Next Article in Journal
N-Chlorotaurine Solutions as Agents for Infusion Detoxification Therapy: Preclinical Studies
Previous Article in Journal
Efficient AAV9 Purification Using a Single-Step AAV9 Magnetic Affinity Beads Isolation
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJMS
Volume 25
Issue 15
10.3390/ijms25158343
ijms-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite 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

Characterization of GPX Gene Family in Pepper (Capsicum annuum L.) under Abiotic Stress and ABA Treatment

by
Zeyu Zhang
,
Jing Zhang
,
Cheng Wang
,
Youlin Chang
,
Kangning Han
,
Yanqiang Gao
and
Jianming Xie
*
College of Horticulture, Gansu Agricultural University, Lanzhou 730070, China
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2024, 25(15), 8343; https://doi.org/10.3390/ijms25158343 (registering DOI)
Submission received: 28 June 2024 / Revised: 27 July 2024 / Accepted: 27 July 2024 / Published: 30 July 2024
(This article belongs to the Section Molecular Plant Sciences)
Browse Figures
Review Reports Versions Notes

Abstract

:
Plant glutathione peroxidases (GPXs) are important enzymes for removing reactive oxygen species in plant cells and are closely related to the stress resistance of plants. This study identified the GPX gene family members of pepper (Capsicum annuum L.), “CM333”, at the whole-genome level to clarify their expression patterns and enzyme activity changes under abiotic stress and ABA treatment. The results showed that eight CaGPX genes were unevenly distributed across four chromosomes and one scaffold of the pepper genome, and their protein sequences had Cys residues typical of the plant GPX domains. The analysis of collinearity, phylogenetic tree, gene structure, and conserved motifs indicated that the CaGPX gene sequence is conserved, structurally similar, and more closely related to the sequence structure of Arabidopsis. Meanwhile, many cis elements involved in stress, hormones, development, and light response were found in the promoter region of the CaGPX gene. In addition, CaGPX1/4 and CaGPX6 were basically expressed in all tissues, and their expression levels were significantly upregulated under abiotic stress and ABA treatment. Subcellular localization showed that CaGPX1 and CaGPX4 are localized in chloroplasts. Additionally, the variations in glutathione peroxidase activity (GSH-Px) mostly agreed with the variations in gene expression. In summary, the CaGPXs gene may play an important role in the development of peppers and their response to abiotic stress and hormones.

1. Introduction

Glutathione peroxidase (GPX; EC 1.11.1.9) is not only an important member of the ascorbate–glutathione cycle (AsA-GSH) but also an important enzyme for clearing ROS in cells [1,2]. It belongs to the nonheme thiol peroxidase family [3], which can use glutathione (GSH) or thioredoxin reductase (TRX) as reducing agents to catalyze the reduction of hydrogen peroxide (H2O2), organic hydrogen peroxide oxides, and lipid peroxides into water or corresponding alcohols, thereby maintaining the balance of ROS in plants and protecting cells from the toxic effects of high concentrations of ROS [4,5]. People’s understanding of GPX and research on its functional mechanism started in animals; it was discovered in 1957 by extracting mammalian red blood cells for enzyme testing and H2O2 reaction [6]. Since GPX in mammals uses GSH as an electron donor to reduce peroxides such as H2O2, the name GPX was derived from this [7]. Studies of GPX in plants started late. Criqui et al. [8] identified the first plant-derived GPX in tobacco, isolated it, and then successively found GPX-homologous genes in different plants. In plants, GPX usually exists in the form of a monomer [9], and almost all eukaryotic genomes contain coding genes of the GPX family, exhibiting high sequence similarity in conserved motifs and domains [10]. Compared with mammalian GPXs, plant GPXs contain cysteine (Cys) in their active sites, and when a large number of peroxides accumulates in the plant, the three conserved Cys residues at the N-terminus are converted into sulphenic acid, which forms an intramolecular disulfide bond with the separated conserved Cys residues [11,12]. The disulfide bond is subsequently reduced by the thioredoxin (Trx) or glutathione (Grx) system; while plant GPXs are usually reduced by Trx [13], most mammalian GPXs contain selenocysteine instead of Cys residues in their catalytic active sites, which can be reduced by Grx and Trx [14].
In recent years, researchers have cloned GPX family genes from Arabidopsis, Oryza sativa, and other plants and verified that changes in GPX gene expression are crucial for plants to respond to biotic and abiotic stresses [15,16,17]. In Arabidopsis, a total of eight members of the AtGPX family were identified, among which both AtGPX2 and AtGPX6 were localized in the cytoplasm and cell membrane [18]. The sensitivity of AtGPX3 and AtGPX8 mutant plants to drought and osmotic stress was significantly higher than that of wild-type Arabidopsis plants [19], and the overexpression of the AtGPX5 gene in Arabidopsis leads to changes in plant growth and redox status under salt stress [20]. In rice, the OsGPX gene family has six members, and OsGPX1-4 is upregulated by H2O2 induction [21,22]. In addition, studies have shown that the knockout of OsGPX1 and OsGPX3 in rice may seriously interfere with rice growth and development [23]. The knockout of OsGPX5 increases the sensitivity of rice to salt stress and impairs seed germination and plant development [24]. Silencing OsGPX1 located in the mitochondria blocks photosynthesis and photorespiration in rice under salt stress [25]. A total of 13 GhGPX gene family members have been identified in Gossypium hirsutum, among which GhGPX1 was localized in chloroplasts, GhGPX3 and GhGPX5-8 were localized in the cytoplasm, and GhGPX13 was upregulated by the induction of high temperatures [26]. In sorghum, there were seven members of the SbGPX gene family, among which SbGPX2-5 was upregulated by drought stress and SbGPX6-7 was downregulated by drought stress [27]. In addition, the overexpression of the GPX gene can improve the tolerance of transgenic plants to abiotic stress, such as Rhodiola crenulata RcGPX5 overexpressed in Salvia miltiorrhiza, Pinus massoniana PmGPX6 overexpressed in Arabidopsis, and wheat TaGPX genes W69 and W106, which can enhance the ability of transgenic plants to remove ROS and improve the tolerance of plants to salt, alkali, and drought [28,29,30,31].
Pepper (Capsicum annuum L.) is an important cash crop, a vegetable spice crop, and a value-added processing product widely planted worldwide [32,33]. However, during the cultivation process, pepper is highly vulnerable to both biotic and abiotic stress, which can impede its growth and development, ultimately affecting both its yield and quality. GPX is an effective reactive oxygen species scavenger in plants and is crucial for plants’ resistance to stress. However, the GPX gene family has not been identified and reported in peppers. Therefore, we utilized bioinformatics methods to identify the GPX gene in peppers at the whole-genome level. In addition, we analyzed the physical and chemical properties, protein secondary/tertiary structures, chromosome localization, collinearity, phylogenetic relationship, gene structure, conserved motifs, cis elements, protein interaction network, GO enrichment, and subcellular localization of the identified GPX family members. Furthermore, we conducted expression profiling and enzyme activity change analysis to understand their response to abiotic stress (i.e., cold, drought, and salt) and ABA signaling.

2. Results

2.1. Identification and Basic Information about the CaGPX Gene Family

Using eight AtGPX protein sequences from Arabidopsis as a reference for BLASTP alignment, a total of eight putative GPX genes were identified in the entire genome of the pepper “CM334” and named CaGPX1-8 according to their position on the chromosome (Table 1). The peptide length encoded by CaGPXs is 169 (CaGPX1)-250 (CaGPX2) amino acids (Table 1). The theoretical molecular weight of the protein ranges from 18.81 to 26.54 kDa, and the calculated isoelectric point (PI) values range from 4.98 to 9.56. Only CaGPX6 (PI = 5.05) and CaGPX7 (PI = 4.98) are acidic proteins, while the others are alkaline proteins (Table 1). In addition, all protein instability indices encoded by CaGPX genes were less than 40, and the aliphatic index was greater than 90, indicating good protein stability (Table 1). Moreover, the hydropathicity of CaGPX proteins is less than one, indicating that they are all hydrophilic proteins (Table 1).

2.2. Prediction of Subcellular Localization and Protein Secondary and Tertiary Structure of the CaGPX Gene Family

The results of subcellular localization prediction (Table S1) showed that CaGPX proteins were located in the chloroplasts (CaGPX1, 4, 5, 7, 8), nucleus (CaGPX2), and cytoplasm (CaGPX3, 6), respectively. Secondary structure prediction (Table S1) showed that the CaGPX proteins were mainly composed of α-helices and random coils, which accounted for a large proportion of the protein structure with a small difference in proportion. This was followed by the extended strand structure, which accounted for between 22.35% and 29.6%, while the beta-turn structure accounted for no more than 12%. From the perspective of tertiary structure (Figure S1), CaGPX1 and CaGPX5-8 had a similar structure to AtGPX2, 3, 5, 7, and 8, while CaGPX2-4 had a similar structure to AtGPX1, 4, and 6. In general, the tertiary structure of GPX protein family members in pepper was similar and conserved, basically consistent with the predicted results of the secondary structure. However, the spatial polymerization angle of some proteins was different.

2.3. Predicted Properties of CaGPX Proteins

To analyze the characteristics of all eight CaGPX proteins, we compared the GPX amino acid sequences of peppers, Arabidopsis, and rice (Figure 1). The results showed that the GPXs of all three species contained three completely conserved Cys residues (marked with a red triangle in Figure 1) and three conserved structural domains that exist in most plants and mammals [34]: GPX domain I (GKVLLIVNVASXCG), GPX domain II (ILAFPCNQF), and domain III (WNFXKFL) (marked with black boxes in Figure 2). Furthermore, there were other conserved sequences in the three species, such as CT(R/I)FKE(Y/F)P(I/V)F, K(V/I)(D/E/R)(V/L)NG, P(L/I)Y(K/E/Q/N/V)FLK, and V(V/I//S)(E/D/Q)RY(P/S/A/G)(P/T)TSP (marked with red boxes in Figure 2). In addition to the known catalytic site Cys residues, three high-potential catalytic sites—Gln, Trp, and Asn—were also found (marked with a blue triangle in Figure 1).

