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Article

Physiological and Transcriptome Analysis of Drought-Tolerant Mutant ds-1 of Blue Fescue (Festuca glauca) Under Drought Stress

by
Yong Zhang
1,†,
Peng Han
2,†,
Xuefeng Xiao
3,
Wei Chen
4,
Hang Liu
1,
Hengfeng Zhang
1 and
Lu Xu
1,*
1
School of Landscape Architecture and Horticulture, Jiangsu Agri-Animal Husbandry Vocational College, Taizhou 225300, China
2
College of Agro-Grassland Science, Nanjing Agricultural University, Nanjing 210095, China
3
College of Education and Humanities, Suzhou Polytechnic University, Suzhou 215104, China
4
College of Landscape Architecture, Jiangsu Vocational College of Agriculture and Forestry, Jurong 212400, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Int. J. Plant Biol. 2025, 16(4), 116; https://doi.org/10.3390/ijpb16040116 (registering DOI)
Submission received: 23 August 2025 / Revised: 25 September 2025 / Accepted: 29 September 2025 / Published: 4 October 2025
(This article belongs to the Topic Tolerance to Drought and Salt Stress in Plants, 2nd volume)
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Abstract

Blue fescue (Festuca glauca) is a widely used ornamental grass worldwide. Drought is an important limiting factor for the growth and development of blue fescue; therefore, cultivating new strains of blue fescue with a strong drought tolerance is of great significance for its production practice. To investigate the drought tolerance mechanism of ds-1, this study subjected both ds-1 and “Festina” to a natural drought treatment and measured their physiological and biochemical indicators. A transcriptomic analysis was also conducted to explore the underlying molecular mechanisms. The results showed that, after the drought treatment, the relative water content (RWC), water use efficiency (WUE), and photosynthetic rate (Pn) of ds-1 leaves were significantly higher than those of “Festina”; in addition, the contents of H2O2 and O2−, the relative electrical conductivity (REC), the malondialdehyde (MDA) content, the gas conductance (Gs), and the transpiration rate (Tr) were significantly lower than those of “Festina”. The peroxidase (POD) activity of ds-1 was significantly higher than that of “Festina”, while the superoxide dismutase (SOD) activity of ds-1 was significantly lower than that of “Festina”. The transcriptome data analysis showed that there were a total of 9475 differentially expressed genes (DEGs) between ds-1 and “Festina”. A Venn plot analysis showed 692 DEGs between ds-1—8d vs. “Festina”—8d and ds-1—16d vs. “Festina”—16d. A KEGG enrichment analysis showed that these 692 genes were mainly enriched in 86 pathways, including those related to the photosynthesis antenna protein, plant hormone signal transduction, MAPK signaling, starch and sucrose metabolism, and arginine and proline metabolism. Further screening identified genes that may be associated with drought stress, including PYL, PP2C, SnRK2, ABF, BRI1, JAZ, MYC2, Lhc, and MPK6. The qRT-PCR results indicated that the expression trends of the DEGs were consistent with the transcriptome sequencing results. Our research results can provide a basis for exploring candidate genes for drought tolerance in blue fescue. In addition, our research results provide valuable genetic resources for the development of drought-resistant ornamental grass varieties, which can help reduce water consumption in cities and decrease labor and capital investment.

