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Article

Comprehensive Analysis of Calcium Sensor Families, CBL and CIPK, in Aeluropus littoralis and Their Expression Profile in Response to Salinity

by
Mozhdeh Arab
1,2,
Hamid Najafi Zarrini
1,
Ghorbanali Nematzadeh
1,3,
Parviz Heidari
4,*,
Seyyed Hamidreza Hashemipetroudi
3,5,* and
Markus Kuhlmann
5
1
Department of Plant Biotechnology, Sari Agricultural Sciences and Natural Resources University (SANRU), Sari 4818166996, Iran
2
National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran 14965161, Iran
3
Department of Genetic Engineering and Biology, Genetics and Agricultural Biotechnology Institute of Tabarestan (GABIT), Sari Agricultural Sciences and Natural Resources University (SANRU), Sari 4818166996, Iran
4
Faculty of Agriculture, Shahrood University of Technology, Shahrood 3619995161, Iran
5
RG Heterosis, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 306466 Gatersleben, Germany
*
Authors to whom correspondence should be addressed.
Genes 2023, 14(3), 753; https://doi.org/10.3390/genes14030753
Submission received: 22 February 2023 / Revised: 11 March 2023 / Accepted: 16 March 2023 / Published: 20 March 2023
(This article belongs to the Section Plant Genetics and Genomics)
Browse Figures
Versions Notes

Abstract

:
Plants have acquired sets of highly regulated and complex signaling pathways to respond to unfavorable environmental conditions during evolution. Calcium signaling, as a vital mechanism, enables plants to respond to external stimuli, including abiotic and biotic stresses, and coordinate the basic processes of growth and development. In the present study, two calcium sensor families, CBL and CIPK, were investigated in a halophyte plant, Aeluropus littoralis, with a comprehensive analysis. Here, six AlCBL genes, and twenty AlCIPK genes were studied. The analysis of the gene structure and conserved motifs, as well as physicochemical properties, showed that these genes are highly conserved during evolution. The expression levels of AlCBL genes and AlCIPK genes were evaluated under salt stress in leaf and root tissue. Based on the real-time RT-PCR results, the AlCIPK gene family had a higher variation in mRNA abundance than the AlCBL gene family. AlCIPK genes were found to have a higher abundance in leaves than in roots. The results suggest that the correlation between AlCBL genes and AlCIPK is tissue-specific, and different correlations can be expected in leaves and roots. Based on these correlations, AlCIPK3.1–AlCBL4.1 and AlCIPK1.2–AlCBL4.4 can be co-expressed in the root tissue, while AlCBL10 has the potential to be co-expressed with AlCIPK5, AlCIPK26, and AlCIPK12.3 in the leaf tissue. Our findings reveal valuable information on the structure and function of calcium sensor families in A. littoralis, a halophyte plant, that can be used in future research on the biological function of CBLs and CIPKs on salt stress resistance.

1. Introduction

In sessile organisms such as plants, perception and signaling of environmental stimuli are necessary for survival and growth regulation. Calcium (Ca2+) is one of the signal transduction components that acts as a second messenger in all eukaryotes [1,2,3]. Ca2+ is stored in organelles such as vacuoles, mitochondria, and endoplasmic reticulum, where abiotic stresses such as salt, cold, and drought cause a rapid increase in Ca2+ concentration in the cytosol [3,4,5,6]. However, biotic stresses, pH dynamics, and phytohormones also can affect Ca2+ concentration [7,8,9,10]. In addition, pollen tube development and guard cell regulation are also associated with changes in Ca2+ concentration [8]. Calcium sensors or calcium-binding proteins recognize the modification in Ca2+ concentrations in plant cells, and downstream pathways are induced by affecting the phosphorylation status of calcium sensors and activating protein kinases [11,12]. Calmodulin (CaM), calcium-dependent protein kinases (CDPKs), and calcineurin B-like proteins (CBLs) are part of the known calcium sensors in plants [13]. CBLs are plant-specific sensors that, after sensing a specific calcium signature, can physically interact with a group of protein kinases, CBL-interacting protein kinases (CIPKs), to activate downstream signaling components [14,15,16]. CBL proteins share a common helix–loop–helix structural motif (the EF-hand composition), which acts as a Ca2+-binding region [17]. Moreover, it seems that the EF-hand composition could affect the affinity rate of calcium ions [17].
In the plant model system Arabidopsis, diverse roles were reported for CBLs: The cbl1 mutant is very sensitive to abiotic stresses such as drought, extreme salinity, and hyperosmotic stress. Likewise, the CBL9 gene is involved in ABA signal transduction and stress-induced ABA biosynthesis pathways [18]. In addition, it was reported that CBL9 and CBL1 participate in pollen germination and flower fertilization [19]. Furthermore, it was stated that CBL1 is involved in response to aluminum stress [20] and cold stress [21,22]. Moreover, CBL7 is associated with Arabidopsis responses to alkaline stress [23]. Interestingly, it was reported that CBLs, such as CBL3 and CBL4, could modulate the potassium channel and affect potassium homeostasis [21,24]. It has also been found that the expression patterns of the CBL genes are dependent on tissues and developmental stages and the type of stress. For example, CBL1 expression is not affected by the external application of abscisic acid (ABA) but is induced in response to environmental stresses such as salt, cold, drought, and wounding [25]. While CBL2 and CBL3 do not respond to abiotic stress stimuli, they are transcriptionally induced by light stress [26]. CIPK genes also have differential expression patterns. For example, CIPK9 transcriptional regulation is more induced in response to ABA treatment and is mainly activated in shoot tissues [27]. In addition, CIPK genes in Medicago truncatula, including MtCIPK2, MtCIPK17, and MtCIPK18, were found to be upregulated in response to salinity, PEG, and ABA treatments [28]. Recently, it has been reported that a CIPK gene from chrysanthemum, CmCIPK8, could affect the expression patterns of ion transport-related genes and may enhance tolerance to salinity [29]. Moreover, CIPK10 in potatoes (StCIPK10) could increase tolerance to osmotic and drought stress by affecting the content of osmoregulation substances [30]. Additionally, it was reported that StCIPK10 can interact with several StCBLs, including StCBL4, StCBL8, StCBL1, StCBL6, StCBL12, and StCBL11 [30]. In β vulgaris, it was described that BvCIPKs are upregulated in response to NaCl treatment [31]. In Saccharum spontaneum, CIPK genes were shown to respond to abiotic stresses such as cold and water stress and ABA treatment [32]. Overall, it seems that cell signaling networks linked with CBL–CIPK play critical roles in response to abiotic stresses [33,34,35].
A. littoralis as a halophyte model can grow under high salt concentrations [36,37]. Identifying the genes related to tolerance in plants such as A. littoralis, a valuable germplasm, and determining their function can provide a better understanding of tolerance mechanisms in plants [38]. According to the mentioned materials above, the genes of CBL and CIPK families play a key role in responding to environmental stresses and regulating downstream signaling pathways, but these gene families have not been identified and investigated in A. littoralis. Here, we identified the members of CBL and CIPK families and analyzed their structure and evolution as well as their regulatory systems. In addition, the expression profiles of AlCBL and AlCIPK genes were evaluated under salinity in the root and leaf tissues of A. littoralis.

