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Article

Identification of Key Regulatory Factors of Molecular Marker TGS377 on Chromosome 1 and Its Response to Cold Stress in Tomato

by
Jia-Qi Zhang
1,
Jian-Ping Tao
1,
Liu-Xia Song
2,
Rong-Rong Zhang
1,
Hui Liu
1,
Tong-Min Zhao
1,2,*,
Wei-Min Zhu
1,3,* and
Ai-Sheng Xiong
1,*
1
State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Horticulture, Nanjing Agricultural University, Nanjing 210095, China
2
Institute of Vegetable Crops, Jiangsu Academy of Agricultural Sciences/Jiangsu Key Laboratory for Horticultural Crop Genetic Improvement, Nanjing 210014, China
3
Protected Horticultural Research Institute, Shanghai Academy Agricultural Sciences, Shanghai 201403, China
*
Authors to whom correspondence should be addressed.
Agronomy 2022, 12(12), 2985; https://doi.org/10.3390/agronomy12122985
Submission received: 27 September 2022 / Revised: 12 November 2022 / Accepted: 25 November 2022 / Published: 28 November 2022
(This article belongs to the Special Issue Recent Advances in Horticultural Crops-from Omics to Biotechnology)
Browse Figures
Versions Notes

Abstract

:
Low temperature, as a kind of stress factor, often leads to tomato growth stagnation or yield reduction or even no harvest in production. At present, numerous genes have been shown to be involved in the regulation of cold resistance in the tomato. Complex regulatory mechanisms responding to low temperature stress in the tomato are still unclear in their details. In this study, six accessions of tomato (‘NL-7’, ‘NL-15’, ‘NL-18’, ‘NL-21, ‘NL-37’, and ‘NL-67’) with different cold tolerance were selected to detect the response to low temperature. The results showed that ‘NL-15’, ‘NL-18’, and ‘NL-21’ tomato accessions had cold tolerance under 8 °C/6 °C (day/night) for 15-day treatments. The TGS377 molecular marker, closely related to cold tolerance, was located on chromosome 1. The potential factors were identified and bioinformatics analysis within 50 kb upstream and downstream of TGS377. Fifteen genes were identified, and their structural analysis and functional annotation were also performed. The expression levels of Solyc01g008480 and Solyc01g150104 in the cold-sensitive tomato accessions (‘NL-7’, ‘NL-37’, and ‘NL-67’) were higher than that in the cold-tolerant accessions (‘NL-15’, ‘NL-18’ and ‘NL-21’). The expression levels of Solyc01g008390 and Solyc01g008410 in the cold-tolerant tomato ‘NL-18’ accession was significantly higher than that in the cold-sensitive accessions (‘NL-15’, ‘NL-18’, and ‘NL-21’). The results suggested that these genes may be involved in regulating low temperature response in the tomato, which lays a foundation for the search of potential cold response regulators in the tomato.

