Salinity-induced changes in gene expression, ion homeostasis, and enzymatic antioxidants in contrasting wheat genotypes

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Hasseb, Mohamed A. Karam, Andreas Börner, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7186942/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Salinity is a major constraint on plant development and crop production for main crops such as wheat, which is the most important source of calories, especially at early stages of growth, including seed germination and seedling establishment. Salinity tolerance is a complex trait tailored by several mechanisms, including ion homeostasis, the activation of enzymatic antioxidants, and the alteration of ion transporter genes. Contrasting genotypes of wheat that differed in salinity tolerance were selected from a collection of 172 that were tested under salinity stress (175 mM NaCl) and the control (0 mM NaCl), with the aim of revealing the underlying mechanisms of salinity tolerance in the tolerant genotypes compared with the sensitive ones. These parameters, Na, K and P homeostasis; the presence of enzymatic antioxidants; and the expression profiles of the salinity-responsive ion transporter genes TaAVP1 and NHX1 were measured in one sensitive and six tolerant genotypes. The tolerant genotypes presented higher concentrations of Na + and K + and higher levels of all the enzymatic antioxidants than did the sensitive ones. The tolerant genotypes differentially expressed AVP1 and NHX1 , which were upregulated in Javelin 48 and Kandahar but downregulated in the tolerant genotype 1018d. These results indicate that the tolerant genotypes differentially expressed the ion transporter genes AVP1 and NHX1 . The tolerant genotype Kule presented the highest Na + content and the greatest increase in the levels of the antioxidant enzymes ascorbate peroxidase and glutathione reductase, with 9.20-fold and 2.32-fold changes, respectively, under salinity stress. In conclusion, the tolerant genotypes differed in their response to salinity stress and employed various mechanisms to tolerate salinity. Wheat salinity gene expression AVP1 NHX1 ion homeostasis antioxidants Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Wheat is the prominent staple food of the human diet, but its production is under various threats due to climate change. Salinity represents a major challenge for plant growth and crop productivity. Throughout the plant life cycle, seed germination and early seedling development are the stages with the greatest salinity sensitivity. Salinity can postpone the initiation of germination, slow its progression, and cause greater variability in germination timing, ultimately resulting in reduced plant growth and lower final crop yields [ 1 ]. However, plant species exhibit a wide range of tolerances to salinity, as demonstrated by their ability to thrive in environments ranging from freshwater habitats to highly saline areas. Even among crop plants, there is notable variation in salt tolerance both between species and within a single species. These findings highlight two key points: (1) crop plants have the potential to adapt to saline conditions, and (2) intraspecific variation offers valuable opportunities to study the mechanisms of salt tolerance and sensitivity [ 2 – 4 ]. Ionic imbalance and deficiency are among the consequences of salinity stress [ 5 ]. The effects of salinity on the nutrient composition of plant tissues have been widely studied, and many researchers have confirmed that the deleterious effects of salinity on plant growth can be caused by an ionic imbalance, especially of calcium and potassium ions [ 6 ]. The accumulation of high levels of ions is more costly than the assimilation of carbon in the form of organic solutes [ 7 – 9 ]. During seed germination and the establishment of young seedlings, the mineral nutrient reserves in the seed must be sufficient to support the growth of the seedling to the point of self-sufficiency [ 10 ]. Thus, plants must maintain a relatively high concentration of potassium if they are to grow in a saline soil environment [ 11 ]. Potassium is an important macroelement that represents up to 10% of the dry matter of the cell and plays a fundamental role in maintaining the water state of the plant, stomatal movement, enzyme activity, osmoregulation and membrane stability [ 12 – 14 ]. Maintaining high K + /Na + ratios is considered among the selection criteria for salt tolerance [ 15 ]. However, sodium is unusual as a nutrient for life because it is a nonessential element for most plants [ 16 ]. Under salinity stress, potassium competes for plant uptake through high-affinity potassium transporters and nonselective cation channels, resulting in membrane depolarization, and plants cannot discriminate between Na and K ions [ 17 , 18 ]. However, sodium is known to cause the most deleterious effect of salinity, and its exclusion is effective for conferring salinity tolerance. The sequestration of high levels of Na + confers salinity tolerance in barley, and Na + might act as an osmolyte or a nutrient to compensate for K + deficiency [ 19 ]. Similar results have been reported in other cereals, such as rice [ 20 ] and maize [ 21 ], where high levels of Na + in the cell vacuole can increase salinity tolerance [ 22 , 23 ]. Phosphorus (P) is an important macronutrient for plant growth and development and plays a crucial role in energy production, DNA synthesis and salinity tolerance during seed germination [ 24 ]. The phosphorus content decreased in seedlings of cotton, wheat, barley and faba bean under salinity stress [ 25 ]. However, balanced production and scavenging of ROS are highly important for seed germination, suggesting that seed germination and ROS production are coupled [ 26 , 27 ]. Many studies have reported the induction and accumulation of high levels of both reactive oxygen species and plant antioxidants in relation to salt stress. High levels of ROS can disturb normal metabolism by oxidizing lipids, proteins, and nucleic acids in the absence of protective systems. It is now widely accepted that reactive oxygen species are responsible for various types of stress-induced damage to macromolecules and ultimately to the cellular structure [ 28 – 31 ]. Plants have a well-developed complex antioxidant system that includes enzymatic and nonenzymatic antioxidant processes to intercept ROS. The antioxidant enzymes include superoxide dismutase (SOD), catalase (CAT), peroxidase (POD), and ascorbate peroxidase (APX) [ 32 ]. The antioxidant enzymes SOD, CAT, GR, and APX detoxify H 2 O 2 . The activity of all of these antioxidant enzymes increases under salinity stress during seed germination and seedling establishment in wheat, maize and barley in synchrony with the overproduction of ROS [ 31 , 33 , 34 ]. The response of plants to environmental cues is under polygenic control. Exploring the connection between gene expression and physiological mechanisms remains a bottleneck in selection for improving plant tolerance to these cues [ 35 ]. Approximately 19% of wheat genes are salt responsive (Kawaura et al., 2008). Salt tolerance in wheat has been suggested to be regulated primarily by the activation of transporter genes (Nakayama et al., 2022). Among them are the vacuolar pyro phosphatase (V-PPase) and the Na + /H + antiporter. TAVP1 expression was equivalent to that of vacuolar Na + /H + antiporters in several plant species, indicating that TAVP1 generates a proton gradient that is essential for energizing TNHX1 , which in turn controls vacuolar Na + sequestration, as reviewed by Mansour, (2022). Both V-PPase and tonoplast Na + /H + are more active in salt-tolerant genotypes than in sensitive genotypes in both rice and citrus [ 39 , 40 ]. The overexpression of Arabidopsis V-PPase improved salinity tolerance in alfalfa, and the resulting transgenic plants accumulated high levels of Na, K and Ca ions [ 41 ]. Compared with control plants, transgenic plants of finger millet overexpressing sbVPPase from sorghum presented higher antioxidant levels and accumulated more Na, K and Ca under 100 mM NaCl and 200 mM NaCl stress [ 42 ]. In two contrasting wheat genotypes, with respect to salinity tolerance, the expression levels of TVP1 were similar to those of the vacuolar Na + /H + antiporter TNHX1 in different tissues of the two genotypes [ 43 ]. In barley, HVP10 was upregulated under salinity stress, and the transgenic plants of rice overexpressing HVP10 sequestered more Na + in vacuoles and, in turn, presented greater salt tolerance than did the wild-type plants [ 44 ]. The current study aims to understand the intraspecific variation in the salinity response to study the mechanisms of salt tolerance and sensitivity in wheat. The objectives of the present study were to 1) investigate the molecular basis of salinity tolerance by analyzing the expression patterns of key ion transporter genes ( TaAVP1 and NHX1 ) in tolerant and sensitive genotypes to elucidate their contributions to ion homeostasis, 2) evaluate the physiological responses associated with salinity tolerance during early development in contrasting wheat genotypes, focusing on ion homeostasis (Na⁺/K⁺ balance) and antioxidant enzyme activity under salt stress, and 3) elucidate the role of intraspecific variation in salinity tolerance and sensitivity. Materials and methods Plant material and experimental design The details of the germination experiment and a full description of the plant materials are provided in Hasseb et al. (2022). Briefly, in a complete randomized block design with three replicates, a set of 176 highly diverse wheat genotypes was tested during seed germination and seedling establishment; 0 mM NaCl was used for the control, and 175 mM NaCl was used for salinity stress. The data resulting from that experiment were used for genome-wide association analysis (GWAS) (Hasseb et al. 2022). On the basis of their performance, 12 contrasting genotypes (6 salinity-tolerant + 6 salinity-sensitive) were selected as the most salinity-tolerant and the most salinity-sensitive genotypes. Among those 10 genotypes, seven genotypes were selected for the analyses of ion concentrations and enzymatic antioxidants. Among the seven genotypes, four (1 sensitive + 3 tolerant) were used for gene expression (Table 1 ). Table 1 The gene bank ID, accession name, origin, and classification of the seven contrasting genotypes (6 tolerant genotypes and 1 sensitive genotype) Gene bank ID Accession name Country Character Na and K traits Antioxidant Enzymes Activities Gene expression PI 220127 Kandahar Afghanistan Tolerant √ √ √ PI 542666 Ghati Algeria Tolerant √ √ PI 201414 Gavelin 48 Australia Tolerant √ √ √ PI 525241 1049 Morocco Tolerant √ √ PI525221 1018d Morocco Tolerant √ √ √ PI532249 Kule Oman Tolerant √ √ 122 Sohag-5 Egypt Sensitive √ √ √ Antioxidant enzyme activities Extraction The antioxidant enzyme activities of superoxide dismutase (SOD, EC 1.15.1.1), ascorbate peroxidase (APX, EC 1.11.1.11), catalase (CAT, EC 1.11.1.6), and glutathione (GR, EC 1.6.4.2) were estimated in homogenates extracted from seedling tissue samples. All the homogenates were centrifuged at 4°C in a refrigerated centrifuge at 15,000xg for 15 min. The supernatant was used to assay the enzymatic activity at the corresponding wavelength for each enzyme. Superoxide dismutase assay SOD activity was estimated according to Dhindsa et al., (1981) by recording the decrease in the absorbance of the superoxide nitro blue tetrazolium complex by the enzyme at 560 nm. Approximately 3 ml of the reaction mixture, containing 0.1 ml of 200 mM methionine, 0.1 ml of 2.25 mM nitro blue tetrazolium (NBT), 0.1 ml of 3 mM ethylene diamine tetra acetic acid (EDTA), 1.5 ml of 100 mM potassium phosphate buffer, 1 ml of distilled water and 0.05 ml of extracted enzyme, was taken from each sample in duplicate tubes. Additionally, two control tubes were prepared without enzyme extraction. The reaction was started by adding 0.1 ml of riboflavin (60 µm) to all the tubes placed under a light source of two florescent lamps (15 W) for 15 min. The reaction was stopped after the light was turned off and the tubes were covered with dark covers. The maximum color developed in the tubes without the enzyme. A non-irradiated complete reaction mixture that did not produce color was used as a blank. Ascorbate peroxidase assay APX activity was estimated at 290 nm according to Nakano and Asada, (1980) via spectrophotometric monitoring of the decrease in absorbance as an indicator of the rate of ascorbate oxidation. The reaction mixture contained 25 mM phosphate buffer (pH = 7), 0.1 mm ethylene diamine tetra acetic acid (EDTA), 1 mm hydrogen peroxide, 0.25 mm AsA and the enzyme sample. Catalase assay The activity of CAT was used to estimate the rate of H2O2 decomposition at 240 nm following [ 47 ]. Approximately 3 ml of the reaction mixture contained 1.5 ml of 100 mm buffered potassium phosphate (pH = 7), 0.5 ml of 75 mm hydrogen peroxide, 0.05 ml of extracted enzyme mixture and distilled water. When H2O2 was added, the reaction started, and the decrease in absorbance was recorded for 1 min. Glutathione reductase assay GR activity was estimated in the presence of oxidized glutathione (GSSG) and 5,5-dithiobis-2-nitrobenzoic acid (DTNB) by recording the increase in absorbance according to Smith et al., (1988). The reaction mixture consisted of 1 ml of 0.2 M potassium phosphate buffer (pH = 7.5) containing 0.1 mM EDTA, 0.5 ml of 3 mM DTNB in 0.01 M potassium phosphate buffer (pH = 7.5), 0.1 ml of 2 mM NADPH, 0.1 ml of enzyme extract and distilled water to make up a final volume of 2.9 ml. When 0.1 2 mM GSSG was added, the reaction started. The increase in absorbance at 412 nm was recorded at 25°C over a period of 5 min via a spectrophotometer. Estimation of sodium (Na), potassium (K) and phosphorus (P) contents : The samples were dried at 80°C for 72 h. A coffee grinder was used to pulverize the dried samples to measure the sodium and potassium concentrations. One day before digestion, the samples were dried overnight at 100°C. In a microwave-assisted acid digestion system (Anton Paar Multiwave 5000, Graz, Austria), 0.5 g from each sample was placed in a vessel with 10 ml of nitric acid. At 175°C, the samples were placed in the microwave system for 10 minutes (heated to 175°C in 5.5 minutes and maintained for 4.5 minutes). After cooling, the samples were diluted to 50 ml with deionized water. The Na, K, and P contents were estimated from the atomic absorbance. The K + /Na + ratio was calculated according to the Na + and K + concentrations. The fold changes in Na, K and P contents were computed as the content under salinity relative to the content under the control. Total inorganic phosphate (Pi) was quantified by adding ammonium vanadomolybdate reagent and measuring the absorbance at 470 nm via a UV/Vis spectrophotometer. Gene expression analysis Gene expression analysis was performed on four contrasting genotypes (three tolerant and one sensitive) under control and salt stress conditions. The expression levels of two genes were compared among the four genotypes under control conditions and salinity stress. These two genes, AK4544458/TaAffx.25629.1S1 (vacuolar pyrophosphates similar to AVP1 ) and AY296910 (Na + /H + vacuolar antiporter “ NHX1 ”), were previously reported Mott & Wang, (2007). The sequences of the