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Identification of MYC genes in four Cucurbitaceae species and their roles in the response to temperature stress

BMC Genomics volume 25, Article number: 867 (2024) Cite this article

Abstract

Background

Myelocytomatosis (MYC) transcription factors are crucial mediators of the response of plants to environmental stresses through via binding to DNA regulatory regions. However, few systematic characterizations of MYC genes are available in Cucurbitaceae species.

Results

In this study, we identified 10, 8, 12, and 10 MYC genes in Cucumis sativus, Cucumis melo, Citrullus lanatus, and Benincasa hispida, respectively. Characterization revealed that all of the MYC proteins contain a highly conserved H4-V5-E6-E8-R9-R11-R12 sequence, which is essential for the binding of DNA regulatory regions. Evolutionary analysis enabled us to categorize 40 predicted MYC proteins from seven species into five distinct groups and revealed that the expansion of the MYC genes occurred before the divergence of monocots and dicots. The upstream promoter regions of the MYC genes contain a variety of developmental, stress, and hormone-responsive regulatory elements. The expression of cucumber MYC genes varies significantly across organs, with particularly high expression of CsaV3_3G001710 observed across all organs. Transcriptomic analysis revealed that certain cucumber MYC genes undergo specific upregulation or downregulation in response to both biotic and abiotic stressors. In particular, under temperature stress, the cucumber genes CsaV3_3G007980 and CsaV3_3G001710 were significantly upregulated. Interestingly, the homologs of these two genes in C. lanatus presented a similar expression pattern to that in C. sativus, whereas in B. hispida, they presented the opposite pattern, i.e., significant downregulation. These findings indicated that these two genes indeed respond to temperature stress but with different expression patterns, highlighting the divergent functions of homologous genes across different species.

Conclusions

This study analyzed the size and composition of the MYC gene family in four Cucurbitaceae species and investigated stress-responsive expression profiles, especially under temperature stress. All the results showed that MYC genes play important roles in development and stress responses, laying a theoretical foundation for further investigations of these response mechanisms.

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Background

Myelocytomatosis oncogene (MYC) transcription factors (TFs) are an important class of TFs belonging to the basic helix-loop-helix (bHLH) TF family and contain two conserved functional domains, namely, the bHLH_MYC_N domain in the N-terminal region and the bHLH region in the C-terminal region [1,2,3]. As a subfamily of the bHLH family, MYC plays important roles in plant growth and development, secondary metabolism and signal transduction [4].

The first MYC gene, AtMYC1, was cloned from Arabidopsis thaliana, and functional studies revealed that it plays a certain role in plant seed development [5]. Successively, more MYC genes have been found in Arabidopsis. MYC2 can regulate leaf aging by antagonizing bHLH IIId subfamily transcription factors [6] and can also interact with jasmonate ZIM-domain 7 (JAZ7) to inhibit leaf aging under dark conditions [7]. In Arabidopsis thaliana, AtMYC2 can cooperate with AtMYC3 and AtMYC4 to regulate leaf development [8], chlorophyll degradation [9], seed production and seed storage protein accumulation [10, 11]. Previous studies also revealed that AtMYC2 can inhibit the growth of leaf veins by inhibiting the synthesis of auxin in plant leaves [12]. In addition, the Arabidopsis Aborted Microspores (AMS) gene, which encodes a MYC transcription factor, plays a crucial role in tapetum cell development and pollen wall formation [13]. In addition, MYC genes in other plants are involved in plant growth and development. In apple (Malus pumila Mill.), at the fruit ripening stage, MdMYC2 can affect ethylene biosynthesis and promote fruit ripening by promoting the expression of MdACS1 and MdACO1 [14]. In rice (Oryza sativa), overexpressed OsMYC2 can interact with OsJAZ1 and activate the downstream gene OsMADS1, which then regulates the development of spikelets [15]. The MYC genes also have important effects on the accumulation of plant secondary metabolites. For example, overexpression of AtMYC3 and AtMYC4 resulted in excessive accumulation of anthocyanins in Arabidopsis. Similarly, wheat (Triticum aestivum) MYC1 can regulate anthocyanin synthesis in the pericarp [16]. CrMYC2 can control jasmonate-responsive expression of the ORCA genes, which regulate alkaloid biosynthesis in Catharanthus roseus. In a few cases, TcJAMYC could negatively regulate the jasmonic acid-responsive expression of taxol biosynthesis genes in cultured cells of Taxus cuspidata [17]. In Artemisia annua, AaMYC2 can bind to AaJAZ1-4 and activate the expression of the artemisinin biosynthetic enzymes CYP71AV1 and DBR2, which positively regulate artemisinin biosynthesis [18].

Although many studies on MYC genes in various species have been conducted, studies on MYC genes in Cucurbitaceae crops are still lacking. Cucurbitaceae is one of the most important edible plant families in the world, among which cucumbers, melons, watermelons and wax gourds are widely grown worldwide and have great economic benefits. In this study, we aimed to identify the MYC genes in four Cucurbitaceae crops and compare MYC gene evolution and variation among species through bioinformatics analysis. We also analyzed the expression patterns of MYC genes under biotic and abiotic stresses, with a focus on identifying MYC genes involved in the temperature stress response, to provide theoretical support for stress-resistant breeding in Cucurbitaceae crops.

Methods

Identification and bioinformatics analysis of the MYC gene family in Cucurbitaceae crops

The HMM model files (PF14215.7 and PF00010) for the MYC gene family were downloaded from the Pfam database (http://pfam.xfam.org/), and the protein sequence files of Cucumis sativus L., Cucumis melo L., Citrullus lanatus, and Benincasa hispida were downloaded from the Cucurbitaceae Genomic Database (http://cucurbitgenomics.org; [19,20,21,22]). The hidden Markov model (HMM) plugin in the HMMER v3 software package was used to predict candidate MYC gene family members in the Cucumis sativus L., Cucumis melo L., Citrullus lanatus, and Benincasa hispida genomes [23], and the sequence information of high-quality candidate proteins was extracted via Perl scripts (E < 1 × 10− 5). The candidate MYC gene family genes were subsequently identified via the BLASTP program and NCBI-Conserved Domain Data (CDD) (http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi; [24]).