1. Introduction

In recent years, extreme temperatures have been more common as the climate change process has intensified, which affects agricultural production and leads to reduced or even no harvest [1,2]. Low temperatures limit crop development and yield formation as an essential abiotic stress factor [3,4]. Generally, the impact of low temperatures 0 °C to 12 °C on tomato plants was referred to as chilling damage, whereas the impact of low temperatures below 0 °C on plants was referred to as freezing damage [5,6]. The crops from tropical and subtropical locations fail to grow and develop correctly, or possibly die due to low temperature stress [7]. The effects of low temperature on plant morphology, cell structure, and physiological active substances are reflected in many aspects. Plants develop weakly and wither. The fluidity of the cell membrane decreases, the degree of lipid peroxidation of the membrane increases, the selective permeability decreases, and cell activity decreases. The content of reactive oxygen species (ROS) substances in plants increases. In addition, the activities of various antioxidant enzymes in plants decreases and biochemical reactions are blocked [8,9,10,11].
Molecular marker technology emerged in the 1980s as a method to detect genetic differences in organisms at the level of DNA molecules [12]. Molecular markers have good stability, are not affected by the growth environment or season, and can detect genetic changes in the tested species rapidly and reliably [13]. As a result, the technology is widely utilized in the identification of plant species, the creation of genetic maps, and the detection of genetic variation [14]. Up to now, molecular marker technology has been commonly used to identify genetic differences in cabbage (Brassica oleracea L.) [15], celery (Apium graveolens L. var. dulce) [16], potato (Solanum tuberosum L.) [17], pepper (Capsicum annuum L.) [18], and tomato (Solanum lycopersicum L.) [19]. Foolad et al. detected three and four QTLs related to cold response in BC1 populations with parent S. lycopersicum NC84173 and S. pimpinellifolium LA722 tomatoes using RFLP markers, which were located on chromosome 1 and chromosome 4, respectively [20]. There were lots of molecular markers associated with cold tolerance on the chromosome 1 of tomatoes, including TG301, TG125, TGS329, TGS377, and so on [20,21]. Among these molecular markers associated with cold tolerance, the molecular marker TGS377, which is closely related to low temperature stress response and located at 2.47 Mb on the tomato chromosome 1, was selected.
Tomatoes (Solanum lycopersicum L.), a popular solanaceous vegetable, are usually grown in solar greenhouses throughout northern China [22,23]. The tomato (Solanum lycopersicum L.) is a subtropical plant that prefers a warm climate and cannot resist low temperatures [24,25]. According to statistics, the global tomato production in 2020 was 186,821,216 tons, while China’s tomato production was 64,768,158 tons, accounting for 34.67% of world production (FAOSTAT, 2020). Tomatoes are rich in bioactive substances, such as ascorbic acid and lycopene, which help to promote health and disease prevention in humans [26,27]. Tomato plants are frequently affected by low temperatures in the winter and spring, which have a negative impact on their growth and development [28]. Previous studies have shown that exogenous application of 5-aminolevulinic acid (ALA) under low temperature stress can improve the reactive oxygen species (ROS)’s scavenging ability of tomatoes and alleviate the effects of low temperature on the growth and development of roots in tomatoes [29]. Exogenous application of potassium fertilizer can resist low temperature stress by promoting photosynthesis, improving the utilization rate of light energy, and reducing energy loss [30]. Otherwise, overexpression of SpCPk33 in cultivated tomatoes can improve the cold tolerance of tomato plants by scavenging malonaldehyde (MDA) and ROS [31]. Exploring the molecular mechanism of the tomato’s low temperature response is helpful to provide reference to find some key genes and discover cold-tolerant tomato germplasm resources.
The present study aimed to investigate the potential regulatory factors of cold tolerance related to molecular marker TGS377 located on chromosome 1 of the tomato. We attempted to identify low temperature response factors in the vicinity of TGS377. Those genes’ expression profiles were also detected and analyzed in six accessions of tomato with different cold tolerance.

2. Materials and Methods

2.1. Plant Materials and Growth Conditions

Six tomato accessions with different cold tolerance were selected as experimental materials. ‘NL-15’, ‘NL-18’, and ‘NL-21’ were cold-tolerant accessions; ‘NL-7’, ‘NL-37’, and ‘NL-67’ were cold-sensitive accessions. The seedlings of the tomatoes were grown in pots within a soil/vermiculite (1/1) mixture in phytotron of the Institute of Vegetable Crops, Jiangsu Academy of Agricultural Sciences and State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Horticulture, Nanjing Agricultural University, Nanjing, China.
The photosynthetic photon flux density (PPFD) was set at 375 μmol·m−2·s−1, the photoperiod cycle was 12 h light/12 h dark, the day and night temperatures were kept at 25 °C, and the relative humidity was 70%. Twelve tomato plants were planted in each accession and placed in the above-mentioned normal environmental conditions in the pots for 30 days. Then, the low temperature stress treatment was started. The low temperature was set at 8/6 °C (day/night), and the seedlings of the six tomato accessions were placed under low temperature conditions for 15 days. At 16 days, the chilling injury index of each tomato accession was counted and recorded. At the same time, the tomato plants from each accession were divided into three groups, and three biological replicates were set. For each biological replicate, the first fully unfolded leaf of the tomato plant was sampled for subsequent RT-qPCR experimental analysis. All the samples were immediately frozen in liquid nitrogen and stored at −80 °C.

2.2. Determination of Chilling Injury Index

The procedure for calculating the chilling injury index was as follows. Briefly, the chilling injury index was divided into 5 levels. Level 1, the plant was growing well, and the leaves were green. Level 2, the plant leaves were green, and the leaf margins were slightly dehydrated and curled. Level 3, the leaf color of the plant was slightly yellow, and the leaves were slightly wilted. Level 4, the leaves of the plants turned yellow, and some leaves withered. Level 5, the leaves of the plant were dry, and most leaves turned yellow. The following formula was used to determine the chilling injury index: chilling injury index = (S1 + 2 × S2 + 3 × S3 + 4 × S4 + 5 × S5)/(total number of tomato plants × 5). The number of tomato plants with level 1–5 chilling injury was calculated using the formula S1, S2, S3, S4, and S5 (S1 referred to the number of tomato plants classified as level 1 cold damage; S2 referred to the number of tomato plants classified as level 2 cold damage; S3 referred to the number of tomato plants classified as level 3 cold damage; S4 referred to the number of tomato plants classified as level 4 cold damage; and S5 referred to the number of tomato plants classified as level 5 cold damage) [21]. The chilling injury index of tomato plants in this study was between 0 and 0.7; the threshold was set up as 0.35. Cold-tolerant types were classified as those with a chilling damage value of less than 0.35, while cold-sensitive types were identified as those with a chilling injury index of greater than 0.35.