1. Introduction

Blue fescue (Festuca glauca) is a cold-season ornamental grass mainly used for flower bed arrangements and road greening [1]. Blue fescue has a beautiful plant shape and blue leaves, and it has a high ornamental value. Therefore, it is widely used in countries such as the United States, the United Kingdom, and China [2]. In order to maintain the optimal plant morphology of blue fescue, irrigation is the main factor that must be maintained during its growth process, as this plant requires a large amount of water [3]. The application of exogenous substances such as paclobutrazol, chlormequat chloride, and melatonin is an important way to enhance plant drought tolerance [4]. The ways in which different exogenous substances alleviate plant drought stress are different. However, they all alleviate the damage of drought stress to plants by promoting the plant’s antioxidant defense system to clear reactive oxygen species, increasing the plant cell water absorption capacity, and maintaining membrane stability [5,6]. In addition to using exogenous growth substances, cultivating drought-tolerant blue fescue varieties is an effective way to improve the ability of blue fescue to cope with drought stress.
Drought is the most common type of abiotic stress and has a significant impact on plant growth and crop yield [7]. Drought stress has a series of effects on the morphology, physiology, and molecular processes of plants [8]. The response of plants to drought stress is regulated by multiple factors, including osmotic adjustments, environmental signals, photosynthesis, hormone regulation, the CO2 concentration, and respiration [9]. Under drought stress, the content of proline, soluble sugar, and soluble protein in plants will increase [10]. At the same time, drought will cause the stomata of plant leaves to close, affecting the absorption of CO2 during photosynthesis and leading to a decrease in the leaf photosynthetic rate and a reduction in the accumulation of photosynthetic products [11]. Drought stress also activates several signaling pathways to cope with the adverse effects of stress, such as the MAPK cascade, the Ca2+ signaling pathway, and the phytohormone signaling pathway [12,13,14]. Many drought stress response proteins have also been discovered, such as the drought response protein (RD22) and the late-embryogenesis abundant protein (LEA), which enhance the water-binding capacity of cells under drought stress [15,16]. Some transcription factors have been proven to be related to drought tolerance in plants, such as AREB/ABFs, DREBs, AP2/ERF, NAC, WRKY, and MYB [17,18]. AREB/ABFs are key transcription factors in the ABA signaling pathway that can bind to ABA response elements and activate the expression of downstream genes. Research has shown that AREB1, AREB2, and ABF3 are phosphorylated and activated under drought stress, thereby regulating the expression of various drought-responsive genes [19]. OsNAC17 positively regulates lignin synthesis genes, promoting lignin accumulation in the leaves and roots. Transgenic plants overexpressing OsNAC17 exhibit drought resistance, while transgenic plants with a knockout of OsNAC17 exhibit a drought-sensitive phenotype [20].
In recent years, with the rapid development of multi-omics technologies, omics techniques such as transcriptomics, metabolomics, and proteomics have been widely applied in the molecular mechanism research of plant responses to drought stress [21]. Among them, transcriptomics has become an indispensable and powerful tool for studying the response mechanisms of plants to drought stress. Researchers have utilized transcriptomics to investigate the molecular mechanisms by which plants such as potatoes [22] soybeans [23], sorghum [24], and maize [25] respond to drought stress, and they have identified a large number of differentially expressed genes. These studies have deepened our understanding of how plants respond to drought stress at the molecular level and provide a theoretical basis and potential targets for improving crop drought resistance through molecular breeding techniques. In the related research of blue fescue, transcriptomics technology has also been applied to study its dwarfing mechanism [3].
Currently, there are no reports on the drought tolerance of blue fescue, which is crucial for its promotion and application in cities. In previous studies, we irradiated “Festina” callus tissue with 60Co-γ rays and screened drought-tolerant strains using PEG6000, ultimately obtaining a series of blue fescue mutant strains with an improved drought tolerance (method for creating new drought-tolerant lines of blue fescue through mutation induction using 60Co-γ radiation, Patent No.: 202411694238.9). Among them, ds-1 exhibits the strongest drought tolerance, making it valuable for further investigation into its drought tolerance mechanism. In this study, we identified the physiological characteristics of “Festina” and its mutant ds-1 and utilized RNA-seq to investigate the transcriptome profiles of “Festina” and ds-1, screening for drought-tolerant candidate genes. Based on physiological and transcriptome data, we speculate that the enhanced drought resistance of ds-1 is attributable to the expression of genes related to photosynthetic antenna proteins, plant hormone signal transduction, the MAPK signaling pathway, and osmotic regulation. This study provides a theoretical basis for enhancing the drought tolerance of blue fescue.

2. Materials and Methods

2.1. Plant Material and Drought Treatment

The materials tested were the drought-tolerant ds-1 mutant of blue fescue and its wild type, “Festina”. ds-1 is a mutant derived from the callus tissue of “Festina” through mutation induction using 60Co-γ ray irradiation. After identification, ds-1 was found to have no phenotypic segregation in its offspring and was considered to be a stable strain. Both materials were provided by the Jiangsu Agri-Animal Husbandry Vocational College.
This study was conducted in the summer of 2024 in the intelligent greenhouse of the Jiangsu Agri-Animal Husbandry Vocational College. The growth conditions were set at a humidity of 55%, a temperature of 25 °C, and a photoperiod of 16 h/8 h (light/dark). We selected plants of a consistent size (plant height of 13 cm) and robust growth and transplanted them into flower pots (top diameter × bottom diameter × height = 10 cm × 10 cm × 10 cm) containing cultivation substrate (peat/perlite/vermiculite = 2:1:1). To reduce experimental error, we ensured that each pot contained the same mass of substrate, which was 1.5 kg. Subsequently, cultivation continued in the intelligent greenhouse, with water supplied every 2 days to ensure sufficient water during the growth period of the blue fescue. The amount of water added to each plant pot was 200 mL per time. After the 7th addition of water, the growth of the experimental materials had met the requirements of drought stress, so we stopped watering. At this point, the natural drought stress treatment began. During the drought treatment process, to ensure the consistency of the drought conditions, we replenished water through the weighing method. The soil relative moisture content at 0 days of the natural drought treatment was 75–80% of the field capacity; at 8 days of the natural drought treatment, it was 45–50% of the field capacity; and at 16 days of the natural drought treatment, it was 30–35% of the field capacity. At 0, 8, and 16 days after watering was ceased, blue fescue leaves were collected, rapidly frozen in liquid nitrogen, and stored in a −80 ° C refrigerator for physiological and biochemical analyses as well as a transcriptome analysis. Each treatment had three biological replicates, with six pots of plants per biological replicate. Six leaves were collected from each plant for indicator measurements.

