Proteomic Analysis of Proteins Responsive to Drought stress in barley

Proteomic Analysis of Proteins Responsive to Drought stress in barley | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Proteomic Analysis of Proteins Responsive to Drought stress in barley Walaa Abdel-Kader Ramadan, Fatma El-Sayed Mahmoud, Mahmoud Hussien Abou-Deif, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7475122/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 11 Feb, 2026 Read the published version in BMC Plant Biology → Version 1 posted 14 You are reading this latest preprint version Abstract Background Drought stress is one of the main environmental factors limiting the development, growth, and crop yield of barley plants. Finding drought-tolerant genes and the proteins they encode that are linked to the interplay between drought tolerance and growth/yield is crucial for enhancing genotypes' ability to withstand drought and other abiotic stressors. Our study's objective was to leverage prior proteomic research to identify candidate genes and the proteins they encode that are important in barley's responses to drought tolerance and to examine how drought stress alters their expression. Results This study reveals that proteome alterations linked to drought stress in the Giza132 barley genotype were examined using two-dimensional (2-DE) electrophoresis. Seedlings with one week old were subjected with 10% of Polyethylene Glycol (PEG) treatment for eight days and protein expression profiles were determined with 2-DE gel using total proteins extracted from leaf tissues after treatment in comparison to control (irrigated with tap water during this period). Our Investigations of protein expression profiles revealed that drought stress using 10% of PEG results in global changes in the barley proteome and consequently the genes that related to drought stress tolerance responses. From our results, we identified 56 spots (proteins) most of them are related to the drought and other stresses tolerance. These previous proteins were up /down regulated or remained unaltered in barley plants that are stressed by drought in comparison with control. Moreover, Bioinformatics databases were used to determine the potential tissue expression of our genes at transverse and sagittal slices, various tissues under light and shade, and various tissues at entire spike and provascular tissue. Conclusions Using two-dimensional gel data analysis and the putative expression analysis for the candidate genes and their encoding proteins, we can comprehend how these genes would function in barley in response to drought stress. Drought stress barley proteomics two dimensional (2-DE) electrophoresis Polyethylene Glycol (PEG) putative tissue expression Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction One of the most detrimental abiotic stresses for plants is drought, which affects their growth, reproduction, and yield. To adapt to dry conditions, plants use morphological, physiological, biochemical, cellular, and molecular processes [ 44 ]. All intracellular processes involve proteins, which are also essential for drought tolerance. As genomics has advanced quickly, proteomics has emerged as a viable technique for identifying proteins resistant to drought that could be employed in marker-assisted selection to improve crops [ 48 ]. Protein separation and identification methods, such as two-dimensional gel electrophoresis (2-DE), liquid chromatography, and mass spectrometry (MS) have made tremendous strides in recent years. Database accessibility and searching have also improved [ 45 ]. One of the most popular proteomics methods is two-dimensional gel electrophoresis (2-DE), which makes it easy to resolve and view thousands of protein species on a single gel, hence resolving proteoforms [ 59 ]. Expression proteomics is used to study the qualitative expression of proteins under different situations [ 60 ]. Understanding how distinct genomic regions affect the composition of grain proteins, the function of enzymes, and the expression of particular genes under various growing circumstances is made possible by proteomics. [ 62 , 63 ]. Proteomics in barley is therefore a useful technique for explaining protein expression and how it adds to the grain's value and drought resistance. Proteomic technique of agricultural drought response in rice has been revealed by the use of proteomic method in crop plants [ 49 ] such as; wheat [ 50 ]. maize [ 51 ]. barley [ 52 ] soybean [ 17 ] bean [ 53 ] and sorghum [ 54 ]. Specifically, transcriptome and proteome investigations of wheat revealed that the growing grains have a large number of genes that withstand drought [ 55 ], and proteins that are crucial for grain development and yield creation in response to drought stress [ 56 , 57 ]. The combination of functional genomics, proteomics, bioinformatics, breeding, and genetic resources is helping to better understand the genetic and biochemical underpinnings of barley quality features. High throughput screening techniques and breeding programs must include this information in order to combine good yield and agronomic features with good quality. [ 46 ]. The objective of this work was to identify the subunits that underwent considerable alteration as a result of stress circumstances and to ascertain how drought stress affected proteins as separated by 2-DE. Material and methods Plant material: The Egyptian cultivar of barley ( Hordeum vulgare L.) used in this study is Giza132 (G132) with genetic origin Rihane-05//As46/Aths*2Aths/Lignee686, were kindly obtained by the Barley Research Department, Field Crops Research Institute, Agriculture Research Center, Giza, Egypt. The experiment was carried out in the Laboratory of Genetics and Cytology Department, National Research Centre, Egypt. While performed at room temperature in a Petri dish that was 15 cm in diameter. After five minutes of immersion in 1% sodium hypochlorite, the grains were rinsed with distilled water. An autoclave was used to sterilize the barley grains and petri plates. Fifteen cultivar grains were moved into filter paper inside the Petri dish after that distilled water was added for one week then the cultivar was evaluated for drought tolerance using 10% concentration of Polyethylene Glycol (PEG) for eight days in which the control plant was irrigated during this period. For the proteome analysis, ten seedlings from each genotype were chosen from the control and drought treatment. Protein extraction and two dimensional (2-DE) electrophoresis: Using a mortar and pestle, 0.2g of seedlings were ground in liquid nitrogen for 2-D electrophoresis. The powder was then added to 2 ml of lysis buffer that contained 7 M urea, 2 M thiourea, 4% CHAPS, 18 mM Tris–HCl pH 8.0, and 4% Triton X-100. The powder was mixed with a mixture of protease inhibitors (1 mM PMSF, 0.1 mM pepstatin, 2 mM leupeptin, 1 mM E-64, and 1 mM aprotinin) and 53 u/mL DNase I and 4.9 u/mL RNase. For 20 minutes, they were incubated at 4°C. After adding 14 mM of DTT, the samples were centrifuged at 10,000 xg for 20 minutes at 4ºC until the supernatant was entirely clear and free of lipids. The Bradford technique was used to estimate the protein concentration. [ 42 ] Employing the BSA-based Bio-Rad Protein Assay. Equal and standard loading quantities were verified on 1-DE gels that were stained with CBB. Protein extracts were diluted for 2-DE analysis using a rehydration solution that contained 1.6% (v/v) DeStreak Reagent (GE Healthcare), 7 M urea, 2 M thiourea, 18 mM Tris–HCl pH 8.0, 4% (w/v) CHAPS, 0.5% (v/v) IPG buffer in the same range as the IPG strip, and 0.002% Bromophenol Blue. Samples with 2 mg of protein were placed onto pH 3– 10, 24 cm immobilized pH gradient (IPG) strips (Immobiline DryStrips, GE Healthcare) for the first dimension after being diluted to a final volume of 450 µl. IEF was carried out. at 50 V for 10 h (rehydration), 500 V in gradient for 1 h 30 min, 1000 V in gradient for 1 h 30 min, 2000 V in gradient for 1 h 30 min, 4000 V in gradient for 1 h 30 min, 8000 V in gradient for 2 h and 8000 V holding for 6 h, using Ettan™ IPGphor™ Isoelectric Focusing System (Amersham, Biosciences). IPG strips were equilibrated with 50 mM Tris–HCl (pH 8.8), 6 M urea, 30% (v/v) glycerol, 2% SDS, a trace of Bromophenol Blue, and 10 mg/ml DTT for 15 minutes prior to the second dimension. This was followed by a second equilibration step using the same buffer, but this time with 25 mg/ml iodoacetamide in place of DTT, for an additional 15 minutes while being gently shaken. For the second dimension, the focused strips was performed on vertical slabs (20 X 18 X 0.2 cm) where loaded and run on sodium dodecyl sulfate polyacrylamide gel by electrophoresis method SDS-PAGE (13% polyacrylamide) for 30 min, 100 V at room temperature followed by 250 V during 4 hours. Proteins were visualized with silver stain dyes [ 43 ]. An ImageScanner desktop device (Amersham, Biosciences) was used to scan the 2-DE gels. Images were obtained using the LabScan scanning application, in transmission mode, at a greyscale level of 16 bips, at 300 dpi, with a magnification factor of 1:1 (100%) and saved as TIFF (Tag Image File Format) files. The ImageMasterTM 2-D Platinum 5.0 software (Amersham, Biosciences) was used to analyze the images. Image analysis and protein identification The gel images were analysis using the using the ImageJ and Melanie v.9 software for 2D gel analysis, and the detected spots on the gel were then contrasted with the NCBI and Swiss-Prot databases and an exact match was found through the Mascot search program [ 63 ].Furthermore, the Swiss-Prot and NCBI protein databases were examined for the annotation of the detected proteins in their descriptions. Identification and Functional Assignments for Protein-Associated with dots in H. vulgare . Putative sequences of protein from dots analysis were used as a query to search against the H. vulgare genomics that we already get from NCBI genomics ( https://phytozome-next.jgi.doe.gov/blast-search , accessed on 25 Dec.2023). The alignment sequence was then examined with the Phytozome and KEGG databases in order to predict the biological function of these chosen candidate proteins that were linked to different H. vulgare dots. Ultimately, we obtain 53 genes that are closely associated with different functions in H. vulgare . [ 37 , 40 , 41 ]. Putative expression pattern of our target genes at transverse and sagittal sections based on H. vulgare transcript expression. Profiles of putative expression of 47 genes from H. vulgare were extracted based on H. vulgare transcript expression database