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Article

Differential Responses of Two Sorghum Genotypes to Drought Stress at Seedling Stage Revealed by Integrated Physiological and Transcriptional Analysis

by
Manhong Wang
1,2,
Irshad Ahmad
1,2,
Muhi Eldeen Hussien Ibrahim
1,
Bin Qin
1,
Hailu Zhu
1,2,
Guanglong Zhu
1,2 and
Guisheng Zhou
1,2,3,*
1
Joint International Research Laboratory of Agriculture and Agri-Product Safety, The Ministry of Education of China, Yangzhou University, Yangzhou 225009, China
2
Jiangsu Provincial Key Lab of Crop Genetics and Physiology, Yangzhou University, Yangzhou 225009, China
3
College for Overseas Education, Yangzhou University, Yangzhou 225000, China
*
Author to whom correspondence should be addressed.
Agriculture 2025, 15(16), 1780; https://doi.org/10.3390/agriculture15161780
Submission received: 12 July 2025 / Revised: 12 August 2025 / Accepted: 15 August 2025 / Published: 20 August 2025
(This article belongs to the Special Issue Effects of Salt Stress on Crop Production—2nd Edition)
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Abstract

Drought stress significantly limits crop growth and yield, and the mechanisms underlying genotypic variation in drought tolerance remain unclear. This study investigated the growth and transcriptomic responses of two sorghum varieties, drought-sensitive Jinza 35 (V1) and drought-tolerant Longza 24 (V2), under drought conditions. Comparative transcriptomic analysis, along with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, revealed distinct molecular mechanisms between the two varieties. Both varieties exhibited drought-responsive changes in photosynthesis-related pathways. However, the drought-tolerant V2 showed significant enrichment in phenylpropanoid biosynthesis, starch-sucrose metabolism, and plant hormone signaling pathways, suggesting enhanced metabolic flexibility under stress. In contrast, V1 primarily activated ribosome metabolism and cell cycle regulation pathways, indicating a less adaptive response focused on basic cellular processes. These findings highlight key metabolic and regulatory differences underlying drought tolerance in sorghum. The study provides valuable molecular insights and candidate pathways for future functional studies and the breeding of drought-resistant sorghum varieties.

1. Introduction

Drought represents one of the most devastating abiotic stresses constraining global crop productivity, posing severe threats to sustainable agriculture [1]. With the increasing frequency and intensity of drought events under climate change [2], developing tolerant crops has become imperative. Sorghum (Sorghum bicolor L.), a C4 cereal originating from semi-arid Africa, sustains over 500 million people in tropical regions while serving as a vital feedstock and bioenergy source [3,4]. Its drought resilience stems from inheritable morphological adaptations (dense leaf epicuticular wax, deep root architecture), physiological mechanisms (osmotic adjustment, stay-green phenotype), and multilayered molecular responses enabling survival under water deficit [5].
During long-term adaptation to drought stress, plants evolve complex regulatory networks to mitigate the detrimental effects imposed by drought. At the physiological and biochemical levels, plants respond by enhancing stomatal closure to reduce transpiration, decreasing chlorophyll synthesis and photosynthesis [6], regulating antioxidant enzyme activities (including CAT, POD, and SOD) to maintain reactive oxygen species (ROS) homeostasis [7], and accumulating osmoregulatory substances (such as proline, carbohydrates, and betaine) to minimize cellular damage [8]. At the molecular level, drought responses involve multiple pathways including cell-wall stress, phytohormone signaling, epigenetic modifications, and non-coding RNA regulation [9,10]. Drought tolerance in sorghum involves polygenic regulatory networks integrating physiological, morphological, and molecular processes [11,12,13]. In terms of plant stress resistance, transcriptome sequencing can comprehensively monitor the differences in plant genes under adversity and discover functional genes to analyze the regulatory mechanism of stress response, providing a molecular genetic basis for the study of plant stress resistance mechanisms and the cultivation of stress resistant varieties [14,15]. Although the combined application of physiological and transcriptomic approaches has been widely adopted for abiotic stress research in numerous plant species [16,17,18], its utilization in sorghum remains unclear, particularly during the seedling growth stage. To address this gap, by employing this multi-omics strategy, we aimed to uncover key molecular and physiological mechanisms underlying drought tolerance in sorghum. Therefore, in this study, we employed comparative transcriptomics on V1 and V2 sorghum genotypes during seedling establishment. By correlating phenotypic, physiological, and transcriptional datasets, we revealed genotype-specific adaptation strategies. The findings provide critical insights for drought-resistant sorghum breeding, offering both theoretical guidance and technical support for the development of high-yielding cultivars suited to arid environments.

