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Article

Genome-Wide Exploration and Expression Analysis of the CNGC Gene Family in Eggplant (Solanum melongena L.) under Cold Stress, with Functional Characterization of SmCNGC1a

by
Zheng Jiang
†,
Lihui Du
†,
Lei Shen
,
Jie He
,
Xin Xia
,
Longhao Zhang
and
Xu Yang
*
College of Horticulture and Landscape Architecture, Yangzhou University, Yangzhou 225009, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Int. J. Mol. Sci. 2023, 24(17), 13049; https://doi.org/10.3390/ijms241713049
Submission received: 27 July 2023 / Revised: 14 August 2023 / Accepted: 18 August 2023 / Published: 22 August 2023
(This article belongs to the Special Issue Advances in Research for Horticultural Crops Breeding and Genetics)
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Abstract

:
Eggplant (Solanum melongena L.) is an important economic crop, and to date, there has been no genome-wide identification and analysis of the cyclic nucleotide-gated channel (CNGC) gene family in eggplant. In this study, we identified the CNGC gene family in eggplant, and the results showed that 29 SmCNGC genes were classified into five groups, unevenly distributed across the 12 chromosomes of eggplant. The gene structure and motif analysis indicated that the SmCNGC family proteins may exhibit apparent preferences during evolution. Furthermore, our study revealed the presence of numerous light-responsive elements, hormone-responsive elements, and transcription factor binding sites in the promoter regions of SmCNGC genes, suggesting their significant role in environmental adaptability regulation. Finally, we analyzed the expression patterns of all SmCNGC genes under cold stress and found that SmCNGC1a was significantly upregulated under cold stress. Subcellular localization experiments indicated that this gene is located on the plasma membrane. Subsequently, its importance in the low-temperature response of eggplant was validated through virus-induced gene silencing (VIGS), and its protein interactome was predicted. In summary, our study provides a comprehensive understanding of the function and regulatory mechanisms of the CNGC gene family in eggplant, laying an important foundation for further research on cold adaptation in eggplant.

1. Introduction

Eggplant (Solanum melongena L.), a thermophilic vegetable belonging to the Solanaceae family, is extensively cultivated on a global scale. It is an important vegetable variety during the off season and is also one of the most popular and widely consumed vegetables [1]. Eggplant contains rich nutritional components, such as vitamins, minerals, and especially high levels of vitamin E, P, and iron. It also contains various bioactive compounds, offering health benefits and medicinal value [2]. Calcium ions (Ca2+) are indispensable for upholding the integrity of plant cell architecture [3]. They assume a pivotal role as both a critical cellular signal and a secondary messenger in numerous pathways, governing various responses to environmental stimuli, including plant hormones, temperature fluctuations, light exposure, and salt stress [4,5]. Cyclic nucleotide-gated channels (CNGCs) are non-selective cation channels situated on the cytoplasmic membrane. They play a crucial role in facilitating the transmembrane transport of monovalent cations, such as sodium and potassium, as well as divalent cations, like calcium and magnesium [6]. CNGCs in plants were first discovered in 1998 during the screening of a barley calcium-binding transporter (Hordeum vulgare CaM-binding transporter, HvCBT1), which revealed the existence of this non-selective cation channel [7]. CNGCs are widely distributed in animals and plants, serving as universal calcium ion channels in eukaryotes [8]. Prior research has substantiated the existence of CNGCs in both monocotyledonous and dicotyledonous plant species [9]. Preliminary investigations have suggested that CNGCs function as ligand-gated ion channels, facilitating the passage of calcium ions. These channels can be activated by cyclic nucleotides (cNMP) and their activity can be inhibited through binding with Ca2+/calmodulin (CaM) [10,11]. Structurally, CNGCs consist of six transmembrane domains (S1–S6), a pore region (P) located between the fifth and sixth domains, a C-terminal CaM-binding domain (CaMB), and a cyclic nucleotide-binding domain (CNBD) [12]. The CNBD, which represents a highly conserved region within CNGCs, is characterized by the presence of a cyclic nucleotide-binding cassette (PBC) and an adjacent unique “hinge” region. The PBC specifically interacts with the sugar and phosphate groups of the nucleotide ligand, while the adjacent “hinge” region contributes to the efficiency and selectivity of ligand binding [13]. Previous investigations have demonstrated that the carboxyl-terminal tails of specific plant CNGCs exhibit a Ca2+-dependent interaction with CaM [14,15,16]. In plants, CNGCs contain a conserved cNMP-binding domain that is considered a specific domain for identifying CNGCs [17]. Early studies proposed that plant CNGCs are regulated by cNMP gating. However, as research on calcium signaling has progressed, many scholars have questioned whether cNMP activation is necessary for CNGCs [18]. Recent studies have found that in Xenopus laevis oocyte cells, cAMP and cGMP can hyperpolarize activate calcium channels through heterologous assembly, without requiring an increase in cNMP levels [19]. Therefore, cNMP may only act as an auxiliary factor for CNGC subunits or exert its effects by modulating the membrane voltage or other regulators [19]. Furthermore, with further research, an increasing number of experimental findings indicate that the activation and regulation of CNGC channels rely more on phosphorylation modifications and the binding of CaM. The mechanisms underlying cNMP regulation of CNGCs require further investigation [20].
CNGCs regulate the growth of root tips in plants. Recent studies have shown that CNGC5, CNGC6, CNGC9, and CNGC14 in Arabidopsis thaliana are involved in regulating the growth of root hairs [21]. CNGC14 plays a role in maintaining cell integrity during polar growth of root hairs, and its mutation leads to abnormal growth of root hairs, including swelling, branching, and bursting at the tip [22]. Additionally, CNGC5, CNGC6, CNGC9, and CNGC14 are also involved in maintaining the stability of unidirectional cell proliferation and cytoplasmic Ca2+ oscillations. In CNGC14 mutants, the stability of cytoplasmic Ca2+ oscillations are severely impaired, and cngc14/cngc6 and cngc14/cngc9 double mutants lose the typical 30 s Ca2+ oscillation cycle [22]. In the double mutants of cngc6 and cngc9, as well as in the single mutants of cngc9, this oscillation cycle still exists but with reduced stability [23]. These findings indicate that CNGC14 plays a crucial role in these processes. Another study found that CNGC5, CNGC6, and CNGC9 are essential Ca2+ channels in the structural growth of root hairs and auxin signal transduction in Arabidopsis. Mutations in these three genes lead to root hair growth defects, including shorter and defective root hairs. However, expressing any one of the CNGC subtypes individually or providing a high concentration of exogenous Ca2+ can restore this growth defect, whereas the supply of exogenous K+ cannot [24]. These three genes also exhibit Ca2+ permeation channel function in HEK293T cells. Cytosolic Ca2+ imaging and patch clamp data in root hairs indicate a significant reduction in the Ca2+ gradient and oscillation at the tip when CNGC5, CNGC6, and CNGC9 are absent [24].
CNGCs play important roles in the growth and development of plant pollen tubes. The CNGC family in Arabidopsis comprises a total of 20 members [25]. Studies have shown that AtCNGC16 contributes to the development of pollen grains in Arabidopsis under high-temperature conditions [26]. AtCNGC7 and AtCNGC8 share high amino acid sequence homology, and both have overlapping functions in the germination and development of pollen as the cngc7/cngc8 double mutation leads to pollen sterility, confirming their roles in plant pollen development [27]. Further research has revealed that CNGC7 or CNGC8 interacts with CNGC18 to form an inactive heterotetramer. However, when the Ca2+ concentration reaches its peak level, CaM dissociates from the CNGC18-CNGC8 heterotetramer, relieving the inhibition of CNGC18 by CNGC8. This pathway, regulated by Ca2+-CaM interaction with CNGC channels, facilitates autoregulatory feedback in calcium oscillations while facilitating pollen tube growth and plays an important role in fine-tuning the growth of pollen tubes [28]. Moreover, CNGC18 exhibits asymmetric distribution on the plasma membrane at the growing tip of pollen tubes and possesses Ca2+ channel activity, which is crucial for pollen tube tip growth and guidance [29,30].
In recent years, with the increasing demand for year-round vegetables, particularly the rising requirements for eggplant production during the winter and spring seasons, eggplants frequently encounter cold stress during protected cultivation in winter and early spring, leading to cold damage, blossom and fruit drop, as well as poor fruit coloration. These phenomena severely affect the yield and quality of eggplants. Additionally, low-temperature stress hampers the growth and development of eggplants, resulting in stunted growth, yellowing and withering of leaves, and even plant death [31]. These occurrences not only directly impact the yield and quality of eggplants, but also cause economic losses and agricultural production instability for growers. Cold damage during the winter and spring seasons has become a bottleneck factor restraining the development of the eggplant industry, thereby imposing higher demands on the cold tolerance of eggplant cultivars during these seasons. Therefore, conducting research on the cold-tolerance mechanism of eggplants, exploring cultivation techniques to enhance their cold tolerance, and breeding new cold-tolerant eggplant varieties hold significant importance. In this study, we analyzed the genomic data of the eggplant CNGC gene family, identified 29 members of the SmCNGCs gene family, and conducted physicochemical property analysis, promoter analysis, phylogenetic tree construction, gene structure analysis, motif analysis, chromosome localization analysis, and collinearity analysis. We also investigated the expression patterns of SmCNGCs under different cold-stress conditions at different time points. Expression pattern analysis and subcellular localization were performed for the cold-stress-responsive gene SmCNGC1a in different tissues. Furthermore, the functionality of SmCNGC1a was validated using VIGS (virus-induced gene silencing) technology, and protein interaction networks were analyzed to explore the role of this gene under low-temperature stress in eggplants.

