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Article

Identification of Tomato SET Domain Group Gene Family and Function Analysis Under Temperature Stress

by
Chuanlong Lu
1,2,
Yuan Cheng
2,3,
Hongjian Wan
2,
Zhuping Yao
2,
Meiying Ruan
2,
Rongqing Wang
2,
Qingjing Ye
2,
Guozhi Zhou
2,
Huasen Wang
1,* and
Chenxu Liu
2,*
1
College of Horticulture, Qingdao Agricultural University, Qingdao 266109, China
2
State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-Products, Vegetable Research Institute, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China
3
Zhejiang Xianghu Laboratory, Hangzhou 311258, China
*
Authors to whom correspondence should be addressed.
Horticulturae 2025, 11(8), 958; https://doi.org/10.3390/horticulturae11080958
Submission received: 28 June 2025 / Revised: 7 August 2025 / Accepted: 11 August 2025 / Published: 13 August 2025
(This article belongs to the Special Issue Advancements in Genetic Improvement of Stress Tolerance in Vegetable Crops)
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Versions Notes

Abstract

Histone methylation plays important roles in plant development and adaptation to multiple stresses. SET domain group (SDG) proteins are identified as plant histone lysine methyltransferases in Arabidopsis and other crops. However, the SDG gene family and its functional roles in tomato remain unknown. In this research, 48 tomato SDG (SlSDG) gene family members were identified, and their chromosomal locations and conserved motifs were determined. According to phylogenetic analysis, the SlSDGs are divided into seven groups, which is consistent with Arabidopsis and rice. Promoter analysis indicated that the SlSDGs may be associated with biotic and abiotic stress responses. The expression pattern of SlSDGs illustrates that heat and cold stress significantly influence the transcript abundance of SDG14/19/21/23/48. The results of a VIGS assay showed that silencing SlSDG19 and SlSDG48 decreases tomato heat tolerance, while silencing SlSDG14 improves the heat tolerance of tomato plants. The analysis of downstream regulating genes indicated that heat shock proteins (HSPs), especially HSP70 and HSP90, act as critical effectors. Similarly, the experimental assay and expression analysis suggest that SDG21 and SDG23 positively and negatively regulate tomato cold tolerance through the CBF-COR pathway, respectively. These findings clarify the function of tomato SDG proteins and provide insight for the genetic improvement of tomato for temperature stress tolerance.

1. Introduction

As a critical epigenetic modification, histone methylation affects the transformation of euchromatin and heterochromatin, which further regulates gene expression patterns [1,2]. Various types and degrees of histone methylation occur in lysine (K) and arginine (R) residues at the histone tails [1]. Lysine methylation exists in K4, K9, K27 and K36 of H3 at three main levels: mono-methylation, di-methylation and tri-methylation [3]. Lysine methylation in H3K4 and H3K36 is often associated with euchromatin and transcriptional activation, while H3K9 and H3K27 are commonly linked with heterochromatin and transcriptional inhibition [4].
The dynamic of histone lysine methylation is mediated by histone lysine methyltransferase and demethylase [5]. In plants, SET domain group (SDG) proteins are responsible for transferring methyl groups to lysine residues, which are mainly classified into three kinds of protein, including the suppressor of variegation 3-9 (Su(var)3-9), enhancer of zeste (E(z)) and trithorax (Trx) [6]. The SET domain is an evolutional conserved sequence with an approximate length of 130 aa [7]. According to the sequence characteristics and evolutionary relationship, SDG proteins are divided into seven subgroups, including subgroup I: E(z) homologs; subgroup II: ASH1 homologs; subgroup III: Trx homologs; subgroup IV: protein with SET domain and PHD domain; subgroup V: Su(var) homologs; subgroup VI: with split SET domain and subgroup protein; and subgroup VII: ribose-1,5-diphosphate carboxylase/oxygenase (Rubisco) methyltransferase [8].
Plant SDG proteins have been broadly reported to participate in development and stress responses [8,9,10]. The first SDG protein identified in plants was Arabidopsis homolog Trithorax1 (ATX1), which inhibits flowering by regulating the level of H3K4me3 at Flowering Locus C (FLC) [11]. This SDG protein also takes part in regulating plant seed germination and callus differentiation [12,13,14]. Arabidopsis SUVH4 positively regulates seed germination by decreasing Delay of Germination 1 (DOG) gene expression and inhibiting ABA signaling transduction factor [12]. ATX4 is an H3K4me2/3 methyltransferase in Arabidopsis, and accelerates callus formation by increasing the gene expression level of shoot identity genes [13].
Previous studies have also revealed the function of SDG proteins in regulating plant adaptation to abiotic stress [10,15]. In Arabidopsis, ATX1 and SDG25 are H3K4me3 methyltransferases that coordinately regulate the expression of heat-responsive genes, enhancing the plant’s thermotolerance [16]. Furthermore, the H3K27me3 level on COR15A, a cold tolerance-related gene, is significantly reduced under low temperatures, leading to its up-regulated expression and enhanced cold tolerance in Arabidopsis [17]. Additionally, this SDG protein also mediates plant tolerance to biotic stress in Arabidopsis [18]. The Arabidopsis H3K36me3 methyltransferase SDG8 positively regulates a series of signaling transduction genes associated with phytohormones, including jasmonic acid, ethylene and salicylic acid, enhancing resistance against multiple pathogenic bacteria [18,19]. However, the function of SDG proteins in modulating abiotic stress adaptation of horticultural crops remains unknown.
Originating from South America, tomato is now cultivated around the world and is one of the most important vegetables today, mainly due to its unique flavor [20]. It has long been used as a model plant for fruit ripening, disease response, genetics and whole-genome sequence research [21]. However, studies on SDG proteins in tomato, especially on their functional roles in temperature stress response, are still insufficient. In this research, the chromosome position, phylogenetic relationship, gene structure and expression of the SDG gene family were comprehensively analyzed, and the functional roles of several SDGs in tomato heat tolerance/cold tolerance were determined through virus-induced gene silencing (VIGS). This study will deepen our understanding of the evolutionary relationship between tomato SDG (SlSDG) genes and their potential functions in resisting temperature stress.

2. Materials and Methods

2.1. Identification and Chromosomal Location of SlSDG Family Members

The protein sequences and gene IDs of the Arabidopsis SDG gene family were obtained from the TAIR database (https://www.arabidopsis.org/, accessed on 5 January 2025). The tomato genome and its annotation files were obtained from the Sol Genomics Network (https://solgenomics.net/, accessed on 8 January 2025). The tomato SDG gene family was identified using the BLASTP method (Version 2.15.0) in the NCBI database with AtSDG protein sequences. The hidden Markov model from the Interpro database (https://www.ebi.ac.uk/interpro/, accessed on 11 January 2025) was also used to search for tomato genes containing SET functional domains. The overlapping genes from two methods were identified as tomato SDG genes. The chromosomal distribution of tomato SDG genes was determined using TB tools (Version 2.121).

2.2. Phylogenetic Tree Construction of SDG Proteins

The SDG protein sequences of Arabidopsis thaliana and rice were downloaded from the TAIR database and NCBI database, respectively, and their sequences were compared using ClustalX software (Version 2.1). The phylogenetic tree was constructed with MEGA11.0 software using the maximum likelihood method.

2.3. Conserved Motif and Gene Structure Analysis of SlSDG Family

Conserved motifs were analyzed using the MEME website (https://meme-suite.org/meme/tools/meme, accessed on 20 January 2025) and the results were visualized using TB tools (Version 2.121). The gene structure of the SlSDGs was analyzed using the GSDS website (http://gsds.gao-lab.org/, accessed on 14 February 2025) and the results were also visualized using TB tools (Version 2.121).