2. Materials and Methods

2.1. Identification of CBL and CIPK Family Genes in A. littoralis

In this study, the putative protein sequences of CBL and CIPK in rice were retrieved from the RGAP database (http://rice.plantbiology.msu.edu/, accessed on 25 December 2022) and for Arabidopsis thaliana from the TAIR database (https://www.arabidopsis.org/, accessed on 25 December 2022). Sequences were used as queries in blastp and tblastn tools, E-value < 1 × 10−10, to identify members of CBL and CIPK gene families from the transcriptome platform e!DAL of A. littoralis [39]. The presence of PKinase and NAF domains in CIPK proteins, as well as EF-hand domains in CBL proteins, was tested and confirmed using the CDD database [40], SMART [41], and InterPro Scan [42]. The confirmed protein sequences were renamed based on their orthologs in Arabidopsis. Further AlCBL and AlCIPK proteins were analyzed using the ExPASy online database ProtParam tool [43] to predict their physiochemical properties, including molecular weight (MW), GRAVY, and isoelectric point (pI).

2.2. Phylogenetic Analysis and Classification of AlCBL and AlCIPK Gene Families

To investigate the evolutionary relationships in calcium sensor gene families, the protein sequences of AlCBL and AlCIPK families, along with their orthologs in Arabidopsis and rice, were analyzed. First, the sequences were aligned using the ClustalW tool [44], and then a phylogenetic tree was drawn with the IQ tree software [45] using the maximum likelihood (ML) method with 1000 bootstrap replications. Finally, the tree file was restored and upgraded in the iTOL database [46].

2.3. Motif Analysis and Gene Structure of AlCBLs and AlCIPKs

Ten conserved motifs of AlCBL and AlCIPK protein sequences were predicted using the MEME motif finder [47] based on its default setting. In addition, the gene structure of AlCBL and AlCIPK genes was illustrated based on exon and intron distribution using TBtools [48].

2.4. Promoter Analysis of AlCBLs and AlCIPKs

In the current study, the upstream region, 1500 bp, of AlCBL and AlCIPK genes was analyzed using the PlantCARE tool (https://bioinformatics.psb.ugent.be/webtools/plantcare/html/, accessed on 25 December 2022) to identify the putative cis-regulatory elements.

2.5. Plant Materials’ Growth Conditions and Salt Treatments

The cultivation of A. littoralis seeds was carried out at a temperature of 25 ± 3 and a photoperiod of 16 h of light and 8 h of darkness. Then, the cloned samples were transferred to Hoagland’s solution, and after two months, salt stress treatment was started. In order to apply salinity stress, sodium chloride was gradually added; specifically, 100 mM salt was added to the solution every 3 days until the final concentration reached 600 mM. The sampling of leaf and root tissues was carried out in the time series of 0 (as a control sample), 3, 12, and 24 h after the application of salt stress. The collected samples were kept in a freezer at −80 for the next steps. All experiments were performed in three biological replications.

2.6. RNA Extraction and cDNA Synthesis

The extraction of total RNA from leaf and root tissues was carried out using a Trizol Kit (Threezol, Riragene). To remove genomic DNA from RNA, DNase I treatment (DNase I RNase-free, Thermo Scientific, Waltham, MA, USA) was applied. Finally, cDNA was synthesized using a RevertAid First-Strand cDNA Synthesis Kit (Thermo Scientific, Waltham, MA, USA) based on the company’s instructions and diluted four times.

2.7. Real-Time PCR

In the present study, the levels of mRNA abundance from six AlCBL and twelve AlCIPK genes were investigated in two tissues, roots and leaves, under salinity and normal conditions. Genes were selected based on phylogenetic analysis. The primers of candidate genes were designed using AlleleID [49] (Tables S1 and S2). The Maxima SYBR Green/ROX qPCR Master Mix (Thermo Scientific) was used to evaluate the relative expression based on the manufacturer’s instructions, with a Bio-Rad CFX96 machine. The temperature cycle was performed in two stages according to the manufacturer’s instructions: 10 min activation stage at 95 °C, 40 cycles at 95 °C for 15 s, and 60 °C for 1 min. In the current study, three reference genes, namely AlUBQ, AlRPS3, and AlRPS3, were used for each tissue. The geometric mean of these genes was used to normalize the data. Finally, the relative expression levels of each target gene were calculated using the 2−ΔΔCT method [50].

3. Results

3.1. Physicochemical Properties of AlCBLs and AlCIPKs

In the present study, six AlCBL genes and twenty AlCIPK genes were identified in the genome of A. littoralis. The evaluation of the physicochemical characteristics of CBL proteins revealed variable molecular weight in the range of 18.70 (AlCBL4.4) to 34.67 kDa (AlCBL10), and all AlCBLs were predicted as acidophilic proteins, pI less than 5.5 (Table 1). Furthermore, all AlCBLs (except for AlCBL10 protein) had negative GRAVY values, revealing that most AlCBLs have hydrophilic properties. In general, in terms of physicochemical characteristics, the AlCBL10 protein was different from other members of the AlCBL gene family, which can be more considered in molecular functional research. According to the genes’ physicochemical characteristics, AlCIPK family members showed more diversity than AlCBLs. Molecular weight in AlCIPKs ranged from 42.04 (AlCIPK10.6) to 58.97 kDa (AlCIPK10.1), and pI varied from 6.21 (AlCIPK21) to 9.28 (AlCIPK10.2).

3.2. Phylogenetic Analysis of AlCBLs

AlCBL proteins, along with their orthologs in rice and Arabidopsis, were subjected to phylogenetic analysis. The results disclosed that CBL proteins could be classified into four main groups (Figure 1). None of the AlCBLs could be identified in group I. AlLAC4.1, AlLAC4.2, AlLAC4.3, and AlLAC4.4 were located in group II, AlLAC10 in group III, and AlLAC2 in group IV. In addition, AlCBLs and rice CBLs showed more similarity to each other than Arabidopsis CBLs. Overall, our results revealed that the diversity in the CBL family occurred after the splitting of monocots and dicots.