MYC gene family characterization and phylogenetic tree construction in Cucurbitaceae crops

Using the online tool ExPASy (https://web.expasy.org/protparam/) [25], we analyzed the amino acid length, molecular weight, isoelectric point, instability coefficient, aliphatic index, and average hydrophobicity of the members of the MYC gene family. We used the online website CELLO (http://cello.life.nctu.edu.tw/) for subcellular localization prediction. We employed the online software MEME (http://meme-suite.org/) to analyze the conserved motifs of MYC family proteins, with the parameters set as follows: 10 motifs and optimal motif width ranging from 6 to 200. Multiple sequence alignment was performed via ClustalX 2.0 and visualized via Jalview [26]. Phylogenetic analysis was performed via MEGA 7 [27] via the neighbor-joining (NJ) method, and the parameters used were the Poisson model, pairwise deletion, and 1000 bootstrap replications [28].

Chromosomal distribution and collinearity analysis of MYC genes

Based on the physical location information in the genome database, we used a mapchart to map the MYC gene family members onto Cucurbitaceae crop chromosomes [29]. The chromosomal distribution of the Cucurbitaceae crop SRS gene family was visualized via TBtools software [30]. Gene duplication events were analyzed via the multiple collinearity scan tool (MCScanX) [31]. A collinearity analysis plot was generated via Dual Synteny Plotter software (https://github.com/CJ-Chen/TBtools) [32].

Gene expression analysis

Transcriptome sequencing data related to cucumbers were downloaded from the NCBI database (https://www.ncbi.nlm.nih.gov/). The SRA-to-Fastq plugin in TBtools was used to convert the downloaded SRA data into Fastq format. Data quality was assessed via the FastQC plugin [33], and adapter sequences and low-quality sequences were removed via the Trimmomatic plugin [34], resulting in clean data. The filtered transcriptome data were aligned to the cucumber ChineseLong_V3 genome via the STAR plugin, generating SAM files [35]. Gene expression levels were analyzed via the StringTie Quantify plugin [36]. Finally, differential gene expression analysis was conducted via the DESeq2 plugin [37].

Tissue-specific expression analysis of cucumber MYC genes

Using transcriptome sequencing data from the NCBI database (PRJNA80169) [38], we analyzed the tissue-specific expression of the cucumber MYC gene family in various tissues and organs, including cucumber leaves, stems, female flowers, male flowers, unfertilized ovaries, fertilized ovaries, ovaries, roots, tendrils, and tendril bases. We utilized TBtools software to create an expression heatmap depicting the specific expression patterns of the cucumber MYC gene family in different cucumber tissues and organs.

Stress-responsive expression analysis of cucumber MYC genes

Using transcriptome sequencing data from the NCBI database, including PRJNA634519 [39], PRJNA438923 [40], PRJNA477930 [41], PRJNA321023 [42], and PRJNA419665 [43], we analyzed the specific expression patterns of the cucumber MYC gene family in response to various stress conditions, such as high temperature, low temperature, high salinity, silicon, powdery mildew, downy mildew, and southern root-knot nematodes. We used TBtools software to create expression heatmaps illustrating the gene expression responses of the cucumber MYC gene family under abiotic and biotic stress conditions.

Temperature stress treatment, RNA extraction and qRT‒PCR

The cultivars Jinyan-4 (Cucumis sativus), Harukei-3 (Cucumis melo), B227 (Benincasa hispida), and 8424 (Citrullus lanatus) provided by the Hebei Engineering Research Center for Seedling Breeding of Solanaceae and Fruit Vegetables of Hebei University Engineering were used to explore gene expression under temperature stress. The seedlings (two-leaf and one-heart stage) of the four cultivars were treated at 42 °C, and the leaves of the seedlings were removed at 0, 3, 6 and 12 h after treatment for qRT‒PCR. At the same time, the seedlings of the four cultivars were treated at 10 °C, and the leaves of the seedlings were removed at 0, 3, 6 and 12 h after treatment for qRT‒PCR. Three biological replicates were prepared for all samples, which were frozen in liquid nitrogen and then immediately stored at -80 °C.

Total RNA was extracted via the RNAprep Pure Plant Kit (DP432; Tiangen Biotech, Beijing, China) according to the manufacturer’s instructions. cDNA was synthesized from total RNA via the PrimeScript RT Kit (Takara). Specific primers for each gene were designed through Primer 6 (Table 1). The synthesized cDNA was subsequently subjected to qRT‒PCR on an Opticon thermocycler (CFX96 Connect Real-Time System; Bio-Rad, Hercules, CA) with SYBR Green PCR master mix (Vazyme, Nanjing, China) according to the manufacturer’s instructions. The 2-ΔΔCT method was used to calculate the relative expression of the MYC genes [44]. The value of relative expression showed the log2 FC (Fold change) of each gene compared with that of the control. The data analysis was conducted by Excel.

Table 1 List of primers used in quantitative RT‒PCR. All primers used were designed with primer 6
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Results

Identification and physicochemical property analysis of MYC genes

A total of 40 MYC genes were identified in the genomes of four Cucurbitaceae crops: 10 in C. sativus, 8 in C. melo, 12 in C. lanatus, and 10 in B. hispida. The MYC genes were unequally distributed on each chromosome. For example, C. sativus L. contains 6 MYC genes on chromosome 3, whereas there are no MYC genes on chromosomes 1, 2, 4, or 5. In C. melo L., chromosomes 2, 3, 5, 7, 8, 9, 10, and 12 contain no MYC genes, but the other chromosomes each have up to 3 MYC genes (Fig. 1). Sequence analysis revealed that the amino acid lengths encoded by the CsMYC genes varied from 431 aa (CsMYC8) to 694 aa (CsMYC5), those encoded by the CmMYC genes varied from 433 aa (CmMYC8) to 745 aa (CmMYC1), those encoded by the ClMYC genes varied from 423 aa (ClMYC3) to 969 aa (ClMYC1), and those encoded by the BhMYC genes varied from 501 aa (BhMYC4) to 968 aa (BhMYC3). Except for the acidic proteins encoded by CsMYC1, CmMYC5, ClMYC10 and BhMYC1, the MYC proteins in these Cucurbitaceae crops are alkaline proteins. Most proteins are unstable (with an instability index greater than 40), with the exceptions of CsMYC5, CmMYC1, ClMYC12, BhMYC7, and BhMYC9. The average hydropathicity values of all the proteins are less than 0, indicating that all the proteins are hydrophobic. Subcellular localization prediction revealed that most MYC proteins are localized in the cell nucleus, followed by chloroplasts. (Table 2).

