05).
Figure 2. The expression analysis of CbCBFs during cold stress weeks. (A–C) DEGs in SW2, SW5, and SW8. Genes with a log2FoldChange (Log2FC) > 1.5 and −log10p-value (−Log10pval) > 1.3 were defined as DEGs. Red dots represent significantly upregulated genes, green dots represent significantly downregulated genes, and blue dots represent genes with no significant change. (D) Heatmap analyzed the expression trends DREB family genes. The colors represent the readcounts of each gene after log10 normalization. Genes with similar expression trends are clustered in adjacent areas. (E) Categorized statistics of the normalized FPKM for each gene. Asterisk indicates a significant difference between the experimental and control groups (p < 0.05).
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Figure 3. Exploration of the biological functions related to CBFs. (A) Schematic diagram of co-expression analysis between high-confidence associated genes (HAGs) and CBFs. Red represents positive correlation, and blue represents negative correlation. Solid lines indicate that the correlation is statistically significant (p < 0.05). (B) KEGG enrichment analysis of HAGs. (C) GO enrichment analysis of HAGs.
Figure 3. Exploration of the biological functions related to CBFs. (A) Schematic diagram of co-expression analysis between high-confidence associated genes (HAGs) and CBFs. Red represents positive correlation, and blue represents negative correlation. Solid lines indicate that the correlation is statistically significant (p < 0.05). (B) KEGG enrichment analysis of HAGs. (C) GO enrichment analysis of HAGs.
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Figure 4. Correlation analysis of CbCBFs with plant hormone signal transduction genes and terpenoids. (A) The Pearson coefficients of CbCBFs with plant hormone signal transduction genes are represented one-to-one by the color of the circles, the size of the circles indicating significance. Asterisks indicate that the correlation is statistically significant (p < 0.05). (B) Schematic diagram of co-expression analysis between plant hormone signal transduction genes, terpenoids, and CbCBF1/2/3. Red represents positive correlation, and blue represents negative correlation. Solid lines indicate that the correlation is statistically significant (p < 0.05).
Figure 4. Correlation analysis of CbCBFs with plant hormone signal transduction genes and terpenoids. (A) The Pearson coefficients of CbCBFs with plant hormone signal transduction genes are represented one-to-one by the color of the circles, the size of the circles indicating significance. Asterisks indicate that the correlation is statistically significant (p < 0.05). (B) Schematic diagram of co-expression analysis between plant hormone signal transduction genes, terpenoids, and CbCBF1/2/3. Red represents positive correlation, and blue represents negative correlation. Solid lines indicate that the correlation is statistically significant (p < 0.05).
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Figure 5. The impact of CbCBF2 on terpenoid metabolism. (A) The expression levels of key enzyme genes in the MEP pathway under the CbCBF2-OE background. (B) The expression levels of key enzyme genes in the MVA pathway under the CbCBF2-OE background. (C) The blinin content under the CbCBF2-OE background. (D) The total saponin content under the CbCBF2-OE background. (E) The oleanolic acid content under the CbCBF2-OE background. All the above experiments used transient transformation with pCambia1300 as the empty vector control. Different letters indicate significant differences at the p < 0.05 level when comparing different experimental groups according to a one-way ANOVA.
Figure 5. The impact of CbCBF2 on terpenoid metabolism. (A) The expression levels of key enzyme genes in the MEP pathway under the CbCBF2-OE background. (B) The expression levels of key enzyme genes in the MVA pathway under the CbCBF2-OE background. (C) The blinin content under the CbCBF2-OE background. (D) The total saponin content under the CbCBF2-OE background. (E) The oleanolic acid content under the CbCBF2-OE background. All the above experiments used transient transformation with pCambia1300 as the empty vector control. Different letters indicate significant differences at the p < 0.05 level when comparing different experimental groups according to a one-way ANOVA.
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Yang, M.; Zhang, G.; Deng, J.; Zheng, T.; Liu, M. CbCBF2 Integrates JA and BR Signaling to Enhance Oleanolic Acid Biosynthesis in Conyza blinii H. Lév Under Cold Stress. Agronomy 2025, 15, 1001. https://doi.org/10.3390/agronomy15051001

AMA Style

Yang M, Zhang G, Deng J, Zheng T, Liu M. CbCBF2 Integrates JA and BR Signaling to Enhance Oleanolic Acid Biosynthesis in Conyza blinii H. Lév Under Cold Stress. Agronomy. 2025; 15(5):1001. https://doi.org/10.3390/agronomy15051001

Chicago/Turabian Style

Yang, Ming, Guodong Zhang, Junjie Deng, Tianrun Zheng, and Moyang Liu. 2025. "CbCBF2 Integrates JA and BR Signaling to Enhance Oleanolic Acid Biosynthesis in Conyza blinii H. Lév Under Cold Stress" Agronomy 15, no. 5: 1001. https://doi.org/10.3390/agronomy15051001

APA Style

Yang, M., Zhang, G., Deng, J., Zheng, T., & Liu, M. (2025). CbCBF2 Integrates JA and BR Signaling to Enhance Oleanolic Acid Biosynthesis in Conyza blinii H. Lév Under Cold Stress. Agronomy, 15(5), 1001. https://doi.org/10.3390/agronomy15051001

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