3.3. Phylogenetic Analysis of AlCIPKs

To determine the evolutionary origin of AlCIPKs, the phylogenetic tree of AlCIPKs with their orthologs in Arabidopsis (26 CIPK proteins) and rice (33 CIPK proteins) was drawn based on protein sequences (Figure 2). The results revealed that CIPKs could be separated into four main groups. The highest number of CIPKs was found in group III, and the lowest number was observed in group IV. Similar to AlCBLs, AlCIPKs also showed a close relationship with rice CIPKs. In addition, it can be concluded that the expansion of the CIPK family probably occurred after the derivation of monocots and dicots.

3.4. Gene Structure and Conserved Motifs of AlCBLs

AlCBLs with their orthologs in rice (OsCBLs) were analyzed based on their conserved motifs and domain and gene structure (Figure 3). Ten conserved motifs were recognized in AlCBLs and OsCBLs; of those, motifs 6 and 9 were not detected in CBLs from group II, and motif 9 was only observed in OsCBLs from group III (Figure 3a). The calcium-binding superfamily, namely EF-hand 7, EF-hand 5, and EF-hand 1 domains, were observed in AlCBLs and OsCBLs, although they differed based on the location and number of domains (Figure 3b). In addition, two copies of EF-hand 7 and EF-hand 1 domains were found in AlCBL10 and its ortholog, OsCBL9, suggesting that AlCBL10 probably has more potential to interact with the downstream elements of involved pathways. In addition, AlCBLs were different based on their gene structure, and all AlCBLs had a high number of exons/introns (Figure 3c).

3.5. Gene Structure and Conserved Motifs of AlCIPKs

To identify conserved motifs and determine the position of these motifs in KINAS and NAF domains, AlCIPK proteins with their orthologs in rice (OsCIPKs) were analyzed using the MEME tool (Figure 4a). The results show that the spatial distribution of the motifs in the investigated proteins is strongly conserved. All ten identified motifs were observed in AlCIPK3.1, AlCIPK3.2, AlCIPK10.1, AlCIPK10.2, AlCIPK10.4, AlCIPK20, AlCIPK23, and AlCIPK26 proteins, while motif 10 was not detectable in AlCIPK1.1, AlCIPK12.1, AlCIPK12.2, and AlCIPK12.3. Motif 5 was not detected in AlCIPK4, motif 4 was not detected in AlCIPK5, motif 1 was not observed in AlCIPK10.3, and motif 2 was not observed in AlCIPK10.5. In the AlCIPK1.2 protein, motifs 10 and 3, in the AlCIPK11 protein, motifs 10 and 6, in the AlCIPK10.6 protein, motifs 3 and 8, and in the AlCIPK21 protein, motifs 10 and 4 were not present. These results indicate that the main (conserved) motifs play an important role in the function of CIPK proteins. Moreover, two KINAS and NAF domains were identified in AlCIPKs and OsCIPKs (Figure 4b); all the studied proteins showed one copy of the KINAS and NAF domains. Based on gene structure analysis, 60% of AlCIPK genes have 1 exon and no intron, about 20% of genes have 14 exons and 13 introns, about 10% of genes have 2 exons and 1 intron, about 5% of genes have 13 exons and 12 introns, and about 5% of genes have 12 exons and 11 introns (Figure 4c).

3.6. Promoter Analysis

In the present study, the upstream of AlCIPKs and AlCBLs was screened to identify the cis-regulatory elements related to stress, hormone, and growth and development (Figure 5). The most recognized elements were related to common cis-regulatory and elements with unknown functions (Figure 5a). In addition, putative cis-regulatory elements related to transcription factors’ binding site, response to phytohormones, and stresses were observed in the upstream sites of AlCIPKs and AlCBLs. The cis-regulatory elements involved in response to ABA hormone were frequently identified in the promoter sites of AlCIPKs and AlCBLs (Figure 5b). Moreover, the putative cis-regulatory elements related to GA, auxin, SA, and MeJA hormones were recognized in the upstream sites of AlCIPKs, while in AlCBLs, regulatory elements responding to GA and MeJA hormones were observed. The cis-regulatory elements involved in responsive to abiotic stresses, including low temperature, MBS, DRE, and STRE, and biotic stresses, including wound, elicitor, and defense mechanisms, were identified in the promoter regions of AlCBLs and ALCIPKs (Figure 5c). In addition, the binding sites of several TFs such as MYB, MYS, and WRKY were observed in the upstream sites of AlCIPKs and AlCBLs (Figure 5d). In general, AlCIPKs were richer than AlCBLs based on the number of stress-related cis-elements.

3.7. Expression Profiles of AlCBL Genes in Response to Salinity

The expression levels of AlCBL genes were investigated under salinity in root and leaf tissues. According to our results, AlCBL2 was not expressed under the tested conditions. It seems that AlCBL2 is not probably induced in response to salinity stress. After 3 h of salinity treatment, AlCBL4.1, AlCBL4.2, and AlCBL4.4 showed an upregulation in root tissues (Figure 6). Three AlCBL genes, namely AlCBL4.3, AlCBL4.4, and AlCBL10, were differentially induced after 24 h; all three genes were upregulated in the leaf, while they were downregulated in the root.

3.8. Expression Profile of AlCIPK Genes in Response to Salinity

In the root tissue, the expression levels of AlCIPK1.2 (1.96 times), AlCIPK3.1 (4.90 times), AlCIPK5 (2.32 times), AlCIPK11 (4.21 times), AlCIPK12.1 (2.62 times), and AlCIPK26 (4.63 times) were increased after three hours (h) of applying salt stress (Figure 7). In the leaf tissue, at 3 h after applying salt stress, AlCIPK11 (4.10 times), AlCIPK1.2 (2.89 times), AlCIPK4 (1.82 times), AlCIPK12.3 (1.77 times), AlCIPK5 (1.69 times), AlCIPK10.2 (−2.50 times), and AlCIPK10.6 (−1.91 times) were more induced. In the root tissue, after 12 h of salinity, the AlCIPK10.2 gene (−4.46 times) just showed a sharp downregulation, while in the leaf tissues, AlCIPK4 (3.43 times), AlCIPK10.2 (−6.39 times), AlCIPK11 (3.72 times), AlCIPK1.2 (2.00 times), AlCIPK3.1 (−1.82 times), AlCIPK5 (2.13 times), AlCIPK10.6 (−1.34 times), AlCIPK12.1 (1.58 times), AlCIPK26 (2.00 times), and AlCIPK12.3 (2.61 times) showed a significant modification in their expression levels after 12 hr. Interestingly, AlCIPK10.2 was notably downregulated in both root and leaf tissues. In addition, the expression levels of AlCIPK4 (3.47 times) and AlCIPK12.3 (3.78 times) were increased in leaf tissue after 24 h. In total, CIPKs were more expressed in the leaf tissue, while AlCIPK12.3 was expressed only in the leaf tissue, and AlCIPK1.1 gene expression was observed only in the root tissue. AlCIPK4, AlCIPK5, AlCIPK10.2, AlCIPK10.6, AlCIPK11, and AlCIPK12.3 genes were significantly expressed in the leaf tissue at all times of stress.