2.4. Chromosome Distribution and Collinearity Analysis of the CaGPX Gene Family

TBtools (V 1.118) and MCScanX software (V 2.096) were used to visualize the chromosomal location information of CaGPX genes. As shown in Figure 2, the eight CaGPX genes were only localized on four chromosomes of pepper, including two on chromosome 1 (CaGPX1, 2), two on chromosome 6 (CaGPX3, 4), one on chromosome 9 (CaGPX5), and two on chromosome 12 (CaGPX4, 5). Notably, CaGPX8 is not anchored to the chromosome but is in the scaffold. Additionally, CaGPX6 and CaGPX7 belong to a pair of tandem repeat genes (represented by blue lines in the figure). However, no fragment replication gene pairs were found in the eight GPX genes of pepper. Collinearity analysis (Figure 3) found that the GPX gene between pepper and Arabidopsis had high homology. There were four pairs of collinear gene pairs between three CaGPX genes and four AtGPX genes, among which CaGPX1 and AtGPX6/8 had collinear relationships, respectively; CaGPX3 and AtGPX3 had a collinear relationship; and CaGPX5 and AtGPX5 had collinear relationships.
The nonsynonymous substitution to synonymous substitution (Ka/Ks) ratio is an important indicator for evaluating gene replication events and selection pressure [35]. Therefore, we used KaKs_Calculator 2.0 software to calculate the Ka/Ks values of these three pairs of collinear genes (Table S2) and found that the ratio of Ka/Ks was less than 1.0, indicating that they mainly evolved under the influence of purification selection, with repeated events occurring 230.2 (CaGPX1/AtGPX8), 196.0 (CaGPX1/AtGPX6), 131.69 (CaGPX3/AtGPX3), and 159.8 million years ago (CaGPX5/AtGPX5) [36].

2.5. Phylogenetic Relationships of the GPX Gene Family

To study the evolutionary relationship between GPX genes from different species and CaGPX genes in peppers, we constructed an unrooted phylogenetic tree using GPX protein sequences from seven species, including pepper, Arabidopsis, cucumber, watermelon, Rhodiola crenulata, apple, and rice. As a result, a total of 43 GPX proteins from 7 species were clustered into four groups according to their sequence similarity and named Group I–Group IV (Figure 4). Group I consisted of 9 members, Group II consisted of 15 members, Group III consisted of 12 members, and Group IV consisted of 7 members. Among them, CaGPX8 fell into Group I; CaGPX2, 3, 6, and 7 fell into Group II; CaGPX4 and 5 fell into Group III, and CaGPX1 fell into Group IV. Overall, the GPX protein sequences clustered into the same group had a high similarity. In addition, it was worth noting that each group contains GPX proteins from different species, and the pepper GPX proteins have a strong phylogenetic relationship with Arabidopsis and rice, indicating that each GPX has homology in several other plant species, so they may have similar functions in different plants.

2.6. Analysis of CaGPXs Conserved Motifs and Gene Structures

Given that the pattern diversity of exon/intron structure and protein domains plays a crucial role in the evolution of gene families, we conducted an analysis of the phylogenetic relationships (Figure 5a), conservative motifs (Figure 5b; Table S3), and gene structures (Figure 5c) of GPX proteins in pepper, Arabidopsis, and rice. The results showed that all GPX protein sequences contained three conserved motifs (named motifs 1, 2, and 3). These conserved motifs were similar in GPX proteins of the same group. Additionally, another special motif (named motifs 4-10) was detected in some groups (Figure 5; Table S4). For example, OsGPX4 and CaGPX2 in Group I had motif 7; AtGPX1, 7 and CaGPX8 had motif 5 but were not found in other groups; and motif 10 was limited to two genes (OsGPX1 and OsGPX3) in Group IV. It is worth noting that all members in Group II only had motifs 1–3 (except for CaGPX3 and AtGPX3, which had motif 6); and only motifs 1–4 existed among all members of Group III. In addition, motif 9 (only present in AtGPX7 and CaGPX2) and motif 8 were specific to Group I. From the perspective of gene structure (Figure 5c), the GPX gene structure of each group was generally similar, but there were differences in the exon/intron arrangement of some genes. For example, all GPX genes have 5–6 exons. In Group I, all members had six exons, and the sequence lengths were generally similar. It is worth noting that the CaGPX7 sequence in Group II had the longest length (exceeding 15 kb); The member sequences in Group IV were similar in length, OsGPX1 had only five exons, and other members had similar structures. Overall, GPX genes in the same subgroup had similar structures and conserved motif distributions, indicating that GPX proteins contain highly conserved amino acid residues and that GPX members in the same cluster may have similar roles.

2.7. Cis Element Analysis of the CaGPX Promoter in Pepper

Since GPX genes play important roles in response to various stresses, we utilized PlantCARE to analyze the cis elements in the pre-2000 bp region of the CaGPX gene promoter to explore their key roles in stress and hormone signal transduction. From the promoter region of the GPX genes of the target species, we screened 25 putative cis-acting elements and divided them into four categories, including abiotic/biotic stress elements, hormone response elements, light response elements, and growth/development-related elements (Figure 6; Table S4). The results (Figure 6 and Figure 7) showed that among abiotic/biotic stress elements, hypoxia (ARE) elements were present in all CaGPX genes, and in drought-related elements (MYC, as-1, MBS), MYC elements were the most abundant, which was not found in CaGPX6. In addition, other cis-acting elements were specifically present in CaGPX genes, such as defense and stress responsiveness elements (TC-rich repeats), which only existed in CaGPX1, 3, and 4; hypoxia (GC-motif) elements only exist in CaGPX4, 5, and 7. Notably, among the hormone-responsive elements, elements related to abscisic acid responsiveness (ABRE and AAGAA-motif) were the most diverse and present in all CaGPX genes. The next was the ethylene-responsive element (ERE), which only exists in CaGPX5, 6, and 8. However, the gibberellin-responsive element was only present in CaGPX3 and was not found in other CaGPX genes. Finally, light response elements were relatively abundant in all CaGPX genes, with the GATA motif only existing in CaGPX2 and 8, while growth and development elements were specifically present in CaGPX8 genes.

2.8. Functional Annotation Evaluation of CaGPX Genes

To further understand and distinguish the role of CaGPX genes, we utilized the eggNOG online website to perform GO annotation and enrichment analysis of their functions. The biological process (BP) enrichment results (Table S5) showed that the CaGPX gene was mainly involved in cellular response to chemical stimulus (GO:0070887), detoxification (GO:0098754), cellular oxidant detoxification (GO:0098869), response to stimulus (GO:0050896), response to stress (GO:0006950), and cellular response to stimulus (GO:0051716), etc. The cellular component (CC) enrichment showed that CaGPX genes were mainly associated with cytosol (GO:0005829) and cytoplasm (GO:0005737). It is worth noting that molecular function (MF) was enriched in six GO terms, including antioxidant activity (GO:0016209), peroxidase activity (GO:0004601), glutathione peroxidase activity (GO:0004602), oxidoreductase activity (GO:0016491), and oxidoreductase activity, acting on peroxide as acceptor (GO:0016684), and catalytic activity (GO:0003824). These terms indicate that the CaGPX gene plays a role in reactive oxygen scavenging and antioxidant defense.

2.9. Analysis of the Protein Interaction Network of CaGPX Family Genes

To further understand the function of CaGPX genes in pepper, we utilized the STRING website to construct a potential protein–protein interaction network (PPI) between CaGPX proteins and other coding proteins in peppers. The results (Figure 8; Table S6) showed that the PPI network involves a total of 28 nodes and 392 edges. CaGPX1, T459_13041, GR1, T459_08909, T459_08876, and DHAR were the most significant genes with a betweenness centrality value greater than 20. In the PPI network, there were a total of 19 encoded proteins interacting with CaGPX proteins, among which three were glutathione reductase (GR1, T459_08876, and T459_08909); DHAR and T459_29115 belong to the GST superfamily, and T459_12719, T459_16601, T459_28703 and T459_32139 belong to the peroxidase family; two types were monodehydroascorbate reductase (T459_00229, T459_06854), two types were gamma-glutamyl transpeptidase 2, 3 (T459_15015, T459_24309), and two types were 2-Cys peroxiredoxin BAS1(T459_03397, T459_26258). The other three types were MRG domain-containing protein (T459_13041), glutathione synthetase (T459_22335), and thioredoxin reductase (T459_26495).

2.10. Tissue-Specific Expression Profiles of the CaGPX Gene in Peppers

To explore whether the GPX gene family plays a role in the tissue development of pepper, the expression profiles of CaGPXs in the roots, stems, leaves, pericarp, and placenta were observed using RNA-seq data from the pepper cultivar “CM334”. The results (Figure 9) showed that the expression of GPX genes was specific in different tissues of peppers, and CaGPX1, 4, and 6 were highly expressed in all tissues. Similarly, the expression of CaGPX8 was higher in leaves, stems, pericarp (6 d, 16 d, and 25 d after anthesis, green ripening, color change stage, and 5 d, 10 d after color change), and placentas (16 d after anthesis and 5 d and 10 d after color change), while it was less expressed in other tissues. By contrast, compared with other genes, CaGPX2 and CaGPX3 were expressed at lower levels in all tissues. Therefore, we speculated that CaGPX1, CaGPX4, and CaGPX6 play a greater role than other genes in the development processes of pepper.

