Introduction
Wheat (Triticum aestivum L.) is the third most significant cereal in the world (Horvath et al., Reference Horvath, Didier, Koenig, Exbrayat, Charmet and Balfourier2009; Clifton and Keogh, Reference Clifton and Keogh2018; Ghotbzadeh and Gianinetti, Reference Ghotbzadeh and Gianinetti2018; Wulff and Dhugga, Reference Wulff and Dhugga2018). The higher level of ploidy and the complexity of the hexaploid wheat genome have increased its physiological and ecological flexibility in comparison with the tetraploid and diploid ancestors (Dubcovsky and Dvorak, Reference Dubcovsky and Dvorak2007; Feldman et al., Reference Feldman, Levy, Fahima and Korol2012). Environmental stresses such as salinity are one of the most important limiting factors in agricultural production worldwide (Subedi et al., Reference Subedi, Gregory, Summerfield and Gooding2000; Khan et al., Reference Khan, Qazi, Rasheed and Mujeeb-Kazi2017; Ghotbzadeh Kermani et al., Reference Ghotbzadeh Kermani, Saeidi, Sabzalian and Gianinetti2019; Jamshidi Goharrizi et al., Reference Jamshidi Goharrizi, Amirmahani and Salehi2019a, Reference Jamshidi Goharrizi, Amirmahani, Fatehi, Nazari and Moosavib, Reference Jamshidi Goharrizi, Moosavi, Amirmahani, Salehi and Nazaric, Reference Jamshidi Goharrizi, Riahi-Madvar, Rezaee, Pakzad, Jadid Bonyad and Ghazizadeh Ahsaeid). Plants react to environmental stresses through their morphological, physiological (Jamshidi Goharrizi et al., Reference Jamshidi Goharrizi, Baghizadeh, Kalantar and Fatehi2020a, Reference Jamshidi Goharrizi, Fatehi, Nazari, Salehi and Malekib) and gene expression changes in all of their organs (Jamshidi Goharrizi et al., Reference Jamshidi Goharrizi, Amirmahani and Salehi2019a).
One of the most important multifunctional amino acids in many metabolism pathways is proline (Verbruggen and Hermans, Reference Verbruggen and Hermans2008; Lehmann et al., Reference Lehmann, Funck, Szabados and Rentsch2010). Proline is made of two different precursors in plants. In the first pathway, glutamate is transformed to proline through two consecutive reductions catalysed by P5CS or Δ1-pyrroline-5-carboxylate synthase and P5CR or pyrroline-5-carboxylate reductase, respectively, and this pathway is the most important pathway of proline biosynthesis in response to salinity stress. Ornithine is the other precursor of proline biosynthesis (Verbruggen and Hermans, Reference Verbruggen and Hermans2008; Špoljarević et al., Reference Špoljarević, Agić, Lisjak, Gumze, Wilson, Hancock and Teklić2011). Furthermore, it has been found that the proline content was higher in tolerant cultivars and under salinity, drought and drought + salinity stresses, than in sensitive cultivars (Jamshidi Goharrizi et al., Reference Jamshidi Goharrizi, Amirmahani and Salehi2019a; Reference Jamshidi Goharrizi, Baghizadeh, Kalantar and Fatehi2020a, Reference Jamshidi Goharrizi, Fatehi, Nazari, Salehi and Malekib).
ATPases can catalyse adenosine triphosphate into adenosine diphosphate and a free phosphate ion and play significant roles in ion transportation (Griffith, Reference Griffith2017). In all eukaryotes, vacuolar-type H+-ATPase is conserved and has the membrane-bound proton-trans-locating V0 sub-complex and cytosol ATP-hydrolyzing V1 sub-complex which includes eight subunits including A, B, C, D, E, F, G and H (Nishi and Forgac, Reference Nishi and Forgac2002). The vacuolar H+-ATPase or V-Type H+-ATPase functions as an electrogenic H+ pump. The wheat E subunit of the V-type H+-ATPase gene, W36, could be up-regulated by cold, salt and drought stresses (Zhang et al., Reference Zhang, Li, Hu, Chen and Min2014). Additionally, W36 protein accumulates in the cytoplasm and has some Cis-acting elements responding to abiotic stresses. Also, the overexpression of W36 gene in Arabidopsis transgenic plants enhances the salt tolerance (Zhang et al., Reference Zhang, Li, Hu, Chen and Min2014).
