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Article

Transcriptomic Analysis Reveals Calcium and Ethylene Signaling Pathway Genes in Response to Cold Stress in Cinnamomum camphora

by
Bo Bi
1,2,3,
Lingmei Shao
1,
Tong Xu
1,
Hao Du
1,3 and
Danqing Li
4,*
1
Department of Horticulture, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China
2
Crop Station, Agriculture and Rural Bureau of Qingtian County, Lishui 323900, China
3
ZJU-Hangzhou Global Scientific and Technological Innovation Centre, Hangzhou 311200, China
4
Department of Landscape Architecture, School of Civil Engineering and Architecture, Zhejiang Sci-Tech University, Hangzhou 310018, China
*
Author to whom correspondence should be addressed.
Horticulturae 2024, 10(9), 995; https://doi.org/10.3390/horticulturae10090995
Submission received: 13 August 2024 / Revised: 16 September 2024 / Accepted: 17 September 2024 / Published: 20 September 2024

Abstract

:
Cinnamomum camphora is one of the most dominant broad-leaved evergreen trees in tropical and subtropical regions. Understanding its response to cold stress is crucial for enhancing its resilience to climate changes and expanding the cultivation range. Cold stress response is a vital strategy for plants to withstand cold stress, typically involving transcriptional changes across various pathways. In this study, RNA-Sequencing (RNA-Seq) was conducted on the leaves of C. camphora subjected to different cold stress treatments (0 h, 2 h, and 12 h). Transcriptome analyses revealed that short-term cold stress treatment rapidly induced the upregulation of genes associated with calcium and ethylene signaling pathways, including GLR2.7, CaM, CPK7, and ERF1/3/4/5/7. Subsequently, 12 h cold response treatment further activated genes related to the cold response, jasmonic acid signaling pathways, and the negative regulation of cellular biosynthetic processes, such as CBF2 and CBF4. Notably, ERFs emerged as the most differentially expressed transcription factors in this study. A total of 133 ERF family members from C. camphora were identified through phylogenetic analysis, and these ERFs were classified into 12 clusters. Many of these ERFs are likely to play pivotal roles in the cold response of C. camphora, especially ERF1/3/4/5/7. These findings offer novel insights into the mechanisms underlying the cold response and present valuable candidates for further research, advancing our understanding of plant responses to cold stress.

1. Introduction

Low temperatures are a major environmental stress that restricts plant growth, development, and geographical distribution, further impacting flowering and yield in the subsequent growing season [1,2,3]. In tropical and subtropical regions, 0–15 °C chilling temperatures are the primary cold stress. Upon exposure to chilling temperatures, plants can develop enhanced freezing tolerance through a process known as cold acclimation [4]. To withstand chilling stress, plants have evolved various regulatory mechanisms, including multiple signal transduction pathways [5,6], hormone homeostasis [7], osmoprotectants [8], and reactive oxygen species (ROS) scavenging [9]. In recent years, research on the cold stress response process of evergreen woody plants has garnered increasing attention due to their significant economic, ornamental, and ecological value, as well as the impact of severe climate abnormal changes.
The regulatory mechanisms underlying the cold stress response in model plants have been extensively investigated. Numerous studies have demonstrated that the perception and transduction of cold signals are two pivotal steps in the plant cold response [10]. Low temperatures may alter the structure of the plasma membrane, leading to cytoskeletal rearrangement, a process involving the perception of ion channels, transport proteins, and membrane-localized protein kinases [11]. In plant cells, calcium signaling acts as a secondary messenger and is an early signaling molecule in the cold response [12]. Under cold stress conditions, calcium enters the cells through calcium channels and is detected using calcium sensors, which then triggers the expression of downstream genes [13]. Various calcium sensors have been identified in plants, such as CALMODULIN (CaM), CALMODULIN-LIKE (CML), CALCINEURIN B-LIKE PROTEIN (CBL), CALCIUM DEPENDENT PROTEIN KINASE (CPK), and CALCIUM DEPENDENT PROTEIN KINASE (CDPK) [14]. Furthermore, secondary signal transduction is mediated by the calcium binding protein calmodulin. For example, CALMODULIN-BINDING TRANSCRIPTION ACTIVATOR (CAMTA) is a calcium-loaded CaM-dependent transcription factor [15]. Cold-induced calcium signaling also promotes the production of ROS and the Mitogen-activated protein kinase (MAPK) cascade [16,17]. Ultimately, these pathways further regulate the downstream cold response cascade involving ICE-CBF-COR.
Phytohormones also play significant signaling roles in regulating the cold response. Increasing evidence has shown that ethylene is integral to the plant cold response, with cold stress affecting ethylene biosynthesis and signal transduction [18]. For instance, exposure to 4 °C can promote ethylene release in grape (Vitis vinifera) seedlings, and ethylene positively modulates the cold response in apples (Malus domestica) [19,20]. ETHYLENE RESPONSIVE FACTOR (ERF) family members are crucial in mediating plant cold acclimation [21]. ERF102 and ERF103 are indispensable for cold acclimation in Arabidopsis thaliana [22]. The ERF family members contain an APETALA2/ERF (AP2/ERF) domain [23]. This family is further divided into two major subfamilies: the ERF subfamily and the DEHYDRATION RESPONSE ELEMENT/DEHYDRATION-RESPONSIVE ELEMENT BINDING PROTEIN (CBF/DREB) subfamily. The role of CBF/DREB in the cold response is well-established. Simultaneously, ERFs are likely key hubs in the ethylene-mediated cold response. ERFs rely on ethylene signal-mediated cold response pathways to regulate plant freezing tolerance [20]. They can initiate the expression of downstream CBF and COLD-REGULATED (COR) genes, thereby influencing plant freezing tolerance [24]. In summary, ethylene plays a crucial regulatory role in the cold response, yet the underlying molecular mechanisms remain unclear.
Cinnamomum camphora is a broad-leaved evergreen tree belonging to the Lauraceae family, renowned as a prominent component in tropical and subtropical urban landscapes and valued for its significant economic and ornamental contributions [25]. The Lauraceae family includes approximately 45 genera and around 2500 to 3000 species. In contrast to the widespread distribution of C. camphora, most Lauraceae species are confined to tropical regions [25,26]. Li et al. (2023) [26] identified the genes responsible for cold acclimation in C. camphora through comparative genomic analysis between C. camphora and its close relative C. kanehrae, revealing the factors contributing to its dominance in subtropical urban landscapes. Studying the cold response mechanisms of C. camphora offers valuable theoretical insights and potential candidate genes to enhance the environmental adaptability of plants within the Lauraceae family. In this study, RNA-Sequencing (RNA-Seq) was conducted on C. camphora leaves subjected to different cold stress treatments. Transcriptome analysis revealed differentially expressed genes (DEGs) related to the cold response under both 2 h and 12 h cold stress responses. Our findings elucidate key pathways and genes involved in the cold response of C. camphora, providing a substantial number of candidate genes for genetic improvement to enhance cold resilience and expand the cultivation range of Lauraceae plants.