2.4. Analysis of Cis-Acting Elements of SlSDG in Tomato

For cis-acting element analysis, the 2000 bp promoter region upstream of each SlSDG was obtained using TB tools (Version 2.121). The cis-acting elements were predicted using the Plant CARE website (http://bioinformatics.psb.ugent.be/webtools/plantcare/html/, accessed on 20 February 2025) and the cis-acting structure of SlSDG genes was determined using TB tools (Version 2.121).

2.5. Plant Material and Growth Condition

Seeds of the tomato variety ‘Ailsa Craig’ (AC) were obtained from Tomato Genetic Resource Center (TGRC) for experimental use. The seeds were imbibed and placed under dark conditions for 3 days at 25 °C. The germinated seeds were sown in a tray filled with substrate and placed in a growth chamber for a photoperiod of 12 h under a temperature of 25 °C, humidity of 70% and photosynthetic photon flux density of 250 μmol m−2 s−1. Plants were irrigated with 1/2 Hoagland nutrient solution every 4 days. Five-leaf-stage plants were transferred to a growth chamber for heat and cold stress.

2.6. Total RNA Extraction and qRT-PCR Analysis

Tomato leaf samples weighing 0.1 g were immediately frozen in liquid nitrogen and then reserved in −80 °C refrigerator for total RNA extraction. The HiPure Plant RNA Plus Kit (R4150, Magen Biotechnology, Guangzhou, China) was used for total RNA extraction. Then, 0.5 μg of the extracted RNA was transformed into cDNA using the Hiscript II qRT Supermix for qPCR reagent (R223, Vazyme, Nanjing, China). The qRT-PCR was performed on a CFX96 real-time system (Bio-Rad, Hercules, CA, USA). The RT-PCR reaction system included 10 μL of SupRealQ Purple Universal SYBR qPCR Master Mix reagent (Q412, Vazyme, Nanjing, China), 0.4 μL of forward primer (10 μM), 0.4 μL of reverse primer (10 μM), 8.2 μL of ddH2O and 1 μL of cDNA. The reaction procedure consisted of 95 °C for 30 s, 95 °C for 10 s and 60 °C for 30 s. Each reaction was carried out with three replicates and ACTIN was used as the internal reference. The relative expressions of SlSDG genes were calculated using the 2−ΔΔCt method. The primers used for qRT-PCR are listed in the Table S3.

2.7. Protein Extraction and Western Blot Assay

Tomato leaf samples weighing 0.1 g were collected and ground in liquid nitrogen. The protein extraction buffer, which included 50 mM Tris-HCl pH 7.5, 1 mM EDTA, 150 mM NaCl, 1 mM PMSF, 10 mM DTT and 0.2% Triton, was added to the powder. After thorough vortexing, the mixtures were centrifuged with 13,000× g for 10 min at 4 °C. The supernatant was collected and then denatured at 95 °C for 5 min. The 10% SDS-PAGE was used for protein separation. Protein signals were detected with a chemiluminescence kit (FD8030, Fdbio Science, Hangzhou, China). The antibody used in this assay included HSP70 (PHY1305, PhytoAB, San Jose, CA, USA), HSP90 (AS08346, Agrisera, Vannas, Sweden), Actin (AC053, ABclonal, Wuhan, China), Anti-rabbit (HA1001, HUABIO, Hangzhou, China) and Anti-mouse (HA1006, HUABIO, Hangzhou, China). The antibody concentration was prepared following the manufacturer’s guide.

2.8. Virus-Induced Gene Silencing (VIGS) Experiment

The DNA segments of SlSDG14, SlSDG19, SlSDG21, SlSDG23 and SlSDG48 for gene silencing assays were obtained from the VIGS Tool (https://vigs.solgenomics.net/, accessed on 1 March 2025) and then inserted into the EcoRI and BamHI sites of the pTRV2 vector. After sequencing and alignment, the vectors were transformed into Agrobacterium tumefaciens strain GV3101. A previously described VIGS assay for tomato seedlings was used with minor modification [22]. The infection solution was composed of GV3101 strain pTRV1 and pTRV2-SDGs at a 1:1 ratio and an OD600 between 1.2 and 1.5. A mixture of pTRV1 and pTRV2 was used as the control. The composed bacteria were then infiltrated into wild-type tomato (AC) cotyledons. After 2 days under dark treatment, the tomato plants were transferred to a growth chamber under the previously described conditions. Two-and three-leaf-stage plants were used to determine the VIGS silencing efficiency.

2.9. Temperature Stress Treatment and Phenotype Identification

To identify the cold and heat tolerance of tomato, four-and five-leaf-stage plants were transferred to a growth chamber. The leaf sample for RNA isolation was collected at 0 h, 3 h, 6 h, 12 h and 24 h. After 3 days of high temperature treatment and 7 days of cold treatment, the PlantExplore XS (Phenovation B.V., Wageningen, The Netherlands) was used to identify the maximum quantum yield of PSII (Fv/Fm). The protocol for detecting plant electrolyte leakage was described previously, with minor modification [23]. After cold/heat treatment, tomato leaf samples weighing 0.1 g were cut into small segments and placed in 50 mL tubes containing 20 mL deionized water. The electrolyte leakage 1 (EL1) was detected after 2 h of shaking, and electrolyte leakage 1 (EL2) was detected after boiling for 15 min. The relative electrolyte leakage was calculated as the EL1/EL2 ratio.

2.10. Data Statistics and Analysis

Date variance was analyzed using SPSS software (SPSS 16.0) and two-way ANOVA was used to analyze significant differences among multiple groups with p < 0.05.

3. Results

3.1. Identification and Chromosomal Location of SlSDG Gene Family

A total of 48 SlSDG genes containing the SET domain was identified in the whole tomato genome based on the BLAST (Version 2.15.0) search of the functional domain. The SlSDG gene names were named SlSDG1-SlSDG48 according to their chromosomal locations. As shown in Figure S1, SlSDG genes are unevenly distributed across all tomato chromosomes. Among them, ten genes are localized on chromosome 3, which is the highest number among all chromosomes. This is followed by chromosome 7 and 9, which both contain seven SlSDGs and chromosome 1, with six genes. Chromosome 2 contains five SlSDG genes, and chromosome 6 has four genes. The remaining nine SlSDG genes are distributed across six other chromosomes. Chromosome 4, 8 and 11 only have one SlSDG gene each, and chromosome 5, 10 and 12 both have two SlSDG genes.
The comprehensive information of all SlSDG genes is listed in the Table S1. The amino acid lengths of the SlSDGs range from 146 to 2341, with molecular weights ranging from 16.49 to 267.20. The isoelectric point (PI) spans from 4.47 to 9.04. The subcellular locations of all SlSDG proteins were also identified using Cell-PLoc2.0, and 43 SlSDG proteins were found to be located in the nucleus. The subcellular locations of SlSDG1, SlSDG7 and SlSDG24 were the chloroplast or nucleus. SlSDG8 and SlSDG33 were located in the chloroplast only.

3.2. Phylogenetic Analysis of SlSDG Genes

To clarify the evolutionary relationships within the SlSDG gene family in tomato, rice and Arabidopsis, we constructed a phylogenetic tree of 48 SlSDG, 47 AtSDG and 46 OsSDG protein sequences. As shown in Figure 1, all 141 proteins from the three species are divided into seven groups, forming two main branches in the phylogenetic tree. Group V, which forms an independent branch, has the largest number of members, with 17 SlSDG. The remaining six groups independently form another branch. Group I, II and III, which represent E(z) homologs, ASH1 homologs and Trx homologs, respectively, show relatively close relationships. Groups IV, VI and VII are also closely related, with group VI appearing more ancestral compared to the other groups, except for group V.

