Next Article in Journal
Toxicity and Anti-Inflammatory Activity of Phenolic-Rich Extract from Nopalea cochenillifera (Cactaceae): A Preclinical Study on the Prevention of Inflammatory Bowel Diseases
Previous Article in Journal
Turmeric and Cumin Instead of Stock Cubes: An Internet Survey of Spices and Culinary Herbs Used in Poland Compared with Historical Cookbooks and Herbals
Previous Article in Special Issue
Effect of Elevated CO2 and Drought on Biomass, Gas Exchange and Wood Structure of Eucalyptus grandis
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Plants
Volume 12
Issue 3
10.3390/plants12030592
plants-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Genome-Wide Analysis and Expression of Cyclic Nucleotide–Gated Ion Channel (CNGC) Family Genes under Cold Stress in Mango (Mangifera indica)

by
Yajie Zhang
1,†,
Yubo Li
2,3,†,
Jing Yang
1,
Xinli Yang
4,
Shengbei Chen
5,
Zhouli Xie
6,
Mingjie Zhang
1,
Yanlei Huang
7,
Jinghong Zhang
1,8,* and
Xing Huang
2,9,10,*
1
Hainan Climate Center, Haikou 570203, China
2
Environment and Plant Protection Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou 571101, China
3
College of Tropical Crops, Hainan University, Haikou 570228, China
4
Guilinyang Campus, Qiongtai Normal University, Haikou 571127, China
5
Hainan Meteorological Service Center, Haikou 570203, China
6
School of Life Sciences, Peking University, Beijing 100871, China
7
College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
8
Key Laboratory of South China Sea Meteorological Disaster Prevention and Mitigation of Hainan Province, Haikou 570203, China
9
Key Laboratory of Integrated Pest Management on Tropical Crops, Ministry of Agriculture and Rural Affairs, Haikou 571101, China
10
Hainan Key Laboratory for Monitoring and Control of Tropical Agricultural Pests, Haikou 571101, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Plants 2023, 12(3), 592; https://doi.org/10.3390/plants12030592
Submission received: 28 November 2022 / Revised: 15 January 2023 / Accepted: 20 January 2023 / Published: 29 January 2023
(This article belongs to the Special Issue Abiotic Stress Responses in Woody Plants)
Browse Figures
Versions Notes

Abstract

:
The ‘king of fruits’ mango (Mangifera indica) is widely cultivated in tropical areas and has been threatened by frequent extreme cold weather. Cyclic nucleotide–gated ion channel (CNGC) genes have an important function in the calcium-mediated development and cold response of plants. However, few CNGC-related studies are reported in mango, regardless of the mango cold stress response. In this study, we identified 43 CNGC genes in mango showing tissue-specific expression patterns. Five MiCNGCs display more than 3-fold gene expression induction in the fruit peel and leaf under cold stress. Among these, MiCNGC9 and MiCNGC13 are significantly upregulated below 6 °C, suggesting their candidate functions under cold stress. Furthermore, cell membrane integrity was damaged at 2 °C in the mango leaf, as shown by the content of malondialdehyde (MDA), and eight MiCNGCs are positively correlated with MDA contents. The high correlation between MiCNGCs and MDA implies MiCNGCs might regulate cell membrane integrity by regulating MDA content. Together, these findings provide a valuable guideline for the functional characterization of CNGC genes and will benefit future studies related to cold stress and calcium transport in mango.

1. Introduction

The cyclic nucleotide–gated ion channel (CNGC) family belongs to nonselective cation channels, which enable the uptake of ions, including K+, Ca2+ and Na+ [1]. The channel gate-control function of CNGC genes confers their essential roles in regulating plant growth and development [2]. Furthermore, members of the CNGC family are reported to mediate cellular ion homeostasis to regulate abiotic and biotic stress response [3]. Usually, plant CNGC genes contain six transmembrane domains, in which the cyclic nucleotide-binding domain (CNBD) is between the fifth and sixth transmembrane domains [4]. The CNBD domain is highly conserved and could be used to identify CNGC genes among plant species [5]. To date, the CNGC family has been widely reported in many plant species, such as in Arabidopsis thaliana (20), Atalantia buxfolia (31), Brassica oleracea (26), Brassica rapa (29), Citrus grandis (30), Citrus recticulata (27), Citrus sinensis (32), Gossypium hirsutum (40), Gossypium barbadense (41), Gossypium herbaceum (20), Gossypium arboreum (20), Gossypium raimondii (20), Nicotiana tabacum (35), Oryza sativa (16), Poncirus trifoliata (30), Pyrus bretchneideri (21), Solanum tuberosum (20), Triticum aestivum (47), Zea mays (12) and Ziziphus jujuba (15) [2,5,6,7]. Most importantly, their functions have been well characterized in model plant Arabidopsis. For example, 15 AtCNGCs (AtCNGC1-10/12/14/16/18/20) are encoded Ca2+-permeable channels [8], and numerous studies confirm their functions in plant development, such as AtCNGC2 in leaf senescence, AtCNGC3 in germination, AtCNGC5/6/9 in root hair development, AtCNGC7/8 in male fertility, AtCNGC14 in root gravitropism and AtCNGC16/18 in pollen development [9,10,11,12,13,14,15]. Several AtCNGCs are involved in stress response, including AtCNGC1/10/19/20 in salt stress, AtCNGC2/4/11/12 in abiotic stress, AtCNGC2/5/6/9/12 in stomatal defense and AtCNGC6 in heat stress [16,17,18,19,20,21,22]. Together, these findings provide valuable references for functional characterization and application of CNGC genes in non-model plant species.
Mango, known as the ‘king of fruits’, is one of the most popular fruits [23]. Its annual fruit yield ranks fifth around the world [24]. The main cultivated Mangifera species in the tropical areas around the world is Mangifera indica [25]. As a typical tropical plant, mango is sensitive to cold temperature [26], especially frequent extreme cold weather, which has significantly threatened to mango production in recent years [27]. However, few studies have revealed the molecular basis of cold stress response in mango trees, even if the cold storage of detached fruits has been well studied [28]. Considering that overexpression of CNGC genes promotes rice cold tolerance, we conducted genome-wide analysis of the CNGC family in mango and evaluated its expression in mango tissues, as well as that under cold stress [29]. The results showed that expression of several MiCNGCs was upregulated under cold temperature and highly correlated to leaf damage index malondialdehyde (MDA) contents, implying their beneficial roles in regulating mango cold tolerance. Therefore, our study will offer guidance for functional characterization of CNGC genes and benefit future studies in mango.