from three tissues of transverse and sagittal sections at different times, including; 4D- SMT, 4D-END, 4D-EMB, 8D- SMT, 8D-END, 8D-EMB, 16D- SMT, 16D-END, 16D-EMB, 24D- SMT, 24D-END, 24D-EMB, 32D- SMT, 32D-END and 32D-EMB (see supplementary Table 1). The creation of expression profiles was done using the barley plant Electronic Fluorescent Pictograph Browsers (barley eFP browsers) ( http://bar.utoronto.ca/eplant_Arabidopsis/ ) accessed on 25 April 2024 [ 33 , 34 , 35 , 36 , 38 , 39 ]. Putative expression pattern of our target genes at various tissue, whole spike and provascular Tissue based on H. vulgare transcript expression. The putative expression profiles of 47 genes from H. vulgare were extracted based on H. vulgare transcript expression database from various tissues, whole spike and provascular tissue such as; Vegatative Apex (I-Va-SAM), Double Ridhe (I-Dr-IM),Double Ridhe (I-Dr-LRM), Double Ridhe (I-Dr-SRM), Triple Mound (I-Tm-IM),Triple Mound (I-Tm-LSM),Triple Mound (I-Tm-CSM), Glume Primordium (I-Gp-IM),Glume Primordium (I-Gp-LSM),Glume Primordium (I-Gp-CSM), Legmma Primodium (I-Lp-IM),Legmma Primodium (I-Lp-LSM),Legmma Primodium (I-Lp-CSM), Stamen Primordium (I-Sp-IM),Stamen Primordium (I-Sp-LSM),Stamen Primordium (I-Sp-CSM), Awa Primordium (I-Ap-IM),Awa Primordium (I-Ap-LSM),Awa Primordium (I-Ap-CSM), White Anther (I-Wa-IM), Leaf Blade Base (I-LBB), Root Apical Meristem (I-RAM), Double Ridge (W-DR), Triple Mound (W-TM), Glume Primordium (W-GP), Lemma Primordium (W-LP), Stamen (W-SP), Awn Primordium (W-AP), Double Ridge (R-DR), Triple Mound (R-GP), Glume Primordium (R-GP), Lemma Primordium (R-LP), Stamen (R-SP) and Awn Primordium (R-AP) (see supplementary Table 1. The Electronic Fluorescent Pictograph Browsers for barley plants were used to develop expression profiles. (barley eFP browsers) ( http://bar.utoronto.ca/eplant_Arabidopsis/ ) accessed on 30April 2024 [ 33 , 34 , 35 , 36 , 38 , 39 ]. Putative expression pattern of our target genes at various tissues under light and shade based on H. vulgare transcript expression. To analyses the putative expression profiles of 47 genes from H. vulgare were extracted based on H. vulgare transcript expression database from various tissues under light and shade conditions, including; Double Ridhe (I-Dr-IM), Double Ridhe (I-Dr-LRM),Double Ridhe (I-Dr-SRM), Triple Mound (I-Tm-IM),Triple Mound (I-Tm-LSM),Triple Mound (I-Tm-CSM), Glume Primordium (I-Gp-IM),Glume Primordium (I-Gp-LSM),Glume Primordium (I-Gp-CSM), Legmma Primodium (I-Lp-IM),Legmma Primodium (I-Lp-LSM),Legmma Primodium (I-Lp-CSM), Stamen Primordium (I-Sp-IM),Stamen Primordium (I-Sp-LSM),Stamen Primordium (I-Sp-CSM), Awa Primordium (I-Ap-IM), Awa Primordium (I-Ap-LSM) and Awa Primordium (I-Ap-CSM), (see supplementary Table S3 ). Expression profiles were created using the barley plant Electronic Fluorescent Pictograph Browsers (barley eFP browsers) ( http://bar.utoronto.ca/eplant_Arabidopsis/ ) accessed on 5 June 2024 [ 33 , 34 , 35 , 36 , 38 , 39 ]. Results Protein extraction and Identification in H. vulgare leaves. Leaf proteins were taken out of barley leaf under drought stress and without drought stress (control), and then the proteins were separated in the 2D gels using electrophoreticism. After that, using 2-DE, we examined the protein patterns in the pH range of 3–10. The barley proteins that were visible were packed, and all our spots (dots) became visible in the pH range of 5–10. Moreover, we used 2-DE to further examine the protein patterns of these areas and the resulting 2DE images of the proteins in barley leaves are displayed in Fig. 1 A, B and Supplementary Fig. 1. After being chosen from 2-D gels, spots were analyzed using a MASCOT database. These protein spots were located through a search in barley, rice, wheat and other cereal crops protein sequences from Swiss-Prot, phytozome 13 and NCBI databases. As results, 56 spots (barely proteins) were chosen for identification, according to the putative functions of each spot, see supplementary table 1 . The spots were visualized by silver staining. Protein spots are indicated by white numbers. Spots indicate the differentially expressed protein spots whose expression levels were significantly induced or down regulated. Functional Annotations of the Gene-Associated dots in H. vulgare . In order to estimate the possible activities of our target genes, the H. vulgare genomic sequence served as a template for searching the protein dot sequence. We discovered 53 genes that may be involved in barley's resistance to drought and other abiotic stressors based on sequence homology. (see Table 1 ). Subsequently, multiple databases, including the Phytozome, NCBI, InterPro, and KEGG databases, predicted additional function annotations for these genes. Contextually, these genes were linked to numerous biological processes, such as HORVU.MOREX.r3.2HG0202350 (gi|251832986), HORVU.MOREX.r3.2HG0202350 (gi|121340), HORVU.MOREX.r3.UnG0798500 (gi|108711272), HORVU.MOREX.r3.UnG0808370 (gi|110915608), HORVU.MOREX.r3.5HG0483130 (RBL_AGRST), HORVU.MOREX.r3.5HG0490180 (gi|32765549), HORVU.MOREX.r3.1HG0001110 (gi|17425184), HORVU.MOREX.r3.1HG0001420 (gi|53854906), HORVU.MOREX.r3.2HG0167220 (BAS1_WHEAT), HORVU5Hr1G124160 (CAA32900.1), HORVU.MOREX.r3.2HG0120840 (gi|326496957), HORVU.MOREX.r3.6HG0591100 (CAA36498.1), HORVU.MOREX.r3.2HG0138840 (XP_002518555.1), HORVU.MOREX.r3.3HG0276570 (gi|326493350), HORVU.MOREX.r3.5HG0421460 (gi|326493798), HORVU.MOREX.r3.5HG0511770 (AAF98561.1), HORVU.MOREX.r3.4HG0417260 (AAC67246.1), HORVU.MOREX.r3.5HG0421370 (gi|326493636), HORVU.MOREX.r3.4HG0385790 (CAA06996.1), HORVU.MOREX.r3.7HG0720010 (GI:18412879), HORVU.MOREX.r3.4HG0345760 (AAO42684.1), HORVU.MOREX.r3.3HG0304680 (ACO44685.1) and HORVU.MOREX.r3.4HG0392240 (CAA38036.1) that associated with Plastid glutamine synthetase 2, Glutamine synthetase leaf isozyme, Chloroplastic, ATP synthase beta chain, putative, ATP synthase beta subunit, Ribulose bisphosphate carboxylase large chain, Predicted: 20 kDa chaperonin, chloroplastic-like respectivelly, Cytosolic heat shock protein 90, LMW- glutenin subunit group 3 type II, LMW- glutenin, 2-cys peroxiredoxin BAS1, Chlorophyll a-b binding protein 1, chloroplastic, thioredoxin peroxidase, Elongation factor Tu, chloroplastic, cysteine-rich receptor-like protein kinase 10, isocitrate dehydrogenase, glycine rich protein, RNA binding protein, UDP-glucose 6-dehydrogenase, Beta-amylase, enolase, L-ascorbate peroxidase, Leucine-rich repeat family protein LRR, Alcohol dehydrogenase I, fructose-bisphosphate aldolase and Heat shock protein 21, chloroplastic, respectively (see Table 1 ). The putative expression of our target genes at different transverse and sagittal sections based on H. vulgare transcript expression using barley eFP browsers tool. Based on the transcript expression of H. vulgare, the potential expression of our target genes in various transverse and sagittal sections was predicted using the Barley eFP browsers tool. The findings demonstrated that all fifteen tissues had high expression levels of the majority of our target genes from H. vulgare. (e.g. 4D- SMT, 4D-END, 4D-EMB, 8D- SMT, 8D-END, 8D-EMB, 16D- SMT, 16D-END, 16D-EMB, 24D- SMT, 24D-END, 24D-EMB, 32D- SMT, 32D-END and 32D-EMB) see Fig. 2 For example, HORVU.MOREX.r3.2HG0202350 (gi|251832986), HORVU.MOREX.r3.6HG0613270 (gi|121340), HORVU.MOREX.r3.5HG0490180 (gi|32765549), HORVU.MOREX.r3.3HG0232910 (gi|326497973), HORVU.MOREX.r3.2HG0120840 (gi|326496957), HORVU.MOREX.r3.6HG0591100 (CAA36498.1), HORVU.MOREX.r3.2HG0138840 (XP_002518555.1), HORVU.MOREX.r3.3HG0276570 (gi|326493350), HORVU.MOREX.r3.5HG0421460 (gi|326493798), HORVU.MOREX.r3.5HG0511770 (AAF98561.1), HORVU.MOREX.r3.4HG0417260 (AAC67246.1), HORVU.MOREX.r3.5HG0451540 (KAE8821856), HORVU.MOREX.r3.5HG0421460 (gi|326493798), HORVU.MOREX.r3.4HG0385790 (CAA06996.1), HORVU.MOREX.r3.4HG0369570 (ADK56176.1), HORVU.MOREX.r3.3HG0290880 (CAA77237.1), HORVU.MOREX.r3.7HG0720010 (GI:18412879), HORVU.MOREX.r3.4HG0345760 (AAO42684.1), HORVU.MOREX.r3.3HG0304680 (ACO44685.1) and HORVU.MOREX.r3.4HG0392240 (CAA38036.1) see Fig. 1 , Table 1 and supplementary Table 2.. Furthermore, these previous genes encoding Plastid glutamine synthetase 2 [ T. Aestivum ], Glutamine synthetase leaf isozyme, Chloroplastic, Cytosolic heat shock protein 90 [ H. vulgare ], predicted protein ( H. vulgare ), thioredoxin peroxidase ( H. vulgare ), Elongation factor Tu, chloroplastic ( Arabidopsis thaliana ), cysteine-rich receptor-like protein kinase 10 ( Ricinus communis ), isocitrate dehydrogenase ( H. vulgare ), Beta-amylase, 70 kDa heat shock protein (H. vulgare), glycine rich protein, RNA binding protein (H. vulgare), UDPglucose 6-dehydrogenase (Zea mays), L-ascorbate peroxidase ( H. vulgare ) glycosyltransferase 75 ( Triticum aestivum ), reversibly glycosylated polypeptide ( Triticum aestivum ), Leucine-rich repeat family protein LRR ( Arabidopsis thaliana ), Alcohol dehydrogenase I ( Oryza eichingeri ), fructose-bisphosphate aldolase ( H. vulgare ) and Heat shock protein 21, chloroplastic see Fig. 2 , Table 1 and supplementary Table 2. Predication the putative expression pattern of our target genes at various tissue, whole spike and provascular tissue based on H. vulgare transcript expression. The putative tissue expression of our candidate genes from H. vulgare at various tissue, whole spike and provascular tissue based on H. vulgare transcript expression was analyzed to realize their roles and functions in drought tolerance and other a biotic stress Fig. 3 . The results showed that some of our target genes from H. vulgare were abundantly expressed across all tissues. at various tissue, whole spike and provascular tissue. For example, the HORVU.MOREX.r3.5HG0480620 (gi|357158586), HORVU.MOREX.r3.7HG0661950 (gi|51090748), HORVU.MOREX.r3.5HG0490180 (gi|32765549), HORVU.MOREX.r3.3HG0276570 (gi|326493350), HORVU.MOREX.r3.5HG0421460 (gi|326493798), HORVU.MOREX.r3.5HG0421460 (gi|326493798), HORVU.MOREX.r3.5HG0421370 (gi|326493636), HORVU.MOREX.r3.4HG0370860 (AAC32060.1), HORVU.MOREX.r3.4HG0385790 (CAA06996.1), HORVU.MOREX.r3.4HG0369570 (ADK56176.1) and HORVU.MOREX.r3.3HG0304680 (ACO44685.1) that is connected to The following are predicted: cytosolic heat shock protein 90 [H. vulgare], putative chaperonin 21 precursor [Oryza sativa Japonica], 20 kDa chaperonin, chloroplastic-like (Brachypodium distachyon), isocitrate dehydrogenase ( H. vulgare ), glycine rich protein, RNA binding protein ( H. vulgare ), glycine rich protein, RNA binding protein ( H. vulgare ), enolase (Hordeum vulgare), 20S proteasome subunit PAE1 (Arabidopsis thaliana), L-ascorbate