2. Results

2.1. Identification of the CNGC Genes in Eggplant

Based on the HMM file of the CNGC gene family, a search was conducted on the reference genome of eggplant. After manual screening and removal of redundant genes, a total of 29 SmCNGC genes were identified. Following the nomenclature guidelines for CNGC genes in Arabidopsis and referring to the information in the eggplant database, the identified 29 eggplant CNGC genes were named as SmCNGC1a-SmCNGC24 (Table 1). The predicted lengths of SmCNGC proteins ranged from 482 amino acids (SmCNGC9) to 1074 amino acids (SmCNGC7). The majority of SmCNGC proteins had lengths concentrated in the range of 600–800 amino acids, with molecular weights varying from 55.40 kDa (SmCNGC9) to 122.28 kDa (SmCNGC7). The significant differences in amino acid length and molecular weight suggest potential structural variations among members of the SmCNGC gene family. Among the 29 SmCNGC proteins, seven had a theoretical pI value below 7, indicating a potential negative charge within the alkaline pH range. The remaining 22 SmCNGC proteins had theoretical pI values above 7, suggesting a positive charge within the acidic pH range. Additionally, 8 SmCNGC proteins had an instability index value below 40, indicating relative stability, while the remaining 21 proteins were relatively unstable. The predicted aliphatic index for SmCNGC proteins ranged from 88.78 (SmCNGC18) to 99.63 (SmCNGC22). The grand average of hydropathicity predicted that, with the exception of SmCNGC13, the remaining proteins were hydrophilic. The prediction of subcellular localization results indicated that the majority of SmCNGC proteins were located in the cell membrane (plasma membrane), consistent with their primary function as channel proteins. However, there were some special cases: SmCNGC22 was found in the nucleus, SmCNGC10 and SmCNGC9 were located in the cytoplasm, and SmCNGC23 was present in the chloroplast, suggesting potential diverse biological functions for these proteins.

2.2. Phylogenetic Analysis of SmCNGC Proteins

To investigate the evolutionary relationships of the SmCNGC gene family, we constructed a phylogenetic tree of the CNGC protein family, including eggplant, Arabidopsis, and tomato (Solanum lycopersicum L.). The maximum likelihood (ML) method was employed to generate the phylogenetic tree with five groups (Figure 1). Group 1 consists of 6 eggplant CNGC proteins, 11 Arabidopsis CNGC proteins, and 9 tomato CNGC proteins. Group 2 comprises seven eggplant CNGC proteins, five Arabidopsis CNGC proteins, and five tomato CNGC proteins. Group 3 contains three eggplant CNGC proteins, two Arabidopsis CNGC proteins, and three tomato CNGC proteins. Group 4 consists of one eggplant CNGC protein, two Arabidopsis CNGC proteins, and one tomato CNGC protein. Group 5 exclusively includes 12 eggplant CNGC proteins, indicating a relatively distant evolutionary relationship with Arabidopsis and tomato. Based on the evolutionary analysis results, it can be inferred that CNGC maintains a high degree of stability throughout the process of species evolution, suggesting its conserved and indispensable role in organisms.

2.3. SmCNGC Gene Structures and the Conserved Motifs Analyses

Motif analysis was conducted on the CNGC gene family in eggplant. The results revealed that the encoded proteins of this family possess 10 conserved motifs (motif 1–10, Figure 2A). Members within the same subfamily exhibited similar distribution patterns of these conserved motifs. Motif 10 was identified as a shared motif among 28 SmCNGC members, while motif 1 was absent in SmCNGC9. Furthermore, it was observed that CNGC members in group 5 displayed unique regularity in the motifs they contained, with motif 6 being exclusive to this group (Figure 2B). Structural domain analysis indicated that most of the genes contained the PLN03192 superfamily domain. However, SmCNGC1a lacked this domain, which suggests that there might be functional differences associated with this gene (Figure 2C). Gene structure analysis, as shown in the diagram on the right, revealed that the number of coding sequences (CDSs) and untranslated regions (UTRs) were similar within the same subfamily. Additionally, SmCNGC13 displayed significant structural differences compared to other members, indicating possible variations in gene structure during the process of evolution (Figure 2D).