2. Materials and Methods

2.1. Plant Materials and Cold Stress Treatments

Branches with leaves were harvested from three 30-year-old C. camphora trees located in Hangzhou (30° N, 120° E), Zhejiang Province, China. Branches with leaves at 25 °C were subjected to different cold stress treatments (0 h, 2 h, and 12 h) in a chamber and were divided into three groups: CK (plants with no treatment), CA2 (2-h treatment at 4 °C), and CA12 (12-h treatment at 4 °C). After different cold stress treatments in branches of C. camphora, we randomly selected three mature C. camphora leaves from each of the branches as a biological replicate. Three biological replicates were collected, rapidly frozen in liquid nitrogen, and subsequently stored at −80 °C until further analysis.

2.2. RNA Extraction

The total RNA from C. camphora leaves was extracted using the RNAprep Pure Plant Plus Kit (DP441, Tiangen, Beijing, China). The RNA concentration and purity were quantified using a Nanodrop ND-1000 spectrophotometer (Isogen Life Science, Utrecht, The Netherlands). The quality and integrity of the RNA were evaluated using 1% agarose gel electrophoresis.

2.3. Transcriptome Analysis

RNA-Seq was conducted on C. camphora leaves subjected to various cold stress treatments (0 h, 2 h, and 12 h). Three biological replicates for each treatment were used to construct cDNA libraries following the Illumina standard operating procedure. Then, RNA-seq was performed on the Illumina X-ten platform with 150-bp paired-end reads to obtain raw data. We downloaded RNA-seq data from the NCBI BioProject database under the accession number PRJNA1000241 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1000241, accessed on 4 July 2024), which was uploaded by our team during the publication of the C. camphora genome. Genome assembly and gene annotations were downloaded from figshare (https://doi.org/10.6084/m9.figshare.20647452.v1, accessed on 4 July 2024). RNA-seq reads were filtered with FASTP (v.0.12.4) [27], mapped to genome assemblies using HiSAT2 (v.2.2.0) [28], and analyzed for transcripts per kilobase of exon model per million mapped reads (TPM) with StringTie (v.2.1.4) [29]. Transcription factors were identified using PlantTFDB v5.0 (https://planttfdb.gao-lab.org/, accessed on 10 July 2024).
DEGs were identified using RStudio with the DESeq2 R package. Genes with |log2 (fold change)| > 1 and Padj < 0.01 were classified as DEGs. The accuracy of the RNA-Seq was validated by quantitative real-time PCR (qRT-PCR). Gene ontology (GO) enrichment analysis and weighted gene co-expression network analysis (WGCNA) were conducted using RStudio, employing the topGO and WGCNA R packages, respectively.

2.4. Identification of ERF Proteins in C. camphora

To identify ERF proteins in C. camphora, HMM Search and BLAST screening were conducted using TBtools v2.110 [30]. Specifically, the domain of the ERF family, the AP2/ERF domain (PF00847), was downloaded as an hmm file from the Pfam database (http://pfam.xfam.org/, accessed on 10 July 2024). This was used as a seed for identifying ERF proteins against all protein sequences of C. camphora using the Simple HMM Search function in TBtools v2.110 (E-value threshold 0.05). BLAST screening (E-value threshold 1 × 10−5) was conducted to identify ERF proteins in C. camphora based on ERF protein sequences from Arabidopsis (derived from the TAIR database). The sequences obtained from both methods were analyzed using the CDD search tool from the NCBI website (https://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi, accessed on 12 July 2024), and the results were visualized with TBtools v2.110. Ultimately, only those sequences featuring a single AP2 domain were selected to identify all ERF proteins in C. camphora [31].

2.5. Phylogenetic Analysis

To clarify the evolutionary relationship of ERF proteins in C. camphora, a phylogenetic tree was constructed that includes all ERF proteins from both Arabidopsis and C. camphora. According to the study by Nakano et al. (2006) [31], the ERF protein sequences of Arabidopsis were downloaded from the TAIR database (http://www.arabidopsis.org/, accessed on 12 July 2024). Subsequently, multiple sequence alignment of ERF proteins from Arabidopsis and C. camphora was performed using MAFFT v7.467 with default parameters [32]. FastTree v2.1.12 was used to construct maximum-likelihood phylogenetic trees employing the JTT+CAT model [33]. MEGA 7.0 was utilized for visualizing and enhancing the phylogenetic trees [34].

2.6. Reverse Transcription and qRT-PCR Analysis

RNA (1 µg) was reverse transcribed into cDNA using the PrimeScript™ RT Reagent Kit with gDNA Eraser (TaKaRa, Kyoto, Japan). The cDNA was diluted 20-fold with deionized water and utilized as the template for qRT-PCR, following the protocol established by Wang et al. (2020) [35].
The primers used for qRT-PCR, listed in Table S1, were designed using the Primer-BLAST tool from NCBI (https://www.ncbi.nlm.nih.gov/tools/primer-blast/index.cgi, accessed on 20 July 2024), with a product length ranging from 200 to 300 bp, an annealing temperature of approximately 60 °C, and a GC content of 40% to 60%. UBC22 was used as a reference gene for normalizing gene expression levels [36]. qRT-PCR was conducted on the CFX Connect™ Real-Time PCR Detection System (Bio-Rad, Hercules, CA, USA) using the TB Green® Premix Ex Taq enzyme (TaKaRa, Kyoto, Japan). The reaction system consisted of 4 µL of 20-fold diluted cDNA, 5 µL of TB Green, and 0.5 µL 10 μmol/L each of forward and reverse primers. The reaction program was as follows: 95 °C for 2 min; then 95 °C for 5 s, 55 °C for 30 s, repeated for 39 cycles; followed by a melting curve analysis of 95 °C for 5 s, 65 °C for 5 s, and 95 °C for 5 s. The temperature increments used between 65 °C and 95 °C were set at 0.5 °C per 5 s to check the specificity of the reaction. Finally, relative gene expression levels for each sample were evaluated using the 2−ΔΔCt method [37].

2.7. Statistical Analyses

Statistical analyses were carried out utilizing SPSS 23 (IBM Corporation, Armonk, NY, USA). One-way ANOVA and Duncan’s multiple range test were employed to compare differences among various samples, with the significance threshold set at 0.05 (denoted by different letters). All data comprised a minimum of three biological replicates.