2. Results

2.1. Characterisation of CNGC Family in Mango

The Arabidopsis and rice CNGC genes were selected to search homologous genes in the genomes of Amborella trichopoda, sweet orange (Citrus sinensis) and mango [24,30,31]. Because sweet orange belongs to the Sapindales order together with mango, it was selected as a nearby reference [24]. Amborella was chosen as the outgroup reference to the Sapindales order since it is the basal angiosperm [30]. As a result, 7, 33 and 43 CNGC genes were identified in above three species (Table 1 and Table S1). In mango species, these genes ranged from 399 to 2343 bp with predicted protein lengths of 132–780 aa. Their molecular weights and theoretical pI ranged from 14907.27 to 89883.31 Da and 4.88 to 9.67, respectively. Most of them (36 of 43) were predicted to be located at the plasma membrane, contain 3–7 transmembrane helices (Figure S1). Five and two were predicted to be nuclear and extracellular, respectively. There was no more than one transmembrane helix in these seven genes. A total of 39 mango CNGC genes were distributed at 13 chromosomes. Two major gene clusters, including 10 and 12 CNGC genes at chromosomes 9 and 15, respectively, were labeled (Figure 1).

2.2. Phylogenetic Relationships of Mango CNGC Genes

The CNGC proteins of Arabidopsis, rice, Amborella, sweet orange and mango were selected to construct the maximum-likelihood phylogenetic tree (Figure 2). Finally, four groups (I–IV) were generated, where almost the same quantities of CNGC proteins from the four species existed in each group. Interestingly, only sweet orange and mango CNGC proteins were clustered into group IV-C. Mango CNGC proteins were further aligned to identify their conserved domains. The results showed that most of them contained the CNBD domain ([L]-X(0,1,2)-[G]-X(1,3)-G-X(1,2)-[L]-[L]-X(0,1)-[W]–X(0,2)-[L]–X (0,7,8,9,10,18)-[P]-X-S-X(10)-[E]-A-[F]-X(0,1)-L) except MiCNGC43 (Figure S2). However, nine mango CNGC proteins lost the N-termini due to evolution issues, namely MiCNGC10, 11, 15, 21, 25, 27, 28, 35 and 36. We further calculated the values of synonymous substitutions (Ks), nonsynonymous site (Ka) and their ratio (Ka/Ks). The results indicated that all the Ka/Ks values were below 1 in homologous gene pairs (Table S2).

2.3. In Silico Expression of CNGC Genes in Mango Tissues

We further examined the expression levels of mango CNGC genes in leaf, fruit peel and fruit flesh based on published transcriptome data. The expression data were normalized into fragments per kilobase of exon model per million mapped fragments (FPKM) (Table S3). MiCNGC17, 19 and 22 were relatively expressed at high levels in all three tissues (FPKM > 10) (Figure 3). Several tissue-specific expressed mango CNGC genes were revealed too, such as MiCNGC13, 31 and 38 in leaf and MiCNGC4, 9, 36 and 34 in fruit peel. At the same time, 10 mango CNGC genes displayed extremely low expression (FPKM < 10) in all three tissues, namely MiCNGC2, 11, 14, 24, 30, 33, 35, 37, 42 and 43, whereas 23 genes showed no expression detected by transcriptome sequencing (Table S3).

2.4. In Silico Expression of CNGC Genes under Cold Stress in Mango Fruit Peel

In order to evaluate their molecular functions under cold stress in fruit peel, moderate (12 °C) and extreme (5 °C) temperatures were chosen to compare CNGC expression patterns. The two treatments allow us to better understand the expression tendency of CNGC genes under cold stress. The results indicated that most CNGC genes (33 of 43) showed no or relatively low expression levels (FPKM < 10) under cold treatments of both 5 and 12 °C, implying that they might play minimal roles for cold tolerance (Table S3). However, 10 CNGC genes showed higher expression triggered by cold stress (Figure 4). Among these, three of them showed moderate expression patterns under 12 °C, but more than three-fold upregulated expression level under 5 °C (MiCNGC4, 9 and 34). Five genes showed similar expression patterns whether at 5 or 12 °C (MiCNGC13, 17, 19, 31 and 36), while MiCNGC13 and 36 were up and downregulated over 3-fold under 5 °C after prolonged 14-day cold treatment, respectively. Moreover, MiCNGC22 and MiCNGC33 showed absolutely opposite expression patterns under the two degrees.

2.5. Expression Profiles of CNGC Genes under Cold Stress in Mango Leaf

To better understand how the CNGC genes affect cold stress response in mango plant, 10 mango CNGC genes were selected for qRT-PCR validation in mango leaf. These genes include five with expression changes over threefold under cold stress in fruit peel and five with FPKM values over 10 in leaf. The results indicated that most genes were upregulated after cold treatment in leaf except MiCNGC4 (Figure 5). Among these, six were up-regulated more than threefold, namely MiCNGC9, 13, 17, 22, 31 and 38. Additionally, the expression of MiCNGC13 was not significantly affected when temperature was higher than 4 °C, indicating that MiCNGC13 might have leaf- and fruit-peel-specific temperature sensitivity.

2.6. Positively Correlated Mango CNGC Genes with MDA Contents

The content of malondialdehyde (MDA) is usually considered as a lipid peroxidation index that indicates the damage of stress. We therefore further measured MDA in mango leaf to evaluate the physiological effects of cold stress. As expected, MDA contents were significantly increased under cold treatment, specially under 2 °C (Figure 6A). This result suggested that temperatures under 2 °C might cause irreversible damage to the mango plant. To further determine whether CNGC genes regulate MDA level or not, we performed correlation analysis to explore CNGC genes that were highly correlated with MDA contents. The results showed that three and five CNGC genes were positively correlated with MDA contents with significant correlation coefficients at 0.05 (R > 0.532) and 0.01 (R > 0.661) cut-offs, respectively.