2.11. Changes in the Relative Expression of the CaGPX Gene under Osmotic Stress and ABA Treatment

To further understand the expression of the CaGPX gene under different abiotic stress conditions, qRT-PCR was used to analyze the expression of the eight CaGPX genes under ABA, cold, drought, and salt stress (Figure 10). Under 100 μmol/L ABA treatment (Figure 10a), the expression of most CaGPX genes reached the highest level at 12 h after treatment, with CaGPX1 being the most significant, 53-fold higher than that at 0 h (CK), followed by CaGPX6, which was 29-fold higher than that at 0 h. However, the expression of CaGPX4 reached its maximum at 6 h, which was 81.5-fold higher than that at CK. By contrast, after 24 h of treatment, the expression levels of CaGPX5, 7, and 8 were downregulated, and the expression level of CaGPX7 was the most significantly downregulated (0.25). Notably, CaGPX3 expression was downregulated at all other times and increased only 12 h after treatment, rising 1.7-fold over CK. Under cold stress (Figure 10b), the expression of CaGPX4 and CaGPX6 were significantly upregulated, reaching a maximum at 6 h, which was 65-fold and 16-fold higher than that at 0 h, respectively; CaGPX1 reached the maximum value at 12 h, which was more than 19 times higher than that at 0 h; CaGPX2 and CaGPX3 reached the maximum value at 24 h, which was 9 times and 2.5 times higher than at 0 h, respectively; and CaGPX8 peaked at 12 h after treatment, 9 times that at 0 h. However, although the upregulation of CaGPX7 expression level reached a significant level after treatment, the highest was only 1.7 times that of 0 h. Notably, the expression levels of all CaGPX genes increased first and then decreased under drought stress (Figure 10c) and reached a maximum at 6 h (except for CaGPX5 and CaGPX3), which were 92-, 5-, 54-, 21-, 9-, and 23-fold higher than those at 0 h, respectively. The expression levels of CaGPX5 and CaGPX8 decreased to 0.7 at 24 h. Similarly, the expression trends of CaGPX1 and CaGPX4 under salt stress were the same as those under drought stress (Figure 10d), reaching their maxima at 6 h, which was 55 times and 74 times higher than that at 0 h, respectively. The expression levels of CaGPX5 and CaGPX6 were the highest at 9 h, which was 9.3 times and 9.6 times higher than that at 0 h, respectively. The above results indicate that CaGPX1, 4 and CaGPX6 play an important role in alleviating abiotic stress in pepper.

2.12. Subcellular Localization Analysis

Subcellular localization of genes helps to understand the working position of proteins. Because the relative expression levels of CaGPX1 and CaGPX4 were significantly upregulated under different stress treatments, and the expression trends were also similar. Therefore, in order to verify the results of subcellular prediction, we analyzed the instantaneous expression of CaGPX1 and CaGPX4 proteins in tobacco leaves using Agrobacterium-mediated methods and observed the fluorescence signals by laser confocal microscopy. The results showed that the strong fluorescence signal was localized in chloroplasts (Figure 11), which was also consistent with our prediction.

2.13. Changes in Glutathione Peroxidase Activity (GSH-Px) and Morphological Characteristics of Pepper Seedlings under Osmotic Stress and ABA Treatment

The activity of glutathione peroxidase and the phenotypic changes in pepper seedlings under different treatments are shown in Figure 12 and Figure S2, respectively. The results showed that the activity of glutathione antioxidant enzymes showed a trend of first increasing and then decreasing under different treatments. The enzyme activity under ABA (Figure 12a) and cold treatment (Figure 12b) peaked at 12 h, 3.2 and 2.2 times that at 0 h, respectively, followed by 9 h, 2.9 and 1.7 times that at 0 h, respectively. The maximum enzyme activity under PEG (Figure 12c) and NaCl treatment (Figure 12d) was reached at 6 h, which was 2.9 and 2.3 times that of 0 h, respectively; 9 h arrived next, with 2.5 and 1.8 times the values at 0 h, respectively. Additionally, the variations in gene expression are essentially consistent with the variations in enzyme activity, and the degree of wilting of pepper plants also increased with the lengthening of the treatment period, but the phenotype of plants receiving ABA treatment was good (Figure S2).

3. Discussion

As a consequence of the various biotic or abiotic stress processes that plants can face, a large amount of ROS accumulates in plant cells, leading to the damage of biological macromolecules and cell death. In this sense, the protein encoded by the GPX gene plays an important role in protecting plant cells from oxidative damage caused by ROS accumulation [2,37,38]. Therefore, a systematic and comprehensive analysis of the pepper GPX gene family and understanding their response to a variety of stress conditions is a justified scientific question to address [17]. In our study, a total of eight CaGPX genes were identified from the “CM334” pepper genome. All eight CaGPX genes encode hydrophilic proteins with stable structures. CaGPX6 and CaGPX7 encode proteins with isoelectric points lower than the others (Table 1). This result was similar to that in rapeseed and watermelon. In BnGPX and ClGPX, all the proteins encoded by genes are hydrophilic proteins with stable structures, and they also contain two acidic proteins, while the remaining proteins are alkaline [12,39]. Subcellular localization prediction can locate a certain protein or expression product at a specific location in the cell, providing a research direction for understanding the mechanism of gene action [40]. Like CsGPXs in cucumber and GhGPXs in cotton, CaGPXs were mainly located in the cytoplasm, nucleus, and chloroplast (Table S1), indicating that GPX genes act on these organelles and protect them from damage during ROS production. In addition, H2O2 produced in chloroplast PSI is one of the main sources of intracellular ROS, so CaGPXs located in chloroplasts may also be involved in regulating the generation of H2O2 in chloroplasts [41].
The amino acid sequence analysis of CaGPX proteins, AtGPX proteins, and OsGPX proteins showed that their encoded proteins have three typical GPX domains and three conserved Cys residues of GPX active centers (Figure 1), and Cys residues are specific structures of selenium-independent plant GPXs [42]. The first two Cys residues were located within domain I and domain II, respectively, and the third was located outside the domain. These results indicate that biological GPX proteins are highly similar in sequence, and the key active site Cys residues are crucial to the perception of redox potential [11,43]. Chromosome mapping showed that the eight CaGPX genes were distributed on four chromosomes of pepper, and CaGPX6/CaGPX7 were a pair of tandem repeat gene pairs (Figure 2). Segment repetition, tandem repetition, and translocation events are the primary sources of gene family amplification [44], which is a fundamental evolutionary process in the genome that assists plants in adapting to varied environmental conditions [45]. The collinearity analysis of the CaGPX gene and AtGPX gene showed that there were four pairs of collinearity relationships between two CaGPX genes and three AtGPX genes (Figure 3), and they belonged to purification selection during evolution (Table S2), indicating that the GPX gene had a common ancestor and was highly conserved in the evolutionary process. These results also indicate that tandem duplication events play an important role in the GPX gene replication process in peppers.
The phylogenetic tree shows that the GPX genes from peppers and other species were divided into four groups, which was consistent with the classification in cucumber [46], cotton [26], Thellungiella salsuginea [47], rapeseed [12], and bread wheat [17]. By observing the phylogenetic tree, similarities and differences between different species can be analyzed. Our results show that each group contains GPX proteins from different species, and pepper GPX proteins are closely branched with Arabidopsis and rice on the phylogenetic tree (Figure 4). This suggests that these gene families have undergone numerous evolutionary processes, including gene replication, division, and modification, leading to the emergence of numerous isoforms and potential orthologs in various species. Simultaneously, in Figure 5a, there were also four clusters discernible in the grouping classifications of CaGPXs, AtGPXs, and OsGPXs. GPX genes aggregated into the same group have similar conserved motifs and gene structures (Figure 5). Three conserved motifs (1–3) are present in all GPX genes in pepper, Arabidopsis, and rice, while some other conserved motifs are limited to particular groups or species of GPX proteins (Figure 5b), suggesting that these motifs may support the maintenance of particular GPX functions. The structure of gene exons and introns is an important marker to reveal the evolutionary relationship between gene family members [48]. Gene structure analysis showed that CaGPXs, AtGPXs, and OsGPXs almost all had five introns and six exons (Figure 5c), which was similar to the results in cucumber [46], Thellungiella salsuginea [47], and cotton [26]. Their GPX genes also have five introns and six exons. The above results indicate that GPX genes were highly conserved during evolution and may have similar functions.
Cis-acting elements play an important role in the regulation of gene expression, which can bind to transcription factors and regulate gene transcription [49,50]. By analyzing the cis elements in the promoter region of the CaGPXs gene, we can better understand its regulatory mechanism and infer the function of the CaGPXs gene and its influence on the development of pepper. The results showed that the identified cis elements were mainly divided into four categories, i.e., stress response elements, plant hormone response elements, growth and development elements, and light response elements (Figure 7; Table S4). The types and quantities of elements contained in different CaGPXs were different, indicating that the CaGPX genes have different levels of stress and hormone responses, so it was speculated that there were functional differences among CaGPXs. Additionally, GO enrichment annotations demonstrated that CaGPX genes are involved in many stress responses and possess peroxidase activity (Table S5), and previous reports have also suggested that GPX genes are involved in several different stress responses [16,27,47]. These results indicate the importance of CaGPX genes in the growth and development of peppers.
The results of the interaction network show that GPX proteins all interact with each other, and there was an interaction relationship with the GST superfamily, peroxidase family, glutathione reductase, and glutathione synthetase (Figure 8; Table S6), which was not addressed in Wang et al.’s study [51] or in previous reports [26,27,39,46]. Since the interaction networks of multiple GPX proteins were highly crossed and clustered into a very large network, we speculated that GPX proteins may be functionally related and may interact with the other families to participate in the clearance of reactive oxygen species in peppers.
Understanding the expression patterns of genes in different plant tissues is important for studying gene function and biological development [52]. The tissue-specific expression profile of CaGPX genes showed that during the growth and development of peppers, the expression of some genes had obvious tissue specificity (Figure 9). In cotton, GhGPX2 was highly expressed in roots and stems, GhGPX13 was highly expressed in flowers but lower in other tissues, and GhGPX1, 3, and 5 and GhGPX8 were also highly expressed in flowers [26]. In watermelon, all ClGPX genes were highly expressed in flowers and fruits, and ClGPX3 was also highly expressed in mature leaves [39]. In cucumber, CsGPX1, CsGPX3, CsGPX5, and CsGPX6 were highly expressed in the tendrils and tendril bases but were expressed at low levels in other tissues [46]. These results indicate that the expression patterns of GPX genes vary in different plant tissues, and they play their respective potential roles in plant development.
Similar to the tissue-specific expression results, CaGPX1, 4 and CaGPX6 expression levels were significantly upregulated under ABA and abiotic stress (Figure 10). However, the expression levels of other genes only changed during certain periods after treatment. These results indicate that GPX genes exhibit complex expression patterns in stress treatments and thus perform different functions. At the same time, studies have shown that some members of the GPX gene family can be regulated through ABA-dependent signaling pathways [31], in which AtGPX3 can act as an H2O2 scavenger in ABA and drought stress signals to transmit H2O2 signals, thereby removing H2O2 [53]. In watermelon and cucumber, almost all GPX genes were significantly upregulated under ABA, cold, salt, and drought treatments [39,46]. In wheat, the GPX genes W69 and W106 play an important role in response to salt, drought, hydrogen peroxide, and ABA, and their overexpression enhances salt tolerance in transgenic Arabidopsis [31]. In T. salsuginea, almost all TsGPX genes were significantly upregulated at least at one time point under salt and drought stress [47]. Furthermore, the variations in glutathione peroxidase (GSH-Px) activity in peppers are essentially compatible with the variations in gene expression levels, and the variations in glutathione peroxidase activity in peppers were also described for the first time in this study. The above results indicate that the CaGPX gene may enhance the stress resistance of pepper by regulating ABA signaling pathways, and CaGPX1, 4 and CaGPX6 may be more important in this process. At the same time, our findings also lay the foundation for further research on the function of the CaGPX gene family in abiotic stress and ABA responses.