Fig. 1
figure 1

Distribution of MYC family genes on the chromosomes of four Cucurbitaceae crop species. (A), C. sativus (B), C. melo (C), B. hispida (D), C. lanatus

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Table 2 Protein information for MYC gene family members in Cucurbitaceae crops
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Structure and phylogenetic analysis of the Cucurbitaceae crop MYC genes

Motif prediction analysis of the protein sequences of the MYC family members revealed that among 10 categorized motifs, no MYC family member contained all of them (Fig. 2). Motifs 1, 2, 5, 7, and 8 were relatively conserved and were common to all MYC genes. Gene structure analysis revealed that the number of exons in the MYC genes ranged from 1 to 15 (Fig. 2). The gene structures of most MYC genes within the same lineage are similar, further indicating the conservation of protein motifs and gene structures within each MYC evolutionary branch.

Fig. 2
figure 2

Phylogenetic tree, gene structure and conserved domains of the MYC genes of the four Cucurbitaceae crop species. (A), The MYC phylogenetic tree is divided into five groups, and different colors indicate different branches. (B), Conserved sequence of the MYC genes. (C), MYC gene structure; green indicates the CDS, yellow indicates the untranslated region, and the black line indicates introns

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According to an alignment of the bHLH domains in the MYC proteins, there is a basic amino acid region (Basic) composed of approximately 12 amino acids. This region contained a highly conserved H4-V5-E6-E8-R9-R11-R12 sequence, which was essential for the binding of bHLHs to target genes. This region also included two helical structures, consisting of approximately 37 amino acids. Notably, the 22nd and 38th amino acids in the HLH domain, both leucine (Leu), were highly conserved, indicating their necessity for dimer formation (Fig. 3).

Fig. 3
figure 3

Sequence alignment of the MYC proteins of the four Cucurbitaceae species

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To clarify the evolutionary relationships among the MYC gene family members in the Cucurbitaceae crops and in Zea mays, Brachypodium distachyon, and Oryza sativa, we constructed a phylogenetic tree. All the MYC proteins can be divided into five subgroups, labeled I to V. Each subgroup included both monocotyledonous and dicotyledonous plants, indicating that the MYC genes were relatively conserved during the evolution of both monocots and dicots. Group IV is the largest subgroup, consisting of 4, 4, 6, 3, 2, 1, and 1 MYC proteins from C. sativus L., C. melo L., C. lanatus, B. hispida, Z. mays, B. distachyon, and O. sativa, respectively. Group I was the smallest, with only 4 MYC genes (Fig. 4). In group II, there were 7 MYC genes, only 1 of which was from a monocotyledonous plant.

Fig. 4
figure 4

Phylogenetic tree of MYC family members in C. sativus, C. melo, C. lanatus, B. hispida, Z. mays, B. distachyon, and O. sativa

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Collinearity analysis of the MYC genes among Cucurbitaceae crops

A total of 36 MYC genes (9 in C. sativus L., 7 in C. melo L., 11 in C. lanatus, and 9 in B. hispida) were located within synteny blocks in the four Cucurbitaceae genomes (Fig. 5; Table 3). We identified five orthologous gene pairs that exist among all four species. These MYC genes were conserved during the evolution of all four Cucurbitaceae species, suggesting conserved roles. Furthermore, some MYC genes have been lost in some species. For example, certain MYC genes, such as the CsaV3_3G000850/MELO3C013772.2/Cla97C10G185380 collinear gene pair, were found in C. sativus L., C. melo L., and B. hispida but were absent in B. hispida. These results revealed the specific traits of different Cucurbitaceae species during evolution and amplification of the genome. In addition, two collinear gene pairs were detected in only C. lanatus and B. hispida.

Table 3 Collinear gene pairs present in the four Cucurbitaceae genomes
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Fig. 5
figure 5

Syntenic analysis of the MYC genes among C. sativus, C. melo, C. lanatus, and B. hispida. The gray lines in the background indicate the collinear blocks within the C. sativus, C. melo, C. lanatus, and B. hispida genomes, whereas the red lines highlight the homologous gene pairs

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Regulatory TFs of the MYC genes

The 1.5-kb upstream sequences of the MYC genes were selected for prediction of the TFs that regulate them. Three types of cis-elements related to development, hormone stress, and abiotic stress were identified (Fig. 6). Among the cis-elements related to development, the number of G-box (CACGTC) elements, which are light-responsive elements, is the greatest. For example, the genes MELO3C021212.2.1, MELO3C003412.2.1, and Cla97C10G186220.1 contain 9 G-box elements, indicating that they might be regulated by the light environment. Among the cis-elements related to hormone stress, the abscisic acid (ABA)-responsive element (ABRE) (ACGTG) is present in relatively large proportions, with 8 in MELO3C021212.2.1, MELO3C003412.2.1, and Cla97C10G186220.1 and 6 in Bhi02M001191, CsaV3_3G001710.1, and Bhi11M000137. Among the cis-elements related to abiotic stress, anaerobic induction AREs (AAACCA) were detected in a series of members, with 6 in Cla97C07G128490.1 and CsaV3_3G007980.1 and 5 in Cla97C05G080890.1.

Fig. 6
figure 6

Heatmap of various cis-elements in the promoters of each Cucurbitaceae MYC gene. The colors represent the quantity of the cis-elements, with deeper red indicating greater quantities. The numbers in the image represent the counts of the cis-elements

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Tissue-specific expression analysis of the MYC genes in C. Sativus

To investigate the expression profiles of the MYC gene family members in different tissues, using cucumber as a representative, we conducted transcriptome analysis on various tissues based on publicly available cucumber transcriptome sequencing data (PRJNA80169). The results revealed significant variation in the expression of MYC gene family members across different tissues (Fig. 7). For example, while the CsaV3_3G001710 gene presented a relatively high level of expression across all tissues or organs, three genes (CsaV3_3G000850, CsaV3_6G008940, and CsaV3_6G037080) presented relatively low expression levels across all tissues or organs. Some genes presented significant tissue-specific expression patterns. For example, the CsaV3_3G049150 gene presented relatively high expression in roots and fertilized ovaries but low expression in other tissues or organs. Similarly, compared with other tissues or organs, the CsaV3_7G027460 gene presented greater expression in roots. These results indicate that cucumber MYC family genes play distinct roles in the development of tissues or organs, contributing to various functions in plant growth and development.