3.3. Conserved Motif and Gene Structure Analysis of SlSDG Genes

To understand the gene characteristics and structures of SlSDGs, we analyzed the conserved motifs and intron/exon configuration of all SlSDG genes. As shown in Figure 2, they contain 10 conserved motifs (motifs 1–10), with the motif length ranging from 15 to 50 amino acids. In general, the distribution of conserved motifs in SlSDG proteins varies across different groups and is consistent with the group classification identified through phylogenetic analysis. However, group V exhibited small differences, as seven SlSDG proteins, including SlSDG4, SlSDG10, SlSDG11, SlSDG28, SlSDG38, SlSDG41 and SlSDG44, show different motif distribution patterns compared with the others. Motif 8 is a unique motif that distinguishes two components in group V.
The intron–exon configuration provides insight into the fine structure and evolutionary relationships among SlSDGs. The results suggest that SlSDGs have 0–23 introns, with SlSDG21 in group III containing the highest number (23 introns). A total of ten genes was found to have no introns. In addition, it was found that some SlSDG genes do not contain the untranslated region (UTR) structure. Among them, 3 genes only have the 5′UTR region, 9 genes only have the 3′UTR region and 15 genes have no UTR regions.

3.4. Collinearity and Duplication Analysis of SlSDG Gene

To further analyze the evolutionary relationships between SlSDG, AtATX and OsSET, gene collinearity analysis was conducted using TB tools software (Figure 3A). The results showed that there are 26 pairs of orthologous genes in tomato and Arabidopsis, and 6 pairs of SDG genes are collinear with rice. To analyze gene duplication of SlSDGs in tomato, the tomato genome data and genome annotation files were imported into One Step MCScanX within TB tools software. Among the 48 SlSDG genes, 5 duplicate gene pairs were identified (Figure 3B). There are three pairs of tandemly repeated genes in group Ⅴ (SDG27/SDG36, SDG38/SDG41 and SDG42/SDG47), one pair of tandemly repeated genes in group III (SDG6/SDG15) and one pair in group II (SDG2/SDG48).

3.5. Cis-Element Analysis of SlSDG Gene Promoters

To clarify the potential regulating mechanism of the SlSDG gene family, the cis-elements of SDG promoters (2000 bp) were analyzed using the PlantCARE database. As shown in Figure 4, three main categories of cis-elements were assessed: hormone responsive elements, light-responsive elements and abiotic stress response elements. Light responsive elements are relatively abundant in the tomato SDG promoters across the three categories. Additionally, the MeJA elements are widely present in tomato SDG genes compared with the four other hormone-responsive elements. Among all SlSDG genes, SlSDG7 only contains 3 types of cis-elements in this analysis, while SlSDG44 contains the highest number, with 13 cis-elements. These data indicate that tomato SDG genes may participate in plant growth and development.

3.6. Expression Patterns of SlSDG Genes Under Temperature Stress

Based on the analysis of cis-acting elements, we hypothesized that SlSDG genes may be affected by abiotic stress response elements, such as low temperature. Hence, we detected the expression patterns of SlSDGs under heat and cold stress. Tomato leaf samples from the control and treated groups were collected for RNA isolation with five time points, including 0 h, 3 h, 6 h, 12 h and 24 h. We first analyzed the SlSDG gene expression levels under heat stress. As shown in Figure 5A, heat stress notably influences the transcript abundance of SlSDGs. Three SlSDG genes (SlSDG14, SlSDG23 and SlSDG29) are significantly down-regulated after heat stress, while nine genes are notably up-regulated (SlSDG1, SlSDG2, SlSDG8, SlSDG19, SlSDG25, SlSDG34, SlSDG45, SlSDG47 and SlSDG48). Among these genes, SlSDG19 and SlSDG48 exhibit dramatic up-regulation, while SlSDG14 is significantly down-regulated, making them suitable candidates for further examination (Figure S2C–E).
The transcript abundance of SlSDG genes under cold stress was also analyzed. As shown in Figure 5B, 6 genes are up-regulated, while 13 genes are down-regulated under cold treatment. Among these six up-regulated genes (SlSDG3, SlSDG14, SlSDG20, SlSDG21, SlSDG25 and SlSDG48), SlSDG21 shows the most significant increase. Among the 13 down-regulated genes, the expression level of SlSDG23 exhibits the most significant decrease (Figure S2A,B). In conclusion, the SlSDG gene family was found to respond to temperature stress in tomato, and SlSDG14, SlSDG19, SlSDG21, SlSDG23 and SlSDG48 were selected for further verification.

3.7. SlSDG19 and SlSDG48 Positively Regulate and SlSDG14 Negatively Regulates Tomato Heat Tolerance

To further explore whether SlSDG14, SlSDG19 and SlSDG48 regulate tomato heat tolerance, we constructed plants in which the SlSDG14, SlSDG19 and SlSDG48 genes were silenced. The silencing efficiency of the three genes were detected using qRT-PCR, and the results showed that all three genes were significantly silenced compared with the control group (Figure S3A,B,E). As shown in Figure 6, the phenotypes of three gene silenced plants do not significantly differ from those of the control plants (TRV2) under normal conditions. After heat treatment for 3 days, the TRV2-SlSDG19 and TRV2-SlSDG48 plants exhibited more severely wilting phenotypes, lowering the maximum quantum yield of PSII (Fv/Fm) and showing higher electrolyte leakage values compared with the TRV2 plants. Meanwhile, the TRV2-SlSDG14 plants were more tolerant to heat stress than the TRV2 plants, as indicated by the plant phenotype, Fv/Fm values and electrolyte leakage levels. These data suggest that SlSDG19 and SlSDG48 positively regulate, while SlSDG14 negatively regulates, tomato heat tolerance. To investigate how SlSDG genes regulate tomato heat tolerance, we detect the gene expression levels of HSP70 and HSP90 (Figure 6E,F). As shown in Figure 6G, the expression levels of HSP70 and HSP90 in TRV2 plants are significantly up-regulated after treatment at 42 °C for 3 h. However, the expression levels of HSP70 and HSP90 in TRV-SlSDG14 plants were higher than those in TRV2 lines. Meanwhile, they were both lower in the TRV-SlSDG19 and TRV-SlSDG48 lines compared with the TRV2 plants. These data further illustrate that SlSDG14, SlSDG19 and SlSDG48 may regulate the transcription of HSP70 and HSP90 to mediate tomato heat tolerance. To support this, the protein abundance of HSP70 and HSP90 was also measured, showing similar trends to the gene expression levels. After heat treatment for 6 h, the TRV2-SlSDG14 plants aggregated more HSP70 and HSP90 protein compared with the TRV2 plants, while the protein abundances in the TRV2-SlSDG19 and TRV2-SlSDG48 plants were lower than those in the TRV2 plants (Figure 6G). In general, these results indicate that SlSDG19 and SlSDG48 positively regulate, while SlSDG14 negatively regulates tomato heat tolerance by modulating HSP gene expression levels.

3.8. SlSDG21 Positively Regulates and SlSDG23 Negatively Regulates Tomato Cold Tolerance

To further determine whether SlSDG21 and SlSDG48 regulate tomato cold tolerance, we constructed gene silencing vectors for SlSDG21 and SlSDG23 and then transformed them into tomato plants. The silencing efficiency of TRV2-SlSDG21 and TRV2-SlSDG23 were analyzed and successfully gene-silenced tomato plants were subjected to cold treatment (Figure S3C,D). As shown in Figure 7, measurements of the electrolyte leakage, Fv/Fm and phenotype of VIGS and control plants reveal no obvious difference between the TRV2 plants and the TRV2-SlSDG21 or TRV2-SlSDG23 plants under normal temperatures. After cold stress, the TRV2 plants show an impairment and TRV2-SlSDG21 plants exhibit this more severely, while the TRV2-SlSDG23 plants show less injury compared with the TRV2 lines. Meanwhile, silencing SlSDG21 results in higher electrolyte leakage and lower Fv/Fm compared with the TRV2 plants. However, the electrolyte leakage of the TRV2-SlSDG23 plants under cold treatment was lower than that of TRV2 plants, and their Fv/Fm was higher, which indicates that silencing SlSDG23 enhances tomato cold tolerance. Next, we studied whether SlSDG21 and SlSDG23 mediated cold responsive genes to modulate tomato cold tolerance. We detected the relative expression levels of CBF1/2/3 and COR47-like, and the results indicated that silencing SlSDG21 significantly decreases the transcript abundance of CBF1/2/3 and COR47-like compared with the TRV2 plants under cold treatment. In contrast, the expression levels of four genes were higher than those of the control group (TRV2) (Figure 7E–H). In conclusion, these data suggest that SlSDG21 positively regulates and SlSDG23 negatively regulates tomato cold tolerance by modulating the CBF-COR pathway.