forward and reverse primers corresponding to these genes are listed in Table 2. RNA extraction, cDNA preparation, and real-time PCR Like the germination conditions, the same concentrations of sodium chloride (0 mM NaCl) for the control and (175 mM NaCl) for salinity stress were applied to the four selected genotypes. Three biological samples were collected from leaves of each genotype (0.1 g for each replication). The leaves of all the samples were transferred immediately to liquid nitrogen and stored at -80°C until further analysis. The RNA was extracted via an RNeasy Plant Mini Kit (Qiagen, Valencia, CA, USA). To obtain purified RNA, all the samples were treated with RNase-free DNase I (Thermo Fisher Scientific, USA). Complementary DNA (cDNA) was prepared with a Revert Aid First Strand cDNA Synthesis Kit according to the manufacturer’s protocol. (Thermo Fisher Scientific, USA). Finally, all the samples were prepared for real-time PCR via Maxima SYBR Green/ROX qPCR Master Mix (2X) (Thermo Fisher Scientific, USA). The thermocycling was performed under the following conditions: 2 min at 50°C, 10 min at 95°C, and 40 cycles alternating between 15 s at 95°C and 1 min at 60°C. The expression levels for each sample from each genotype under both treatments were analyzed in three biological replicates and calculated via the 2 − ΔΔCT method. Accession number/probe set Annotation/predicted function Primer sequence (5'-3') Amplicon (bp) Reference AK4544458/TaAffx.25629.1.S1 Vacuolar pyro phosphatase similar to AVP1 ( TaAVP1 ) Fwd GACCGGTCTTGCCATTGATG 162 Mott and Wang (2007) Rev CTGAGCCAATTGCGAATCCC AY296910 Na + /H + antiporter ( NHX1 ) Fwd GCCTGGTTCACCCATAGAGA Rev CACCGAAAGAATCCCAAGAG 159 Mott and Wang (2007 Data analysis The analysis of variance (ANOVA) was calculated under control and salt stress conditions via PLABSTAT software (43) and the R package (44) via the following statistical model: Y ijk = µ + g i + r j + t k + t ik + tgr ijk stress) k, µ is the general mean value; gi, rj, tk are the main effects of genotype, replication, and treatment, respectively. tik represents the genotype × treatment interaction. tgrijk represents the genotype × replication × treatment interaction (error). Broad-sense heritability ( H 2 ) was estimated via PLABSTAT via the following equation: $$\:{H}^{2}=\:\frac{{\sigma\:}_{G}^{2}}{{\sigma\:}_{G}^{2}+\left(\frac{{\sigma\:}_{GR}^{2}}{r}\right)}$$ where G refers to genotypes and where r refers to replications. Phenotypic correlation analysis was performed via PLABSTAT. Correlation coefficients ranging from 0–39, 0.40–0.60 and above 0.60 were considered low, moderate, and high correlations, respectively. The data visualization for all the parameters was conducted via SRplot: A free online platform for data visualization and graphing [ 50 ] and Excel 365 [ 51 ]. Results Sodium (Na), potassium (K) and phosphorus (P)-related traits : The Na + , K + , K + /Na + , Na + /K + , and P contents and ratios were measured and calculated for 7 contrasting genotypes: one sensitive genotype (Soha-5; from Egypt) and six tolerant genotypes (Table 1 ). All the genotypes presented an increase in Na content under salinity stress (175 mM NaCl) compared with the control (0 mM NaCl), including some of the tolerant genotypes (Supplementary Fig. 1). The fold change in Na content under salinity relative to the control (Na-S/Na-C) was very dramatic in the sensitive genotype Sohag-5 from Egypt, with a 9.95-fold change, and three of the tolerant genotypes, Kandahar from Afghanistan, 1049 and 1018 d from Morocco, and Kule from Oman, with folding changes of 11.40, 10.62, and 12.79, respectively (Fig. 1). Moreover, the tolerant genotypes presented different levels of Na, and the genotypes Ghati from Algeria and Javelin 48 from Australia presented the lowest levels of Na under salinity stress, with 1.51- and 1.43-fold changes, respectively. The K content decreased in all the genotypes except at Javelin 48 and 1018d, whereas it did not change in Kule (Fig. 1). As expected, for the K and Na ratios under the control conditions, the K + /Na + (K + /Na + -C) ratio was high for all the genotypes and varied from 2.91 for Kule to 5.02 for 1018d. The sensitive genotype Sohag-5 had a ratio of 4.61. Under salinity, the K + /Na + (K + /Na + -S) ratio decreased in all the genotypes; in the tolerant group, it ranged from 0.23 for Kule to 3.20 for Javelin 48. The sensitive genotype Sohag-5 had a ratio of 0.38 (Fig. 2). In contrast, under salinity, the Na + /K + (Na + /K + -S) ratio was very low in all the genotypes under the control conditions, ranging from 0.20 for 1018 d to 0.30 for Ghati, and the sensitive genotype Sohag-5 had a ratio of 0.22. Moreover, with respect to salinity, it was very high, with values of 0.31, 0.39 and 0.44 for Gavelin 48, 1018d and Ghati, respectively. The sensitive genotype Sohag-5 had a ratio of 2.65. With respect to the P content, under salinity, all the genotypes presented a high reduction in P content except for the tolerant genotypes 1018d and Kule (Fig. 2). The activity of antioxidant enzymes under control conditions and salt stress The activities of the antioxidant enzymes superoxide dismutase (SOD), catalase (CAT), glutathione reductase (GR) and ascorbate peroxidase (APX) were estimated in 7 contrasting genotypes under the control (0 mM NaCl) and salinity (175 mM NaCl) treatments. The enzyme activity of all the enzymes varied among the sensitive and tolerant genotypes (Fig. 3). Compared with that of the control, the activity of ascorbate peroxidase increased under salinity stress for all 7 genotypes (Fig. 3). Sohag-5 (the sensitive genotype) showed a 6.65-fold change. Among the tolerant genotypes, Ghati presented the greatest fold change, with a 14.1-fold change, followed by Kule, with a 9.20-fold change, while 1018d presented no change (Fig. 4). The activity of catalase increased under salinity for all the genotypes, including the sensitive cultivar Sohag-5 (Fig. 3). The greatest increase in CAT activity was recorded by Javelin 48, whereas CAT activity decreased in the two tolerant genotypes, Ghati and Kule (Fig. 4). SOD activity decreased in Sohag-5, whereas it increased in all of the tolerant genotypes (Fig. 3). The greatest increase was recorded in Kule (2.32-fold change), and the lowest increase was recorded in Kandahar, with a 1.03-fold change (Fig. 4). The activity of glutathione reductase increased under salinity for all the genotypes except for the two tolerant genotypes 1048d and Kule (Fig. 3). Javelin 48 exhibited the greatest increase, with a 7.80-fold change, and Kandahar presented the lowest fold change, with a value of 1.79 (Fig. 4). Sohag-5 presented an increase in GR activity of 1.39-fold (Fig. 4). Analysis of variance (ANOVA) : The analysis of variance for all measured traits revealed highly significant genotypic (G) and G × E variations (p ≤ 0.01) (Table 3 ). These findings indicate that wide genetic variability exists among the genotypes in terms of ion homeostasis, ion-related traits, and key enzymatic antioxidants, which are valuable for further selection and breeding of genotypes with superior ionic homeostasis and antioxidant responses under salinity stress. Significant treatment effects were detected for most traits; the most significant variation was observed for K⁺/Na⁺ (p ≤ 0.01) and for Na⁺, Na⁺/K⁺, SOD, and APX ( p ≤ 0.05 or p ≤ 0.1) (Table 3 ). Moreover, K + , CAT and GR were not significantly associated with the salinity treatment. The replication effect was not significant except for that of Na⁺ and CAT. The genotypic-environmental effect was significant for all traits (p ≤ 0.01), indicating the importance of testing these genotypes under various environmental conditions to select the most environmentally stable genotypes. The heritability estimates were very high, ranging from 94 for K + and SOD, 98 for K + /Na + and GR, and 99 for Na + , Na + /K + , P, APX, and CAT (Table 3 ). These high heritabilities indicate that these traits are under high genetic factor control. Table 3 Analysis of variance (ANOVA) and heritability of sodium and potassium traits and antioxidant enzyme activities in 7 contrasting genotypes. Source of Variance K + Na + K + /Na + Na + /K + P APX CAT GR SOD Treatments 0.97 8.58* 26.36** 8.30* 0.89 11.26* 0.92 1.97 5.98 + Replications 1.47 6.21** 0.38 3.31 + 0.18 0.11 4.94* 1.88 2.35 Genotypes 93.93** 5910.30** 390.57** 1151.24** 9018.13** 2148.59** 4565.21** 392.11** 89.85** Treatment × Genotype 57.25** 5455.80** 332.69** 1098.89** 12438.75** 965.85** 605.26** 565.14** 42.63** Heritability 94 99 98 99 99 99 99 98 94 *, **, and *** represent significance levels of P ≤ 0.05, 0.01 and 0.001, respectively. Correlation analysis 4.1.1 Correlation coefficients for the traits of the 7 contrasting genotypes When the traits of interest were controlled for, the significant positive and negative correlations were low to highly significant (Supplementary Fig. 2a, b). Positive and significant correlations were detected between APX-C and FW-C, with r = 0.82*, CAT-C and K/Na-C, with r = 0.77*, and between Na-C and Na/K-C, with r = 0.77*. Negative and significant correlations were observed between Na-C and GR-C (r =-0.83*), K/Na-C and Na-C (r=-80*), and Na/K-C with K/Na-C and CAT-C (r=-99*** and − 83*, respectively). Unexpectedly, P-C was highly negatively correlated with APX-C and FW-C (r=-99*** and − 0.76, respectively). No significant correlations were detected among the enzyme-related traits (Supplementary Fig. 2a). Under salinity, the correlations ranged from high to very high in terms of negative significance and high positive significance (Figure b). Strong positive correlations were detected between SOD-S and RL-S (r = 0.93***) and between Na/K-S and Na-S (r = 0.99***). Highly significant correlations were observed between K/Na-S and Na/K-C and Na-S (r=-99** and 0.99**, respectively). Additionally, under salinity, no significant correlations were detected among the enzymatic activity-related traits (Supplementary Fig. 2b). To consider the expected correlations between the gene expression of the two genes AVP1 and NHX1 , we conducted a correlation analysis for the four genotypes that were considered for gene expression analysis. Under the control, the expression of the AVP1 gene was highly significantly positively correlated with SL-C (r = 96*), RSR-C (r = 0.99**), and K/Na-C (r = 0.95*). Moreover, it was significantly negatively correlated with Na/K-C (r=-0.97*). Under salinity, AVP1 showed a highly positive significant correlation with RSR-S (r = 0.99*). The expression of NHX1-C was highly positively and significantly correlated with that of NHX1-S (r = 99*) (Fig. 5). For the remaining control traits, P-C was negatively and significantly correlated with APX-C (r=-99*), K-C was strongly positively correlated with Na-S and Na/K-S (r = 0.99** and 1.00**, respectively), and K-C was strongly negatively correlated with K/Na-S (r=-0.98*). Under salinity, SL-S exhibited very high positive and significant correlations with G%-S and FW-S (r = 0.99* and 0.96*, respectively). CAT-S was positively and significantly correlated with APX-C (r = 0.96*); likewise, GR-S was positively and significantly correlated with RSR-C and CAT-C, with r = 0.97* and 0.97*, respectively. SOD-S and RL-S were positively and significantly correlated, with r = 0.95*. K/Na-S exhibited very high negative and positive correlations with K/Na-S and Na-S (r=-0.99* and 0.99**, respectively) (Fig. 5). Bidirectional clustering heatmap for all traits under control and salinity conditions : In the first level of clustering, the genotypes were clustered according to their performance under control and salinity conditions into two main clusters. The first cluster included the genotypes under control conditions, and the second cluster included the genotypes under saline conditions. The first cluster is subdivided into two subclusters: the first subcluster includes three tolerant genotypes; 1018d clustered separately, and Javelin 48 and Ghati clustered together. The second subcluster includes the remaining four genotypes; 1049 (tolerant) and Soha-5 (sensitive) are grouped together, whereas Kandahar and Kule are grouped together. Similarly, the second main cluster (genotypes under salinity) was further subdivided into two subclusters, in which the genotypes presented the same clustering pattern as the control (Fig. 6). The second level of clustering was for traits; at this level, the traits were subdivided into two major clusters. The first major cluster included all of the morphological traits except NoR; moreover, it included two physiological traits, P and K/Na. The first cluster was subdivided into three subclusters; the P content was separated into the first subcluster, the second subcluster included the RSR, and the third subcluster included the GP and RL. Similarly, the second cluster was subclustered into subcluster one, which included FW and G%, and subcluster two, which included SL and K/Na. The second major cluster included enzyme activity-related traits and Na-, K-, and P-related traits. It was further subdivided into two subclusters, and CAT and K were clustered into the first subcluster. Moreover, the second subcluster includes four subclusters: the first includes Na and Na/K, the second includes APX, the third includes SOD, and the fourth includes NoR and GR (Fig. 6). Principal component analysis (PCA) for all traits under control and salinity conditions : In the biplot, at the trait level, the first PCA1 and the second PCA explained 34.5% and 15.7%, respectively (Fig. 7a). The traits were clustered into two main groups. The first group (red group) included the traits that accounted for the greatest proportion of variation under the control treatment, and the second group (blue group) included the traits that accounted for the greatest proportion of variation under salinity. The opposite directions of the arrows may reflect the correlations between these traits; for example, K/Na and Na/K exhibited the highest negative correlation, with r=-1.00***. The length of the arrow indicates the contribution of the corresponding trait to the variation among the genotypes under a certain treatment. For example, K/Na and RL are the most discriminative factors under control, whereas Na and Na/K are the most discriminative factors among the genotypes under salinity (Fig. 7a). At the genotype level, similar to bibelot, PCA1 and PCA explained 34.5% and 15.7%, respectively, of the variation (Fig. 7b). The genotypes were grouped into two groups. The first group (red group) shows the performance of the genotypes under the control, and the second group (blue group) presents the performance of the genotypes under salinity. Notably, genotypes such as Kule, Javelin 48, and Ghati presented strong (genotype × treatment) interactions and occupied distinct positions across both PCA1 and PCA2 (Fig. 7b). The sensitive genotype Sohag-5 shows relatively modest (genotype × treatment) interactions, with small shifts across both PCA1 and PCA2 (Fig. 7b). Gene expression profiling of the vacuolar pyro phosphatase ( AVP1 ) gene and the Na + /H + antiporter ( NHX1 ) gene under control conditions and salt stress The expression patterns of both the Vacuolar pyro phosphatase gene, similar to AVP1 ( TaAVP1 ), and the Na + /H + antiporter ( NHX1 ) gene were previously reported in salt-tolerant Chinese wheat [ 49 ]. The seven contrasting genotypes