Fig. 7
figure 7

Expression heatmaps of MYC family genes in different tissues of C. sativus

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Expression analysis of cucumber MYC genes under different stress conditions

Using publicly available transcriptome data from the NCBI SRA database, we analyzed the expression levels of the cucumber MYC genes under both biotic and abiotic (high temperature, low temperature, salt and silicon stress, powdery mildew, and southern root-knot nematode) stress conditions.

Under high-temperature stress, most MYC genes were not significantly differentially expressed (Fig. 8). For example, the expression levels of the genes CsaV3_6G037080, CsaV3_3G000850, and CsaV3_6G008940 did not change under high-temperature stress, and their expression levels were relatively low. However, the CsaV3_3G001710 gene was significantly upregulated at 6 h after high-temperature treatment (6 hph), whereas the CsaV3_3G007980 gene presented high expression levels at both 3 hph and 6 hph. These results suggest that the CsaV3_3G007980 gene is likely involved in the response of cucumber to high-temperature stress.

Fig. 8
figure 8

Expression heatmap of the cucumber MYC genes under high-temperature stress. HT0h represents the control treatment, HT3h represents high-temperature treatment for 3 h, and HT6h represents high-temperature treatment for 6 h. (A), The data in the table represent the raw FPKM values. (B), The data in the table represent the log2 FC values of the raw FPKM values

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Under low-temperature stress, the expression levels of four genes (CsaV3_6G037080, CsaV3_3G000850, CsaV3_6G008940, and CsaV3_6G000530) did not significantly change and remained relatively low. Two genes presented relatively high expression levels during the low-temperature treatment, with the CsaV3_3G007980 gene being significantly upregulated at 6 hph. The expression levels of the other genes remained unchanged before and after low-temperature treatment. Additionally, the expression of CsaV3_3G049150 was significantly downregulated at both 6 hph and 12 hph. Notably, the expression levels of all the genes did not significantly change at 3 hph. These results suggest that the CsaV3_3G007980 and CsaV3_3G049150 genes play key roles in the response of cucumber to prolonged low-temperature stress and that CsaV3_3G007980 is positively regulated, whereas CsaV3_3G049150 is negatively regulated (Fig. 9).

Fig. 9
figure 9

Expression heatmap of cucumber MYC family genes under low-temperature stress. CT represents the control treatment, CS_2h represents low-temperature treatment for 2 h, CS_6h represents low-temperature treatment for 6 h, and CS_12h represents low-temperature treatment for 12 h. (A), The data in the table represent the raw FPKM values. (B), The data in the table represent the log2 FC of the raw FPKM values

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Under salt and silicon treatment, most genes did not show differential expression after NaCl and silicon treatments. One gene (CsaV3_3G000850) was significantly downregulated after NaCl treatment and significantly upregulated after silicon treatment. However, when the plants were treated simultaneously with NaCl and silicon, a greater degree of downregulation was found (Fig. 10). Despite the significant differential expression of the CsaV3_3G00850 gene after treatment, its expression level remained relatively low under both the control and stress conditions.

Fig. 10
figure 10

Expression heatmap of the cucumber MYC family genes under salt and silicon treatment treatments. CT represents the control treatment, NaCl represents salt treatment, Silicon represents silicon treatment, and NaCl + Silicon represents combined salt and silicon treatment. (A), The data in the table represent the raw FPKM values. (B), The data in the table represent the log2 FC of the raw FPKM values

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Similarly, we analyzed the response of the MYC genes to biotic stress. Forty-eight hours after inoculation with powdery mildew, the expression of most genes did not significantly differ between the resistant (SSL508-28) and susceptible (D8) materials (Fig. 11). However, certain MYC genes presented differential expression patterns between SSL508-28 and D8. For example, CsaV3_3G000850 was upregulated to a significantly greater degree in D8 than in SSL508-28 after powdery mildew treatment. Interestingly, post-inoculation, the absolute expression level of CsaV3_3G000850 in D8 was much lower than its expression in SSL508-28. In addition, after inoculation with powdery mildew, CsaV3_3G049150 presented significantly downregulated expression in D8 and some degree of upregulation in SSL508-28.

Fig. 11
figure 11

Expression patterns of the cucumber MYC family genes under powdery mildew stress treatment. SSL508-28: resistant material; D8: susceptible material; CT: uninfected; 48 h, 48 h after inoculation. (A), The data in the table represent the raw FPKM values. (B), The data in the table represent the log2 FC of the raw FPKM values

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After inoculation with root-knot nematodes (Meloidogyne incognita), the expression levels of most genes, such as CsaV3_3G000850 and CsaV3_3G034600, in both resistant (IL10-1) and susceptible (CC3) materials generally exhibited similar trends (Fig. 12). However, two genes, CsaV3_6G000530 and CsaV3_6G037080, were upregulated in resistant materials but downregulated in susceptible materials. Nevertheless, the degree of differential expression of these genes is relatively low between the resistant and susceptible materials.