Abiotic stresses such as salinity and drought (alone or in combination) can change the physiological and biochemical traits, gene expression levels and proteomic profile of plants to a large extent (Jamshidi Goharrizi et al., Reference Jamshidi Goharrizi, Wilde, Amirmahani, Moemeni, Zaboli, Nazari, Moosavi and Jamalvandi2018; Jamshidi Goharrizi et al., Reference Jamshidi Goharrizi, Amirmahani and Salehi2019a, Reference Jamshidi Goharrizi, Amirmahani, Fatehi, Nazari and Moosavib, Reference Jamshidi Goharrizi, Moosavi, Amirmahani, Salehi and Nazaric, Reference Jamshidi Goharrizi, Riahi-Madvar, Rezaee, Pakzad, Jadid Bonyad and Ghazizadeh Ahsaeid; Reference Jamshidi Goharrizi, Baghizadeh, Kalantar and Fatehi2020a, Reference Jamshidi Goharrizi, Fatehi, Nazari, Salehi and Malekib). Elsewhere, in response to moisture stress, the proteomic profile of wheat changed significantly (Nazari et al., Reference Nazari, Moosavi, Maleki and Jamshidi Goharrizi2020). Furthermore, it was proven that wheat's agronomic traits are extremely affected in response to abiotic stresses (Nazari et al., Reference Nazari, Goharrizi, Moosavi and Maleki2019).
The main aim of this study was to select the most resistant and sensitive bread wheat cultivars under moderate and high salinity stress levels. In the next step, we evaluated the proline content plus P5CS and W36 genes expression levels in these cultivars.
Materials and methods
Plant material
The experiment was conducted on 14 varieties of bread wheat (online Supplementary Table S1), cultivated in different regions of Iran. These cultivars were collected from agricultural research centres in Kerman and Shiraz, and evaluated under different conditions during 2018–2019 in Kerman, Iran.
Experimental design
This experiment was conducted at the Graduate University of Advanced Technology, located 28 km away from Kerman in Mahan during 2018–2019. The soil type was clay – loam in surface (0–20 cm) with pH = 7.78 and 0.61% organic matter. The total N was 0.49%, available P and exchangeable K were 3.4 ppm and 2.01 Meq 100/g, respectively. The experiment was in the form of split-plot based on a randomized complete block design with three replications in non-stress (0 mM NaCl) and salinity stress (75 mMNaCl and 150 mMNaCl) conditions. The plot contained nine separated blocks (three blocks for 0 mM NaCl, three blocks for 75 mM NaCl and three blocks for 150 mM NaCl). Every block contained 14 rows and in each row 15 of each cultivar were cultured. The width and length of each row were 0.5 and 3 m, respectively. Row spacing was 1 m from each other. For uniform growth until the stage of 2–3 leaves, normal water was used after which salty water was utilized for irrigation. Three salt concentrations were used as follows: 0 mM NaCl (control), 75 mM NaCl (moderate salinity level) and 150 mM NaCl (high salinity level), with a full-strength nutrient solution. The salinity treatments began from 25 and 50 mM and increased step by step in aliquots of 25 and 50 mM on other days until the desired treatment concentration reached 75 and 150 mM NaCl, respectively. The accumulation of soil salinity was estimated by EC meter after every irrigation. Then, the shortage or abundance of NaCl was managed through irrigation with a full-strength nutrient solution without or with NaCl. In our research, after three times of irrigation, the plants were irrigated by the full-strength nutrient solution without NaCl to organize the accumulation of NaCl concentration in the next irrigations. This kind of irrigation prevented the accumulation of NaCl in soil. In order to prevent drought stress, the irrigation was carried out once a week until physiological maturity. After sowing and harvesting, five samples from each row were selected and analysed. Traits such as plant height (PH), number of internodes (NI), number of stems per plant (NSP), number of fertilized stems (NFS), flag leaf length (FLL), flag leaf width (FLW), flag leaf distance to spike (FLDS), peduncle length (PL), number of spikelets per spike (NSPS), spike length with awn (SLA), spike length without awn (SLWA), awn length (AL), shoot width (SW), number of seeds per spike (NSS), number of grains per plant (NGP), the weight of one thousand seeds (WTS) and plant yield (PY) were measured in this study.