3. Discussion

3.1. Species-Specific Expansion of CNGC Family in Mango

In the present study, we have successfully identified 7, 33 and 43 CNGC genes in Amborella, sweet orange and mango (Table 1 and Table S1). As a basal angiosperm, Amborella has a relatively small number of CNGC genes compared with other four species (Figure 2). Beyond this, these genes are almost evenly distributed into three groups (I, II and III) and two subgroups (IV-A and IV-B), indicating the conserved evolution patterns and pressure among these groups [4]. Interestingly, there is a subgroup (IV-C) containing CNGC genes from either mango (23) or sweet orange (21). Most of them are distributed at chromosomes 9 and 15 in mango (18) and chromosome 9 in sweet orange (21) (Figure 1), verifying their Sapindales classification. However, the species-specific expansion of CNGC genes among mango and sweet orange also emphasizes the species divergence during evolution [32]. In addition, mango CNGC genes are classified into two major gene clusters, which might be divided from the same cluster during the hypothetical auto-diploidization [24]. Seven mango CNGC genes contain short coding regions (<1000 bp), such as MiCNGC10, MiCNGC28 and so on (Table 1), which might be caused by frequent chromosomal recombination (Table S3) [33]. They might lose the function of Ca2+-permeable channels without complete transmembrane structure (Figure S1), which also affected their subcellular localizations predicted by CELLO.

3.2. Candidate CNGC Genes in Cold Stress Response in Mango

The in silico expression of CNGC genes in mango tissues illustrates that mango CNGC genes have tissue-specific expression patterns (Figure 3). The high and constitutive expression of MiCNGC17 indicate that it might affect the whole mango development period. We further evaluated the expression of CNGC genes under cold stress to identify candidate regulators that contribute to cold tolerance. As shown, five MiCNGCs in fruit peel and five in leaf displayed more than three-fold upregulation of gene expression; specifically, MiCNGC9 and MiCNGC13 are induced in both tested tissues suggesting their potential functions under cold stress (Figure 4 and Figure 5). Since MDA is the main indicator of cell membrane integrity [34], we observed that MDA content is significantly increased at 2 °C compared with 4, 6 and 8 °C (Figure 6A), which means that lower temperature leads higher damage. Then we revealed that eight MiCNGCs are positively correlated with MDA by correlation analysis (Figure 6B), emphasizing that MiCNGCs might regulate MDA content to adjust cell membrane integrity. Therefore, these eight genes could be considered as early cold-responsive markers in the mango leaf, among which MiCNGC13 ranks first as the early cold-responsive maker gene in the mango leaf and fruit peel.

4. Materials and Methods

4.1. Bioinformatic Analysis of CNGC Genes

CNGC protein sequences of Arabidopsis and rice were selected as queries to search homologous proteins using the Blastp method [4,35]. The genomes of Amborella, sweet orange and mango were set as targets for sequence retrieval [24,30,31]. The details of CNGC genes in Ambrella and sweet orange are listed in Table S1. The accession numbers and chromosome positions of mango CNGC genes are in Table 1 and were further used to illustrate their distribution in chromosomes using TBtools software [36]. The sequence features of length, molecular weight and pI were predicted using the ProtParam tool with subcellular localization predicted using CELLO software [37,38]. The TMHMM2.0 software was selected to predict the transmembrane helices in CNGC proteins [39]. A maximum-likelihood phylogenetic tree was constructed for phylogenetic analysis with bootstrap values of 1000 using MEGA 7.0 software [40]. The mango CNGC proteins were further aligned by DNAMAN7 software to examine the conserved domains [41]. The Ks, Ka and Ka/Ks values were calculated using TBtools software [36].

4.2. In Silico Gene Expression Analysis

The raw data of transcriptome sequencing were downloaded from the Sequence Read Archive (SRA) database [42]. The raw data of leaf (SRR3288569), fruit peel (SRR2960401) and fruit flesh (SRR11060165) were selected to evaluate the expression patterns of CNGC genes in different mango tissues. The raw data of cold-treated fruit peel (SRP066658) were selected to evaluate the expression patterns of CNGC genes in mango fruit peels under cold stress, which were generated at 0, 2, 7 and 14 days after storage at 5 and 12 °C [43]. All raw data were trimmed to generate clean reads, which were further mapped to mango CNGC genes to calculate FPKM values for each gene with the RSEM software [44,45]. The heat map was generated using Morpheus software [46]. The hierarchical clustering method was selected to cluster the FPKM values at the levels of tissues and genes [47].

4.3. Plant Materials and Treatment

The mango variety Hongyu was selected for cold treatment. Experiments were carried out in a mango garden (109.11° E, 19.22° N) at Jishi Village, Changjiang, China. The branches of 15-year-old trees were put into RR-CTC806C incubators (Rainroot Scientific, Beijing, China) for cold treatments at four temperatures, namely 2, 4, 6 and 8 °C. After that, leaves were collected at 0, 1, 2 and 4 h. Leaves from two branches were put together as one sample and each sample was repeated three times as a biological replicate. All the samples were stored at −80 °C before further analysis.

4.4. Quantitative PCR and MDA Assay

Total RNA was isolated from each sample using the Tiangen RNA prep Pure Plant Kit (Tiangen Biomart, Beijing, China) and then transcribed into cDNA using the GoScript Reverse Transcription System (Promega, Madison, WI, USA) [48]. Quantitative PCR was conducted with the QuantStudio 6 Flex Real-Time PCR System (Thermo Fisher Scientific, Waltham, MA, USA). The reaction program contained three stages of initiation (94 °C for 30 s), 40 cycles (94 °C for 5 s and 60 °C for 30 s) and dissociation. The TransStart Tip Green qPCR SuperMix (Transgen Biotech, Beijing, China) was selected as the reaction solution, containing 10 μL supermix, 0.4 μL Passive Reference Dye, 1 μL cDNA, 0.5 μL of two primers and 7.6 μL nuclease-free water. Each sample was repeated three times as technical replicates. The Primer 3 software was used for primer design, and MiActin was selected as a reference gene (Table 2) [49]. The relative expression levels were calculated with the ΔΔCt method as previously described [50,51]. The MDA contents were examined using the Malondialdehyde (MDA) Content Assay Kit (Solarbio, Beijing, China) according to the manufacturer’s instruction [52]. About 0.1 g of each sample was broken into powder in liquid nitrogen and isolated with 1 mL Extraction reagent, which was fully homogenized in ice and centrifuged for supernatant (8000× g for 10 min at 4 °C). A total of 100 μL supernatant was mixed with 300 μL MDA working reagent and 100 μL Reagent III. Distilled water was selected as a blank reference. The mixtures of samples (T) and distilled water (B) were incubated for 60 min under 100 °C, which were cooled and centrifuged (10,000× g for 10 min) for supernatant at room temperature. The supernatants of mixtures (200 μL) were placed in a 96-well flat-bottom plate for the detection of absorbance (A) at 450, 532 and 600 nm with the Biotek Synergy H1 system (Agilent Technologies, Lexington, MA, USA). The MDA content was calculated with the following formula, MDA (nmol/g) = (12.9 × (∆A532 − ∆A600) − 1.12 × ∆A450) × Vrv ÷ (W × Vs ÷ Vsv) = 5 × (12.9 × (∆A532 − ∆A600) − 1.12 × ∆A450) ÷ W. Vrv, Vs, Vsv and W represent total reaction volume (0.5 mL), sample volume (0.1 mL), the volume of Extraction reagent (1 mL) and sample weight, respectively. ∆A450 = A450(T) − A450(B), ∆A532 = A532(T) − A532(B), ∆A600 = A600(T) − A600(B).