2. Materials and Methods

2.1. Plant Materials

This study used two varieties of sorghum: Jinza 35 (V1), a drought-sensitive variety, and Longza 24 (V2), a drought-tolerant one. V1 was provided by Shanxi Agricultural University, has a red seed coat, and has an average growing period of 135 days. V2 was provided by Heilongjiang Academy of Agricultural Sciences, has a red seed coat, and has an average growing period of 100 days. Seeds of both varieties were stored in craft paper bags to maintain good germination rates prior to the study; seeds of uniform color, size, and shape were selected and sterilized in a solution of 2.5% sodium hypochlorite for 5 min, then rinsed with deionized water.

2.2. Experimental Design

All tests were conducted in 2024. The sterilized seeds were sown in seedling trays (the width of the top opening was 6 cm, the width of the bottom opening was 2.6 cm, the depth was 5.1 cm, and there was a hole in the bottom), with two seeds placed in each cell at a sowing depth of 2–3 cm. The trays were then transferred to a greenhouse for cultivation. At the time of sowing, the soil moisture content in the trays was maintained at 40%. After 7 days, the soil relative humidity was reduced to 20% and maintained at this level for continuous stress treatment until sampling at 21 days (denoted as D for drought stress), with soil moisture monitored every 12 h using a soil hygrometer and supplemented with minor watering when readings fell below the target to ensure stable stress intensity. Each variety and drought treatment was replicated three times. Soil moisture was measured daily using a soil moisture meter. The soil used in the trays was collected from farmland and classified as sandy loam, with the following properties in the 20 cm tillage layer: total nitrogen content of 1.5 g/kg, alkali-hydrolysable nitrogen of 87.7 mg/kg, available phosphorus of 38.1 mg/kg, and available potassium of 82.3 mg/kg.

2.3. Observations and Measurements

2.3.1. Determination of Physiological and Biochemical Indicators in Plant Growth

Seed emergence rate was recorded on day 7 of stress exposure, while survival rate of seedlings was measured on day 14 of stress exposure. The calculations were performed as follows:
Seed emergence rate (%) = (Number of germinated seeds on day 7/Total number of tested seeds) × 100%
Survival rate of seedlings (%) = (Number of established seedlings on day 14/Total number of tested seeds) × 100%
After 21 days of stress exposure, three plants were sampled from each treatment. Plants were carefully uprooted from the seedling trays and washed with clean water. Plant height, total root length, SPAD and leaf area were measured. Plant height was measured from the base of the plant at the soil surface to the tip of the head [19]. Leaf area equals leaf length × leaf width × 0.75. A root analytical system (Model SC-GX, Zhejiang Hangzhou Shangsheng Instrument, Hangzhou, China) was used to analyze total root length. The SPAD readings of the leaves were determined in vivo using a chlorophyll meter (SPAD-502, Konica Minolta, Saitama Prefecture, Japan).

2.3.2. Determination of Antioxidant Enzymes

Three weeks after sowing, the leaves of three plants from each treatment were sampled and the collected samples were immediately frozen in liquid nitrogen and stored at −80 °C for the determination of malondialdehyde (MDA) content, superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD) activities, soluble protein (Sp), and superoxide anion production (O2−). Leaf samples (0.2 g) were homogenized in 1.8 mL of 25 mM phosphate buffer (pH 7.8) using a ball mill, followed by centrifugation at 12,000× g for 20 min at 4 °C. The supernatant was immediately analyzed for determination of stress indicators. MDA content was quantified using the thiobarbituric acid method [20]. SOD activity was determined using the nitroblue tetrazolium photoinduction method following Qian et al. [21], CAT activity was determined using the H2O2 method, and POD activity was estimated using the guaiacol method according to Assaha et al. [22]. Sp content was tested using the methods of Zhu et al. [23], and superoxide anion production rate according to Liu and Pang’s protocol [24].

2.3.3. cDNA Library Preparation and RNA-Seq

Fresh leaf tissues of sweet sorghum seedlings were collected and rapidly frozen in liquid nitrogen after 7 days of stress treatment (three biological replicates per experiment). Total RNA was extracted using a commercial kit manufactured by Guangdong Magigene Biotechnology Co., Ltd. (Guangzhou, China). RNA degradation and contamination were assessed by electrophoresis on a 1% agarose gel. RNA quantity was measured using a Qubit 4.0 (Thermo Fisher Scientific, Waltham, MA, USA) and a Nanodrop One (Thermo Fisher Scientific, MA, USA). RNA integrity was accurately evaluated using the Agilent 4200 system (Agilent Technologies, Waldbronn, Germany). cDNA libraries were constructed using the ALFA-SEQ RNA Library Prep Kit (Guangzhou Findrop Biotechnology Co., Ltd. Findrop, Guangzhou, China) following the manufacturer’s instructions. A total of 12 cDNA libraries, representing triplicate biological replicates for each of the four treatments, were prepared. The libraries were then subjected to paired-end sequencing on an Illumina (Novaseq Xplus platform, San Diego, CA, USA).

2.4. Data Analysis

Data are presented as mean ± standard deviation (SD) in tables and figures. Statistical analysis was performed using SPSS 25, with t-tests employed to assess significant differences between treatments and varieties. Figures were generated using Origin 2021.
RNA-seq data analysis was performed on a cloud platform from Guangdong Magigene Biotechnology Co., Ltd. RSEM (v1.3.1, https://github.com/deweylab/RSEM, accessed on 28 June 2018) was used to obtain read counts for each gene. To ensure comparability of gene expression levels across different genes and experiments, transcripts per million (TPM) values were calculated for each gene. Differential expression analysis between two conditions/groups was conducted using DESeq2 (v1.34.0, http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html, accessed on 26 October 2021). Genes with a false discovery rate (FDR) ≤ 0.05 and |log2(fold change)| ≥ 1 were identified as differentially expressed genes (DEGs) and used for subsequent analysis. Enrichment analysis of DEGs in Gene Ontology (GO, http://www.geneontology.org, accessed on 17 January 2024) and the Kyoto Encyclopedia of Genes and Genomes (KEGG, http://www.genome.jp/kegg/, accessed on 1 November 2023) was performed using the clusterProfiler package (v4.2.2, http://www.bioconductor.org/packages/release/bioc/html/clusterProfiler.html, accessed on 13 January 2021). GO terms and KEGG pathways with an FDR ≤ 0.05 were considered significantly enriched.

3. Results

3.1. Phenotypic and Physiological Responses of Two Sorghum Varieties to Drought Stress

Drought significantly impacted sorghum plant growth (Figure 1). Compared to the control, the seed emergence rates of V1 and V2 decreased by 41.43% and 18.61%, respectively, while the survival rate of seedlings dropped by 49.73% and 39.46%. Plant height was reduced by 55.29% in V1 and 34.68% in V2 compared to their respective controls; under drought, V2 was 32.53% taller than V1. Total root length decreased by 75.46% in V1 and 65.83% in V2. The SPAD value declined by 40.11% in V1 and 14.55% in V2. The leaf area reduced by 66.71% in V1 and 25.04% in V2, with V2’s maximum leaf area being 14.85 cm2.
As compared to the control, under the drought treatment, MDA content in V1 and V2 was increased by 25.15% and 39.99%, respectively; O2− was increased in V1 and V2 by 87.10% and 82.16%; POD activity in V1 increased by 55.86%, and in V2 by 46.21%. CAT activity in V1 was increased by 29.19%, and in V2 by 49.97%. Under drought conditions, SOD activity significantly increased, with V1 showing a 31.51% increase and V2 a 50.71% increase; Sp content was increased in V1 by 80.76% and in V2 by 50.13%, relative to the control treatment (Figure 2).