Sample preparation for proline content measurement
With some modification, Bates et al. method was performed. To this end, 100 mg of flag leaves was homogenized in 10 ml of 3% aqueous sulfosalicylic acid and then centrifuged at 13,000 g for 10 min. In the next step, the supernatant was removed using a sampler and transferred into a new micro-tube to which the same content of glacial acetic acid and ninhydrin solution was added. Also, a separate micro-tube containing 3 ml of sulfosalicylic acid was used as blank. At 100°C and for 1 h, micro-tubes were heated and then cooled, to which 6 ml of toluene was added. At 520 nm, the absorption of the toluene was calculated using a spectrophotometer and proline quantity was calculated via a standard curve (Bates et al., Reference Bates, Waldren and Teare1973).
RNA extraction, cDNA synthesis and real-time polymerase chain reactions (RT-PCRs)
According to the manufacturer's instruction and using RNX plus solution (Cinnagen, Tehran, Iran), total RNA was extracted from flag leaves of Backcross, Roshan, Mihan and Shirudi cultivars as described previously (Jamshidi Goharrizi et al., Reference Jamshidi Goharrizi, Wilde, Amirmahani, Moemeni, Zaboli, Nazari, Moosavi and Jamalvandi2018). DNase (Thermo Fisher Scientific, USA) was used for removing DNA. In addition, 1% agarose gel electrophoresis was used to prove the integrity of the isolated RNA. RNA samples with OD 260/280 and OD 260/230 > 2 were used for cDNA synthesis. First-strand cDNA was synthesized using 1 μg of total RNA by PrimeScriptTM RT reagent Kit (Takara, Japan) following the manufacturer's guidelines. P5CS primers (GenBank: KM523670.1) for amplification with a length of 212 base pairs and melting temperature of 60°C were designed for RT-PCR with the following sequences: P5CSF: 5′-CCATGCTGATGGTGTTTGTC-3′ and P5CSR:5′-CAGGCCCGCAATAAAGATTA-3′. Further, W36 Primers (GenBank: DQ272489.1) with a length of 210 base pairs and melting temperature of 60°C were designed as follows: W36F: 5′- TTCGGTTGAAAGAGCCAGCT -3′ and W36R: 5′- CCAGCACAACACCTCCATG -3′. According to our previous findings, GAPDH was selected as the most stable reference gene under salinity and drought stresses in wheat. Thus, this internal control gene was considered as the reference gene (Paolacci et al., Reference Paolacci, Tanzarella, Porceddu and Ciaffi2009; Long et al., Reference Long, Liu, Rocheleau, Ouellet and Chen2011; Jamshidi Goharrizi et al., Reference Jamshidi Goharrizi, Wilde, Amirmahani, Moemeni, Zaboli, Nazari, Moosavi and Jamalvandi2018). Forward primer GAPDH, 5′-GGTGCCAAGAAGGTCATCAT-3′ and reverse primer GAPDH, 5′-TGGTCATCAAACCCTCAACA-3′ produce a product with 187 base pairs length at 60°C melting temperature (Nazari et al., Reference Nazari, Goharrizi, Moosavi and Maleki2019). The accuracy of all primers was checked by NCBI Blast search tool (Amirmahani and Jamshidi Goharrizi, Reference Amirmahani and Jamshidi Goharrizi2018). RT-PCR was performed on a Rotor-Gene 3000 Real-time Fast thermocycler (Sydney, Australia) based on the following conditions: 90°C for 35 s, 45 cycles of 95°C for 10 s and melting temperature of each primer for 30 s. The negative control was used to confirm the accuracy of the reactions. Also, 2−ΔCt method was used for calculating the expression levels of W36 and P5CS genes.