4. Discussion

4.1. The Structure, Characteristics and Evolutionary Relationships of Tomato SlSDG Genes

Histone methylation is well known to regulate plant growth and development by influencing chromatin structure and function [24]. SDG proteins are identified as histone lysine methyltransferases that transfer methyl donors to lysine residues [25]. Recently, the SDG gene family has been identified in many crops, including Arabidopsis, rice, Populus trichocarpa and Brassica napus, with its functional roles in plant growth, development and stress tolerance elucidated [6,7,26,27]. In tomato, the SDG gene family has also been previously identified, while the number of genes and functional roles of SDG proteins under temperature stress are still unclear. In this study, the SDG genes of tomato were comprehensively analyzed, and 48 SlSDG genes were identified, which is more than in previous research [28]. This may be due to updates in the tomato genome version based on the development of technology and methods [29,30,31,32]. In detail, Solyc02g093200, Solyc04g024600 and Solyc04g071570, which were all identified in previous works, were verified to contain no SET domain. However, SDG7, SDG8, SDG16, SDG18, SDG24, SDG33, SDG43 and SDG44 were first identified with a SET domain and included in the current work. Among these eight genes, four belonged to group VII, which contains a truncated SET domain and rubisco LSMT substrate-binding domain. Two genes were from group I, and groups V and III each contained one gene. The evolutionary relationship of SDG genes between three species was also studied. The number of SlSDG genes in tomato, rice and Arabidopsis is similar, which suggests evolutionary conservativity of the SDG family in different species. Interestingly, former studies in other species have also identified the conservativity of the SDG family in evolution [33,34]. Moreover, the SDG gene family can be divided into seven groups (I–VII) based on their sequence features and domain architectures [8]. Our research also confirms that tomato SDGs can be classified into seven groups. As shown in Figure 1, groups I, II and III exhibit a close relationship, while groups IV, VI and VII exhibit a similar close relationship. Group V, which consists of Su(var) homolog proteins with a pre-SET-SET-post-SET domain combination, forms a clearly independent branch. The results of phylogenetic analysis and conserved motif analysis suggest that group V may have deeper functional divergence compared with the other groups [35]. In addition, the truncated SET domain exists both in group VI and group VII, which indicates its closer genetic relationship. In the phylogenetic tree (Figure 1), group VI and group VII also exhibit ancestral branches of other groups. Similarly, phylogenetic analysis of Camellia sinensis revealed that it also exhibits the same evolutionary relationships of different SDG groups [36].
Conserved motif analysis can identify recognition sites or coding functional protein domains to reveal the structural and functional diversity among gene family members [37]. In general, the distribution of conserved motifs in different groups follows the same pattern as the evolutionary tree, which reflects the reliability of phylogenetic analysis. In this research, group V showed various patterns of conserved motifs and exhibited a unique gene structure, with seven genes lacking introns. Combined with phylogenetic analysis, evolutionary simplification and functional divergence may occur in group V during evolution.
The results of cis-element analysis provide insight into gene expression patterns and potential regulation mechanisms [38]. In this study, three main types of cis-acting elements were identified, with light-responsive elements being the most abundant, which indicates that there is a potential regulatory relationship between SlSDG gene expression and light conditions. It is worth noting that many SlSDG promoters contain stress-responsive elements related to drought, low temperature and anaerobic conditions, which is similar to the promoter analysis of SDGs in Brassica napus and rice [7,26]. The cis-elements analysis indicated that SlSDG genes may be regulated by hormones, the environment and other factors, highlighting directions to explore the regulating mechanism of tomato SDG proteins.

4.2. Transcript and Genetic Analysis Reveal That SlSDGs Regulate Tomato Heat Stress by Influencing the HSP System

According to previous studies and cis-element analysis, SlSDG genes are highly likely to respond to environmental stresses, such as low temperature and high temperature. Hence, we conducted a heat stress experiment to identify SlSDG expression patterns and select potential responsive genes. SlSDG14 was significantly down-regulated after heat stress, while SlSDG19 and SlSDG48 were notably up-regulated. In previous research, MD17G1091000, an SDG gene of apple, was found to have high expression levels under heat stress [39]. In Gossypium raimondii, the expression levels of several SDG genes significantly fluctuated under heat stimuli, indicating that SDGs may play pivotal roles in modulating plant heat-stress tolerance [40]. Gene-silenced plants for SlSDG14, SlSDG19 and SlSDG48 were generated for further exploration, and the phenotypic results verified that SlSDG19 and SlSDG48 positively regulate, while SlSDG14 negatively regulates tomato heat stress.
Histone methylation regulates gene expression by modulating chromatin structure and function, thereby influencing plant growth and stress tolerance [41]. SDG proteins are responsible for transferring methyl groups to different histone lysine residues, which alters chromatin conformation to regulate gene silencing or expressing [1]. In Arabidopsis, the SDG proteins ATX4 and ATX5 positively regulate the gene expression levels of several downstream genes in the ABA signaling pathway, which further modulates plant drought tolerance [42]. Similarly, rice SDG721 modulates the H3K4me level of OsHKT1;5, increasing plant tolerance to saline-alkaline stress [43]. HSP protein is well known for its function in regulating plant heat stress through multiple pathways, including protein quality control, membrane stability and cellular homeostasis [44]. In Arabidopsis, heat stress induces histone demethylase JMJs, decreasing the H3K27me3 of HSP22 and HSP17.6, and subsequently activating their expression for stronger plant heat resistance [45]. Therefore, we hypothesize that tomato SDGs may also influence the gene expression levels of HSPs to modulate plant heat tolerance. The gene expression levels and protein abundances of HSPs in different tomato lines showed that silencing SlSDG19 and SlSDG48 reduced the transcription abundances and protein levels of HSP70/HSP90, while silencing SlSDG14 showed opposite trends. SlSDG14 is a homologous gene of AtATXR6, a H3K27me1 methyltransferase, which is a repressively transcriptional regulator [46]. Silencing SlSDG14 may decrease the H3K27me1 level of HSP70/HSP90, which further increases the gene expression level. The homologous genes of SlSDG19 and SlSDG48, are AtSUVH5/6 and ASHH3/4, which are responsible for H3K27 methyltransferase. Meanwhile, silencing SlSDG19 and SlSDG48 decreased the gene expression level and protein abundance of HSP70/90, which indicates that SlSDG19 and SlSDG48 may function as histone lysine methyltransferases related to transcriptional activation. The function of SDGs in tomato and Arabidopsis may have diverged [47]. In general, the catalytic sites and activity of tomato SDGs should be clarified, and the histone methylation levels of target genes in TRV-SlSDG14/SlSDG19/SlSDG48 plants require further in-depth investigation.