5. Conclusions

Extreme cold weather is a significant threat to the tropical fruit tree mango. Thus, we carried out a genome-wide analysis and assessed the expression of mango CNGC genes under cold stress, due to their importance in calcium-mediated development and cold response. The result revealed 43 CNGC genes with species-specific expansion in the mango genome. In silico expression analysis indicated their tissue-specific expression patterns and five differentially expressed CNGC genes under cold stress in mango fruit peel. The results of the qRT-PCR validation and MDA assay revealed five differentially expressed CNGC genes under cold stress in the mango leaf, which are also positively correlated with MDA contents. These results indicate a candidate early cold-responsive marker gene, MiCNGC13, in the mango leaf and fruit peel, which will be helpful to future studies related to cold stress in mango.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/plants12030592/s1, Figure S1: Transmembrane topology analysis for mango CNGC proteins; Figure S2: Alignment of CNGC proteins in mango; Table S1: Details of CNGC genes in amborella and sweet orange; Table S2: The values of synonymous substitutions (Ks), nonsynonymous site (Ka) and their ratio (Ka/Ks) in homologous gene pairs.; Table S3: FPKM values of mango CNGC genes in different tissues and under cold stress.

Author Contributions

Conceptualization, Y.Z., J.Z. and X.H.; formal analysis, Y.Z., Y.L., and X.H.; investigation, Y.Z., Y.L., J.Y., X.Y., S.C., M.Z. and Y.H.; writing—original draft preparation, Y.Z. and X.H.; writing—review and editing, Z.X.; supervision, J.Z.; funding acquisition, J.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by National Key Research and Development Program of China [2019YFD1002203] and the innovation platform for Academicians of Hainan Province.