4. Materials and Methods

4.1. Genome-Wide Identification of CaGPX Genes in Pepper

The protein sequences of 8 GPX genes in Arabidopsis were downloaded from the Arabidopsis information resource website (https://www.arabidopsis.org/, accessed on 6 November 2023) [54]. The “CM334” (C. annuum) genomic data were downloaded from the pepper website (http://peppergenome.snu.ac.kr/download.php, accessed on 6 November 2023) [32]. Then, BLASTp comparisons were performed using the amino acid sequences of eight Arabidopsis GPXs as a query, with the E-value < E−10. Next, we used the hidden Markov model (HMM) profile of the GPX structural domain in the Pfam database (https://www.ebi.ac.uk/interpro/, accessed on 6 November 2023) [55] to identify candidate GPX sequences (Pfam: PF00255). Finally, the NCBI-CDD databases (https://www.ncbi.nlm.nih.gov/cdd/, accessed on 6 November 2023) [56] were used for domain identification of candidate gene sequence structures. Candidate genes that did not contain the specific domain of the GPX gene (Pfam: PF00255) were manually removed.

4.2. Sequence Information and Structural Analysis of the Pepper GPX Gene Family

The subcellular localization of GPX proteins in pepper was predicted using the WoLf PSORT online website (https://wolfpsort.hgc.jp/, accessed on 6 November 2023) [57]. ExPASy (http://expasy.org/, accessed on 6 November 2023) was used to identify the number of amino acids, the isoelectric point, and other physical and chemical properties of CaGPX proteins [58]. Then, the secondary structure of the pepper GPX protein was predicted by the online site SOPMA (https://npsa-prabi.ibcp.fr/cgi-bin/npsa_automat.pl?page=npsa%20_sopma.html, accessed on 6 November 2023) [59]. Finally, the tertiary structures of pepper GPX and Arabidopsis GPX proteins were predicted by Phyre2 (http://www.sbg.bio.ic.ac.uk/, accessed on 6 November 2023) [60] and visualized using PyMOL software (V 2.60a0) [61].

4.3. Analysis of Chromosome Location and Collinearity

TBtools software (V 1.118) was used to map and visualize the position of the GPX genes identified in the 12 chromosomes of pepper [62]. Homology was searched using MCScanX, protein-coding genes in the pepper genome were compared with the protein-coding genes in the Arabidopsis genome using BLASTp, and the search threshold was set to an E-value < E−5. Other parameters default. Whole-genome BLASTp results were used to compute collinear blocks for all possible pairs of chromosomes and scaffolds [63]. Finally, the GPX gene colinear pairs of pepper and Arabidopsis were highlighted using TBtools (V 1.118) [62]. In addition, we used KaKs_Calculator 2.0 software to calculate the Ka/Ks ratio of CaGPX genes that have a collinear relationship with Arabidopsis [64].

4.4. Multiple Sequence Alignments and Construction of Phylogenetic Tree

To understand the evolutionary relationship of the CsGPX gene family, we used the muscle sequence alignment method in MEGA 11 software (V 11.08) to compare the GPX protein sequences of seven species (Table S7), including pepper, Arabidopsis, cucumber, watermelon, Rhodiola crenulata, apple, and rice. Then, we selected the maximum likelihood (ML) method to construct a phylogenetic tree. The amino acid substitution model was LG+G (Additional File S1), and the bootstrap values were calculated for 1000 replicates [65]. Next, the constructed tree was beautified using the EvolView online website (https://www.evolgenius.info/evolview/#/treeview, accessed on 6 November 2023) [66]. Finally, a sequence alignment representation of the GPX protein sequences of pepper, Arabidopsis, and rice was generated using Jalview software (V 1.8.3) [67].

4.5. Analysis of Gene Exon–Intron Structures and Protein Conserved Motifs

The structure of GPX genes in pepper, Arabidopsis, and rice was analyzed by GSDS 2.0 (http://gsds.gao-lab.org/, accessed on 6 November 2023) [68]. Then, the conserved motifs of the GPX genes in pepper, Arabidopsis, and rice were analyzed by MEME version 5.5.1 (http://meme-suite.org/tools/meme, accessed on 6 November 2023) [69]. The maximum number of motifs was set as 10, and the remaining parameters were set as default values.

4.6. Analysis of Cis-Acting Elements in CaGPX Gene Promoters

To understand the inferred cis-elements in the CaGPX promoter, the first 2000 bp upstream sequence of 8 identified CaGPX gene initiation codons (ATG) was extracted using TBtools (V 1.118) [62]. Then, each extracted gene promoter sequence was submitted to the PlantCARE website (http://bioinformatics.psb.ugent.be/webtools/plantcare/html/, accessed on 6 November 2023) [70] for cis-acting element prediction, and a figure of its distribution into the promoters was generated using TBtools (V 1.118) [62].

4.7. Tissue Expression Analysis of GPX Genes

To investigate the specific expression of the CaGPX gene in different tissues of peppers, this study utilized transcriptome data from “CM334” and normalized the fragment count of each gene using the million fragments per thousand bases method (FPKM) [32]. Finally, data conversion was performed using the log2 (FPKM + 1) method, and TBtools software (V1.118) was used to obtain the expression profiles of the GPX genes in various tissues [62].

4.8. Functional Annotation Study of CaGPX Genes and Protein Interaction Network Prediction

CaGPX protein sequences were uploaded to the eggNOG website (http://eggnog-mapper.embl.de/, accessed on 6 November 2023) to perform their gene ontology (GO) annotation [71]. Additionally, TBtools (V 1.118) was used for GO enrichment analysis and visualization. The STRING website (https://cn.string-db.org/cgi/, accessed on 6 November 2023) [72] was used to predict protein–protein interaction networks using the five CsGPX protein sequences as targets.

4.9. Test Materials and Treatment

This study used the Longjiao 10 pepper variety (Capsicum chinense). Pepper seedlings were cultured in an artificial climate incubator under photoperiod conditions of 26/20 °C day/night and 16/8 h day/night with a light intensity of 300 μmol m−2 s−1 for 6–8 true leaf stages, and various treatments were performed. Plants of uniform growth were then treated with four treatments, T1: 100 μmol/L ABA; T2: cold stress (4 °C); T3: 20% PEG; and T4: 200 mmol/L NaCl. All treatments were performed simultaneously, and leaves were harvested from the same location of the seedlings after treatment for 0, 3, 6, 9, 12, and 24 h, with three biological replicates. Samples were placed in liquid nitrogen and immediately stored in a refrigerator at −80 °C.

4.10. RNA Extraction and Quantitative PCR (qRT-PCR)

Total RNA from pepper leaves was extracted using an RNA extraction kit (Accyrate Biotechnology Co., Ltd., Yiyang, China). With 2 µL RNA as a template, cDNA was obtained by reverse transcription using the Evo M-MLV reverse transcription kit (Accyrate Biotechnology Co., Ltd., China). Using pepper actin as the internal reference gene (NCBI login number: LOC107875540), the coding sequences of CaGPX genes were input into the homepage of Shanghai Biology Company (Shanghai, China) for online primer design (Table S8). qRT-PCR was performed by fluorescence quantitative analysis using the SYBR Green kit (Accyrate Biotechnology Co., Ltd., China). The volume of the reaction system was 20 µL, containing 1 µL cDNA solution, 10 µL 2 SYBR, 2 µL of 10 µM forward and reverse primers, and 7 µL of distilled deionized water. Next, qRT-PCR was performed using the LightCycler® 480 II real-time fluorescence quantitative PCR instrument. The amplification program conditions were as follows: 95 °C for 15 min, 40 cycles of 95 °C for 10 s and 60 °C for 30 s. Each sample was replicated three times.