were used for measuring the Na and K contents and antioxidant enzyme activities. Four contrasting genotypes, including the sensitive genotype 122 (Sohag-5, from Egypt) and three tolerant genotypes Javelin 48, from South Australia, Kandahar, from Afghanistan and 1018d, from Morocco, were selected to quantify the gene expression patterns of both genes under control and salinity conditions (Table 1 ). Under salinity relative to the control, both genes presented low- to moderate-fold changes (Supplementary Fig. 3). The two genes presented different expression patterns in the sensitive genotype (Sohag-5); AVP1 was slightly upregulated, with a 1.05-fold change, whereas NHX1 did not change. The tolerant genotypes differentially expressed both the AVP1 and NHX1 genes. The AVP1 gene was upregulated the most in Javelin 48, with a 1.43-fold change, followed by Kandahar, with a 1.05-fold change; meanwhile, 1018d was differentially expressed, and TaAVP1 was downregulated (Fig. 8, Supplementary Fig. 3). Similarly, for the NHX1 gene , the three tolerant genotypes presented different profiles: Javelin 48 presented the greatest upregulation, with a 1.42-fold change, followed by Kandahar, with a 1.16-fold change, while 1018d presented different patterns, and NHX1 was downregulated (Fig. 8, Supplementary Fig. 3). Discussion As plants cannot escape abiotic stresses such as salinity, plants have developed various mechanisms to combat the damaging effects of these stresses. Salinity causes alterations in all plant parts, extending from a single cell to the whole plant. The response of plants to salinity encompasses changes in several pathways, such as ion homeostasis, antioxidant machinery activation and changes in the genes that regulate ion cycling via exclusion and sequestration. Notably, ion homeostasis via exclusion or vacuolar sequestration is a profound mechanism for salinity tolerance. The genotypes included in the current study revealed highly significant genotypic variation ( p ≤ 0.01 ) for all measured traits (Table 3 ). This suggests that considerable genetic diversity exists among the tested genotypes regarding both ion-related traits (K⁺, Na⁺, K⁺/Na⁺, Na⁺/K⁺, P) and antioxidant enzyme activities (SOD, CAT, APX, GR), indicating that these traits represent valuable selection criteria for salinity tolerance in wheat. Given the high heritability and strong genetic control observed (0.94 to 0.99), this finding highlights the considerable genetic control of the measured traits and substantial genetic gains. These findings indicate the potential for genetic improvement through selection of genotypes with superior ionic homeostasis and antioxidant responses under salinity stress. In terms of the genotypic response to salinity, Sohag-5 consistently clustered separately from the tolerant genotypes under salinity conditions, confirming its divergent response profile, whereas the tolerant genotypes (especially Kandahar, 1018d, and Kule) grouped closely, reflecting adaptive traits shared under salinity stress (Fig. 6). Compared with the Sohag-5-sensitive genotype, the Sohag-5-tolerant genotype presented greater genotypic plasticity, which was reflected by the narrow plasticity of the Sohag-5-tolerant genotype, which was reflected by its placement under control and salinity conditions (Fig. 7b). Roles of mineral-related traits and antioxidant enzymes in salinity tolerance Our results revealed that the sensitive genotype (Sohag-5) accumulated high levels of Na + under salinity compared with the control. The tolerant genotypes presented different responses and were subdivided into two groups. The first group included Javelin 48, Ghati and 1018d, which maintained low levels of Na, low Na + /K + values, high K values and high K + /Na + values under salinity stress (Supplementary Fig. 1). The second group included Kandahar, Kule and 1049, which maintained high levels of Na, low levels of K, high Na + /K + and low K + /Na + (Supplementary Fig. 1). These results indicate that tolerant genotypes have different mechanisms to tolerate salinity. More likely, Javelin 48 and Ghati can exclude excess Na + and retain the Na + and K + levels at healthy concentrations for all biological processes. On the other hand, salt-tolerant Na + accumulators can use it to maintain osmotic adjustment to maintain the water uptake rate. Our findings revealed that the tolerant genotypes accumulated high concentrations of K + except for Kanda; nevertheless, it is still among the tolerant genotypes that might benefit from the accumulation of excess Na + . Similarly, in young Arabidopsis seedlings, natural variation in salinity tolerance is achieved by maintaining high K + and K + and K + /Na + ratios in the most tolerant genotypes [ 52 ]. In support of our results, in both Arabidopsis and wheat at the seedling stage, high K + concentrations maintain plant growth under salinity stress by maintaining a high K + /Na + ratio, decreasing the Na + /K + ratio, reducing reactive oxygen species production and increasing the activity of antioxidant enzymes [ 52 , 53 ]. The retention of high K + under salinity stress confers salinity tolerance in various cereals, including rice [ 54 ], wheat [ 55 ] and barley [ 56 ]. Potassium is a key player in conferring salinity tolerance by tailoring various biological processes [ 57 ]. In line with our results, several studies reported that K + /Na + is essential for salinity tolerance in bread wheat [ 58 ], barley [ 59 ], and maize [ 60 ]. Notably, the tolerant genotypes Kandahar, 1049 and Kule maintained high Na + even more than the most sensitive genotype (Sohag-5) did (Supplementary Fig. 1); more likely, they have other mechanisms that tailor their salinity tolerance. Compared with the remaining tolerant genotypes, they likely presented more efficient portioning and localization of the excessive Na content; the greatest increase in Na content under salinity relative to the control was 10.62-, 11.40- and 12.79-fold greater for 1049, Kandahar and Kuli, respectively, and presented the highest Na/K ratios (Fig. 1, Supplementary Fig. 1). Moreover, Kule maintained the highest P content under salinity, which may help in seedling growth or as an osmoticum. In support of our results, salinity- and sodality-tolerant wheat lines retained high levels of Na + [ 61 ], demonstrating that salinity tolerance can be conferred by the use of Na + for osmotic adjustment. Under salinity stress, K + uptake is reduced; in such cases, Na + represents a cheap osmoticum that can replace the biosynthesis of organic osmolytes, which is time- and energy-consuming for the cells (Munns et al., 2020b; Shabala et al., 2020). Additionally, Na + can compensate for K + deficiency, enabling continuous shoot growth (Shabala et al., 2020). Phosphorus availability helps maintain other essential minerals, such as Mg 2+ , and Na + exclusion (reviewed by Khan et al., 2023). Ashraf et al., (2023) reported that, in wheat, salinity stress increased the Na + content in both salt-tolerant and salt-sensitive genotypes; nevertheless, the tolerant genotypes presented high K + /Na + ratios compared with the sensitive genotypes. Similarly, six Malawian tomato cultivars were evaluated for salinity tolerance under 200 mM NaCl, and the tolerant cultivar retained high K + and low Na + and, in turn, high K + /Na + relative to the sensitive cultivar [ 66 ]. In the present study, all the genotypes presented increased antioxidant enzyme activities, with the exception of SOD in Sohag-5, GR in 1018d, and CAT and GR in Kule (Fig. 3). The increase in SOD is expected, as SOD represents the frontline of a plant’s ROS scavenging system. SOD catalyzes the first step to neutralize ROS via the conversion of O 2 to H 2 O 2, which remains toxic to the cell; therefore, it is catalyzed by CAT into H 2 O and O 2 [ 67 , 68 ]. In line with our results, an increase in SOD activity was observed under salinity stress in tolerant wheat genotypes at the seedling stage [ 65 ]. Similarly, in wheat at the seedling stage, compared with the control treatment, the 120 mM NaCl treatment increased the SOD level (Rady et al., 2019a). Our results revealed that SOD was highly positively correlated with RL_S, r = 0.93*** (Fig. 4b). SOD activity increased in all the genotypes but decreased in Sohag-5, indicating that SOD activity is involved in salinity tolerance. SOD improved plant growth under salinity stress in Arabidopsis [ 70 ]. The APX activity increased in all the genotypes, including the sensitive genotype Sohag-5, and the increase was more pronounced in the tolerant genotype (Fig. 3). These results suggest that APX contributes to the salinity tolerance of tolerant genotypes, even those with high Na contents. For example, the APX activity of Ghati and Kuli increased the most strongly, by 14.10- and 9.20-fold, respectively. Similarly, 1049 resulted in a 7.60-fold change in the GR. APX was found to be positively correlated with plant growth under salinity in Arabidopsis [ 70 ]. This may be attributed to the high affinity of APX for H 2 O 2 in different organelles when ascorbate is used as an electron donor [ 71 ]. APX alleviation increased the salinity tolerance of wheat under salinity stress caused by 120 mM NaCl (Rady et al., 2019a). APX markedly increased under 350 mM NaCl treatment in wheat neglected and ancestral relatives at the young plant growth stage, and the expression of the APX gene was highly upregulated [ 72 ]. Similar findings for APX increase and APX gene upregulation were reported in two contrasting wheat varieties, and the tolerant genotypes presented higher APX contents and APX gene expression than did the salt-sensitive variety [ 73 ]. Compared with that in sensitive cultivars, APX significantly increased under salinity stress in salt-tolerant cultivars [ 65 ]. For GR, a genotype-dependent pattern was observed, and salinity stress increased GR in all the genotypes except the two tolerant genotypes Kule and 1018d (Fig. 3). The greatest increases were observed in the two tolerant genotypes, Ghati and Javelin 48, with 5.7- and 8.6-fold changes, respectively. Several studies have reported an increase in GR in wheat under different concentrations of salinity stress and at different growth stages [ 65 , 69 , 73 – 75 ]. In a comparative study between two Egyptian wheat cultivars, Misr 2 and Sakha 95, the cultivar Misr 2 retained high GR levels and tolerated salinity better than Sakha 95 did [ 76 ]. The GR is a key player under abiotic stresses, especially salinity, and maintains optimum levels of the reduced form of glutathione, which is vital for ROS homeostasis through the glutathione‒ascorbate cycle. Taken together, the antioxidant enzymes SOD, CAT, APX and GR play a protective role in plant tolerance to salinity by neutralizing the oxidative damage caused by an overdose of ROS resulting from salinity stress. Our results revealed intraspecific variability for each enzyme. Salinity stress increased enzymatic activity even in the salt-sensitive genotype Soahg-5. The tolerant genotypes presented the highest levels of enzymatic activity (Fig. 6 and Fig. 7a, b). Gene expression profiling of the genes encoding AVP (a vacuolar pyrophosphatase similar to AVP1) and NHX1 (a Na + /H + antiporter) under salinity stress : The expression profiles of both genes were estimated in four contrasting genotypes, one salt-sensitive genotype (Sohag-5) and three salt-tolerant genotypes (Javelin 48, Kandahar and 1018d). The two genes presented different expression profiles under salinity treatment compared with the control. In the sensitive genotype (Sohag-5), the two genes presented different expression profiles: TaAVP was slightly upregulated (1.05-fold), whereas NHX1 remained unchanged under salinity stress (Fig. 8, Supplementary Fig. 2). The tolerant genotypes presented differential expression of both genes. The highest expression levels of AVP1 and NHX1 were observed in Javelin 48 (1.4-fold relative to the control), followed by Kandahar (1.14-fold relative to the control), while both genes were downregulated at 1018 d (Fig. 8, Supplementary Fig. 2). These findings indicate that gene expression varied among the sensitive and tolerant genotypes as well as within the tolerant set in a genotype-specific pattern. In the context of low expression levels, our results are in agreement with the findings of Genc et al., (2019), who reported low expression levels of both genes in low-Na + wheat. Our results are in agreement with the findings of Nakayama et al., (2022), who reported that, in tolerant common wheat, salt-responsive genes presented a genotype-specific pattern and that the Na + /H + antiporter gene was significantly upregulated in some salt-tolerant lines and downregulated in other tolerant lines. These results indicate that NHX1 was differentially expressed in the tolerant genotypes. However, the tolerance genotype Javelin 48 presented the highest expression level of both genes (expectedly included in Na sequestration in the vacuole), the lowest Na + content, the highest K + and K + /Na + ratio and the lowest Na-S/Na-C fold change among the salt-tolerant genotypes. More likely, it has an efficient Na-excluding active allele of membrane antiporters ( NHX2 ), which helps in maintaining physiological Na levels. Another possibility is that NHX1 favored the vacuolar sequestration of K at the expense of Na. In contrast, in Kandahars (tolerant to high Na concentrations), Na is sequestered at the expense of K, reflecting the multiple functions of NHX1 in tolerant wheat genotypes. In the present study, both the AVP1 and NHX1 genes were downregulated in the tolerant genotype 1018d, which presented the highest Na + content among the tolerant genotypes, indicating that this genotype uses another mechanism to tolerate salinity, such as osmotic adjustment and activation of antioxidant enzymatic systems. In the present study, AVP1 was strongly positively correlated with the RSR (r = 0.99*) (Fig. 5). This finding is in agreement with that of Gaxiola et al., (2001), who reported that the overexpression of TaAVP1 confers salinity tolerance to Arabidopsis transgenic plants relative to wild-type plants. The transgenic plants maintained high levels of both Na + and K + and retained more water. Nakayama et al., (2022) reported that the NHX genes of two salt-tolerant lines were upregulated via different mechanisms, with the second leading to the upregulation of antioxidant genes. Notably, there was concomitant upregulation/downregulation of both genes in the tolerant genotypes, indicating that both genes are involved in salt tolerance and that they are likely working in a synchronized way. Coordinate upregulation of NHX1 and AVP1 has been reported in several plant species (Mansour, 2022). AVP1 expression is equivalent to that of NHX antiporters in several plant species, indicating that AVP1 generates a proton gradient that is essential for the energization of NHX1 , which in turn controls vacuolar Na + sequestration, as reviewed by Mansour, (2022). Several studies reported that the coexpression of both the NHX and AVP genes improved salinity tolerance in transgenic plants that expressed both genes together rather than expressing only one of them; this finding has been demonstrated in various plant species, such as rice, sugar beet, lotus, tobacco, and Arabidopsis [ 80 ]. In two contrasting wheat genotypes, with respect to salinity tolerance, the expression levels of TVP1 were similar to those of the vacuolar Na + /H + antiporter ( TNHX1 ) in different tissues of the two genotypes [ 43 ]. Conclusion The current study highlights that wheat salinity tolerance is governed by complex, genotype-specific mechanisms that integrate ion homeostasis, antioxidant defense, and gene expression regulation. Tolerant genotypes display diverse strategies, ranging from Na⁺ exclusion and K⁺ retention to Na⁺ sequestration for osmotic adjustment, which is supported by high K⁺/Na⁺ ratios and increased antioxidant enzyme activities. The upregulation of NHX1 and AVP1 in tolerant genotypes suggests a coordinated role in salinity tolerance. The tolerant genotypes Javelin 48 (high K) and Kandahar (high Na) combined effective ion homoeostasis with elevated expression of both genes. These results highlight the plasticity of adaptive responses and provide valuable molecular and physiological markers for improving wheat salinity tolerance through targeted breeding. Declarations Data availability statement All relevant data can be found within the manuscript and its supporting materials, and any further inquiries can be directed to the corresponding author(s). Author contributions AS, NH, MA, and YM conceptualization; NH, MA, and YM funding acquisition; NH and AS methodology; YM, MA, and AS wrote the original draft and review. Funding This work was funded by the Academy of Scientific Research and Technology (ASRT) under the 6 th call of master grants, namely, Scientists for Next Generation Scholarships (SNG), Egypt. Conflict of interest The authors declare that there are no potential conflicts of interest. Clinical trial number not applicable Ethics, Consent to Participate, and Consent to Publish declarations: not applicable References Ashraf M, Foolad MR. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7186942","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":497291499,"identity":"11f3a122-00a2-4345-b995-67ac476527ee","order_by":0,"name":"Ahmed Sallam","email":"","orcid":"","institution":"Badr University in Assiut (BUA)","correspondingAuthor":false,"prefix":"","firstName":"Ahmed","middleName":"","lastName":"Sallam","suffix":""},{"id":497291500,"identity":"7727761a-d853-4f53-a684-5b7658b19499","order_by":1,"name":"Nouran M. Hasseb","email":"","orcid":"","institution":"Fayoum University","correspondingAuthor":false,"prefix":"","firstName":"Nouran","middleName":"M.","lastName":"Hasseb","suffix":""},{"id":497291501,"identity":"fe18edba-a423-4566-a43c-bb509213f6a9","order_by":2,"name":"Mohamed A. Karam","email":"","orcid":"","institution":"Fayoum University","correspondingAuthor":false,"prefix":"","firstName":"Mohamed","middleName":"A.","lastName":"Karam","suffix":""},{"id":497291502,"identity":"40d27672-2b4f-43df-ad42-f859c5ee706f","order_by":3,"name":"Andreas Börner","email":"","orcid":"","institution":"Leibniz Institute of Plant Genetics and Crop Plant Research (IPK)","correspondingAuthor":false,"prefix":"","firstName":"Andreas","middleName":"","lastName":"Börner","suffix":""},{"id":497291503,"identity":"7834a0f5-3b73-494f-94ff-c99c642e47d0","order_by":4,"name":"Yasser S. Moursi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2ElEQVRIiWNgGAWjYFACxoYDH2xgHDaitDAfPDgjjTQtbMmHeUjSIj/tjMFhmwS7xH6J7ASGD2WHGfj5F+DXYnA7x+BwTkJy4swZuRsYZ5w7zCA54wEBLdJALbk/mBM33MjdwMzbdpjB4MYBAg6bDdRikVAP0fIXqMWekBaG22kJhxkSDkO0MIJs4W8g5JfkAwd7Eo4bz+x5u+Fgz7l0HokbBCyRn53Y/OFHQrVsP3vuxgc/yqzl+PsJOQwKHEGuAanlYZBIIE6LPYLJT6Qto2AUjIJRMGIAAN7PTTM1JILGAAAAAElFTkSuQmCC","orcid":"","institution":"Fayoum University","correspondingAuthor":true,"prefix":"","firstName":"Yasser","middleName":"S.","lastName":"Moursi","suffix":""}],"badges":[],"createdAt":"2025-07-22 12:23:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7186942/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7186942/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88592293,"identity":"d3a84e84-8949-44cc-8a72-3836add8942f","added_by":"auto","created_at":"2025-08-08 06:04:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":61319,"visible":true,"origin":"","legend":"\u003cp\u003eThe fold change of Na, K and P ions in 7 contrasting wheat genotypes under control (0 mM NaCl and salt stress (175 mM NaCl).\u003c/p\u003e","description":"","filename":"FiguresofPaper21.png","url":"https://assets-eu.researchsquare.com/files/rs-7186942/v1/c4fc43cdec292968b6a08224.png"},{"id":88592995,"identity":"1992f0b4-e93a-410b-a3b4-87ff8106debc","added_by":"auto","created_at":"2025-08-08 06:12:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":56324,"visible":true,"origin":"","legend":"\u003cp\u003eThe ratio of Na and K ions in 7 contrasting wheat genotypes under control (0 mM NaCl and salt stress (175 mM NaCl)\u003c/p\u003e","description":"","filename":"FiguresofPaper22.png","url":"https://assets-eu.researchsquare.com/files/rs-7186942/v1/fbf6d3a20fa901b1ede29464.png"},{"id":88592294,"identity":"b9244c8f-47d1-4350-b444-9eaefd786f87","added_by":"auto","created_at":"2025-08-08 06:04:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":19288,"visible":true,"origin":"","legend":"\u003cp\u003eAntioxidants enzymes activity; APX = Ascorbate Peroxidase, CAT = Catalase, SOD = Super Oxide Dismutase, and GR = Glutathione Reductase in 7 contrasting wheat genotypes and control (0 mM NaCl and salt stress (175 mM NaCl)\u003c/p\u003e","description":"","filename":"FiguresofPaper23.png","url":"https://assets-eu.researchsquare.com/files/rs-7186942/v1/23d7df3171ffa2ded9115a22.png"},{"id":88592299,"identity":"95cdf744-2fa6-4699-8c6b-8c241cf7aca0","added_by":"auto","created_at":"2025-08-08 06:04:28","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":20277,"visible":true,"origin":"","legend":"\u003cp\u003eThe fold change of antioxidants enzymes; ascorbate peroxidase (APX), catalase (CAT), glutathione reductase (GR), superoxide dismutase (SOD) in 7 contrasting wheat genotypes under control (0 mM NaCl and salt stress (175 mM NaCl).\u003c/p\u003e","description":"","filename":"FiguresofPaper24.png","url":"https://assets-eu.researchsquare.com/files/rs-7186942/v1/c5560cd30b6579cdb3ec7ba3.png"},{"id":88592300,"identity":"8f2cd6d5-5cd5-47ab-8bc4-f0e8d4a59868","added_by":"auto","created_at":"2025-08-08 06:04:28","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":338823,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation of morphological traits, antioxidants enzymes, Na+/K+, P content and \u003cem\u003eTaATV1\u003c/em\u003eand \u003cem\u003eNHX1\u003c/em\u003eexpression in 4 contrasting wheat genotypes under control (0 mM NaCl and salt stress (175 mM NaCl)\u003c/p\u003e","description":"","filename":"FiguresofPaper25.png","url":"https://assets-eu.researchsquare.com/files/rs-7186942/v1/68a2f752279be264424795ed.png"},{"id":88592304,"identity":"0e5462bd-a3b6-4f40-ba5f-2a113a4a9a59","added_by":"auto","created_at":"2025-08-08 06:04:28","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":111474,"visible":true,"origin":"","legend":"\u003cp\u003eClustering heat map for the traits of 7 contrasting wheat genotypes. C stands for control and S stands for salt\u003c/p\u003e","description":"","filename":"FiguresofPaper26.png","url":"https://assets-eu.researchsquare.com/files/rs-7186942/v1/40af6142a01e2efab42f411c.png"},{"id":88592301,"identity":"f76f94aa-a7ec-4d8d-8235-1399c974228e","added_by":"auto","created_at":"2025-08-08 06:04:28","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":178967,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal Component Analysis (PCA) in 7 contrasting wheat genotypes and control (0 mM NaCl and salt stress (175 mM NaCl), a) biplot of the traits, and b) PCA shows the clustering of genotypes. C stands for control and S stands for salinity.\u003c/p\u003e","description":"","filename":"FiguresofPaper27.png","url":"https://assets-eu.researchsquare.com/files/rs-7186942/v1/3e88cdc9b66b0da22bb5f6ee.png"},{"id":88592296,"identity":"8f024471-e59a-45fa-8a81-502f31629ebc","added_by":"auto","created_at":"2025-08-08 06:04:28","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":31666,"visible":true,"origin":"","legend":"\u003cp\u003eRelative expression levels of APV1 and NHX1 genes in 4 contrasting wheat genotypes; one sensitive genotype “Sohag-5 and three tolerant genotypes “Kandahar, Javelin 48, and 1018d”.\u003c/p\u003e","description":"","filename":"FiguresofPaper28.png","url":"https://assets-eu.researchsquare.com/files/rs-7186942/v1/6f6b0a809da111f75e583343.png"},{"id":88593736,"identity":"5534cb0f-1026-47b1-ba3c-d2fbb11dfca0","added_by":"auto","created_at":"2025-08-08 06:24:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1967478,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7186942/v1/af612523-ee41-4915-8405-83297f37e30a.pdf"},{"id":88592305,"identity":"11425552-e450-4ecb-bae3-f3ebb9bf5783","added_by":"auto","created_at":"2025-08-08 06:04:28","extension":"pptx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":2164301,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigures.pptx","url":"https://assets-eu.researchsquare.com/files/rs-7186942/v1/aa73b3eb7124e96962d14a39.pptx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Salinity-induced changes in gene expression, ion homeostasis, and enzymatic antioxidants in contrasting wheat genotypes","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWheat is the prominent staple food of the human diet, but its production is under various threats due to climate change. Salinity represents a major challenge for plant growth and crop productivity. Throughout the plant life cycle, seed germination and early seedling development are the stages with the greatest salinity sensitivity. Salinity can postpone the initiation of germination, slow its progression, and cause greater variability in germination timing, ultimately resulting in reduced plant growth and lower final crop yields [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, plant species exhibit a wide range of tolerances to salinity, as demonstrated by their ability to thrive in environments ranging from freshwater habitats to highly saline areas. Even among crop plants, there is notable variation in salt tolerance both between species and within a single species. These findings highlight two key points: (1) crop plants have the potential to adapt to saline conditions, and (2) intraspecific variation offers valuable opportunities to study the mechanisms of salt tolerance and sensitivity [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Ionic imbalance and deficiency are among the consequences of salinity stress [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The effects of salinity on the nutrient composition of plant tissues have been widely studied, and many researchers have confirmed that the deleterious effects of salinity on plant growth can be caused by an ionic imbalance, especially of calcium and potassium ions [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The accumulation of high levels of ions is more costly than the assimilation of carbon in the form of organic solutes [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. During seed germination and the establishment of young seedlings, the mineral nutrient reserves in the seed must be sufficient to support the growth of the seedling to the point of self-sufficiency [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Thus, plants must maintain a relatively high concentration of potassium if they are to grow in a saline soil environment [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Potassium is an important macroelement that represents up to 10% of the dry matter of the cell and plays a fundamental role in maintaining the water state of the plant, stomatal movement, enzyme activity, osmoregulation and membrane stability [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Maintaining high K\u003csup\u003e+\u003c/sup\u003e/Na\u003csup\u003e+\u003c/sup\u003e ratios is considered among the selection criteria for salt tolerance [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, sodium is unusual as a nutrient for life because it is a nonessential element for most plants [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Under salinity stress, potassium competes for plant uptake through high-affinity potassium transporters and nonselective cation channels, resulting in membrane depolarization, and plants cannot discriminate between Na and K ions [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, sodium is known to cause the most deleterious effect of salinity, and its exclusion is effective for conferring salinity tolerance. The sequestration of high levels of Na\u003csup\u003e+\u003c/sup\u003e confers salinity tolerance in barley, and Na\u0026thinsp;+\u0026thinsp;might act as an osmolyte or a nutrient to compensate for K\u003csup\u003e+\u003c/sup\u003e deficiency [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Similar results have been reported in other cereals, such as rice [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] and maize [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], where high levels of Na\u003csup\u003e+\u003c/sup\u003e in the cell vacuole can increase salinity tolerance [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Phosphorus (P) is an important macronutrient for plant growth and development and plays a crucial role in energy production, DNA synthesis and salinity tolerance during seed germination [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The phosphorus content decreased in seedlings of cotton, wheat, barley and faba bean under salinity stress [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHowever, balanced production and scavenging of ROS are highly important for seed germination, suggesting that seed germination and ROS production are coupled [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Many studies have reported the induction and accumulation of high levels of both reactive oxygen species and plant antioxidants in relation to salt stress. High levels of ROS can disturb normal metabolism by oxidizing lipids, proteins, and nucleic acids in the absence of protective systems. It is now widely accepted that reactive oxygen species are responsible for various types of stress-induced damage to macromolecules and ultimately to the cellular structure [\u003cspan additionalcitationids=\"CR29 CR30\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Plants have a well-developed complex antioxidant system that includes enzymatic and nonenzymatic antioxidant processes to intercept ROS. The antioxidant enzymes include superoxide dismutase (SOD), catalase (CAT), peroxidase (POD), and ascorbate peroxidase (APX) [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. The antioxidant enzymes SOD, CAT, GR, and APX detoxify H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e. The activity of all of these antioxidant enzymes increases under salinity stress during seed germination and seedling establishment in wheat, maize and barley in synchrony with the overproduction of ROS [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe response of plants to environmental cues is under polygenic control. Exploring the connection between gene expression and physiological mechanisms remains a bottleneck in selection for improving plant tolerance to these cues [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Approximately 19% of wheat genes are salt responsive (Kawaura et al., 2008). Salt tolerance