Stress tolerant indices
Six indices including mean productivity (MP), geometric mean productivity (GMP), harmonic mean (HARM), stress-tolerant index (STI), yield stability index (YSI) and yield index (YI) were calculated for each cultivar based on their seed yield under stress and normal conditions according to the following formulas:
In these equations, Yp and Ys represent the yield obtained under the control and stress conditions, respectively. Also, the 
$\overline Y _p$ and 
$\overline Y _s$ indicate the average yield for all cultivars under normal and stresses conditions, respectively.
Statistical analysis
This study was conducted in a split-plot experiment using a randomized complete block design with three replicates. Analysis of variance (ANOVA) and mean comparison were performed using SAS v 9.1 (SAS Institute, USA). Duncan test at 1 and 5% levels was used to determine significant differences. The correlation coefficients between the studied indices and plant yield were calculated using proc CORR of SAS. To select the most sensitive and tolerant cultivars, PCA (based on the principal component method by varimax orthogonal rotation) and Ward's cluster analyses (through similarity level measurement and Euclidean distance) were undertaken in Minitab v 16.0 (Minitab, UK). Also, multiple plots were drawn by Stat graphics software (v XVII). The proline content and gene expression levels graphs were drawn using graph pad prism v 6.0 software.
Results
Mean comparison and variance analysis
The results of ANOVA indicated that there was a significant influence of salinity stress and cultivars on all studied traits (online Supplementary Table S2). The significant effect of salinity × cultivar for all traits (except FLW and NSS) showed that the response of cultivars to stress and non-stress conditions was different. For more information, comparison of means in the cultivars (online Supplementary Table S3) indicated that salt stress caused a significant reduction in most traits in the majority of cultivars with increasing salinity stress treatments (except for NI (G5 9 and 13), FLL (G9), PL (G 11), NSPS (G 4), SLA (G 10) and AL (G 5)).
Biplot analysis
Regarding the bi-plot analysis, based on the first two principal components (online Supplementary Figs S2 and S3), G7 and G9 (Backcross and Roshan) were identified as the resistant cultivars, while G5 and G4 (Mihan and Shirudi) were identified as the sensitive ones under 75 and 150 mM NaCl conditions.
Cluster analysis
The results of cluster analysis under normal conditions for 14 evaluated cultivars are shown in online Supplementary Fig S4. According to this classification, the studied wheat cultivars were classified into four groups: (i) G1, G3, G7 and G9; (ii) G14; (iii) G2, G4, G6, G8, G12 and G13; and (iv) G5, G10 and G11. Furthermore, at the moderate salinity level, based on online Supplementary Fig. S5, the 14 wheat cultivars were classified into four groups: (i) G7, G9 and G1; (ii) G3; (iii) G2 and G14; finally, (iv) G4, G8, G5, G11, G6, G10, G12 and G13. Eventually, at the high salinity level, based on online Supplementary Fig. S6, the cultivars were divided into four main groups: (i) G1, G9 and G7; (ii) G3; (iii) G2, G6, G13, G11, G12 and G14; and (iv) G5, G4, G8 and G10.
Multiple plot analysis
Six tolerance indices including STI, MP, GMP, HARM, YSI and YI were calculated to assess the salinity tolerance of the studied cultivars. All studied indices were estimated based on plant yield at moderate and severe salinity stress conditions separately. Then, multiple plots were drawn using six indices and plant yield at two salinity conditions (S1: moderate and S2: high salinity stress). These indices had a high correlation with plant yield under the three studied conditions (online Supplementary Table S4). According to multiple plots, the Backcross and Roshan were identified as the most tolerant cultivars, while Mihan and Shirudi were recognized as the most sensitive ones (online Supplementary Fig. S7).