peroxidase (Hordeum vulgare), glycosyltransferase 75 ( Triticum aestivum ) and fructose-bisphosphate aldolase (Hordeum vulgare) see Fig. 3 ,Table 1 and supplementary Table 3. Analyses of different expression pattern of target genes at Putative expression pattern of our target genes at various tissues under light and shade based on H. vulgare transcript expression. The putative tissue expression of our candidate genes from H. vulgare under light and shade based on H. vulgare transcript expression was analyzed to comprehend their operations and involvement in a biotic stress and drought tolerance. Figure 4 some of our target genes from H. vulgare were found to be substantially expressed in all tissues, according to the results. For example, the HORVU.MOREX.r3.7HG0661950 (gi|51090748), HORVU.MOREX.r3.5HG0490180 (gi|32765549), HORVU.MOREX.r3.3HG0232890 (gi|326516152), HORVU.MOREX.r3.3HG0276570 (gi|326493350), HORVU.MOREX.r3.5HG0421460 (gi|326493798), HORVU.MOREX.r3.5HG0421460 (gi|326493798), HORVU.MOREX.r3.5HG0421370 (gi|326493636), HORVU.MOREX.r3.4HG0370860 (AAC32060.1), HORVU.MOREX.r3.4HG0385790 (CAA06996.1), HORVU.MOREX.r3.4HG0369570 (ADK56176.1) and HORVU.MOREX.r3.3HG0304680 (ACO44685.1) that associated with Putative chaperonnin 21 precursor [ Oryza sativa ], Cytosolic heat shock protein 90 [ H. vulgare ], predicted protein ( H. vulgare ), isocitrate dehydrogenase ( H. vulgare ), glycine rich protein, RNA binding protein ( H. vulgare ), glycine rich protein, enolase ( H. vulgare ), 20S proteasome subunit PAE1 ( Arabidopsis thaliana ), L-ascorbate peroxidase ( H. vulgare ), glycosyltransferase 75 ( Triticum aestivum ) and fructose-bisphosphate aldolase ( H. vulgare ) see Fig. 4 ,Table 1 and and supplementary Table 4. Discussion Drought and other stresses co-occur in the natural environment, especially in dry hot areas [ 2 , 5 ]. An essential and top research objective is learning more about how plants react to drought and salinity stresses [ 1 , 3 , 4 ]. Moreover, in our study we used the 2-DE gels for proteome analysis and Determine the key proteins linked to stress and their related genes, to comprehend the fundamental processes behind barley's resistance to drought stress. Based on our results we identified among 56 proteins and most of them are related to the drought and other stresses tolerance in this study see Table 1 . These previous proteins were up-regulated or down-regulated or remained unaltered in barely plant under drought stress in compared with control see Figure. Proteins whose quantity is highly dependent on drought and other stresses are primarily linked to a number of biological processes, including photosynthesis, plant growth and development. [ 64 ]. As results, Figs. 1 A and B display two distinct 2D-GE pictures, and after analyzing each gel we found unique spots for everyone and common spots between the two gels. Also, Fig. 1 A and B displays the correlation between the spot sizes.and the expression of proteins under the stress and control condition. In particular, the gel analysis for leaf sample under 10% PEG has 10 unique spots such as; spot 13 (HORVU1Hr1G001420), spot 17 (HORVU2Hr1G073760), spot 24 (HORVU2Hr1G026810), spot 29 (HORVU5Hr1G096370), spot 34 (HORVU5Hr1G038630), spot 42 (HORVU2Hr1G029840), spot 44 (HORVU4Hr1G040770), spot 49 (HORVU3Hr1G073780), spot 50 (HORVU7Hr1G090240) and spot 56 (HORVU4Hr1G063350), and these previous spots related with various proteins such as; LMW- glutenin, 2-cys peroxiredoxin BAS1 (Triticum aestivum), Thioredoxin peroxidase (Hordeum vulgare), UDP-glucose 6-dehydrogenase (Zea mays), Ribulose-bisphosphate carboxylase small chain, Putative hydrolase (Arabidopsis thaliana), Proteasome subunit alpha type-5-A (Arabidopsis thaliana), Reversibly glycosylated polypeptide (Triticum aestivum), Leucine-rich repeat family protein LRR (Arabidopsis thaliana) and Heat shock protein 21, chloroplastic see Fig. 1 , Table 1 and and supplementary Table 1.. And from our data analysis we found these previous proteins were classified and showed various biological functions in barley leaf see Table 1 . [ 6 ]. they found positively relationship between the relative water content in leave and the total Rubisco activity, which mean the Ribulose-bisphosphate carboxylase small chain can plays a complex role under drought conditions, through maintain photosynthetic rates under stress and these response based on the kind, intensity, and length of the stress. Moreover, as we know the barley and some other cereal crops quality are governed largely by two types of glutenin proteins: the high molecular weight (HMW) and the low molecular weight (LMW) - glutenin subunit [ 8 ]. Moreover, [ 7 , 9 , 10 ]. Study the influence of heat and drought stress on the levels of various glutenin types, and found a linear relationship between the impact of drought stress and the LMW-glutenin, and any alter in the composition and properties of glutenin may be affected on strength and bread-making quality. For Thioredoxin peroxidase protein, several studies have been reported about its vital function in the growth and development of a plant under various abiotic Stress as a component of a redox system, and it is ability to modulate the redox signalling during plant development, growth and stress adaptation through dithiol-disulfide exchanges [ 11 , 12 , 13 ]. And this dithiol-disulfide is essential for both signal transduction and redox sensing pathways [ 13 ]. And another proteins such as; Heat shock protein 21 and 2-cys peroxiredoxin BAS1 (Triticum aestivum) have been reported as a unique spot under 10% PEG, and these two proteins plays a significant part in plants' ability to withstand drought stress. Through activation the antioxidant enzymatic system, which working on avoiding and scavenging reactive oxygen species (ROS) over-accumulation by 2-cys peroxiredoxin enzyme [ 16 , 17 ]. Heat shock protein 21 reduces the effect of drought stress by mediates stress signal transduction, controlling with ATPase-coupled, and interactions with co-chaperone proteins [ 15 ]. Furthermore, the function of UDP-glucose 6-dehydrogenase (UGDH) in tolerance to drought stress has been reported by [ 18 , 19 ]. They found the UGDH can enhance the plant response to drought stress through their effect on cell wall potentially and composition. And the UGDH enzyme have ability to conversion of UDP-glucose to UDP-glucuronic acid by catalyze response, and the second component is a precursor for different cell wall polysaccharides, such as; hemicellulose and pectin. On the other hand, the gel analysis for control sample has five unique spots such as; spot 25 (HORVU6Hr1G053680), spot 26 (HORVU2Hr1G044650), spot 27 (HORVU3Hr1G059060), spot 28 (HORVU5Hr1G002150) and spot 46 (HORVU7Hr1G043150) and these previous spots were related to various proteins such as; Elongation factor Tu, chloroplastic ( Arabidopsis thaliana ), Cysteine-rich receptor-like protein kinase 10 ( Ricinus communis ), Isocitrate dehydrogenase ( H. vulgare) , Glycine rich protein, RNA binding protein (Hordeum vulgare) and Protein-serine/threonine kinase ( Glycine max ), respectively (Fig. 1 and Table 1 ). Additionally, after analysis the two gels from leaf sample under 10% PEG and control we have found 26 common spots and most of these spots were significantly increased in the size under the effect of stress in compared with the control, which mean the drought stress has positively effect on the expression on these proteins (shown in Fig. 1 ). These common proteins such as; spot 1 (HORVU2Hr1G111300), spot 2 (HORVU6Hr1G074030), spot 3 (HORVU7Hr1G088200), spot 6 (HORVU5Hr1G062310), spot 7 (HORVU7Hr1G033900), spot 8 (HORVU5Hr1G072420), spot 11 (HORVU1Hr1G001020), spot 12 (HORVU1Hr1G000990), spots 14, 15, 16, 18, 19 (HORVU2Hr1G073760), spot 21 (HORVU6Hr1G049250), spot 23 and 33 (HORVU5Hr1G124160), spot 30 (HORVU7Hr1G048820), spot 31 (HORVU0Hr1G003270), spot 32 (HORVU4Hr1G089510), spot 47 (HORVU4Hr1G057210), spot 48 (HORVU4Hr1G038960), spot 51(HORVU4Hr1G016810), spot 52 (HORVU3Hr1G088540), and spots 53, 54, 55 (HORVU4Hr1G063350) see Fig. 1 and Table 1 . Furthermore, these previous common spots are related with various proteins such as; Plastid glutamine synthetase 2 [T. Aestivum], Glutamine synthetase leaf isozyme, Chloroplastic, ATP synthase beta chain, putative [ Oryza sativa Japonica Group], Predicted: 20 kDa chaperonin, chloroplastic-like ( B. distachyon ), Putative chaperonin 21 precursor [ O. sativa Japonica], Cytosolic heat shock protein 90 [H. vulgare], Glutenin, LMW- glutenin subunit group 3 type II, high molecular weight subunit PC237, 2-cys peroxiredoxin BAS1 ( Triticum aestivum ), ATP synthase beta subunit [Calotheca brizoides], Chlorophyll a-b binding protein 1, chloroplastic, Protein RAFTIN 1B ( T. aestivum ), Oxygen-evolving enhancer protein 3 − 1, chloroplastic, Beta-amylase, L-ascorbate peroxidase ( H. vulgare ), Glycosyltransferase 75 ( T. aestivum ), Alcohol dehydrogenase I (Oryza eichingeri), Fructose-bisphosphate aldolase ( H. vulgare ) and Heat shock protein 21, chloroplastic, respectively. And from our data analysis we found these previous proteins showed various biological functions and some of these functions were related with the ability of drought tolerance in plants see Table 1 . For example, the spot 32 (HORVU4Hr1G089510) was related to Beta-amylase (BAM) protein and this protein plays an important function in plants drought stress tolerance through degradation the starch into maltose sugar, and this last one can used by plant as source of energy and as an osmoprotectant to protect plant from plants cope [ 20 , 21 , 22 ]. Also, the spot 47 (HORVU4Hr1G057210) was related to L-ascorbate peroxidase and this enzyme helping plants cope with drought stress through utilizes ascorbate (vitamin C) as a substrate to reduce H2O2 to water, and decrease the oxidative damage imposed by drought stress. By scavenge ROS then mitigating the harmful of the effects of ROS produced [ 23 , 24 , 25 ]. Moreover, the spot 51 (HORVU4Hr1G016810) was involved in Alcohol dehydrogenase I (ADH1), and this enzyme has a vital function in drought and other stress tolerance by catalyzing the conversion of acetaldehyde to ethanol, and this helps plant under various stress to regenerate NAD + for continue energy production under anaerobic conditions that occur under drought [ 26 , 27 , 28 ]. At the end, the spot 52 (HORVU3Hr1G088540) was related with Fructose-bisphosphate aldolase enzyme (FBA), and this enzyme play an important role in drought and other abiotic stress tolerance by converting fructose-1,6-bisphosphate into dihydroxyacetone phosphate