in wheat has been suggested to be regulated primarily by the activation of transporter genes (Nakayama et al., 2022). Among them are the vacuolar pyro phosphatase (V-PPase) and the Na\u003csup\u003e+\u003c/sup\u003e/H\u003csup\u003e+\u003c/sup\u003e antiporter. TAVP1 expression was equivalent to that of vacuolar Na\u003csup\u003e+\u003c/sup\u003e/H\u003csup\u003e+\u003c/sup\u003e antiporters in several plant species, indicating that TAVP1 generates a proton gradient that is essential for energizing \u003cem\u003eTNHX1\u003c/em\u003e, which in turn controls vacuolar Na\u003csup\u003e+\u003c/sup\u003e sequestration, as reviewed by Mansour, (2022). Both V-PPase and tonoplast Na\u003csup\u003e+\u003c/sup\u003e/H\u003csup\u003e+\u003c/sup\u003e are more active in salt-tolerant genotypes than in sensitive genotypes in both rice and citrus [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The overexpression of Arabidopsis V-PPase improved salinity tolerance in alfalfa, and the resulting transgenic plants accumulated high levels of Na, K and Ca ions [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Compared with control plants, transgenic plants of finger millet overexpressing sbVPPase from sorghum presented higher antioxidant levels and accumulated more Na, K and Ca under 100 mM NaCl and 200 mM NaCl stress [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. In two contrasting wheat genotypes, with respect to salinity tolerance, the expression levels of TVP1 were similar to those of the vacuolar Na\u003csup\u003e+\u003c/sup\u003e/H\u003csup\u003e+\u003c/sup\u003e antiporter \u003cem\u003eTNHX1\u003c/em\u003e in different tissues of the two genotypes [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. In barley, \u003cem\u003eHVP10\u003c/em\u003e was upregulated under salinity stress, and the transgenic plants of rice overexpressing \u003cem\u003eHVP10\u003c/em\u003e sequestered more Na\u003csup\u003e+\u003c/sup\u003e in vacuoles and, in turn, presented greater salt tolerance than did the wild-type plants [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe current study aims to understand the intraspecific variation in the salinity response to study the mechanisms of salt tolerance and sensitivity in wheat. The objectives of the present study were to 1) investigate the molecular basis of salinity tolerance by analyzing the expression patterns of key ion transporter genes (\u003cem\u003eTaAVP1\u003c/em\u003e and \u003cem\u003eNHX1\u003c/em\u003e) in tolerant and sensitive genotypes to elucidate their contributions to ion homeostasis, 2) evaluate the physiological responses associated with salinity tolerance during early development in contrasting wheat genotypes, focusing on ion homeostasis (Na⁺/K⁺ balance) and antioxidant enzyme activity under salt stress, and 3) elucidate the role of intraspecific variation in salinity tolerance and sensitivity.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e\u003cb\u003ePlant material and experimental design\u003c/b\u003e\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe details of the germination experiment and a full description of the plant materials are provided in Hasseb et al. (2022). Briefly, in a complete randomized block design with three replicates, a set of 176 highly diverse wheat genotypes was tested during seed germination and seedling establishment; 0 mM NaCl was used for the control, and 175 mM NaCl was used for salinity stress. The data resulting from that experiment were used for genome-wide association analysis (GWAS) (Hasseb et al. 2022). On the basis of their performance, 12 contrasting genotypes (6 salinity-tolerant\u0026thinsp;+\u0026thinsp;6 salinity-sensitive) were selected as the most salinity-tolerant and the most salinity-sensitive genotypes. Among those 10 genotypes, seven genotypes were selected for the analyses of ion concentrations and enzymatic antioxidants. Among the seven genotypes, four (1 sensitive\u0026thinsp;+\u0026thinsp;3 tolerant) were used for gene expression (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe gene bank ID, accession name, origin, and classification of the seven contrasting genotypes (6 tolerant genotypes and 1 sensitive genotype)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGene bank ID\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAccession name\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCountry\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCharacter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNa and K traits\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAntioxidant Enzymes Activities\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eGene expression\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePI 220127\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKandahar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAfghanistan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTolerant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026radic;\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026radic;\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e\u0026radic;\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePI 542666\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGhati\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAlgeria\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTolerant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026radic;\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026radic;\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePI 201414\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGavelin 48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAustralia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTolerant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026radic;\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026radic;\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e\u0026radic;\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePI 525241\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1049\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMorocco\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTolerant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026radic;\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026radic;\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePI525221\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1018d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMorocco\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTolerant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026radic;\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026radic;\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e\u0026radic;\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePI532249\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKule\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOman\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTolerant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026radic;\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026radic;\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e122\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSohag-5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEgypt\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSensitive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026radic;\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026radic;\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e\u0026radic;\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eAntioxidant enzyme activities\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eExtraction\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe antioxidant enzyme activities of superoxide dismutase (SOD, EC 1.15.1.1), ascorbate peroxidase (APX, EC 1.11.1.11), catalase (CAT, EC 1.11.1.6), and glutathione (GR, EC 1.6.4.2) were estimated in homogenates extracted from seedling tissue samples. All the homogenates were centrifuged at 4\u0026deg;C in a refrigerated centrifuge at 15,000xg for 15 min. The supernatant was used to assay the enzymatic activity at the corresponding wavelength for each enzyme.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSuperoxide dismutase assay\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSOD activity was estimated according to Dhindsa et al., (1981) by recording the decrease in the absorbance of the superoxide nitro blue tetrazolium complex by the enzyme at 560 nm. Approximately 3 ml of the reaction mixture, containing 0.1 ml of 200 mM methionine, 0.1 ml of 2.25 mM nitro blue tetrazolium (NBT), 0.1 ml of 3 mM ethylene diamine tetra acetic acid (EDTA), 1.5 ml of 100 mM potassium phosphate buffer, 1 ml of distilled water and 0.05 ml of extracted enzyme, was taken from each sample in duplicate tubes. Additionally, two control tubes were prepared without enzyme extraction. The reaction was started by adding 0.1 ml of riboflavin (60 \u0026micro;m) to all the tubes placed under a light source of two florescent lamps (15 W) for 15 min. The reaction was stopped after the light was turned off and the tubes were covered with dark covers. The maximum color developed in the tubes without the enzyme. A non-irradiated complete reaction mixture that did not produce color was used as a blank.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAscorbate peroxidase assay\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAPX activity was estimated at 290 nm according to Nakano and Asada, (1980) via spectrophotometric monitoring of the decrease in absorbance as an indicator of the rate of ascorbate oxidation. The reaction mixture contained 25 mM phosphate buffer (pH\u0026thinsp;=\u0026thinsp;7), 0.1 mm ethylene diamine tetra acetic acid (EDTA), 1 mm hydrogen peroxide, 0.25 mm AsA and the enzyme sample.\u003c/p\u003e\u003cp\u003e\u003cb\u003eCatalase assay\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe activity of CAT was used to estimate the rate of H2O2 decomposition at 240 nm following [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Approximately 3 ml of the reaction mixture contained 1.5 ml of 100 mm buffered potassium phosphate (pH\u0026thinsp;=\u0026thinsp;7), 0.5 ml of 75 mm hydrogen peroxide, 0.05 ml of extracted enzyme mixture and distilled water. When H2O2 was added, the reaction started, and the decrease in absorbance was recorded for 1 min.\u003c/p\u003e\u003cp\u003e\u003cb\u003eGlutathione reductase assay\u003c/b\u003e\u003c/p\u003e\u003cp\u003eGR activity was estimated in the presence of oxidized glutathione (GSSG) and 5,5-dithiobis-2-nitrobenzoic acid (DTNB) by recording the increase in absorbance according to Smith et al., (1988). The reaction mixture consisted of 1 ml of 0.2 M potassium phosphate buffer (pH\u0026thinsp;=\u0026thinsp;7.5) containing 0.1 mM EDTA, 0.5 ml of 3 mM DTNB in 0.01 M potassium phosphate buffer (pH\u0026thinsp;=\u0026thinsp;7.5), 0.1 ml of 2 mM NADPH, 0.1 ml of enzyme extract and distilled water to make up a final volume of 2.9 ml. When 0.1 2 mM GSSG was added, the reaction started. The increase in absorbance at 412 nm was recorded at 25\u0026deg;C over a period of 5 min via a spectrophotometer.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEstimation of sodium (Na), potassium (K) and phosphorus (P) contents\u003c/b\u003e:\u003c/p\u003e\u003cp\u003eThe samples were dried at 80\u0026deg;C for 72 h. A coffee grinder was used to pulverize the dried samples to measure the sodium and potassium concentrations. One day before digestion, the samples were dried overnight at 100\u0026deg;C. In a microwave-assisted acid digestion system (Anton Paar Multiwave 5000, Graz, Austria), 0.5 g from each sample was placed in a vessel with 10 ml of nitric acid. At 175\u0026deg;C, the samples were placed in the microwave system for 10 minutes (heated to 175\u0026deg;C in 5.5 minutes and maintained for 4.5 minutes). After cooling, the samples were diluted to 50 ml with deionized water. The Na, K, and P contents were estimated from the atomic absorbance. The K\u003csup\u003e+\u003c/sup\u003e/Na\u003csup\u003e+\u003c/sup\u003e ratio was calculated according to the Na\u003csup\u003e+\u003c/sup\u003e and K\u003csup\u003e+\u003c/sup\u003e concentrations. The fold changes in Na, K and P contents were computed as the content under salinity relative to the content under the control. Total inorganic phosphate (Pi) was quantified by adding ammonium vanadomolybdate reagent and measuring the absorbance at 470 nm via a UV/Vis spectrophotometer.\u003c/p\u003e\u003cp\u003e\u003cb\u003eGene expression analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eGene expression analysis was performed on four contrasting genotypes (three tolerant and one sensitive) under control and salt stress conditions. The expression levels of two genes were compared among the four genotypes under control conditions and salinity stress. These two genes, AK4544458/TaAffx.25629.1S1 (vacuolar pyrophosphates similar to \u003cem\u003eAVP1\u003c/em\u003e) and AY296910 (Na\u003csup\u003e+\u003c/sup\u003e/H\u003csup\u003e+\u003c/sup\u003e vacuolar antiporter \u0026ldquo;\u003cem\u003eNHX1\u003c/em\u003e\u0026rdquo;), were previously reported Mott \u0026amp; Wang, (2007). The sequences of the forward and reverse primers corresponding to these genes are listed in Table\u0026nbsp;2.\u003c/p\u003e\u003cp\u003e\u003cb\u003eRNA extraction, cDNA preparation, and real-time PCR\u003c/b\u003e\u003c/p\u003e\u003cp\u003eLike the germination conditions, the same concentrations of sodium chloride (0 mM NaCl) for the control and (175 mM NaCl) for salinity stress were applied to the four selected genotypes. Three biological samples were collected from leaves of each genotype (0.1 g for each replication). The leaves of all the samples were transferred immediately to liquid nitrogen and stored at -80\u0026deg;C until further analysis. The RNA was extracted via an RNeasy Plant Mini Kit (Qiagen, Valencia, CA, USA). To obtain purified RNA, all the samples were treated with RNase-free DNase I (Thermo Fisher Scientific, USA). Complementary DNA (cDNA) was prepared with a Revert Aid First Strand cDNA Synthesis Kit according to the manufacturer\u0026rsquo;s protocol. (Thermo Fisher Scientific, USA). Finally, all the samples were prepared for real-time PCR via Maxima SYBR Green/ROX qPCR Master Mix (2X) (Thermo Fisher Scientific, USA). The thermocycling was performed under the following conditions: 2 min at 50\u0026deg;C, 10 min at 95\u0026deg;C, and 40 cycles alternating between 15 s at 95\u0026deg;C and 1 min at 60\u0026deg;C. The expression levels for each sample from each genotype under both treatments were analyzed in three biological replicates and calculated via the 2\u0026thinsp;\u0026minus;\u0026thinsp;\u003csup\u003eΔΔCT\u003c/sup\u003e method.