2.3. Total RNA Extraction and cDNA Synthesis

Total plant RNA extraction kit (Proteinssci, Shanghai, China) was used to extract total RNA from tomato leaves after low temperature treatment. About 1 μg RNA was used to synthesize the first strand cDNA to 20 μL of the HiScript II QRT SuperMix for qPCR reverse transcription kit (Vazyme, Nanjing, China), and kept at −20 °C for further study.

2.4. Bioinformatics Analysis of Genes within 50 kb Upstream and Downstream of Tomato Molecular Marker TGS377

According to the information of TGS377 molecular marker (the forward sequence information of TGS377 is 5′-GTGCACCACAAGAGTCAAAGC-3′ and the reverse sequence information of TGS377 is 5′-AATGTTTGTGGAATATTGAGATATTGT-3′) [32], genes within 50 kb upstream and downstream of TGS377 were searched in the Phytozome database (https://phytozome-next.jgi.doe.gov/) (accessed on 5 April 2022), and the information of genes was downloaded for subsequent experiments and bioinformatics analysis. The TBtools software was used to label TGS377 molecular marker loci on chromosomes. The Gene Structure Display Server (GSGD) software (https://gsds.gao-lab.org/) (accessed on 15 May 2022) was used to annotate the gene structure. The Multiple Em for Motif Elicitation (MEME) software (https://meme-suite.org/meme/tools/meme/) (accessed on 15 May 2022) was used for motif analysis. ProtParam (https://www.expasy.ch/tools/protparam/) (accessed on 15 May 2022) software was used to analyze amino acid length, relative molecular weight, theoretical isoelectric point, and hydrophilicity. Tomato functional genomics database (https://ted.bti.cornell.edu/cgi-bin/TFGD/digital/home.cgi/) (accessed on 15 May 2022) was used to download Heinz tomato transcriptome data of different tissues (flowers, fully opened flowers, fruits, 2 cm fruits, 3 cm fruits, roots, 1 cm fruits, green fruits, leaves, and breaker + 10 fruits). The software Origin 2022B was used to draw the expression heat map. The Gene Ontology Resource (https://geneontology.org) (accessed on 15 May 2022) was used to download the GO information of genes within 50 KB upstream and downstream of TGS377 for GO term analysis.

2.5. RT-qPCR Analysis

Genius 2× SYBR Green Fast qPCR Mix (No ROX) (Abclone, Wuhan, China) kit was used for RT-qPCR analysis. Bio-Rad software and Bio-Rad CFX96 real-time PCR system were used to conduct RT-qPCR analysis with the following procedure: 95 °C for 3 min, 40 cycles at 95 °C for 5 s, 60 °C for 30 s, and melting curve analysis (65 to 95 °C, increasing 0.5 °C every 5 s) [33]. Tubulin (Solyc04g077020) gene was used to regulate expression levels of target genes with the 2−ΔΔCT method [34]. The experiments were performed with three independent biological replicates. RT-qPCR primers were designed by Primer Premier 5 software and the primers used for RT-qPCR were as follows (Table 1).

2.6. Gene Coexpression Network Analysis

Pearson correlation coefficient analysis was performed using RT-qPCR data. The Cytoscape 9.3.1 software was used to draw the gene coexpression network diagrams.

2.7. Statistical Analysis

All data in the text were obtained from the average of three biological repeats. Statistical analysis was performed using the SPSS package program version 26.0 (SPSS Inc., Chicago, IL, USA). Data was analyzed using one-way ANOVA. The means were compared through the least significant difference (LSD) test at a significance level of 0.05 (p < 0.05). GraphPad Prism 9.3.1 software was used to draw diagrams.