and glyceraldehyde-3-phosphate in the Calvin cycle of photosynthesis pathway for producing sugars that fuel plant growth and metabolism see Table 1 [ 29 , 30 , 31 , 32 ]. On the other hand, numerous investigations have revealed that the effects of drought and other abiotic stress not ceasing only at the leave of plantlet but they can effects on various tissues at transverse and sagittal sections, various tissues under light and shade, and various tissues at whole spike and provascular tissue. For that, in this study we used various tools and parameters from the barley Plant Fluorescent Electronic Pictograph Browsers (barley eFP browsers) ( http://bar.utoronto.ca/eplant_Arabidopsis/ ) For predicting the putative expression of our target genes at all previous tissues see (Figs. 2 , 3 and 4 ). And from our data analysis, we found all our genes have different expression levels at each tissue and under various development stages and growth conditions. In addition, some genes have variable putative expression from tissue to another one under various development stages and conditions see (Figs. 2 , 3 and 4 ). Conclusion All this study, we used two-dimensional electrophoresis (2D-gel), and various bioinformatics databases to inquire that how drought stress affects the levels expression of different proteins in barley leaves. Our results show various unique and common proteins which are related with the ability of barley plants to drought stress tolerance. Moreover, in this research we have determined a list from 56 spots (proteins), and from our analysis using bioinformatics databases, we found these proteins have various biological functions and roles related with response to drought stress tolerance in barley. Finally, this information can be relied upon in future programs related to the production a new barley genotypes that are tolerant to drought and other biotic stresses. Abbreviations SDS Sodium Dodecyl Sulfate 2-DE Two-Dimensional Electrophoresis PEG Polyethylene Glycol MS Mass Spectrometry G 132 Giza 132 V Volt IEF Iso Electric Focusing PAGE Polyacrylamide Gel Electrophoresis NCBI National Center for Biotechnology FBA Fructose-Bisphosphate Aldolase Enzyme ADH Alcohol Dehydrogenase BAM Beta-Amylase ROS Reactive Oxygen Species HMW High Molecular Weight LMW Low Molecular Weight LRR Leucine-Rich Repeat eFP Electronic Fluorescent Pictograph Browsers IPG Immobilized pH Gradient CBB Coomassie Brilliant Blue DTT Dithiothreitol Declarations Availability of data and material All data supporting my findings can be available and found in the supplementary data. Author contributions All authors revised the manuscript, read and approved the final manuscript. Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests. 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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-7475122","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":528016053,"identity":"cf185e8e-f10c-43da-bb29-bb0a3937d608","order_by":0,"name":"Walaa Abdel-Kader Ramadan","email":"","orcid":"","institution":"National Research Centre","correspondingAuthor":false,"prefix":"","firstName":"Walaa","middleName":"Abdel-Kader","lastName":"Ramadan","suffix":""},{"id":528016054,"identity":"304c5e01-d9f6-46da-8c81-d0034f55b87c","order_by":1,"name":"Fatma El-Sayed Mahmoud","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3klEQVRIiWNgGAWjYBAC9gYog5+9+QADYwMepTDAc4AZwpDsOZZAohaDGzkGRGphP390w88d9+QZDuR8k/i5w0aOgf3w0Q14tfAks93sPVNs2Nhwdptk75k0YwaetLQb+LTYMySz3eBtS0hgZuzdJsHbdjixQYLHDK8WHv7HbDf/ArWwMfM8k/xLlBaJZLbbIFt42HjYpImzReKx2W3ZtgTDGTxsxtaybWnGbIT8wsOf+Ozm27YEefv7jx8CGTZy/OyHj+HVggxYJEAkG7HKQYD5AymqR8EoGAWjYOQAAHX/SbI2yzx2AAAAAElFTkSuQmCC","orcid":"","institution":"National Research Centre","correspondingAuthor":true,"prefix":"","firstName":"Fatma","middleName":"El-Sayed","lastName":"Mahmoud","suffix":""},{"id":528016055,"identity":"6c0512b0-f2dd-45cb-9954-69187687ad56","order_by":2,"name":"Mahmoud Hussien Abou-Deif","email":"","orcid":"","institution":"National Research 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14:56:56","extension":"xml","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":236084,"visible":true,"origin":"","legend":"","description":"","filename":"fac15490cb284ad8bd2630455b6d55231structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7475122/v1/72bbcc2e50cee9da549433df.xml"},{"id":93507600,"identity":"5f12ba17-3e23-4f77-b3ca-a63ae24a9a83","added_by":"auto","created_at":"2025-10-14 14:56:56","extension":"html","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":247638,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7475122/v1/7deee157c78ecfca414bd07f.html"},{"id":93507574,"identity":"2ce50097-e842-41f4-8062-4770235582ce","added_by":"auto","created_at":"2025-10-14 14:56:55","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1014829,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative two-dimensional gel electrophoresis (2-DE) maps of barley leaf proteins in Giza132. Under normal condition (control) (A) and exposed to drought (B).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7475122/v1/79542cbcf1a6b9f963afc8d2.png"},{"id":93507919,"identity":"32fa8339-ece5-4984-8788-b0b61cc6c382","added_by":"auto","created_at":"2025-10-14 15:04:55","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":433753,"visible":true,"origin":"","legend":"\u003cp\u003eHeat map represent the putative expression of our target genes at various transverse and sagittal sections based on \u003cem\u003eH. vulgare \u003c/em\u003etranscript expression using barley eFP browsers tool. The colour represents the expression scale (the more intense the red color, the more gene expression)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7475122/v1/37ab9ada3b034fc96f0a0702.png"},{"id":93507921,"identity":"f75c6173-beaf-4bfc-b624-780f9ef9037a","added_by":"auto","created_at":"2025-10-14 15:04:55","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":941146,"visible":true,"origin":"","legend":"\u003cp\u003eHeat map represent the putative expression pattern of our target genes at various tissue, whole spike and provascular tissue based on \u003cem\u003eH. vulgare \u003c/em\u003etranscript expression. The color represents the expression scale (the more intense the red color, the more gene expression)\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7475122/v1/688635d47ff478f708f85b49.png"},{"id":93508871,"identity":"0f10a24b-c9d3-4457-96be-b2f529b05c49","added_by":"auto","created_at":"2025-10-14 15:12:55","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1047683,"visible":true,"origin":"","legend":"\u003cp\u003eHeat map represent the Putative expression pattern of our target genes at various tissues under light and shade based on \u003cem\u003eH. vulgare \u003c/em\u003etranscript expression. The color represents the expression scale (the more intense the red color, the more gene expression)\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7475122/v1/132ae679c4e37666999f44e1.png"},{"id":102785708,"identity":"10320178-1c85-4978-a112-61479603f309","added_by":"auto","created_at":"2026-02-16 16:08:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4706108,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7475122/v1/22913213-9338-4f5f-82c5-88fcca3e2f93.pdf"},{"id":93508870,"identity":"866edc39-8e2b-47cc-9050-a778701a3d9b","added_by":"auto","created_at":"2025-10-14 15:12:55","extension":"doc","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":122368,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.doc","url":"https://assets-eu.researchsquare.com/files/rs-7475122/v1/c8497875547e94fd9919d691.doc"},{"id":93507576,"identity":"2673f828-186e-436d-927b-617851ad6979","added_by":"auto","created_at":"2025-10-14 14:56:55","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":44510,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarytables.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7475122/v1/e2452ab74bc7864a9d14be53.xlsx"},{"id":93507927,"identity":"13efe43d-4731-4793-9d5d-0564e23666ed","added_by":"auto","created_at":"2025-10-14 15:04:55","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":578979,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7475122/v1/06aad6e78be3a6bdd07859ff.pdf"},{"id":93507582,"identity":"2303e742-0346-40e7-b10c-a454ed31f767","added_by":"auto","created_at":"2025-10-14 14:56:55","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":45469,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarytable234.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7475122/v1/3d867295c1a89367ce581f1e.xlsx"},{"id":93507597,"identity":"0c841611-586d-4b82-bed0-3c985a3eb672","added_by":"auto","created_at":"2025-10-14 14:56:56","extension":"pptx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":3386373,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure1.pptx","url":"https://assets-eu.researchsquare.com/files/rs-7475122/v1/2f79958b9523941f56a68160.pptx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Proteomic Analysis of Proteins Responsive to Drought stress in barley","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOne of the most detrimental abiotic stresses for plants is drought, which affects their growth, reproduction, and yield. To adapt to dry conditions, plants use morphological, physiological, biochemical, cellular, and molecular processes [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. All intracellular processes involve proteins, which are also essential for drought tolerance. As genomics has advanced quickly, proteomics has emerged as a viable technique for identifying proteins resistant to drought that could be employed in marker-assisted selection to improve crops [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Protein separation and identification methods, such as two-dimensional gel electrophoresis (2-DE), liquid chromatography, and mass spectrometry (MS) have made tremendous strides in recent years. Database accessibility and searching have also improved [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. One of the most popular proteomics methods is two-dimensional gel electrophoresis (2-DE), which makes it easy to resolve and view thousands of protein species on a single gel, hence resolving proteoforms [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. Expression proteomics is used to study the qualitative expression of proteins under different situations [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Understanding how distinct genomic regions affect the composition of grain proteins, the function of enzymes, and the expression of particular genes under various growing circumstances is made possible by proteomics. [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. Proteomics in barley is therefore a useful technique for explaining protein expression and how it adds to the grain's value and drought resistance.