3. Results

3.1. Functional Enrichment Analysis of DEGs between Different Cold Stress Treatments

Mature leaves of C. camphora that underwent different cold stress treatments were randomly selected for phenotype observation. The results showed that there were no significant phenotype changes in mature leaves of C. camphora after different cold stress treatments, although water-soaked lesions increased with prolonged exposure to cold stress (Figure S1).
Furthermore, we obtained a total of 83.13 Gb raw data, and the average mapping rate was over 90% as calculated by HiSAT2 (v.2.2.0) [28]. RNA-Seq analysis revealed a total of 34,918 genes expressed in at least one sample [with TPM > 2]. Furthermore, a total of 1377 DEGs were identified across the different cold stress treatments, as illustrated in Figure S2. To investigate the key pathways and genes involved in the cold response of C. camphora under different cold stress treatments, GO enrichment analysis was conducted on DEGs comparing the different treatments, including CK vs. CA2, CA2 vs. CA12, and CA12 vs. CK (Figure 1). The results indicated that DEGs following 2 h cold stress treatment (CK vs. CA2) were predominantly enriched in the biological processes of “calcium ion transport”, “calcium ion transmembrane transport”, “ethylene-activated signaling pathway”, and “cellular response to hypoxia”. Compared to the 2 h cold stress treatment, after 12 h cold stress treatment DEGs (CA2 vs. CA12) were primarily involved in the biological processes of “regulation of signal transduction”, “response to cold”, and “regulation of the jasmonic acid-mediated signaling pathway”. The DEGs in the comparison between CK and CA12 were mainly enriched in the biological processes of “response to cold”, “negative regulation of cellular biosynthetic”, and “cellular response to oxygen levels”.

3.2. WGCNA—Revealed Key Pathways and Gene Responses to Cold

To identify key stage-specific modules, module-stage association analyses were conducted using all 1448 DEGs through WGCNA. In total, six distinct co-expression modules were identified (Figure 2A). Notably, MEblack and MEmidnightblue were highly correlated with the CA2 stage (correlation coefficients of 0.86 and 0.78, respectively, p < 0.01). Moreover, MEblue and MEgreenyellow showed a significant positive correlation with the CA12 stage (correlation coefficients of 0.95 and 0.73, respectively, p < 0.05). Based on the correlation between modules and stages, MEblack, MEmidnightblue, MEblue, and MEgreenyellow were identified as key modules related to the cold response.
GO enrichment analysis was conducted on all DEGs within these four key cold response-related modules (Figure 2B). The results indicated that the DEGs within cold response-related modules were predominantly enriched in the biological processes of “calcium ion transport”, “calcium ion transmembrane transport”, “ethylene-activated signaling pathway”, and “cellular response to ethylene stimulus”. This is consistent with the findings for DEGs following 2 h cold stress treatment (CK vs. CA2). Additionally, there were 218, 321, 310, and 139 genes in MEblack, MEmidnightblue, MEblue, and MEgreenyellow, respectively (Figure 2C). The gene expression patterns of MEblack and MEmidnightblue exhibited two distinct trends: one where DEGs were significantly upregulated during the CA2 stage and then downregulated back to CK stage levels during the CA12 stage; and another where DEGs were significantly downregulated during the CA2 stage and subsequently restored during the CA12 stage. The gene expression patterns of MEblue were characterized by two main trends: most DEGs showed a significant upregulation with the cold response, while a smaller portion displayed a significant downregulation. For MEgreenyellow, the gene expression pattern predominantly showed a significant upregulation with the cold response.

3.3. Impact of Cold Stress Treatment on Calcium Signaling-Related Gene Expression

The results of GO enrichment analyses and WGCNA consistently highlighted that transcriptional changes during cold stress in C. camphora were predominantly associated with the calcium and ethylene signaling pathways. Consequently, we initially visualized the stage-specific expression patterns of DEGs involved in the calcium signaling pathway (Figure 3A). The results indicated that genes encoding proteins associated with calcium ion transport were significantly upregulated at both the CA2 and CA12 stages, such as CYCLIC NUCLEOTIDE GATED CHANNEL (CNGC) and GLUTAMATE RECEPTOR (GLR) (Figure 3B). Genes encoding calcium-sensing proteins, including CaM and CML, were predominantly upregulated at the CA2 stage. Additionally, genes encoding calcium-binding sensory proteins, such as CPK, were significantly upregulated at both the CA2 and CA12 stages. Furthermore, the calcium sensor target gene CIPK was predominantly upregulated at the CA12 stage.
In addition to genes directly involved in calcium signaling, those associated with MAPK pathways were also markedly upregulated during cold stress treatment, such as MAPK/ERK KINASE KINASE (MAPKKK) and MITOGEN-ACTIVATED PROTEIN KINASE (MPK) (Figure 3B). Similarly, cold-responsive genes such as CBF were significantly upregulated at both the CA2 and CA12 stages, with a notable increase at the CA12 stage.
To further validate the expression levels of genes related to the calcium signaling pathway, qRT-PCR analyses were conducted (Figure 3C). The qRT-PCR results were in concordance with the RNA-Seq. Overall, calcium signaling pathway genes were rapidly upregulated at the CA2 stage, whereas cold response and MAPK pathway genes exhibited delayed upregulation compared to the calcium signaling pathway genes. These results suggest that the calcium signaling pathway may play a crucial role in the early cold response of C. camphora leaves.

3.4. Alterations in Gene Expression Related to Ethylene Biosynthesis and Signaling Pathways

Under cold stress treatment, significant changes were observed in genes associated with the ethylene biosynthesis and signaling pathways (Figure 4A). Specifically, the key regulatory gene in ethylene biosynthesis, ACC SYNTHASE (ACS), was markedly upregulated at both the CA2 and CA12 stages, with a particularly pronounced increase at the CA2 stage (Figure 4B). ERF family genes, which play a positive regulatory role in the ethylene signaling pathway, exhibit a variety of expression patterns (Figure 4B). The 36 differentially expressed ERF family genes can be broadly categorized into four expression patterns. The first pattern demonstrates a decrease in expression following cold stress treatment, with downregulation observed at the CA2 or CA12 stages. The second pattern reveals consistently high expression levels at both the CA2 and CA12 stages. The third pattern is characterized by a significant upregulation after 2 h cold stress treatment (CA2 stage). The fourth pattern exhibits substantial upregulation following a prolonged cold stress treatment (CA12 stage).