3. Results

3.1. Determination of Chilling Injury Index

After 15 days of low temperature treatment, the chilling injury index levels of the tomato plants are shown in Figure 1. The chilling injury index of the six tomato accessions was calculated using the chilling injury index evaluation method. The six tomato accessions were separated into two groups (cold tolerance and cold sensitivity) based on the chilling injury index. Cold-tolerant accessions included ‘NL-15’, ‘NL-18’, and ‘NL-21’, while cold-sensitive accessions contained ‘NL-7’, ‘NL-37’, and ‘NL-67’ (Table 2).

3.2. Gene Structure and Motif Analysis of Tomato Molecular Marker TGS377 within 50 kb Upstream and Downstream

The location of the molecular marker TGS377 was marked on the chromosome according to its information, and the results showed that the TGS377 molecular marker was located at 2.47 Mb on tomato chromosome 1 (Figure 2A). Fifteen genes were predicted within 50 kb upstream and downstream of the TGS377 molecular marker. There were Solyc01g008370, Solyc01g008390, Solyc01g008400, Solyc01g008410, Solyc01g008420, Solyc01g008440, Solyc01g008450, Solyc01g008460, Solyc01g008470, Solyc01g008475, Solyc01g008477, Solyc01g008479, Solyc01g008480, Solyc01g150104, and Solyc01g150107. The structure of those genes among the 100 kb region were analyzed by GSGD software. The results showed that the number of exons was 1~13 (Figure 2B). Nine genes had 1~3 exons, whereas Solyc01g008370 and Solyc01g008420 genes had up to 10 and 13 exons, respectively (Figure 2B). Motif analysis was performed on the amino acid sequences using MEME software. The results showed that the length of the motif 1 domain was 50 aa, the length of the motif 2 domain was 21 aa, and the length of the motif 3 domain was 25 aa. Solyc01g008477, Solyc01g150107, Solyc01g008479, and Solyc01g150104 contained motif 1, motif 2, and motif 3 domains, while Solyc01g008475 had only motif 1 and motif 2 domains. Otherwise, the motif 1, motif 2, and motif 3 domains were not detected in the rest of the other 10 genes using MEME software (Figure 2C).

3.3. Protein Information Prediction Analysis of Tomato Molecular Marker TGS377 within 50 kb Upstream and Downstream

The characteristics of amino acid sequences of the genes within 50 kb upstream and downstream of the tomato molecular marker TGS377 were predicted by ProtParam software. The length of the amino acids ranged from 64 to 720 aa, the molecular weight ranged from 7491.06 to 80748.07 Da, the theoretical isoelectric point was between 5.04 and 10.30, and the hydrophilicity was between −0.796 and 0.609. Solyc01g008400 had the minimum protein length (64 aa) and molecular weight (7491.06 Da), while Solyc01g008410 had the maximum protein length (720 aa) and molecular weight (80748.07 Da). The theoretical isoelectric point (pI) of the Solyc01g008450 protein was 5.04, which was an acidic protein. The maximum theoretical isoelectric point of the Solyc01g150107 protein was 10.30, which belonged to basic protein. In addition, the Solyc01g008400, Solyc01g008420, Solyc01g008477 and Solyc01g150107 proteins were hydrophobic proteins, and the other 11 proteins were hydrophilic proteins (Table 3).

3.4. Analysis of Gene Expression in Different Tissues of Heinz Tomato

The expression profiles of the 15 genes within 50 kb upstream and downstream of the molecular marker TGS377 in different tissues were analyzed in Heinz tomato. The Solyc01g008370 gene was expressed in all tissues and had the highest expression level compared with the other 14 genes. The expression level of the Solyc01g008440 gene in flower buds and complete flowers was higher than in other tissues. The expression of the other 13 genes was low or not detected in different tissues (Figure 3).

3.5. GO Term Analysis of Genes within 50 KB Upstream and Downstream of Tomato Molecular Marker TGS377

According to GO enrichment analysis of the genes within 50 kb upstream and downstream of the molecular marker TGS377, 14 genes were enriched in molecular function. Among the molecular functions, the number of genes enriched in binding protein functions was 4, while the number of other genes enriched in molecular functions was 1. Moreover, there were 4 genes enriched in biological process and 2 genes enriched in cellular component (Figure 4).