2.4. Chromosome Localization and Cis-Acting Elements Prediction of SmCNGCs

Chromosomal localization analysis revealed that members of the SmCNGC gene family are distributed across all 12 chromosomes of eggplant. Most of these genes are located at the ends of the chromosomes. Chromosome 3 harbors the highest number of CNGC gene family members, with five genes. Chromosome 8 contains four CNGC gene family members. Chromosomes 1, 2, and 12 have three members each, while chromosomes 4, 5, 7, and 9 have two members each. Chromosomes 6, 10, and 11 have only one member of the CNGC gene family (Figure 3A). Promoter analysis predicted the presence of numerous cis-regulatory elements. The results indicate that the promoters of SmCNGC genes contain a substantial number of light-responsive elements, anaerobic-induction elements, hormone-responsive elements, and MYB transcription factor binding sites. All SmCNGC gene promoters contain light-responsive elements, suggesting their potential involvement in light signal regulation. Additionally, we found that a significant portion of SmCNGC genes contain methyl jasmonate, salicylic acid, or abscisic-acid-responsive elements, indicating their potential role in responding to these hormones and regulating plant growth and development. Nearly half of the SmCNGC genes contain MYB transcription factor binding sites, suggesting that SmCNGC may be directly regulated by MYB transcription factors, thus modulating ion channel activity and signal transduction (Figure 3B).

2.5. Collinearity Analysis of SmCNGCs

To elucidate the origin and evolutionary relationship of the SmCNGC gene family, we analyzed the gene duplication events of SmCNGC. The results showed that the SmCNGC gene family has a total of nine pairs of gene sequence duplication events, namely SmCNGC13/SmCNGC15c, SmCNGC7/SmCNGC23/SmCNGC17, and SmCNGC15b/SmCNGC15c, etc. (Figure 4A). This indicates that the SmCNGC genes have undergone multiple duplication events during the evolutionary process, which facilitated the rapid expansion of the SmCNGC gene family. In addition, we performed collinearity analysis of the genomes of eggplant, Arabidopsis, and tomato using MCScanX v1.5.1. The results showed that there are 22 pairs of collinearity relationships between eggplant and Arabidopsis CNGC genes, and 34 pairs of collinearity relationships between eggplant and tomato. It is noteworthy that eggplant’s chromosome 3 (E03) has the highest number of collinear gene pairs (Figure 4B).

2.6. Expression Patterns of SmCNGC Genes in Cold Stress

To investigate the expression patterns of the SmCNGC genes under cold stress in eggplant and evaluate their roles during cold stress, we employed qRT-PCR to detect the expression levels of SmCNGC genes at different time points (0, 0.25, 0.5, 1, 2, and 4 h) of cold stress. The results revealed that the SmCNGC genes exhibited distinct expression patterns in response to cold stress at different time intervals. Specifically, the expression levels of SmCNGC1a, SmCNGC1c, SmCNGC7, SmCNGC12, and SmCNGC20 showed an initial increase followed by a decrease, suggesting their potential importance in the response to cold stress. This initial upregulation of expression might be associated with the rapid adaptation to environmental changes induced by cold stress and could be involved in the regulation of ion channels and signal transduction within the cells. As the duration of cold stress continued, the expression levels of these genes gradually decreased, which could indicate cellular acclimation to the cold-stress conditions or involvement of negative feedback regulatory mechanisms. Furthermore, the expression levels of SmCNGC4a, SmCNGC6, SmCNGC18, and SmCNGC24 decreased with prolonged cold stress, indicating their negative regulatory roles in eggplant’s adaptation to cold stress. Interestingly, we observed a trend: initially decreased expression levels followed by increased expression levels for SmCNGC2 and SmCNGC21 (Figure 5). These experimental findings suggest that the SmCNGC genes may exhibit temporal specificity during the plant’s response to cold stress. Of note, we observed a significant upregulation of SmCNGC1a at 0.5 h of cold stress, indicating its potential crucial role in the response of young eggplant seedlings to cold stress. Subsequent experiments will be conducted to further investigate this gene.

2.7. Expression Patterns of SmCNGC1a under Various Stress Conditions

To comprehensively investigate the expression patterns of SmCNGC1a under various stress conditions, we conducted analyses of its response to cold stress, heat stress, and salt stress. The qPCR results revealed distinct expression profiles of SmCNGC1a under these diverse stress scenarios. Under cold stress, the transcription level of SmCNGC1a rapidly increased during the initial phase of exposure to cold stress, reaching a significant level after 0.5 h, followed by a gradual decline during sustained cold stress. This transient nature implies that SmCNGC1a may be involved in the early perception and response phases of cold stress. Under heat stress, the transcription level of SmCNGC1a showed a sustained upregulation, maintaining a significant elevation compared to the untreated control. This sustained upregulation suggests that SmCNGC1a could potentially play a role in mediating eggplant’s response to heat stress. In contrast to cold and heat stress, the response of SmCNGC1a to salt stress exhibited a different expression pattern. Although there was a slight increase in gene expression, it was not statistically significant. This indicates a potential subtle role of SmCNGC1a in the regulation of salt-stress response (Figure 6).

2.8. Subcellular Localization and Tissue-Specific Expression Patterns of SmCNGC1a

To investigate the subcellular localization and expression patterns of SmCNGC1a in different plant tissues, we cloned SmCNGC1a into the pCambia1300-35S-EGFP plant expression vector containing the 35S promoter and GFP reporter gene (Figure 7A). The recombinant constructs, 35S:SmCNGC1a-GFP and 35S:GFP (control), were transformed into N. benthamiana epidermal cells using Agrobacterium-mediated transformation and injected. After 48 h, the fluorescence signals of the genes in the leaves were observed using a laser scanning confocal microscope. The results indicate that the fluorescence signal of SmCNGC1a-GFP was localized to the plasma membrane of the cells, while the control group (GFP) exhibited a fluorescence signal distributed throughout the entire cell, suggesting that SmCNGC1a is localized to the plasma membrane (Figure 7B). Furthermore, we performed qRT-PCR to detect the expression patterns of SmCNGC1a in different tissues of eggplant (root, stem, leaf, and flower). The results revealed that SmCNGC1a exhibited relatively higher expression levels in the root and leaf, and relatively lower expression levels in the stem and flower, suggesting its possible association with environmental adaptation in roots and leaves (Figure 8).

2.9. Silencing of SmCNGC1a Reduced Eggplant Tolerance to Cold Stress

To further investigate the function of SmCNGC1a in the cold-stress response of eggplant, we employed the VIGS method to silence SmCNGC1a. Agrobacterium infiltration solution was injected into the leaves of “JS221” seedlings, and 21 days later, the JS221 leaves injected with TRV:SmPDS exhibited pronounced chlorosis symptoms (Figure 9A), while no significant phenotype was observed in the control plants. Subsequently, we used qRT-PCR to examine the expression levels of the SmCNGC1a gene in the roots of silenced and control plants under cold stress to calculate the silencing efficiency. The results showed that the relative expression level of SmCNGC1a was significantly lower in the silenced plants compared to the control plants. In the control group, the expression of SmCNGC1a in the leaves was significantly upregulated under cold stress, while the expression level of SmCNGC1a in the silenced plants was suppressed (Figure 9B). These findings indicate successful silencing of SmCNGC1a. Furthermore, after 2 h of cold stress, the silenced plants exhibited more severe leaf wilting, stem bending, and loss of turgidity (Figure 9C), and the survival rate of the plants also significantly decreased (Figure 9D), suggesting that the silencing of SmCNGC1a reduced the cold tolerance of JS221, thus preliminarily confirming its positive regulatory role in the cold-stress response of eggplant. We also monitored the contents of chlorophyll a, chlorophyll b, carotenoids, proline, and malondialdehyde in the leaves of plants before and after silencing. The results revealed a significant decrease in the levels of photosynthetic pigments (chlorophyll a and chlorophyll b) compared to the control, accompanied by a substantial increase in proline and malondialdehyde content (Figure 9E). This suggests that the silencing of SmCNGC1a significantly affects the accumulation of proline and malondialdehyde in eggplant leaves, leading to a more pronounced degradation of chlorophyll a and chlorophyll b when compared to non-silenced plants.