4. Discussion

Calcium sensors such as calcineurin B-like proteins (CBLs) and CBL-interacting protein kinases (CIPKs) not only participate in the processes of plant growth and development but are also involved in stress responses [30]. In the present study, the available genome of A. littoralis was used as a reference [38] and screened for the respective gene families. Six AlCBL genes and twenty AlCIPK genes were identified. Due to the importance of calcium-dependent signaling pathways, CBL and CIPK gene families have been studied in various plants. Notably, 23 CBLs and 58 CIPK genes were identified from the genome of Medicago sativa [28], 27 CIPK genes from potato [30], 9 CBLs and 30 CIPK genes from the pecan genome [51], 10 CBLs and 26 CIPKs from Arabidopsis [17], 7 CBLs and 20 CIPK genes from bread wheat [52], 7 CBLs and 23 CIPK genes from canola [53], 16 CBLs and 41 CIPK genes from quinoa [35], and 20 CIPK genes from sugar beet [31]. The different number of members of this gene family suggests that they may have been subjected to evolutionary pressures differently in each plant [54,55]. Based on their physicochemical properties, AlCBL proteins have similar properties, except for the AlCBL10 protein. The proteins of the AlCIPK family showed more diversity. This result supports the hypothesis that AlCIPKs are highly diverse due to their involvement in different pathways [56,57]. While AlCIPKs showed a high variation in terms of gene structure, AlCIPKs could be separated into two groups. This grouping was based on their low intron number (less than three introns) and high intron number (more than ten introns). Moreover, this feature has also been reported in previous studies, where CIPKs have been classified into two groups based on their intron structure [35,58]. It was stated that partial duplication has probably affected the intron number of gene family members [59]. Moreover, it was reported that the expression levels of genes can be affected by intron number, and genes with low intron number could be faster induced [60]. According to phylogenetic analysis, both AlCBL and AlCIPK families are closely related to their rice orthologs. This finding suggests that the diversity in these gene families occurred after the derivation of monocots and dicots species [61,62].
Halophyte plants have a high potential to grow in substrates with high salinity. Therefore, these species are of great interest to investigate the mechanisms of tolerance to salinity. Such mechanisms include the absorption, transport, and homeostasis of ions, osmotic regulation, and salt removal from leaves [37,38]. Although the cultivation of these plants is not an easy task, the germplasm of halophyte plants is considered a valuable source for providing genes resistant to environmental conditions, for the implementation of plant-breeding programs [63]. In the current study, the expression profiles of AlCBLs and AlCIPKs were investigated under salt stresses in the roots and leaves of A. littoralis. AlCBLs and AlCIPKs showed tissue-specific expression patterns. For instance, AlCIPK mRNAs were more in leaves than in roots, while AlCBL4.3, AlCBL4.4, and AlCBL10 showed upregulation in roots and downregulation in shoots. This pattern might be related to the presence of as-1-specific motifs in the promoter region of AlCBL genes. Each of the AlCBL4.3, AlCBL4.1, and AlCBL2 genes had two as-1 motifs, while six as-1 motifs were observed in AlCBL4.2, three as-1 motifs were observed in AlCBL4.4, and one as-1 motif was observed in AlCBL10 promoter region.
The results revealed that the co-expression pattern of AlCBL with AlCIPK was tissue-specific, and different co-expressions were observed in two tissues of leaves and roots. Based on the expression pattern, AlCIPK3.1–AlCBL4.1 and AlCIPK1.2–AlCBL4.4 genes can be potentially co-expressed in the root tissue, while in the leaf tissue, the AlCBL10 gene can correlate with AlCIPK5, AlCIPK12.3 and AlCIPK26 genes. A positive correlation was reported between CBLs and CIPKs in response to stresses, such as salinity [64], drought [65], and disease [58]. In Arabidopsis, the interaction between CBL4 (called SOS3) and CIPK24 (called SOS2) could active the kinases and +/H+ antiporters called SOS1 and vacuolar H+-ATPase to increase stress tolerance [53,66,67]. Subsequent research in Arabidopsis showed that the AtCBL10 gene also interacts with AtCIPK24. Thus, the CBL10–CIPK24 complex interacts with vacuoles to protect the shoot from damage caused by salt stress [67]. This result suggests that calcium sensors may exhibit very different functions despite high sequence similarity or close evolutionary relationships.

5. Conclusions

This review is the first comprehensive study of the family of calcium sensors with the aim of clarifying the evolution, expression patterns, and possible functions of the genes of this superfamily in A. littoralis in response to salinity stress. These findings provide information to predict the function of calcium sensor genes in plant tolerance to salinity stress. Additional studies on the expression of AlCBL and AlCIPK family genes under different abiotic stresses in future research can be useful in understanding the mechanism of gene expression adjustments related to the SOS pathway. The AlCIPK genes reported in this research, while providing preliminary information, provide a basis for identifying the functions and mechanisms of the stress response, especially the responses related to the CBL/CIPK pathway in the A. littoralis plant.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/genes14030753/s1, Table S1: List of primers of AlCBL genes used in qPCR analysis; Table S2: List of primers of AlCIPK genes used in qPCR analysis.