Fig. 12
figure 12

Expression patterns of the cucumber MYC family genes under southern root–knot nematode stress treatment. IL10-1: resistant material; CC3: susceptible material; 0d, 1d, 2d, and 3d represent 0 days, 1 day, 2 days, and 3 days after inoculation, respectively. (A), The data in the table represent the raw FPKM values. (B), The data in the table represent the log2 FC of the raw FPKM values

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The response of eight genes in the four Cucurbitaceae crops under temperature stress

Eight genes in the four Cucurbitaceae crops (CsaV3_3G007980, CsaV3_3G001710, MELO3C006016, MELO3C013851, Bhi01M000362, Bhi11M000137, Cla97C10G186220, and Cla97C05G080890) were selected for analysis of the response to temperature stress. As shown in Fig. 13, in Cucumis sativus, the genes CsaV3_3G007980 and CsaV3_3G001710 were upregulated under both low- and high-temperature stress. Especially under high temperature treatment, its expression level increased significantly as the treatment time increased. Which is relatively consistent with the transcriptome results, indicating their involvement in the cucumber response to temperature stress (Fig. 13A and B). This expression pattern also appeared in Cucumis melo and Citrullus lanatus. The CsaV3_3G007980 homologs MELO3C013851 and Cla97C05G080890 were upregulated under high-temperature stress (Fig. 13C and G). However, the homologous gene MELO3C006016 was significantly downregulated at 3 and 6 h of high-temperature treatment and then upregulated at 12 h of high-temperature treatment (Fig. 13D). However, the expression pattern of this gene was opposite under low-temperature treatment compared to high-temperature treatment. Under low-temperature treatment, gene MELO3C006016 was upregulated at 3 h of high-temperature treatment and then significantly downregulated at 6 and12 hours of high-temperature treatment. In Benincasa hispida, the expression of the two homologous genes Bhi01M000362 and Bhi11M000137 was downregulated at all time points under both the low- and high-temperature treatment groups (Fig. 13E and F).

Fig. 13
figure 13

Expression of MYC genes in the four Cucurbitaceae crops under high-temperature and low-temperature stress. HT: high-temperature; LT: low-temperature; CK: control. The error bars in the graphs indicate SD. The value of relative expression showed the log2 FC of each gene compared with that of the control. Letters (a, b, c) indicates a significant difference at p < 0.05

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Discussion

Characteristics of the MYC genes in the Cucurbitaceae crops

The MYC transcription factors have been reported to participate in various life activities in plants, playing crucial roles in regulating the growth and development of plant organs and in modulating tolerance to abiotic stress responses. The MYC protein has a bHLH_MYC_N domain in the N-terminal region, which consists of two subdomains: JID and TAD. The former is essential for interacting with JAZ proteins, whereas the latter is a putative transcriptional activation domain [45]. In the C-terminal region, the conserved bHLH domain determines its specificity and affinity for DNA sequence binding, and it can facilitate the formation of various homodimers and heterodimers [46]. The bHLH domain comprises a basic region and an HLH region. The basic region is located at the N-terminus of the domain and contains sites for DNA recognition and binding. In this study, a highly conserved H4-V5-E6-E8-R9-R11-R12 sequence was found in the basic region, in which the highly conserved Leu at residues 22 and 38 were necessary for dimer formation (Fig. 3); it has been shown [47] that mutations at these two Leu sites significantly affect bHLH dimerization in Arabidopsis. bHLH-type transcription factors can be classified into six main groups (designated A to F) according to the differences in the recognition mode between the basic region and the cis-acting elements [1]. Most of the MYC genes in Cucurbitaceae crops can specifically bind to the G-box (5’-CACNTG-3’), which could be bounded by the GBF family of bZIP proteins [48], and belong to Group B. Consistent with previous findings, the C-terminus of the domain includes a conserved helix‒loop‒helix (HLH) structure that can form homodimers or heterodimers with other proteins.

Gene structure analysis revealed that the MYC genes in groups III and IV had fewer introns (less than or equal to 2), with approximately 50% of all MYC genes lacking introns. In contrast, the MYC genes in the other three groups contained many introns. Previous studies have indicated that introns and exons play important roles in the diversity and evolution of gene families through gain/loss and insertion/deletion events [49, 50]. The significant difference in the number of introns among the MYC genes suggests that the Cucurbitaceae crops have undergone intron loss events during their evolution to adapt to environmental changes. Jeffares et sl. reported that having fewer introns in genes enables plants to respond more rapidly to environmental changes [51]. In addition, in an evolutionary analysis between monocots and dicots, all the groups included both monocot and dicot species, indicating that the MYC genes have been relatively conserved during the evolution of both monocots and dicots.

Functions of the MYC genes and their role in the response to temperature stress

Many studies have shown that MYC transcription factors play significant roles in the growth and development of plants. For example, MYC TFs are involved in regulating processes such as plant seed production [52], stamen development [53], hormone regulation [54], and secondary metabolism [55]. In this study, the majority of the MYC genes were expressed in roots, leaves, and unfertilized ovaries (Fig. 7). Coupled with the identification of numerous cis-elements related to development and hormone stress, these findings further underscore their functions in growth and development.

Moreover, MYC genes play important roles in the response to abiotic and biotic stresses. Previous research found that silicon application promotes the growth of plants under salt stress, significantly reduces the Na+ content, especially in the leaves, and counteracts the effects of NaCl on gas exchange [56]. Zhu et al. found that silicon confers resistance to salt stress in cucumber by regulating proline and cytokinins [57]. In this study, The CsaV3_3G000850 gene was significantly downregulated after NaCl treatment and significantly upregulated after silicon treatment. These results indicate that silicon treatment induced high expression of CsaV3_3G000850, thereby increasing salt tolerance in cucumber. Similar results have been reported in Arabidopsis, MYB2 and MYC2 function in ABA-inducible gene expression of the RD22 gene, where overexpression of the AtMYC2 gene significantly increased osmotic stress tolerance [58]. In recent years, there has been a growing focus on the responses of MYC genes to temperature stress. Overexpressing SlICE1, which encodes a MYC-type transcription factor, enhances cold tolerance in tomato [59]. In Arabidopsis, MYC67 and MYC70 interact with ICE1, leading to negative regulation of cold tolerance [60]. The overexpression of PtrbHLH, a basic helix-loop-helix transcription factor from Poncirus trifoliata, confers enhanced cold tolerance in pummelo (Citrus grandis) by regulating Catalase (CAT) to modulate the level of H2O2 [61]. Under cold conditions, StICE1 in potato enhances the stability of cell membranes by increasing the expression of the StLTI6A gene, thereby increasing its tolerance [62]. The MYC-type TF MdbHLH4 negatively regulates apple cold tolerance by inhibiting the expression of MdCBF1/3 and the promoter-binding activity of MdICE1L, as well as by promoting the expression of MdCAX3L-2 and the cold-induced degradation of MdICE1L [63]. In this study, we identified two MYC genes (CsaV3_3G007980 and CsaV3_3G001710) in cucumber that are significantly differentially expressed under temperature stress (Figs. 8 and 9). To validate the involvement of these two genes in the temperature stress response in the other cucurbit species, we analyzed their homologous genes for their reactions under temperature stress (Fig. 13). Gene expression analysis revealed differential expression of these two genes across all four species, albeit with varying patterns. Comparative functional genomics research has indicated that if regulatory elements in evolutionarily related species are conserved, then gene expression characteristics within species are correspondingly conserved [64]. In this study, cis-regulatory element analysis revealed certain differences in both the type and quantity of these elements among the eight homologous genes, which may account for the differential expression of homologous genes across species. These findings suggest that CsaV3_3G007980 and CsaV3_3G001710, along with their homologs in the other Cucurbitaceae crops, are highly responsive to temperature stress. However, the differential expression patterns between species remain unresolved. Further exploration of the response mechanisms of these genes to temperature stress will be the focus of future research.