2.10. Analysis Interaction Network of SmCNGC1a in Eggplant

To further investigate the function of SmCNGC1a, we utilized STEING v11.5 to predict and analyze its interaction network in eggplant. The results revealed that SmCNGC1a interacts with proteins related to defense response by callose deposition in the cell wall, regulation of anion channel activity, and receptor-mediated endocytosis (Smechr0201361.1, Smechr0201358.1, Smechr0201356.1, Smechr0201360.1). Additionally, it interacts with proteins associated with protein serine/threonine kinase activity, adenyl ribonucleotide binding, and ATP binding (Smechr0201224.1, Smechr0801839.1, Smechr0201360.1, Smechr0103284.1, Smechr0201226.1, Smechr0201225.1). The predicted interacting proteins’ KEGG pathways indicate their potential involvement in the plant MAPK signaling pathway and plant–pathogen interaction. The results of STEING local network cluster analysis suggest that these proteins may participate in cGMP-binding defense response by cell wall thickening and plant MAPK signaling pathway (Figure 10).

3. Discussion

With the increasing exploration of reference genomes in various plant species, many gene families have been identified; however, the CNGC gene family in eggplant remains unknown. In this study, we identified the CNGC gene family in eggplant and conducted comprehensive bioinformatics analyses of its physicochemical properties, phylogenetic evolutionary relationships, chromosome localization, gene structure, cis-acting elements, and gene duplication events. Subsequently, we analyzed the expression patterns of the CNGC gene family under cold stress and identified a significantly upregulated gene, SmCNGC1a, in response to cold stress. We further analyzed its subcellular localization and tissue-specific expression patterns. Finally, we employed VIGS technology to validate the function of this gene and analyzed its protein interaction network. Our physicochemical property analysis revealed that most members of the SmCNGC family are hydrophilic proteins localized in the plasma membrane, which confirms their role as ion channel proteins. Phylogenetic evolutionary analysis showed that the SmCNGC family has relatively more members compared to Arabidopsis and tomato, with a distinct branch exhibiting a distant evolutionary relationship with other species. This indicates that CNGC proteins in eggplant may have undergone unique evolutionary processes, possibly due to differences in the environmental conditions for eggplant survival during natural evolution compared to Arabidopsis and tomato, leading to adaptive evolution of the genes. Motif analysis identified a total of 10 motifs, among which the majority of SmCNGC proteins exhibit 8 conserved motifs characterized by similar sequences. However, a unique motif 6 is present in another branch, while motif 5 is absent, suggesting that this subset of SmCNGC proteins may have distinct preferences and potentially exert specialized functions during evolution.
According to reports, Ca2+ channels play a crucial role in plant responses to temperature stress [32]. Studies conducted on rice (Oryza sativa L.), cabbage (Brassica oleracea L.), tobacco (Nicotiana benthamiana), and mango (Mangifera indica L.) have shown that the expression of CNGC gene family undergoes changes under cold-stress conditions. For instance, 10 OsCNGCs in rice [33], 13 BoCNGCs in cabbage [34], 10 NtabcCNGCs in tobacco [35], and the genes MiCNGC15 and MiCNGC15II in mango fruit peel [36] were found to be upregulated under cold stress. Additionally, a study in 2020 identified 15 ZjCNGCs in the jujube (Ziziphus zizyphus) genome, where ZjCNGC2, 8, 10, and ZjCNGC15 showed downregulation within 24 h of cold-stress treatment, while the expression levels of ZjCNGC4 and ZjCNGC12 increased approximately four-fold and two-fold, respectively, after 1 h of cold treatment [37]. According to the research on temperature-stress treatment in Chinese cabbage (Brassica rapa pekinensis), it was found that the expression of BrCNGC1, 2, 3, 10, 17, 22, 23, 27, and BrCNGC29 was upregulated under low-temperature stress [38]. Apart from cold stress, CNGCs have also been found to be involved in regulating heat stress. Specifically, the genes AtCNGC6 and AtCNGC2 are involved in plant response to heat stress and are closely associated with plant thermotolerance. Under high-temperature induction, AtCNGC6 triggers Ca2+ influx and the adaptive expression of heat-shock proteins. Mutants of AtCNGC2, namely cngc2-1 and cngc2-2, exhibit enhanced tolerance to heat stress and accumulate more heat-responsive proteins [39,40]. Conversely, interference with CNGCb (a homologous gene of AtCNGC2) from the moss Physcomitrella patens leads to a super-thermosensitive phenotype in plants [41]. In rice, OsCNGC14 and OsCNGC16 also play important roles in plant thermotolerance. Mutants cngc14 and cngc16 show lower survival rates under high and low-temperature stress, and the extent of heat-stress induction and inhibition of certain genes is altered in the cngc16 mutant. Furthermore, the absence of OsCNGC14 or OsCNGC16 reduces or eliminates the cytosolic Ca2+ signals induced by temperature stress [42]. In this study, we found numerous light-responsive elements, hormone-responsive elements, and transcription factor binding sites in the promoter region of the SmCNGC gene, indicating that this gene family may respond to environmental signals and stress, potentially playing an important role in regulating eggplant’s environmental adaptation. The expression pattern analysis of SmCNGC genes under cold stress also suggests that many genes in this family can respond to low-temperature signals. Specifically, we observed significant upregulation of SmCNGC1a under cold stress, and this finding was further validated through VIGS experiments, highlighting its importance in eggplant’s response to low temperatures.
In addition, we predict complex interactions between SmCNGC1a and various proteins in eggplant, including cell wall defense response proteins, anion channel activity regulatory proteins, and serine/threonine-kinase-related proteins. Cell wall defense response proteins participate in the synthesis and deposition of pectin, enhancing the defensive capacity of plant cell walls. They are important mechanisms for plants to resist stress and adversity [43]. Anion channel activity regulatory proteins, similar to CNGCs, constitute a class of membrane protein channels that can regulate intracellular ion balance and signal transduction [44]. During stress and adversity, these proteins may interact synergistically with CNGCs to resist stress. Serine/threonine kinases are a class of enzyme proteins that phosphorylate serine (Ser) or threonine (Thr) residues in target proteins and participate in the regulation of various signal transduction pathways [45]. We speculate that SmCNGC1a may interact with the aforementioned proteins to transmit cold-stress signals and activate cold-stress-defense-related genes. However, this speculation requires further experimental validation. It is worth noting that although our study confirms the positive regulatory role of SmCNGC1a in cold tolerance in eggplant, there are still many unresolved questions that require further investigation. For example, a deeper understanding of the process by which SmCNGC1a transmits cold-stress signals and clarification of its regulatory relationships with other genes, as well as the detailed mechanisms of the regulatory pathways, are needed. Our study provides a reference for further research on cold-tolerance genes in eggplant.