4.11. Subcellular Localization of CaGPX1 and CaGPX4 Proteins

In order to determine the subcellular localization of CaGPX1 and CaGPX4 proteins, we amplified the full length without the stop codon of the CaGPX1 and CaGPX4 genes and inserted the amplified fragments into the Pac402 vector. The primer sequences are shown in Table S8. Subsequently, the fusion vector plasmid was transformed into A. tumefaciens (GV3101) using the freeze–thaw method. Then, A. tumefaciens was infiltrated into tobacco (Nicotiana benthamiana) leaves. After 48 h of dark infection at 25 °C, green fluorescence was observed using a laser-scanning confocal microscope (Olympus FV3000, Tokyo, Japan).

4.12. Determination of Glutathione Antioxidant Enzyme Activity

The determination of GSH-Px activity was based on Xue et al.’s method [73], with slight modifications. One enzyme activity unit of glutathione peroxidase is defined as 1 mU of GSH-Px mL−1 min−1.

4.13. Statistical Analysis

The relative expression levels of the CaGPX genes were calculated using the 2−∆∆CT method [74], and raw CT values were placed in Additional File S2. SPSS 20.0 was used to analyze the relative expression, and Origin 9.0 was used to complete the histogram of relative expression.

5. Conclusions

In conclusion, a total of eight members of the CaGPX gene family were identified in the “CM334” genome database of pepper. Analysis of their physical and chemical properties, multiple sequence alignment, phylogeny, collinearity, and gene structure revealed that the family had a conserved sequence and stable structure. Furthermore, GO annotation, protein interaction network, subcellular localization, tissue-specific expression profiling, and expression profile analysis under different osmotic stress and ABA treatment suggest that certain CaGPX genes play distinct roles in pepper development and stress response and may contribute to the ABA signaling pathway. However, the exact function of these genes remains to be elucidated in future studies. In addition, these findings will lay the foundation for studying the role of the CaGPX gene in the development of capsicum, as well as using CRISPR/Cas system overexpression, knockout, and other functional verification schemes.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms25158343/s1. References [75,76] are cited in the Supplementary Materials.