Proline content
According to our results, the proline content increased in response to rising stress levels. In this regard, the proline content elevation was higher in the tolerant genotypes (Backcross and Roshan) than in the sensitive cultivars (Mihan and shirudi) under 75 mM NaCl, as moderate stress condition and 150 mM NaCl, as severe stress condition compared to the normal environment. The proline contents were calculated as 0.106, 0.574 and 0.914 (μmol/g fw) for Backcross, 0.105, 0.562 and 0.949 (μmol/g fw) for Roshan, 0.101, 0.249 and 0.452 (μmol/g fw) for Mihan and 0.099, 0.226 and 0.372 (μmol/g fw) for Shirudi under 0, 75 and 150 mM NaCl, respectively (Fig. 1).
Proline content in Mihan and Shirodi as the most sensitive cultivars and Backcross and Roshan as the most resistant ones under normal, moderate and severe salinity stress conditions. Each column with the same letter is not significantly different at 5% level of probability.
P5CS gene expression
Using 2−ΔCT method, P5CS gene expression level was enhanced by elevating stress levels. The expression ratios were calculated in comparison with the GAPDH as an internal control gene. Similar to the results of proline content, P5CS gene expression enhancement was also sharper in the tolerant genotypes than in the sensitive ones. The obtained results were as follows: for Mihan: 0.0031, 0.0058, 0.0071 (P5CS/GAPDH mRNA), for Shirudi: 0.0026, 0.0048, 0.007 (P5CS/GAPDH mRNA), for Backcross: 0.0033, 0.011, 0.021 (P5CS/GAPDH mRNA) and for Roshan: 0.0036, 0.013, 0.021 (P5CS/GAPDH mRNA) under 0, 75 and 150 mM NaCl, respectively (Fig. 2).
P5CS gene expression level in Mihan and Shirodi as the most sensitive cultivars and Backcross and Roshan as the most resistant ones under normal, moderate and severe salinity stress conditions. Each column with the same letter is not significantly different at 5% level of probability.
W36 gene expression
Similarly, 2−ΔCT method for W36 gene expression analysis showed its elevation with increasing stress levels. The greatest extent of W36 gene expression was identified in Backcross and the Roshan cultivars as the most resistant cultivars in response to 75 and 150 mM NaCl. W36 gene expression was calculated 0.0068, 0.057, 0.1042 for Backcross, 0.0061, 0.060, 0.1147 for Roshan, 0.0066, 0.0103, 0.027 for Mihan and 0.0058, 0.0092, 0.0256 (P5CS/GAPDH mRNA expression ratios) for Shirudi under 0, 75 and 150 mM NaCl, respectively (Fig. 3).
W36 gene expression level in Mihan and Shirodi as the most sensitive cultivars and Backcross and Roshan as the most resistant ones under normal, moderate and severe salinity stress conditions. Each column with the same letter is not significantly different at 5% level of probability.
Discussion
Plant yield improvement is an important goal of wheat breeding programs (Mitrofanova and Khakimova, Reference Mitrofanova and Khakimova2017; Nazari et al., Reference Nazari, Moosavi and Maleki2018, Reference Nazari, Goharrizi, Moosavi and Maleki2019; Rasheed et al., Reference Rasheed, Mujeeb-Kazi, Ogbonnaya, He and Rajaram2018; Tadesse et al., Reference Tadesse, Sanchez-Garcia, Assefa, Amri, Bishaw, Ogbonnaya and Baum2019). In this regard, the determination of plant yield and growth components is one of the major areas of breeding programs. The yields of wheat are finally distinguished by the number of spikes per plant and yield components such as the number of spikelets, number of grains and grain weight (El-Hendawy et al., Reference El-Hendawy, Hu, Yakout, Awad, Hafiz and Schmidhalter2005). In the current study, 14 cultivars of wheat (Alvand, Chamran, Omid, Shirudi, Mihan, Pishtaz, Backcross, Arg, Roshan, Gaspard, Verinak, Atila, Niknejad and Darab2) were evaluated at three different stress conditions (0, 75 and 150 mM Nacl). The field experiments revealed that different cultivars of wheat responded variably to salinity stress in terms of the studied traits. In order to complete data interpretation and determine the superior cultivars under salinity stress conditions, the mean comparison was performed in terms of all significant traits. The statistical analysis revealed that both different cultivars and various salinity stress concentrations have considerably affected various traits. Bi-plot analysis was