3.5. Phylogenetic Characterization of ERF Gene Family Members in C. camphora

To investigate the impact of cold stress treatment on the expression levels of transcription factors, the number of differentially expressed transcription factors in the four cold response-related modules was calculated (Figure 5A). Among these, the ERF, MYB DOMAIN PROTEIN (MYB), and WRKY DNA-BINDING PROTEIN (WRKY) transcription factor families exhibited the highest differential expression ratios in C. camphora.
Given that the ERF family is a large gene family of transcription factors and part of the AP2/ERF superfamily [38], the proteins of the ERF family are characterized by containing a single AP2/ERF domain. A total of 133 ERF genes from C. camphora were identified using Simple HMM Search and BLAST, with ERF proteins from Arabidopsis. Phylogenetic analysis was conducted to identify ERF genes in C. camphora (Figure 5B). The phylogenetic tree includes 133 of the AtERF protein sequences and 133 of the CcERF protein sequences, categorized into 12 main clusters. These 12 clusters were named according to the results by Nakano et al. (2006) [31] as I to X, VI-like (VI-L), and Xb-like (Xb-L). Clusters A-1 to A-6 belong to the CBF/DREB subfamily, while clusters B-1 to B-6 belong to the ERF subfamily. Additional detailed information on the CcERF proteins is available in Table S3.
qRT-PCR was performed on nine ERF subfamily members, and the results were consistent with the RNA-Seq data (Figure 5C). All nine ERF subfamily genes were markedly upregulated following 2 h cold stress treatment. Moreover, considering the phylogenetic analysis and the annotation of DEGs identified as ERF (Figure 4B), it was found that the upregulation of ERF subfamily genes occurred earlier than that of CBF/DREB subfamily genes.

4. Discussion

C. camphora is a widely distributed evergreen broadleaf tree, valued for its significant ornamental and economic value. In addition to C. camphora, many other species in the Lauraceae family possess considerable practical value. However, their limited cold tolerance restricts these species primarily to tropical regions, thereby constraining the development and utilization of Lauraceae family resources. The extensive distribution of C. camphora may be attributed to its unique cold response mechanisms. Under cold stress, plants transmit cold signals via various regulatory pathways, initiating the expression of downstream genes that subsequently regulate multiple transcriptional and metabolic processes, ultimately enhancing freezing tolerance. This study aims to explore the key regulatory pathways and genes involved in the cold stress response of C. camphora by conducting RNA-Seq on leaves subjected to different cold stress treatments.
Through GO enrichment analysis and WGCNA, we identified four key modules related to the cold response. Notably, genes in the MEblack and MEmidnightblue modules were predominantly upregulated after 2 h of 4 °C treatment, while genes in the MEblue and MEgreenyellow modules showed upregulation after 12 h of 4 °C treatment (Figure 2). Further analysis revealed that the calcium and ethylene signaling pathways are the earliest activated in the C. camphora cold response (Figure 2). Conversely, transcriptional changes in the salicylic acid, jasmonic acid, and ICE-CBF-COR cascades become prominent after 12 h cold stress treatment (Figure 6). Consistent with our findings, signaling pathways involved in the perception and transmission of cold stress signals, such as the calcium signaling pathway, have been identified in the early gene expression profiles of many plants [38,39].
Under cold stress, calcium rapidly influxes into plant cells, triggering molecular mechanisms that enable plants to adapt to the environment [40]. Exogenous calcium can enhance the cold resistance of maize (Zea mays) and tea (Camellia sinensis) [41,42]. Calcium channels and sensors have been widely studied in the cold stress response. In rice (Oryza sativa), transcriptional activation and phosphorylation of OsCNGC9 confer enhanced chilling tolerance [43]. Cold acclimation elevates the expression of tomato (Solanum lycopersicum) GLR3.3 and GLR3.5, subsequently enhancing chilling tolerance [44]. In C. camphora, the calcium channel genes CNGC and GLR were rapidly upregulated after 2 h of 4 °C treatment (Figure 3), suggesting that these genes may play a positive regulatory role in the cold response of C. camphora.
Additionally, various calcium sensors in C. camphora also respond promptly to cold stress, with significant upregulation of CaM, CML, CPK, and RGA (Figure 3). Among these, CaM is one of the most essential calcium sensors. CaM plays a crucial role in positively regulating cold resistance in tea plants [45]. In rice, OsCPK24 is upregulated in response to cold and positively regulates chilling tolerance [46]. Moreover, the CaM4/PATL1 complex, CML42, and CIPK13 positively regulate the expression of downstream CBF genes [47,48,49]. In C. camphora, the upregulation of genes in the MAPK pathway and the CBF-COR module occurs later than that of calcium channel and sensor genes, possibly because the calcium signaling pathway is more upstream in the cold response process. Based on these findings, we speculate that calcium channels and sensor proteins in C. camphora may enhance freezing tolerance by modulating downstream CBF genes.
Ethylene also plays a crucial role in plant stress resistance. Cold stress significantly induces the expression of the apple ethylene synthesis gene MdACS1, which positively modulates the apple’s responses to cold stress [20]. Similarly, a 4 °C treatment significantly induces the expression of the Gossypium hirsutum ACS gene [50]. In apple and grape seedlings, exposure to 4 °C rapidly triggers ethylene release, whereas blocking ethylene signaling reduces the sensitivity of grape seedlings to cold stress [19,20]. Cold storage also induces the expression of the LeACS2 gene and promotes ethylene synthesis in tomato fruit [51]. Conversely, ethylene negatively regulates cold tolerance in Medicago truncatula and Arabidopsis [52,53]. In this study, 2 h of 4 °C treatment rapidly induced the expression of the C. camphora ACS1 gene (Figure 4), suggesting that ethylene may positively regulate the response of C. camphora to cold stress.
ERF family members in the ethylene signaling pathway have been identified as a key regulator in plant responses to cold stress [21]. A 4 °C treatment rapidly induces the expression of MdERF1B, which encodes an ethylene signal activator, in apple seedlings. Citrus ERF1, RsERF40, BpERF13, and MdERF1B have been demonstrated to enhance cold tolerance [20,54,55,56]. Moreover, ERF102, ERF103, and ERF105 are essential for cold acclimation responses in Arabidopsis [22,57]. In grapes, the expression of VaERF057 and VaERF092 is inhibited by the ethylene biosynthesis inhibitor, thereby diminishing their roles in cold tolerance [19,58]. In this study, ERF family genes showed significant differential expression following cold treatment, especially ERF1/3/4/5/7 (Figure 4). Phylogenetic analysis indicated that most ERF subfamily genes were rapidly upregulated after 2 h of 4 °C exposure, whereas CBF/DREB subfamily genes were mainly upregulated after 12 h of 4 °C exposure. In tomato, TERF2/LeERF2 is a transcription factor that acts upstream of CBF, mediating cold tolerance by feedback-regulating ethylene biosynthesis genes [24]. Therefore, we hypothesize that ERFs such as ERF1/3/4/5/7 in C. camphora may similarly function upstream of CBF genes, responding rapidly to cold stimuli and regulating the expression of downstream CBF genes, ultimately enhancing cold tolerance. The diverse roles of ERF subfamily members in cold stress responses merit further investigation.