Data Availability Statement

All data are contained within the article or Supplementary Materials.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Kaplan, B.; Sherman, T.; Fromm, H. Cyclic nucleotide-gated channels in plants. FEBS Lett. 2007, 581, 2237–2246. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Baloch, A.A.; Raza, A.M.; Rana, S.S.A.; Ullah, S.; Khan, S.; Zaib-Un-Nisa; Zahid, H.; Malghani, G.K.; Kakar, K.U. BrCNGC gene family in field mustard: Genome-wide identification, characterization, comparative synteny, evolution and expression profiling. Sci. Rep. 2021, 11, 24203. [Google Scholar] [CrossRef] [PubMed]
  3. Jha, S.K.; Sharma, M.; Pandey, G.K. Role of Cyclic Nucleotide Gated Channels in Stress Management in Plants. Curr. Genom. 2016, 17, 315–329. [Google Scholar] [CrossRef] [PubMed]
  4. Nawaz, Z.; Kakar, K.U.; Saand, M.A.; Shu, Q.Y. Cyclic nucleotide-gated ion channel gene family in rice, identification, characterization and experimental analysis of expression response to plant hormones, biotic and abiotic stresses. BMC Genom. 2014, 15, 853. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. Saand, M.A.; Xu, Y.P.; Munyampundu, J.P.; Li, W.; Zhang, X.R.; Cai, X.Z. Phylogeny and evolution of plant cyclic nucleotide-gated ion channel (CNGC) gene family and functional analyses of tomato CNGCs. DNA Res. 2015, 22, 471–483. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Zia, K.; Rao, M.J.; Sadaqat, M.; Azeem, F.; Fatima, K.; Tahir Ul Qamar, M.; Alshammari, A.; Alharbi, M. Pangenome-wide analysis of cyclic nucleotide-gated channel (CNGC) gene family in Citrus spp. Revealed their intraspecies diversity and potential roles in abiotic stress tolerance. Front. Genet. 2022, 13, 1034921. [Google Scholar] [CrossRef] [PubMed]
  7. Zhao, J.; Peng, S.; Cui, H.; Li, P.; Li, T.; Liu, L.; Zhang, H.; Tian, Z.; Shang, H.; Xu, R. Dynamic Expression, Differential Regulation and Functional Diversity of the CNGC Family Genes in Cotton. Int. J. Mol. Sci. 2022, 23, 2041. [Google Scholar] [CrossRef]
  8. Demidchik, V.; Shabala, S.; Isayenkov, S.; Cuin, T.A.; Pottosin, I. Calcium transport across plant membranes: Mechanisms and functions. New Phytol. 2018, 220, 49–69. [Google Scholar] [CrossRef] [Green Version]
  9. Gobert, A.; Park, G.; Amtmann, A.; Sanders, D.; Maathuis, F.J. Arabidopsis thaliana cyclic nucleotide gated channel 3 forms a non-selective ion transporter involved in germination and cation transport. J. Exp. Bot. 2006, 57, 791–800. [Google Scholar] [CrossRef]
  10. Gu, L.L.; Gao, Q.F.; Wang, Y.F. Cyclic nucleotide-gated channel 18 functions as an essential Ca2+ channel for pollen germination and pollen tube growth in Arabidopsis. Plant Signal. Behav. 2017, 12, e1197999. [Google Scholar] [CrossRef]
  11. Ma, W.; Smigel, A.; Walker, R.K.; Moeder, W.; Yoshioka, K.; Berkowitz, G.A. Leaf senescence signaling: The Ca2+-conducting Arabidopsis cyclic nucleotide gated channel2 acts through nitric oxide to repress senescence programming. Plant Physiol. 2010, 154, 733–743. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Shih, H.W.; DePew, C.L.; Miller, N.D.; Monshausen, G.B. The Cyclic Nucleotide-Gated Channel CNGC14 Regulates Root Gravitropism in Arabidopsis thaliana. Curr. Biol. 2015, 25, 3119–3125. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Tan, Y.Q.; Yang, Y.; Zhang, A.; Fei, C.F.; Gu, L.L.; Sun, S.J.; Xu, W.; Wang, L.; Liu, H.; Wang, Y.F. Three CNGC Family Members, CNGC5, CNGC6, and CNGC9, Are Required for Constitutive Growth of Arabidopsis Root Hairs as Ca2+-Permeable Channels. Plant Commun. 2019, 1, 100001. [Google Scholar] [CrossRef] [PubMed]
  14. Tunc-Ozdemir, M.; Rato, C.; Brown, E.; Rogers, S.; Mooneyham, A.; Frietsch, S.; Myers, C.T.; Poulsen, L.R.; Malhó, R.; Harper, J.F. Cyclic nucleotide gated channels 7 and 8 are essential for male reproductive fertility. PLoS ONE 2013, 8, e55277. [Google Scholar] [CrossRef] [Green Version]
  15. Tunc-Ozdemir, M.; Tang, C.; Ishka, M.R.; Brown, E.; Groves, N.R.; Myers, C.T.; Rato, C.; Poulsen, L.R.; McDowell, S.; Miller, G.; et al. A cyclic nucleotide-gated channel (CNGC16) in pollen is critical for stress tolerance in pollen reproductive development. Plant Physiol. 2013, 161, 1010–1020. [Google Scholar] [CrossRef] [Green Version]
  16. Chin, K.; DeFalco, T.A.; Moeder, W.; Yoshioka, K. The Arabidopsis cyclic nucleotide-gated ion channels AtCNGC2 and AtCNGC4 work in the same signaling pathway to regulate pathogen defense and floral transition. Plant Physiol. 2013, 163, 611–624. [Google Scholar] [CrossRef] [Green Version]
  17. Guo, K.M.; Babourina, O.; Christopher, D.A.; Borsics, T.; Rengel, Z. The cyclic nucleotide-gated channel, AtCNGC10, influences salt tolerance in Arabidopsis. Physiol. Plant. 2008, 134, 499–507. [Google Scholar] [CrossRef]
  18. Niu, W.T.; Han, X.W.; Wei, S.S.; Shang, Z.L.; Wang, J.; Yang, D.W.; Fan, X.; Gao, F.; Zheng, S.Z.; Bai, J.T.; et al. Arabidopsis cyclic nucleotide-gated channel 6 is negatively modulated by multiple calmodulin isoforms during heat shock. J. Exp. Bot. 2020, 71, 90–104. [Google Scholar] [CrossRef]
  19. Oranab, S.; Ghaffar, A.; Kiran, S.; Yameen, M.; Munir, B.; Zulfiqar, S.; Abbas, S.; Batool, F.; Farooq, M.U.; Ahmad, B.; et al. Molecular characterization and expression of cyclic nucleotide gated ion channels 19 and 20 in Arabidopsis thaliana for their potential role in salt stress. Saudi J. Biol. Sci. 2021, 28, 5800–5807. [Google Scholar] [CrossRef]