also carried out for assessing different cultivar responses to different NaCl concentrations. Bi-plot analysis can efficiently separate different genotypes based on all traits which are used in PCA analysis (LeBuhn et al., Reference LeBuhn, Griswold, Minckley, Droege, Roulston, Cane, Parker, Buchmann, Tepedino and Williams2003). Thus, the bi-plot analysis could be recommended for assessing genotypic variations for salt tolerance research. According to the results of the bi-plot analysis in this study, Mihan and Shirudi cultivars were recognized as the most sensitive and Backcross and Roshan as the most resistant bread wheat cultivars under moderate and high salinity levels, respectively. Cluster analysis was also performed to classify cultivars in different groups (Calin´ski and Harabasz, Reference Calin´ski and Harabasz1974; Poudel et al., Reference Poudel, Thapa and Sapkota2017; Bazzaz et al., Reference Bazzaz, Hossain, Khaliq, Karim, Farooq and Teixeira da Silva2019). Based on the cluster analysis, Mihan and Shirudi, as the sensitive cultivars, as well as the Backcross and Roshan, as the tolerant ones, were grouped into a separated group under moderate and high salinity levels (online Supplementary Figs S5 and S6).
P5CS is a key enzyme in the first two steps of proline biosynthesis and has been isolated from many plants so far (Garg and Neha, Reference Garg and Neha2019). A previous study showed a correlation between the infusion of P5CS gene and the proline accumulation in Arabidopsis thaliana (Yoshiba et al., Reference Yoshiba, Kiyosue, Katagiri, Ueda, Mizoguchi, Yamaguchi-Shinozaki, Wada, Harada and Shinozaki1995; Signorelli and Monza, Reference Signorelli and Monza2017; Anton et al., Reference Anton, Guzman, Vetö, Krause, Kulcheski, Coelho, Duarte, Margis, Dillenburg and Turchetto-Zolet2020). Another study showed that P5CS gene expression, under salinity stress on days 9 and 11 of treatment with NaCl, was enhanced in cactus pear (Silva-Ortega et al., Reference Silva-Ortega, Ochoa-Alfaro, Reyes-Agüero, Aguado-Santacruz and Jiménez-Bremont2008). Also, it has been proven that the elevation of proline content and P5CS gene expression could increase the osmotic stress tolerance. Enhancing osmotic stress increases the proline content and P5CS gene expression in plants (Kavi Kishor and Sreenivasulu, Reference Kavi Kishor and Sreenivasulu2014), which are completely similar to our results. Other researchers suggested a model for proline metabolism in Arabidopsis in response to salinity stress, which explains proline accumulation with down-regulation of PDH and P5CDH, and up-regulation of P5CS (Verslues and Sharma, Reference Verslues and Sharma2010). Further, Xue et al. (Reference Xue, Liu and Hua2009) stated that under salt stress the expression of BnP5CS1and BnP5CS2 increased, while the expression of BnPDH was suppressed (Xue et al., Reference Xue, Liu and Hua2009). A previous study reported 27.4- and 19-fold increase in the proline content in sensitive and resistant bread wheat cultivars under NaCl stress (Kumar et al., Reference Kumar, Beena, Awana and Singh2017). Additionally, with growing concentrations of NaCl, proline content increased in all cultivars and all environments, though the extent of increase was completely different between cultivars; the proline content increased far more substantially in the resistant cultivars compared to the sensitive cultivars. Based on our results and previous studies, it can be concluded that the proline content and P5CS gene expression are completely involved in salinity stress. Additionally, our results showed that P5CS gene expression and the proline content have a direct relationship with each other where the elevation of the P5CS gene expression would lead to higher proline content. Also, changes in the proline content and P5CS gene expression levels depend on the type of cultivar and salinity stress levels. Finally, a direct relationship was observed in this study between the proline content as well as P5CS gene expression and resistance of cultivars in physiological maturity stage under salinity stress in bread wheat cultivars. In this regard, unlike susceptible cultivars, the resistant ones showed a higher level of proline content and P5CS gene expression.