3.2. Transcriptome Sequencing and Differential Gene Expression Analysis

Under drought conditions compared with normal water conditions, 8408 DEGs were identified in V2, including 3306 upregulated and 5102 downregulated genes. 4318 DEGs were identified in V1, including 2423 upregulated and 1895 downregulated genes. The number of DEGs in V2 was slightly higher than in V1. Venn diagram analysis of DEGs from V1 and V2 revealed that 2730 DEGs were shared between the two varieties, indicating commonly responsive genes in sorghum’s drought stress response. Furthermore, 1624 DEGs were unique to V1, while 5772 were unique to V2. These distinct genes may account for the different responses of the two varieties to drought stress, highlighting how drought conditions impact gene expression in both types (Figure 3).
Following this, correlation and principal component analyses (PCA) were conducted to evaluate the similarity between samples. As illustrated in Figure 2C, biological replicates are consistently clustered together. The PCA further confirmed the strong reproducibility of the biological samples, with each sample type forming its distinct group. Additionally, the two principal components effectively distinguish the two varieties.
To elucidate the function of the DEGs under drought stress, we performed GO classification encompassing biological processes, cellular components, and molecular functions. Figure 4A,B presents the top 20 significantly enriched GO terms. DEGs in V1 were significantly enriched for processes including photosynthesis, chloroplast- and plastid-related functions, and ribosome biogenesis. In contrast, DEGs in the drought-tolerant variety V2 were enriched for photosynthesis, photosynthetic membrane functions, and chloroplast-related terms. Subsequent KEGG pathway analysis was conducted to investigate the metabolic pathways associated with the DEGs. Figure 4C,D highlights the top 30 significantly enriched KEGG pathways. DEGs in V1 exhibited significant enrichment in photosynthetic pathways and ribosomal metabolism. Conversely, V2 DEGs showed significant enrichment in photosynthesis alongside key metabolic pathways, specifically phenylpropanoid biosynthesis and starch and sucrose metabolism. These results indicate that modulation of photosynthetic processes represents a common response mechanism to drought across both varieties. However, V1 primarily relies on pathways involving ribosome biogenesis, while V2 activates critical metabolic pathways including phenylpropanoid and glutathione biosynthesis and carbohydrate metabolism. The distinct enrichment patterns observed in both GO and KEGG analyses strongly suggest these pathways are closely linked to sorghum’s molecular response to drought stress.

3.3. Response Pathways to Drought in Two Sorghum Varieties

3.3.1. Response of Phenylpropane Metabolic Pathway to Drought Stress

In the phenylpropanoid biosynthesis pathway, the number of DEGs was the highest, and the enrichment results were the most significant, although no significant enrichment was observed in V1. The expression patterns of the DEGs were illustrated by constructing a clustered heatmap of the various genes (Figure 5). Phenylalanine is converted into cinnamic acid primarily through deamination catalyzed by phenylalanine ammonia-lyase (PAL), or by phenylalanine/tyrosine ammonialyase (PTAL). In V2, the expression of three PAL genes was downregulated under drought stress, while the gene LOC8054283 was upregulated in both varieties. In both sorghum varieties, several genes related to the conversion of cinnamic acid to cinnamyl aldehyde were associated with catalytic enzymes such as 4-coumarate-CoA ligase (4CL), trans-cinnamate 4-monooxygenase (CYP73A), cinnamoyl-CoA reductase (CCR), and cinnamyl alcohol dehydrogenase (CAD). Under drought stress, some of these genes were downregulated, while others were upregulated. Notably, the gene LOC8084483 encoding CYP73A was only significantly upregulated in V2, and the genes LOC110430515 and LOC8054528 encoding 4CL were significantly upregulated in V2 as well. Shikimate O-hydroxy cinnamoyl transferase (HCT) is a bifunctional enzyme that plays a crucial role in the production of caffeoyl-CoA, directing the metabolic pathway from the general phenylpropanoid pathway to monolignol biosynthesis. In monolignol biosynthesis, two key steps involve transferring the p-coumaroyl group to shikimate and forming caffeoyl-CoA, with HCT essential for lignin biosynthesis. Under drought stress, several genes related to HCT were upregulated. The basic structural units of natural lignin polymers are p-hydroxyphenyl, guaiacyl, and syringyl, which are derived from three lignin monolignols: p-coumaryl alcohol, coniferyl alcohol, and sinapyl alcohol. P-coumaryl alcohol is an important flavonoid compound catalyzed by POD to produce lignin, and guaiacyl alcohol is also synthesized through a similar POD catalyzed process. The primary function of lignin is to provide mechanical strength to the cell wall and to facilitate the formation of the xylem, which is vital for the long-distance transport of water and nutrients. In both sorghum varieties studied, many genes encoding POD were downregulated under drought stress. However, genes LOC8078972 and LOC8055466 were upregulated in V2, potentially indicating that they contribute to the increased enzyme activity observed in this variety. During drought stress, lignin deposition enhances cell wall thickening, which reduces water permeability and enables plants to maintain cell turgor even when water is limited.