\u003c/p\u003e\u003cp\u003eProteomic technique of agricultural drought response in rice has been revealed by the use of proteomic method in crop plants [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e] such as; wheat [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. maize [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. barley [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e] soybean [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] bean [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] and sorghum [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Specifically, transcriptome and proteome investigations of wheat revealed that the growing grains have a large number of genes that withstand drought [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e], and proteins that are crucial for grain development and yield creation in response to drought stress [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. The combination of functional genomics, proteomics, bioinformatics, breeding, and genetic resources is helping to better understand the genetic and biochemical underpinnings of barley quality features. High throughput screening techniques and breeding programs must include this information in order to combine good yield and agronomic features with good quality. [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. The objective of this work was to identify the subunits that underwent considerable alteration as a result of stress circumstances and to ascertain how drought stress affected proteins as separated by 2-DE.\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003ePlant material:\u003c/h2\u003e\u003cp\u003eThe Egyptian cultivar of barley (\u003cem\u003eHordeum vulgare\u003c/em\u003e L.) used in this study is Giza132 (G132) with genetic origin Rihane-05//As46/Aths*2Aths/Lignee686, were kindly obtained by the Barley Research Department, Field Crops Research Institute, Agriculture Research Center, Giza, Egypt. The experiment was carried out in the Laboratory of Genetics and Cytology Department, National Research Centre, Egypt. While performed at room temperature in a Petri dish that was 15 cm in diameter. After five minutes of immersion in 1% sodium hypochlorite, the grains were rinsed with distilled water. An autoclave was used to sterilize the barley grains and petri plates. Fifteen cultivar grains were moved into filter paper inside the Petri dish after that distilled water was added for one week then the cultivar was evaluated for drought tolerance using 10% concentration of Polyethylene Glycol (PEG) for eight days in which the control plant was irrigated during this period. For the proteome analysis, ten seedlings from each genotype were chosen from the control and drought treatment.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eProtein extraction and two dimensional (2-DE) electrophoresis:\u003c/h3\u003e\n\u003cp\u003eUsing a mortar and pestle, 0.2g of seedlings were ground in liquid nitrogen for 2-D electrophoresis. The powder was then added to 2 ml of lysis buffer that contained 7 M urea, 2 M thiourea, 4% CHAPS, 18 mM Tris\u0026ndash;HCl pH 8.0, and 4% Triton X-100. The powder was mixed with a mixture of protease inhibitors (1 mM PMSF, 0.1 mM pepstatin, 2 mM leupeptin, 1 mM E-64, and 1 mM aprotinin) and 53 u/mL DNase I and 4.9 u/mL RNase. For 20 minutes, they were incubated at 4\u0026deg;C. After adding 14 mM of DTT, the samples were centrifuged at 10,000 xg for 20 minutes at 4\u0026ordm;C until the supernatant was entirely clear and free of lipids. The Bradford technique was used to estimate the protein concentration. [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] Employing the BSA-based Bio-Rad Protein Assay. Equal and standard loading quantities were verified on 1-DE gels that were stained with CBB.\u003c/p\u003e\u003cp\u003eProtein extracts were diluted for 2-DE analysis using a rehydration solution that contained 1.6% (v/v) DeStreak Reagent (GE Healthcare), 7 M urea, 2 M thiourea, 18 mM Tris\u0026ndash;HCl pH 8.0, 4% (w/v) CHAPS, 0.5% (v/v) IPG buffer in the same range as the IPG strip, and 0.002% Bromophenol Blue. Samples with 2 mg of protein were placed onto pH 3\u0026ndash; 10, 24 cm immobilized pH gradient (IPG) strips (Immobiline DryStrips, GE Healthcare) for the first dimension after being diluted to a final volume of 450 \u0026micro;l. IEF was carried out. at 50 V for 10 h (rehydration), 500 V in gradient for 1 h 30 min, 1000 V in gradient for 1 h 30 min, 2000 V in gradient for 1 h 30 min, 4000 V in gradient for 1 h 30 min, 8000 V in gradient for 2 h and 8000 V holding for 6 h, using Ettan\u0026trade; IPGphor\u0026trade; Isoelectric Focusing System (Amersham, Biosciences). IPG strips were equilibrated with 50 mM Tris\u0026ndash;HCl (pH 8.8), 6 M urea, 30% (v/v) glycerol, 2% SDS, a trace of Bromophenol Blue, and 10 mg/ml DTT for 15 minutes prior to the second dimension. This was followed by a second equilibration step using the same buffer, but this time with 25 mg/ml iodoacetamide in place of DTT, for an additional 15 minutes while being gently shaken. For the second dimension, the focused strips was performed on vertical slabs (20 X 18 X 0.2 cm) where loaded and run on sodium dodecyl sulfate polyacrylamide gel by electrophoresis method SDS-PAGE (13% polyacrylamide) for 30 min, 100 V at room temperature followed by 250 V during 4 hours. Proteins were visualized with silver stain dyes [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. An ImageScanner desktop device (Amersham, Biosciences) was used to scan the 2-DE gels. Images were obtained using the LabScan scanning application, in transmission mode, at a greyscale level of 16 bips, at 300 dpi, with a magnification factor of 1:1 (100%) and saved as TIFF (Tag Image File Format) files. The ImageMasterTM 2-D Platinum 5.0 software (Amersham, Biosciences) was used to analyze the images.\u003c/p\u003e\n\u003ch3\u003eImage analysis and protein identification\u003c/h3\u003e\n\u003cp\u003eThe gel images were analysis using the using the ImageJ and Melanie v.9 software for 2D gel analysis, and the detected spots on the gel were then contrasted with the NCBI and Swiss-Prot databases and an exact match was found through the Mascot search program [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e].Furthermore, the Swiss-Prot and NCBI protein databases were examined for the annotation of the detected proteins in their descriptions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eIdentification and Functional Assignments for Protein-Associated with dots in\u003c/b\u003e \u003cb\u003eH. vulgare\u003c/b\u003e.\u003c/p\u003e\u003cp\u003ePutative sequences of protein from dots analysis were used as a query to search against the \u003cem\u003eH. vulgare\u003c/em\u003e genomics that we already get from NCBI genomics (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://phytozome-next.jgi.doe.gov/blast-search\u003c/span\u003e\u003cspan address=\"https://phytozome-next.jgi.doe.gov/blast-search\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, accessed on 25 Dec.2023). The alignment sequence was then examined with the Phytozome and KEGG databases in order to predict the biological function of these chosen candidate proteins that were linked to different \u003cem\u003eH. vulgare\u003c/em\u003e dots. Ultimately, we obtain 53 genes that are closely associated with different functions in \u003cem\u003eH. vulgare\u003c/em\u003e. [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003ePutative expression pattern of our target genes at transverse and sagittal sections based on\u003c/b\u003e \u003cb\u003eH. vulgare\u003c/b\u003e \u003cb\u003etranscript expression.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eProfiles of putative expression of 47 genes from \u003cem\u003eH. vulgare\u003c/em\u003e were extracted based on \u003cem\u003eH. vulgare\u003c/em\u003e transcript expression database from three tissues of transverse and sagittal sections at different times, including; 4D- SMT, 4D-END, 4D-EMB, 8D- SMT, 8D-END, 8D-EMB, 16D- SMT, 16D-END, 16D-EMB, 24D- SMT, 24D-END, 24D-EMB, 32D- SMT, 32D-END and 32D-EMB (see supplementary Table\u0026nbsp;1). The creation of expression profiles was done using the barley plant Electronic Fluorescent Pictograph Browsers (barley eFP browsers) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://bar.utoronto.ca/eplant_Arabidopsis/\u003c/span\u003e\u003cspan address=\"http://bar.utoronto.ca/eplant_Arabidopsis/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) accessed on 25 April 2024 [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003ePutative expression pattern of our target genes at various tissue, whole spike and provascular Tissue based on\u003c/b\u003e \u003cb\u003eH. vulgare\u003c/b\u003e \u003cb\u003etranscript expression.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe putative expression profiles of 47 genes from \u003cem\u003eH. vulgare\u003c/em\u003e were extracted based on \u003cem\u003eH. vulgare\u003c/em\u003e transcript expression database from various tissues, whole spike and provascular tissue such as; Vegatative Apex (I-Va-SAM), Double Ridhe (I-Dr-IM),Double Ridhe (I-Dr-LRM), Double Ridhe (I-Dr-SRM), Triple Mound (I-Tm-IM),Triple Mound (I-Tm-LSM),Triple Mound (I-Tm-CSM), Glume Primordium (I-Gp-IM),Glume Primordium (I-Gp-LSM),Glume Primordium (I-Gp-CSM), Legmma Primodium (I-Lp-IM),Legmma Primodium (I-Lp-LSM),Legmma Primodium (I-Lp-CSM), Stamen Primordium (I-Sp-IM),Stamen Primordium (I-Sp-LSM),Stamen Primordium (I-Sp-CSM), Awa Primordium (I-Ap-IM),Awa Primordium (I-Ap-LSM),Awa Primordium (I-Ap-CSM), White Anther (I-Wa-IM), Leaf Blade Base (I-LBB), Root Apical Meristem (I-RAM), Double Ridge (W-DR), Triple Mound (W-TM), Glume Primordium (W-GP), Lemma Primordium (W-LP), Stamen (W-SP), Awn Primordium (W-AP), Double Ridge (R-DR), Triple Mound (R-GP), Glume Primordium (R-GP), Lemma Primordium (R-LP), Stamen (R-SP) and Awn Primordium (R-AP) (see supplementary Table\u0026nbsp;1. The Electronic Fluorescent Pictograph Browsers for barley plants were used to develop expression profiles. (barley eFP browsers) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://bar.utoronto.ca/eplant_Arabidopsis/\u003c/span\u003e\u003cspan address=\"http://bar.utoronto.ca/eplant_Arabidopsis/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) accessed on 30April 2024 [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003ePutative expression pattern of our target genes at various tissues under light and shade based on\u003c/b\u003e \u003cb\u003eH. vulgare\u003c/b\u003e \u003cb\u003etranscript expression.