  20. Sunkar, R.; Kaplan, B.; Bouché, N.; Arazi, T.; Dolev, D.; Talke, I.N.; Maathuis, F.J.; Sanders, D.; Bouchez, D.; Fromm, H. Expression of a truncated tobacco NtCBP4 channel in transgenic plants and disruption of the homologous Arabidopsis CNGC1 gene confer Pb2+ tolerance. Plant J. 2000, 24, 533–542. [Google Scholar] [CrossRef]
  21. Yoshioka, K.; Moeder, W.; Kang, H.G.; Kachroo, P.; Masmoudi, K.; Berkowitz, G.; Klessig, D.F. The chimeric Arabidopsis CYCLIC NUCLEOTIDE-GATED ION CHANNEL11/12 activates multiple pathogen resistance responses. Plant Cell 2006, 18, 747–763. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Upadhyay, S.K. Calcium Channels, OST1 and Stomatal Defence: Current Status and Beyond. Cells 2023, 12, 127. [Google Scholar] [CrossRef] [PubMed]
  23. Tharanathan, R.N.; Yashoda, H.M.; Prabha, T.N. Mango (Mangifera indica L.), “the king of fruits”—An overview. Food Rev. Int. 2006, 22, 29. [Google Scholar] [CrossRef]
  24. Wang, P.; Luo, Y.; Huang, J.; Gao, S.; Zhu, G.; Dang, Z.; Gai, J.; Yang, M.; Zhu, M.; Zhang, H.; et al. The genome evolution and domestication of tropical fruit mango. Genome Biol. 2020, 21, 60. [Google Scholar] [CrossRef] [Green Version]
  25. Sherman, A.; Rubinstein, M.; Eshed, R.; Benita, M.; Ish-Shalom, M.; Sharabi-Schwager, M.; Rozen, A.; Saada, D.; Cohen, Y.; Ophir, R. Mango (Mangifera indica L.) germplasm diversity based on single nucleotide polymorphisms derived from the transcriptome. BMC Plant Biol. 2015, 15, 277. [Google Scholar] [CrossRef] [Green Version]
  26. Sun, C.; Lin, W.; Huang, C.; Wu, L.; Chen, J.; Wang, J.; Lin, H. GIS-based Risk Zoning and Assessment of Mongo Cold and Freezing Injury in South China. Chin. J. Agrometeorol. 2022, 43, 563–575. [Google Scholar]
  27. Lesk, C.; Rowhani, P.; Ramankutty, N. Influence of extreme weather disasters on global crop production. Nature 2016, 529, 84–87. [Google Scholar] [CrossRef] [Green Version]
  28. Sanches, A.G.; Da Silva, M.B.; Fernandes, T.F.S.; Pedrosa, V.M.D.; Wong, M.C.C.; Gratão, P.L.; Teixeira, G.H.A. Reducing chilling injury in ‘Palmer’ mangoes submitted to quarantine cold treatment. J. Sci. Food Agric. 2022, 102, 6112–6122. [Google Scholar] [CrossRef]
  29. Cui, Y.; Lu, S.; Li, Z.; Cheng, J.; Hu, P.; Zhu, T.; Wang, X.; Jin, M.; Wang, X.; Li, L.; et al. CYCLIC NUCLEOTIDE-GATED ION CHANNELs 14 and 16 Promote Tolerance to Heat and Chilling in Rice. Plant Physiol. 2020, 183, 1794–1808. [Google Scholar] [CrossRef]
  30. Amborella Genome Project. The Amborella genome and the evolution of flowering plants. Science 2013, 342, 1241089. [Google Scholar] [CrossRef]
  31. Xu, Q.; Chen, L.L.; Ruan, X.; Chen, D.; Zhu, A.; Chen, C.; Bertrand, D.; Jiao, W.B.; Hao, B.H.; Lyon, M.P.; et al. The draft genome of sweet orange (Citrus sinensis). Nat. Genet. 2013, 45, 59–66. [Google Scholar] [CrossRef] [PubMed]
  32. Li, W.; Liu, W.; Wei, H.; He, Q.; Chen, J.; Zhang, B.; Zhu, S. Species-specific expansion and molecular evolution of the 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR) gene family in plants. PLoS ONE 2014, 9, e94172. [Google Scholar] [CrossRef] [PubMed]
  33. Hunter, N. Meiotic Recombination: The Essence of Heredity. Cold Spring Harb. Perspect. Biol. 2015, 7, a016618. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Guo, X.; Liu, D.; Chong, K. Cold signaling in plants: Insights into mechanisms and regulation. J. Integr. Plant Biol. 2018, 60, 745–756. [Google Scholar] [CrossRef] [Green Version]
  35. Altschul, S.F.; Gish, W.; Miller, W.; Myers, E.W.; Lipman, D.J. Basic local alignment search tool. J. Mol. Biol. 1990, 215, 403–410. [Google Scholar] [CrossRef]
  36. Chen, C.; Chen, H.; Zhang, Y.; Thomas, H.R.; Frank, M.H.; He, Y.; Xia, R. TBtools—An Integrative Toolkit Developed for Interactive Analyses of Big Biological Data. Mol. Plant 2020, 13, 1194–1202. [Google Scholar] [CrossRef] [PubMed]
  37. ProtParam Tool. Available online: web.expasy.org/protparam/ (accessed on 7 November 2022).
  38. Yu, C.S.; Chen, Y.C.; Lu, C.H.; Hwang, J.K. Prediction of protein subcellular localization. Proteins 2006, 64, 643–651. [Google Scholar] [CrossRef] [PubMed]
  39. Krogh, A.; Larsson, B.; Von Heijne, G.; Sonnhammer, E.L. Predicting transmembrane protein topology with a hidden Markov model: Application to complete genomes. J. Mol. Biol. 2001, 305, 567–580. [Google Scholar] [CrossRef] [Green Version]
  40. Kumar, S.; Stecher, G.; Tamura, K. MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets. Mol. Biol. Evol. 2016, 33, 1870–1874. [Google Scholar] [CrossRef] [Green Version]
  41. DNAMAN—Bioinformatics Solutions. Available online: www.lynnon.com (accessed on 7 November 2022).
  42. Sequence Read Archive. Available online: www.ncbi.nlm.nih.gov/sra (accessed on 7 November 2022).
  43. Sivankalyani, V.; Sela, N.; Feygenberg, O.; Zemach, H.; Maurer, D.; Alkan, N. Transcriptome Dynamics in Mango Fruit Peel Reveals Mechanisms of Chilling Stress. Front. Plant Sci. 2016, 7, 1579. [Google Scholar] [CrossRef] [Green Version]
  44. Li, B.; Dewey, C.N. RSEM: Accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinform. 2011, 12, 323. [Google Scholar] [CrossRef] [PubMed]
  45. Sharma, H.; Sharma, A.; Rajput, R.; Sidhu, S.; Dhillon, H.; Verma, P.C.; Pandey, A.; Upadhyay, S.K. Molecular Characterization, Evolutionary Analysis, and Expression Profiling of BOR Genes in Important Cereals. Plants 2022, 11, 911. [Google Scholar] [CrossRef] [PubMed]
  46. Morpheus. Available online: software.broadinstitute.org/morpheus/ (accessed on 7 November 2022).