Conclusions

In summary, we identified 10, 8, 12, and 10 MYC genes in C. sativus, C. melo, C. lanatus, and B. hispida, respectively, each of which play distinct roles in plant development. In particular, under environmental stress, some genes respond actively to external pressures through the upregulation or downregulation of expression. Additionally, we identified two genes that are relatively more sensitive to temperature stress, namely, CsaV3_3G007980 and CsaV3_3G001710. However, these two genes exhibit contrasting expression patterns across the different species. This finding implied that some degree of alterations in gene function occurred following species divergence. These results provide valuable insights for future functional studies of MYC genes and present potential candidate genes for enhancing the environmental adaptability of Cucurbitaceae species.

Data availability

The authors confirm that the data supporting the findings of this study from NCBI database with accession numbers of PRJNA80169 [39], PRJNA634519 [39], PRJNA438923 [40], PRJNA477930 [41], PRJNA321023 [42], and PRJNA419665 [43] are available within the manuscript.

Abbreviations

MYC:

Myelocytomatosis

TF:

Transcription factor

JAZ:

Jasmonate ZIM-domain

AMS:

Arabidopsis Aborted Microspores

CDD:

Conserved domain data

ABA:

Abscisic acid

Hph:

Post high-temperature treatment

HLH:

Helix-loop-helix

References

  1. Ledent V, Vervoort M. The basic helix-loop-helix protein family: comparative genomics and phylogenetic analysis. Genome Res. 2001;11:754–70.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  2. Nuno P, Liam D. Origin and diversification of basic-helix-loop-helix proteins in plants. Mol Biol Evol. 2010;27:862–74.

    Article  Google Scholar 

  3. Xu YH, Liao YC, Lv FF, Zhang Z, Sun PW, Gao ZH, Hu KP, Sui C, Jin Y, Wei JH. Transcription factor AsMYC2 controls the Jasmonate-responsive expression of ASS1 regulating Sesquiterpene Biosynthesis in Aquilaria sinensis (Lour.) Gilg. Plant Cell Physiol. 2017;58:1924–33.

    Article  PubMed  CAS  Google Scholar 

  4. Pires N, Dolan L. Origin and diversification of basic-helix-loop-helix proteins in plants. Mol Biol Evol. 2010;27(4):862–74.

    Article  PubMed  CAS  Google Scholar 

  5. Urao T, Yamaguchi-Shinozaki K, Mitsukawa N, et al. Molecular cloning and characterization of a gene that encodes a MYC-related protein in Arabidopsis. Plant Mol Biol. 1996;32(3):571–6.

    Article  PubMed  CAS  Google Scholar 

  6. Butterfield DA, Drake J, Pocernich C, et al. Evidence of oxidative damage in Alzheimer’s disease brain: central role for amyloid β-peptide. Trends Mol Med. 2001;7(12):548–54.

    Article  PubMed  CAS  Google Scholar 

  7. Zong S, Zeng G, Zou B, et al. Effects of Polygonatum sibiricum polysaccharide on the osteogenic differentiation of bone mesenchymal stem cells in mice. Int J Clin Exp Pathol. 2015;8(6):6169.

    PubMed  PubMed Central  Google Scholar 

  8. Qi T, Wang J, Huang H, et al. Regulation of jasmonate-induced leaf senescence by antagonism between bHLH subgroup IIIe and IIId factors in Arabidopsis. Plant Cell. 2015a;27(6):1634–49.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. Zhu X, Chen J, Xie Z, et al. Jasmonic acid promotes degreening via MYC 2/3/4-and ANAC 019/055/072‐mediated regulation of major chlorophyll catabolic genes. Plant J. 2015;84(3):597–610.

    Article  PubMed  CAS  Google Scholar 

  10. Qi T, Huang H, Song S, et al. Regulation of jasmonate-mediated stamen development and seed production by a bHLH-MYB complex in Arabidopsis. Plant Cell. 2015b;27(6):1620–33.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  11. Gao C, Qi S, Liu K et al. MYC2, MYC3, and MYC4 function redundantly in seed storage protein accumulation in Arabidopsis. Plant Physiol Biochem. 2016;108:63–70.

  12. Huang CF, Yu CP, Wu YH, et al. Elevated auxin biosynthesis and transport underlie high vein density in C4 leaves[J]. PNAS. 2017;114(33):E6884–91.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  13. Sorensen AM, Kröber S, Unte US, et al. The Arabidopsis ABORTED MICROSPORES (AMS) gene encodes a MYC class transcription factor[J]. Plant J. 2003;33(2):413–23.

    Article  PubMed  CAS  Google Scholar 

  14. Li T, Xu Y, Zhang L, et al. The jasmonate-activated transcription factor MdMYC2 regulates ETHYLENE RESPONSE FACTOR and ethylene biosynthetic genes to promote ethylene biosynthesis during apple fruit ripening[J]. Plant Cell. 2017;29(6):1316–34.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  15. Uji Y, Taniguchi S, Tamaoki D, et al. Overexpression of OsMYC2 results in the up-regulation of early JA-rresponsive genes and bacterial blight resistance in rice[J]. Plant Cell Physiol. 2016;57(9):1814–27.