4.3. Tomato SlSDG21/23 Modulates Cold Tolerance by Mediating the CBFs-CORs Signaling Pathway

Low temperature is a critical abiotic stress that influences the entire process of tomato growth and development [48]. Epigenetic modifications, such as DNA methylation, histone methylation and chromatin remodeling, have been reported to regulate plant cold tolerance through the ICE1-CBF-CORs signaling pathway, membrane lipid structure and membrane fluidity [17,49,50,51]. In Arabidopsis, H3K27me3 levels in two cold-responsive genes, including COR15A and ATGOLS3, decrease under cold stress, leading to enhanced gene expression and improved plant tolerance [17]. Cold treatment also increased histone acetylation at COR6.6 and COR15, increasing the gene expression levels [51]. According to previous studies, we speculated that tomato SDG genes may participate in cold stress responses. Gene transcript abundance analysis under cold stress revealed that SlSDG21 and SlSDG23 were affected by low temperatures. Further genetic validation confirmed that SlSDG21 positively regulates and SlSDG23 negatively regulates tomato cold tolerance. The CBF-CORs pathway is a well-studied classical cold signaling transduction pathway in plants, with a complex regulation mechanism [48]. The gene expression levels of CBF1/2/3 and COR47-like in TRV2, TRV2-SlSDG21 and TRV2-SlSDG23 plants were detected. The results suggest that SlSDG21 and SlSDG23 modulate tomato cold tolerance through the CBF-CORs pathway. Phylogenetic analysis indicated that SlSDG21 is a homologous gene of AtATX3, which encodes a H3K4me methyltransferase. Silencing SlSDG21 may reduce the level of H3K4me at the CBFs/CORs locus, ultimately decreasing tomato cold tolerance. For SlSDG23, the homologous gene in Arabidopsis is ATXR1, whose methylation site is still unclear. SlSDG23 may regulate the histone methylation sites associated with transcriptional inhibition. Silencing SlSDG23 decreased the methylation of CBFs/CORs and increased the gene expression level. In general, the regulation mechanisms of plant SDG proteins in cold stress are still unclear. How tomato SDG proteins modulate the CBF-COR signaling pathway requires further investigation.

5. Conclusions

In conclusion, 48 SlSDG genes were identified in tomato through genome-wide analysis, and their conserved motifs, gene structures and evolutionary relationships were explored. Cis-element analysis revealed that tomato SDG genes may participate in growth, development and stress responses. qRT-PCR analysis revealed that SlSDG genes play roles in tomato heat and cold stress. In addition, a VIGS assay identified the SDG genes that modulate tomato heat tolerance and cold tolerance through the HSP system and CBF-COR pathway, respectively. These findings provide a theoretical basis for further study of the function of SDG genes and the regulatory mechanisms underlying tomato tolerance to temperature stress.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/horticulturae11080958/s1, Figure S1: Chromosomal localization of the SlSDG genes in tomato. The grey bar structure represents the chromosome. The chromosome number displayed in black font is labelled above the grey bar. SlSDG genes are represented in red font on right side of chromosomes. Scale represents a 20 Mb chromosomal distance; Figure S2: The relative expression level of SlSDG genes under heat and cold stress. (A,B) The gene expression level of SlSDG21 and SlSDG23 under cold stress with time courses (0 h, 3 h, 6 h, 12 h and 24 h). (C–E) The gene expression level of SlSDG14, SlSDG19 and SlSDG23 under heat stress with time courses (0 h, 3 h, 6 h, 12 h and 24 h); Figure S3: The silence efficiency of VIGS plants. (A) The gene expression level of SlSDG14 in TRV2 and TRV2-SDG14 plants. (B) The gene expression level of SDG19 in TRV2 and TRV2-SDG19 plants. (C) The gene expression level of SDG21 in TRV2 and TRV2-SDG21 plants. (D) The gene expression level of SDG23 in TRV2 and TRV2-SDG23 plants. (E) The gene expression level of SDG48 in TRV2 and TRV2-SDG48 plants; Table S1: SlSDG gene family members and related information; Table S2: The list of conserved motifs found in SlSDG proteins; Table S3: The primers used in qRT-PCR analysis in this study; Table S4: Primer sequence of tomato VIGS assay.

Author Contributions

C.L. (Chuanlong Lu): writing—original draft. Y.C.: conceptualization, writing—review and editing. H.W. (Hongjian Wan): writing—review and editing. Z.Y.: investigation. M.R.: investigation. R.W.: Investigation. Q.Y.: investigation. G.Z.: writing—review and editing, project administration. H.W. (Huasen Wang): conceptualization, methodology, project administration. C.L. (Chenxu Liu): conceptualization, writing—review and editing, project administration. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Zhejiang “Nine aspects of three Rural issues” Science and Technology Cooperation Plan (2024SNJF014), National Natural Science Foundation of China (32341044), Zhejiang Provincial Major Agricultural Science and Technology Projects of New Varieties Breeding (2016C02051), National Key Research and Development Program of China (2023YFD1201504) and the Qingdao Science and Technology Benefiting People Demonstration Special Project (25-1-5-xdny-13-nsh).

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors on request.