2.2. Measurement of Physiological Indicators

The relative water content (RWC) was determined using Li Jingrui’s weighing method, with the calculation formula being RWC = (Wf − Wd)/(Wt − Wd) [26]. The relative conductivity (REC) was determined using Dou Lingling’s weighing method, with the calculation formula being REC = R1/R2 × 100% [27]. The relevant reagent kit of Beijing Solaibao Technology Co., Ltd. (Beijing, China) was used to determine the content of MDA (item number: BC6410), H2O2 (item number: BC3590), and O2− (item number: BC1290), as well as the activity of the SOD (item number: BC0170) and POD (item number: BC0090) enzymes. The photosynthetic parameters of the plants were measured using a Li-6400 photosynthesis meter (Li-COR, Lincoln, NM, USA) [28]. To minimize measurement errors, each measurement was conducted between 9:00 and 11:00 am. During the measurement, the leaf chamber temperature was set at 28 °C, the CO2 concentration at 400 μmol/(m2·s), the relative humidity at 55%, and the light intensity at 1500 μmol/(m2·s). The third to fifth fully functional leaves on the sunny side of the plant top were selected from each treatment group, marked, and used to measure the net photosynthetic rate (Pn), stomatal conductance (Gs), and transpiration rate (Tr) of the plant leaves. The water use efficiency (WUE) of the leaves was calculated using the formula WUE = Pn/Tr. Three plants were measured from each treatment group, and three mature and healthy leaves were measured from each plant, with the average values taken. Each physiological indicator included 3 biological replicates, and each biological replicate included 3 technical replicates.

2.3. Transcriptome Sequencing

A transcriptome analysis was conducted on the leaves of the two blue fescue varieties subjected to drought stress for 0 days (CK), 8 days, or 16 days. There were 3 biological replicates at each sampling time point of each treatment. Total RNA extraction from the leaves of the blue fescue plants was performed according to the instructions of the RNAprep Pure Plant Kit (Tiangen Biotech, Beijing, China). After extracting the sample RNA, the purity, concentration, and integrity of the RNA were determined using a Nanodrop spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) and Bioanalyzer 2100 (Agilent, Santa Clara, CA, USA). After the quality inspection of the RNA samples, cDNA library construction was carried out, and the size and concentration of the library were detected using Bioanalyzer 2100 (Agilent, Santa Clara, CA, USA). We utilized the Illumina HiSeqTM 2000 platform (Illumina, San Diego, CA, USA) to sequence the qualified cDNA library.
The sequencing depth of each sample in this transcriptome sequencing reached 5 Gb, with 150 bp double-ended sequencing. The raw data obtained from sequencing were evaluated for quality using the Fastp v0.20.1 software (HaploX, Shenzhen, China), and reads with a low quality, adapter contamination, or an unknown base N content greater than 5% were filtered out using the trimomatic v0.32 software (Wageningen UR, The Netherlands) [29]. Blue fescue lacks a reference genome, so we used non-parametric transcriptome sequencing for this transcriptome study. The transcriptome assembly of blue fescue was performed using the Trinity software, v2.15.1 (Broad Institute, Boston, MA, USA) [30]. Using the assembled transcript sequence as the reference transcript sequence, clean reads were aligned to the reference transcript sequence using bowtie2 [31]. The obtained unigenes were annotated using functional databases such as KEGG, GO, NR, NT, SwissProt, Pfam, and KOG to obtain their annotation information [32]. We used DESeq2 to screen and analyze differentially expressed genes (DEGs) between two samples, with a screening threshold of |log2Fold Change| ≥ 1 and FDR < 0.05 [33]. The DEGs were subjected to KEGG and GO enrichment analyses using the KOBAS software, version 2.0 (Peking University, Beijing, China), with p ≤ 0.05 as the criterion for determining significant enrichment in the KEGG pathways or GO functions [34].

2.4. qRT-PCR Verification of DEGs

Nine DEGs were selected for qRT-PCR verification. The RNA extraction and quality detection methods for leaf samples were the same as above. The primers for qRT-PCR were designed using the Primer 5.0 software; the β-actin gene was used as an internal reference gene [3]. The synthesis of the first strand of cDNA was carried out using the Prime script TM RT-PCR Kit (item number: RR014A, Takara, Beijing, China). qRT-PCR was performed using the SYBR Premix EX Taq (item number: DRR041A, Takara, Beijing, China). The relative expression level of the genes was calculated using the 2−△△CT method [35]. The reaction procedure was as follows: 1 cycle of 95 °C for 30 s; 40 cycles of denaturation at 95 °C for 5 s, annealing at 55 °C for 10 s, and extension at 72 °C for 15 s; and 1 cycle of 10 s at 95 °C, 10 s at 70 °C, and 10 s at 40 °C. All the samples were replicated three times, and the amplification results were presented as the “mean ± standard error” (n = 3).