3.6. Expression Profiles of Predicted Genes under Low Temperature Treatment in Tomatoes

RT-qPCR was used to quantify mRNA levels of the predicted genes to validate the response to low temperature in tomatoes. As shown in Figure 5, the expression levels of Solyc01g008370, Solyc01g008440, Solyc01g008460, Solyc01g008470, and Solyc01g008480 genes in cold-sensitive tomato accessions (‘NL-37’ and ‘NL-67’) were significantly higher than those in cold-tolerant tomato accessions (‘NL-15’, ‘NL-18’, and ‘NL-21’) (Figure 5A,F,H,I,M). The expression levels of the Solyc01g008475 and Solyc01g008477 genes in ‘NL-15’ and ‘NL-67’ tomato accessions were significantly higher than those in the other four tomato accessions (Figure 5J,K). The expression of the Solyc01g008450 gene in the ‘NL-18’ tomato accession was significantly lower than that in the other five tomato accessions (Figure 5G). The expression levels of the Solyc01g008479, Solyc01g150104, and Solyc01g150107 genes in ‘NL-21’ tomato accession were significantly lower than in the cold-sensitive tomato accessions (Figure 5L,O). The expression levels of Solyc01g008420 in the ‘NL-15’ and ‘NL-37’ tomato accessions were significantly lower than those in other tomato accessions (Figure 5E). Additionally, the expression of the Solyc01g008400 gene in the ‘NL-21’ and ‘NL-67’ tomato accessions was significantly lower than that in other tomato accessions (Figure 5C). The expression levels of Solyc01g008480 and Solyc01g150104 in the cold-sensitive tomato accessions (‘NL-7’, ‘NL-37’, and ‘NL-67’) were higher than that in the cold-tolerant accessions (‘NL-15’, ‘NL-18’, and ‘NL-21’) (Figure 5M,N). The expression levels of Solyc01g008390 and Solyc01g008410 in the cold-tolerant tomato ‘NL-18’ accession were significantly higher than those in the cold-sensitive accessions (‘NL-7’, ‘NL-37’, and ‘NL-67’) (Figure 5B,D).

3.7. Gene Coexpression Network Analysis

The Pearson correlation coefficient analysis was performed and visualized by the RT-qPCR data and Cytoscape software, respectively. The results showed that the two proteins Solyc01g008370 and Solyc01g008480 were at the core position in the coexpression network, which could be correlated with how the Solyc01g008479, Solyc01g008470, Solyc01g008460, Solyc01g008440, Solyc01g008420, and Solyc01g008400 six proteins interacted. There was single interaction among the three proteins Solyc01g150107, Solyc01g008477, and Solyc01g008475. The two proteins Solyc01g008390 and Solyc01g008410 were also single interaction. In addition, Pearson correlation coefficient analysis showed that the correlation between the Solyc01g008410 protein and the Solyc01g008390 protein was the strongest, with a correlation coefficient of 0.9988, while the correlation between the Solyc01g008480 protein and the Solyc01g008470 protein was the weakest, with the correlation coefficient 0.4694. The correlation coefficient between the Solyc01g008480 protein and the Solyc01g008370 protein was 0.7713 (Figure 6).