  47. Zolfaghari, F.; Khosravi, H.; Shahriyari, A.; Jabbari, M.; Abolhasani, A. Hierarchical cluster analysis to identify the homogeneous desertification management units. PLoS ONE 2019, 14, e0226355. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  48. Huang, X.; Xiao, M.; Xi, J.; He, C.; Zheng, J.; Chen, H.; Gao, J.; Zhang, S.; Wu, W.; Liang, Y.; et al. De novo transcriptome assembly of Agave H11648 by Illumina sequencing and identification of cellulose synthase genes in Agave species. Genes 2019, 10, 103. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  49. Liu, F.; Wu, J.B.; Zhan, R.L.; Ou, X.C. Transcription Profiling Analysis of Mango-Fusarium mangiferae Interaction. Front. Microbiol. 2016, 7, 1443. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  50. Huang, X.; Wang, B.; Xi, J.; Zhang, Y.; He, C.; Zheng, J.; Gao, J.; Chen, H.; Zhang, S.; Wu, W.; et al. Transcriptome comparison reveals distinct selection patterns in domesticated and wild Agave species, the important CAM plants. Int. J. Genom. 2018, 2018, 5716518. [Google Scholar] [CrossRef] [Green Version]
  51. Livak, K.J.; Schmittgen, T.D. Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔC(T) Method. Methods 2001, 25, 402–408. [Google Scholar] [CrossRef]
  52. Sun, G.; Geng, S.; Zhang, H.; Jia, M.; Wang, Z.; Deng, Z.; Tao, S.; Liao, R.; Wang, F.; Kong, X.; et al. Matrilineal empowers wheat pollen with haploid induction potency by triggering postmitosis reactive oxygen species activity. New Phytol. 2022, 233, 2405–2414. [Google Scholar] [CrossRef]
Plants 12 00592 g001 550
Figure 1. Chromosome distribution of CNGC genes in mango (blue) and sweet orange (light blue). The chromosome numbers are marked with numbers beside the chromosomes. Homologous gene pairs between the two species are linked with lines. The ‘un’ represents unanchored scaffolds.
Figure 1. Chromosome distribution of CNGC genes in mango (blue) and sweet orange (light blue). The chromosome numbers are marked with numbers beside the chromosomes. Homologous gene pairs between the two species are linked with lines. The ‘un’ represents unanchored scaffolds.
Plants 12 00592 g001
Plants 12 00592 g002 550
Figure 2. Maximum-likelihood phylogenetic tree of CNGC proteins in Arabidopsis thaliana (red), Amborella trichopoda (pink), Oryza sativa (green), Mangifera indica (blue) and Citrus sinensis (light blue).
Figure 2. Maximum-likelihood phylogenetic tree of CNGC proteins in Arabidopsis thaliana (red), Amborella trichopoda (pink), Oryza sativa (green), Mangifera indica (blue) and Citrus sinensis (light blue).
Plants 12 00592 g002
Plants 12 00592 g003 550
Figure 3. In silico expression of mango CNGC genes in different tissues, including leaf (L), fruit peel (P) and fruit flesh (F).
Figure 3. In silico expression of mango CNGC genes in different tissues, including leaf (L), fruit peel (P) and fruit flesh (F).
Plants 12 00592 g003
Plants 12 00592 g004 550
Figure 4. In silico expression of CNGC genes under cold stress of (blue) and 12 °C (red) in mango fruit peel. The x-axis represents the samples collected at 0, 2, 7 and 14 days after treatment. The y-axis represents FPKM values. The error bar represents the standard error. * represents that the expression level was up or downregulated over 3-fold.
Figure 4. In silico expression of CNGC genes under cold stress of (blue) and 12 °C (red) in mango fruit peel. The x-axis represents the samples collected at 0, 2, 7 and 14 days after treatment. The y-axis represents FPKM values. The error bar represents the standard error. * represents that the expression level was up or downregulated over 3-fold.
Plants 12 00592 g004
Plants 12 00592 g005 550
Figure 5. The expression of CNGC genes under cold stress of 2 (red), 4 (blue), 6 (green) and 8 °C (purple) in mango leaf according to qRT-PCR. The x-axis represents the samples collected at 0, 1, 2 and 4 h after incubation (hai) at different temperatures. The y-axis represents the values of 2−ΔΔCt. The error bar represents the standard error.
Figure 5. The expression of CNGC genes under cold stress of 2 (red), 4 (blue), 6 (green) and 8 °C (purple) in mango leaf according to qRT-PCR. The x-axis represents the samples collected at 0, 1, 2 and 4 h after incubation (hai) at different temperatures. The y-axis represents the values of 2−ΔΔCt. The error bar represents the standard error.
Plants 12 00592 g005
Plants 12 00592 g006 550
Figure 6. The MDA contents under cold stress of 2 (red), 4 (blue), 6 (green) and 8 °C (purple) in mango leaf (A) and their correlations with the relative expression levels of CNGC genes (B). * and ** represent that the correlation coefficients are significant at 0.05 (R > 0.532) and 0.01 (R > 0.661) levels, respectively.
Figure 6. The MDA contents under cold stress of 2 (red), 4 (blue), 6 (green) and 8 °C (purple) in mango leaf (A) and their correlations with the relative expression levels of CNGC genes (B). * and ** represent that the correlation coefficients are significant at 0.05 (R > 0.532) and 0.01 (R > 0.661) levels, respectively.
Plants 12 00592 g006
Table
Table 1. Characterization of mango CNGC genes, including their accession numbers, chromosome positions, the lengths of coding sequences and predicted proteins, pI and subcellular locations.
Table 1. Characterization of mango CNGC genes, including their accession numbers, chromosome positions, the lengths of coding sequences and predicted proteins, pI and subcellular locations.
Gene IDAccession NumberChromosome PositionCoding Sequence (bp)Predicted Protein (aa)Molecular Weight (Da)Theoretical pISubcellular Localization
MiCNGC1LOC123217317Chr1: 26617757–26622513 (+)208869580,238.878.59Plasma Membrane (4.159)
MiCNGC2LOC123202006Chr2: 18877379–18881267 (−)211570480,732.559.33Plasma Membrane (4.168)