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAccession number/probe set\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnnotation/predicted function\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePrimer sequence (5'-3')\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAmplicon (bp)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eAK4544458/TaAffx.25629.1.S1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVacuolar pyro phosphatase similar to AVP1 (\u003cem\u003eTaAVP1\u003c/em\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFwd GACCGGTCTTGCCATTGATG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e162\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMott and Wang (2007)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRev CTGAGCCAATTGCGAATCCC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eAY296910\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eNa\u003csup\u003e+\u003c/sup\u003e/H\u003csup\u003e+\u003c/sup\u003e antiporter (\u003cem\u003eNHX1\u003c/em\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFwd GCCTGGTTCACCCATAGAGA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRev CACCGAAAGAATCCCAAGAG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e159\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMott and Wang (2007\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eData analysis\u003c/h2\u003e\u003cp\u003eThe analysis of variance (ANOVA) was calculated under control and salt stress conditions via PLABSTAT software (43) and the R package (44) via the following statistical model:\u003c/p\u003e\u003cp\u003e\u003cem\u003eY\u003c/em\u003e\u003csub\u003e\u003cem\u003eijk\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e=\u0026thinsp;\u0026micro;\u0026thinsp;+\u0026thinsp;g\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e+ r\u003c/em\u003e\u003csub\u003e\u003cem\u003ej\u003c/em\u003e\u003c/sub\u003e \u003cem\u003e+ t\u003c/em\u003e\u003csub\u003e\u003cem\u003ek\u003c/em\u003e\u003c/sub\u003e \u003cem\u003e+ t\u003c/em\u003e\u003csub\u003e\u003cem\u003eik\u003c/em\u003e\u003c/sub\u003e \u003cem\u003e+ tgr\u003c/em\u003e\u003csub\u003e\u003cem\u003eijk\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e\u003cp\u003estress) k, \u0026micro; is the general mean value; gi, rj, tk are the main effects of genotype, replication, and treatment, respectively. tik represents the genotype \u0026times; treatment interaction. tgrijk represents the genotype \u0026times; replication \u0026times; treatment interaction (error). Broad-sense heritability (\u003cem\u003eH\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e) was estimated via PLABSTAT via the following equation:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:{H}^{2}=\\:\\frac{{\\sigma\\:}_{G}^{2}}{{\\sigma\\:}_{G}^{2}+\\left(\\frac{{\\sigma\\:}_{GR}^{2}}{r}\\right)}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere G refers to genotypes and where r refers to replications.\u003c/p\u003e\u003cp\u003ePhenotypic correlation analysis was performed via PLABSTAT. Correlation coefficients ranging from 0\u0026ndash;39, 0.40\u0026ndash;0.60 and above 0.60 were considered low, moderate, and high correlations, respectively. The data visualization for all the parameters was conducted via SRplot: A free online platform for data visualization and graphing [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] and Excel 365 [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eSodium (Na), potassium (K) and phosphorus (P)-related traits\u003c/b\u003e:\u003c/p\u003e\u003cp\u003eThe Na\u003csup\u003e+\u003c/sup\u003e, K\u003csup\u003e+\u003c/sup\u003e, K\u003csup\u003e+\u003c/sup\u003e/Na\u003csup\u003e+\u003c/sup\u003e, Na\u003csup\u003e+\u003c/sup\u003e/K\u003csup\u003e+\u003c/sup\u003e, and P contents and ratios were measured and calculated for 7 contrasting genotypes: one sensitive genotype (Soha-5; from Egypt) and six tolerant genotypes (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). All the genotypes presented an increase in Na content under salinity stress (175 mM NaCl) compared with the control (0 mM NaCl), including some of the tolerant genotypes (Supplementary Fig.\u0026nbsp;1). The fold change in Na content under salinity relative to the control (Na-S/Na-C) was very dramatic in the sensitive genotype Sohag-5 from Egypt, with a 9.95-fold change, and three of the tolerant genotypes, Kandahar from Afghanistan, 1049 and 1018 d from Morocco, and Kule from Oman, with folding changes of 11.40, 10.62, and 12.79, respectively (Fig.\u0026nbsp;1). Moreover, the tolerant genotypes presented different levels of Na, and the genotypes Ghati from Algeria and Javelin 48 from Australia presented the lowest levels of Na under salinity stress, with 1.51- and 1.43-fold changes, respectively. The K content decreased in all the genotypes except at Javelin 48 and 1018d, whereas it did not change in Kule (Fig.\u0026nbsp;1). As expected, for the K and Na ratios under the control conditions, the K\u003csup\u003e+\u003c/sup\u003e/Na\u003csup\u003e+\u003c/sup\u003e (K\u003csup\u003e+\u003c/sup\u003e/Na\u003csup\u003e+\u003c/sup\u003e -C) ratio was high for all the genotypes and varied from 2.91 for Kule to 5.02 for 1018d. The sensitive genotype Sohag-5 had a ratio of 4.61. Under salinity, the K\u003csup\u003e+\u003c/sup\u003e/Na\u003csup\u003e+\u003c/sup\u003e (K\u003csup\u003e+\u003c/sup\u003e/Na\u003csup\u003e+\u003c/sup\u003e-S) ratio decreased in all the genotypes; in the tolerant group, it ranged from 0.23 for Kule to 3.20 for Javelin 48. The sensitive genotype Sohag-5 had a ratio of 0.38 (Fig.\u0026nbsp;2). In contrast, under salinity, the Na\u003csup\u003e+\u003c/sup\u003e/K\u003csup\u003e+\u003c/sup\u003e (Na\u003csup\u003e+\u003c/sup\u003e/K\u003csup\u003e+\u003c/sup\u003e-S) ratio was very low in all the genotypes under the control conditions, ranging from 0.20 for 1018 d to 0.30 for Ghati, and the sensitive genotype Sohag-5 had a ratio of 0.22. Moreover, with respect to salinity, it was very high, with values of 0.31, 0.39 and 0.44 for Gavelin 48, 1018d and Ghati, respectively. The sensitive genotype Sohag-5 had a ratio of 2.65. With respect to the P content, under salinity, all the genotypes presented a high reduction in P content except for the tolerant genotypes 1018d and Kule (Fig.\u0026nbsp;2).\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe activity of antioxidant enzymes under control conditions and salt stress\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe activities of the antioxidant enzymes superoxide dismutase (SOD), catalase (CAT), glutathione reductase (GR) and ascorbate peroxidase (APX) were estimated in 7 contrasting genotypes under the control (0 mM NaCl) and salinity (175 mM NaCl) treatments. The enzyme activity of all the enzymes varied among the sensitive and tolerant genotypes (Fig.\u0026nbsp;3). Compared with that of the control, the activity of ascorbate peroxidase increased under salinity stress for all 7 genotypes (Fig.\u0026nbsp;3). Sohag-5 (the sensitive genotype) showed a 6.65-fold change. Among the tolerant genotypes, Ghati presented the greatest fold change, with a 14.1-fold change, followed by Kule, with a 9.20-fold change, while 1018d presented no change (Fig.\u0026nbsp;4). The activity of catalase increased under salinity for all the genotypes, including the sensitive cultivar Sohag-5 (Fig.\u0026nbsp;3). The greatest increase in CAT activity was recorded by Javelin 48, whereas CAT activity decreased in the two tolerant genotypes, Ghati and Kule (Fig.\u0026nbsp;4). SOD activity decreased in Sohag-5, whereas it increased in all of the tolerant genotypes (Fig.\u0026nbsp;3). The greatest increase was recorded in Kule (2.32-fold change), and the lowest increase was recorded in Kandahar, with a 1.03-fold change (Fig.\u0026nbsp;4). The activity of glutathione reductase increased under salinity for all the genotypes except for the two tolerant genotypes 1048d and Kule (Fig.\u0026nbsp;3). Javelin 48 exhibited the greatest increase, with a 7.80-fold change, and Kandahar presented the lowest fold change, with a value of 1.79 (Fig.\u0026nbsp;4). Sohag-5 presented an increase in GR activity of 1.39-fold (Fig.\u0026nbsp;4).\u003c/p\u003e\u003cp\u003e\u003cb\u003eAnalysis of variance (ANOVA)\u003c/b\u003e:\u003c/p\u003e\u003cp\u003eThe analysis of variance for all measured traits revealed highly significant genotypic (G) and G \u0026times; E variations (p\u0026thinsp;\u0026le;\u0026thinsp;0.01) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These findings indicate that wide genetic variability exists among the genotypes in terms of ion homeostasis, ion-related traits, and key enzymatic antioxidants, which are valuable for further selection and breeding of genotypes with superior ionic homeostasis and antioxidant responses under salinity stress. Significant treatment effects were detected for most traits; the most significant variation was observed for K⁺/Na⁺ (p\u0026thinsp;\u0026le;\u0026thinsp;0.01) and for Na⁺, Na⁺/K⁺, SOD, and APX (\u003cem\u003ep\u0026thinsp;\u0026le;\u0026thinsp;0.05\u003c/em\u003e or p\u0026thinsp;\u0026le;\u0026thinsp;0.1) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Moreover, K\u003csup\u003e+\u003c/sup\u003e, CAT and GR were not significantly associated with the salinity treatment. The replication effect was not significant except for that of Na⁺ and CAT. The genotypic-environmental effect was significant for all traits (p\u0026thinsp;\u0026le;\u0026thinsp;0.01), indicating the importance of testing these genotypes under various environmental conditions to select the most environmentally stable genotypes.\u003c/p\u003e\u003cp\u003eThe heritability estimates were very high, ranging from 94 for K\u003csup\u003e+\u003c/sup\u003e and SOD, 98 for K\u003csup\u003e+\u003c/sup\u003e/Na\u003csup\u003e+\u003c/sup\u003e and GR, and 99 for Na\u003csup\u003e+\u003c/sup\u003e, Na\u003csup\u003e+\u003c/sup\u003e/K\u003csup\u003e+\u003c/sup\u003e, P, APX, and CAT (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These high heritabilities indicate that these traits are under high genetic factor control.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAnalysis of variance (ANOVA) and heritability of sodium and potassium traits and antioxidant enzyme activities in 7 contrasting genotypes.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"10\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSource of Variance\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eK\u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNa\u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eK\u003csup\u003e+\u003c/sup\u003e/Na\u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNa\u003csup\u003e+\u003c/sup\u003e/K\u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eAPX\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eCAT\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eGR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eSOD\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTreatments\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.58*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26.36**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.30*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e11.26*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e5.98\u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReplications\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.21**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.31\u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4.94*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e2.35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGenotypes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e93.93**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5910.30**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e390.57**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1151.24**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9018.13**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2148.59**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4565.21**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e392.11**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e89.85**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTreatment \u0026times; Genotype\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e57.25**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5455.80**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e332.69**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1098.89**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e12438.75**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e965.85**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e605.26**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e565.14**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e42.63**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHeritability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e94\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e*, **, and *** represent significance levels of P\u0026thinsp;\u0026le;\u0026thinsp;0.05, 0.01 and 0.001, respectively.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e\u003cb\u003eCorrelation analysis\u003c/b\u003e\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e4.1.1 Correlation coefficients for the traits of the 7 contrasting genotypes\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWhen the traits of interest were controlled for, the significant positive and negative correlations were low to highly significant (Supplementary Fig.\u0026nbsp;2a, b). Positive and significant correlations were detected between APX-C and FW-C, with r\u0026thinsp;=\u0026thinsp;0.82*, CAT-C and K/Na-C, with r\u0026thinsp;=\u0026thinsp;0.77*, and between Na-C and Na/K-C, with r\u0026thinsp;=\u0026thinsp;0.77*. Negative and significant correlations were observed between Na-C and GR-C (r =-0.83*), K/Na-C and Na-C (r=-80*), and Na/K-C with K/Na-C and CAT-C (r=-99*** and \u0026minus;\u0026thinsp;83*, respectively). Unexpectedly, P-C was highly negatively correlated with APX-C and FW-C (r=-99*** and \u0026minus;\u0026thinsp;0.76, respectively). No significant correlations were detected among the enzyme-related traits (Supplementary Fig.\u0026nbsp;2a).\u003c/p\u003e\u003cp\u003eUnder salinity, the correlations ranged from high to very high in terms of negative significance and high positive significance (Figure b). Strong positive correlations were detected between SOD-S and RL-S (r\u0026thinsp;=\u0026thinsp;0.93***) and between Na/K-S and Na-S (r\u0026thinsp;=\u0026thinsp;0.99***). Highly significant correlations were observed between K/Na-S and Na/K-C and Na-S (r=-99** and 0.99**, respectively). Additionally, under salinity, no significant correlations were detected among the enzymatic activity-related traits (Supplementary Fig.\u0026nbsp;2b).\u003c/p\u003e\u003cp\u003eTo consider the expected correlations between the gene expression of the two genes \u003cem\u003eAVP1\u003c/em\u003e and \u003cem\u003eNHX1\u003c/em\u003e, we conducted a correlation analysis for the four genotypes that were considered for gene expression analysis. Under the control, the expression of the \u003cem\u003eAVP1\u003c/em\u003e gene was highly significantly positively correlated with SL-C (r\u0026thinsp;=\u0026thinsp;96*), RSR-C (r\u0026thinsp;=\u0026thinsp;0.99**), and K/Na-C (r\u0026thinsp;=\u0026thinsp;0.95*). Moreover, it was significantly negatively correlated with Na/K-C (r=-0.97*). Under salinity, \u003cem\u003eAVP1\u003c/em\u003e showed a highly positive significant correlation with RSR-S (r\u0026thinsp;=\u0026thinsp;0.99*). The expression of \u003cem\u003eNHX1-C\u003c/em\u003e was highly positively and significantly correlated with that of NHX1-S (r\u0026thinsp;=\u0026thinsp;99*) (Fig.