Plants have sophisticated signalling networks that can understand environmental pressures such as salinity and drought, and react to them accordingly (Jamshidi Goharrizi et al., Reference Jamshidi Goharrizi, Amirmahani and Salehi2019a, Reference Jamshidi Goharrizi, Amirmahani, Fatehi, Nazari and Moosavib, Reference Jamshidi Goharrizi, Moosavi, Amirmahani, Salehi and Nazaric, Reference Jamshidi Goharrizi, Riahi-Madvar, Rezaee, Pakzad, Jadid Bonyad and Ghazizadeh Ahsaeid; Reference Jamshidi Goharrizi, Baghizadeh, Kalantar and Fatehi2020a, Reference Jamshidi Goharrizi, Fatehi, Nazari, Salehi and Malekib). Using the energy produced by hydrolysing cytoplasmic adenosine triphosphate (ATP), vacuolar H+-ATPase manages proton stimulus power (PMF) and pumps H+ from cytoplasma into vacuole. Thus, vacuolar H+-ATPase activity could stimulate solute transfer among cytoplasma and vacuole, and is necessary for life activities. Additionally, the V-type H+-ATPase activity under salinity stress is one of the most important mechanisms of plant survival (Dabbous et al., Reference Dabbous, Saad, Brini, Farhat-Khemekhem, Zorrig, Abdely and Hamed2017). The vacuolar-type H+-ATPase is an ATP-driven enzyme which converts the energy of ATP hydrolysis to electrochemical potential variations of protons through various biologic membranes via the primitive energetic transport of H+ (Dabbous et al., Reference Dabbous, Saad, Brini, Farhat-Khemekhem, Zorrig, Abdely and Hamed2017). Vacuolar-type H+-ATPase has a membrane-bound proton-trans-locating V0 sub-complex and cytosol ATP-hydrolysing V1 sub-complex. Cytosol ATP-hydrolysing V1 sub-complex has eight subunits (A, B, C, D, E, F, G and H) (Nishi and Forgac, Reference Nishi and Forgac2002) with the expression of the E subunit examined in this study. In response to salt stress, many studies have shown increased V-ATPase and vacuolar H+-ATPase as well as protein levels (Nishi and Forgac, Reference Nishi and Forgac2002). In a similar study, the expression of A, B, E, F and c vacuolar-type H+-ATPase subunits increased under salt stress in the leaves of Mesembryanthemum crystallinum treated with 400 mM NaCl for 72 h (Golldack and Dietz, Reference Golldack and Dietz2001). In addition, enhanced expression of vacuolar H+-ATPase subunit E in the roots of Broussonetia papyrifera was observed in response to salt stress (Zhang et al., Reference Zhang, Fang, Liang and Huang2012).