5. Conclusions

In this study, transcriptome analysis revealed that genes involved in calcium signaling, ethylene biosynthesis and signaling, and cold response pathways were upregulated following cold stress treatment. The 2 h cold stress treatment rapidly activated gene expression related to calcium signaling and ethylene biosynthesis and signaling pathways. In contrast, the 12 h cold stress treatment further activated processes related to the cold response, jasmonic acid signaling pathways, and the negative regulation of cellular biosynthetic processes. Additionally, this study preliminarily identified 133 ERF family members in C. camphora, which were divided into 12 clusters. qRT-PCR results indicated that many ERFs likely play a crucial role in the cold response of C. camphora leaves, especially ERF1/3/4/5/7. This study suggested that the response of C. camphora to cold stress is closely related to the calcium and ethylene signaling pathways, providing a wealth of candidate genes for further research on the cold response in C. camphora.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/horticulturae10090995/s1, Table S1: Primers used in qRT-PCR; Table S2: Gene Ontology (GO) enrichment analysis of RNA-Seq data in the cold response of Cinnamomum camphora; Table S3: Details of the ERF family members in Cinnamomum camphora; Table S4: Gene name; Figure S1: Phenotype observation of the leaves of Cinnamomum camphora under different cold stress treatments; Figure S2: Numbers of up- and down-regulated DEGs in comparisons between different cold stress treatments of Cinnamomum camphora; Figure S3: The raw figure of phylogenetic analysis of ERF family proteins in Arabidopsis thaliana and Cinnamomum camphora.

Author Contributions

Conceptualization: B.B. and D.L.; writing—original draft preparation, B.B.; investigation, D.L., B.B., L.S. and T.X.; form analysis and visualization, B.B., L.S. and T.X.; writing—review and editing, H.D. and D.L.; funding acquisition, D.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the China Postdoctoral Science Foundation (No. 2021M692790) and the Zhejiang Sci-Tech University Start-up Fund (No. 24052162-Y).