MiCNGC3LOC123211819Chr3: 6181866–6187338 (+)229876588,428.889.17Plasma Membrane (3.621)
MiCNGC4LOC123223438Chr8: 1942929–1947032 (+)215171682,987.459.38Plasma Membrane (3.546)
MiCNGC5LOC123224898Chr9: 570085–574702 (−)173457767,095.529.67Plasma Membrane (3.860)
MiCNGC6LOC123225620Chr9: 590058–593780 (−)120340046,407.249.12Plasma Membrane (2.575)
MiCNGC7LOC123225300Chr9: 599306–603542 (+)199866577,653.89.42Plasma Membrane (3.398)
MiCNGC8LOC123225621Chr9: 608291–611565 (+)137745853,035.699.52Plasma Membrane (2.835)
MiCNGC9LOC123225476Chr9: 613450–633947 (−)182160669,498.225.61Plasma Membrane (3.921)
MiCNGC10LOC123225622Chr9: 613655–614273 (+)51617119,510.664.88Nuclear (2.027)
MiCNGC11LOC123225623Chr9: 640657–644088 (−)126041948,200.045.71Plasma Membrane (2.541)
MiCNGC12LOC123226204Chr9: 654424–660087 (−)173157666,396.968.51Plasma Membrane (3.243)
MiCNGC13LOC123225899Chr9: 662666–667252 (−)213070981,778.719.18Plasma Membrane (4.474)
MiCNGC14LOC123224819Chr9: 17603913–17607726 (−)215171682,061.849.54Plasma Membrane (4.714)
MiCNGC15LOC123226709Chr10: 13110947–13113872 (+)102334038,771.019.24Plasma Membrane (2.866)
MiCNGC16LOC123193626Chr12: 337616–340675 (−)163554461,685.378.3Plasma Membrane (3.945)
MiCNGC17LOC123195239Chr13: 132576–141356 (+)220873583,845.529.06Plasma Membrane (4.347)
MiCNGC18LOC123195166Chr13: 2244118–2249930 (+)219373084,150.348.66Plasma Membrane (4.075)
MiCNGC19LOC123196387Chr14: 571224–582588 (−)234378089,883.319.05Plasma Membrane (4.810)
MiCNGC20LOC123196103Chr14: 2913165–2916467 (+)214871582,156.578.92Plasma Membrane (4.612)
MiCNGC21LOC123198417Chr15: 882187–884231 (+)72924228,545.329.19Nuclear (1.618)
MiCNGC22LOC123198080Chr15: 884570–888789 (+)171657166,348.136.17Plasma Membrane (3.842)
MiCNGC23LOC123198017Chr15: 894806–897058 (+)126642148,693.955.97Plasma Membrane (4.227)
MiCNGC24LOC123197882Chr15: 899688–903479 (+)180960270,104.718.73Plasma Membrane (4.512)
MiCNGC25LOC123198019Chr15: 937711–939887 (−)74424728,653.798.06Nuclear (1.582)
MiCNGC26LOC123198301Chr15: 944971–947978 (−)156352059,757.678.86Plasma Membrane (3.850)
MiCNGC27LOC123197889Chr15: 957259–959253 (−)70823527,110.79.57Extracellular (1.327)
MiCNGC28LOC123197890Chr15: 968337–969069 (−)39913214,907.278.37Extracellular (1.999)
MiCNGC29LOC123197893Chr15: 998581–1002107 (−)152450758,308.018.81Plasma Membrane (4.361)
MiCNGC30LOC123197894Chr15: 1002388–1013277 (−)192664174,391.258.83Plasma Membrane (4.326)
MiCNGC31LOC123198006Chr15: 1014910–1019679 (−)213070981,816.519.13Plasma Membrane (4.548)
MiCNGC32LOC123197621Chr15: 13323057–13327587 (−)202867577,023.979.41Plasma Membrane (4.667)
MiCNGC33LOC123199977Chr17: 659050–663360 (−)216372083,381.028.99Plasma Membrane (4.360)
MiCNGC34LOC123200530Chr17: 10040631–10047558 (+)217872583,488.059.09Plasma Membrane (4.053)
MiCNGC35LOC123201033Chr17: 11813705–11815638 (−)69623126,664.049.05Nuclear (1.519)
MiCNGC36LOC123200218Chr17: 11846751–11849774 (−)69022926,194.338.47Nuclear (1.544)
MiCNGC37LOC123200982Chr17: 12162919–12170581 (+)213671181,639.439.03Plasma Membrane (4.349)
MiCNGC38LOC123201393Chr18: 10879862–10886175 (+)206168679,312.979.09Plasma Membrane (4.272)
MiCNGC39LOC123204873Chr20: 2710625–2713311 (+)205268379,142.169Plasma Membrane (4.212)
MiCNGC40LOC123206450NW_025401129.1: 250730–254202 (−)222974285,358.839.37Plasma Membrane (3.988)
MiCNGC41LOC123206532NW_025401132.1: 147597–150404 (+)205268379,185.189.05Plasma Membrane (4.213)
MiCNGC42LOC123206927NW_025401145.1: 36673–40482 (+)215171682,061.849.54Plasma Membrane (4.714)
MiCNGC43LOC123208231NW_025401260.1: 224–2797 (−)117639144,867.269.23Plasma Membrane (3.815)
Table
Table 2. Primers used for qRT-PCR analysis.
Table 2. Primers used for qRT-PCR analysis.
GenesForward PrimerReverse PrimerProduct Size (bp)Accession Number
MiCNGC4TTTACTGCTTCTGGTGGGGTAGGGAGCAAACGATGAGACA236XM_044646600.1
MiCNGC9TCAGCTTCCTCGTTGACCTTCTTCCCGCTTCCAACATCAG226XM_044649431.1
MiCNGC13TCGGGCTTCAGGATTCTTGTCCCAGTCCACCTCTTCATGT196XM_044650230.1
MiCNGC17CTTCAAACGAGCACCTTCCCTCCTCGTGTTTCCAACCACT246XM_044608894.1
MiCNGC19ACTTGGGAATGTCAGGAGCACCAACAACATGACCAGCCAA193XM_044610397.1
MiCNGC22TCACATGGGCTCTAGATGGCAAACAGAGTCATCCGGCAGA175XM_044612662.1
MiCNGC31GACTTGGGCAGCTTGTTTCATGAATCCTTGCCTTCCGAGT216XM_044612575.1
MiCNGC34CGCCGTTTTGACCAGTACAAAGCATCTCGGTTACAGGGTC248XM_044615727.1
MiCNGC36GCAAGACAGAGCAGTGGATGTCCTCTAATGCCGATTCGCT232XM_044615370.1
MiCNGC38ATTCTCCCTCTCCCTCAGGTTGTGCCGAAAATGTAGCCAG183XM_044616876.1
MiActinCCACTGCTGAACGGGAAATGTGATGGCTGGAAGAGGAC192HQ585999.1
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Zhang, Y.; Li, Y.; Yang, J.; Yang, X.; Chen, S.; Xie, Z.; Zhang, M.; Huang, Y.; Zhang, J.; Huang, X. Genome-Wide Analysis and Expression of Cyclic Nucleotide–Gated Ion Channel (CNGC) Family Genes under Cold Stress in Mango (Mangifera indica). Plants 2023, 12, 592. https://doi.org/10.3390/plants12030592

AMA Style

Zhang Y, Li Y, Yang J, Yang X, Chen S, Xie Z, Zhang M, Huang Y, Zhang J, Huang X. Genome-Wide Analysis and Expression of Cyclic Nucleotide–Gated Ion Channel (CNGC) Family Genes under Cold Stress in Mango (Mangifera indica). Plants. 2023; 12(3):592. https://doi.org/10.3390/plants12030592

Chicago/Turabian Style

Zhang, Yajie, Yubo Li, Jing Yang, Xinli Yang, Shengbei Chen, Zhouli Xie, Mingjie Zhang, Yanlei Huang, Jinghong Zhang, and Xing Huang. 2023. "Genome-Wide Analysis and Expression of Cyclic Nucleotide–Gated Ion Channel (CNGC) Family Genes under Cold Stress in Mango (Mangifera indica)" Plants 12, no. 3: 592. https://doi.org/10.3390/plants12030592

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop