Adaptation of highland barley to drought stress: from phenotypic analysis to physiological and molecular mechanisms

Abstract

Background

Drought severely limits crop growth and yield. Highland barley (Hordeum vulgare L.), a naturally stress-tolerant crop, serves as an ideal model for investigating the molecular and physiological mechanisms underlying plant drought adaptation.

Results

In this study, two highland barley varieties, Xi-La 22 (XL22) and Zang-Qing 17 (ZQ17), with different degrees of drought tolerance, were used to investigate the mechanism of drought tolerance in highland barley. Compared with XL22, ZQ17 exhibited significant reductions in the biomass and root/shoot ratio, and the increase in ion leakage and malondialdehyde content under drought stress. Natural drought experiment further confirmed that ZQ17 had a higher fatality rate and water loss rate than XL22, indicating that XL22 had higher drought tolerance. Drought induced significant increase in H₂O₂ and O₂.⁻ levels in both barley varieties, especially in ZQ17. Moreover, compared with XL22, more distribution of H₂O₂ in chloroplasts of ZQ17 might lead to greater degradation of photosynthetic protein complexes (PSI, PSII, LHCII trimers), thereby reducing photosynthetic capacity. The activities of glutathione reductase and glutathione peroxidase and content of reduced glutathione and ascorbate acid were markedly higher in XL22 compared with ZQ17 under drought stress. RNA-seq results showed many genes related to reactive oxygen species (ROS) scavenging, osmotic adjustment (LEA, HSP, aquaporins), hormone signaling and transcription factors (TFs) were specifically up-regulated in XL22. Weighted gene co-expression network analysis (WGCNA) further identified key modules and clarified core hub genes in XL22, mainly including genes in bZIP, AP2/ERF, bHLH transcription factor (TF) families and ABA signaling pathway, which help maintain high ROS scavenging capacity, root/shoot ratio and photosynthetic performance.

Conclusion

This study reveals that drought-tolerant highland barley maintains antioxidant activity, photosynthetic complex integrity, hormone signaling, and drought-responsive TF activation, providing insights for barley germplasm screening.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12870-026-08690-9.

Introduction

Drought, exacerbated by global warming, has become a paramount environmental stressor that severely impairs crop growth, development, and productivity [1, 2]. It threatens to reduce global cereal yields by over 50% by 2050, despite the need for a 70% increase in agricultural output to feed a burgeoning population [3–6]. Drought triggers cellular dehydration, which suppresses enzyme activities and degrades chlorophyll content, leading to metabolic dysfunction [7–9]. Furthermore, water deficit induces a surge in reactive oxygen species (ROS), causing membrane damage and secondary oxidative stress [10]. Ultimately, prolonged drought stunts plant growth, causes leaf wilting, and severely reduces final crop yield and quality [11]. To adapt to drought stress, plants have evolved many physiological adaptation strategies, such as reducing stomatal conductance to limit water loss, increasing the accumulation of osmotic regulating substances to maintain water potential, and enhancing antioxidant enzyme activities to eliminate ROS [10, 12]. For example, overexpression of TaWRKY24 in tobacco enhanced the accumulation of proline and soluble sugars, thereby increasing relative water content (RWC), and increased the enzyme activities, thus reducing membrane oxidative damage under drought stress [13]. In rice, ZmGLK (GOLDEN2-LIKE) overexpression enhanced drought tolerance by promoting stomatal closure compared to wild-type plants [14].

A comprehensive understanding of the molecular mechanisms underlying plant drought tolerance can not only decipher physiological and biochemical reactions but also elucidate potential molecular regulatory networks. To date, RNA sequencing has been employed as a key approach for identifying drought-responsive genes, pathways, and processes in various crops, including rice [15], wheat [16], and wild barley [17, 18], thereby revealing the molecular mechanisms of drought tolerance. Notably, these transcriptomic analyses have identified multiple drought-responsive transcription factors (TFs), including members of the WRKY, MYB, dehydration responsive element binding protein (DREB), APETALA2/ethylene responsive factor (AP2/ERF), basic leucine zipper (bZIP), and NAM, ATAF1/2, and CUC2 protein (NAC) families [19–23], which play central regulatory roles in plant drought responses. Overexpression of stress-responsive NAC family genes (OsSNAC2 and OsNAC78) in rice enhances drought tolerance [24, 25]. Furthermore, KEGG pathway enrichment analysis has revealed that the mitogen-activated protein kinase (MAPK) signaling pathway and the calcium ion (Ca²⁺) signaling pathway are significantly activated under drought stress [26, 27].

Highland barley (Hordeum vulgare L.), known as ‘qingke’ in Chinese or ‘nas’ in Tibetan, has served as a staple crop in the Tibetan Plateau region for centuries [28, 29]. As a natural stress-tolerant species native to the Qinghai Tibet Plateau, such as tolerance to drought, cold, and salt, poor fertility, and low dependence on agricultural chemicals, highland barley has become a valuable crop resource with research potential and application value due to its unique environmental adaptability [30–32]. To date, several stress-related genes have been identified and functionally characterized in highland barley. For example, the genes encoding flavonoid C-pentosyltransferase, tyramine hydroxycinnamoyl transferase, and myeloblastosis (MYB) TF are involved in the tolerance of highland barley to UV-B stress by regulating phenylpropanoid content [29]. The RNA interference lines of HVA1 and Dhn6, two enriched late embryogenesis (LEA) family genes, showed the significantly reduced survival rate under drought stress in highland barley [33]. Although the drought tolerance mechanism of barley has been studied in recent years, the key genes and metabolic pathways responsible for its drought tolerance remain poorly characterized.

In this study, two varieties of highland barley, the drought-sensitive line (Zang-Qing 17, ZQ17) and drought-tolerant line (Xi-La 22, XL22), were used as experimental materials to investigate the molecular mechanism of highland barley tolerance to drought stress. In the study, the changes of growth parameters, ROS levels, and photosynthetic performance in ZQ17 and XL22 seedlings were compared under drought stress and followed by transcriptomic analysis. Through integrated transcriptomics and Weighted Gene Co-expression Network Analysis (WGCNA), key drought stress-related genes, pathways, and biological processes were identified by analyzing differentially expressed genes (DEGs). This research provides novel insights into the molecular mechanisms of drought tolerance in highland barley, deepens the understanding of drought tolerance mechanisms in extremophilic plants, and offers a critical scientific foundation for evaluating and identifying drought-tolerant germplasm resources in highland barley.

Materials and methods

Plant growth and drought treatment

Highland barley cultivars “XL22”, “ZQ17”, “DLH”, “ZQ16”, “ZQ18”, “ZQ20, “ZQ2000” and barley “Ganpi 6” were used in this study and obtained from the Tibet Academy of Agriculture and Animal Husbandry Sciences. Seeds were sterilized with 2% NaClO for 15 min, rinsed with sterile water, and sown in soil. Plants were cultivated in a greenhouse at 22 ± 2 ℃ with a 16 h light/8 h dark cycle under normal water conditions for 2 weeks. Then, seedlings of different highland barley cultivars were treated by completely depriving irrigation for 14 d. Subsequently, a 3-day rehydration treatment was implemented for phenotypic recovery analysis.

PEG6000 (PEG) treatment was performed using the hydroponic method. Seeds were sterilized with 2% NaClO for 15 min. Then, they were washed with sterile water and germinated on aseptic sponge and gauze for 24 h in the dark. Germinated seeds were transferred to 300-mL hydroponic pots and grown in 1/4-strength Hoagland liquid medium (pH 6.0) for 3 d. Highland barley seedlings with uniform growth were selected and transplanted to 1/4-strength Hoagland solution with or without 25% PEG for 48–96 h. The solution was replaced every two days.

Measurement of physiological traits

Biomass quantification was carried out following the protocol of Gao [34]. After cleaning and removing surface moisture from highland barley plants, fresh weight (FW) was recorded using an analytical balance. Subsequently, the samples were dried at 105 °C for 30 min, then dried to constant weight at 65 °C, and the dry weight (DW) was measured. Leaf area was analyzed by capturing digital images with a Nikon camera and quantified with the Image J software (n = 12). Leaf temperature dynamics during drought treatment were monitored using an infrared thermal imaging system.

Determination of RWC and survival rate

The RWC was determined as described by Jones [35] with some modifications. Leaves from the same parts of plants were collected and weighed as FW. Then, the leaves were immersed in distilled water until a constant weight was reached. After that, leaves were weighed as turgid weight (TW). Subsequently, the leaves were first dried at 105 °C for 30 min, then dried to constant weight at 65 °C, and weighed as DW. The RWC was calculated using the formula: RWC (%) = [ (FW − DW) ∕ (TW − DW) ] × 100.

After 14 d of continuous drought treatment and 3 d of rehydration, the survival rate was recorded. The survival rate (%) was calculated using the formula: Survival rate (%) = (Number of surviving plants / Total plants in the treatment group) × 100. Each group contained at least 15 plants as biological replicates, and the experiment was independently repeated at least 3 times.

Measurement of electrolyte leakage (EL) and malondialdehyde (MDA) concentration

Relative EL was measured using a modified method [36]. Leaves were washed with deionized water three times and incubated in deionized water at 25 °C for 2–3 h, the initial conductivity (C1) was measured with a DDS-307 A meter. Then, the leaves were incubated at 100 °C for 30 min, and the final conductivity (C2) was recorded. The conductivity of deionized water was recorded as C0. Relative EL was calculated using the formula: EL (%) = (C1-C0) / (C2-C0) × 100. MDA content was determined using the thiobarbituric acid reactive substances assay as described by Peever and Higgins [37].

Determination of chlorophyll (Chl) content

Chl was extracted from leaves (0.1 g) with 80% acetone, and the absorbance of the supernatant at 664.5 and 647 nm was measured. Chl content was calculated based on the following formulas [38].

Measurement of photosynthetic parameters

Photosynthetic parameters were measured using an LI-6400XT photosynthesis system (LI-COR, USA) equipped with a 2 cm² fluorescence leaf chamber, with leaf temperature maintained at a constant 22 °C. Under simulated native growth conditions, the following parameters were recorded: net photosynthetic rate (Pn), intercellular CO₂ concentration (Ci), and transpiration rate (Tr). Measurements were carried out at a photosynthetically active radiation (PAR) of 300 µmol·m⁻²·s⁻¹ and a stable CO₂ concentration of 400 ppm, with a controlled vapor pressure deficit of 1.10 ± 0.05 kPa to ensure environmental consistency. Additionally, Chl fluorescence parameters, including maximum photochemical quantum efficiency of PSII (Fv/Fm), non-photochemical quenching coefficient (NPQ) and electron transport rate (ETR), were determined using an FMS-2 pulse-modulated fluorescence analyzer (Hansatech Instruments).

Determination of ROS content

ROS staining was performed using 20 µM 2,7-dichlorodihydrofluorescein diacetate (H₂DCF-DA) as a fluorochrome dye. Leaves were incubated with 20 µM H₂DCF-DA in darkness for 15 min, followed by three washes with 100 mM phosphate buffer (pH 7.5). H₂DCF green fluorescence (indicative of ROS) was detected at 525 nm under 488 nm excitation using a laser scanning confocal microscope (Leica SP8), while Chl autofluorescence served as a reference signal. Hydrogen peroxide (H₂O₂) staining was performed as follows: leaves were incubated in a staining buffer [50 mM Tris-HCl (pH 5.0), 1 mg/mL DAB, and 0.05% TritonX-100] at 28 °C for 4 h in the dark. For superoxide (O₂·⁻) staining, leaf samples were stained with nitroblue tetrazolium chloride (NBT). The samples were incubated in NBT solution (0.5 mg/mL NBT, 0.05% Triton X-100, 50 mM PBS, pH 7.4) for 6 h at 28 °C in darkness, then the stained leaves were imaged using a stereoscopic microscope (Zeiss Discover.V20).

H₂O₂ content was analyzed following the method of Alexieva [39] using three biological replicates. H₂O₂ was extracted from shoots with 0.1% TCA buffer. After 12,000 g at 4 °C for 15 min, the supernatant was mixed with the reaction buffer containing 1 M KI and 0.1 M Tris-HCl (pH 7.6). The absorbance was measured at 390 nm. For O₂·⁻ determination, tissues were homogenized in 3 mM hydroxylammonium chloride solution and centrifuged at 12,000 g for 15 min at 4 °C. The supernatant was mixed sequentially with 17 mM sulfanilic acid and 7 mM α-naphthylamine, followed by incubation at 25 °C for 20 min in complete darkness. After a final centrifugation step (4,000 rpm, 10 min), the absorbance was measured at 530 nm [40].

Analysis of stomatal morphology in leaves

Prior to stomatal morphological analysis, plants were light-acclimated for at least 30 min to stabilize physiological conditions. Leaf segments (0.5–1 cm²) were excised and immediately mounted on conductive adhesives, followed by rapid cryofixation in liquid nitrogen for 10 s to preserve native stomatal architecture. The cryo-fixed samples were transferred to a Hitachi S-3400 N scanning electron microscope (Tokyo, Japan) for imaging. Stomatal distribution and morphology were examined at both low (10 ×) and high (300 ×) magnification. Subsequent quantitative analysis of the SEM images included measurements of stomatal density, aperture dimensions (length and width), and structural variations, enabling comprehensive characterization of stomatal morphology at a high resolution.

Determination of antioxidant enzyme activities

Fresh tissue samples (0.3 g) were homogenized in 3 mL ice-cold 25 mM HEPES buffer (pH 7.4), centrifuged (12,000 rpm, 20 min, 4 °C), and the supernatant was analyzed for enzyme activities. The APX activity was measured using the method of Jian [41]. The reaction mixture contained 100 µL of the enzyme extract, 1 mL of the assay buffer (0.1 mM EDTA-Na₂, 0.3 mM ascorbate), and was initiated with 20 µL of 9 mM H₂O₂. Absorbance at 290 nm was monitored continuously for 1 min to determine the enzyme activity. The SOD activity was determined using a modified method [41]. The assay mixture contained 39 mM methionine, 0.225 mM NBT, 0.6 mM EDTA-Na₂, and 0.012 mM riboflavin. Parallel reactions were conducted under light exposure (30 min) and dark conditions (control). The SOD activity was quantified by measuring the absorbance at 560 nm after incubation. The CAT activity was determined by mixing 100 µL of extract with 1 mL of 15 mM H₂O₂ and monitoring at 240 nm [41]. The POD activity was measured by mixing 25 µL of enzyme extract with 1 mL of 20 mM guaiacol and 20 µL of H₂O₂, then monitoring absorbance at 470 nm for 3 min [42].

The glutathione reductase (GR) activity was assayed spectrophotometrically by monitoring NADPH oxidation at 340 nm for 3 min at 25 °C [43]. The 3-mL reaction mixture contained 0.52 mM Tris-HCl (pH 7.5), 6 mM EDTA, 2 mM GSSG (oxidized glutathione), 4 mM NADPH-Na₄, and 100 µL of crude enzyme extract. The glutathione peroxidase (GPX) activity was determined spectrophotometrically at 340 nm by monitoring NADPH oxidation [44]. The 3-mL reaction mixture contained 50 mM phosphate buffer (pH 7.0), 1 mM EDTA, 1 mM sodium azide, 2.5 U/mL GR, 2 mM NADPH-Na₄, and 50 µL of crude enzyme extract. The reaction was initiated by adding 1.6 mM H₂O₂.

Determination of ascorbic acid (AsA) and glutathione contents

The AsA content was measured as described by Law [45] with some modifications. Leaf samples (0.3 g) were homogenized in ice-cold 2.5 M HClO₄ and centrifuged (10,000 g, 10 min, 4 °C). The supernatant (500 µL) was adjusted to pH 6.0 with saturated Na₂CO₃ and diluted with 1 M NaH₂PO₄ to 800 µL. Following DTT activation (0.3 M, 25 °C, 30 min), the AsA content was assayed spectrophotometrically by monitoring the ascorbate oxidation at 265 nm (15 s intervals for 2 min) after initiating the reaction with 100 µL of enzyme extract in 1 mL of 1 M NaH₂PO₄ containing 1 U ascorbate oxidase.

Total glutathione (GSH) content was quantified spectrophotometrically using a DTNB-based enzymatic recycling assay [46]. Briefly, leaf samples (0.3 g) were homogenized in ice-cold extraction buffer (2 mL) and centrifuged (10,000 g, 10 min, 4 °C). The assay mixture consisted of 400 µL of reagent 1 (110 mM Na₂HPO₄, 40 mM NaH₂PO₄, 15 mM EDTA, 0.3 mM DTNB, 0.04% BSA), 320 µL of reagent 2 (1 mM EDTA, 50 mM imidazole, 0.02% BSA, 5% Na₂HPO₄), GR enzyme, 80 µL of enzyme extract, and 80 µL of NADPH-Na₄, with the extraction buffer as a blank control. The absorbance change at 412 nm was recorded immediately upon mixing for 3 min.

Blue native polyacrylamide gel electrophoresis (BN-PAGE)

Thylakoid membrane was isolated by homogenizing 1.0 g of leaves in 5 mL of ice-cold extraction buffer [400 mM sucrose, 50 mM HEPES-KOH (pH 7.6), 5 mM EDTA-KOH, 5 mM MgCl₂, and 10 mM NaCl]. The homogenate was subjected to sequential centrifugation at 4 °C to collect membrane fractions. The final pellet was resuspended in 200 µL of thylakoid storage buffer [330 mM sorbitol, 50 mM HEPES-KOH (pH 8.0), 2 mM EDTA-KOH, 1 mM MgCl₂, and 1 mM DTT] and stored on ice to maintain structural integrity. Spectrophotometric Chl quantification was conducted, followed by native-PAGE with 50 µg Chl equivalents per lane using the NativePAGE™ Buffer System (Thermo Fisher Scientific, Cat. #BN2007).

RNA extraction, cDNA synthesis and quantitative real-time PCR (qRT-PCR) analysis

Total RNA extraction was performed with the Plant RNA Extraction Kit (TIANGEN Biotech, Beijing, China), while cDNA synthesis was conducted using the EasyScript One-Step gDNA Removal and cDNA Synthesis SuperMix Kit (TransGen Biotech, Beijing, China). qRT-PCR analysis was carried out with the SYBR Green qRT-PCR Mix Kit (TransGen Biotech). Gene expression levels were normalized and calculated via the comparative 2^−ΔΔCT method to determine relative transcript abundance. HvACTIN (MK034133) was used as the internal controls for highland barley. The PCR conditions were 98 °C for 2 min, 40 cycles of 20 s at 98 °C, 30 s at 58 °C, and a final 10 min at 72 °C. Primer sequences are provided in Supplemental Table 1.

Transcriptome analysis

Leaves were sampled from the two highland barley cultivars subjected to control and 20% PEG treatment mentioned above, and frozen rapidly with liquid nitrogen. Each treatment group included three biological replicates, yielding a total of twelve independent samples. The transcriptome sequencing was carried out at Biomarker Technologies (Beijing, China).

Gene expression levels were expressed as FPKM (Fragments Per Kilobase per Million mapped reads). DEGs were identified using a significance threshold of false discovery rate (FDR) < 0.01 and an absolute |log₂(fold change)| ≥ 2. Functional enrichment and pathway analysis were conducted using the KEGG database (Kyoto Encyclopedia of Genes and Genomes). Gene co-expression networks were constructed from transcriptomic data and five physiological parameters using WGCNA. DEGs were clustered into color-coded modules according to expression profile similarities. Module-trait relationships were established through correlation analysis, and drought-responsive DEGs were subsequently subjected to functional annotation via KEGG enrichment analyses.

Statistics analysis

Statistical analyses were conducted to evaluate genotype- and treatment-specific variations using one-way ANOVA with Tukey’s post hoc test (significance threshold: P < 0.05). The graphs were generated using Graphpad Prism 11.0. Heat map analysis was generated by TBtools v2.056 [47]. All experiments were conducted with ≥ 3 biological replicates. Data represents mean values ± standard error (SE).

Results

XL22 has stronger drought tolerance than ZQ17

Drought severely limits crop yield. To explore the physiological and molecular mechanism of highland barley tolerance to drought stress, we selected seven representative highland barley varieties, i.e., DLH, XL22, ZQ16, ZQ17, ZQ18, ZQ20, and ZQ2000, and compared their drought tolerance using natural drought methods. The phenotype analysis results showed that Ganpi 6 and seven highland barley varieties exhibited obvious wilting under natural drought conditions, and their leaves turned yellow and white (Supplemental Fig. 1a). The RWC of DLH, Ganpi6, XL22, ZQ16, ZQ17, ZQ18, ZQ20, and ZQ2000 decreased by 50.3%, 53.6%, 30.2%, 52.5%, 50.2%, 34.4%, 58.1%, and 50.4%, respectively, under natural drought for 11 d (Supplemental Fig. 1b). The re-watering experiment further confirmed that XL22 had the lowest mortality rate (about 20.0%); comparatively, the mortality rate of Ganpi6, ZQ16, and ZQ17 reached 60.0%, 60.0%, and 55.0%, respectively (Supplemental Fig. 1c). Based on the above results, XL22 and ZQ17 were selected as drought tolerant and sensitive varieties, respectively, for subsequent experimental materials.

To further investigate the difference in drought tolerance between the barley varieties XL22 and ZQ17, plants were subjected to natural drought for 12 d and followed by 3 days of re-watering. The phenotypic results showed that ZQ17 suffered severe damage compared with XL22 after natural drought for 12 d, i.e., yellow leaves and wilting shoots (Fig. 1A). Shoot RWC was markedly decreased from the sixth day (16.3% soil RWC) in ZQ17 and eighth day (13.9% soil RWC) in XL22 under natural drought conditions (Fig. 1B, C). After re-watering, the survival rate of XL22 (79.65%) was significantly higher than that of ZQ17 (28.85%; Fig. 1D). Thermal imaging results showed that the leaf temperature of XL22 was significantly lower than that of ZQ17 (Fig. 1E). Overall, these results suggest that ZQ17 is more sensitive to drought stress than XL22.

Fig. 1.

Effects of natural drought on XL22 and ZQ17 seedlings. A Phenotypes of seedlings after natural drought and re-watering experiments, bar = 1 cm. B Soil water content. C Relative water content (RWC). D Survival rate. E Infrared thermal imaging. Seven-day-old highland barley seedlings were grown under normal or natural drought (water withhold) conditions for 12 d, and then, the seedlings were re-watered for 3 d. Different lowercase letters indicate significant difference at the P < 0.05 level

XL22 exhibits better growth than ZQ17 under drought stress

To further investigate the physiological and molecular mechanisms of drought tolerance in XL22, we simulated drought stress using 25% PEG6000 (PEG). PEG treatment severely inhibited the shoot and root growth of ZQ17 compared with that of XL22 at 48 h and 96 h (Fig. 2A). The shoot FW of ZQ17 was significantly decreased by 33.6% and 64.6% after PEG treatment for 48 h and 96 h, respectively. Comparatively, it was only decreased by 26.2% and 49.7% in XL22 (Fig. 2B). Similarly, the shoot DW was decreased by 29.5% and 34.9% in ZQ17 and by 25.6% and 20.4% in XL22 after PEG treatment for 48 h and 96 h, respectively (Fig. 2C). These results indicate that drought stress significantly decreased the shoot biomass of XL22 and ZQ17, but there was no significant difference between them under PEG treatment for 96 h. A developed root structure and a high root to shoot ratio can enhance plant tolerance to drought stress by increasing water uptake capacity and reducing shoot transpiration [48]. After PEG treatment for 48 h, there was no significant difference in root FW between ZQ17 and XL22. However, at 96 h, the root FW and DW in XL22 were 27.6% and 2.6% higher than those in ZQ17, respectively (Fig. 2D, E). Under PEG treatment for 96 h, the ratio of root to shoot (R/S ratio) of XL22 was 58.9% and that of ZQ17 was only 41.4% (Fig. 2F). The RWC in XL22 was also significantly higher than that in ZQ17 (Fig. 2G). In addition, drought stress significantly inhibited lateral root development. However, the numbers of lateral roots and lateral root primordia (LRP) in ZQ17 were significantly lower than those in XL22 under drought conditions, with reductions of 56.2% and 43.3% in XL22 and 75.1% and 56.1% in ZQ17, respectively (Fig. 2H-J). The above results indicate that XL22 exhibits stronger drought tolerance by maintaining higher R/S ratio, RWC, and lateral root development stability.

Fig. 2.

Analysis of growth parameters in XL22 and ZQ17 seedlings under 25% PEG treatment. A Phenotypes of seedlings, bar = 1 cm. B Shoot fresh weight (FW). C Shoot dry weight (DW). D Root FW. E Root DW. F Root/Shoot (R/S). G Relative water content (RWC). H Developmental phenotypes of roots and lateral root primordium under 25% PEG treatment for 96 h, bar = 1 cm. I, J Quantification of numbers of lateral roots (I) and lateral root primordium (J) in H. Three-day-old barley seedlings were treated with 1/4 Hoagland solution containing 25% PEG6000 for 48 h and 96 h. Different lowercase letters indicate significant difference at the P < 0.05 level

XL22 has superior photosynthetic performance compared with ZQ17 under drought stress

To study the mechanism of XL22 tolerance to drought stress, we examined leaf area, Chl content, and photosynthetic parameters under 25% PEG treatment. PEG treatment significantly inhibited leaf growth (Fig. 3A). After 48 h and 96 h of PEG treatment, the leaf area in ZQ17 decreased by 52.3% and 72.3%, respectively, and by 51.4% and 63.7% in XL22, respectively, compared to the CK (Fig. 3B). At 96 h, the total Chl content declined by 58.5% in ZQ17 and 49.2% in XL22 (Fig. 3C). Notably, drought severely suppressed Pn in ZQ17 (77.63% and 92.2% reduction at 48 h and 96 h, respectively) and in XL22 (by 36.72% and 68.48%, respectively), while Tr decreased and Ci increased in both XL22 and ZQ17 (Fig. 3D-F). Photosynthetic electron transfer was significantly impaired under drought stress. After 48 h and 96 h of PEG treatment, ZQ17 exhibited significantly reduced ETR values (by 38.8% and 55.1%, respectively; Fig. 3G) and Fv/Fm values (by 2.2% and 2.3%, respectively; Fig. 3H) compared to XL22. Conversely, NPQ in ZQ17 increased by 19.5% and 35.2% at 48 h and 96 h, respectively compared with that in XL22 (Fig. 3I).

Fig. 3.

Analysis of photosynthetic parameters of XL22 and ZQ17 seedlings under PEG treatment. A Leaf phenotypes, bar = 1 cm. B Leaf area. C Chlorophyll (Chl) content. D Net photosynthetic rate (Pn). E Transpiration rate (Tr). F Intercellular CO2 concentration (Ci). G Electron transport rate (ETR). H Maximum photochemical quantum efficiency of PSII (Fv/Fm). I Non-photochemical quenching coefficient (NPQ). J Blue-green stained native gel image. 1: PSI; 2: PSII; 3: the degraded PSII (lacking CP43); 4: LHCII trimer. Three-day-old barley seedlings were treated with 1/4 Hoagland solution containing 25% PEG6000 for 48 h and 96 h. Different lowercase letters indicate significant difference at the P < 0.05 level

The decrease in the photosynthetic parameters might be closely related to the instability of thylakoid membrane protein complexes. Under drought stress for 48 h, there were no significant differences in the thylakoid membrane protein complexes compared to the control in both XL22 and ZQ17 (Fig. 3J). However, after drought stress for 96 h, the contents of PSI monomers, PSII monomers and LCHII trimers were significantly decreased in ZQ17 compared to the control, but there was no significant change in XL22 (Fig. 3J). Overall, these results indicate that XL22 exhibits a stronger ability to maintain the stability of photosynthetic system under drought stress.

Effects of drought stress on leaf damage and stomatal characteristics

To study the effects of drought stress on leaves of the two barley varieties, ultrastructural observations were conducted. Results in Fig. 4A showed that leaf cells of the two highland barleys exhibited structural integrity and tight arrangement under control conditions. After 96 h of PEG treatment, compared with XL22, the leaf epidermal cells of ZQ17 showed significant shrinkage and disordered arrangement. Statistical results showed that the cell damage rate in ZQ17 was significantly higher than that in XL22 by 49.5% (Fig. 4B). In addition, under drought stress, the stomatal aperture decreased by 23.3% in XL22 and by 10.9% in ZQ17 (Fig. 4C). Drought stress significantly increased EL and MDA content in ZQ17 and XL22 leaves. However, the EL and MDA were increased by 2.3-fold and 0.6-fold in XL22 and by 2.7-fold and 1.2-fold in ZQ17, respectively (Fig. 4D, E). These results indicate that XL22 exhibits better drought tolerance than ZQ17 by maintaining cell structural stability, reducing stomatal aperture, and enhancing cell membrane integrity.

Fig. 4.

Effects of drought on leaf epidermal cells in XL22 and ZQ17. A Leaf epidermal cell morphology, bar = 50 μm. B The rate of injured epidermal cells (%). C Stomatal aperture. D Electrical conductivity (EL). E MDA content in shoots. Three-day-old barley seedlings were treated with 1/4 Hoagland solution containing 25% PEG6000 for 96 h. Different lowercase letters indicate significant difference at the P < 0.05 level

XL22 shows greater drought tolerance via enhanced ROS scavenging and antioxidant accumulation than ZQ17

Excessive accumulation of ROS induced by drought stress can impair plant growth [49]. To compare ROS levels between XL22 and ZQ17 under drought, H₂O₂ and O₂^·− were analyzed using DAB and NBT staining, respectively. The staining results revealed that drought stress significantly increased the H₂O₂ and O₂·⁻ levels in both root tips and leaves compared to the control (Fig. 5A-D). Notably, under PEG treatment, XL22 accumulated significantly less H₂O₂ and O₂·⁻ than ZQ17 did. Quantitative analysis showed that in leaves, H₂O₂ and O₂·⁻ levels in XL22 were 20.2% and 11.2% lower than those in ZQ17, respectively. Similarly, in root tips, the reductions were more pronounced, with XL22 exhibiting 59.0% and 27.2% lower in H₂O₂ and O₂·⁻ levels compared with ZQ17 (Fig. 5E, F). Additionally, H₂DCF fluorescence staining was further used to assess the H₂O₂ content in chloroplasts under drought stress. Under normal conditions, H₂O₂ accumulation in chloroplasts was nearly undetectable (Fig. 5G). However, drought stress induced significant H₂O₂ accumulation, particularly in ZQ17. These findings demonstrate that ZQ17 suffers more oxidative damage than XL22 does under drought stress.

Fig. 5.

The content and distribution of ROS (H2O2, O2.-) in XL22 and ZQ17 leaves under drought stress. A DAB staining analysis of H2O2 content in leaves (a) and roots (b). B NBT staining analysis of O2.- content in leaves (c) and roots (d). Bar = 20 mm. C, D The H2O2 (C) and O2.- (D) content in leaves and roots. E The analysis of H2O2 content and distribution with H2DCF-DA fluorescence staining in XL22 and ZQ17 leaves. I: H2DCF-DA fluorescence, bar = 100 μm. II: Chloroplast spontaneous fluorescence, bar = 100 μm. III: Bright field, bar = 100 μm. IV: Green and red merged field, bar = 100 μm. V: Merged field, bar= 500 μm. Three-day-old barley seedlings were treated with 1/4 Hoagland solution containing 25% PEG6000 for 96 h. Different lowercase letters indicate significant difference at the P < 0.05 level

To elucidate the antioxidant capability in XL22 and ZQ17 seedlings under drought stress, we measured the antioxidant enzymatic activities involved in the key ROS scavenging systems. Under control conditions, SOD, POD, CAT, and APX activities were low, with no significant differences between XL22 and ZQ17 leaves (Fig. 6A-D). However, following 96 h of PEG treatment, all the enzymatic activities were significantly increased, though their levels in XL22 remained markedly lower than those in ZQ17. Specifically, SOD, POD, CAT, and APX activities in XL22 were 24.5%, 18.7%, 32.6%, and 26.0% lower than those in ZQ17, respectively. GR and GPX, which utilize reduced GSH-derived reducing power for ROS detoxification [50], also showed elevated activities under drought stress. In both cultivars, GR and GPX activities increased significantly by 60.7% and 56.4%, respectively, in XL22 and by 67.4% and 26.9%, respectively, in ZQ17, compared to the control (Fig. 6E, F). To assess non-enzymatic ROS scavenging system, GSH and AsA contents were analyzed. Figure 6G, H showed that drought stress induced substantial accumulation of both compounds in XL22 and ZQ17, with XL22 exhibiting 44.2% higher GSH and 28.9% higher AsA levels than ZQ17.

Fig. 6.

Changes of antioxidant enzyme activities and antioxidant contents in XL22 and ZQ17 leaves under drought stress. A SOD activity. B POD activity. C CAT activity. D APX activity. E GR activity. F GPX activity. G GSH content. H AsA content. Three-day-old barley seedlings were treated with 1/4 Hoagland solution containing 25% PEG6000 for 96 h. Different lowercase letters indicate significant difference at the P < 0.05 level

DEGs involved in highland barley tolerance to drought stress

To further investigate the molecular mechanism of highland barley response to drought stress, RNA-seq technology was applied. The results showed that there were 1871 up-regulated and 1554 down-regulated genes in XL22 leaves under drought stress, and 2933 up-regulated and 2303 down-regulated genes in ZQ17 leaves (Fig. 7A). qRT-PCR results were consistent with gene expression patterns revealed by RNA seq (Fig. 7B). To identify active biological pathways enriched with DEGs in XL22-CK vs. XL 22-D and ZQ17-CK vs. ZQ17-D, KEGG analysis was performed. Results of the top 20 pathways were shown in Fig. 7C, D. Results showed that DEGs only in XL22 (3425 genes) were mainly involved in plant-pathogen interaction, plant hormone signaling transduction, and MAPK signaling pathway. DEGs only in ZQ17 (5236 genes) were mainly enriched in ribosome, phenylpropanoid biosynthesis and starch and sucrose metabolism (Fig. 7C, D).

Fig. 7.

Transcriptomic analysis of DEGs in XL22 and ZQ17 leaves under drought stress. A Venn diagrams of DEGs in XL22 and ZQ17. B qRT-PCR verification of six target genes: GL1-6 (Glossy1-homologous gene), bHLH70 (Basic Helix-Loop-Helix 70), PYL4 (Pyrabactin resistance 1-like 4), GATA2 (GATA binding protein 2), WSD1 (Wax ester synthase/diacylglycerol O-acyltransferase 1) and SCL1 (SCARECROW-like 1), with HvACTIN (MK034133) as the internal reference. C KEGG enrichment map of DEGs in XL22. D KEGG enrichment map of DEGs in ZQ17. RNA sequencing was performed on shoot tissues harvested from 3-day-old barley seedlings treated with 1/4 Hoagland solution containing 25% PEG6000 for 96 h. HvACTIN was used to normalize relative expression levels. E DEGs involved in plant hormone regulation. F DEGs involved in antioxidant stress. G DEGs involved in water stress responses. Three-day-old barley seedlings were treated with 1/4 Hoagland solution containing 25% PEG6000 for 96 h. The leaves were used for RNA-Seq analysis

To understand the roles of plant hormones in the response of highland barley to drought stress, we analyzed the DEGs involved in plant hormone signaling pathways. Results in Fig. 7E and Supplemental Table 2 showed that plant hormone metabolism-related DEGs were involved in the biosynthesis/degradation of indole-3-acetic acid (IAA), abscisic acid (ABA), cytokinin (CTK), brassinosteroids (BR) and gibberellin (GA). Notably, transcriptions of early auxin-regulated genes, such as GH3.1 (HORVU.MOREX.r2.1HG0054200), GH3.8 (HORVU.MOREX.r2.2HG0106420) and GH3.11 (HORVU.MOREX.r2.2HG0093610), were up-regulated only in XL22. SAURs, auxin-responsive genes, are involved in auxin signal transduction [51]. Under drought stress, SAUR21 (HORVU.MOREX.r2.2HG0167390), SAUR38 (HORVU.MOREX.r2.2HG0108660), and SAUR41 (HORVU.MOREX.r2.2HG0157620) were up-regulated in ZQ17 and XL22; in contrast, SAUR32 (HORVU.MOREX.r2.2HG0167370), SAUR32-Like (HORVU.MOREX.r2.2HG0167380) and SAUR36 (HORVU.MOREX.r2.2HG0152760) were down-regulated in ZQ17 and XL22. In addition, NCED9 (HORVU.MOREX.r2.5HG0421990), which encodes a key enzyme in ABA biosynthesis, was significantly up-regulated in XL22 and ZQ17. CTK regulates cell division and development and plays crucial roles in plant growth and development [52]. Genes that participate in the CTK biosynthetic process (IPT3, HORVU.MOREX.r2.3HG0201810) were strongly up-regulated in XL22, but showed no significant increase or were even repressed in ZQ17. Meanwhile, CKX1 (HORVU.MOREX.r2.3HG0196660) and CKX3 (HORVU.MOREX.r2.7HG0620270), which catalyze the degradation of CTK, were up-regulated in ZQ17, but suppressed in XL22. Additionally, GID1 (HORVU.MOREX.r2.1HG0051770) in the GA signaling pathway and BSK1/BZR1 (HORVU.MOREX.r2.5HG00381560) in the BR signaling pathway were up-regulated only in XL22.

Transcriptomic analysis showed that the antioxidant pathways were also modulated under drought stress. We identified 27 DEGs related to various antioxidases and antioxidants, including genes encoding GR (4 DEGs), glutathione S-transferases (GST; 12 DEGs), APX (4 DEGs), POD (4 DEGs), and SOD (3 DEGs) (Fig. 7F and Supplemental Table 2). Of these, 9 GST genes and 2 GR genes were up-regulated in XL22 under drought stress, and some GST genes were down-regulated in ZQ17. Furthermore, three SOD genes (HORVU.MOREX.r2.2HG0094720, HORVU.MOREX.r2.2HG0154740, HORVU.MOREX.r2.2HG0173140 ), four POD genes (HORVU.MOREX.r2.1HG0013370, HORVU.MOREX.r2.1HG0013460, HORVU.MOREX.r2.1HG0013490, HORVU.MOREX.r2.2HG0088590) and one APX gene (HORVU.MOREX.r2.2HG0085360) were up-regulated in XL22 under drought stress. These results showed that the genes involved in antioxidant pathways are activated by drought stress in highland barley, especially in XL22.

Finally, we also examined several functional genes involved in drought stress responses, such as late embryogenesis abundant proteins (LEA), aquaporins, and heat shock proteins (HSPs), which play crucial protective roles in plant tolerance to drought stress [53, 54]. The expressions of DEGs in LEA (8 members), HSP (5 members), and aquaporin (4 members) families were higher in XL22 than those in ZQ17 under drought stress (Fig. 7G and Supplemental Table 2), indicating that enrichment of these genes in XL22 might increase the water retention capacity.

Identification and analysis of TFs involved in drought stress

TFs serve as critical regulators of plant growth and development, orchestrating transcriptional activation or suppression of stress-responsive genes to ensure physiological homeostasis under stress [55]. As shown in Fig. 8A, after drought stress, the top three TF families showing significant enrichment in XL22 were identified as AP2/ERF (37 members), bHLH (22 members), and MYB (20 members). In ZQ17, the top three enriched TF families were identified as AP2/ERF (26 members), MYB (21 members), and bHLH (21 members; Fig. 8B). Among them, there were 8, 5, 1, 7, 9, 4 and 4 DEGs in MYB, bHLH, bZIP, C2H2, AP2/ERF, WRKY and NAC families, respectively (Fig. 8C). Compared with ZQ17, the up-regulated DEGs in XL22 were AP2/ERF (HORVU.MOREX.r2.6HG0498060, HORVU.MOREX.r2.2HG0157200, HORVU.MOREX.r2.6HG0498080), bHLH (HORVU.MOREX.r2.4HG6343750, HORVU.MOREX.r2.5HG6377110), C2H2 (HORVU.MOREX.r2.4HG0346770, HORVU.MOREX.r2.1HG0046260), WRKY (HORVU.MOREX.r2.6HG0614712, Hordeum_vulgare_newGene_2310) and NAC (Hordeum_vulgare_newGene_4791). Taken together, the drought response in XL22 leaves was positively regulated by multiple metabolic pathways and a number of TFs.

Fig. 8.

Transcription factors (TFs) analysis of DEGs in XL22 and ZQ17. A TFs of DEGs in XL22. B TFs of DEGs in ZQ17. Red dots represent top three TFs with the highest number, and red boxes represent species-specific TFs in the top three. C Clustering analysis of TFs in XL22 and ZQ17. Three-day-old barley seedlings were treated with 1/4 Hoagland solution containing 25% PEG6000 for 96 h. The leaves were used for RNA-Seq analysis

WGCNA of DEGs in highland barley under drought stress

To explore the core pathways and genes involved in highland barley response to drought stress, DEGs were analyzed through WGCNA. After optimization and cutting of the imported genes, a total of eight co-expressed modules were obtained, namely, MEpink (891 DEGs), MEturquoise (1312 DEGs), MEgreenyellow (1501 DEGs), MEblue (1230 DEGs), MEgreen (494 DEGs), MEblack (1706 DEGs), MEpurple (1087 DEGs), and MEgrey (102 DEGs; Fig. 9A, B). The gene expression trends for the blue module were shown in Fig. 9C. Further analysis revealed that the blue module (R ≥ 0.5, P < 0.05) was highly positively correlated with RWC (R = 0.76, P = 0.004), Pn (R = 0.91, P = 3 × 10^− 5) and GS (R = 0.93, P = 1 × 10^− 5). According to the K-means clustering algorithm, the core 150 DEGs in MEblue module were selected as the candidate hub genes for KEGG analysis. Figure 9D showed that the core DEGs were mainly enriched in plant hormone signal transduction, carbon metabolism, biosynthesis of amino acids, and plant pathogen interaction. To identify the hub genes in the blue module, top 10 genes were selected for functional annotation based on the module membership coefficient (kME). A total of three genes encoding TFs were focused, including one bZIP (HORVU.MOREX.r2.5HG0434960), one AP2/ERF (HORVU.MOREX.r2.6HG0498080) and one bHLH (HORVU.MOREX.r2.1HG0041620). In addition, two genes related to plant hormones were identified in this module, including ABI4 (HORVU.MOREX.r2.3HG0246690) and PYL4 (HORVU.MOREX.r2.1HG0057870). In conclusion, WGCNA results suggest that XL22 responds to drought stress mainly through TFs and plant hormone signaling pathways.

Fig. 9.

WGCNA of drought-related DEGs in XL22 and ZQ17. A Cluster dendrograms of DEGs show different modules. B Module-sample relationship. The numbers represent correlations and P values. “1” and “-1” indicates positive and negative correlation, respectively. C Heatmaps of gene expression in the blue module. D KEGG enrichment analysis of the core 150 DEGs in the blue module in (B). Three-day-old barley seedlings were treated with 1/4 Hoagland solution containing 25% PEG6000 for 96 h. The leaves were used for RNA-Seq analysis

Discussion

Drought significantly inhibits plant growth and development [1, 2]. Plants have developed complex adaptive mechanisms involving physiological, biochemical, cellular, and molecular processes to cope with drought stress [56]. However, the key molecular mechanisms governing drought tolerance remain elusive in plants. Therefore, we systematically investigated the physiological and molecular basis of drought tolerance in highland barley by integrating physiological and transcriptomic analyses.

XL22 has enhanced drought adaptation by maintaining water balance and cell membrane integrity

Drought severely limits the organogenesis of roots, stems and leaves in plants, resulting in reduced biomass and yield [57]. In this study, drought-tolerant (XL22) and drought-sensitive (ZQ17) barley varieties exhibited significant reductions in shoot and root biomass under water deficit conditions. However, compared to ZQ17, the biomass reduction in XL22 was significantly less pronounced (Fig. 2A-E), indicating an enhanced ability to retain dry matter under water deficient conditions. Comparative analysis revealed distinct physiological adaptations between XL22 and ZQ17 under drought conditions. XL22 maintained significantly higher leaf RWC than ZQ17 did (Figs. 1C and 2G), demonstrating superior water retention capacity - a critical trait of drought-tolerant cultivars [58]. This enhanced water retention capacity might help maintain cellular homeostasis and reduce oxidative damage. Membrane stability is another key indicator reflecting drought tolerance of plants [59]. Under drought stress, the EL in XL22 was lower, indicating that its membrane integrity was higher than that in ZQ17 (Fig. 4D). In addition, XL22 showed a significant decrease in the MDA content compared with ZQ17 (Fig. 4E, F), indicating a reduction in membrane lipid peroxidation under drought stress. Importantly, XL22 exhibited significantly less accumulation of ROS (H₂O₂ and O₂^·−) in both leaves and roots (Fig. 5A-D), indicating enhanced ROS scavenging capacity through potential up-regulation of antioxidant enzyme activities. Overall, XL22 has established a more stable cellular micro-environment by maintaining higher RWC, enhancing membrane structural stability, and reducing oxidative stress. These coordinated physiological adaptations may form a core foundation of the superior drought tolerance in XL22.

XL22 establishes drought tolerance by stabilizing photosynthetic structures and enhancing ROS scavenging systems

Drought stress significantly impairs photosynthetic performance and reduces organic matter accumulation in crops [60]. Our findings demonstrate cultivar-dependent variation in photosynthetic responses to water deficit in highland barley, with the drought-tolerant genotype XL22 maintaining significantly higher Pn compared to the drought-sensitive variety ZQ17 (Fig. 3D). This photosynthetic advantage correlates with elevated Ci and Tr in XL22 (Fig. 3E, F), suggesting a more efficient ability to regulate stomata and leaf temperature. Chl fluorescence analysis revealed that XL22 preserves PSII functionality by maintaining higher Fv/Fm and activating greater NPQ (Fig. 3H, I), indicating improved capacity to dissipate excess energy excitation. These protective mechanisms collectively minimize photo-oxidative damage to PSII reaction centers, consistent with reports demonstrating that NPQ-mediated photoprotection enhances drought tolerance [61]. Importantly, analysis of thylakoid membrane protein complexes showed that XL22 exhibits significantly less degradation of PSI monomers, PSII monomers, and LHCII trimers under drought stress (Fig. 3J), suggesting enhanced structural integrity of the photosynthetic machinery [62].