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 authors.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Ding, Y.; Yang, S. Surviving and thriving: How plants perceive and respond to temperature stress. Dev. Cell 2022, 57, 947–958. [Google Scholar] [CrossRef] [PubMed]
  2. Hasanuzzaman, M.; Nahar, K.; Hossain, M.S.; Mahmud, J.A.; Rahman, A.; Inafuku, M.; Oku, H.; Fujita, M. Coordinated Actions of Glyoxalase and Antioxidant Defense Systems in Conferring Abiotic Stress Tolerance in Plants. Int. J. Mol. Sci. 2017, 18, 200. [Google Scholar] [CrossRef] [PubMed]
  3. Sedaghathoor, S.; Baladeh, M.K.; Piri, S. A study on chilling hardiness of three persimmon genotypes by electrolyte leakage parameter. Technol. Hortic. 2023, 3, 10. [Google Scholar] [CrossRef]
  4. Liu, C.T.; Wang, W.; Mao, B.G.; Chu, C.C. Cold stress tolerance in rice: Physiological changes, molecular mechanism, and future prospects. Yi Chuan = Hered. 2018, 40, 171–185. [Google Scholar] [CrossRef]
  5. Guo, X.; Liu, D.; Chong, K. Cold signaling in plants: Insights into mechanisms and regulation. J. Integr. Plant Biol. 2018, 60, 745–756. [Google Scholar] [CrossRef]
  6. Liu, Q.; Ding, Y.; Shi, Y.; Ma, L.; Wang, Y.; Song, C.; Wilkins, K.A.; Davies, J.M.; Knight, H.; Knight, M.R.; et al. The calcium transporter ANNEXIN1 mediates cold-induced calcium signaling and freezing tolerance in plants. EMBO J. 2021, 40, e104559. [Google Scholar] [CrossRef]
  7. Shao, L.; Xu, T.; Wang, X.; Zhang, R.; Wang, X.; Ren, Z.; Zhang, J.; Xia, Y.; Li, D. Integrative Comparative Assessment of Cold Acclimation in Evergreen and Deciduous Iris Species. Antioxidants 2022, 11, 977. [Google Scholar] [CrossRef]
  8. Wingler, A.; Tijero, V.; Müller, M.; Yuan, B.; Munné-Bosch, S. Interactions between sucrose and jasmonate signalling in the response to cold stress. BMC Plant Biol. 2020, 20, 176. [Google Scholar] [CrossRef]
  9. You, J.; Chan, Z. ROS Regulation During Abiotic Stress Responses in Crop Plants. Front. Plant Sci. 2015, 6, 1092. [Google Scholar] [CrossRef]
  10. Nykiel, M.; Gietler, M.; Fidler, J.; Prabucka, B.; Labudda, M. Abiotic Stress Signaling and Responses in Plants. Plants 2023, 12, 3405. [Google Scholar] [CrossRef]
  11. Sangwan, V.; Orvar, B.L.; Beyerly, J.; Hirt, H.; Dhindsa, R.S. Opposite changes in membrane fluidity mimic cold and heat stress activation of distinct plant MAP kinase pathways. Plant J. Cell Mol. Biol. 2002, 31, 629–638. [Google Scholar] [CrossRef] [PubMed]
  12. Yang, T.; Poovaiah, B.W. Calcium/calmodulin-mediated signal network in plants. Trends Plant Sci. 2003, 8, 505–512. [Google Scholar] [CrossRef] [PubMed]
  13. Sanders, D.; Pelloux, J.; Brownlee, C.; Harper, J.F. Calcium at the crossroads of signaling. Plant Cell 2002, 14, S401–S417. [Google Scholar] [CrossRef] [PubMed]
  14. Kim, M.C.; Chung, W.S.; Yun, D.J.; Cho, M.J. Calcium and calmodulin-mediated regulation of gene expression in plants. Mol. Plant 2009, 2, 13–21. [Google Scholar] [CrossRef]
  15. Liu, J.; Lenzoni, G.; Knight, M.R. Design Principle for Decoding Calcium Signals to Generate Specific Gene Expression Via Transcription. Plant Physiol. 2020, 182, 1743–1761. [Google Scholar] [CrossRef] [PubMed]
  16. Yuan, P.; Yang, T.; Poovaiah, B.W. Calcium Signaling-Mediated Plant Response to Cold Stress. Int. J. Mol. Sci. 2018, 19, 3896. [Google Scholar] [CrossRef]
  17. Lv, X.; Li, H.; Chen, X.; Xiang, X.; Guo, Z.; Yu, J.; Zhou, Y. The role of calcium-dependent protein kinase in hydrogen peroxide, nitric oxide and ABA-dependent cold acclimation. J. Exp. Bot. 2018, 69, 4127–4139. [Google Scholar] [CrossRef]
  18. Huang, J.; Zhao, X.; Bürger, M.; Chory, J.; Wang, X. The role of ethylene in plant temperature stress response. Trends Plant Sci. 2023, 28, 808–824. [Google Scholar] [CrossRef]
  19. Sun, X.; Zhao, T.; Gan, S.; Ren, X.; Fang, L.; Karungo, S.K.; Wang, Y.; Chen, L.; Li, S.; Xin, H. Ethylene positively regulates cold tolerance in grapevine by modulating the expression of ETHYLENE RESPONSE FACTOR 057. Sci. Rep. 2016, 6, 24066. [Google Scholar] [CrossRef]
  20. Wang, Y.; Jiang, H.; Mao, Z.; Liu, W.; Jiang, S.; Xu, H.; Su, M.; Zhang, J.; Wang, N.; Zhang, Z.; et al. Ethylene increases the cold tolerance of apple via the MdERF1B-MdCIbHLH1 regulatory module. Plant J. Cell Mol. Biol. 2021, 106, 379–393. [Google Scholar] [CrossRef]
  21. Ritonga, F.N.; Ngatia, J.N.; Wang, Y.; Khoso, M.A.; Farooq, U.; Chen, S. AP2/ERF, an important cold stress-related transcription factor family in plants: A review. Physiol. Mol. Biol. Plants Int. J. Funct. Plant Biol. 2021, 27, 1953–1968. [Google Scholar] [CrossRef] [PubMed]
  22. Illgen, S.; Zintl, S.; Zuther, E.; Hincha, D.K.; Schmülling, T. Characterisation of the ERF102 to ERF105 genes of Arabidopsis thaliana and their role in the response to cold stress. Plant Mol. Biol. 2020, 103, 303–320. [Google Scholar] [CrossRef] [PubMed]
  23. Sakuma, Y.; Liu, Q.; Dubouzet, J.G.; Abe, H.; Shinozaki, K.; Yamaguchi-Shinozaki, K. DNA-binding specificity of the ERF/AP2 domain of Arabidopsis DREBs, transcription factors involved in dehydration- and cold-inducible gene expression. Biochem. Biophys. Res. Commun. 2002, 290, 998–1009. [Google Scholar] [CrossRef] [PubMed]
  24. Zhang, Z.; Huang, R. Enhanced tolerance to freezing in tobacco and tomato overexpressing transcription factor TERF2/LeERF2 is modulated by ethylene biosynthesis. Plant Mol. Biol. 2010, 73, 241–249. [Google Scholar] [CrossRef] [PubMed]
  25. Li, H.; Liu, B.; Davis, C.C.; Yang, Y. Plastome phylogenomics, systematics, and divergence time estimation of the Beilschmiedia group (Lauraceae). Mol. Phylogenet. Evol. 2020, 151, 106901. [Google Scholar] [CrossRef]
  26. Li, D.Q.; Lin, H.Y.; Wang, X.Y.; Bi, B.; Gao, Y.; Shao, L.M.; Zhang, R.L.; Liang, Y.W.; Xia, Y.P.; Zhao, Y.P.; et al. Genome and whole-genome resequencing of elucidate its dominance in subtropical urban landscapes. BMC Biol. 2023, 21, 192. [Google Scholar] [CrossRef]
  27. Chen, S.F.; Zhou, Y.Q.; Chen, Y.R.; Gu, J. fastp: An ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 2018, 34, 884–890. [Google Scholar] [CrossRef]
  28. Kim, D.; Paggi, J.M.; Park, C.; Bennett, C.; Salzberg, S.L. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat. Biotechnol. 2019, 37, 907–915. [Google Scholar] [CrossRef]
  29. Kovaka, S.; Zimin, A.V.; Pertea, G.M.; Razaghi, R.; Salzberg, S.L.; Pertea, M. Transcriptome assembly from long-read RNA-seq alignments with StringTie2. Genome Biol. 2019, 20, 278. [Google Scholar] [CrossRef]
  30. Chen, C.; Chen, H.; Zhang, Y.; Thomas, H.R.; Frank, M.H.; He, Y.; Xia, R. TBtools: An Integrative Toolkit Developed for Interactive Analyses of Big Biological Data. Mol. Plant 2020, 13, 1194–1202. [Google Scholar] [CrossRef]
  31. Nakano, T.; Suzuki, K.; Fujimura, T.; Shinshi, H. Genome-wide analysis of the ERF gene family in Arabidopsis and rice. Plant Physiol. 2006, 140, 411–432. [Google Scholar] [CrossRef] [PubMed]
  32. Katoh, K.; Standley, D.M. MAFFT multiple sequence alignment software version 7: Improvements in performance and usability. Mol. Biol. Evol. 2013, 30, 772–780. [Google Scholar] [CrossRef] [PubMed]