Author Contributions

Conceptualization, M.A., S.H.H., H.N.Z. and G.N.; methodology, M.A., S.H.H. and P.H.; software, M.A. and S.H.H.; validation, S.H.H., H.N.Z. and G.N.; formal analysis, S.H.H.; investigation, P.H. and M.K.; writing—original draft preparation, P.H.; writing—review and editing, P.H. and M.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by Genetics and Agricultural Biotechnology Institute of Tabarestan (GABIT), Sari Agricultural Sciences and Natural Resources University (SANRU) (Grant number: GABIT-98/D/PI271). Open access publishing was partially funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, grant 491250510).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Dodd, A.N.; Kudla, J.; Sanders, D. The language of calcium signaling. Annu. Rev. Plant Biol. 2010, 61, 593–620. [Google Scholar] [CrossRef] [PubMed]
  2. Tang, R.-J.; Luan, S. Regulation of calcium and magnesium homeostasis in plants: From transporters to signaling network. Curr. Opin. Plant Biol. 2017, 39, 97–105. [Google Scholar] [CrossRef] [PubMed]
  3. Aslam, M.; Fakher, B.; Jakada, B.H.; Zhao, L.; Cao, S.; Cheng, Y.; Qin, Y. Genome-Wide Identification and Expression Profiling of CBL-CIPK Gene Family in Pineapple (Ananas comosus) and the Role of Ac CBL1 in Abiotic and Biotic Stress Response. Biomolecules 2019, 9, 293. [Google Scholar] [CrossRef] [Green Version]
  4. Costa, A.; Navazio, L.; Szabo, I. The contribution of organelles to plant intracellular calcium signalling. J. Exp. Bot. 2018, 69, 4175–4193. [Google Scholar] [CrossRef] [Green Version]
  5. Kudla, J.; Becker, D.; Grill, E.; Hedrich, R.; Hippler, M.; Kummer, U.; Parniske, M.; Romeis, T.; Schumacher, K. Advances and current challenges in calcium signaling. New Phytol. 2018, 218, 414–431. [Google Scholar] [CrossRef]
  6. Ding, Y.; Shi, Y.; Yang, S. Advances and challenges in uncovering cold tolerance regulatory mechanisms in plants. New Phytol. 2019, 222, 1690–1704. [Google Scholar] [CrossRef] [Green Version]
  7. Behera, S.; Xu, Z.; Luoni, L.; Bonza, M.C.; Doccula, F.G.; De Michelis, M.I.; Morris, R.J.; Schwarzländer, M.; Costa, A. Cellular Ca2+ signals generate defined pH signatures in plants. Plant Cell 2018, 30, 2704–2719. [Google Scholar] [CrossRef] [Green Version]
  8. Michard, E.; Simon, A.A.; Tavares, B.; Wudick, M.M.; Feijó, J.A. Signaling with ions: The keystone for apical cell growth and morphogenesis in pollen tubes. Plant Physiol. 2017, 173, 91–111. [Google Scholar] [CrossRef] [Green Version]
  9. De Vriese, K.; Himschoot, E.; Dünser, K.; Nguyen, L.; Drozdzecki, A.; Costa, A.; Nowack, M.K.; Kleine-Vehn, J.; Audenaert, D.; Beeckman, T. Identification of novel inhibitors of auxin-induced Ca2+ signaling via a plant-based chemical screen. Plant Physiol. 2019, 180, 480–496. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  10. Meena, M.K.; Prajapati, R.; Krishna, D.; Divakaran, K.; Pandey, Y.; Reichelt, M.; Mathew, M.K.; Boland, W.; Mithöfer, A.; Vadassery, J. The Ca2+ channel CNGC19 regulates Arabidopsis defense against Spodoptera herbivory. Plant Cell 2019, 31, 1539–1562. [Google Scholar] [CrossRef] [PubMed]
  11. Gill, S.S.; Tuteja, N. Reactive oxygen species and antioxidant machinery in abiotic stress tolerance in crop plants. Plant Physiol. Biochem. 2010, 48, 909–930. [Google Scholar] [CrossRef]
  12. Bender, K.W.; Zielinski, R.E.; Huber, S.C. Revisiting paradigms of Ca2+ signaling protein kinase regulation in plants. Biochem. J. 2018, 475, 207–223. [Google Scholar] [CrossRef]
  13. Ranty, B.; Aldon, D.; Cotelle, V.; Galaud, J.-P.; Thuleau, P.; Mazars, C. Calcium sensors as key hubs in plant responses to biotic and abiotic stresses. Front. Plant Sci. 2016, 7, 327. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Zhang, Y.; Lv, Y.; Jahan, N.; Chen, G.; Ren, D.; Guo, L. Sensing of abiotic stress and ionic stress responses in plants. Int. J. Mol. Sci. 2018, 19, 3298. [Google Scholar] [CrossRef] [Green Version]
  15. Batistic, O.; Kudla, J. Integration and channeling of calcium signaling through the CBL calcium sensor/CIPK protein kinase network. Planta 2004, 219, 915–924. [Google Scholar] [CrossRef]
  16. Halfter, U.; Ishitani, M.; Zhu, J.-K. The Arabidopsis SOS2 protein kinase physically interacts with and is activated by the calcium-binding protein SOS3. Proc. Natl. Acad. Sci. USA 2000, 97, 3735–3740. [Google Scholar] [CrossRef]
  17. Kolukisaoglu, U.; Weinl, S.; Blazevic, D.; Batistic, O.; Kudla, J. Calcium sensors and their interacting protein kinases: Genomics of the Arabidopsis and rice CBL-CIPK signaling networks. Plant Physiol. 2004, 134, 43–58. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  18. Pandey, G.K.; Cheong, Y.H.; Kim, K.-N.; Grant, J.J.; Li, L.; Hung, W.; D’Angelo, C.; Weinl, S.; Kudla, J.; Luan, S. The calcium sensor calcineurin B-like 9 modulates abscisic acid sensitivity and biosynthesis in Arabidopsis. Plant Cell 2004, 16, 1912–1924. [Google Scholar] [CrossRef] [Green Version]
  19. Mähs, A.; Steinhorst, L.; Han, J.-P.; Shen, L.-K.; Wang, Y.; Kudla, J. The calcineurin B-like Ca2+ sensors CBL1 and CBL9 function in pollen germination and pollen tube growth in Arabidopsis. Mol. Plant 2013, 6, 1149–1162. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  20. Ligaba-Osena, A.; Fei, Z.; Liu, J.; Xu, Y.; Shaff, J.; Lee, S.; Luan, S.; Kudla, J.; Kochian, L.; Piñeros, M. Loss-of-function mutation of the calcium sensor CBL 1 increases aluminum sensitivity in Arabidopsis. New Phytol. 2017, 214, 830–841. [Google Scholar] [CrossRef] [Green Version]
  21. Liu, L.-L.; Ren, H.-M.; Chen, L.-Q.; Wang, Y.; Wu, W.-H. A protein kinase, calcineurin B-like protein-interacting protein Kinase9, interacts with calcium sensor calcineurin B-like Protein3 and regulates potassium homeostasis under low-potassium stress in Arabidopsis. Plant Physiol. 2013, 161, 266–277. [Google Scholar] [CrossRef] [Green Version]
  22. Huang, C.; Ding, S.; Zhang, H.; Du, H.; An, L. CIPK7 is involved in cold response by interacting with CBL1 in Arabidopsis thaliana. Plant Sci. 2011, 181, 57–64. [Google Scholar] [CrossRef]
  23. Yang, Y.; Wu, Y.; Ma, L.; Yang, Z.; Dong, Q.; Li, Q.; Ni, X.; Kudla, J.; Song, C.P.; Guo, Y. The Ca2+ sensor SCaBP3/CBL7 fine tunes Arabidopsis alkali tolerance and modulats plasma membrane H+-ATPase activity. Plant Cell 2019, 31, 1367–1384. [Google Scholar] [CrossRef]
  24. Held, K.; Pascaud, F.; Eckert, C.; Gajdanowicz, P.; Hashimoto, K.; Corratgé-Faillie, C.; Offenborn, J.N.; Lacombe, B.; Dreyer, I.; Thibaud, J.-B. Calcium-dependent modulation and plasma membrane targeting of the AKT2 potassium channel by the CBL4/CIPK6 calcium sensor/protein kinase complex. Cell Res. 2011, 21, 1116–1130. [Google Scholar] [CrossRef] [Green Version]
  25. Albrecht, V.; Weinl, S.; Blazevic, D.; D’Angelo, C.; Batistic, O.; Kolukisaoglu, Ü.; Bock, R.; Schulz, B.; Harter, K.; Kudla, J. The calcium sensor CBL1 integrates plant responses to abiotic stresses. Plant J. 2003, 36, 457–470. [Google Scholar] [CrossRef]
  26. Nozawa, A.; Koizumi, N.; Sano, H. An Arabidopsis SNF1-related protein kinase, AtSR1, interacts with a calcium-binding protein, AtCBL2, of which transcripts respond to light. Plant Cell Physiol. 2001, 42, 976–981. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  27. Gong, D.; Guo, Y.; Jagendorf, A.T.; Zhu, J.-K. Biochemical characterization of the Arabidopsis protein kinase SOS2 that functions in salt tolerance. Plant Physiol. 2002, 130, 256–264. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  28. Du, W.; Yang, J.; Ma, L.; Su, Q.; Pang, Y. Identification and characterization of abiotic stress responsive CBL-CIPK family genes in Medicago. Int. J. Mol. Sci. 2021, 22, 4634. [Google Scholar] [CrossRef]
  29. Ding, X.; Liu, B.; Liu, H.; Sun, X.; Sun, X.; Wang, W.; Zheng, C. A new CIPK gene CmCIPK8 enhances salt tolerance in transgenic Chrysanthemum. Sci. Hortic. 2023, 308, 111562. [Google Scholar] [CrossRef]
  30. Ma, R.; Liu, W.; Li, S.; Zhu, X.; Yang, J.; Zhang, N.; Si, H. Genome-Wide Identification, Characterization and Expression Analysis of the CIPK Gene Family in Potato (Solanum tuberosum L.) and the Role of StCIPK10 in Response to Drought and Osmotic Stress. Int. J. Mol. Sci. 2021, 22, 13535. [Google Scholar] [CrossRef]
  31. Wu, G.-Q.; Xie, L.-L.; Wang, J.-L.; Wang, B.-C.; Li, Z.-Q. Genome-Wide Identification of CIPK Genes in Sugar Beet (Beta vulgaris) and Their Expression Under NaCl Stress. J. Plant Growth Regul. 2023, 42, 260–274. [Google Scholar] [CrossRef]
  32. Su, W.; Ren, Y.; Wang, D.; Huang, L.; Fu, X.; Ling, H.; Su, Y.; Huang, N.; Tang, H.; Xu, L. New insights into the evolution and functional divergence of the CIPK gene family in Saccharum. BMC Genom. 2020, 21, 868. [Google Scholar] [CrossRef]
  33. Xiao, C.; Zhang, H.; Xie, F.; Pan, Z.-Y.; Qiu, W.-M.; Tong, Z.; Wang, Z.-Q.; He, X.-J.; Xu, Y.-H.; Sun, Z.-H. Evolution, gene expression, and protein—protein interaction analyses identify candidate CBL-CIPK signalling networks implicated in stress responses to cold and bacterial infection in citrus. BMC Plant Biol. 2022, 22, 420. [Google Scholar] [CrossRef] [PubMed]
  34. Mao, J.; Mo, Z.; Yuan, G.; Xiang, H.; Visser, R.G.F.; Bai, Y.; Liu, H.; Wang, Q.; van der Linden, C.G. The CBL-CIPK network is involved in the physiological crosstalk between plant growth and stress adaptation. Plant. Cell Environ. 2022. Early view. [Google Scholar] [CrossRef]
  35. Xiaolin, Z.; Baoqiang, W.; Xian, W.; Xiaohong, W. Identification of the CIPK-CBL family gene and functional characterization of CqCIPK14 gene under drought stress in quinoa. BMC Genom. 2022, 23, 447. [Google Scholar] [CrossRef]
  36. Saad, R.B.; Romdhan, W.B.; Zouari, N.; Azaza, J.; Mieulet, D.; Verdeil, J.-L.; Guiderdoni, E.; Hassairi, A. Promoter of the AlSAP gene from the halophyte grass Aeluropus littoralis directs developmental-regulated, stress-inducible, and organ-specific gene expression in transgenic tobacco. Transgenic Res. 2011, 20, 1003–1018. [Google Scholar] [CrossRef]
  37. Hashemi, S.H.; Nematzadeh, G.; Ahmadian, G.; Yamchi, A.; Kuhlmann, M. Identification and validation of Aeluropus littoralis reference genes for Quantitative Real-Time PCR Normalization. J. Biol. Res. 2016, 23, 18. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  38. Hashemi-Petroudi, S.H.; Arab, M.; Dolatabadi, B.; Kuo, Y.-T.; Baez, M.A.; Himmelbach, A.; Nematzadeh, G.; Maibody, S.A.M.M.; Schmutzer, T.; Mälzer, M. Initial Description of the Genome of Aeluropus littoralis, a Halophile Grass. Front. Plant Sci. 2022, 13, 906462. [Google Scholar] [CrossRef]
  39. Arend, D.; Lange, M.; Chen, J.; Colmsee, C.; Flemming, S.; Hecht, D.; Scholz, U. e!DAL-a framework to store, share and publish research data. BMC Bioinform. 2014, 15, 214. [Google Scholar] [CrossRef] [Green Version]
  40. Marchler-Bauer, A.; Derbyshire, M.K.; Gonzales, N.R.; Lu, S.; Chitsaz, F.; Geer, L.Y.; Geer, R.C.; He, J.; Gwadz, M.; Hurwitz, D.I. CDD: NCBI’s conserved domain database. Nucleic Acids Res. 2015, 43, D222–D226. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  41. Schultz, J.; Copley, R.R.; Doerks, T.; Ponting, C.P.; Bork, P. SMART: A web-based tool for the study of genetically mobile domains. Nucleic Acids Res. 2000, 28, 231–234. [Google Scholar] [CrossRef]
  42. Quevillon, E.; Silventoinen, V.; Pillai, S.; Harte, N.; Mulder, N.; Apweiler, R.; Lopez, R. InterProScan: Protein domains identifier. Nucleic Acids Res. 2005, 33, W116–W120. [Google Scholar] [CrossRef] [Green Version]