Conflicts of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

References

  1. Liu, C.Y.; Lu, F.L.; Cui, X.; Cao, X.F. Histone methylation in higher plants. Annu. Rev. Plant Biol. 2010, 61, 395–420. [Google Scholar] [CrossRef] [PubMed]
  2. Jenuwein, T.; Allis, C.D. Translating the histone code. Science 2001, 293, 1074–1080. [Google Scholar] [CrossRef]
  3. Deng, X.; Song, X.W.; Wei, L.Y.; Liu, C.Y.; Cao, X.F. Epigenetic regulation and epigenomic landscape in rice. Natl. Sci. Rev. 2016, 3, 309–327. [Google Scholar] [CrossRef]
  4. Xiao, J.; Lee, U.S.; Wagner, D. Tug of war: Adding and removing histone lysine methylation in Arabidopsis. Curr. Opin. Plant Biol. 2016, 34, 41–53. [Google Scholar] [CrossRef]
  5. Klose, R.J.; Zhang, Y. Regulation of histone methylation by demethylimination and demethylation. Nat. Rev. Mol. Cell Biol. 2007, 8, 307–318. [Google Scholar] [CrossRef] [PubMed]
  6. Ng, D.W.K.; Wang, T.; Chandrasekharan, M.B.; Aramayo, R.; Kertbundit, S.; Hall, T.C. Plant SET domain-containing proteins: Structure, function and regulation. Biochim. Biophys. Acta (BBA)—Gene Struct. Expr. 2007, 1769, 316–329. [Google Scholar] [CrossRef]
  7. Sehrish, S.; Sumbal, W.; Xie, M.L.; Zhao, C.J.; Zuo, R.; Gao, F.; Liu, S.Y. Genome-wide identification and characterization of SET domain family genes in Brassica napus L. Int. J. Mol. Sci. 2022, 23, 1936. [Google Scholar] [CrossRef]
  8. Zhou, H.Y.; Liu, Y.H.; Liang, Y.W.; Zhou, D.; Li, S.F.; Lin, S.; Dong, H.; Huang, L. The function of histone lysine methylation related SET domain group proteins in plants. Protein Sci. 2020, 29, 1120–1137. [Google Scholar] [CrossRef]
  9. Thorstensen, T.; Grini, P.E.; Aalen, R.B. SET domain proteins in plant development. Biochim. Biophys. Acta (BBA)—Gene Regul. Mech. 2011, 1809, 407–420. [Google Scholar] [CrossRef]
  10. Liu, Y.T.; Wang, J.; Liu, B.; Xu, Z.Y. Dynamic regulation of DNA methylation and histone modifications in response to abiotic stresses in plants. J. Integr. Plant Biol. 2022, 64, 2252–2274. [Google Scholar] [CrossRef] [PubMed]
  11. Alvarez Venegas, R.; Pien, S.; Sadder, M.; Witmer, X.; Grossniklaus, U.; Avramova, Z. ATX-1, an Arabidopsis homolog of trithorax, activates flower homeotic genes. Curr. Biol. 2003, 13, 627–637. [Google Scholar] [CrossRef]
  12. Zheng, J.; Chen, F.Y.; Wang, Z.; Cao, H.; Li, X.Y.; Deng, X.; Soppe, W.J.J.; Li, Y.; Liu, Y.X. A novel role for histone methyltransferase KYP/SUVH4 in the control of Arabidopsis primary seed dormancy. New Phytol. 2012, 193, 605–616. [Google Scholar] [CrossRef] [PubMed]
  13. Lee, K.; Park, O.S.; Choi, C.Y.; Seo, P.J. ARABIDOPSIS TRITHORAX 4 facilitates shoot identity establishment during the plant regeneration process. Plant Cell Physiol. 2019, 60, 826–834. [Google Scholar] [CrossRef]
  14. Gu, D.C.; Ji, R.J.; He, C.M.; Peng, T.; Zhang, M.Y.; Duan, J.; Xiong, C.Y.; Liu, X.C. Arabidopsis histone methyltransferase SUVH5 is a positive regulator of light-mediated seed germination. Front. Plant Sci. 2019, 10, 841. [Google Scholar] [CrossRef]
  15. Chang, Y.N.; Zhu, C.; Jiang, J.; Zhang, H.; Zhu, J.K.; Duan, C.G. Epigenetic regulation in plant abiotic stress responses. J. Integr. Plant Biol. 2020, 62, 563–580. [Google Scholar] [CrossRef]
  16. Song, Z.T.; Zhang, L.L.; Han, J.J.; Zhou, M.; Liu, J.X. Histone H3K4 methyltransferases SDG25 and ATX1 maintain heat-stress gene expression during recovery in Arabidopsis. Plant J. 2021, 105, 1326–1338. [Google Scholar] [CrossRef]
  17. Kwon, C.S.; Lee, D.; Choi, G.; Chung, W.I. Histone occupancy-dependent and -independent removal of H3K27 trimethylation at cold-responsive genes in Arabidopsis. Plant J. 2009, 60, 112–121. [Google Scholar] [CrossRef]
  18. Zhang, X.; Ménard, R.; Li, Y.; Coruzzi, G.M.; Heitz, T.; Shen, W.H.; Berr, A. Arabidopsis SDG8 potentiates the sustainable transcriptional induction of the pathogenesis-related genes PR1 and PR2 during plant defense response. Front. Plant Sci. 2020, 11, 277. [Google Scholar] [CrossRef] [PubMed]
  19. Berr, A.; McCallum, E.J.; Alioua, A.; Heintz, D.; Heitz, T.; Shen, W.H. Arabidopsis histone methyltransferase SET DOMAIN GROUP8 mediates induction of the jasmonate/ethylene pathway genes in plant defense response to necrotrophic fungi. Plant Physiol. 2010, 154, 1403–1414. [Google Scholar] [CrossRef]
  20. Tieman, D.; Zhu, G.T.; Resende, M.F.R.; Lin, T.; Nguyen, C.; Bies, D.; Rambla, J.L.; Beltran, K.S.O.; Taylor, M.; Zhang, B.; et al. A chemical genetic roadmap to improved tomato flavor. Science 2017, 355, 391–394. [Google Scholar] [CrossRef] [PubMed]
  21. Liu, W.; Liu, K.; Chen, D.G.; Zhang, Z.Q.; Li, B.Q.; El-Mogy, M.M.; Tian, S.P.; Chen, T. Solanum lycopersicum, a model plant for the studies in developmental biology, stress biology and food science. Foods 2022, 11, 2402. [Google Scholar] [CrossRef]
  22. Xia, X.-J.; Gao, C.-J.; Song, L.-X.; Zhou, Y.-H.; Shi, K.; Yu, J.-Q. Role of dynamics in brassinosteroid-induced stomatal closure and opening in Solanum lycopersicum. Plant Cell Environ. 2014, 37, 2036–2050. [Google Scholar] [CrossRef] [PubMed]
  23. Cao, W.H.; Liu, J.; He, X.J.; Mu, R.L.; Zhou, H.L.; Chen, S.Y.; Zhang, J.S. Modulation of ethylene responses affects plant salt-stress responses. Plant Physiol. 2007, 143, 707–719. [Google Scholar] [CrossRef]
  24. Sui, P.F.; Jin, J.; Ye, S.; Mu, C.; Gao, J.; Feng, H.Y.; Shen, W.H.; Yu, Y.; Dong, A.W. H3K36 methylation is critical for brassinosteroid-regulated plant growth and development in rice. Plant J. 2012, 70, 340–347. [Google Scholar] [CrossRef]
  25. Strahl, B.D.; Ohba, R.; Cook, R.G.; Allis, C.D. Methylation of histone H3 at lysine 4 is highly conserved and correlates with transcriptionally active nuclei in Tetrahymena. Proc. Natl. Acad. Sci. USA 1999, 96, 14967–14972. [Google Scholar] [CrossRef] [PubMed]
  26. Lu, Z.H.; Huang, X.L.; Ouyang, Y.D.; Yao, J.L. Genome-wide identification, phylogenetic and co-expression analysis of OsSET gene family in rice. PLoS ONE 2013, 8, e65426. [Google Scholar] [CrossRef]
  27. Lei, L.; Zhou, S.L.; Ma, H.; Zhang, L.S. Expansion and diversification of the SET domain gene family following whole-genome duplications in Populus trichocarpa. BMC Evol. Biol. 2012, 12, 51. [Google Scholar] [CrossRef] [PubMed]
  28. Aiese Cigliano, R.; Sanseverino, W.; Cremona, G.; Ercolano, M.R.; Conicella, C.; Consiglio, F.M. Genome-wide analysis of histone modifiers in tomato: Gaining an insight into their developmental roles. BMC Genom. 2013, 14, 57. [Google Scholar] [CrossRef]
  29. Lin, T.; Zhu, G.T.; Zhang, J.H.; Xu, X.Y.; Yu, Q.H.; Zheng, Z.; Zhang, Z.H.; Lun, Y.Y.; Li, S.; Wang, X.X.; et al. Genomic analyses provide insights into the history of tomato breeding. Nat. Genet. 2014, 46, 1220–1226. [Google Scholar] [CrossRef]
  30. Su, X.; Wang, B.; Geng, X.L.; Du, Y.F.; Yang, Q.Q.; Liang, B.; Meng, G.; Gao, Q.; Yang, W.C.; Zhu, Y.F.; et al. A high-continuity and annotated tomato reference genome. BMC Genom. 2021, 22, 898. [Google Scholar] [CrossRef]
  31. Zhou, Y.; Zhang, Z.Y.; Bao, Z.G.; Li, H.B.; Lyu, Y.Q.; Zan, Y.J.; Wu, Y.Y.; Cheng, L.; Fang, Y.H.; Wu, K.; et al. Graph pangenome captures missing heritability and empowers tomato breeding. Nature 2022, 606, 527–534. [Google Scholar] [CrossRef] [PubMed]
  32. Li, N.; He, Q.; Wang, J.; Wang, B.; Zhao, J.T.; Huang, S.Y.; Yang, T.; Tang, Y.P.; Yang, S.B.; Aisimutuola, P.; et al. Super-pangenome analyses highlight genomic diversity and structural variation across wild and cultivated tomato species. Nat. Genet. 2023, 55, 852–860. [Google Scholar] [CrossRef]
  33. Zhang, L.S.; Ma, H. Complex evolutionary history and diverse domain organization of SET proteins suggest divergent regulatory interactions. New Phytol. 2012, 195, 248–263. [Google Scholar] [CrossRef]
  34. Chen, D.H.; Qiu, H.L.; Huang, Y.; Zhang, L.; Si, J.P. Genome-wide identification and expression profiling of SET DOMAIN GROUP family in Dendrobium catenatum. BMC Plant Biol. 2020, 20, 40. [Google Scholar] [CrossRef]
  35. Zhu, X.Y.; Ma, H.; Chen, Z.D. Phylogenetics and evolution of Su(var)3-9 SET genes in land plants: Rapid diversification in structure and function. BMC Evol. Biol. 2011, 11, 63. [Google Scholar] [CrossRef] [PubMed]
  36. Chen, Q.H.; Hu, S.L.; Guo, F.; Zhao, H.; Wang, M.L.; Ni, D.J.; Wang, Y.; Wang, P. Characterization of the SET DOMAIN GROUP gene family members in Camellia sinensis and functional analysis of the SDG43 gene in abiotic stresses. Environ. Exp. Bot. 2021, 182, 104306. [Google Scholar] [CrossRef]
  37. Li, Z.X.; Yao, Z.P.; Ruan, M.Y.; Wang, R.Q.; Ye, Q.J.; Wan, H.J.; Zhou, G.Z.; Cheng, Y.; Guo, S.J.; Liu, C.C.; et al. The PLA gene family in tomato: Identification, phylogeny, and functional characterization. Genes 2025, 16, 130. [Google Scholar] [CrossRef] [PubMed]
  38. Pang, X.; Chen, J.; Xu, Y.; Liu, J.; Zhong, Y.; Wang, L.; Zheng, J.; Wan, H. Genome-wide characterization of ascorbate peroxidase gene family in pepper (Capsicum annuum L.) in response to multiple abiotic stresses. Front. Plant Sci. 2023, 14, 1189020. [Google Scholar] [CrossRef]
  39. Li, W.J.; Yan, J.J.; Wang, S.C.; Wang, Q.Y.; Wang, C.X.; Li, Z.X.; Zhang, D.H.; Ma, F.W.; Guan, Q.M.; Xu, J.D. Genome-wide analysis of SET-domain group histone methyltransferases in apple reveals their role in development and stress responses. BMC Genom. 2021, 22, 283. [Google Scholar] [CrossRef]
  40. Huang, Y.; Mo, Y.J.; Chen, P.Y.; Yuan, X.L.; Meng, F.N.; Zhu, S.W.; Liu, Z. Identification of SET Domain-containing proteins in Gossypium raimondii and their response to high temperature stress. Sci. Rep. 2016, 6, 32729. [Google Scholar] [CrossRef] [PubMed]
  41. Yancoskie, M.N.; Maritz, C.; van Eijk, P.; Reed, S.H.; Naegeli, H. To incise or not and where: SET-domain methyltransferases know. Trends Biochem. Sci. 2023, 48, 321–330. [Google Scholar] [CrossRef]
  42. Liu, Y.T.; Zhang, A.; Yin, H.; Meng, Q.X.; Yu, X.M.; Huang, S.Z.; Wang, J.; Ahmad, R.; Liu, B.; Xu, Z.Y. Trithorax-group proteins ARABIDOPSIS TRITHORAX4 (ATX4) and ATX5 function in abscisic acid and dehydration stress responses. New Phytol. 2018, 217, 1582–1597. [Google Scholar] [CrossRef]