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo analyses the putative expression profiles of 47 genes from \u003cem\u003eH. vulgare\u003c/em\u003e were extracted based on \u003cem\u003eH. vulgare\u003c/em\u003e transcript expression database from various tissues under light and shade conditions, including; Double Ridhe (I-Dr-IM), Double Ridhe (I-Dr-LRM),Double Ridhe (I-Dr-SRM), Triple Mound (I-Tm-IM),Triple Mound (I-Tm-LSM),Triple Mound (I-Tm-CSM), Glume Primordium (I-Gp-IM),Glume Primordium (I-Gp-LSM),Glume Primordium (I-Gp-CSM), Legmma Primodium (I-Lp-IM),Legmma Primodium (I-Lp-LSM),Legmma Primodium (I-Lp-CSM), Stamen Primordium (I-Sp-IM),Stamen Primordium (I-Sp-LSM),Stamen Primordium (I-Sp-CSM), Awa Primordium (I-Ap-IM), Awa Primordium (I-Ap-LSM) and Awa Primordium (I-Ap-CSM), (see supplementary Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). Expression profiles were created using the barley plant Electronic Fluorescent Pictograph Browsers (barley eFP browsers) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://bar.utoronto.ca/eplant_Arabidopsis/\u003c/span\u003e\u003cspan address=\"http://bar.utoronto.ca/eplant_Arabidopsis/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) accessed on 5 June 2024 [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003e\u003cstrong\u003eProtein extraction and Identification in\u003c/strong\u003e \u003cstrong\u003eH. vulgare\u003c/strong\u003e \u003cstrong\u003eleaves.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eLeaf proteins were taken out of barley leaf under drought stress and without drought stress (control), and then the proteins were separated in the 2D gels using electrophoreticism. After that, using 2-DE, we examined the protein patterns in the pH range of 3\u0026ndash;10. The barley proteins that were visible were packed, and all our spots (dots) became visible in the pH range of 5\u0026ndash;10. Moreover, we used 2-DE to further examine the protein patterns of these areas and the resulting 2DE images of the proteins in barley leaves are displayed in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eA, B and Supplementary Fig. 1. After being chosen from 2-D gels, spots were analyzed using a MASCOT database. These protein spots were located through a search in barley, rice, wheat and other cereal crops protein sequences from Swiss-Prot, phytozome 13 and NCBI databases. As results, 56 spots (barely proteins) were chosen for identification, according to the putative functions of each spot, see supplementary table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cp\u003eThe spots were visualized by silver staining. Protein spots are indicated by white numbers. Spots indicate the differentially expressed protein spots whose expression levels were significantly induced or down regulated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunctional Annotations of the Gene-Associated dots in\u003c/strong\u003e \u003cstrong\u003eH. vulgare\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eIn order to estimate the possible activities of our target genes, the \u003cem\u003eH. vulgare\u003c/em\u003e genomic sequence served as a template for searching the protein dot sequence. We discovered 53 genes that may be involved in barley\u0026apos;s resistance to drought and other abiotic stressors based on sequence homology. (see Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Subsequently, multiple databases, including the Phytozome, NCBI, InterPro, and KEGG databases, predicted additional function annotations for these genes. Contextually, these genes were linked to numerous biological processes, such as HORVU.MOREX.r3.2HG0202350 (gi|251832986), HORVU.MOREX.r3.2HG0202350 (gi|121340), HORVU.MOREX.r3.UnG0798500 (gi|108711272), HORVU.MOREX.r3.UnG0808370 (gi|110915608), HORVU.MOREX.r3.5HG0483130 (RBL_AGRST), HORVU.MOREX.r3.5HG0490180 (gi|32765549), HORVU.MOREX.r3.1HG0001110 (gi|17425184), HORVU.MOREX.r3.1HG0001420 (gi|53854906), HORVU.MOREX.r3.2HG0167220 (BAS1_WHEAT), HORVU5Hr1G124160 (CAA32900.1), HORVU.MOREX.r3.2HG0120840 (gi|326496957), HORVU.MOREX.r3.6HG0591100 (CAA36498.1), HORVU.MOREX.r3.2HG0138840 (XP_002518555.1), HORVU.MOREX.r3.3HG0276570 (gi|326493350), HORVU.MOREX.r3.5HG0421460 (gi|326493798), HORVU.MOREX.r3.5HG0511770 (AAF98561.1), HORVU.MOREX.r3.4HG0417260 (AAC67246.1), HORVU.MOREX.r3.5HG0421370 (gi|326493636), HORVU.MOREX.r3.4HG0385790 (CAA06996.1), HORVU.MOREX.r3.7HG0720010 (GI:18412879), HORVU.MOREX.r3.4HG0345760 (AAO42684.1), HORVU.MOREX.r3.3HG0304680 (ACO44685.1) and HORVU.MOREX.r3.4HG0392240 (CAA38036.1) that associated with Plastid glutamine synthetase 2, Glutamine synthetase leaf isozyme, Chloroplastic, ATP synthase beta chain, putative, ATP synthase beta subunit, Ribulose bisphosphate carboxylase large chain, Predicted: 20 kDa chaperonin, chloroplastic-like respectivelly, Cytosolic heat shock protein 90, LMW- glutenin subunit group 3 type II, LMW- glutenin, 2-cys peroxiredoxin BAS1, Chlorophyll a-b binding protein 1, chloroplastic, thioredoxin peroxidase, Elongation factor Tu, chloroplastic, cysteine-rich receptor-like protein kinase 10, isocitrate dehydrogenase, glycine rich protein, RNA binding protein, UDP-glucose 6-dehydrogenase, Beta-amylase, enolase, L-ascorbate peroxidase, Leucine-rich repeat family protein LRR, Alcohol dehydrogenase I, fructose-bisphosphate aldolase and Heat shock protein 21, chloroplastic, respectively (see Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe putative expression of our target genes at different transverse and sagittal sections based on\u003c/strong\u003e \u003cstrong\u003eH. vulgare\u003c/strong\u003e \u003cstrong\u003etranscript expression using barley eFP browsers tool.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on the transcript expression of H. vulgare, the potential expression of our target genes in various transverse and sagittal sections was predicted using the Barley eFP browsers tool. The findings demonstrated that all fifteen tissues had high expression levels of the majority of our target genes from H. vulgare. (e.g. 4D- SMT, 4D-END, 4D-EMB, 8D- SMT, 8D-END, 8D-EMB, 16D- SMT, 16D-END, 16D-EMB, 24D- SMT, 24D-END, 24D-EMB, 32D- SMT, 32D-END and 32D-EMB) see Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e For example, HORVU.MOREX.r3.2HG0202350 (gi|251832986), HORVU.MOREX.r3.6HG0613270 (gi|121340), HORVU.MOREX.r3.5HG0490180 (gi|32765549), HORVU.MOREX.r3.3HG0232910 (gi|326497973), HORVU.MOREX.r3.2HG0120840 (gi|326496957), HORVU.MOREX.r3.6HG0591100 (CAA36498.1), HORVU.MOREX.r3.2HG0138840 (XP_002518555.1), HORVU.MOREX.r3.3HG0276570 (gi|326493350), HORVU.MOREX.r3.5HG0421460 (gi|326493798), HORVU.MOREX.r3.5HG0511770 (AAF98561.1), HORVU.MOREX.r3.4HG0417260 (AAC67246.1), HORVU.MOREX.r3.5HG0451540 (KAE8821856), HORVU.MOREX.r3.5HG0421460 (gi|326493798), HORVU.MOREX.r3.4HG0385790 (CAA06996.1), HORVU.MOREX.r3.4HG0369570 (ADK56176.1), HORVU.MOREX.r3.3HG0290880 (CAA77237.1), HORVU.MOREX.r3.7HG0720010 (GI:18412879), HORVU.MOREX.r3.4HG0345760 (AAO42684.1), HORVU.MOREX.r3.3HG0304680 (ACO44685.1) and HORVU.MOREX.r3.4HG0392240 (CAA38036.1) see Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and supplementary Table 2.. Furthermore, these previous genes encoding Plastid glutamine synthetase 2 [\u003cem\u003eT. Aestivum\u003c/em\u003e], Glutamine synthetase leaf isozyme, Chloroplastic, Cytosolic heat shock protein 90 [\u003cem\u003eH. vulgare\u003c/em\u003e], predicted protein (\u003cem\u003eH. vulgare\u003c/em\u003e), thioredoxin peroxidase (\u003cem\u003eH. vulgare\u003c/em\u003e), Elongation factor Tu, chloroplastic (\u003cem\u003eArabidopsis thaliana\u003c/em\u003e), cysteine-rich receptor-like protein kinase 10 (\u003cem\u003eRicinus communis\u003c/em\u003e), isocitrate dehydrogenase (\u003cem\u003eH. vulgare\u003c/em\u003e), Beta-amylase, 70 kDa heat shock protein (H. vulgare), glycine rich protein, RNA binding protein (H. vulgare), UDPglucose 6-dehydrogenase (Zea mays), L-ascorbate peroxidase (\u003cem\u003eH. vulgare\u003c/em\u003e) glycosyltransferase 75 (\u003cem\u003eTriticum aestivum\u003c/em\u003e), reversibly glycosylated polypeptide (\u003cem\u003eTriticum aestivum\u003c/em\u003e), Leucine-rich repeat family protein LRR (\u003cem\u003eArabidopsis thaliana\u003c/em\u003e), Alcohol dehydrogenase I (\u003cem\u003eOryza eichingeri\u003c/em\u003e), fructose-bisphosphate aldolase (\u003cem\u003eH. vulgare\u003c/em\u003e) and Heat shock protein 21, chloroplastic see Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and supplementary Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePredication the putative expression pattern of our target genes at various tissue, whole spike and provascular tissue based on\u003c/strong\u003e \u003cstrong\u003eH. vulgare\u003c/strong\u003e \u003cstrong\u003etranscript expression.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe putative tissue expression of our candidate genes from H. vulgare at various tissue, whole spike and provascular tissue based on \u003cem\u003eH. vulgare\u003c/em\u003e transcript expression was analyzed to realize their roles and functions in drought tolerance and other a biotic stress Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. The results showed that some of our target genes from \u003cem\u003eH. vulgare\u003c/em\u003e were abundantly expressed across all tissues. at various tissue, whole spike and provascular tissue. For example, the HORVU.MOREX.r3.5HG0480620 (gi|357158586), HORVU.MOREX.r3.7HG0661950 (gi|51090748), HORVU.MOREX.r3.5HG0490180 (gi|32765549), HORVU.MOREX.r3.3HG0276570 (gi|326493350), HORVU.MOREX.r3.5HG0421460 (gi|326493798), HORVU.MOREX.r3.5HG0421460 (gi|326493798), HORVU.MOREX.r3.5HG0421370 (gi|326493636), HORVU.MOREX.r3.4HG0370860 (AAC32060.1), HORVU.MOREX.r3.4HG0385790 (CAA06996.1), HORVU.MOREX.r3.4HG0369570 (ADK56176.1) and HORVU.MOREX.r3.3HG0304680 (ACO44685.1) that is connected to The following are predicted: cytosolic heat shock protein 90 [H. vulgare], putative chaperonin 21 precursor [Oryza sativa Japonica], 20 kDa chaperonin, chloroplastic-like (Brachypodium distachyon), isocitrate dehydrogenase (\u003cem\u003eH. vulgare\u003c/em\u003e), glycine rich protein, RNA binding protein (\u003cem\u003eH. vulgare\u003c/em\u003e), glycine rich protein, RNA binding protein (\u003cem\u003eH. vulgare\u003c/em\u003e), enolase (Hordeum vulgare), 20S proteasome subunit PAE1 (Arabidopsis thaliana), L-ascorbate peroxidase (Hordeum vulgare), glycosyltransferase 75 (\u003cem\u003eTriticum aestivum\u003c/em\u003e) and fructose-bisphosphate aldolase (Hordeum vulgare) see Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e,Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and supplementary Table 3.