Author Contributions

Conceptualization, Z.Z. and C.W.; methodology, Y.C.; software, Z.Z.; validation, J.Z., C.W. and Z.Z.; formal analysis, Y.G. and Y.C.; investigation, K.H.; resources, J.X.; data curation, J.X. and J.Z.; writing—original draft preparation, Z.Z.; writing—review and editing, J.Z., C.W. and J.X.; supervision, J.Z.; project administration, J.X. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the Scientific Research Start-Up Funds for Openly Recruited Doctors (GAU-KYQD-2020-8) and the Special Fund for Technical System of Melon and Vege-table Industry of Gansu Province (GARS-GC-1).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data is contained within the article and Supplementary Materials.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Passaia, G.; Margis-Pinheiro, M. Glutathione peroxidases as redox sensor proteins in plant cells. Plant Sci. 2015, 234, 22–26. [Google Scholar] [CrossRef]
  2. Margis, R.; Dunand, C.; Teixeira, F.K.; Margis-Pinheiro, M. Glutathione peroxidase family—An evolutionary overview. FEBS J. 2008, 275, 3959–3970. [Google Scholar] [CrossRef]
  3. Drotar, A.; Phelps, P.; Fall, R. Evidence for glutathione peroxidase activities in cultured plant cells. Plant Sci. 1985, 42, 35–40. [Google Scholar] [CrossRef]
  4. Zhao, L.; Zong, W.; Zhang, H.; Liu, R. Kidney toxicity and response of selenium containing protein-glutathione peroxidase (Gpx3) to CdTe QDs on different levels. Toxicol. Sci. 2019, 168, 201–208. [Google Scholar] [CrossRef]
  5. Mittler, R.; Zandalinas, S.I.; Fichman, Y.; Van Breusegem, F. Reactive oxygen species signalling in plant stress responses. Nat. Rev. Mol. Cell Biol. 2022, 23, 663–679. [Google Scholar] [CrossRef]
  6. Mills, G.C. Hemoglobin catabolism: I. Glutathione peroxidase, an erythrocyte enzyme which protects hemoglobin from oxidative breakdown. J. Biol. Chem. 1957, 229, 189–197. [Google Scholar] [CrossRef]
  7. Brigelius-Flohé, R.; Maiorino, M. Glutathione peroxidases. Biochim. Biophys. Acta (BBA)-Gen. Subj. 2013, 1830, 3289–3303. [Google Scholar] [CrossRef]
  8. Criqui, M.; Jamet, E.; Parmentier, Y.; Marbach, J.; Durr, A.; Fleck, J. Isolation and characterization of a plant cDNA showing homology to animal glutathione peroxidases. Plant Mol. Biol. 1992, 18, 623–627. [Google Scholar] [CrossRef]
  9. Toppo, S.; Vanin, S.; Bosello, V.; Tosatto, S.C. Evolutionary and structural insights into the multifaceted glutathione peroxidase (Gpx) superfamily. Antioxid. Redox Signal. 2008, 10, 1501–1514. [Google Scholar] [CrossRef] [PubMed]
  10. San Koh, C.; Didierjean, C.; Navrot, N.; Panjikar, S.; Mulliert, G.; Rouhier, N.; Jacquot, J.-P.; Aubry, A.; Shawkataly, O.; Corbier, C. Crystal structures of a poplar thioredoxin peroxidase that exhibits the structure of glutathione peroxidases: Insights into redox-driven conformational changes. J. Mol. Biol. 2007, 370, 512–529. [Google Scholar]
  11. Navrot, N.; Collin, V.; Gualberto, J.; Gelhaye, E.; Hirasawa, M.; Rey, P.; Knaff, D.B.; Issakidis, E.; Jacquot, J.-P.; Rouhier, N. Plant glutathione peroxidases are functional peroxiredoxins distributed in several subcellular compartments and regulated during biotic and abiotic stresses. Plant Physiol. 2006, 142, 1364–1379. [Google Scholar] [CrossRef]
  12. Li, W.; Huai, X.; Li, P.; Raza, A.; Mubarik, M.S.; Habib, M.; Fiaz, S.; Zhang, B.; Pan, J.; Khan, R.S.A. Genome-wide characterization of glutathione peroxidase (GPX) gene family in rapeseed (brassica napus L.) revealed their role in multiple abiotic stress response and hormone signaling. Antioxidants 2021, 10, 1481. [Google Scholar] [CrossRef]
  13. Herbette, S.; Roeckel-Drevet, P.; Drevet, J.R. Seleno-independent glutathione peroxidases: More than simple antioxidant scavengers. FEBS J. 2007, 274, 2163–2180. [Google Scholar] [CrossRef]
  14. Rouhier, N.; Cerveau, D.; Couturier, J.; Reichheld, J.-P.; Rey, P. Involvement of thiol-based mechanisms in plant development. Biochim. Biophys. Acta (BBA)-Gen. Subj. 2015, 1850, 1479–1496. [Google Scholar] [CrossRef]
  15. Sugimoto, M.; Sakamoto, W. Putative phospholipid hydroperoxide glutathione peroxidase gene from Arabidopsis thaliana induced by oxidative stress. Genes Genet. Syst. 1997, 72, 311–316. [Google Scholar] [CrossRef]
  16. Li, W.-J.; Feng, H.; Fan, J.-H.; Zhang, R.-Q.; Zhao, N.-M.; Liu, J.-Y. Molecular cloning and expression of a phospholipid hydroperoxide glutathione peroxidase homolog in Oryza sativa. Biochim. Biophys. Acta (BBA)-Gene Struct. Expr. 2000, 1493, 225–230. [Google Scholar] [CrossRef]
  17. Tyagi, S.; Sembi, J.K.; Upadhyay, S.K. Gene architecture and expression analyses provide insights into the role of glutathione peroxidases (GPXs) in bread wheat (Triticum aestivum L.). J. Plant Physiol. 2018, 223, 19–31. [Google Scholar] [CrossRef]
  18. Bela, K.; Horváth, E.; Gallé, Á.; Szabados, L.; Tari, I.; Csiszár, J. Plant glutathione peroxidases: Emerging role of the antioxidant enzymes in plant development and stress responses. J. Plant Physiol. 2015, 176, 192–201. [Google Scholar] [CrossRef]
  19. Miao, Y.; Guo, J.; Liu, E.; Li, K.; Dai, J.; Wang, P.; Chen, J.; Song, C. Osmotically stress-regulated the expression of glutathione peroxidase 3 in Arabidopsis. Chin. Sci. Bull. 2007, 52, 127–130. [Google Scholar] [CrossRef]
  20. Riyazuddin, R.; Bela, K.; Horváth, E.; Rigó, G.; Gallé, Á.; Szabados, L.; Fehér, A.; Csiszár, J. Overexpression of the Arabidopsis glutathione peroxidase-like 5 gene (AtGPXL5) resulted in altered plant development and redox status. Environ. Exp. Bot. 2019, 167, 103849. [Google Scholar] [CrossRef]
  21. Kruger, W.M.; Pritsch, C.; Chao, S.; Muehlbauer, G.J. Functional and comparative bioinformatic analysis of expressed genes from wheat spikes infected with Fusarium graminearum. Mol. Plant-Microbe Interact. 2002, 15, 445–455. [Google Scholar] [CrossRef] [PubMed]
  22. Passaia, G.; Fonini, L.S.; Caverzan, A.; Jardim-Messeder, D.; Christoff, A.P.; Gaeta, M.L.; de Araujo Mariath, J.E.; Margis, R.; Margis-Pinheiro, M. The mitochondrial glutathione peroxidase GPX3 is essential for H2O2 homeostasis and root and shoot development in rice. Plant Sci. 2013, 208, 93–101. [Google Scholar] [CrossRef] [PubMed]
  23. Passaia, G.; Caverzan, A.; Fonini, L.; Carvalho, F.; Silveira, J.; Margis-Pinheiro, M. Chloroplastic and mitochondrial GPX genes play a critical role in rice development. Biol. Plant. 2014, 58, 375–378. [Google Scholar] [CrossRef]
  24. Wang, X.; Fang, G.; Yang, J.; Li, Y. Athioredoxin-dependent glutathione peroxidase (OsGPX5) is required for rice normal development and salt stress tolerance. Plant Mol. Biol. Rep. 2017, 35, 333–342. [Google Scholar] [CrossRef]
  25. Lima-Melo, Y.; Carvalho, F.E.; Martins, M.O.; Passaia, G.; Sousa, R.H.; Neto, M.C.L.; Margis-Pinheiro, M.; Silveira, J.A. Mitochondrial GPX1 silencing triggers differential photosynthesis impairment in response to salinity in rice plants. J. Integr. Plant Biol. 2016, 58, 737–748. [Google Scholar] [CrossRef] [PubMed]
  26. Chen, M.; Li, K.; Li, H.; Song, C.-P.; Miao, Y. The glutathione peroxidase gene family in Gossypium hirsutum: Genome-wide identification, classification, gene expression and functional analysis. Sci. Rep. 2017, 7, 44743. [Google Scholar] [CrossRef] [PubMed]
  27. Akbudak, M.A.; Filiz, E.; Vatansever, R.; Kontbay, K. Genome-wide identification and expression profiling of ascorbate peroxidase (APX) and glutathione peroxidase (GPX) genes under drought stress in sorghum (Sorghum bicolor L.). J. Plant Growth Regul. 2018, 37, 925–936. [Google Scholar] [CrossRef]
  28. Zhang, L.; Wu, M.; Teng, Y.; Jia, S.; Yu, D.; Wei, T.; Chen, C.; Song, W. Overexpression of the glutathione peroxidase 5 (RcGPX5) gene from Rhodiola crenulata increases drought tolerance in Salvia miltiorrhiza. Front. Plant Sci. 2019, 9, 1950. [Google Scholar] [CrossRef] [PubMed]
  29. Zhang, L.; Wu, M.; Yu, D.; Teng, Y.; Wei, T.; Chen, C.; Song, W. Identification of glutathione peroxidase (GPX) gene family in Rhodiola crenulata and gene expression analysis under stress conditions. Int. J. Mol. Sci. 2018, 19, 3329. [Google Scholar] [CrossRef]
  30. Cai, Q.; Ding, G.; Wen, X. Cloning of glutathione peroxidase PmGPX6 gene from Pinus massoniana and the study on drought tolerance of transgenic Arabidopsis thaliana. For. Res. 2016, 29, 839–846. [Google Scholar]
  31. Zhai, C.-Z.; Zhao, L.; Yin, L.-J.; Chen, M.; Wang, Q.-Y.; Li, L.-C.; Xu, Z.-S.; Ma, Y.-Z. Two wheat glutathione peroxidase genes whose products are located in chloroplasts improve salt and H2O2 tolerances in Arabidopsis. PLoS ONE 2013, 8, e73989. [Google Scholar] [CrossRef] [PubMed]
  32. Kim, S.; Park, M.; Yeom, S.-I.; Kim, Y.-M.; Lee, J.M.; Lee, H.-A.; Seo, E.; Choi, J.; Cheong, K.; Kim, K.-T. Genome sequence of the hot pepper provides insights into the evolution of pungency in Capsicum species. Nat. Genet. 2014, 46, 270–278. [Google Scholar] [CrossRef] [PubMed]
  33. Qin, C.; Yu, C.; Shen, Y.; Fang, X.; Chen, L.; Min, J.; Cheng, J.; Zhao, S.; Xu, M.; Luo, Y. Whole-genome sequencing of cultivated and wild peppers provides insights into Capsicum domestication and specialization. Proc. Natl. Acad. Sci. USA 2014, 111, 5135–5140. [Google Scholar] [CrossRef] [PubMed]
  34. Churin, Y.; Schilling, S.; Börner, T. A gene family encoding glutathione peroxidase homologues in Hordeum vulgare (barley). FEBS Lett. 1999, 459, 33–38. [Google Scholar] [CrossRef] [PubMed]
  35. Hurst, L.D. The Ka/Ks ratio: Diagnosing the form of sequence evolution. TRENDS Genet. 2002, 18, 486–487. [Google Scholar] [CrossRef] [PubMed]
  36. Lynch, M.; Conery, J.S. The evolutionary fate and consequences of duplicate genes. Science 2000, 290, 1151–1155. [Google Scholar] [CrossRef] [PubMed]
  37. Attacha, S.; Solbach, D.; Bela, K.; Moseler, A.; Wagner, S.; Schwarzländer, M.; Aller, I.; Müller, S.J.; Meyer, A.J. Glutathione peroxidase-like enzymes cover five distinct cell compartments and membrane surfaces in Arabidopsis thaliana. Plant Cell Environ. 2017, 40, 1281–1295. [Google Scholar] [CrossRef] [PubMed]
  38. Pakzad, R.; Goharrizi, K.J.; Riahi-Madvar, A.; Amirmahani, F.; Mortazavi, M.; Esmaeeli, L. Identification of Lepidium draba Δ 1-pyrroline-5-carboxylate synthetase (P5CS) and assessment of its expression under NaCl stress: P5CS identification in L. draba plant. Proc. Natl. Acad. Sci. India Sect. B Biol. Sci. 2021, 91, 195–203. [Google Scholar] [CrossRef]