W36 gene, which belongs to wheat (ABC70183.1) was isolated from stress-induced de novo transcriptome sequencing of wheat (Zhang et al., Reference Zhang, Li, Hu, Chen and Min2014), which the expression of this gene was explored in this research. In this study, in order to survey W36 gene role under salinity stress in resistant and susceptible wheat cultivars, W36 gene expression was analysed under different salinity stress conditions including normal, moderate and severe. Our results showed that W36 gene expression was specifically up-regulated in the resistant cultivars by NaCl stresses, but this was not observed in the susceptible cultivars. Also, W36 gene expression was enhanced in all cultivars but the extent of expression in cultivars was completely different in each condition. In normal conditions, W36 gene expression was almost similar in both susceptible and resistant cultivars, and no significant change was observed between 0 and 75 mM NaCl conditions regarding the W36 gene expression in the susceptible cultivars (Mihan and Shirudi) (Fig. 3). Additionally, in susceptible cultivars (Mihan and Shirudi), minor changes were calculated between 0 and 75 mM NaCl environments with 150 mM NaCl condition for W36 gene expression, while extensive changes between 0, 75 and 150 mM NaCl environments for W36 gene expression were observed in the tolerant bread wheat cultivars (Backcross and Roshan) (Fig. 3). The V-type H+-ATPase activity under salinity stress is one of the most important mechanisms of plant survival (Dietz et al., Reference Dietz, Tavakoli, Kluge, Mimura, Sharma, Harris, Chardonnens and Golldack2001). A previous study proved that V-type H+-ATPase activities affect protection of the cytoplasma pH, response to stress, water potential and Ca2+ concentration. Additionally, another study revealed that plants promote their salt tolerance through V-type H+-ATPase activity, which is an additional key function of SOS2 in coordinating changes into ion transportation during salinity pressure (Batelli et al., Reference Batelli, Verslues, Agius, Qiu, Fujii, Pan, Schumaker, Grillo and Zhu2007). ABA content increases when salinity stress is induced and takes part in the SOS signalling pathway via increasing Ca2+ condensation and high Ca2+ rate in the cytosol causes phosphorylation of proteins in cells (Chinnusamy et al., Reference Chinnusamy, Zhu and Zhu2006). Also, a calcium/calmodulin-dependent protein kinase, susceptible to staurosporine, is implicated in V-type H+-ATPase phosphorylation which is activated by NaCl (Zhang et al., Reference Zhang, Li, Hu, Chen and Min2014). NaCl increases ABA content, ABA in turn increases the overexpression of W36 (Zhang et al., Reference Zhang, Li, Hu, Chen and Min2014), thereby increasing V-type H+-ATPase function and finally reducing the cellular Na+ toxicity to increase plant salt tolerance via providing more energy for ion transfer. Zhang et al. (Reference Zhang, Li, Hu, Chen and Min2014) showed that the overexpression of W36 gene increases salt and mannitol tolerance in transgenic Arabidopsis. Further, they proved that W36 gene is involved in the plant response to osmotic pressures. Some Cis-acting elements responding to abiotic stresses located on W36 promoter are the main reason of this gene activation in response to abiotic stresses. Cis-acting elements are involved in the supply of multiple secondary actions to plant systems such as morphological repairs, regulating senescence, DNA damage maintenance, developmental arrangement and response to abiotic stresses (Zou et al., Reference Zou, Sun, Mackaluso, Seddon, Jin, Thomashow and Shiu2011). Under pressure situations, molecular equilibrium in plants changes and makes transcription factors bind to their special diagnosis sequences located upstream of the stress-responsive genes (called cis-elements). Based on our results and other studies, it can be concluded that increasing W36 gene expression can enhance the V-type H+-ATPase activity and can be an index for resistance of plants by reducing the cellular Na+ toxicity (Zhang et al., Reference Zhang, Li, Hu, Chen and Min2014). Also, V-type H+-ATPase activity increases because of W36 gene expression induction and enhancement of V-type H+-ATPase activity energizing the transportation of proline through tonoplast under osmotic stress induced by salinity stress (Claussen, Reference Claussen2005). As the accumulation of proline leads to increased osmotic adjustment in plants (Gaxiola et al., Reference Gaxiola, Palmgren and Schumacher2007), it can be justified that these reactions of plants under salinity stress are the main reasons of tolerance in Backcross and Roshan cultivars in this study.
Conclusion
Based on our results, Roshan and Backcross were identified as the most tolerant cultivars under moderate and high salinity concentrations. Thus, these cultivars can be considered as two of the valuable germplasms and can be used for breeding programs to improve the tolerance of salt-sensitive wheat cultivars. It can also be concluded that the proline content, P5CS and V-Type H+-ATPase subunit E (W36) genes expression levels are completely involved in response to salinity stress. Additionally, since the proline content, as well as P5CS and W36 genes expression levels, were higher in the most resistant cultivars than in susceptible ones, it can be concluded that most likely the proline content and expression of these two genes play a substantial role in the resistance of the tolerant cultivars in this study under salinity stress.
Conflict of interest
The authors declare that they have no conflict of interests.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/S1479262120000350.