4. Discussion

Low temperature is one of the most important environmental elements attacking crop growth and development, as well as the establishment of crop distribution patterns [25]. Low temperatures have a deadly effect on tropical and subtropical crops’ yield and quality [35]. Tomato plant development and metabolism are slower when the temperature in the producing area is below 12 °C [6,36]. Long-term low temperature stress is detrimental to tomato development, resulting in a variety of negative reactions, including stomatal closure and photosynthetic inhibition [37,38]. Under low temperatures, the plants cannot obtain nutrients or water from the soil in time [39,40]. The tropical and subtropical crops, such as tomatoes, may adapt to low temperatures and improve their ability to respond to stress after undergoing cold resistance training [25,41]. The tomato is one of the most important vegetable crops. The reduction of tomato production was caused by the stress of low temperature environments every year.
At present, tomato cold tolerance mainly focuses on improving its ability to withstand low temperatures through exogenous administration of growth regulators and inserting cold-tolerance genes into tomatoes. In previous studies exogenous administration of gamma-aminobutyric acid (GABA) and 5-aminolevulinic acid (ALA) was able to increase endogenous ALA and GABA levels, boost the antioxidant system, improve enzyme function, and enhance tomato cold-tolerance [42,43]. Exogenous spraying of 24-epi-brassinolide (EBR) and melatonin (MT, N-acetyl-5-methoxytryptamine) under low temperature stress could raise the activity of antioxidant enzymes in tomatoes, increase the amount of intracellular osmotic adjustment chemicals, and minimize the damage caused by reactive oxygen species (ROS) to cells, enhancing tomato cold resistance [44,45]. With the rapid advancement of molecular biology technology, an increasing number of researchers are focusing on genetically engineering stress tolerance into crops at the molecular level. In 1991, the antifreeze protein gene of fish was transplanted into tomatoes to make tomatoes have cold resistance [46]. Introducing AtIpk2β [47] and AtRCI2A [48] genes into the tomato could improve the ability of tomatoes to resist low temperature stress. Liang et al. [49] expressed the grape VvBAM1 gene in tomato, which improved tomato cold resistance by regulating the synthesis and breakdown of starch in mesophyll cells, influencing the level of soluble sugar, and boosting the elimination of ROS.
Previous studies indicated that the cold-tolerant trait in tomatoes is a quantitative trait, with most of the cold-tolerance genes being present in wild resources [21]. The advent of molecular markers has provided a convenient way to identify and search for genes associated with cold tolerance [13]. Vallejos et al. identified three sites of QTLs on chromosomes 6, 7, and 12 that were associated with hypothermia, using isolated populations of BC1 obtained by the hybridization of common Lycopersicon esculentum Mill. Cv. T3 with wild L. hirsutum f. typicum accession LA1777 [50]. Truco et al. identified six loci of QTLs associated with hypothermia on chromosomes 5, 6, 7, 9, 11, and 12 using isolated populations of BC1 obtained by crossing L. esculentum Mill. cv. T5 and wild L. hirsutum f. typicum accession LA1778 [51]. In this study, the molecular marker TGS377 relating to cold tolerance was selected, and the genes within 50 kb upstream and downstream of the molecular marker TGS377 were identified and analyzed by bioinformatics and RT-qPCR. Meanwhile, six tomato accessions with different cold tolerance and sensitivity were selected, then the tomato plants were treated with low temperatures for 15 days. The cold-sensitive plants showed chilling injury symptoms, such as leaf dehydration and wilting of old leaves, and these results were consistent with previous findings [52,53]. In this study, Solyc01g008440 was annotated as an ATP-binding function associated with energy in the GO term, and RT-qPCR showed that the expression level of the gene was significantly lower in cold-tolerant tomato accessions than in cold-sensitive tomato accessions. The results were also similar to previous studies that found that plant growth slowed or stopped under cold stress and genes involved in energy were downregulated [53].
Higher plants encounter adversity stress, the plant’s own response mechanism frequently quickly alleviates the stress effects, which often involves many changes associated with gene expression related to the stress response. The changes of gene expression profiles under cold stress were a complex network [52,54]. Cold response transcription factor expression was regulated when plants encountered low temperature stress, and then regulated the expression of downstream genes to improve the cold tolerance of plants [55]. Weiss et al. [56] indicated that the expression of a transcription factor was upregulated in leaves after low temperature treatment of tomatoes compared with the control. In this study, the expression of two genes, Solyc01g008390 and Solyc01g008410, was upregulated in the ‘NL-18’ tomato accession after 15 days of low temperature stress treatment, which was significantly higher than that of the other five tomato accessions. The Solyc01g008390 and Solyc01g008410 genes might play a vital role in regulating cold tolerance in the tomato, so we will focus on them in the future.
Here, we aimed to compare the response of different resistant tomato accession to low temperature stress. We mainly focused on low temperature effects on six tomato accessions and the related gene’s response. In the future, normal environmental conditions should be set as the control, the function of related genes could be verified in more detail. It will also help to remove the false genes related to low temperature stress.

Author Contributions

Conceptualization, T.-M.Z., A.-S.X., W.-M.Z. and J.-Q.Z.; methodology, J.-Q.Z., R.-R.Z. and J.-P.T.; investigation, J.-Q.Z., R.-R.Z., J.-P.T. and L.-X.S.; formal analysis, J.-Q.Z. and H.L.; resources, A.-S.X. and T.-M.Z.; writing—original draft preparation, J.-Q.Z.; writing—review and editing, A.-S.X.; visualization, J.-Q.Z.; supervision, A.-S.X., T.-M.Z. and W.-M.Z.; project administration, A.-S.X.; funding acquisition, A.-S.X. and T.-M.Z. All authors have read and agreed to the published version of the manuscript.