  39. Zhou, Y.; Li, J.; Wang, J.; Yang, W.; Yang, Y. Identification and characterization of the glutathione peroxidase (GPX) gene family in watermelon and its expression under various abiotic stresses. Agronomy 2018, 8, 206. [Google Scholar] [CrossRef]
  40. Yu, C.S.; Chen, Y.C.; Lu, C.H.; Hwang, J.K. Prediction of protein subcellular localization. Proteins Struct. Funct. Bioinform. 2006, 64, 643–651. [Google Scholar] [CrossRef]
  41. Leister, D. Piecing the puzzle together: The central role of reactive oxygen species and redox hubs in chloroplast retrograde signaling. Antioxid. Redox Signal. 2019, 30, 1206–1219. [Google Scholar] [CrossRef]
  42. Jung, B.G.; Lee, K.O.; Lee, S.S.; Chi, Y.H.; Jang, H.H.; Kang, S.S.; Lee, K.; Lim, D.; Yoon, S.C.; Yun, D.-J. A Chinese Cabbage cDNA with High Sequence Identity to Phospholipid Hydroperoxide Glutathione Peroxidases Encodes a Novel Isoform of Thioredoxin-dependent Peroxidase. J. Biol. Chem. 2002, 277, 12572–12578. [Google Scholar] [CrossRef]
  43. Iqbal, A.; Yabuta, Y.; Takeda, T.; Nakano, Y.; Shigeoka, S. Hydroperoxide reduction by thioredoxin-specific glutathione peroxidase isoenzymes of Arabidopsis thaliana. FEBS J. 2006, 273, 5589–5597. [Google Scholar] [CrossRef]
  44. Cannon, S.B.; Mitra, A.; Baumgarten, A.; Young, N.D.; May, G. The roles of segmental and tandem gene duplication in the evolution of large gene families in Arabidopsis thaliana. BMC Plant Biol. 2004, 4, 10. [Google Scholar] [CrossRef]
  45. Kong, H.; Landherr, L.L.; Frohlich, M.W.; Leebens-Mack, J.; Ma, H.; DePamphilis, C.W. Patterns of gene duplication in the plant SKP1 gene family in angiosperms: Evidence for multiple mechanisms of rapid gene birth. Plant J. 2007, 50, 873–885. [Google Scholar] [CrossRef]
  46. Zhou, Y.; Hu, L.; Ye, S.; Jiang, L.; Liu, S. Genome-wide identification of glutathione peroxidase (GPX) gene family and their response to abiotic stress in cucumber. 3 Biotech 2018, 8, 159. [Google Scholar] [CrossRef]
  47. Gao, F.; Chen, J.; Ma, T.; Li, H.; Wang, N.; Li, Z.; Zhang, Z.; Zhou, Y. The glutathione peroxidase gene family in Thellungiella salsuginea: Genome-wide identification, classification, and gene and protein expression analysis under stress conditions. Int. J. Mol. Sci. 2014, 15, 3319–3335. [Google Scholar] [CrossRef]
  48. Long, M.; Betrán, E.; Thornton, K.; Wang, W. The origin of new genes: Glimpses from the young and old. Nat. Rev. Genet. 2003, 4, 865–875. [Google Scholar] [CrossRef]
  49. Mishra, S.; Shukla, A.; Upadhyay, S.; Sharma, P.; Singh, S.; Phukan, U.J.; Meena, A.; Khan, F.; Tripathi, V.; Shukla, R.K. Identification, occurrence, and validation of DRE and ABRE Cis-regulatory motifs in the promoter regions of genes of Arabidopsis thaliana. J. Integr. Plant Biol. 2014, 56, 388–399. [Google Scholar]
  50. Hernandez-Garcia, C.M.; Finer, J.J. Identification and validation of promoters and cis-acting regulatory elements. Plant Sci. 2014, 217, 109–119. [Google Scholar] [CrossRef]
  51. Wang, W.; Cheng, Y.; Ruan, M.; Ye, Q.; Yao, Z.; Wang, R.; Zhou, G.; Liu, D.; Wan, H. Comprehensive identification of glutathione peroxidase (GPX) gene family in response to abiotic stress in pepper (Capsicum annuum L.). Gene 2023, 881, 147625. [Google Scholar] [CrossRef] [PubMed]
  52. Islam, T.; Manna, M.; Kaul, T.; Pandey, S.; Reddy, C.S.; Reddy, M. Genome-wide dissection of Arabidopsis and rice for the identification and expression analysis of glutathione peroxidases reveals their stress-specific and overlapping response patterns. Plant Mol. Biol. Report. 2015, 33, 1413–1427. [Google Scholar] [CrossRef]
  53. Miao, Y.; Lv, D.; Wang, P.; Wang, X.-C.; Chen, J.; Miao, C.; Song, C.-P. An Arabidopsis glutathione peroxidase functions as both a redox transducer and a scavenger in abscisic acid and drought stress responses. Plant Cell 2006, 18, 2749–2766. [Google Scholar] [CrossRef] [PubMed]
  54. Rhee, S.Y.; Beavis, W.; Berardini, T.Z.; Chen, G.; Dixon, D.; Doyle, A.; Garcia-Hernandez, M.; Huala, E.; Lander, G.; Montoya, M. The Arabidopsis Information Resource (TAIR): A model organism database providing a centralized, curated gateway to Arabidopsis biology, research materials and community. Nucleic Acids Res. 2003, 31, 224–228. [Google Scholar] [CrossRef] [PubMed]
  55. Finn, R.D.; Clements, J.; Arndt, W.; Miller, B.L.; Wheeler, T.J.; Schreiber, F.; Bateman, A.; Eddy, S.R. HMMER web server: 2015 update. Nucleic Acids Res. 2015, 43, W30–W38. [Google Scholar] [CrossRef] [PubMed]
  56. 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]
  57. Horton, P.; Park, K.-J.; Obayashi, T.; Fujita, N.; Harada, H.; Adams-Collier, C.; Nakai, K. WoLF PSORT: Protein localization predictor. Nucleic Acids Res. 2007, 35, W585–W587. [Google Scholar] [CrossRef] [PubMed]
  58. Artimo, P.; Jonnalagedda, M.; Arnold, K.; Baratin, D.; Csardi, G.; De Castro, E.; Duvaud, S.; Flegel, V.; Fortier, A.; Gasteiger, E. ExPASy: SIB bioinformatics resource portal. Nucleic Acids Res. 2012, 40, W597–W603. [Google Scholar] [CrossRef] [PubMed]
  59. Geourjon, C.; Deleage, G. SOPMA: Significant improvements in protein secondary structure prediction by consensus prediction from multiple alignments. Bioinformatics 1995, 11, 681–684. [Google Scholar] [CrossRef]
  60. Kelley, L.A.; Mezulis, S.; Yates, C.M.; Wass, M.N.; Sternberg, M.J. The Phyre2 web portal for protein modeling, prediction and analysis. Nat. Protoc. 2015, 10, 845–858. [Google Scholar] [CrossRef]
  61. DeLano, W.L. Pymol: An open-source molecular graphics tool. CCP4 Newsl. Protein Crystallogr 2002, 40, 82–92. [Google Scholar]
  62. 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]
  63. Wang, Y.; Tang, H.; Debarry, J.D.; Tan, X.; Li, J.; Wang, X.; Lee, T.-H.; Jin, H.; Marler, B.; Guo, H. MCScanX: A toolkit for detection and evolutionary analysis of gene synteny and collinearity. Nucleic Acids Res. 2012, 40, e49. [Google Scholar] [CrossRef] [PubMed]
  64. Wang, D.; Zhang, Y.; Zhang, Z.; Zhu, J.; Yu, J. KaKs_Calculator 2.0: A toolkit incorporating gamma-series methods and sliding window strategies. Genom. Proteom. Bioinform. 2010, 8, 77–80. [Google Scholar] [CrossRef]
  65. Tamura, K.; Stecher, G.; Kumar, S. MEGA11: Molecular evolutionary genetics analysis version 11. Mol. Biol. Evol. 2021, 38, 3022–3027. [Google Scholar] [CrossRef] [PubMed]
  66. Subramanian, B.; Gao, S.; Lercher, M.J.; Hu, S.; Chen, W.-H. Evolview v3: A webserver for visualization, annotation, and management of phylogenetic trees. Nucleic Acids Res. 2019, 47, W270–W275. [Google Scholar] [CrossRef] [PubMed]
  67. Waterhouse, A.M.; Procter, J.B.; Martin, D.M.; Clamp, M.; Barton, G.J. Jalview Version 2—A multiple sequence alignment editor and analysis workbench. Bioinformatics 2009, 25, 1189–1191. [Google Scholar] [CrossRef] [PubMed]
  68. Hu, B.; Jin, J.; Guo, A.-Y.; Zhang, H.; Luo, J.; Gao, G. GSDS 2.0: An upgraded gene feature visualization server. Bioinformatics 2015, 31, 1296–1297. [Google Scholar] [CrossRef]
  69. 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]
  70. Lescot, M.; Déhais, P.; Thijs, G.; Marchal, K.; Moreau, Y.; Van de Peer, Y.; Rouzé, P.; Rombauts, S. PlantCARE, a database of plant cis-acting regulatory elements and a portal to tools for in silico analysis of promoter sequences. Nucleic Acids Res. 2002, 30, 325–327. [Google Scholar] [CrossRef] [PubMed]
  71. Powell, S.; Forslund, K.; Szklarczyk, D.; Trachana, K.; Roth, A.; Huerta-Cepas, J.; Gabaldon, T.; Rattei, T.; Creevey, C.; Kuhn, M. eggNOG v4. 0: Nested orthology inference across 3686 organisms. Nucleic Acids Res. 2014, 42, D231–D239. [Google Scholar] [CrossRef] [PubMed]
  72. Von Mering, C.; Jensen, L.J.; Kuhn, M.; Chaffron, S.; Doerks, T.; Krüger, B.; Snel, B.; Bork, P. STRING 7—Recent developments in the integration and prediction of protein interactions. Nucleic Acids Res. 2007, 35, D358–D362. [Google Scholar] [CrossRef] [PubMed]
  73. Xue, T.; Hartikainen, H.; Piironen, V. Antioxidative and growth-promoting effect of selenium on senescing lettuce. Plant Soil 2001, 237, 55–61. [Google Scholar] [CrossRef]
  74. 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]
  75. Nei, M.; Kumar, S. Molecular Evolution and Phylogenetics; Oxford University Press: New York, NY, USA, 2000. [Google Scholar]
  76. Kumar, S.; Stecher, G.; Li, M.; Knyaz, C.; Tamura, K. MEGA X: Molecular Evolutionary Genetics Analysis across computing platforms. Mol. Biol. Evolut. 2018, 35, 1547–1549. [Google Scholar] [CrossRef]
Ijms 25 08343 g001
Figure 1. Multiple sequence alignment of GPX protein sequences from pepper, rice, and Arabidopsis. Sequence alignment was performed using the ClusterW method in MAGA11 (V 11.08), and the alignment results were visualized with Jalview (V 1.8.3). The bottom two yellow column areas indicate the degree of base similarity, the black part indicates the common base, and the higher the column, the higher the base similarity. The three conserved domains found in most animal and plant GPXs are marked with black boxes; the amino acid residues that form part of the catalytic sites of GPXs are labeled with different colored triangles, including the strictly conserved Cys (C), Gln (Q), Asn (N), and Trp (W). Other conserved domains are marked with a red box.
Figure 1. Multiple sequence alignment of GPX protein sequences from pepper, rice, and Arabidopsis. Sequence alignment was performed using the ClusterW method in MAGA11 (V 11.08), and the alignment results were visualized with Jalview (V 1.8.3). The bottom two yellow column areas indicate the degree of base similarity, the black part indicates the common base, and the higher the column, the higher the base similarity. The three conserved domains found in most animal and plant GPXs are marked with black boxes; the amino acid residues that form part of the catalytic sites of GPXs are labeled with different colored triangles, including the strictly conserved Cys (C), Gln (Q), Asn (N), and Trp (W). Other conserved domains are marked with a red box.
Ijms 25 08343 g001
Ijms 25 08343 g002
Figure 2. Chromosomal distribution of CaGPXs. The green bars represent chromosomes. The chromosome names are shown at the left of each chromosome. The chromosome scale is in millions of bases (Mb) on the left. The blue line represents a tandem repeat gene pair.
Figure 2. Chromosomal distribution of CaGPXs. The green bars represent chromosomes. The chromosome names are shown at the left of each chromosome. The chromosome scale is in millions of bases (Mb) on the left. The blue line represents a tandem repeat gene pair.