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalyses of different expression pattern of target genes at Putative expression pattern of our target genes at various tissues under light and shade based on\u003c/strong\u003e \u003cstrong\u003eH. vulgare\u003c/strong\u003e \u003cstrong\u003etranscript expression.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe putative tissue expression of our candidate genes from \u003cem\u003eH. vulgare\u003c/em\u003e under light and shade based on \u003cem\u003eH. vulgare\u003c/em\u003e transcript expression was analyzed to comprehend their operations and involvement in a biotic stress and drought tolerance. Figure \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e some of our target genes from H. vulgare were found to be substantially expressed in all tissues, according to the results. For example, the HORVU.MOREX.r3.7HG0661950 (gi|51090748), HORVU.MOREX.r3.5HG0490180 (gi|32765549), HORVU.MOREX.r3.3HG0232890 (gi|326516152), HORVU.MOREX.r3.3HG0276570 (gi|326493350), HORVU.MOREX.r3.5HG0421460 (gi|326493798), HORVU.MOREX.r3.5HG0421460 (gi|326493798), HORVU.MOREX.r3.5HG0421370 (gi|326493636), HORVU.MOREX.r3.4HG0370860 (AAC32060.1), HORVU.MOREX.r3.4HG0385790 (CAA06996.1), HORVU.MOREX.r3.4HG0369570 (ADK56176.1) and HORVU.MOREX.r3.3HG0304680 (ACO44685.1) that associated with Putative chaperonnin 21 precursor [\u003cem\u003eOryza sativa\u003c/em\u003e], Cytosolic heat shock protein 90 [\u003cem\u003eH. vulgare\u003c/em\u003e], predicted protein (\u003cem\u003eH. vulgare\u003c/em\u003e), isocitrate dehydrogenase (\u003cem\u003eH. vulgare\u003c/em\u003e), glycine rich protein, RNA binding protein (\u003cem\u003eH. vulgare\u003c/em\u003e), glycine rich protein, enolase (\u003cem\u003eH. vulgare\u003c/em\u003e), 20S proteasome subunit PAE1 (\u003cem\u003eArabidopsis thaliana\u003c/em\u003e), L-ascorbate peroxidase (\u003cem\u003eH. vulgare\u003c/em\u003e), glycosyltransferase 75 (\u003cem\u003eTriticum aestivum\u003c/em\u003e) and fructose-bisphosphate aldolase (\u003cem\u003eH. vulgare\u003c/em\u003e) see Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e,Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and and supplementary Table 4.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eDrought and other stresses co-occur in the natural environment, especially in dry hot areas [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. An essential and top research objective is learning more about how plants react to drought and salinity stresses [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Moreover, in our study we used the 2-DE gels for proteome analysis and Determine the key proteins linked to stress and their related genes, to comprehend the fundamental processes behind barley's resistance to drought stress. Based on our results we identified among 56 proteins and most of them are related to the drought and other stresses tolerance in this study see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e. These previous proteins were up-regulated or down-regulated or remained unaltered in barely plant under drought stress in compared with control see Figure. Proteins whose quantity is highly dependent on drought and other stresses are primarily linked to a number of biological processes, including photosynthesis, plant growth and development. [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAs results, Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and B display two distinct 2D-GE pictures, and after analyzing each gel we found unique spots for everyone and common spots between the two gels. Also, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and B displays the correlation between the spot sizes.and the expression of proteins under the stress and control condition. In particular, the gel analysis for leaf sample under 10% PEG has 10 unique spots such as; spot 13 (HORVU1Hr1G001420), spot 17 (HORVU2Hr1G073760), spot 24 (HORVU2Hr1G026810), spot 29 (HORVU5Hr1G096370), spot 34 (HORVU5Hr1G038630), spot 42 (HORVU2Hr1G029840), spot 44 (HORVU4Hr1G040770), spot 49 (HORVU3Hr1G073780), spot 50 (HORVU7Hr1G090240) and spot 56 (HORVU4Hr1G063350), and these previous spots related with various proteins such as; LMW- glutenin, 2-cys peroxiredoxin BAS1 (Triticum aestivum), Thioredoxin peroxidase (Hordeum vulgare), UDP-glucose 6-dehydrogenase (Zea mays), Ribulose-bisphosphate carboxylase small chain, Putative hydrolase (Arabidopsis thaliana), Proteasome subunit alpha type-5-A (Arabidopsis thaliana), Reversibly glycosylated polypeptide (Triticum aestivum), Leucine-rich repeat family protein LRR (Arabidopsis thaliana) and Heat shock protein 21, chloroplastic see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e and and supplementary Table\u0026nbsp;1.. And from our data analysis we found these previous proteins were classified and showed various biological functions in barley leaf see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e. [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. they found positively relationship between the relative water content in leave and the total Rubisco activity, which mean the Ribulose-bisphosphate carboxylase small chain can plays a complex role under drought conditions, through maintain photosynthetic rates under stress and these response based on the kind, intensity, and length of the stress. Moreover, as we know the barley and some other cereal crops quality are governed largely by two types of glutenin proteins: the high molecular weight (HMW) and the low molecular weight (LMW) - glutenin subunit [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Moreover, [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Study the influence of heat and drought stress on the levels of various glutenin types, and found a linear relationship between the impact of drought stress and the LMW-glutenin, and any alter in the composition and properties of glutenin may be affected on strength and bread-making quality. For Thioredoxin peroxidase protein, several studies have been reported about its vital function in the growth and development of a plant under various abiotic Stress as a component of a redox system, and it is ability to modulate the redox signalling during plant development, growth and stress adaptation through dithiol-disulfide exchanges [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. And this dithiol-disulfide is essential for both signal transduction and redox sensing pathways [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. And another proteins such as; Heat shock protein 21 and 2-cys peroxiredoxin BAS1 (Triticum aestivum) have been reported as a unique spot under 10% PEG, and these two proteins plays a significant part in plants' ability to withstand drought stress. Through activation the antioxidant enzymatic system, which working on avoiding and scavenging reactive oxygen species (ROS) over-accumulation by 2-cys peroxiredoxin enzyme [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Heat shock protein 21 reduces the effect of drought stress by mediates stress signal transduction, controlling with ATPase-coupled, and interactions with co-chaperone proteins [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Furthermore, the function of UDP-glucose 6-dehydrogenase (UGDH) in tolerance to drought stress has been reported by [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. They found the UGDH can enhance the plant response to drought stress through their effect on cell wall potentially and composition. And the UGDH enzyme have ability to conversion of UDP-glucose to UDP-glucuronic acid by catalyze response, and the second component is a precursor for different cell wall polysaccharides, such as; hemicellulose and pectin.\u003c/p\u003e\u003cp\u003eOn the other hand, the gel analysis for control sample has five unique spots such as; spot 25 (HORVU6Hr1G053680), spot 26 (HORVU2Hr1G044650), spot 27 (HORVU3Hr1G059060), spot 28 (HORVU5Hr1G002150) and spot 46 (HORVU7Hr1G043150) and these previous spots were related to various proteins such as; Elongation factor Tu, chloroplastic (\u003cem\u003eArabidopsis thaliana\u003c/em\u003e), Cysteine-rich receptor-like protein kinase 10 (\u003cem\u003eRicinus communis\u003c/em\u003e), Isocitrate dehydrogenase (\u003cem\u003eH. vulgare)\u003c/em\u003e, Glycine rich protein, RNA binding protein (Hordeum vulgare) and Protein-serine/threonine kinase (\u003cem\u003eGlycine max\u003c/em\u003e), respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Additionally, after analysis the two gels from leaf sample under 10% PEG and control we have found 26 common spots and most of these spots were significantly increased in the size under the effect of stress in compared with the control, which mean the drought stress has positively effect on the expression on these proteins (shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). These common proteins such as; spot 1 (HORVU2Hr1G111300), spot 2 (HORVU6Hr1G074030), spot 3 (HORVU7Hr1G088200), spot 6 (HORVU5Hr1G062310), spot 7 (HORVU7Hr1G033900), spot 8 (HORVU5Hr1G072420), spot 11 (HORVU1Hr1G001020), spot 12 (HORVU1Hr1G000990), spots 14, 15, 16, 18, 19 (HORVU2Hr1G073760), spot 21 (HORVU6Hr1G049250), spot 23 and 33 (HORVU5Hr1G124160), spot 30 (HORVU7Hr1G048820), spot 31 (HORVU0Hr1G003270), spot 32 (HORVU4Hr1G089510), spot 47 (HORVU4Hr1G057210), spot 48 (HORVU4Hr1G038960), spot 51(HORVU4Hr1G016810), spot 52 (HORVU3Hr1G088540), and spots 53, 54, 55 (HORVU4Hr1G063350) see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Furthermore, these previous common spots are related with various proteins such as; Plastid glutamine synthetase 2 [T. Aestivum], Glutamine synthetase leaf isozyme, Chloroplastic, ATP synthase beta chain, putative [\u003cem\u003eOryza sativa\u003c/em\u003e Japonica Group], Predicted: 20 kDa chaperonin, chloroplastic-like (\u003cem\u003eB. distachyon\u003c/em\u003e), Putative chaperonin 21 precursor [\u003cem\u003eO. sativa\u003c/em\u003e Japonica], Cytosolic heat shock protein 90 [H. vulgare], Glutenin, LMW- glutenin subunit group 3 type II, high molecular weight subunit PC237, 2-cys peroxiredoxin BAS1 (\u003cem\u003eTriticum aestivum\u003c/em\u003e), ATP synthase beta subunit [Calotheca brizoides], Chlorophyll a-b binding protein 1, chloroplastic, Protein RAFTIN 1B (\u003cem\u003eT. aestivum\u003c/em\u003e), Oxygen-evolving