\u0026nbsp;5). For the remaining control traits, P-C was negatively and significantly correlated with APX-C (r=-99*), K-C was strongly positively correlated with Na-S and Na/K-S (r\u0026thinsp;=\u0026thinsp;0.99** and 1.00**, respectively), and K-C was strongly negatively correlated with K/Na-S (r=-0.98*). Under salinity, SL-S exhibited very high positive and significant correlations with G%-S and FW-S (r\u0026thinsp;=\u0026thinsp;0.99* and 0.96*, respectively). CAT-S was positively and significantly correlated with APX-C (r\u0026thinsp;=\u0026thinsp;0.96*); likewise, GR-S was positively and significantly correlated with RSR-C and CAT-C, with r\u0026thinsp;=\u0026thinsp;0.97* and 0.97*, respectively. SOD-S and RL-S were positively and significantly correlated, with r\u0026thinsp;=\u0026thinsp;0.95*. K/Na-S exhibited very high negative and positive correlations with K/Na-S and Na-S (r=-0.99* and 0.99**, respectively) (Fig.\u0026nbsp;5).\u003c/p\u003e\u003cp\u003e\u003cb\u003eBidirectional clustering heatmap for all traits under control and salinity conditions\u003c/b\u003e:\u003c/p\u003e\u003cp\u003eIn the first level of clustering, the genotypes were clustered according to their performance under control and salinity conditions into two main clusters. The first cluster included the genotypes under control conditions, and the second cluster included the genotypes under saline conditions. The first cluster is subdivided into two subclusters: the first subcluster includes three tolerant genotypes; 1018d clustered separately, and Javelin 48 and Ghati clustered together. The second subcluster includes the remaining four genotypes; 1049 (tolerant) and Soha-5 (sensitive) are grouped together, whereas Kandahar and Kule are grouped together. Similarly, the second main cluster (genotypes under salinity) was further subdivided into two subclusters, in which the genotypes presented the same clustering pattern as the control (Fig.\u0026nbsp;6).\u003c/p\u003e\u003cp\u003eThe second level of clustering was for traits; at this level, the traits were subdivided into two major clusters. The first major cluster included all of the morphological traits except NoR; moreover, it included two physiological traits, P and K/Na. The first cluster was subdivided into three subclusters; the P content was separated into the first subcluster, the second subcluster included the RSR, and the third subcluster included the GP and RL. Similarly, the second cluster was subclustered into subcluster one, which included FW and G%, and subcluster two, which included SL and K/Na. The second major cluster included enzyme activity-related traits and Na-, K-, and P-related traits. It was further subdivided into two subclusters, and CAT and K were clustered into the first subcluster. Moreover, the second subcluster includes four subclusters: the first includes Na and Na/K, the second includes APX, the third includes SOD, and the fourth includes NoR and GR (Fig.\u0026nbsp;6).\u003c/p\u003e\u003cp\u003e\u003cb\u003ePrincipal component analysis (PCA) for all traits under control and salinity conditions\u003c/b\u003e:\u003c/p\u003e\u003cp\u003eIn the biplot, at the trait level, the first PCA1 and the second PCA explained 34.5% and 15.7%, respectively (Fig.\u0026nbsp;7a). The traits were clustered into two main groups. The first group (red group) included the traits that accounted for the greatest proportion of variation under the control treatment, and the second group (blue group) included the traits that accounted for the greatest proportion of variation under salinity. The opposite directions of the arrows may reflect the correlations between these traits; for example, K/Na and Na/K exhibited the highest negative correlation, with r=-1.00***. The length of the arrow indicates the contribution of the corresponding trait to the variation among the genotypes under a certain treatment. For example, K/Na and RL are the most discriminative factors under control, whereas Na and Na/K are the most discriminative factors among the genotypes under salinity (Fig.\u0026nbsp;7a).\u003c/p\u003e\u003cp\u003eAt the genotype level, similar to bibelot, PCA1 and PCA explained 34.5% and 15.7%, respectively, of the variation (Fig.\u0026nbsp;7b). The genotypes were grouped into two groups. The first group (red group) shows the performance of the genotypes under the control, and the second group (blue group) presents the performance of the genotypes under salinity. Notably, genotypes such as Kule, Javelin 48, and Ghati presented strong (genotype \u0026times; treatment) interactions and occupied distinct positions across both PCA1 and PCA2 (Fig.\u0026nbsp;7b). The sensitive genotype Sohag-5 shows relatively modest (genotype \u0026times; treatment) interactions, with small shifts across both PCA1 and PCA2 (Fig.\u0026nbsp;7b).\u003c/p\u003e\u003cp\u003e\u003cb\u003eGene expression profiling of the vacuolar pyro phosphatase (\u003c/b\u003e\u003cb\u003eAVP1\u003c/b\u003e\u003cb\u003e) gene and the Na\u003c/b\u003e\u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e/H\u003c/b\u003e\u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e \u003cb\u003eantiporter (\u003c/b\u003e\u003cb\u003eNHX1\u003c/b\u003e\u003cb\u003e) gene under control conditions and salt stress\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe expression patterns of both the Vacuolar pyro phosphatase gene, similar to AVP1 (\u003cem\u003eTaAVP1\u003c/em\u003e), and the Na\u003csup\u003e+\u003c/sup\u003e/H\u003csup\u003e+\u003c/sup\u003e antiporter (\u003cem\u003eNHX1\u003c/em\u003e) gene were previously reported in salt-tolerant Chinese wheat [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. The seven contrasting genotypes were used for measuring the Na and K contents and antioxidant enzyme activities. Four contrasting genotypes, including the sensitive genotype 122 (Sohag-5, from Egypt) and three tolerant genotypes Javelin 48, from South Australia, Kandahar, from Afghanistan and 1018d, from Morocco, were selected to quantify the gene expression patterns of both genes under control and salinity conditions (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eUnder salinity relative to the control, both genes presented low- to moderate-fold changes (Supplementary Fig.\u0026nbsp;3). The two genes presented different expression patterns in the sensitive genotype (Sohag-5); \u003cem\u003eAVP1\u003c/em\u003e was slightly upregulated, with a 1.05-fold change, whereas \u003cem\u003eNHX1\u003c/em\u003e did not change. The tolerant genotypes differentially expressed both the \u003cem\u003eAVP1\u003c/em\u003e and \u003cem\u003eNHX1\u003c/em\u003e genes. The AVP1 gene \u003cem\u003ewas\u003c/em\u003e upregulated the most in Javelin 48, with a 1.43-fold change, followed by Kandahar, with a 1.05-fold change; meanwhile, 1018d was differentially expressed, and \u003cem\u003eTaAVP1\u003c/em\u003e was downregulated (Fig.\u0026nbsp;8, Supplementary Fig.\u0026nbsp;3). Similarly, for the \u003cem\u003eNHX1 gene\u003c/em\u003e, the three tolerant genotypes presented different profiles: Javelin 48 presented the greatest upregulation, with a 1.42-fold change, followed by Kandahar, with a 1.16-fold change, while 1018d presented different patterns, and \u003cem\u003eNHX1\u003c/em\u003e was downregulated (Fig.\u0026nbsp;8, Supplementary Fig.\u0026nbsp;3).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAs plants cannot escape abiotic stresses such as salinity, plants have developed various mechanisms to combat the damaging effects of these stresses. Salinity causes alterations in all plant parts, extending from a single cell to the whole plant. The response of plants to salinity encompasses changes in several pathways, such as ion homeostasis, antioxidant machinery activation and changes in the genes that regulate ion cycling via exclusion and sequestration. Notably, ion homeostasis via exclusion or vacuolar sequestration is a profound mechanism for salinity tolerance.\u003c/p\u003e\u003cp\u003eThe genotypes included in the current study revealed highly significant genotypic variation (\u003cb\u003ep\u0026thinsp;\u0026le;\u0026thinsp;0.01\u003c/b\u003e) for all measured traits (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This suggests that considerable genetic diversity exists among the tested genotypes regarding both ion-related traits (K⁺, Na⁺, K⁺/Na⁺, Na⁺/K⁺, P) and antioxidant enzyme activities (SOD, CAT, APX, GR), indicating that these traits represent valuable selection criteria for salinity tolerance in wheat. Given the high heritability and strong genetic control observed (0.94 to 0.99), this finding highlights the considerable genetic control of the measured traits and substantial genetic gains. These findings indicate the potential for genetic improvement through selection of genotypes with superior ionic homeostasis and antioxidant responses under salinity stress. In terms of the genotypic response to salinity, Sohag-5 consistently clustered separately from the tolerant genotypes under salinity conditions, confirming its divergent response profile, whereas the tolerant genotypes (especially Kandahar, 1018d, and Kule) grouped closely, reflecting adaptive traits shared under salinity stress (Fig.\u0026nbsp;6). Compared with the Sohag-5-sensitive genotype, the Sohag-5-tolerant genotype presented greater genotypic plasticity, which was reflected by the narrow plasticity of the Sohag-5-tolerant genotype, which was reflected by its placement under control and salinity conditions (Fig.\u0026nbsp;7b).\u003c/p\u003e\u003cp\u003e\u003cb\u003eRoles of mineral-related traits and antioxidant enzymes in salinity tolerance\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOur results revealed that the sensitive genotype (Sohag-5) accumulated high levels of Na\u003csup\u003e+\u003c/sup\u003e under salinity compared with the control. The tolerant genotypes presented different responses and were subdivided into two groups. The first group included Javelin 48, Ghati and 1018d, which maintained low levels of Na, low Na\u003csup\u003e+\u003c/sup\u003e/K\u003csup\u003e+\u003c/sup\u003e values, high K values and high K\u003csup\u003e+\u003c/sup\u003e/Na\u003csup\u003e+\u003c/sup\u003e values under salinity stress (Supplementary Fig.\u0026nbsp;1). The second group included Kandahar, Kule and 1049, which maintained high levels of Na, low levels of K, high Na\u003csup\u003e+\u003c/sup\u003e/K\u003csup\u003e+\u003c/sup\u003e and low K\u003csup\u003e+\u003c/sup\u003e/Na\u003csup\u003e+\u003c/sup\u003e (Supplementary Fig.\u0026nbsp;1). These results indicate that tolerant genotypes have different mechanisms to tolerate salinity. More likely, Javelin 48 and Ghati can exclude excess Na\u003csup\u003e+\u003c/sup\u003e and retain the Na\u003csup\u003e+\u003c/sup\u003e and K\u003csup\u003e+\u003c/sup\u003e levels at healthy concentrations for all biological processes. On the other hand, salt-tolerant Na\u003csup\u003e+\u003c/sup\u003e accumulators can use it to maintain osmotic adjustment to maintain the water uptake rate. Our findings revealed that the tolerant genotypes accumulated high concentrations of K\u003csup\u003e+\u003c/sup\u003e except for Kanda; nevertheless, it is still among the tolerant genotypes that might benefit from the accumulation of excess Na\u003csup\u003e+\u003c/sup\u003e. Similarly, in young Arabidopsis seedlings, natural variation in salinity tolerance is achieved by maintaining high K\u003csup\u003e+\u003c/sup\u003e and K\u003csup\u003e+\u003c/sup\u003e and K\u003csup\u003e+\u003c/sup\u003e/Na\u003csup\u003e+\u003c/sup\u003e ratios in the most tolerant genotypes [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. In support of our results, in both Arabidopsis and wheat at the seedling stage, high K\u003csup\u003e+\u003c/sup\u003e concentrations maintain plant growth under salinity stress by maintaining a high K\u003csup\u003e+\u003c/sup\u003e/Na\u003csup\u003e+\u003c/sup\u003e ratio, decreasing the Na\u003csup\u003e+\u003c/sup\u003e/K\u003csup\u003e+\u003c/sup\u003e ratio, reducing reactive oxygen species production and increasing the activity of antioxidant enzymes [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. The retention of high K\u003csup\u003e+\u003c/sup\u003e under salinity stress confers salinity tolerance in various cereals, including rice [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e], wheat [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e] and barley [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Potassium is a key player in conferring salinity tolerance by tailoring various biological processes [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. In line with our results, several studies reported that K\u003csup\u003e+\u003c/sup\u003e/Na\u003csup\u003e+\u003c/sup\u003e is essential for salinity tolerance in bread wheat [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e], barley [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e], and maize [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eNotably, the tolerant genotypes Kandahar, 1049 and Kule maintained high Na\u003csup\u003e+\u003c/sup\u003e even more than the most sensitive genotype (Sohag-5) did (Supplementary Fig.\u0026nbsp;1); more likely, they have other mechanisms that tailor their salinity tolerance. Compared with the remaining tolerant genotypes, they likely presented more efficient portioning and localization of the excessive Na content; the greatest increase in Na content under salinity relative to the control was 10.62-, 11.40- and 12.79-fold greater for 1049, Kandahar and Kuli, respectively, and presented the highest Na/K ratios (Fig.\u0026nbsp;1, Supplementary Fig.\u0026nbsp;1). Moreover, Kule maintained the highest P content under salinity, which may help in seedling growth or as an osmoticum. In support of our results, salinity- and sodality-tolerant wheat lines retained high levels of Na\u003csup\u003e+\u003c/sup\u003e [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e], demonstrating that salinity tolerance can be conferred by the use of Na\u003csup\u003e+\u003c/sup\u003e for osmotic adjustment. Under salinity stress, K\u003csup\u003e+\u003c/sup\u003e uptake is reduced; in such cases, Na\u003csup\u003e+\u003c/sup\u003e represents a cheap osmoticum that can replace the biosynthesis of organic osmolytes, which is time- and energy-consuming for the cells (Munns et al., 2020b; Shabala et al., 2020). Additionally, Na\u003csup\u003e+\u003c/sup\u003e can compensate for K\u003csup\u003e+\u003c/sup\u003e deficiency, enabling continuous shoot growth (Shabala et al., 2020). Phosphorus availability helps maintain other essential minerals, such as Mg\u003csup\u003e2+\u003c/sup\u003e, and Na\u003csup\u003e+\u003c/sup\u003e exclusion (reviewed by Khan et al., 2023). Ashraf et al., (2023) reported that, in wheat, salinity stress increased the Na\u003csup\u003e+\u003c/sup\u003e content in both salt-tolerant and salt-sensitive genotypes; nevertheless, the tolerant genotypes presented high K\u003csup\u003e+\u003c/sup\u003e/Na\u003csup\u003e+\u003c/sup\u003e ratios compared with the sensitive genotypes. Similarly, six Malawian tomato cultivars were evaluated for salinity tolerance under 200 mM NaCl, and the tolerant cultivar retained high K\u003csup\u003e+\u003c/sup\u003e and low Na\u003csup\u003e+\u003c/sup\u003e and, in turn, high K\u003csup\u003e+\u003c/sup\u003e/Na\u003csup\u003e+\u003c/sup\u003e relative to the sensitive cultivar [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn the present study, all the genotypes presented increased antioxidant enzyme activities, with the exception of SOD in Sohag-5, GR in 1018d, and CAT and GR in Kule (Fig.