Drought-induced stomatal closure inhibits CO₂ assimilation, impairing the Calvin cycle and leading to excess excitation energy accumulation in chloroplasts [63]. This imbalance between light absorption and carbon fixation intensifies photorespiratory flux and the production of ROS, particularly H₂O₂, resulting in oxidative damage [64]. Our results demonstrate significant genotypic variation in oxidative stress responses between drought-treated highland barley cultivars. Consistent with its drought sensitivity, ZQ17 exhibited substantially stronger H₂O₂-specific fluorescence staining (Fig. 5G), confirming greater ROS accumulation in chloroplasts compared to XL22. Notably, this observation correlates with elevated NPQ in ZQ17 (Fig. 3I), suggesting insufficient dissipation of excess excitation energy despite heightened thermal dissipation mechanisms. Furthermore, XL22 effectively attenuates oxidative damage by enhancing enzymatic and non-enzymatic antioxidant defenses. Specifically, GR and GPX activities were significantly upregulated in XL22 (Fig. 6E, F), facilitating rapid H₂O₂ scavenging through GSH-dependent pathways [65]. High GR activity can effectively catalyze the reduction of GSSG to GSH, thereby maintaining the AsA-GSH cycling rate and continuously scavenging H₂O₂ [66]. In contrast, ZQ17 primarily relies on elevated activities of SOD, POD, CAT and APX (Fig. 6A-D), suggesting that its antioxidant system might be inefficient or unsustainable under drought stress. Collectively, these findings highlight that drought tolerance in XL22 is associated with a more efficient and integrated antioxidant defense system, limiting photooxidative damage while maintaining photosynthetic function under water deficit.

Plant hormones and TFs play key regulatory roles in highland barley response to drought stress

Under drought stress, integration of TFs and phytohormones forms coordinated regulatory networks that can precisely modulate gene expressions and physiological processes in plant response to abiotic stresses [55]. The profiles of significantly enriched DEGs in both drought-treated ZQ17 and XL22 indicate the critical roles of proteins involved in plant hormone metabolism and TFs (Figs. 7 and 8). This study confirms previous research that signals mediated by plant hormones and TF play a crucial role in regulating plant growth and stress response [67].

ABA is commonly considered a stress hormone as it participates in various responses to abiotic stresses [68]. Under drought stress, the biosynthesis of ABA, mediated by the 9-cis-epoxycarotenoid dioxygenase (NCED) gene family, activates signal transduction pathways involving drought-responsive components such as PYL, PP2C, SnRK, and ABF, ultimately inducing stomatal closure [69]. In the current study, NCED3 (HORVU.MOREX.r2.5HG0421990), encoding a key enzyme for ABA biosynthesis, and PYL4 (HORVU.MOREX.r2.1HG0057870), an ABA receptor, were significantly up-regulated in XL22 (Fig. 7E). This suggests that XL22 may enhance ABA biosynthesis and regulate the ABA signaling pathway in response to drought. Similar activation of ABA-related genes has been reported in barely exposed to drought, supporting the central role of ABA in water-deficit adaptation [70]. However, the stronger induction of ABA biosynthesis and receptor components in XL22 suggests that this genotype may possess a more responsive or tightly regulated ABA module compared with previously characterized barley materials. Meanwhile, many studies have demonstrated that auxin signaling pathway not only promotes plant growth and development but also takes part in regulating plant response to drought stress [71]. Luo et al. [72] revealed that auxin triggers rapid and specific expressions of early responsive genes, including Aux/IAA (Auxin/indole-3-acetic acid), GH3 (Gretchen Hagen 3), and SAURs (Small Auxin Up RNAs) families, thereby enhancing plant drought tolerance. Under drought stress, the GH3 gene is rapidly activated and expressed, thereby regulating plant hormone and stress-related signaling pathways to maintain hormone homeostasis [73]. In our study, three GH3 genes were only up-regulated in XL22, indicating that GH3 may be involved in drought adaptation ability in XL22 by coordinating hormone homeostasis.

TFs play key roles in modulating plant growth and drought tolerance by regulating the expressions of various stress-responsive genes [74]. In the present study, a large number of TFs were identified, including AP2/ER, bZIP, bHLH, MYB, WRKY and NAC (Fig. 8), which could be involved in various physiological processes, such as ROS scavenging and hormone signaling transduction [75]. The functions of TFs in plant tolerance toward various abiotic stresses in crops have been well elucidated. Overexpression of OsERF115/AP2EREBP110 significantly enhances drought tolerance in rice, providing genetic insights for the development of drought tolerant varieties [76]. Similarly, in maize, ZmbZIP4 enhances drought resilience through coordinated regulation of ABA biosynthesis and root system architecture [77]. Likewise, overexpression of SlbHLH96 in tomato exhibits strengthened drought tolerance by up-regulating the expression of genes related to antioxidants and ABA signaling pathways [78]. In barley, members of the bZIP, AP2/ERF, and NAC families have also been linked to drought and osmotic stress responses, but the core transcriptional modules underlying genotype - specific tolerance are still being identified [79, 80]. In our study, one bZIP (HORVU.MOREX.r2.5HG0434960), one AP2/ERF (HORVU.MOREX.r2.6HG0498080) and one bHLH (HORVU.MOREX.r2.1HG0041620) are co-expressed and identified in the MEblue module through WGCNA analysis. Intriguingly, these TFs are only continuously up-regulated in XL22, indicating that they may act as positive regulatory factors, mediating high tolerance of XL22 to drought stress. Taken together, by integrating the complex network from hormone signals and transcriptional regulation to physiological adaptation, the differential expressions of the above genes ultimately lead to higher drought tolerance in XL22 compared with ZQ17.

Conclusion

This study elucidates the physiological and molecular mechanisms underlying drought tolerance in highland barley by comparing the tolerant line (XL22) and sensitive line (ZQ17). Under drought stress, XL22 better preserved the stability of photosynthetic complexes, including PSI, PSII, and LHCII, and showed stronger ROS detoxification capacity supported by the antioxidant system involving GR, GPX, GSH, and AsA. RNA-seq analysis combined with WGCNA further revealed that bZIP, AP2/ERF, and bHLH TFs, together with ABA signal, constitute core regulatory networks in XL22. These networks coordinate the expressions of stress responsive genes associated with osmotic adjustment, cellular protection, and resource allocation, thereby maintaining cellular homeostasis and photosynthetic performance. Overall, these findings provide new insights into the drought - adaptive network of highland barley and establish a valuable foundation for the identification and breeding of drought - tolerant germplasm.

Authors’ contributions

Yurong Bi and Xiaomin wang designed research; Ruiling Li, fangzheng Jing, Xiaoli Ma, Hao Sun, Jie Chen, Yunchuan Zhang performed experiments; Meijin Liu provided experimental materials, Juan Qin, Ruiling Li, Xiaomin Wang analyzed data; Juan Qin and Xiaomin Wang wrote the manuscript.

Funding

This work was supported by the National Natural Science Foundation of China (32560775), the Open Project of State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University (2022-KF-01); Innovation driven assistance for engineering projects (KPZX-010722); the Foundation of Science and Technology Program of Lanzhou City (2025-2-73).

Data availability

The RNA-seq data reported in this paper have been deposited in National Genomics Data Center, China National Center for Bioinformation / Beijing Institute of Genomics, Chinese Academy of Sciences (GSA: CRA036097) that are publicly accessible at https://ngdc.cncb.ac.cn/gsa/s/2bQ5iy19.

Declarations

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Competing interests

The authors declare no competing interests.