4. Materials and Methods

4.1. Identification of CNGC Gene Family in Eggplant Genome

The reference genome, coding sequences (CDS), and protein sequences of eggplant were obtained from the Eggplant Genome Database (Table 2). Hidden Markov model (HMM) profiles for the cyclic nucleotide-binding domain (cNMP, PF00027) and the ion transport protein domain (iTP, PF00520) used by the eggplant CNGC gene family were obtained from the InterPro protein family database (Table 2). The HMM profiles were searched using HMMER v3.0 software to identify genes containing both cNMP and iTP domains. These genes were then extracted, and further manual verification was performed using the NCBI CDD (Table 2) to ensure the inclusion of genes with both conserved domains and to remove pseudogenes. The final set of SmCNGC gene family members was obtained. The molecular weight, theoretical isoelectric point, instability index, aliphatic index, and average hydrophilicity of all the genes in the family were predicted using the Expasy ProtParam tool (Table 2). Additionally, the subcellular localization of the SmCNGCs was predicted using the WoLF PSORT subcellular localization prediction tool (Table 2).

4.2. Multiple Sequence Alignment and Phylogenetic Analysis

The protein sequence information of the Arabidopsis CNGC gene family was obtained from TAIR (Table 2). The protein sequences of the tomato CNGC gene family were referenced based on the identification results from previous studies conducted by other researchers [17] and obtained from the tomato genome database (Table 2). The amino acid sequences of CNGC gene families in Arabidopsis, tomato, and eggplant were aligned using MEGA v7.0. After removing non-conserved gaps, the alignment results were used to construct a phylogenetic tree using the maximum likelihood (ML) method with a bootstrap value set at 1000. The generated phylogenetic tree file was imported into Evolview v3 (Table 2) for visualization.

4.3. Gene Structures and Conserved Motifs Analysis

The genomic annotation file (.gff) for eggplant was obtained from the Eggplant Genome Database. The software TBtools v1.120 was used to extract gene length and positional information from the genomic annotation file of SmCNGCs. The extracted data were then visualized. The amino acid sequence motifs of SmCNGCs were analyzed using MEME (Table 2), with the search model set as “anr” and a minimum motif length of 6 and a maximum motif length of 50. Only the top 10 most reliable pieces of motif information were retained. The analysis results were visualized using MEME and Tbtools software [46].

4.4. Gene Distribution and Cis-Acting Elements Prediction

After extracting the chromosome position information of SmCNGCs using TBtools, the extracted results were imported into MapGene2Chromosome v2.1 (Table 2) to generate a chromosome location map of the gene family members. The promoter sequences of the SmCNGCs family were obtained using TBtools, specifically the 1500bp upstream of the gene’s start codon. These promoter sequences were then analyzed using the PlantCARE website (Table 2) to identify and retain regulatory elements associated with environmental response, hormone response, and transcription factor binding sites that occur frequently. The retained elements were visualized using TBtools [46].

4.5. Collinearity Analysis

To uncover intraspecies microsynteny groups in eggplant, we utilized the MCScanX plugin integrated within the TBtools software to perform collinearity analysis. Subsequently, the Circos plugin in TBtools was employed to generate circos plots depicting the microsynteny groups. Additionally, we employed MCScanX to analyze the co-occurrence relationships between the CNGC gene family in eggplant and those in Arabidopsis thaliana and tomato. Visualization was carried out using TBtools [46].

4.6. Plant Materials and Treatments

The plant materials used in this experiment were eggplant variety “JS221” and N. benthamiana. Seeds were germinated by placing them on moist filter paper in Petri dishes, followed by cultivation in a growth chamber. The growth chamber was kept at a constant temperature of 25 °C, with a relative humidity of 60–70% and a photoperiod of 16 h of light (800 µmol m−2 s−1) followed by 8 h of darkness. After germination, the seedlings were transplanted into seedling trays and subsequently transferred to small pots once the cotyledons had expanded, allowing for further growth. The plants were cultivated at a temperature of 25 °C and a photoperiod of 16 h of light (800 µmol m−2 s−1) followed by 8 h of darkness until they reached the 4–6 leaf stage for subsequent experiments. Cold-stress treatment was conducted in the growth chamber at a temperature of 4 °C and heat-stress treatment was conducted in the growth chamber at 42 °C, while the other conditions remained unchanged. After the treatment, the eggplant leaves were washed with ddH2O. Salt-stress treatment was conducted following the methods described in previous studies, with sampling focused on the root [47]. The samples were cryogenically preserved by immersing them in liquid nitrogen and then stored at a temperature of −80 °C to facilitate further analysis.

4.7. Subcellular Localization

SmCNGC1a was constructed into the pCambia1300-35S-EGFP plant overexpression vector to generate a fusion vector containing 35S: SmCNGC1a-GFP, which was then transformed into Agrobacterium strain GV3101. The composition of Agrobacterium suspension culture medium refers to previous studies in the field [47]. Healthy N. benthamiana were selected as the experimental material. Using a sterile syringe, the leaf surface of N. benthamiana was injected with OD600 = 0.8 suspension of pCambia1300-35S-EGFP empty vector and pCambia1300-SmCNGC1a-GFP separately, avoiding the leaf veins. This process was repeated three times. Subsequently, the injected N. benthamiana were cultivated in a growth chamber under appropriate lighting conditions for 48 h. The N. benthamiana leaves were then cut into suitable sizes, rinsed with sterile water, and mounted on glass slides. The fluorescence signals of the genes in the leaves were observed using a laser scanning confocal microscope (LSM 880NLO; Leica Microsystems, Wetzlar, Germany) to determine the cellular localization of SmCNGC1a.

4.8. Functional Analysis of SmCNGC1a Based on VIGS Method

The VIGS method referred to in previous studies [47] was employed. RNA was isolated from the leaves of pTRV2-SmCNGC1a-silenced plants and pTRV2 negative control plants, followed by qRT-PCR analysis to assess the silencing efficiency of SmCNGC1a. Cold-stress treatment was conducted according to the procedure outlined in Section 2.6. After 2 h treatment, the phenotypes of eggplant seedlings were observed under different experimental conditions, and the survival rates were calculated.

4.9. Gene Expression Analysis by qPCR

To analyze the transcriptional expression levels of the target gene, qPCR was performed following the method established by previous studies [47]. Four biological replicates were used to detect the transcript expression levels of the target gene. The primers used in this study are listed in Table 3.

4.10. Physiological Parameter Determination

The determination method of photosynthetic pigments is as follows: Firstly, 0.2 g of leaf samples were weighed into a mortar, and 12 mL of 95% ethanol was added. The samples were ground until the tissue turned white and left to stand for 3–5 min. Then, the mixture was filtered into a 25 mL brown volumetric flask using filter paper. The filter paper and residue were rinsed several times until no residues remained. Finally, the volume was adjusted to a fixed volume with ethanol and shaken well. The absorbance values (A665, A649, and A470) of the chlorophyll extract were measured at wavelengths of 665 nm, 649 nm, and 470 nm, respectively. The concentrations (mg/L) of chlorophyll a, chlorophyll b, and carotenoids were calculated using the following formulas: Ca = 13.95 × A6656.88 × A649; Cb = 24.96 × A649 − 0.32 × A665; Cx·c = (1000 × A − 2.05 × Ca − 114.8 × Cb)/245. Subsequently, the pigment content in the tissue (mg/g) was calculated using the following formula: Pigment content = Pigment concentration (calculated as above) × Extract volume × Dilution factor/FW (fresh weight) [48]. Proline content was determined using the Proline (Pro) Content Assay Kit (AKAM003C) provided by BoxBio (Beijing BoxBio Science & Technology Co., Ltd., Beijing, China). Malondialdehyde (MDA) content was determined using the Malondialdehyde (MDA) Content Assay Kit (AKFA013C) provided by BoxBio (Beijing BoxBio Science & Technology Co., Ltd.). The experimental procedures for these assays were performed according to the respective kit instructions. All experiments were conducted with three biological replicates to ensure reproducibility.