enhancer protein 3\u0026thinsp;\u0026minus;\u0026thinsp;1, chloroplastic, Beta-amylase, L-ascorbate peroxidase (\u003cem\u003eH. vulgare\u003c/em\u003e), Glycosyltransferase 75 (\u003cem\u003eT. aestivum\u003c/em\u003e), Alcohol dehydrogenase I (Oryza eichingeri), Fructose-bisphosphate aldolase (\u003cem\u003eH. vulgare\u003c/em\u003e) and\u003c/p\u003e\u003cp\u003eHeat shock protein 21, chloroplastic, respectively. And from our data analysis we found these previous proteins showed various biological functions and some of these functions were related with the ability of drought tolerance in plants see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e. For example, the spot 32 (HORVU4Hr1G089510) was related to Beta-amylase (BAM) protein and this protein plays an important function in plants drought stress tolerance through degradation the starch into maltose sugar, and this last one can used by plant as source of energy and as an osmoprotectant to protect plant from plants cope [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Also, the spot 47 (HORVU4Hr1G057210) was related to L-ascorbate peroxidase and this enzyme helping plants cope with drought stress through utilizes ascorbate (vitamin C) as a substrate to reduce H2O2 to water, and decrease the oxidative damage imposed by drought stress. By scavenge ROS then mitigating the harmful of the effects of ROS produced [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Moreover, the spot 51 (HORVU4Hr1G016810) was involved in Alcohol dehydrogenase I (ADH1), and this enzyme has a vital function in drought and other stress tolerance by catalyzing the conversion of acetaldehyde to ethanol, and this helps plant under various stress to regenerate NAD\u0026thinsp;+\u0026thinsp;for continue energy production under anaerobic conditions that occur under drought [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. At the end, the spot 52 (HORVU3Hr1G088540) was related with Fructose-bisphosphate aldolase enzyme (FBA), and this enzyme play an important role in drought and other abiotic stress tolerance by converting fructose-1,6-bisphosphate into dihydroxyacetone phosphate and glyceraldehyde-3-phosphate in the Calvin cycle of photosynthesis pathway for producing sugars that fuel plant growth and metabolism see Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOn the other hand, numerous investigations have revealed that the effects of drought and other abiotic stress not ceasing only at the leave of plantlet but they can effects on various tissues at transverse and sagittal sections, various tissues under light and shade, and various tissues at whole spike and provascular tissue. For that, in this study we used various tools and parameters from the barley Plant Fluorescent Electronic Pictograph Browsers (barley eFP browsers) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://bar.utoronto.ca/eplant_Arabidopsis/\u003c/span\u003e\u003cspan address=\"http://bar.utoronto.ca/eplant_Arabidopsis/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) For predicting the putative expression of our target genes at all previous tissues see (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). And from our data analysis, we found all our genes have different expression levels at each tissue and under various development stages and growth conditions. In addition, some genes have variable putative expression from tissue to another one under various development stages and conditions see (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eAll this study, we used two-dimensional electrophoresis (2D-gel), and various bioinformatics databases to inquire that how drought stress affects the levels expression of different proteins in barley leaves. Our results show various unique and common proteins which are related with the ability of barley plants to drought stress tolerance. Moreover, in this research we have determined a list from 56 spots (proteins), and from our analysis using bioinformatics databases, we found these proteins have various biological functions and roles related with response to drought stress tolerance in barley. Finally, this information can be relied upon in future programs related to the production a new barley genotypes that are tolerant to drought and other biotic stresses.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eSDS Sodium Dodecyl Sulfate\u003c/p\u003e\u003cp\u003e2-DE Two-Dimensional Electrophoresis\u003c/p\u003e\u003cp\u003ePEG Polyethylene Glycol\u003c/p\u003e\u003cp\u003eMS Mass Spectrometry\u003c/p\u003e\u003cp\u003eG 132 Giza 132\u003c/p\u003e\u003cp\u003eV Volt\u003c/p\u003e\u003cp\u003eIEF Iso Electric Focusing\u003c/p\u003e\u003cp\u003ePAGE Polyacrylamide Gel Electrophoresis\u003c/p\u003e\u003cp\u003eNCBI National Center for Biotechnology\u003c/p\u003e\u003cp\u003eFBA Fructose-Bisphosphate Aldolase Enzyme\u003c/p\u003e\u003cp\u003eADH Alcohol Dehydrogenase\u003c/p\u003e\u003cp\u003eBAM Beta-Amylase\u003c/p\u003e\u003cp\u003eROS Reactive Oxygen Species\u003c/p\u003e\u003cp\u003eHMW High Molecular Weight\u003c/p\u003e\u003cp\u003eLMW Low Molecular Weight\u003c/p\u003e\u003cp\u003eLRR Leucine-Rich Repeat\u003c/p\u003e\u003cp\u003eeFP Electronic Fluorescent Pictograph Browsers\u003c/p\u003e\u003cp\u003eIPG Immobilized pH Gradient\u003c/p\u003e\u003cp\u003eCBB Coomassie Brilliant Blue\u003c/p\u003e\u003cp\u003eDTT Dithiothreitol\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data supporting my findings can be available and found in the supplementary data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors revised the manuscript, read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026rsquo;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eYaseen R, El-Sayed M. 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Cells. 2020;9(6):1530. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/cells9061530\u003c/span\u003e\u003cspan address=\"10.3390/cells9061530\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Drought stress, barley, proteomics, two dimensional (2-DE) electrophoresis, Polyethylene Glycol (PEG), putative tissue expression","lastPublishedDoi":"10.21203/rs.3.rs-7475122/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7475122/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eDrought stress is one of the main environmental factors limiting the development, growth, and crop yield of barley plants. Finding drought-tolerant genes and the proteins they encode that are linked to the interplay between drought tolerance and growth/yield is crucial for enhancing genotypes' ability to withstand drought and other abiotic stressors. Our study's objective was to leverage prior proteomic research to identify candidate genes and the proteins they encode that are important in barley's responses to drought tolerance and to examine how drought stress alters their expression.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThis study reveals that proteome alterations linked to drought stress in the Giza132 barley genotype were examined using two-dimensional (2-DE) electrophoresis. Seedlings with one week old were subjected with 10% of Polyethylene Glycol (PEG) treatment for eight days and protein expression profiles were determined with 2-DE gel using total proteins extracted from leaf tissues after treatment in comparison to control (irrigated with tap water during this period). Our Investigations of protein expression profiles revealed that drought stress using 10% of PEG results in global changes in the barley proteome and consequently the genes that related to drought stress tolerance responses. From our results, we identified 56 spots (proteins) most of them are related to the drought and other stresses tolerance. These previous proteins were up /down regulated or remained unaltered in barley plants that are stressed by drought in comparison with control. Moreover, Bioinformatics databases were used to determine the potential tissue expression of our genes at transverse and sagittal slices, various tissues under light and shade, and various tissues at entire spike and provascular tissue.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eUsing two-dimensional gel data analysis and the putative expression analysis for the candidate genes and their encoding proteins, we can comprehend how these genes would function in barley in response to drought stress.\u003c/p\u003e","manuscriptTitle":"Proteomic Analysis of Proteins Responsive to Drought stress in barley","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-14 14:56:51","doi":"10.21203/rs.3.rs-7475122/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-08T06:50:26+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-27T09:09:19+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-25T04:35:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"93862360053477629727851285066920102521","date":"2025-11-24T09:00:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"24779881609975377427460550241330013613","date":"2025-11-21T13:07:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"87931886210608153920482984096010852150","date":"2025-11-19T21:16:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"256518070668260946183148092328782787383","date":"2025-11-19T09:20:13+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-14T11:01:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"4471233409288833743705335571217710127","date":"2025-10-04T13:47:50+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-01T08:36:57+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-27T07:43:43+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-26T07:06:13+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-25T22:15:45+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Plant Biology","date":"2025-09-25T22:11:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e775401b-1d06-448a-bb7f-cce72a48d959","owner":[],"postedDate":"October 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-16T16:06:58+00:00","versionOfRecord":{"articleIdentity":"rs-7475122","link":"https://doi.org/10.1186/s12870-026-08176-8","journal":{"identity":"bmc-plant-biology","isVorOnly":false,"title":"BMC Plant Biology"},"publishedOn":"2026-02-11 15:58:58","publishedOnDateReadable":"February 11th, 2026"},"versionCreatedAt":"2025-10-14 14:56:51","video":"","vorDoi":"10.1186/s12870-026-08176-8","vorDoiUrl":"https://doi.org/10.1186/s12870-026-08176-8","workflowStages":[]},"version":"v1","identity":"rs-7475122","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7475122","identity":"rs-7475122","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}