  43. Liu, Y.T.; Chen, X.; Xue, S.Y.; Quan, T.Y.; Cui, D.; Han, L.Z.; Cong, W.X.; Li, M.T.; Yun, D.J.; Liu, B.; et al. SET DOMAIN GROUP 721 protein functions in saline–alkaline stress tolerance in the model rice variety Kitaake. Plant Biotechnol. J. 2021, 19, 2576–2588. [Google Scholar] [CrossRef]
  44. Askari Khorasgani, O.; Pessarakli, M. Protective roles of plant proteins in conferring tolerance to heat stress. J. Plant Nutr. 2019, 42, 1114–1123. [Google Scholar] [CrossRef]
  45. Yamaguchi, N.; Matsubara, S.; Yoshimizu, K.; Seki, M.; Hamada, K.; Kamitani, M.; Kurita, Y.; Nomura, Y.; Nagashima, K.; Inagaki, S.; et al. H3K27me3 demethylases alter HSP22 and HSP17.6C expression in response to recurring heat in Arabidopsis. Nat. Commun. 2021, 12, 3480. [Google Scholar] [CrossRef] [PubMed]
  46. Potok, M.E.; Zhong, Z.H.; Picard, C.L.; Liu, Q.K.; Do, T.; Jacobsen, C.E.; Sakr, O.; Naranbaatar, B.; Thilakaratne, R.; Khnkoyan, Z.; et al. The role of ATXR6 expression in modulating genome stability and transposable element repression in Arabidopsis. Proc. Natl. Acad. Sci. USA 2022, 119, e2115570119. [Google Scholar] [CrossRef] [PubMed]
  47. Bvindi, C.; Lee, S.; Tang, L.; Mickelbart, M.V.; Li, Y.; Mengiste, T. Improved pathogen and stress tolerance in tomato mutants of SET domain histone 3 lysine methyltransferases. New Phytol. 2022, 235, 1957–1976. [Google Scholar] [CrossRef]
  48. Ding, Y.L.; Shi, Y.T.; Yang, S.H. Advances and challenges in uncovering cold tolerance regulatory mechanisms in plants. New Phytol. 2019, 222, 1690–1704. [Google Scholar] [CrossRef] [PubMed]
  49. Song, C.B.; Yang, Y.Y.; Yang, T.W.; Ba, L.J.; Zhang, H.; Han, Y.C.; Xiao, Y.Y.; Shan, W.; Kuang, J.F.; Chen, J.Y.; et al. MaMYB4 recruits histone deacetylase MaHDA2 and modulates the expression of ω-3 fatty acid desaturase genes during cold stress response in banana fruit. Plant Cell Physiol. 2019, 60, 2410–2422. [Google Scholar] [CrossRef]
  50. Liu, L.J.; Song, Y.; Xu, J.; Li, D.M.; Li, G.P.; An, L.Z. Differential expression by chromatin modifications of alcohol dehydrogenase 1 of Chorispora bungeana in cold stress. Gene 2017, 636, 1–16. [Google Scholar] [CrossRef]
  51. To, T.K.; Nakaminami, K.; Kim, J.-M.; Morosawa, T.; Ishida, J.; Tanaka, M.; Yokoyama, S.; Shinozaki, K.; Seki, M. Arabidopsis HDA6 is required for freezing tolerance. Biochem. Biophys. Res. Commun. 2011, 406, 414–419. [Google Scholar] [CrossRef] [PubMed]
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Figure 1. Phylogenetic tree analysis of SDG proteins in tomato, rice and Arabidopsis. The phylogenetic tree was constructed with MEGA11 software using the maximum likelihood method. Pink is group I, yellow is group II, blue is group III, orange is group IV, purple is group V, red is group VI and green is group VII.
Figure 1. Phylogenetic tree analysis of SDG proteins in tomato, rice and Arabidopsis. The phylogenetic tree was constructed with MEGA11 software using the maximum likelihood method. Pink is group I, yellow is group II, blue is group III, orange is group IV, purple is group V, red is group VI and green is group VII.
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Figure 2. Analysis of the conserved motifs and gene structure of the tomato SlSDG gene family. (A) Conserved motifs of SDG proteins in seven groups. Motif 1 to motif 10 are listed with different color boxes. The X axis represents the length of the amino acid. (B) The gene structure of the SlSDG family. The yellow box represents the exon regions, the black line represents the intron regions and the green box represents the untranslated regions (UTR). The X axis represents gene length.
Figure 2. Analysis of the conserved motifs and gene structure of the tomato SlSDG gene family. (A) Conserved motifs of SDG proteins in seven groups. Motif 1 to motif 10 are listed with different color boxes. The X axis represents the length of the amino acid. (B) The gene structure of the SlSDG family. The yellow box represents the exon regions, the black line represents the intron regions and the green box represents the untranslated regions (UTR). The X axis represents gene length.
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Figure 3. Collinearity and homogeneity analysis of SDG genes. (A) The collinearity analysis of SDG genes on the chromosomes of tomato, Arabidopsis and rice. The grey lines represent collinear regions in tomato and other plants, while the blue lines highlight collinear gene pairs between SDG members from different species. (B) Duplication genes in the SDG gene family. The grey box represents the chromosomes and the red line represents the tandem replication line relationship between SDG genes.
Figure 3. Collinearity and homogeneity analysis of SDG genes. (A) The collinearity analysis of SDG genes on the chromosomes of tomato, Arabidopsis and rice. The grey lines represent collinear regions in tomato and other plants, while the blue lines highlight collinear gene pairs between SDG members from different species. (B) Duplication genes in the SDG gene family. The grey box represents the chromosomes and the red line represents the tandem replication line relationship between SDG genes.
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Figure 4. The prediction of cis-acting elements in the promoter region of the SlSDG gene family. Each box contains the number of cis-acting elements.
Figure 4. The prediction of cis-acting elements in the promoter region of the SlSDG gene family. Each box contains the number of cis-acting elements.
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Figure 5. The gene expression patterns of SlSDG genes under heat stress and cold stress. (A,B) A heatmap of SlSDG gene expression levels under heat stress and cold stress, respectively. Cluster analysis results of expression patterns of SlSDG genes at 0 h, 3 h, 6 h, 12 h and 24 h under heat stress and cold stress. Heat-map data were transformed through log2 function conversion and illustrated with color transition between high expression (red) and low expression (blue).
Figure 5. The gene expression patterns of SlSDG genes under heat stress and cold stress. (A,B) A heatmap of SlSDG gene expression levels under heat stress and cold stress, respectively. Cluster analysis results of expression patterns of SlSDG genes at 0 h, 3 h, 6 h, 12 h and 24 h under heat stress and cold stress. Heat-map data were transformed through log2 function conversion and illustrated with color transition between high expression (red) and low expression (blue).
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Figure 6. SlSDG19 and SlSDG48 positively regulate and SlSDG14 negatively regulates tomato heat tolerance. (A) Phenotypes of TRV2, TRV2-SlSDG14, TRV2-SlSDG19 and TRV2-SlSDG48 lines under normal conditions and heat stress. Bar = 10 cm. (B,D) The maximum quantum yield of PSII (Fv/Fm) in TRV2, TRV2-SlSDG14, TRV2-SlSDG19 and TRV2-SlSDG48 plants exposed to normal and heat conditions after 7 days. (C) Relative electrolyte leakage of TRV2, TRV2-SlSDG14, TRV2-SlSDG19 and TRV2-SlSDG48 plants exposed to normal and heat conditions after 7 days. (E,F) The relative expression levels of HSP70 and HSP90 in TRV2, TRV2-SlSDG14, TRV2-SlSDG19 and TRV2-SlSDG48 plants exposed to heat stress at different time points (0 h, 3 h, 6 h and 12 h). (G) The protein abundances of HSP70, HSP90 and Actin in TRV2, TRV2-SlSDG14, TRV2-SlSDG19 and TRV2-SlSDG48 plants exposed to heat stress for 6 h. Different letters denote significant differences (p < 0.05).
Figure 6. SlSDG19 and SlSDG48 positively regulate and SlSDG14 negatively regulates tomato heat tolerance. (A) Phenotypes of TRV2, TRV2-SlSDG14, TRV2-SlSDG19 and TRV2-SlSDG48 lines under normal conditions and heat stress. Bar = 10 cm. (B,D) The maximum quantum yield of PSII (Fv/Fm) in TRV2, TRV2-SlSDG14, TRV2-SlSDG19 and TRV2-SlSDG48 plants exposed to normal and heat conditions after 7 days. (C) Relative electrolyte leakage of TRV2, TRV2-SlSDG14, TRV2-SlSDG19 and TRV2-SlSDG48 plants exposed to normal and heat conditions after 7 days. (E,F) The relative expression levels of HSP70 and HSP90 in TRV2, TRV2-SlSDG14, TRV2-SlSDG19 and TRV2-SlSDG48 plants exposed to heat stress at different time points (0 h, 3 h, 6 h and 12 h). (G) The protein abundances of HSP70, HSP90 and Actin in TRV2, TRV2-SlSDG14, TRV2-SlSDG19 and TRV2-SlSDG48 plants exposed to heat stress for 6 h. Different letters denote significant differences (p < 0.05).
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Figure 7. SlSDG21 positively regulates and SlSDG23 negatively regulates tomato cold tolerance. (A) Phenotypes of TRV2, TRV2-SlSDG21 and TRV2-SlSDG23 lines under normal and cold stress. Bar = 10 cm. (B,D) The maximum quantum yield of PSII (Fv/Fm) in TRV2, TRV2-SlSDG21 and TRV2-SlSDG23 plants exposed to normal and heat condition after 7 days. (C) Relative electrolyte leakage levels of TRV2, TRV2-SlSDG21 and TRV2-SlSDG23 exposed to normal and heat conditions after 7 days. (E–H) The relative expression levels of CBF1, CBF2, CBF3 and COR47-like in TRV2, TRV2-SlSDG21 and TRV2-SlSDG23 plants exposed to cold stress at different time points (0 h, 3 h, 6 h and 12 h). Different letters denote significant differences (p < 0.05).
Figure 7. SlSDG21 positively regulates and SlSDG23 negatively regulates tomato cold tolerance. (A) Phenotypes of TRV2, TRV2-SlSDG21 and TRV2-SlSDG23 lines under normal and cold stress. Bar = 10 cm. (B,D) The maximum quantum yield of PSII (Fv/Fm) in TRV2, TRV2-SlSDG21 and TRV2-SlSDG23 plants exposed to normal and heat condition after 7 days. (C) Relative electrolyte leakage levels of TRV2, TRV2-SlSDG21 and TRV2-SlSDG23 exposed to normal and heat conditions after 7 days. (E–H) The relative expression levels of CBF1, CBF2, CBF3 and COR47-like in TRV2, TRV2-SlSDG21 and TRV2-SlSDG23 plants exposed to cold stress at different time points (0 h, 3 h, 6 h and 12 h). Different letters denote significant differences (p < 0.05).
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MDPI and ACS Style