4.11. Statistic Analysis

The statistical analysis data were analyzed utilizing Microsoft Office Excel 2019 and IBM SPSS Statistics 26. To assess the variations among the samples, one-way analysis of variance (ANOVA) was conducted, followed by Tukey’s test (p < 0.01) for post hoc comparisons.

5. Conclusions

In general, we identified the CNGC gene family in eggplant and analyzed its expression patterns under cold stress. Finally, functional analysis was performed on the cold-responsive gene SmCNGC1a. These studies provide valuable information for the research on cold tolerance in eggplant. Further investigations can be based on these findings to explore the function of SmCNGC and the regulatory mechanisms of SmCNGC1a in cold tolerance in eggplant. This will provide a theoretical basis for the development of cold-tolerant eggplant varieties and breeding strategies aimed at enhancing cold tolerance in eggplant.

Author Contributions

All authors contributed experimental design oversight. X.Y. and L.S. conceived the experiments. Z.J., L.D., X.X. and L.Z. carried out the experiments with the help of J.H. and X.Y. contributed the plant materials and data analysis. Z.J. wrote the manuscript and J.H. edited the manuscript. All authors contributed to the article and approved the submitted version. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by The National Key Research and Development Program of China (2019YFD1000300).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare that they have no competing interests.

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Figure 1. Phylogenetic relationships among the SmCNGCs, AtCNGCs, and SlCNGCs. The amino acid sequences of CNGC gene families in Arabidopsis, tomato, and eggplant were aligned using MEGA v7.0. After removing non-conserved gaps, the aligned sequences were used to construct a phylogenetic tree using the maximum likelihood (ML) method. Bootstrap values were set to 1000. Sm: eggplant; At: Arabidopsis; Sl: tomato. Different colors represent different groups.
Figure 1. Phylogenetic relationships among the SmCNGCs, AtCNGCs, and SlCNGCs. The amino acid sequences of CNGC gene families in Arabidopsis, tomato, and eggplant were aligned using MEGA v7.0. After removing non-conserved gaps, the aligned sequences were used to construct a phylogenetic tree using the maximum likelihood (ML) method. Bootstrap values were set to 1000. Sm: eggplant; At: Arabidopsis; Sl: tomato. Different colors represent different groups.
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Figure 2. SmCNGC gene structures and the conserved motifs analyses. (A) Amino acid composition of each motif. (B) Motif compositions. (C) Conserved domains. (D) Gene structure. The motif logos were generated using the MEME Suite web server, while the remaining figures were generated using Tbtools.
Figure 2. SmCNGC gene structures and the conserved motifs analyses. (A) Amino acid composition of each motif. (B) Motif compositions. (C) Conserved domains. (D) Gene structure. The motif logos were generated using the MEME Suite web server, while the remaining figures were generated using Tbtools.
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Figure 3. Analysis of Chromosomal Location and Cis-Regulatory Elements of the SmCNGC Gene. (A) Chromosomal localization of SmCNGCs. The blue bars represent the length of each chromosome, reflecting their relative sizes. The SmCNGCs are indicated on the chromosomes using their respective gene names. The placement of gene names along the chromosomes signifies their positions within the genome of eggplant. (B) Prediction of cis-regulatory elements in the upstream regions of SmCNGC genes. Different colors represent different cis-regulatory elements, with each color corresponding to a specific functional motif. The genes are arranged on the left side of the figure according to their evolutionary relationships. The color legend on the right side of the figure indicates the different cis-regulatory elements, with the colors arranged in descending order of their occurrence frequency in SmCNGCs.
Figure 3. Analysis of Chromosomal Location and Cis-Regulatory Elements of the SmCNGC Gene. (A) Chromosomal localization of SmCNGCs. The blue bars represent the length of each chromosome, reflecting their relative sizes. The SmCNGCs are indicated on the chromosomes using their respective gene names. The placement of gene names along the chromosomes signifies their positions within the genome of eggplant. (B) Prediction of cis-regulatory elements in the upstream regions of SmCNGC genes. Different colors represent different cis-regulatory elements, with each color corresponding to a specific functional motif. The genes are arranged on the left side of the figure according to their evolutionary relationships. The color legend on the right side of the figure indicates the different cis-regulatory elements, with the colors arranged in descending order of their occurrence frequency in SmCNGCs.
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Figure 4. Collinearity analysis of SmCNGCs. (A) Chromosome locations and inter-chromosomal associations of SmCNGC genes. The colored lines represent different sets of collinear genes. The gene density in the chromosome is also depicted in the graph, with red indicating high density and blue indicating low density. (B) Collinearity analysis of CNGC genes between eggplant and the other two representative plants. The syntenic gene pairs were linked by blue lines.
Figure 4. Collinearity analysis of SmCNGCs. (A) Chromosome locations and inter-chromosomal associations of SmCNGC genes. The colored lines represent different sets of collinear genes. The gene density in the chromosome is also depicted in the graph, with red indicating high density and blue indicating low density. (B) Collinearity analysis of CNGC genes between eggplant and the other two representative plants. The syntenic gene pairs were linked by blue lines.
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Figure 5. Expression patterns of SmCNGC genes under different time points of 4 °C cold stress. The bar graph represents the expression patterns of SmCNGC genes under different time points of cold stress. The y-axis represents the relative expression levels, and the x-axis represents the time points of cold stress. Data are means ± standard deviation from four biological replicates. Different capital letters between samples denote significant differences according to one-way ANOVA and Tukey’s test (p < 0.01). The error bars represent the standard deviation.