2.5. Data Analysis

The phenotype and physiological indicators were analyzed for differences between the data using a one-way analysis of variance. A statistical analysis was performed on the data using the SPSS22.0 software (Armonk, NY, USA) and the Excel 2014 software (Redmond, WA, USA). The mean comparison was conducted using Tukey’s post hoc test. p < 0.05 was considered statistically significant.

3. Results

3.1. Phenotype Characteristics and Relative Water Content

During the natural drought treatment, the leaves of “Festina” and ds-1 showed varying degrees of influence. At 16 days of drought, both “Festina” and ds-1 showed significant wilting, but the wilting degree of ds-1 was significantly lower than that of “Festina” (Figure 1A,B). This result indicates that ds-1 has a higher drought tolerance than “Festina”. After 0 and 8 days of drought, there was no significant difference in the relative water content (RWC) of the leaves between the two groups of materials (Figure 1C). After 16 days of drought, compared with the control (0 days of drought), the RWC of ds-1 and “Festina” decreased significantly, but the RWC of ds-1 was significantly higher than that of “Festina” (Figure 1C). This result indicates that ds-1 has a stronger water retention ability than “Festina”.

3.2. Integrity of Plasma Membrane

Under normal conditions (0 days of drought), there was no significant difference in the relative conductivity (REC) or MDA content between the two groups of materials. With the extension of the drought treatment time, the REC and MDA content of the two materials showed an increasing trend (Figure 2A,B). After 16 days of the drought treatment, the REC of ds-1 and “Festina” leaves significantly increased, and the REC of the Festina leaves was significantly higher than that of ds-1 (Figure 2A). After 8 and 16 days of the drought treatment, the MDA content in the ds-1 and “Festina” leaves significantly increased, and the MDA content in the “Festina” leaves was significantly higher than that in ds-1 (Figure 2B). The above results indicate that, after the drought treatment, the degree of membrane lipid damage in ds-1 was significantly lower than that in “Festina”.

3.3. Changes in ROS Content and Antioxidant Enzyme Activity

Under normal conditions (0 days of drought), the contents of H2O2 and O2− were relatively low, and there were no significant differences between the two groups of materials. After 16 days of drought, the contents of H2O2 and O2− in the leaves of both groups of materials increased rapidly, and the contents in “Festina” leaves were significantly higher than those in ds-1 leaves (Figure 3A,B). The above results indicate that ds-1 experienced less accumulation of reactive oxygen species (ROS) caused by drought stress.
Under normal conditions (0 days of drought), there was no significant difference in the activities of SOD or POD between the two groups of materials. After 8 days of the drought treatment, the SOD activity of ds-1 leaves was significantly higher than that of “Festina” leaves. After 16 days, the SOD activity of the ds-1 leaves remained at the level of 8 days, while the SOD activity of “Festina” leaves continued to increase and was significantly higher than that of ds-1 (Figure 3C). The activity of POD in ds-1 was significantly higher than that in “Festina” at 8 and 16 days of drought stress (Figure 3D). This result indicates that drought stress causes changes in the antioxidant enzyme activity in blue fescue, thereby activating the antioxidant enzyme system to rapidly respond to drought stress.

3.4. Changes in Photosynthetic Physiological Characteristics

After 0 days of the drought treatment, there were no significant differences in Pn, Gs, Tr, or WUE between the two groups of materials (Figure 4). After experiencing the drought stress treatment (for 8 d or 16 d), the Pn, Gs, and Tr of both groups of materials significantly decreased. Under drought stress (for 8 d or 16 d), the WUE of “Festina” significantly decreased, while the WUE of ds-1 did not show significant changes. Compared to “Festina”, ds-1 had lower Gs and Tr, indicating that ds-1 has a higher water retention capacity. Meanwhile, ds-1 had higher Pn and WUE, indicating that ds-1 can better accumulate biological organic matter under the same drought conditions and demonstrates a better adaptability to drought stress.

3.5. Quality Assessment of Sequencing Data

Transcriptome sequencing generated a total of 18 cDNA libraries, each with raw data ranging from 5.49 to 6.71G. The Q20 base content was 98.08% to 99.31%, the Q30 base content was 95.15% to 96.46%, and the GC content was 48.15% to 49.89% (Table S1). Comparing the filtered clean reads with the reference transcript sequence, the proportion of effective reads that could be aligned to the genome for each sample was over 78.65% (Table S1). This indicates that the sequencing quality was good and the data could be used for subsequent analyses.

3.6. Expression Analysis of DEGs

A comparative analysis was conducted on the transcriptome data of ds-1 and “Festina”. A principal component analysis (PCA) revealed that the main components, PC1 and PC2, accounted for 83.51% and 15.56% of the total variation, respectively (Figure 5A). ds-1 and “Festina” could be clearly distinguished at different treatment time points, indicating differences in gene expression between the two varieties under drought stress. The three biological replicates of the samples clustered together, indicating good reproducibility of the experimental samples. Under the drought treatment, ds-1 vs. “Festina” resulted in a total of 9475 differentially expressed genes (DEGs), including 5064 upregulated genes and 4411 downregulated genes (Table 1). After 0 days of the drought treatment, a total of 916 DEGs were obtained, and these DEGs were most likely due to differences between the two varieties. On the 8th and 16th days of the drought treatment, 1994 DEGs and 6565 DEGs were obtained, respectively. The DEGs in this part were due to the differences between the two varieties and the drought stress treatment (Table 1). A Venn plot analysis showed that 1176 genes were differentially expressed only on the 8th day of treatment, and 5728 genes were differentially expressed only on the 16th day; 67 DEGs were co-expressed at three treatment time points, and 692 DEGs were co-expressed on the 8th and 16th days of the stress treatment (Figure 5B). These 692 DEGs were common to both genotypes of blue fescue and could serve as core DEGs used by blue fescue to cope with drought stress; thus, they are worthy of further analysis.

3.7. GO Enrichment Analysis of Common DEGs

A GO functional enrichment analysis was performed on these 692 common DEGs, and the results showed that 692 DEGs were mainly distributed in 56 GO secondary entries (Figure 6). The major categories of biological processes that were enriched were mainly rRNA processing, ribosome biogenesis, rRNA metabolic processes, ribonucleoprotein complex biogenesis, photosynthesis and light harvesting, photosynthesis, and light reactions. The major categories of cellular components that were enriched were mainly the nucleolus, ribosome, ribosomal subunit, intracellular ribonucleoprotein complex, photosystem, and intracellular non-membrane-bounded organelles. The major categories of molecular functions that were enriched were the structural constituents of ribosomes and structural molecule activity.

3.8. KEGG Enrichment Analysis of Common DEGs

The KEGG enrichment analysis showed that 692 DEGs from ds-1 and “Festina” were involved in 86 metabolic pathways. Among them, six metabolic pathways (p ≤ 0.05) were significantly enriched (Figure 7). The KEGG pathways that were significantly enriched included metabolic pathways, the photosynthesis antenna protein, plant hormone signal transduction, the MAPK signaling pathway, starch and sucrose metabolism, and arginine and proline metabolism. The above results indicate that, compared to Festina, these significantly enriched metabolic pathways may be the main reason why ds-1 has a higher drought resistance.

3.9. qRT-PCR Verification of Transcriptome

Nine DEGs were randomly selected for qRT-PCR validation of the transcriptome data. By comparing the transcriptome sequencing results with the qRT-PCR analysis results, it can be seen that the relative expression levels of these genes were basically consistent with the gene expression patterns in the transcriptome data (Figure 8), indicating that the transcriptome data are relatively reliable.

4. Discussion

4.1. Identification of Drought Tolerance of ds-1

When plants are subjected to varying degrees of drought stress, corresponding phenotypes occur in their leaves. A water deficit can reduce the relative water content (RWC) of leaves, leading to leaf wilting [36]. Under the same degree and duration of drought stress, plants with a higher leaf RWC have a stronger drought tolerance [37]. Research on 30 genotypes of tall fescue has indicated that, under mild drought stress conditions, the stress tolerance index (STI) is positively correlated with the relative water content (RWC) [38]. This is consistent with our research results. After 16 days of drought, the RWC in the leaves of ds-1 plants was significantly higher than that in “Festina” plants (Figure 1C), indicating that ds-1 has a strong drought tolerance.
MDA is the final product of cell membrane lipids, and its content directly reflects the degree of cell membrane damage [39]. Research has shown that, after experiencing the same degree and duration of drought stress, plants with a high level of stress resistance have lower levels of accumulated MDA in their tissues [40]. When the cell membrane is damaged, it cannot maintain ion and substance exchange between the protoplast and the external environment, resulting in severe ion leakage. The level of relative electrical conductivity (REC) can also directly reflect the degree of damage to the plant cell membrane [41]. Similarly, studies have shown that plants with a higher drought tolerance have a lower REC [42]. Drought stress can increase the levels of O2− and H2O2 in plants, and plants with a higher drought tolerance have lower cumulative levels of O2− and H2O2 when subjected to the same degree of drought stress [43,44]. This study found that, after 16 days of the drought stress treatment, the content of reactive oxygen species (Figure 2A,B), the REC (Figure 3A), and the MDA content (Figure 3B) in ds-1 were lower than those in “Festina”, indicating that ds-1 had less cell damage and a higher tolerance for drought stress.
The superoxide anions produced by cellular metabolism undergo a dismutation reaction under the action of SOD to generate H2O2, which is then decomposed into H2O under the action of POD, thereby protecting cells from damage [45]. Related studies have shown that different plants have different SOD response modes due to their own characteristics. In the early stages of mild and moderate drought stress, SOD in plants showed a significant upward trend. When subjected to severe drought stress, SOD in plants showed a significant downward trend, and POD also showed a trend of first increasing and then decreasing [46]. This study showed that, after 16 days of drought stress, the SOD activity in ds-1 leaves was lower than that in “Festina”, while the POD activity was higher. The reason for this may be that the O2− produced in ds-1 was lower than that in “Festina”, and the lower SOD activity was sufficient to respond to the catalytic process of O2− conversion to H2O2 (Figure 3C,D). At the same time, the higher POD activity was beneficial for accelerating the reaction process of H2O2 conversion to H2O, resulting in a higher detoxification efficiency and a higher drought stress tolerance.
Under drought stress, the photosynthetic physiological characteristics of plants also undergo significant changes with increasing drought severity and a prolonged drought duration [47]. Research has shown that drought stress can cause stomatal closure in plants, leading to an increase in the intercellular CO2 concentration and a decrease in Pn and Tr [48]. A study on the drought tolerance of six tall fescue varieties revealed that the Pn, Gs, Tr, and RWC of all the varieties decreased during drought stress, but the severity of the decrease varied among the varieties [49]. This study showed that the Pn and WUE of ds-1 were consistently higher than those of “Festina” during the drought stress treatment, indicating that ds-1 can better maintain growth and development under drought stress. At the same time, the Gs and Tr were lower, indicating that ds-1 exhibited a better water retention performance (Figure 4).
From the above results, it can be concluded that, under drought stress, ds-1 exhibits better water retention, a lower ROS content, better cell membrane integrity, stronger antioxidant enzyme activity, and better photosynthesis, ultimately leading to a higher drought resistance than “Festina”.

4.2. Transcriptional Mechanism of ds-1 Drought Tolerance

Plants undergo many genetic changes in response to drought stress, which are aimed at better resisting adverse stress. Previous studies have found that drought stress can alter the expression of genes related to metabolic pathways, the biosynthesis of secondary metabolites, porphyrin and chlorophyll metabolism, ABC transporters, plant hormone signal transduction, and photosynthesis pathways [50,51,52,53]. From this study, it can be inferred that the differential expression of genes in pathways such as those related to the photosynthesis antenna protein, plant hormone signal transduction, and MAPK signaling is the main reason why ds-1 exhibits a higher drought tolerance than “Festina” (Figure 7).
Plant hormone signaling is a key feature in regulating drought or water deficit responses [54]. The ABA signaling pathway centered around PYR-PP2C-SnRK2 is an important transcriptional regulatory molecular mechanism used by plants to respond to drought stress [55]. After plants are subjected to drought stress, ABA activates downstream signaling components, stimulating the expression of downstream genes, which leads to stomatal closure. This reduces transpiration and prevents water loss, thereby helping plants mitigate the impact of drought stress [56]. The ABA signaling pathway is a signal pathway mediated by PYL receptors, with the core components including PYL, PP2C, and SnRK2 proteins [57]. The increase in ABA can inhibit the expression of PYR/PYL and promote the expression of PP2C [58]. The ABA receptor FePYR1 of tall fescue can bind to the AtPP2C protein in Arabidopsis thaliana and activate the ABA signaling pathway, thus improving the drought tolerance of Arabidopsis thaliana [59]. Under drought stress, the downregulation of PYR/PYL expression and the upregulation of PP2C expression in ds-1 indicate that ds-1 may resist drought stress by activating the abscisic acid signaling pathway. The effect of abscisic acid on the expression of SnRK2- and ABF-family genes in plants exhibits species specificity [60], and ABA induces the upregulation of ABF expression in ds-1 (Figure S1). In the brassinosteroid signaling pathway, genes annotated to BRI1 exhibit different expression trends, which may be related to the “synergistic antagonistic mechanism” of this gene in response to ABA and brassinosteroid signaling [61]. MYC2 is a positive regulatory factor in the jasmonic acid signaling pathway, and transcription inhibitory factors bind to MYC2 to inhibit its regulation of downstream genes [62]. In many plants, JAZ expression is upregulated in response to drought stress [63,64]. In this study, genes annotated as JAZ and MYC2 were upregulated, suggesting that the positive regulation of the jasmonic acid signaling pathway may also promote an increased drought tolerance in ds-1 (Figure S1).
Photosynthesis is the most sensitive physiological process in plants to various abiotic stresses. Lhcs play a crucial role in photosynthesis in higher plants and are widely involved in regulating plant growth, development, and responses to abiotic stress [65]. In this study, eight DEGs were significantly enriched in the photosynthesis antenna protein pathway in ds-1 leaves under drought stress, and all of them were upregulated (Figure S2). Research has shown that the downregulation or disruption of Lhcb family members such as Lhcb1, Lhcb2, Lhcb3, Lhcb4, Lhcb5, or Lhcb6 can reduce the responsiveness of Arabidopsis stomatal movement to ABA, leading to a decrease in plant tolerance to drought stress. Moreover, the overexpression of Lhcb6 enhances the stomatal sensitivity to ABA [66]. Transcriptome sequencing was utilized to analyze the expression of the PpLhc gene in peaches under drought stress, revealing an upregulation of the PpLhc gene [67]. This suggests that this gene could serve as a potential candidate gene for drought resistance research in peaches. Studies on tea trees and barley have also found that drought leads to the upregulation of Lhc genes [68,69]. Therefore, it can be inferred that the Lhc gene is an important candidate gene for enhancing the drought tolerance in ds-1 plants (Figure S2).
MAPK is a highly conserved signaling module that is widely present in various plants, and its role in drought stress responses has been reported [70]. An RNA Seq analysis of maize and pearl millet revealed that MAPKKKs play an important regulatory role in drought tolerance in these plants [71,72]. Some other components of the MAPK cascade are involved in ABA signaling, ethylene signaling, and drought stress responses [73]. The upregulation of these kinases may be an important reason why ds-1 has a higher drought tolerance than “Festina” (Figure S3).
Permeation protectants, such as sugars and proline, can reduce the water potential through osmotic regulation to enhance the plant tolerance to drought [74]. Some studies have speculated that a large number of genes enriched in proline metabolism play an important role in plant drought resistance [75]. Sucrose is one of the important components of soluble sugars, and starch and sucrose metabolism are also important enrichment pathways for plants to respond to drought stress. Research has found that most genes involved in the biosynthesis of sucrose and starch are significantly upregulated in drought-tolerant varieties, indicating that a higher sucrose and starch content may be attributed to their resistance to drought stress [76]. The KEGG enrichment analysis in this study found that genes were significantly enriched in pathways such as starch and sucrose metabolism and in arginine and proline metabolism (Figures S4 and S5). This suggests that the accumulation of osmoregulatory substances such as Pro and SS may also be a reason for the enhanced drought tolerance of ds-1. A plant response to drought stress can be achieved through a complex transcriptional regulatory and metabolic network.
In summary, this study investigated the drought tolerance mechanism of blue fescue at the physiological and transcriptomic levels. However, more in-depth research on the drought tolerance mechanism of blue fescue at the proteomic and metabolomic levels has not yet been conducted, and a functional verification of the selected drought tolerance candidate genes has not been performed. In future research on the drought resistance mechanism of blue fescue, we can continue to explore its drought tolerance mechanism from the following aspects: (1) combining proteomics and transcriptomics to analyze its drought resistance mechanism; (2) using transgenic technology or gene knockout technology to verify the function of candidate genes; and (3) exploring the physiological and molecular mechanisms of the root system under drought stress.

5. Conclusions

The drought tolerance of ds-1 plants is higher than that of Festina plants. A differential gene analysis and a KEGG analysis were used to determine the DEGs and related enrichment pathways between Festina and ds-1. The DEGs were mainly enriched in pathways such as those related to the photosynthesis antenna protein, plant hormone signal transduction, MAPK signaling, starch and sucrose metabolism, and arginine and proline metabolism. Further screening was conducted to identify genes related to the photosynthesis antenna protein, plant hormone signal transduction, and the MAPK signaling pathway, as well as genes that may be associated with drought stress, including PYL, PP2C, SnRK2, ABF, BRI1, JAZ, MYC2, Lhc, and MPK6. The functional validation and research of these DEGs contribute to a deeper understanding of the drought resistance mechanism of blue fescue. Our research results provide a reference for understanding the regulatory pattern of drought tolerance in ornamental plants. In future research, we will focus on integrating multiple omics data (such as proteomics and metabolomics) to establish a more complete drought response network model. In addition, these candidate genes can be overexpressed or knocked out in model plants to confirm their role in enhancing or weakening drought resistance.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/ijpb16040116/s1. Table S1. Quality control analysis of transcriptome sequencing data; Figure S1. Enrichment of DEGs of ds-1 in plant hormone signaling pathways; Figure S2. Enrichment of DEGs of ds-1 in photosynthesis-antenna protein; Figure S3. Enrichment of DEGs of ds-1 in MAPK signaling pathway—plant; Figure S4. Enrichment of DEGs of ds-1 in starch and sucrose metabolism; Figure S5. Enrichment of DEGs of ds-1 in arginine and proline metabolism.

Author Contributions

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

Funding

This research was funded by school-level scientific research projects of the Jiangsu Agri-Animal Husbandry Vocational College (NSF2024ZR10 and NSF2023CB07) and the National Natural Science Foundation of China (32301492).