\u0026nbsp;3). The increase in SOD is expected, as SOD represents the frontline of a plant\u0026rsquo;s ROS scavenging system. SOD catalyzes the first step to neutralize ROS via the conversion of O\u003csub\u003e2\u003c/sub\u003e to H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2,\u003c/sub\u003e which remains toxic to the cell; therefore, it is catalyzed by CAT into H\u003csub\u003e2\u003c/sub\u003eO and O\u003csub\u003e2\u003c/sub\u003e [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. In line with our results, an increase in SOD activity was observed under salinity stress in tolerant wheat genotypes at the seedling stage [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. Similarly, in wheat at the seedling stage, compared with the control treatment, the 120 mM NaCl treatment increased the SOD level (Rady et al., 2019a). Our results revealed that SOD was highly positively correlated with RL_S, r\u0026thinsp;=\u0026thinsp;0.93*** (Fig.\u0026nbsp;4b). SOD activity increased in all the genotypes but decreased in Sohag-5, indicating that SOD activity is involved in salinity tolerance. SOD improved plant growth under salinity stress in Arabidopsis [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe APX activity increased in all the genotypes, including the sensitive genotype Sohag-5, and the increase was more pronounced in the tolerant genotype (Fig.\u0026nbsp;3). These results suggest that APX contributes to the salinity tolerance of tolerant genotypes, even those with high Na contents. For example, the APX activity of Ghati and Kuli increased the most strongly, by 14.10- and 9.20-fold, respectively. Similarly, 1049 resulted in a 7.60-fold change in the GR. APX was found to be positively correlated with plant growth under salinity in Arabidopsis [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e]. This may be attributed to the high affinity of APX for H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e in different organelles when ascorbate is used as an electron donor [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. APX alleviation increased the salinity tolerance of wheat under salinity stress caused by 120 mM NaCl (Rady et al., 2019a). APX markedly increased under 350 mM NaCl treatment in wheat neglected and ancestral relatives at the young plant growth stage, and the expression of the APX gene was highly upregulated [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. Similar findings for APX increase and APX gene upregulation were reported in two contrasting wheat varieties, and the tolerant genotypes presented higher APX contents and APX gene expression than did the salt-sensitive variety [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e]. Compared with that in sensitive cultivars, APX significantly increased under salinity stress in salt-tolerant cultivars [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFor GR, a genotype-dependent pattern was observed, and salinity stress increased GR in all the genotypes except the two tolerant genotypes Kule and 1018d (Fig.\u0026nbsp;3). The greatest increases were observed in the two tolerant genotypes, Ghati and Javelin 48, with 5.7- and 8.6-fold changes, respectively. Several studies have reported an increase in GR in wheat under different concentrations of salinity stress and at different growth stages [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan additionalcitationids=\"CR74\" citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e]. In a comparative study between two Egyptian wheat cultivars, Misr 2 and Sakha 95, the cultivar Misr 2 retained high GR levels and tolerated salinity better than Sakha 95 did [\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e]. The GR is a key player under abiotic stresses, especially salinity, and maintains optimum levels of the reduced form of glutathione, which is vital for ROS homeostasis through the glutathione‒ascorbate cycle.\u003c/p\u003e\u003cp\u003eTaken together, the antioxidant enzymes SOD, CAT, APX and GR play a protective role in plant tolerance to salinity by neutralizing the oxidative damage caused by an overdose of ROS resulting from salinity stress. Our results revealed intraspecific variability for each enzyme. Salinity stress increased enzymatic activity even in the salt-sensitive genotype Soahg-5. The tolerant genotypes presented the highest levels of enzymatic activity (Fig.\u0026nbsp;6 and Fig.\u0026nbsp;7a, b).\u003c/p\u003e\u003cp\u003e\u003cb\u003eGene expression profiling of the genes encoding\u003c/b\u003e \u003cb\u003eAVP\u003c/b\u003e \u003cb\u003e(a vacuolar pyrophosphatase similar to AVP1) and\u003c/b\u003e \u003cb\u003eNHX1\u003c/b\u003e \u003cb\u003e(a Na\u003c/b\u003e\u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e/H\u003c/b\u003e\u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e \u003cb\u003eantiporter) under salinity stress\u003c/b\u003e:\u003c/p\u003e\u003cp\u003eThe expression profiles of both genes were estimated in four contrasting genotypes, one salt-sensitive genotype (Sohag-5) and three salt-tolerant genotypes (Javelin 48, Kandahar and 1018d). The two genes presented different expression profiles under salinity treatment compared with the control. In the sensitive genotype (Sohag-5), the two genes presented different expression profiles: \u003cem\u003eTaAVP\u003c/em\u003e was slightly upregulated (1.05-fold), whereas \u003cem\u003eNHX1\u003c/em\u003e remained unchanged under salinity stress (Fig.\u0026nbsp;8, Supplementary Fig.\u0026nbsp;2). The tolerant genotypes presented differential expression of both genes. The highest expression levels of \u003cem\u003eAVP1\u003c/em\u003e and \u003cem\u003eNHX1\u003c/em\u003e were observed in Javelin 48 (1.4-fold relative to the control), followed by Kandahar (1.14-fold relative to the control), while both genes were downregulated at 1018 d (Fig.\u0026nbsp;8, Supplementary Fig.\u0026nbsp;2). These findings indicate that gene expression varied among the sensitive and tolerant genotypes as well as within the tolerant set in a genotype-specific pattern. In the context of low expression levels, our results are in agreement with the findings of Genc et al., (2019), who reported low expression levels of both genes in low-Na\u003csup\u003e+\u003c/sup\u003e wheat. Our results are in agreement with the findings of Nakayama et al., (2022), who reported that, in tolerant common wheat, salt-responsive genes presented a genotype-specific pattern and that the Na\u003csup\u003e+\u003c/sup\u003e/H\u003csup\u003e+\u003c/sup\u003e antiporter gene was significantly upregulated in some salt-tolerant lines and downregulated in other tolerant lines. These results indicate that \u003cem\u003eNHX1\u003c/em\u003e was differentially expressed in the tolerant genotypes. However, the tolerance genotype Javelin 48 presented the highest expression level of both genes (expectedly included in Na sequestration in the vacuole), the lowest Na\u003csup\u003e+\u003c/sup\u003e content, the highest K\u003csup\u003e+\u003c/sup\u003e and K\u003csup\u003e+\u003c/sup\u003e/Na\u003csup\u003e+\u003c/sup\u003e ratio and the lowest Na-S/Na-C fold change among the salt-tolerant genotypes. More likely, it has an efficient Na-excluding active allele of membrane antiporters (\u003cem\u003eNHX2\u003c/em\u003e), which helps in maintaining physiological Na levels. Another possibility is that \u003cem\u003eNHX1\u003c/em\u003e favored the vacuolar sequestration of K at the expense of Na. In contrast, in Kandahars (tolerant to high Na concentrations), Na is sequestered at the expense of K, reflecting the multiple functions of \u003cem\u003eNHX1\u003c/em\u003e in tolerant wheat genotypes. In the present study, both the \u003cem\u003eAVP1\u003c/em\u003e and \u003cem\u003eNHX1\u003c/em\u003e genes were downregulated in the tolerant genotype 1018d, which presented the highest Na\u003csup\u003e+\u003c/sup\u003e content among the tolerant genotypes, indicating that this genotype uses another mechanism to tolerate salinity, such as osmotic adjustment and activation of antioxidant enzymatic systems. In the present study, AVP1 was strongly positively correlated with the RSR (r\u0026thinsp;=\u0026thinsp;0.99*) (Fig.\u0026nbsp;5).\u003c/p\u003e\u003cp\u003eThis finding is in agreement with that of Gaxiola et al., (2001), who reported that the overexpression of \u003cem\u003eTaAVP1\u003c/em\u003e confers salinity tolerance to Arabidopsis transgenic plants relative to wild-type plants. The transgenic plants maintained high levels of both Na\u003csup\u003e+\u003c/sup\u003e and K\u003csup\u003e+\u003c/sup\u003e and retained more water. Nakayama et al., (2022) reported that the NHX genes of two salt-tolerant lines were upregulated via different mechanisms, with the second leading to the upregulation of antioxidant genes.\u003c/p\u003e\u003cp\u003eNotably, there was concomitant upregulation/downregulation of both genes in the tolerant genotypes, indicating that both genes are involved in salt tolerance and that they are likely working in a synchronized way. Coordinate upregulation of NHX1 and AVP1 has been reported in several plant species (Mansour, 2022). \u003cem\u003eAVP1\u003c/em\u003e expression is equivalent to that of \u003cem\u003eNHX\u003c/em\u003e antiporters in several plant species, indicating that \u003cem\u003eAVP1\u003c/em\u003e generates a proton gradient that is essential \u003cem\u003efor the energization of NHX1\u003c/em\u003e, which in turn controls vacuolar Na\u003csup\u003e+\u003c/sup\u003e sequestration, as reviewed by Mansour, (2022). Several studies reported that the coexpression of both the \u003cem\u003eNHX\u003c/em\u003e and AVP genes improved salinity tolerance in transgenic plants that expressed both genes together rather than expressing only one of them; this finding has been demonstrated in various plant species, such as rice, sugar beet, lotus, tobacco, and Arabidopsis [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. In two contrasting wheat genotypes, with respect to salinity tolerance, the expression levels of \u003cem\u003eTVP1\u003c/em\u003e were similar to those of the vacuolar Na\u003csup\u003e+\u003c/sup\u003e/H\u003csup\u003e+\u003c/sup\u003e antiporter (\u003cem\u003eTNHX1\u003c/em\u003e) in different tissues of the two genotypes [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe current study highlights that wheat salinity tolerance is governed by complex, genotype-specific mechanisms that integrate ion homeostasis, antioxidant defense, and gene expression regulation. Tolerant genotypes display diverse strategies, ranging from Na⁺ exclusion and K⁺ retention to Na⁺ sequestration for osmotic adjustment, which is supported by high K⁺/Na⁺ ratios and increased antioxidant enzyme activities. The upregulation of \u003cem\u003eNHX1\u003c/em\u003e and \u003cem\u003eAVP1\u003c/em\u003e in tolerant genotypes suggests a coordinated role in salinity tolerance. The tolerant genotypes Javelin 48 (high K) and Kandahar (high Na) combined effective ion homoeostasis with elevated expression of both genes. These results highlight the plasticity of adaptive responses and provide valuable molecular and physiological markers for improving wheat salinity tolerance through targeted breeding.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll relevant data can be found within the manuscript and its supporting materials, and any further inquiries can be directed to the corresponding author(s).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAS, NH, MA, and YM conceptualization; NH, MA, and YM funding acquisition; NH and AS methodology; YM, MA, and AS wrote the original draft and review.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was funded by the Academy of Scientific Research and Technology (ASRT) under the 6\u003csup\u003eth\u003c/sup\u003e call of master grants, namely, Scientists for Next Generation Scholarships (SNG), Egypt.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there are no potential conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics, Consent to Participate, and Consent to Publish declarations:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;not applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAshraf M, Foolad MR. 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BMC Plant Biology. 2019;19:1\u0026ndash;13.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Wheat, salinity, gene expression, AVP1, NHX1, ion homeostasis, antioxidants","lastPublishedDoi":"10.21203/rs.3.rs-7186942/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7186942/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSalinity is a major constraint on plant development and crop production for main crops such as wheat, which is the most important source of calories, especially at early stages of growth, including seed germination and seedling establishment. Salinity tolerance is a complex trait tailored by several mechanisms, including ion homeostasis, the activation of enzymatic antioxidants, and the alteration of ion transporter genes. Contrasting genotypes of wheat that differed in salinity tolerance were selected from a collection of 172 that were tested under salinity stress (175 mM NaCl) and the control (0 mM NaCl), with the aim of revealing the underlying mechanisms of salinity tolerance in the tolerant genotypes compared with the sensitive ones. These parameters, Na, K and P homeostasis; the presence of enzymatic antioxidants; and the expression profiles of the salinity-responsive ion transporter genes \u003cem\u003eTaAVP1\u003c/em\u003e and \u003cem\u003eNHX1\u003c/em\u003e were measured in one sensitive and six tolerant genotypes. The tolerant genotypes presented higher concentrations of Na\u003csup\u003e+\u003c/sup\u003e and K\u003csup\u003e+\u003c/sup\u003e and higher levels of all the enzymatic antioxidants than did the sensitive ones. The tolerant genotypes differentially expressed \u003cem\u003eAVP1\u003c/em\u003e and \u003cem\u003eNHX1\u003c/em\u003e, which were upregulated in Javelin 48 and Kandahar but downregulated in the tolerant genotype 1018d. These results indicate that the tolerant genotypes differentially expressed the ion transporter genes \u003cem\u003eAVP1\u003c/em\u003e and \u003cem\u003eNHX1\u003c/em\u003e. The tolerant genotype Kule presented the highest Na\u003csup\u003e+\u003c/sup\u003e content and the greatest increase in the levels of the antioxidant enzymes ascorbate peroxidase and glutathione reductase, with 9.20-fold and 2.32-fold changes, respectively, under salinity stress. In conclusion, the tolerant genotypes differed in their response to salinity stress and employed various mechanisms to tolerate salinity.\u003c/p\u003e","manuscriptTitle":"Salinity-induced changes in gene expression, ion homeostasis, and enzymatic antioxidants in contrasting wheat genotypes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-08 06:04:23","doi":"10.21203/rs.3.rs-7186942/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1bd4e8ad-a177-45ff-9645-a76444f2ebaf","owner":[],"postedDate":"August 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-08T06:23:37+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-08 06:04:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7186942","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7186942","identity":"rs-7186942","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}