Figure 5. Expression patterns of SmCNGC genes under different time points of 4 °C cold stress. The bar graph represents the expression patterns of SmCNGC genes under different time points of cold stress. The y-axis represents the relative expression levels, and the x-axis represents the time points of cold stress. Data are means ± standard deviation from four biological replicates. Different capital letters between samples denote significant differences according to one-way ANOVA and Tukey’s test (p < 0.01). The error bars represent the standard deviation.
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Figure 6. Expression patterns of SmCNGC1a under different stresses. Gene expression was analyzed using qPCR, with 0 h as the control. The blue columns represent cold stress, the red columns represent heat stress, and the yellow columns represent salt stress. Data are means ± standard deviation from four biological replicates. Different capital letters between samples denote significant differences according to one-way ANOVA and Tukey’s test (p < 0.01). The error bars represent the standard deviation.
Figure 6. Expression patterns of SmCNGC1a under different stresses. Gene expression was analyzed using qPCR, with 0 h as the control. The blue columns represent cold stress, the red columns represent heat stress, and the yellow columns represent salt stress. Data are means ± standard deviation from four biological replicates. Different capital letters between samples denote significant differences according to one-way ANOVA and Tukey’s test (p < 0.01). The error bars represent the standard deviation.
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Figure 7. Subcellular localization of SmCNGC1a. (A) Construction of the SmCNGC1a vector. (B) 35S:SmCNGC1a-GFP and 35S:GFP (control) were transformed into N. benthamiana epidermal cells using Agrobacterium-mediated transformation and injected. Results were observed using confocal microscopy 48 h after transformation. Scale bars = 50 μm.
Figure 7. Subcellular localization of SmCNGC1a. (A) Construction of the SmCNGC1a vector. (B) 35S:SmCNGC1a-GFP and 35S:GFP (control) were transformed into N. benthamiana epidermal cells using Agrobacterium-mediated transformation and injected. Results were observed using confocal microscopy 48 h after transformation. Scale bars = 50 μm.
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Figure 8. Expression levels of SmCNGC1a in different tissues of eggplant. Data are means ± standard deviation from four biological replicates. Different capital letters between samples denote significant differences according to one-way ANOVA and Tukey’s test (p < 0.01), The error bars represent the standard deviation.
Figure 8. Expression levels of SmCNGC1a in different tissues of eggplant. Data are means ± standard deviation from four biological replicates. Different capital letters between samples denote significant differences according to one-way ANOVA and Tukey’s test (p < 0.01), The error bars represent the standard deviation.
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Figure 9. Effects of SmCNGC1a silencing on eggplant responses to cold stress (A) TRV: the albino phenotype of SmPDS indicates the success of the silencing system. (B) Silencing efficiency of SmCNGC1a in plants under cold stress based on a qRT-PCR assay. (C) Phenotype of SmCNGC1a-silenced and control plants challenged with cold stress at 2 h post-treatment. RT: 25 °C; LT: 4 °C. (D) Survival frequencies of SmCNGC1a-silenced and control plants subjected to cold stress at 2 h post-treatment. (E) Contents of chlorophyll a, chlorophyll b, carotenoids, proline, and malondialdehyde in SmCNGC1a-silenced and control plants after 2 h of cold stress. Chl-a: chlorophyll a; Chl-b: chlorophyll b; PRO: proline; MDA: malondialdehyde; FW: fresh weight. Different capital letters between samples denote significant differences according to one-way ANOVA and Tukey’s test (p < 0.01).
Figure 9. Effects of SmCNGC1a silencing on eggplant responses to cold stress (A) TRV: the albino phenotype of SmPDS indicates the success of the silencing system. (B) Silencing efficiency of SmCNGC1a in plants under cold stress based on a qRT-PCR assay. (C) Phenotype of SmCNGC1a-silenced and control plants challenged with cold stress at 2 h post-treatment. RT: 25 °C; LT: 4 °C. (D) Survival frequencies of SmCNGC1a-silenced and control plants subjected to cold stress at 2 h post-treatment. (E) Contents of chlorophyll a, chlorophyll b, carotenoids, proline, and malondialdehyde in SmCNGC1a-silenced and control plants after 2 h of cold stress. Chl-a: chlorophyll a; Chl-b: chlorophyll b; PRO: proline; MDA: malondialdehyde; FW: fresh weight. Different capital letters between samples denote significant differences according to one-way ANOVA and Tukey’s test (p < 0.01).
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Figure 10. Interaction network analysis of SmCNGC1a. Nodes represent different proteins, with colored nodes indicating proteins that may have first shell of interactions with SmCNGC1a, and uncolored nodes indicating proteins that may have second shell of interactions with SmCNGC1a. Lines represent known or predicted protein–protein interactions, with blue lines indicating interactions predicted from homologous genes in other species, red lines indicating interactions that have been experimentally validated, green lines indicating interactions predicted using text mining methods, and purple lines indicating the presence of homology between the connected proteins. The “Smechr0500088.1” referred to by the red arrow is identified as SmCNGC1a.
Figure 10. Interaction network analysis of SmCNGC1a. Nodes represent different proteins, with colored nodes indicating proteins that may have first shell of interactions with SmCNGC1a, and uncolored nodes indicating proteins that may have second shell of interactions with SmCNGC1a. Lines represent known or predicted protein–protein interactions, with blue lines indicating interactions predicted from homologous genes in other species, red lines indicating interactions that have been experimentally validated, green lines indicating interactions predicted using text mining methods, and purple lines indicating the presence of homology between the connected proteins. The “Smechr0500088.1” referred to by the red arrow is identified as SmCNGC1a.