Funding

The research was supported by the Natural Science Foundation of Jiangsu (BK20180306; BK20221009), Jiangsu Agricultural Science and Technology Innovation Fund [CX (21) 3025], Key Research and Development Program of Jiangsu (BE2021377), China Postdoctoral Science Foundation (2021M701742), and the Priority Academic Program Development of Jiangsu Higher Education Institutions Project (PAPD).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

In this section, physiological and RT-qPCR data were measured by the authors themselves.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Tomato plant phenotypes with different levels of chilling injury index after 15 days of low temperature treatment.
Figure 1. Tomato plant phenotypes with different levels of chilling injury index after 15 days of low temperature treatment.
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Figure 2. Chromosome position map of TGS377 and analysis of upstream and downstream 50 kb gene structure of tomato. (A) Chromosome position map of TGS377 molecular marker; (B) Gene structure analysis; (C) Motif analysis.
Figure 2. Chromosome position map of TGS377 and analysis of upstream and downstream 50 kb gene structure of tomato. (A) Chromosome position map of TGS377 molecular marker; (B) Gene structure analysis; (C) Motif analysis.
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Figure 3. Heat map of expression profiles in different tissues of Heinz tomato of the genes within 50 kb upstream and downstream of TGS377.
Figure 3. Heat map of expression profiles in different tissues of Heinz tomato of the genes within 50 kb upstream and downstream of TGS377.
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Figure 4. GO term analysis of genes within 50 kb upstream and downstream of TGS377. (m): Molecular function; (b): biological process; (c): cellular component.
Figure 4. GO term analysis of genes within 50 kb upstream and downstream of TGS377. (m): Molecular function; (b): biological process; (c): cellular component.
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Figure 5. The expression profiles of the identified genes within 50 kb upstream and downstream of TGS377 under low temperature treatment. (A): Expression profiles of Solyc01g008370, (B): Expression profiles of Solyc01g008390, (C): Expression profiles of Solyc01g008400, (D): Expression profiles of Solyc01g008410, (E): Expression profiles of Solyc01g008420, (F): Expression profiles of Solyc01g008440, (G): Expression profiles of Solyc01g008450, (H): Expression profiles of Solyc01g008460, (I): Expression profiles of Solyc01g008470, (J): Expression profiles of Solyc01g008475, (K): Expression profiles of Solyc01g008477, (L): Expression profiles of Solyc01g008479, (M): Expression profiles of Solyc01g008480, (N): Expression profiles of Solyc01g150104, (O): Expression profiles of Solyc01g150107. Value is the mean for three biological replicates, with vertical bars representing standard errors. Different letters in the figure indicate statistically significant differences among tomato accessions in low temperature stress (p < 0.05).
Figure 5. The expression profiles of the identified genes within 50 kb upstream and downstream of TGS377 under low temperature treatment. (A): Expression profiles of Solyc01g008370, (B): Expression profiles of Solyc01g008390, (C): Expression profiles of Solyc01g008400, (D): Expression profiles of Solyc01g008410, (E): Expression profiles of Solyc01g008420, (F): Expression profiles of Solyc01g008440, (G): Expression profiles of Solyc01g008450, (H): Expression profiles of Solyc01g008460, (I): Expression profiles of Solyc01g008470, (J): Expression profiles of Solyc01g008475, (K): Expression profiles of Solyc01g008477, (L): Expression profiles of Solyc01g008479, (M): Expression profiles of Solyc01g008480, (N): Expression profiles of Solyc01g150104, (O): Expression profiles of Solyc01g150107. Value is the mean for three biological replicates, with vertical bars representing standard errors. Different letters in the figure indicate statistically significant differences among tomato accessions in low temperature stress (p < 0.05).
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Figure 6. The network analysis of gene coexpression within the identified genes in tomatoes.
Figure 6. The network analysis of gene coexpression within the identified genes in tomatoes.
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Table
Table 1. Primers used for RT-qPCR.
Table 1. Primers used for RT-qPCR.
Gene IDPrimer Sequence 5′→3′
Solyc01g008370FAATTGTTCACCCGCTTGTGC
RCTCCTCCTCAAAGGGCACTG
Solyc01g008390FCGACAAAGGGACTGGAGCTT
RGTACGTGACCTTCCAAGCGA
Solyc01g008400FGCTTCTGTGGCTGTGCAATC
RGCACACGCACAAGCTGATAG
Solyc01g008410FTACCAGCATCACTGCACCAG
RCATCGCCGCCACAATCTTTT
Solyc01g008420FCCCTGGTCAGCGTAACAACT
RCAATGCAGATGACGCGGATG
Solyc01g008440FAAACATGCCTCTGGGAGTGG
RCCCTTGCCTGTGACACATCT
Solyc01g008450FGCATACGACGATGCTGCTCA
RTTTCTGCCCTCCAACCCTTG
Solyc01g008460FCCGGCTATGTTTCACGCTCT
RGACATGTGGAACAGGCAAGC
Solyc01g008470FACCCCTGTGGCAAACACTTC
RGCTCGCCTTCATCCTTCTGA
Solyc01g008477FGGATGATCCGGATTCCGACG
RATGCTCTCTTCAGGGCTTGT
Solyc01g150107FCAACGATTTCGTGTTTTATTGC
RTTGGCATTTTTGACGTCGG
Solyc01g008479FAGCTCCGAAGCGAGCA
RGACGGACGTCCACGAAAAA
Solyc01g150104FGGGTGATCCGAATTTCGACG
RCTCGCTTCGGGGCTCG
Solyc01g008475FGGGTGATCTGGATTCCGACG
RATGGGTCGGACATAACCGTG
Solyc01g008480FGCAAAGCTGGGGAAACACAG
RCCCAGCCATCTTCAACGTCT
Solyc04g077020 [33]FTGACGAAGTCAGGACAGGAA
(Tubulin)RCTGCATCTTCTTTGCCACTG
Table
Table 2. The chilling injury index and chilling injury type of tomato.
Table 2. The chilling injury index and chilling injury type of tomato.
Tomato AccessionsChilling Injury IndexCold Resistance Type
‘NL-7’0.43Cold Sensitive
‘NL-15’0.28Cold Tolerance
‘NL-18’0.17Cold Tolerance
‘NL-21’0.13Cold Tolerance
‘NL-37’0.60Cold Sensitive
‘NL-67’0.57Cold Sensitive
Table
Table 3. Analysis of the genes and predicted amino acids sequences within 50 kb upstream and downstream of TGS377 in tomato.
Table 3. Analysis of the genes and predicted amino acids sequences within 50 kb upstream and downstream of TGS377 in tomato.
Gene IDChromosomal LocationProtein
Length
(aa)		Molecular Weight
(Da)		Theoretical Isoelectric PointGrand Average of Hydropathicity
Solyc01g008370chr1:2424882-243073933738560.235.74−0.126
Solyc01g008390chr1:2434836-243736459565833.155.33−0.047
Solyc01g008400chr1:2433343-2440084647491.067.710.595
Solyc01g008410chr1:2440518-244294372080748.075.51−0.090
Solyc01g008420chr1:2452193-245919852456135.786.960.609
Solyc01g008440chr1:2469910-247659153359987.636.55−0.491
Solyc01g008450chr1:2484922-248575627732020.335.04−0.796
Solyc01g008460chr1:2489427-249442520723197.495.26−0.236
Solyc01g008470chr1:2495684-250183235941177.266.57−0.205
Solyc01g008475chr1:2506199-250670310712454.459.62−0.337
Solyc01g008477chr1:2510337-251067911313012.118.910.004
Solyc01g008479chr1:2512135-251257914716568.219.61−0.161
Solyc01g008480chr1:2515370-252269059167332.118.88−0.180
Solyc01g150104chr1:2504047-250439811613371.659.98−0.067
Solyc01g150107chr1:2510879-251160714016269.2210.300.017
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Zhang, J.-Q.; Tao, J.-P.; Song, L.-X.; Zhang, R.-R.; Liu, H.; Zhao, T.-M.; Zhu, W.-M.; Xiong, A.-S. Identification of Key Regulatory Factors of Molecular Marker TGS377 on Chromosome 1 and Its Response to Cold Stress in Tomato. Agronomy 2022, 12, 2985. https://doi.org/10.3390/agronomy12122985