  43. Gasteiger, E.; Gattiker, A.; Hoogland, C.; Ivanyi, I.; Appel, R.D.; Bairoch, A. ExPASy: The proteomics server for in-depth protein knowledge and analysis. Nucleic Acids Res. 2003, 31, 3784–3788. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Sievers, F.; Wilm, A.; Dineen, D.; Gibson, T.J.; Karplus, K.; Li, W.; Lopez, R.; McWilliam, H.; Remmert, M.; Söding, J.; et al. Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol. Syst. Biol. 2011, 7, 539. [Google Scholar] [CrossRef] [PubMed]
  45. Nguyen, L.-T.; Schmidt, H.A.; von Haeseler, A.; Minh, B.Q. IQ-TREE: A fast and effective stochastic algorithm for estimating Maximum-likelihood phylogenies. Mol. Biol. Evol. 2015, 32, 268–274. [Google Scholar] [CrossRef] [PubMed]
  46. Letunic, I.; Bork, P. Interactive Tree of Life (iTOL) v4: Recent updates and new developments. Nucleic Acids Res. 2019, 47, W256–W259. [Google Scholar] [CrossRef] [Green Version]
  47. Bailey, T.L.; Boden, M.; Buske, F.A.; Frith, M.; Grant, C.E.; Clementi, L.; Ren, J.; Li, W.W.; Noble, W.S. MEME SUITE: Tools for motif discovery and searching. Nucleic Acids Res. 2009, 37, W202–W208. [Google Scholar] [CrossRef] [PubMed]
  48. 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]
  49. Apte, A.; Singh, S. AlleleID. Methods Mol. Biol. 2007, 402, 329–345. [Google Scholar]
  50. Livak, K.J.; Schmittgen, T.D. Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCT method. Methods 2001, 25, 402–408. [Google Scholar] [CrossRef]
  51. Zhu, K.; Fan, P.; Liu, H.; Tan, P.; Ma, W.; Mo, Z.; Zhao, J.; Chu, G.; Peng, F. Insight into the CBL and CIPK gene families in pecan (Carya illinoinensis): Identification, evolution and expression patterns in drought response. BMC Plant Biol. 2022, 22, 221. [Google Scholar] [CrossRef] [PubMed]
  52. Sun, T.; Wang, Y.; Wang, M.; Li, T.; Zhou, Y.; Wang, X.; Wei, S.; He, G.; Yang, G. Identification and comprehensive analyses of the CBL and CIPK gene families in wheat (Triticum aestivum L.). BMC Plant Biol. 2015, 15, 269. [Google Scholar] [CrossRef] [Green Version]
  53. Zhang, H.; Yang, B.; Liu, W.-Z.; Li, H.; Wang, L.; Wang, B.; Deng, M.; Liang, W.; Deyholos, M.K.; Jiang, Y.-Q. Identification and characterization of CBL and CIPK gene families in canola (Brassica napus L.). BMC Plant Biol. 2014, 14, 8. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  54. Ahmadizadeh, M.; Rezaee, S.; Heidari, P. Genome-wide characterization and expression analysis of fatty acid desaturase gene family in Camelina sativa. Gene Rep. 2020, 21, 100894. [Google Scholar] [CrossRef]
  55. Faraji, S.; Filiz, E.; Kazemitabar, S.K.; Vannozzi, A.; Palumbo, F.; Barcaccia, G.; Heidari, P. The AP2/ERF Gene Family in Triticum durum: Genome-Wide Identification and Expression Analysis under Drought and Salinity Stresses. Genes 2020, 11, 1464. [Google Scholar] [CrossRef]
  56. Puresmaeli, F.; Heidari, P.; Lawson, S. Insights into the Sulfate Transporter Gene Family and Its Expression Patterns in Durum Wheat Seedlings under Salinity. Genes 2023, 14, 333. [Google Scholar] [CrossRef]
  57. Yaghobi, M.; Heidari, P. Genome-Wide Analysis of Aquaporin Gene Family in Triticum turgidum and Its Expression Profile in Response to Salt Stress. Genes 2023, 14, 202. [Google Scholar] [CrossRef]
  58. Zhao, J.; Yu, A.; Du, Y.; Wang, G.; Li, Y.; Zhao, G.; Wang, X.; Zhang, W.; Cheng, K.; Liu, X. Foxtail millet (Setaria italica (L.) P. Beauv) CIPKs are responsive to ABA and abiotic stresses. PLoS ONE 2019, 14, e0225091. [Google Scholar] [CrossRef] [PubMed]
  59. Nuruzzaman, M.; Manimekalai, R.; Sharoni, A.M.; Satoh, K.; Kondoh, H.; Ooka, H.; Kikuchi, S. Genome-wide analysis of NAC transcription factor family in rice. Gene 2010, 465, 30–44. [Google Scholar] [CrossRef] [PubMed]
  60. Heidari, P.; Puresmaeli, F.; Mora-Poblete, F. Genome-Wide Identification and Molecular Evolution of the Magnesium Transporter (MGT) Gene Family in Citrullus lanatus and Cucumis sativus. Agronomy 2022, 12, 2253. [Google Scholar] [CrossRef]
  61. Heidari, P.; Abdullah; Faraji, S.; Poczai, P. Magnesium transporter Gene Family: Genome-Wide Identification and Characterization in Theobroma cacao, Corchorus capsularis and Gossypium hirsutum of Family Malvaceae. Agronomy 2021, 11, 1651. [Google Scholar] [CrossRef]
  62. Faraji, S.; Ahmadizadeh, M.; Heidari, P. Genome-wide comparative analysis of Mg transporter gene family between Triticum turgidum and Camelina sativa. BioMetals 2021, 34, 639–660. [Google Scholar] [CrossRef]
  63. Jaradat, A.A. Genetic resources of energy crops: Biological systems to combat climate change. Aust. J. Crop Sci. 2010, 4, 309–323. [Google Scholar]
  64. Li, J.; Jiang, M.; Ren, L.; Liu, Y.; Chen, H. Identification and characterization of CBL and CIPK gene families in eggplant (Solanum melongena L.). Mol. Genet. Genom. 2016, 291, 1769–1781. [Google Scholar] [CrossRef] [PubMed]
  65. Shu, B.; Cai, D.; Zhang, F.; Zhang, D.J.; Liu, C.Y.; Wu, Q.S.; Luo, C. Identifying citrus CBL and CIPK gene families and their expressions in response to drought and arbuscular mycorrhizal fungi colonization. Biol. Plant. 2020, 64, 773–783. [Google Scholar] [CrossRef]
  66. Ma, X.; Li, Q.-H.; Yu, Y.-N.; Qiao, Y.-M.; Haq, S.U.; Gong, Z.-H. The CBL–CIPK pathway in plant response to stress signals. Int. J. Mol. Sci. 2020, 21, 5668. [Google Scholar] [CrossRef]
  67. Yang, Y.; Zhang, C.; Tang, R.-J.; Xu, H.-X.; Lan, W.-Z.; Zhao, F.; Luan, S. Calcineurin B-Like proteins CBL4 and CBL10 mediate two independent salt tolerance pathways in Arabidopsis. Int. J. Mol. Sci. 2019, 20, 2421. [Google Scholar] [CrossRef] [PubMed] [Green Version]