    Article  PubMed  CAS  Google Scholar 

  16. Zong Y, Xi X, Li S, et al. Allelic variation and transcriptional isoforms of wheat TaMYC1 gene regulating anthocyanin synthesis in pericarp[J]. Front Plant Sci. 2017;8:1645.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Lenka SK, Nims NE, Vongpaseuth K, et al. Jasmonate-responsive expression of paclitaxel biosynthesis genes in Taxus cuspidata cultured cells is negatively regulated by the bHLH transcription factors TcJAMYC1, TcJAMYC2, and TcJAMYC4[J]. Front Plant Sci. 2015;6:115.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Shen Q, Lu X, Yan T, et al. The jasmonate-responsive AaMYC2 transcription factor positively regulates artemisinin biosynthesis in Artemisia annua. New Phytol. 2016;210(4):1269–81.

    Article  PubMed  CAS  Google Scholar 

  19. Li Q, Li H, Huang WU, et al. A chromosome-scale genome assembly of cucumber (Cucumis sativus L). GigaScience. 2019;8(6):giz072.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Garcia-Mas J, Benjak A, Sanseverino W, et al. The genome of melon (Cucumis melo L). PNAS. 2012;109(29):11872–7.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  21. Guo S, Zhang J, Sun H, et al. The draft genome of watermelon (Citrullus lanatus) and resequencing of 20 diverse accessions. Nat Genet. 2013;45(1):51–8.

    Article  PubMed  CAS  Google Scholar 

  22. Xie D, Xu Y, Wang J, et al. The wax gourd genomes offer insights into the genetic diversity and ancestral cucurbit karyotype. Nat Commun. 2019;10(1):5158.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Robert DF, Jody C, Sean RE. HMMER web server: interactive sequence similarity searching. Nucleic Acids Res. 2011;39:29–37.

    Article  Google Scholar 

  24. Marchlerbauer A, Bo Y, Han L, He J, Lanczycki CJ, Lu S, Chitsaz F, Derbyshire MK, Geer RC, Gonzales NR. CDD/SPARCLE: functional classification of proteins via subfamily domain architectures. Nucleic Acids Res. 2017;45:D200–3.

    Article  PubMed  CAS  Google Scholar 

  25. Walker JM. The proteomics protocols handbook. Biochemistry. 2006;71(6):696–696.

    Google Scholar 

  26. Waterhouse A, Procter J, Martin DA, et al. Jalview: visualization and analysis of molecular sequences, alignments, and structures[J]. BMC Bioinformatics. 2005;6(3):1–1.

    Google Scholar 

  27. Kumar S, Stecher G, Tamura K. MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol Biol Evol. 2015;33:1870–4.

    Article  Google Scholar 

  28. Sinsheimer JS, Little RJA, Lake JA. Rooting gene trees without outgroups: EP Rooting. Genome Biol Evol. 2012;4(8):709–19.

    Article  PubMed  Google Scholar 

  29. Voorrips RE. MapChart: software for the graphical presentation of linkage maps and QTLs. J Hered. 2002;93(1):77–8.

    Article  PubMed  CAS  Google Scholar 

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

    Article  PubMed  CAS  Google Scholar 

  31. Wang Y, Tang H, Jeremy DD, Xu T, Li J, Wang X, Lee T, Jin H, Barry M, Guo H, Kissinger J, Paterson A. 2012. MCScanX: a toolkit for detection and evolutionary analysis of gene synteny and collinearity. 40 (7):e49–49.

  32. Liu C, Xie T, Chen C, Luan A, Long J, Li C, Ding Y, He Y. Genome-wide organization and expression profiling of the R2R3-MYB transcription factor family in pineapple(Ananas comosus). BMC Genomics. 2017;18(1):503.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Brown J, Pirrung M, McCue LA. FQC Dashboard: integrates FastQC results into a web-based, interactive, and extensible FASTQ quality control tool. Bioinformatics. 2017;33:3137–9.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  34. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114–20.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  35. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R. The sequence alignment/map format and SAMtools. Bioinformatics. 2009;25:2078–9.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Pertea M, Pertea GM, Antonescu CM, Chang TC, Mendell JT, Salzberg SL. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat Biotechnol. 2015;33(3):290–5.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  37. Varet H, Brillet-Guéguen L, Coppée JY, Dillies MA. SARTools: a DESeq2- and EdgeR-Based R pipeline for comprehensive differential analysis of RNA-seq data. PLoS ONE. 2016;11:e0157022.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Li Z, Zhang Z, Yan P, Huang S, Fei Z, Lin K. RNA-Seq improves annotation of protein-coding genes in the cucumber genome. BMC Genomics. 2011;12:1–11.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Chen C, Chen X, Han J, Lu W, Ren Z. Genome-wide analysis of the WRKY gene family in the cucumber genome and transcriptome-wide identification of WRKY transcription factors that respond to biotic and abiotic stresses. BMC Plant Biol. 2020;20:1–19.

    Article  CAS  Google Scholar 

  40. Li C, Dong S, Liu X, Bo K, Miao H, Beckles DM, Zhang S, Gu X. Genome-wide characterization of Cucumber(Cucumis sativus L.)GRAS genes and their response to various abiotic stresses. Horticulturae. 2020;6(4):110–27.

    Article  Google Scholar 

  41. Zhu Y, Yin J, Liang Y, Liu J, Jia J, Huo H, Wu Z, Yang R, Gong H. Transcriptomic dynamics provide an insight into the mechanism for silicon-mediated alleviation of salt stress in cucumber plants. Ecotoxicol Environ Saf. 2019;174:245–54.

    Article  PubMed  CAS  Google Scholar 

  42. Xu Q, Xu X, Shi Y, Qi X, Chen X. Elucidation of the molecular responses of a cucumber segment substitution line carrying Pm5.1 and its recurrent parent triggered by powdery mildew by comparative transcriptome profiling. BMC Genomics. 2017;18:1–14.

    Article  CAS  Google Scholar 

  43. Wang X, Cheng C, Zhang K, Tian Z, Xu J, Yang S, Lou Q, Li J, Chen JF. Comparative transcriptomics reveals suppressed expression of genes related to auxin and the cell cycle contributes to the resistance of cucumber against Meloidogyne incognita. BMC Genomics. 2018;19:1–14.

    Article  Google Scholar 

  44. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2 – ∆∆CT method[J]. methods. 2001;25(4):402–408.

  45. Kazan K, Manners JM. MYC2: the Master in Action. Mol Plant. 2013;6:686–703.

    Article  PubMed  CAS  Google Scholar 

  46. Blackwood E, Eisenman R, Max. A helix-loop-helix zipper protein that forms a sequence-specific DNA-binding complex with Myc. Science. 1991;251:1211.

    Article  PubMed  CAS  Google Scholar 

  47. Heim MA, Jakoby M, Werber M, Martin C, Weisshaar B, Bailey PC. The Basic Helix-Loop-Helix transcription factor family in plants: a genome-wide study of protein structure and functional diversity. Mol Biol Evol. 2003;20:735–47.

    Article  PubMed  CAS  Google Scholar 

  48. Menkens AE, Schindler U, Cashmore AR. The G-box: a ubiquitous regulatory DNA element in plants bound by the GBF family of bZIP proteins[J]. Trends Biochem Sci. 1995;20(12):506–10.

    Article  PubMed  CAS  Google Scholar 

  49. Jeffares DC, Mourier T, Penny D. The biology of intron gain and loss[J]. Trends Genet. 2006;22(1):16–22.

    Article  PubMed  CAS  Google Scholar 

  50. Xu G, Guo C, Shan H, et al. Divergence of duplicate genes in exon–intron structure[J]. PNAS. 2012;109(4):1187–92.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  51. Jeffares DC, Penkett CJ, Bähler J. Rapidly regulated genes are intron poor[J]. Trends Genet. 2008;24(8):375–8.

    Article  PubMed  CAS  Google Scholar 

  52. Qi TC, Huang H, Song SS, Xie DX. Regulation of Jasmonate-mediated stamen development and seed production by a bHLH-MYB complex in Arabidopsis. Plant Cell. 2015;27:1620–33.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  53. Li S, Hu Y, Yang H et al. The regulatory roles of MYC TFs in plant stamen development[J]. Plant Sci. 2023;111734.

  54. Fukazawa J, Mori K, Ando H, et al. Jasmonate inhibits plant growth and reduces gibberellin levels via microRNA5998 and transcription factor MYC2[J]. Plant Physiol. 2023;193(3):2197–214.

    Article  PubMed  CAS  Google Scholar 

  55. Johnson LYD, Major IT, Chen Y, et al. Diversification of JAZ-MYC signaling function in immune metabolism[J]. New Phytol. 2023;239(6):2277–91.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  56. Zuccarini P. Effects of silicon on photosynthesis, water relations and nutrient uptake of Phaseolus vulgaris under NaCl stress[J]. Biol Plant. 2008;52:157–60.

    Article  CAS  Google Scholar 

  57. Zhu Y, Jiang X, Zhang J, et al. Silicon confers cucumber resistance to salinity stress through regulation of proline and cytokinins[J]. Plant Physiol Bioch. 2020;156:209–20.

    Article  CAS  Google Scholar 

  58. Shinozaki K, Yamaguchi-Shinozaki K. Gene networks involved in drought stress response and tolerance. J Exp Bot. 2007;58:221–7.

    Article  PubMed  CAS  Google Scholar 

  59. Miura K, Shiba H, Ohta M, et al. SlICE1 encoding a MYC-type transcription factor controls cold tolerance in tomato, Solanum lycopersicum[J]. Plant Biotechnol J. 2012;29(3):253–60.

    Article  CAS  Google Scholar 

  60. Ohta M, Sato A, Renhu N, et al. MYC-type transcription factors, MYC67 and MYC70, interact with ICE1 and negatively regulate cold tolerance in Arabidopsis[J]. Sci Rep. 2018;8(1):11622.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Geng J, Wei T, Wang Y, et al. Overexpression of PtrbHLH, a basic helix-loop-helix transcription factor from Poncirus trifoliata, confers enhanced cold tolerance in pummelo (Citrus grandis) by modulation of H2O2 level via regulating a CAT gene[J]. Tree Physiol. 2019;39(12):2045–54.

    PubMed  CAS  Google Scholar 

  62. Wang X, Song Q, Guo H, et al. StICE1 enhances plant cold tolerance by directly upregulating StLTI6A expression[J]. Plant Cell Rep. 2023;42(1):197–210.

    Article  PubMed  Google Scholar 

  63. Yang J, Guo X, Mei Q, et al. MdbHLH4 negatively regulates apple cold tolerance by inhibiting MdCBF1/3 expression and promoting MdCAX3L-2 expression[J]. Plant Physiol. 2023;191(1):789–806.

    Article  PubMed  CAS  Google Scholar 

  64. Lee JS, Chu IS, Mikaelyan A, et al. Application of comparative functional genomics to identify best-fit mouse models to study human cancer[J]. Nat Genet. 2004;36(12):1306–11.

    Article  PubMed  CAS  Google Scholar 

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Funding

This work was supported by the National Natural Science Foundation of China (32302542) and Hebei Natural Science Foundation (C2024402002), which provided support for the design of the study; the Science Research Project of the Hebei Education Department (QN2022062 and QN2024122), which provided support for data collection; the Science and Technology Research and Developmental Guidance Program of Handan (23313014019); and the Construction of Innovative Teams in Modern Agricultural Industry Systems in Hebei Province (HBCT2024140206), which supported the analysis and interpretation of the data.

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  1. School of Landscape and Ecological Engineering, Hebei University of Engineering, Handan, 056038, China

    Tao Liu, Yani Zheng, Jingyu Yang, Rourou Li, Huan Chang, Nanyang Li, Wang Suna, Liping Wang & Xing Wang

  2. Hebei Engineering Research Center for Seedling Breeding of Solanaceae Vegetables, Handan, 056038, China

    Nanyang Li, Wang Suna, Liping Wang & Xing Wang

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  1. Tao Liu
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W.X. designed, performed the experiments, analyzed data and wrote the paper; L.T. prepared the material and wrote the paper; Z.Y.N., Y.J.Y., L.R.R. and C.H. analyzed data; L.N.Y. revised the paper; W.S.N. and W.L.P. wrote and revised the paper. All authors read and approved the final version of the manuscript.

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Liu, T., Zheng, Y., Yang, J. et al. Identification of MYC genes in four Cucurbitaceae species and their roles in the response to temperature stress. BMC Genomics 25, 867 (2024). https://doi.org/10.1186/s12864-024-10771-8

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