AMA Style

Zhang J-Q, Tao J-P, Song L-X, Zhang R-R, Liu H, Zhao T-M, Zhu W-M, Xiong A-S. Identification of Key Regulatory Factors of Molecular Marker TGS377 on Chromosome 1 and Its Response to Cold Stress in Tomato. Agronomy. 2022; 12(12):2985. https://doi.org/10.3390/agronomy12122985

Chicago/Turabian Style

Zhang, Jia-Qi, Jian-Ping Tao, Liu-Xia Song, Rong-Rong Zhang, Hui Liu, Tong-Min Zhao, Wei-Min Zhu, and Ai-Sheng Xiong. 2022. "Identification of Key Regulatory Factors of Molecular Marker TGS377 on Chromosome 1 and Its Response to Cold Stress in Tomato" Agronomy 12, no. 12: 2985. https://doi.org/10.3390/agronomy12122985

APA Style

Zhang, J.-Q., Tao, J.-P., Song, L.-X., Zhang, R.-R., Liu, H., Zhao, T.-M., Zhu, W.-M., & Xiong, A.-S. (2022). Identification of Key Regulatory Factors of Molecular Marker TGS377 on Chromosome 1 and Its Response to Cold Stress in Tomato. Agronomy, 12(12), 2985. https://doi.org/10.3390/agronomy12122985

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