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Figure 1. Phylogeny tree of CBL family proteins in A. littoralis (AlCBL), Oryza sativa (started with LOC Os), and A. thalianas (started with AT). The phylogenetic tree was drawn using the maximum likelihood (ML) method with 1000 bootstrap replications.
Figure 1. Phylogeny tree of CBL family proteins in A. littoralis (AlCBL), Oryza sativa (started with LOC Os), and A. thalianas (started with AT). The phylogenetic tree was drawn using the maximum likelihood (ML) method with 1000 bootstrap replications.
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Figure 2. Phylogeny tree of CIPK family proteins in A. littoralis (AlCIPK), rice (started with LOC), and Arabidopsis (started with AT). The phylogenetic tree was drawn using the maximum likelihood (ML) method with 1000 bootstrap replications.
Figure 2. Phylogeny tree of CIPK family proteins in A. littoralis (AlCIPK), rice (started with LOC), and Arabidopsis (started with AT). The phylogenetic tree was drawn using the maximum likelihood (ML) method with 1000 bootstrap replications.
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Figure 3. Structure analysis of AlCBL gene family. Distribution of conserved motifs (a), functional domains (b), and exon/intron (c) in AlCBL and OsCBL family members.
Figure 3. Structure analysis of AlCBL gene family. Distribution of conserved motifs (a), functional domains (b), and exon/intron (c) in AlCBL and OsCBL family members.
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Figure 4. Structure analysis of AlCIPK gene family. Distribution of conserved motifs (a), functional domains (b), and exon/intron (c) in AlCIPK and OsCIPK family members.
Figure 4. Structure analysis of AlCIPK gene family. Distribution of conserved motifs (a), functional domains (b), and exon/intron (c) in AlCIPK and OsCIPK family members.
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Figure 5. Distribution of cis-regulatory elements in the upstream of AlCBLs and ALCIPKs. Grouping of cis-regulatory elements based on their functions (a). Distribution of cis-regulatory elements involved in response to phytohormones (b), stress (c), and TF binding site (d). In this study, the upstream 1500 bp of AlCBL and AlCIPK genes was analyzed using PlantCARE.
Figure 5. Distribution of cis-regulatory elements in the upstream of AlCBLs and ALCIPKs. Grouping of cis-regulatory elements based on their functions (a). Distribution of cis-regulatory elements involved in response to phytohormones (b), stress (c), and TF binding site (d). In this study, the upstream 1500 bp of AlCBL and AlCIPK genes was analyzed using PlantCARE.
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Figure 6. Expression patterns of AlCBL genes in response to salinity in two tissues: root and leaf. Expression levels are presented based on log2 fold change stress/normal condition.
Figure 6. Expression patterns of AlCBL genes in response to salinity in two tissues: root and leaf. Expression levels are presented based on log2 fold change stress/normal condition.
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Figure 7. Expression patterns of AlCIPK genes in response to salinity in two tissues root and leaf. Expression levels are presented based on log2 fold change stress/normal condition.
Figure 7. Expression patterns of AlCIPK genes in response to salinity in two tissues root and leaf. Expression levels are presented based on log2 fold change stress/normal condition.
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Table
Table 1. Physicochemical properties of identified AlCBL and AlCIPK encoded proteins from A. littoralis.
Table 1. Physicochemical properties of identified AlCBL and AlCIPK encoded proteins from A. littoralis.
FamilyGene IDGene NameLength (aa)Intron NumberMW (kDa)pIGRAVY
CBLAlg14121AlCBL2226725.874.98−0.219
Alg15558AlCBL4.1214724.354.71−0.196
Alg11525AlCBL4.2213724.334.94−0.259
Alg8494AlCBL4.3217724.885.19−0.299
Alg13204AlCBL4. 4166518.704.78−0.341
Alg5886AlCBL10303834.675.280.133
CIPKAlg4127AlCIPK1.14731253.486.520.372
Alg7902AlCIPK1.24541150.696.62−0.320
Alg7566AlCIPK3.14421350.767.64−0.460
Alg12052ALCIPK3.24481350.638.23−0.407
Alg15044AlCIPK4427046.348.59−0.115
Alg5583AlCIPK5450048.19-0.054
Alg12300AlCIPK10.1523058.979.030.401
Alg9524ALCIPK10.2438049.729.28−0.260
Alg4701AlCIPK10.3421047.989.030.400
Alg3308AlCIPK10.4478054.669.130.514
Alg13906AlCIPK10.5410145.998.93−0.307
ALg9805AlCIPK10.6383142.048.990.480
Alg2698AlCIPK11433047.408.95−0.151
Alg8115AlCIPK12.1516057.368.64−0.341
Alg10559AlCIPK12.2515057.478.06−0.374
Alg11449AlCIPK12.3490054.068.84−0.254
Alg11347AlCIPK20456051.649.08−0.422
Alg8711AlCIPK214301348.546.21−0.303
Alg1003AlCIPK234491350.519.16−0.371
Alg7179AllCIPK264481350.448.41−0.395
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Arab, M.; Najafi Zarrini, H.; Nematzadeh, G.; Heidari, P.; Hashemipetroudi, S.H.; Kuhlmann, M. Comprehensive Analysis of Calcium Sensor Families, CBL and CIPK, in Aeluropus littoralis and Their Expression Profile in Response to Salinity. Genes 2023, 14, 753. https://doi.org/10.3390/genes14030753

AMA Style

Arab M, Najafi Zarrini H, Nematzadeh G, Heidari P, Hashemipetroudi SH, Kuhlmann M. Comprehensive Analysis of Calcium Sensor Families, CBL and CIPK, in Aeluropus littoralis and Their Expression Profile in Response to Salinity. Genes. 2023; 14(3):753. https://doi.org/10.3390/genes14030753

Chicago/Turabian Style

Arab, Mozhdeh, Hamid Najafi Zarrini, Ghorbanali Nematzadeh, Parviz Heidari, Seyyed Hamidreza Hashemipetroudi, and Markus Kuhlmann. 2023. "Comprehensive Analysis of Calcium Sensor Families, CBL and CIPK, in Aeluropus littoralis and Their Expression Profile in Response to Salinity" Genes 14, no. 3: 753. https://doi.org/10.3390/genes14030753

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