Ijms 25 08343 g002
Ijms 25 08343 g003
Figure 3. Collinearity analysis of the GPX gene family between pepper and Arabidopsis. Gray lines denote the collinear blocks between pepper and Arabidopsis genomes, and the lines of different colors represent collinear gene pairs of GPXs in pepper and Arabidopsis. Different colored squares 1–5 represent Arabidopsis chromosomes and their length, and different colored Ca-1–Ca-12 represents the pepper chromosome and its length. The outermost two circles represent gene density.
Figure 3. Collinearity analysis of the GPX gene family between pepper and Arabidopsis. Gray lines denote the collinear blocks between pepper and Arabidopsis genomes, and the lines of different colors represent collinear gene pairs of GPXs in pepper and Arabidopsis. Different colored squares 1–5 represent Arabidopsis chromosomes and their length, and different colored Ca-1–Ca-12 represents the pepper chromosome and its length. The outermost two circles represent gene density.
Ijms 25 08343 g003
Ijms 25 08343 g004
Figure 4. Phylogenic tree of GPX proteins. Purple triangles represent pepper, black circles represent Arabidopsis, yellow circles represent rice, pink circles represent cucumber, green circles represent watermelon, gray circles represent Rhodiola crenulata, and blue circles represent apple. The phylogenetic tree was constructed by MEGA (V 11.08) using the maximum likelihood method (1000 bootstraps). Different colored areas represent different branches, which are divided into four groups.
Figure 4. Phylogenic tree of GPX proteins. Purple triangles represent pepper, black circles represent Arabidopsis, yellow circles represent rice, pink circles represent cucumber, green circles represent watermelon, gray circles represent Rhodiola crenulata, and blue circles represent apple. The phylogenetic tree was constructed by MEGA (V 11.08) using the maximum likelihood method (1000 bootstraps). Different colored areas represent different branches, which are divided into four groups.
Ijms 25 08343 g004
Ijms 25 08343 g005
Figure 5. Conserved motif and gene structure analysis of GPX family genes. (a) The phylogenetic relationship of GPX in peppers, Arabidopsis, and rice. The tree was constructed by the maximum likelihood method. (b) Distributions of conserved motifs in GPX genes. Each motif is presented with a particular color. (c) The exon/intron structure of the GPXs. Yellow represents exon regions and black lines represent introns. (d) The pattern identification of ten conserved sequences.
Figure 5. Conserved motif and gene structure analysis of GPX family genes. (a) The phylogenetic relationship of GPX in peppers, Arabidopsis, and rice. The tree was constructed by the maximum likelihood method. (b) Distributions of conserved motifs in GPX genes. Each motif is presented with a particular color. (c) The exon/intron structure of the GPXs. Yellow represents exon regions and black lines represent introns. (d) The pattern identification of ten conserved sequences.
Ijms 25 08343 g005
Ijms 25 08343 g006
Figure 6. The distribution of cis-regulatory elements predicted in the CaGPX gene promoter. Different colored boxes represent different cis elements.
Figure 6. The distribution of cis-regulatory elements predicted in the CaGPX gene promoter. Different colored boxes represent different cis elements.
Ijms 25 08343 g006
Ijms 25 08343 g007
Figure 7. Number statistics and element classification of predicted cis-regulatory elements in the CaGPX gene promoter regions. The green part represents the cis-acting elements of biotic/abiotic stress; the red part represents the elements of hormone response; the blue part represents the light response elements, and the yellow part represents the developmental response elements.
Figure 7. Number statistics and element classification of predicted cis-regulatory elements in the CaGPX gene promoter regions. The green part represents the cis-acting elements of biotic/abiotic stress; the red part represents the elements of hormone response; the blue part represents the light response elements, and the yellow part represents the developmental response elements.
Ijms 25 08343 g007
Ijms 25 08343 g008
Figure 8. Interaction network analysis of CaGPX proteins. Protein–protein interaction networks were predicted using STRING. The size of the circle and the depth of the color indicate the number of linked nodes and the degree of the protein in the PPI network.
Figure 8. Interaction network analysis of CaGPX proteins. Protein–protein interaction networks were predicted using STRING. The size of the circle and the depth of the color indicate the number of linked nodes and the degree of the protein in the PPI network.
Ijms 25 08343 g008
Ijms 25 08343 g009
Figure 9. Expression profile analysis of pepper CaGPX genes in different tissues and during fruit development. Note: Pericarp (PC) and placenta (PL) at 6, 16, and 25 days postanthesis (DPA); PC and PL at mature green (MG) and breaker (B) stages; PC and PL at 5 and 10 days postbreaker (B5 and B10, respectively). The FPKM values were log2-transformed, and a heatmap was generated using TBtools software (V 1.118). Expression values are shown as a color gradient from low expression (blue) to high expression (red).
Figure 9. Expression profile analysis of pepper CaGPX genes in different tissues and during fruit development. Note: Pericarp (PC) and placenta (PL) at 6, 16, and 25 days postanthesis (DPA); PC and PL at mature green (MG) and breaker (B) stages; PC and PL at 5 and 10 days postbreaker (B5 and B10, respectively). The FPKM values were log2-transformed, and a heatmap was generated using TBtools software (V 1.118). Expression values are shown as a color gradient from low expression (blue) to high expression (red).
Ijms 25 08343 g009
Ijms 25 08343 g010
Figure 10. Quantitative real-time PCR analysis of CaGPX genes in response to ABA (a), cold (b), PEG (c), and NaCl (d) treatments. The relative gene expression was calculated using the 2−∆∆Ct method with CaActin as an internal control, and the value represents the mean ± SE of three biological replicates. Statistical analyses were carried out by a t-test to determine the differences in gene expression between 0 h and other treatment times. Asterisks indicate values that are significantly different from CK (0 h) (* p < 0.05, ** p < 0.01, one-way ANOVA).
Figure 10. Quantitative real-time PCR analysis of CaGPX genes in response to ABA (a), cold (b), PEG (c), and NaCl (d) treatments. The relative gene expression was calculated using the 2−∆∆Ct method with CaActin as an internal control, and the value represents the mean ± SE of three biological replicates. Statistical analyses were carried out by a t-test to determine the differences in gene expression between 0 h and other treatment times. Asterisks indicate values that are significantly different from CK (0 h) (* p < 0.05, ** p < 0.01, one-way ANOVA).
Ijms 25 08343 g010
Ijms 25 08343 g011
Figure 11. Subcellular localization of CaGPX1 and CaGPX4 proteins in tobacco leaves. GFP signaling displays subcellular localization of Pac402-GFP-CaGPX1 and Pac402-GFP-CaGPX4 proteins. Scale bars represent 20 μm.
Figure 11. Subcellular localization of CaGPX1 and CaGPX4 proteins in tobacco leaves. GFP signaling displays subcellular localization of Pac402-GFP-CaGPX1 and Pac402-GFP-CaGPX4 proteins. Scale bars represent 20 μm.
Ijms 25 08343 g011
Ijms 25 08343 g012
Figure 12. Changes in glutathione peroxidase activity under ABA (a), cold (b), PEG (c), and NaCl (d) treatments. The error bar is the standard error of three independent tests, which are statistically analyzed through a t-test to determine the difference in enzyme activity between 0 h and other treatment times. Asterisks indicate values that are significantly different from CK (0 h) (* p < 0.05, ** p < 0.01, one-way ANOVA).
Figure 12. Changes in glutathione peroxidase activity under ABA (a), cold (b), PEG (c), and NaCl (d) treatments. The error bar is the standard error of three independent tests, which are statistically analyzed through a t-test to determine the difference in enzyme activity between 0 h and other treatment times. Asterisks indicate values that are significantly different from CK (0 h) (* p < 0.05, ** p < 0.01, one-way ANOVA).
Ijms 25 08343 g012
Table 1. Genomic information and protein characteristics of 8 CaGPX gene family members in pepper.
Table 1. Genomic information and protein characteristics of 8 CaGPX gene family members in pepper.
Gene IDGene NameChromosomeGene LocationAmino Acid NumberMolecular Weight (kd)PIInstability IndexAliphatic IndexGrand Average
of Hydropathicity
Start PositionEnd Position
CA.PGAv.1.6.scaffold774.11GPX114864658486751116918,810.488.326.8874.38−0.402
CA.PGAv.1.6.scaffold273.17GPX21493451654935048325028,216.259.4837.8677.2−0.336
CA.PGAv.1.6.scaffold65.187GPX3623172345023172865920022,682.158.1932.286.75−0.148
CA.PGAv.1.6.scaffold1682.18GPX4624144667024145393317018,929.598.8724.8876.82−0.306
CA.PGAv.1.6.scaffold609.2GPX5918010015418011305317018,920.739.5619.4276.82−0.301
CA.PGAv.1.6.scaffold26.15GPX61220275290820275785616919,019.565.0528.9984.2−0.366
CA.PGAv.1.6.scaffold26.14GPX71220294521320296100917019,447.194.9826.7180.24−0.356
CA.PGAv.1.6.scaffold559.5GPX8scaffold559.587979388604023926,537.239.233.0272.18−0.252
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, Z.; Zhang, J.; Wang, C.; Chang, Y.; Han, K.; Gao, Y.; Xie, J. Characterization of GPX Gene Family in Pepper (Capsicum annuum L.) under Abiotic Stress and ABA Treatment. Int. J. Mol. Sci. 2024, 25, 8343. https://doi.org/10.3390/ijms25158343

AMA Style

Zhang Z, Zhang J, Wang C, Chang Y, Han K, Gao Y, Xie J. Characterization of GPX Gene Family in Pepper (Capsicum annuum L.) under Abiotic Stress and ABA Treatment. International Journal of Molecular Sciences. 2024; 25(15):8343. https://doi.org/10.3390/ijms25158343

Chicago/Turabian Style

Zhang, Zeyu, Jing Zhang, Cheng Wang, Youlin Chang, Kangning Han, Yanqiang Gao, and Jianming Xie. 2024. "Characterization of GPX Gene Family in Pepper (Capsicum annuum L.) under Abiotic Stress and ABA Treatment" International Journal of Molecular Sciences 25, no. 15: 8343. https://doi.org/10.3390/ijms25158343

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

Article Metrics

Article metric data becomes available approximately 24 hours after publication online.
Back to TopTop