Lu, C.; Cheng, Y.; Wan, H.; Yao, Z.; Ruan, M.; Wang, R.; Ye, Q.; Zhou, G.; Wang, H.; Liu, C. Identification of Tomato SET Domain Group Gene Family and Function Analysis Under Temperature Stress. Horticulturae 2025, 11, 958. https://doi.org/10.3390/horticulturae11080958

AMA Style

Lu C, Cheng Y, Wan H, Yao Z, Ruan M, Wang R, Ye Q, Zhou G, Wang H, Liu C. Identification of Tomato SET Domain Group Gene Family and Function Analysis Under Temperature Stress. Horticulturae. 2025; 11(8):958. https://doi.org/10.3390/horticulturae11080958

Chicago/Turabian Style

Lu, Chuanlong, Yuan Cheng, Hongjian Wan, Zhuping Yao, Meiying Ruan, Rongqing Wang, Qingjing Ye, Guozhi Zhou, Huasen Wang, and Chenxu Liu. 2025. "Identification of Tomato SET Domain Group Gene Family and Function Analysis Under Temperature Stress" Horticulturae 11, no. 8: 958. https://doi.org/10.3390/horticulturae11080958

APA Style

Lu, C., Cheng, Y., Wan, H., Yao, Z., Ruan, M., Wang, R., Ye, Q., Zhou, G., Wang, H., & Liu, C. (2025). Identification of Tomato SET Domain Group Gene Family and Function Analysis Under Temperature Stress. Horticulturae, 11(8), 958. https://doi.org/10.3390/horticulturae11080958

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