  33. Price, M.N.; Dehal, P.S.; Arkin, A.P. FastTree: Computing large minimum evolution trees with profiles instead of a distance matrix. Mol. Biol. Evol. 2009, 26, 1641–1650. [Google Scholar] [CrossRef] [PubMed]
  34. Kumar, S.; Stecher, G.; Li, M.; Knyaz, C.; Tamura, K. MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms. Mol. Biol. Evol. 2018, 35, 1547–1549. [Google Scholar] [CrossRef] [PubMed]
  35. Wang, X.; Li, D.; Zhang, D.; Shi, X.; Wu, Y.; Qi, Z.; Ding, H.; Zhu, K.; Xia, Y.; Zhang, J. Improving crucial details and selecting the optimal model for evaluating the chilling requirement of Paeonia lactiflora Pall. at low latitudes during four winters. Sci. Hortic. 2020, 265, 109175. [Google Scholar] [CrossRef]
  36. Johnson, N.; Rodriguez Diaz, D.; Ganapathy, S.; Bass, J.S.; Kutchan, T.M.; Khan, A.L.; Flavier, A.B. Evaluation of reference genes for qRT-PCR studies in the colchicine producing Gloriosa superba L. Plant Biotechnol. Rep. 2023, 17, 561–571. [Google Scholar] [CrossRef]
  37. Livak, K.J.; Schmittgen, T.D. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods 2001, 25, 402–408. [Google Scholar] [CrossRef]
  38. Li, W.; Fu, Y.; Lv, W.; Zhao, S.; Feng, H.; Shao, L.; Li, C.; Yang, J. Characterization of the early gene expression profile in Populus ussuriensis under cold stress using PacBio SMRT sequencing integrated with RNA-seq reads. Tree Physiol. 2022, 42, 646–663. [Google Scholar] [CrossRef]
  39. Wang, J.; Yang, Y.; Liu, X.; Huang, J.; Wang, Q.; Gu, J.; Lu, Y. Transcriptome profiling of the cold response and signaling pathways in Lilium lancifolium. BMC Genom. 2014, 15, 203. [Google Scholar] [CrossRef]
  40. Ren, H.; Zhang, Y.; Zhong, M.; Hussian, J.; Tang, Y.; Liu, S.; Qi, G. Calcium signaling-mediated transcriptional reprogramming during abiotic stress response in plants. Theor. Appl. Genet. 2023, 136, 210. [Google Scholar] [CrossRef]
  41. Zhang, Q.; Liu, Y.; Yu, Q.; Ma, Y.; Gu, W.; Yang, D. Physiological changes associated with enhanced cold resistance during maize (Zea mays) germination and seedling growth in response to exogenous calcium. Crop Pasture Sci. 2020, 71, 529–538. [Google Scholar] [CrossRef]
  42. Chen, S.; Wang, L.; Kang, R.; Liu, C.; Xing, L.; Wu, S.; Wang, Z.; Wu, C.; Zhou, Q.; Zhao, R.J.H. Exogenous Calcium Alleviates the Photosynthetic Inhibition and Oxidative Damage of the Tea Plant under Cold Stress. Horticulturae 2024, 10, 666. [Google Scholar] [CrossRef]
  43. Wang, J.; Ren, Y.; Liu, X.; Luo, S.; Zhang, X.; Liu, X.; Lin, Q.; Zhu, S.; Wan, H.; Yang, Y.; et al. Transcriptional activation and phosphorylation of OsCNGC9 confer enhanced chilling tolerance in rice. Mol. Plant 2021, 14, 315–329. [Google Scholar] [CrossRef] [PubMed]
  44. Li, H.; Jiang, X.; Lv, X.; Ahammed, G.J.; Guo, Z.; Qi, Z.; Yu, J.; Zhou, Y. Tomato GLR3.3 and GLR3.5 mediate cold acclimation-induced chilling tolerance by regulating apoplastic H(2) O(2) production and redox homeostasis. Plant Cell Environ. 2019, 42, 3326–3339. [Google Scholar] [CrossRef] [PubMed]
  45. Ye, K.; Shen, W.; Zhao, Y. External application of brassinolide enhances cold resistance of tea plants (Camellia sinensis L.) by integrating calcium signals. Planta 2023, 258, 114. [Google Scholar] [CrossRef]
  46. Liu, Y.; Xu, C.; Zhu, Y.; Zhang, L.; Chen, T.; Zhou, F.; Chen, H.; Lin, Y. The calcium-dependent kinase OsCPK24 functions in cold stress responses in rice. J. Integr. Plant Biol. 2018, 60, 173–188. [Google Scholar] [CrossRef] [PubMed]
  47. Sun, Q.; Huang, R.; Zhu, H.; Sun, Y.; Guo, Z. A novel Medicago truncatula calmodulin-like protein (MtCML42) regulates cold tolerance and flowering time. Plant J. Cell Mol. Biol. 2021, 108, 1069–1082. [Google Scholar] [CrossRef]
  48. Chu, M.; Li, J.; Zhang, J.; Shen, S.; Li, C.; Gao, Y.; Zhang, S. AtCaM4 interacts with a Sec14-like protein, PATL1, to regulate freezing tolerance in Arabidopsis in a CBF-independent manner. J. Exp. Bot. 2018, 69, 5241–5253. [Google Scholar] [CrossRef]
  49. Ma, X.; Gai, W.X.; Li, Y.; Yu, Y.N.; Ali, M.; Gong, Z.H. The CBL-interacting protein kinase CaCIPK13 positively regulates defence mechanisms against cold stress in pepper. J. Exp. Bot. 2022, 73, 1655–1667. [Google Scholar] [CrossRef]
  50. Li, J.; Zou, X.; Chen, G.; Meng, Y.; Ma, Q.; Chen, Q.; Wang, Z.; Li, F. Potential Roles of 1-Aminocyclopropane-1-carboxylic Acid Synthase Genes in the Response of Gossypium Species to Abiotic Stress by Genome-Wide Identification and Expression Analysis. Plants 2022, 11, 1524. [Google Scholar] [CrossRef]
  51. Zhao, R.; Xie, H.; Lv, S.; Zheng, Y.; Yu, M.; Shen, L.; Sheng, J. LeMAPK4 participated in cold-induced ethylene production in tomato fruit. J. Sci. Food Agric. 2013, 93, 1003–1009. [Google Scholar] [CrossRef] [PubMed]
  52. Zhao, M.; Liu, W.; Xia, X.; Wang, T.; Zhang, W.H. Cold acclimation-induced freezing tolerance of Medicago truncatula seedlings is negatively regulated by ethylene. Physiol. Plant. 2014, 152, 115–129. [Google Scholar] [CrossRef] [PubMed]
  53. Shi, Y.; Tian, S.; Hou, L.; Huang, X.; Zhang, X.; Guo, H.; Yang, S. Ethylene signaling negatively regulates freezing tolerance by repressing expression of CBF and type-A ARR genes in Arabidopsis. Plant Cell 2012, 24, 2578–2595. [Google Scholar] [CrossRef]
  54. Ma, Y.; Zhang, L.; Zhang, J.; Chen, J.; Wu, T.; Zhu, S.; Yan, S.; Zhao, X.; Zhong, G. Expressing a Citrus ortholog of Arabidopsis ERF1 enhanced cold-tolerance in tobacco. Sci. Hortic. 2014, 174, 65–76. [Google Scholar] [CrossRef]
  55. Li, C.; Mao, B.; Wang, K.; Xu, L.; Fan, L.; Wang, Y.; Li, Y.; Ma, Y.; Wang, L.; Liu, L. RsERF40 contributes to cold stress tolerance and cell expansion of taproot in radish (Raphanus sativus L.). Hortic. Res. 2023, 10, uhad013. [Google Scholar] [CrossRef]
  56. Lv, K.; Li, J.; Zhao, K.; Chen, S.; Nie, J.; Zhang, W.; Liu, G.; Wei, H. Overexpression of an AP2/ERF family gene, BpERF13, in birch enhances cold tolerance through upregulating CBF genes and mitigating reactive oxygen species. Plant Sci. Int. J. Exp. Plant Biol. 2020, 292, 110375. [Google Scholar] [CrossRef] [PubMed]
  57. Bolt, S.; Zuther, E.; Zintl, S.; Hincha, D.K.; Schmülling, T. ERF105 is a transcription factor gene of Arabidopsis thaliana required for freezing tolerance and cold acclimation. Plant Cell Environ. 2017, 40, 108–120. [Google Scholar] [CrossRef]
  58. Sun, X.; Zhang, L.; Wong, D.C.J.; Wang, Y.; Zhu, Z.; Xu, G.; Wang, Q.; Li, S.; Liang, Z.; Xin, H. The ethylene response factor VaERF092 from Amur grape regulates the transcription factor VaWRKY33, improving cold tolerance. Plant J. Cell Mol. Biol. 2019, 99, 988–1002. [Google Scholar] [CrossRef]
Figure 1. Enriched gene ontology (GO) terms of differentially expressed genes under different cold stress treatments in Cinnamomum camphora. The figure shows the top 15 results of biological processes of GO enrichment analysis between different treatments. The red signs highlight the biological processes that may be related to the C. camphora cold response. CK, plants without any treatment; CA2, 2-h treatment under 4 °C cold stress; CA12, 12-h treatment under 4 °C cold stress.