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Table 1. Identification and Physicochemical Analysis of SmCNGC Proteins.
Table 1. Identification and Physicochemical Analysis of SmCNGC Proteins.
Gene NameGene IDNumber of Amino Acid/aaMolecular WeightTheoretical pIInstability IndexAliphatic IndexGrand Average of HydropathicityPrediction of Subcellular Localization
SmCNGC1aSmechr0500088.171482,462.579.5153.7390.17−0.208cytomembrane
SmCNGC1bSmechr0101357.170881,926.229.3248.7293.4−0.071cytomembrane
SmCNGC1cSmechr0302178.171081,869.68.950.1192.46−0.132cytomembrane
SmCNGC2Smechr0202893.170881,371.839.6553.3492.78−0.034cytomembrane
SmCNGC3Smechr0400998.183896,160.877.3232.8693.05−0.198cytomembrane
SmCNGC4aSmechr1000491.168580,107.488.2846.9690.31−0.169cytomembrane
SmCNGC4bSmechr0400207.166577,317.038.9845.0392.77−0.075cytomembrane
SmCNGC5Smechr1200261.169278,774.979.1951.3292.76−0.114cytomembrane
SmCNGC6Smechr1100117.182394,278.626.3840.3498.54−0.131cytomembrane
SmCNGC7Smechr0700086.11074122,281.259.353.2790.8−0.079cytomembrane
SmCNGC8Smechr0303133.168979,669.918.7843.3591.13−0.183cytomembrane
SmCNGC9Smechr0801568.148255,399.668.2137.0896.24−0.188cytoplasm
SmCNGC10Smechr0800622.171482,222.565.8238.9795.03−0.123cytoplasm
SmCNGC11Smechr0801458.185996,677.46.640.6598.43−0.055cytomembrane
SmCNGC12Smechr0201396.165575,003.77.8439.8393.45−0.092cytomembrane
SmCNGC13Smechr0900702.161269,109.847.3246.0299.10.033cytomembrane
SmCNGC14Smechr0801673.163472,997.998.6747.0591.85−0.097cytomembrane
SmCNGC15aSmechr0900248.165976,020.098.7349.8193.38−0.033cytomembrane
SmCNGC15bSmechr0600577.169680,257.669.2450.5891.18−0.19cytomembrane
SmCNGC15cSmechr1201893.170480,655.839.2653.8188.82−0.217cytomembrane
SmCNGC16Smechr0302884.167477,929.88.3147.4889.39−0.157cytomembrane
SmCNGC17Smechr0700014.172083,011.829.3241.9793.74−0.174cytomembrane
SmCNGC18Smechr0203033.168979,438.127.1749.9888.78−0.15cytomembrane
SmCNGC19Smechr0302451.184095,490.136.1239.0597.96−0.151cytomembrane
SmCNGC20Smechr0302478.177188,894.769.3249.8789.29−0.191cytomembrane
SmCNGC21Smechr0500154.182794,588.856.6239.7894.79−0.13cytomembrane
SmCNGC22Smechr0103753.162972,010.198.1644.8299.63−0.018nucleus
SmCNGC23Smechr1200076.188499,814.776.4739.6596.24−0.111chloroplast
SmCNGC24Smechr0100701.183795,413.16.6133.2495.97−0.13cytomembrane
Table 2. Online Analysis Websites and URLs.
Table 2. Online Analysis Websites and URLs.
WebsiteURL
Eggplant Genome Databasehttp://eggplant-hq.cn/Eggplant/home/index (accessed on 3 March 2023)
InterPro protein family databasehttps://www.ebi.ac.uk/interpro/ (accessed on 3 March 2023)
NCBI CDDhttps://www.ncbi.nlm.nih.gov/cdd/ (accessed on 3 March 2023)
Expasy ProtParam toolhttps://web.expasy.org/protparam/ (accessed on 7 April 2023)
WoLF PSORT subcellular localization prediction toolhttps://wolfpsort.hgc.jp/ (accessed on 7 April 2023)
TAIRhttps://www.arabidopsis.org/ (accessed on 16 March 2023)
Tomato genome databasehttps://solgenomics.net/ (accessed on 16 March 2023)
Evolview v3https://www.evolgenius.info/evolview/ (accessed on 16 March 2023)
MEMEhttp://memesuite.org/tools/meme/ (accessed on 30 March 2023)
MapGene2Chromosome v2.1http://mg2c.iask.in/mg2c_v2.1/ (accessed on 30 March 2023)
PlantCAREhttp://bioinformatics.psb.ugent.be/webtools/plantcare/html/ (accessed on 30 March 2023)
Table 3. Primers used in this study.
Table 3. Primers used in this study.
Gene NameGene IDForward Primer (5’ –> 3’)Reverse Primer (5’ –> 3’)
SmCNGC1aSmechr0500088.1AACCAACGTTTAGCTCGTTGATAGAGGATGCATGCGAATTG
SmCNGC1bSmechr0101357.1AAAGCCACCAATCTGCTCATAGGAAAGGGATGCACATTGA
SmCNGC1cSmechr0302178.1CGGCAAATTTGGAGTGTTCTTTTGGCCAGAAGGCAACTTA
SmCNGC2Smechr0202893.1CAACCTGATAACAGCGACGATCACAACTGGTGGAATGGAA
SmCNGC3Smechr0400998.1GGAAGTGAAATATTCATCATATGGTTTCCACCTCTCTCACCGTACCT
SmCNGC4aSmechr1000491.1GGACAAGGATGTGGATGAGGACACGACCACGACCACTACA
SmCNGC4bSmechr0400207.1GCTCGAGTGATCTGATTGTTGATCCAAAATAAGTGATACCGATCC
SmCNGC5Smechr1200261.1TTGTTGATCTTTTGAGCTTTGCTTTACACAATCGGTGTATATAAAACTC
SmCNGC6Smechr1100117.1TGGAGGTCGAGCAGAGTATGTTTGCCGGCTAATTTTTCTC
SmCNGC7Smechr0700086.1GAGTCGAGTTTGAGGGCTTGTCGCAGTCTTGCTGATGAAC
SmCNGC8Smechr0303133.1TTGGAGGGCAAAAAGAAAAGTGGTTACATGCCCACCAGTA
SmCNGC9Smechr0801568.1CTGAAGGATCTGGATTCTTTGCTCATCTTGACATCTTAACTTATGGA
SmCNGC10Smechr0800622.1GGACATGGAAAGCAAACCAACGTCCACAACTTTCACCTTC
SmCNGC11Smechr0801458.1ATTGCTTGTGGACAATGGTGTCACCTCCATACCGGATGAT
SmCNGC12Smechr0201396.1GGGATTTGGAGGTTTTGGTTTGTCCATCACCTTTCTCTTGC
SmCNGC13Smechr0900702.1TTTCAGAAATGTATCTGATTGACCCTCAATGACTAGAATTCCGCTGT
SmCNGC14Smechr0801673.1AGCTGGCCAAAGAACTTTACATGTTGATCATCCTCGGGTTC
SmCNGC15aSmechr0900248.1CCTCGAGGAGGTCCTATAAACACCATGGGATAACTTGCATCC
SmCNGC15bSmechr0600577.1CAGTTGTAACTTGTAAGATAAGATGGAATGGCACAAAAGCTGCAGTA
SmCNGC15cSmechr1201893.1CAAATGTGGAAGGGTGTTTTGTTTCTCTTCCCCCTCTTGC
SmCNGC16Smechr0302884.1CAGGGAAAGTCGTTTTGGAAGGAAGCAGCAAAAACAGAGG
SmCNGC17Smechr0700014.1TGGGAGGAAAAGCAGACAGTCCTTTTTAGGCCTCCCAAAC
SmCNGC18Smechr0203033.1GGTGGCGTCAGATTTTTGATTGACGAAAGGGACGAAGAAG
SmCNGC19Smechr0302451.1GCCAAAGAAGTTCAGGCAGAAGTAATTCCGCAGCCATTTG
SmCNGC20Smechr0302478.1TTGGTCGAGAGCCTGAGAATTACGCCAACCATTTCGTTCT
SmCNGC21Smechr0500154.1AATCGTCGAGAAGCAGCAGTGAGGCCATTGATGACGTTTT
SmCNGC22Smechr0103753.1AAAAACAGAGGAAACAAATATAATGAATGCTATCATGTTCATCTCATTACCA
SmCNGC23Smechr1200076.1TGGAGCAGCACAAGAAATTGTTGCCGATCATAAGGTGAAA
SmCNGC24Smechr0100701.1TGCAAATGAGCCATTCATACATGCTACTCCCATGGCTATCA
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MDPI and ACS Style

Jiang, Z.; Du, L.; Shen, L.; He, J.; Xia, X.; Zhang, L.; Yang, X. Genome-Wide Exploration and Expression Analysis of the CNGC Gene Family in Eggplant (Solanum melongena L.) under Cold Stress, with Functional Characterization of SmCNGC1a. Int. J. Mol. Sci. 2023, 24, 13049. https://doi.org/10.3390/ijms241713049

AMA Style

Jiang Z, Du L, Shen L, He J, Xia X, Zhang L, Yang X. Genome-Wide Exploration and Expression Analysis of the CNGC Gene Family in Eggplant (Solanum melongena L.) under Cold Stress, with Functional Characterization of SmCNGC1a. International Journal of Molecular Sciences. 2023; 24(17):13049. https://doi.org/10.3390/ijms241713049

Chicago/Turabian Style

Jiang, Zheng, Lihui Du, Lei Shen, Jie He, Xin Xia, Longhao Zhang, and Xu Yang. 2023. "Genome-Wide Exploration and Expression Analysis of the CNGC Gene Family in Eggplant (Solanum melongena L.) under Cold Stress, with Functional Characterization of SmCNGC1a" International Journal of Molecular Sciences 24, no. 17: 13049. https://doi.org/10.3390/ijms241713049

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