Data Availability Statement

All the data are presented in this article.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Changes in phenotype and relative water content of blue fescue. (A) Drought treatment for 0 d; (B) drought treatment for 16 d; and (C) relative water content. Different lowercase letters represent significant differences between treatments at the p < 0.05 level.
Figure 1. Changes in phenotype and relative water content of blue fescue. (A) Drought treatment for 0 d; (B) drought treatment for 16 d; and (C) relative water content. Different lowercase letters represent significant differences between treatments at the p < 0.05 level.
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Figure 2. Plasma membrane damage in blue fescue leaves during drought treatment. (A) Relative conductivity; (B) MDA content. Different lowercase letters represent significant differences between treatments at the p < 0.05 level.
Figure 2. Plasma membrane damage in blue fescue leaves during drought treatment. (A) Relative conductivity; (B) MDA content. Different lowercase letters represent significant differences between treatments at the p < 0.05 level.
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Figure 3. Changes in ROS and antioxidant enzyme activities under drought stress. (A) H2O2 content; (B) O2− content; (C) SOD activity; and (D) POD activity. Different lowercase letters represent significant differences between treatments at the p < 0.05 level.
Figure 3. Changes in ROS and antioxidant enzyme activities under drought stress. (A) H2O2 content; (B) O2− content; (C) SOD activity; and (D) POD activity. Different lowercase letters represent significant differences between treatments at the p < 0.05 level.
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Figure 4. Changes in photosynthetic physiological characteristics of blue fescue during drought treatment. Different lowercase letters represent significant differences between treatments at the p < 0.05 level.
Figure 4. Changes in photosynthetic physiological characteristics of blue fescue during drought treatment. Different lowercase letters represent significant differences between treatments at the p < 0.05 level.
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Figure 5. Differential transcriptome analysis diagram of ds-1 and Festina. (A) Principal component analysis scatter plot; (B) Venn diagram.
Figure 5. Differential transcriptome analysis diagram of ds-1 and Festina. (A) Principal component analysis scatter plot; (B) Venn diagram.
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Figure 6. GO enrichment analysis of 692 common DEGs between ds-1 and “Festina”.
Figure 6. GO enrichment analysis of 692 common DEGs between ds-1 and “Festina”.
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Figure 7. KEGG enrichment analysis of 692 common DEGs between ds-1 and “Festina”.
Figure 7. KEGG enrichment analysis of 692 common DEGs between ds-1 and “Festina”.
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Figure 8. qRT-PCR analysis of differentially expressed genes under drought stress. (A–I) Indicate PP2C, SnRK2, ABF, BRI1, JAZ, MYC2, Lhcb1, Lhcb2, and MPK6, respectively.
Figure 8. qRT-PCR analysis of differentially expressed genes under drought stress. (A–I) Indicate PP2C, SnRK2, ABF, BRI1, JAZ, MYC2, Lhcb1, Lhcb2, and MPK6, respectively.
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Table 1. Number of DEGs in drought treatments.
Table 1. Number of DEGs in drought treatments.
Comparison GroupTotal DEGsUpregulated DEGsDownregulated DEGs
ds-1—0d vs. Festina—0d916262654
ds-1—8d vs. Festina—8d19941213781
ds-1—16d vs. Festina—16d656535892976
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Zhang, Y.; Han, P.; Xiao, X.; Chen, W.; Liu, H.; Zhang, H.; Xu, L. Physiological and Transcriptome Analysis of Drought-Tolerant Mutant ds-1 of Blue Fescue (Festuca glauca) Under Drought Stress. Int. J. Plant Biol. 2025, 16, 116. https://doi.org/10.3390/ijpb16040116

AMA Style

Zhang Y, Han P, Xiao X, Chen W, Liu H, Zhang H, Xu L. Physiological and Transcriptome Analysis of Drought-Tolerant Mutant ds-1 of Blue Fescue (Festuca glauca) Under Drought Stress. International Journal of Plant Biology. 2025; 16(4):116. https://doi.org/10.3390/ijpb16040116

Chicago/Turabian Style

Zhang, Yong, Peng Han, Xuefeng Xiao, Wei Chen, Hang Liu, Hengfeng Zhang, and Lu Xu. 2025. "Physiological and Transcriptome Analysis of Drought-Tolerant Mutant ds-1 of Blue Fescue (Festuca glauca) Under Drought Stress" International Journal of Plant Biology 16, no. 4: 116. https://doi.org/10.3390/ijpb16040116

APA Style

Zhang, Y., Han, P., Xiao, X., Chen, W., Liu, H., Zhang, H., & Xu, L. (2025). Physiological and Transcriptome Analysis of Drought-Tolerant Mutant ds-1 of Blue Fescue (Festuca glauca) Under Drought Stress. International Journal of Plant Biology, 16(4), 116. https://doi.org/10.3390/ijpb16040116

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