Figure 1. Enriched gene ontology (GO) terms of differentially expressed genes under different cold stress treatments in Cinnamomum camphora. The figure shows the top 15 results of biological processes of GO enrichment analysis between different treatments. The red signs highlight the biological processes that may be related to the C. camphora cold response. CK, plants without any treatment; CA2, 2-h treatment under 4 °C cold stress; CA12, 12-h treatment under 4 °C cold stress.
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Figure 2. Weighted gene co-expression network analysis of Cinnamomum camphora under different cold stress treatments. (A) Module-stage relationships. CK, plants without any treatment; CA2, 2-h treatment under 4 °C cold stress; CA12, 12-h treatment under 4 °C cold stress. (B) Enriched gene ontology terms of differentially expressed genes in four key modules (MEblack, MEmidnightblue, MEblue, and MEgreenyellow). The red signs highlight the biological processes that may be related to the C. camphora cold response. (C) Gene expression patterns of four key modules. The expression values were Z-scaled log2(TPM+1).
Figure 2. Weighted gene co-expression network analysis of Cinnamomum camphora under different cold stress treatments. (A) Module-stage relationships. CK, plants without any treatment; CA2, 2-h treatment under 4 °C cold stress; CA12, 12-h treatment under 4 °C cold stress. (B) Enriched gene ontology terms of differentially expressed genes in four key modules (MEblack, MEmidnightblue, MEblue, and MEgreenyellow). The red signs highlight the biological processes that may be related to the C. camphora cold response. (C) Gene expression patterns of four key modules. The expression values were Z-scaled log2(TPM+1).
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Figure 3. Expression patterns of differentially expressed genes (DEGs) involved in the calcium signaling pathway. (A) Calcium signaling-driven plant response to cold stress. The genes showing evidently different expression patterns are highlighted. (B) Heatmap of DEGs in the calcium signaling pathway of Cinnamomum camphora under different treatments. CK, plants without any treatment; CA2, 2-h treatment under 4 °C cold stress; CA12, 12-h treatment under 4 °C cold stress. The expression values were Z-scaled log2(TPM+1). (C) Quantitative real-time PCR expression levels of genes involved in the calcium signaling pathway. Error bars represent ± SE of three biological replicates. Different letters indicate significant differences at p < 0.05, following statistical analysis by one-way ANOVA. Gene names are listed in Table S4.
Figure 3. Expression patterns of differentially expressed genes (DEGs) involved in the calcium signaling pathway. (A) Calcium signaling-driven plant response to cold stress. The genes showing evidently different expression patterns are highlighted. (B) Heatmap of DEGs in the calcium signaling pathway of Cinnamomum camphora under different treatments. CK, plants without any treatment; CA2, 2-h treatment under 4 °C cold stress; CA12, 12-h treatment under 4 °C cold stress. The expression values were Z-scaled log2(TPM+1). (C) Quantitative real-time PCR expression levels of genes involved in the calcium signaling pathway. Error bars represent ± SE of three biological replicates. Different letters indicate significant differences at p < 0.05, following statistical analysis by one-way ANOVA. Gene names are listed in Table S4.
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Figure 4. Expression patterns of differentially expressed genes (DEGs) involved in the ethylene biosynthesis and signaling pathway. (A) Diagram of the ethylene-mediated cold stress response in plants; (B) Heatmap of DEGs in the ethylene biosynthesis and signaling pathway of Cinnamomum camphora under different treatments. The expression values were Z-scaled log2(TPM+1). CK, plants without any treatment; CA2, 2-h treatment under 4 °C cold stress; CA12, 12-h treatment under 4 °C cold stress. CBF_S, C-REPEAT BINDING FACTOR subfamily; ERF_S, ERF DOMAIN PROTEIN subfamily. Gene names are listed in Table S4.
Figure 4. Expression patterns of differentially expressed genes (DEGs) involved in the ethylene biosynthesis and signaling pathway. (A) Diagram of the ethylene-mediated cold stress response in plants; (B) Heatmap of DEGs in the ethylene biosynthesis and signaling pathway of Cinnamomum camphora under different treatments. The expression values were Z-scaled log2(TPM+1). CK, plants without any treatment; CA2, 2-h treatment under 4 °C cold stress; CA12, 12-h treatment under 4 °C cold stress. CBF_S, C-REPEAT BINDING FACTOR subfamily; ERF_S, ERF DOMAIN PROTEIN subfamily. Gene names are listed in Table S4.
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Figure 5. Differentially expressed transcription factor families and phylogenetic analysis of ERF proteins. (A) Transcription factor family analysis of differentially expressed genes (DEGs) in four key modules (MEblack, MEmidnightblue, MEblue, and MEgreenyellow). We have marked the transcription factor family with the highest ratio, ERF, using red signs. (B) The phylogenetic analysis of ERF family proteins in Arabidopsis thaliana and Cinnamomum camphora. (C) Quantitative real-time PCR expression levels of ERF subfamily genes. Different letters indicate significant differences at p < 0.05, following statistic analysis by one-way ANOVA. Gene names are listed in Table S4.
Figure 5. Differentially expressed transcription factor families and phylogenetic analysis of ERF proteins. (A) Transcription factor family analysis of differentially expressed genes (DEGs) in four key modules (MEblack, MEmidnightblue, MEblue, and MEgreenyellow). We have marked the transcription factor family with the highest ratio, ERF, using red signs. (B) The phylogenetic analysis of ERF family proteins in Arabidopsis thaliana and Cinnamomum camphora. (C) Quantitative real-time PCR expression levels of ERF subfamily genes. Different letters indicate significant differences at p < 0.05, following statistic analysis by one-way ANOVA. Gene names are listed in Table S4.
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Figure 6. Key pathways and genes associated with the cold response process of Cinnamomum camphora following cold stress treatment. Gene names are listed in Table S4.
Figure 6. Key pathways and genes associated with the cold response process of Cinnamomum camphora following cold stress treatment. Gene names are listed in Table S4.
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Bi, B.; Shao, L.; Xu, T.; Du, H.; Li, D. Transcriptomic Analysis Reveals Calcium and Ethylene Signaling Pathway Genes in Response to Cold Stress in Cinnamomum camphora. Horticulturae 2024, 10, 995. https://doi.org/10.3390/horticulturae10090995

AMA Style

Bi B, Shao L, Xu T, Du H, Li D. Transcriptomic Analysis Reveals Calcium and Ethylene Signaling Pathway Genes in Response to Cold Stress in Cinnamomum camphora. Horticulturae. 2024; 10(9):995. https://doi.org/10.3390/horticulturae10090995

Chicago/Turabian Style

Bi, Bo, Lingmei Shao, Tong Xu, Hao Du, and Danqing Li. 2024. "Transcriptomic Analysis Reveals Calcium and Ethylene Signaling Pathway Genes in Response to Cold Stress in Cinnamomum camphora" Horticulturae 10, no. 9: 995. https://doi.org/10.3390/horticulturae10090995

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