3.3.2. Ribosome Metabolic Pathways in Response to Drought Stress

The ribosome pathway was significantly enriched in the V1 variety and contained the highest number of DEGs. The process of translating RNA into proteins occurs in ribosomes, which are central to biogenesis, assembly, and the cell cycle. Any alterations in this process can negatively impact cell growth and induce toxic stress responses due to protein misfolding. As shown in the figure, the genes encoding large subunit ribosomal proteins such as L3, L32e, L17, L12e, L10e, L36, L30, LP1, LP2, L7Ae, L11e, L7/L12, L40e, and L26e were significantly upregulated in V1. Additionally, the genes encoding small subunit ribosomal proteins such as S10, S27e, and S13e were also significantly upregulated. In contrast, in V2, only the gene encoding the large subunit protein L10e and the genes encoding small subunit proteins S27e and S7e were significantly upregulated (Figure 6).

3.3.3. Sucrose Metabolic Pathways in Response to Drought Stress

According to the differential gene enrichment results, the starch and sucrose metabolism pathway was the second most significantly enriched pathway in the drought-tolerant sorghum variety (V2) under drought stress (Figure 7). Starch and sucrose metabolism are essential fundamental metabolic pathways for plant survival, requiring the coordinated action of multiple enzymes. Under drought stress, the expression of most genes in the sucrose and starch metabolism pathways was significantly downregulated. In contrast, some genes were upregulated, potentially representing key genes for V2 in sorghum. β-Fructofuranosidase (INV, also known as invertase) is a critical enzyme that hydrolyzes sucrose into glucose and fructose. The expression of INV genes in both sorghum varieties was downregulated under drought stress. Similarly, sucrose synthase (SUS) expression was downregulated in both V1 and V2 under drought stress, but the gene LOC8082319 was significantly upregulated in V2. SUS is a key enzyme in sucrose metabolism, involved in plant osmotic regulation, starch biosynthesis, and stress resistance pathways, directly influencing plant growth and development. D-fructose is catalyzed by HK and scrK to produce D-fructose-6P, with the HK gene LOC5055699 being upregulated in V2 but downregulated in V1. PYG, glgP, glgA, and GBG1/glgB catalyze the conversion of α-D-fructose-1P to starch. PYG and glgP-related genes were downregulated in V1, while LOC110431626 and LOC8060105 were upregulated in V2. In glgA, two genes were significantly upregulated and two were downregulated in V2, whereas in V1, only two were significantly downregulated. INV, HK, scrK, SUS, PYG, glgP, glgA, and GBG1/glgB may represent key genes in sorghum response to drought stress.

3.3.4. Hormone Metabolic Pathways in Response to Drought Stress

Plant hormone signal transduction is crucial in how plants respond to abiotic stress. As shown in the figure, differential gene expression was observed in all eight hormone signaling pathways, which include auxin (IAA), cytokinin (CK), gibberellin (GA), abscisic acid (ABA), ethylene (ETH), brassinosteroid (BR), jasmonic (JA) acid, and salicylic acid. In the auxin pathway, only one DEG belonging to the AUX/IAA gene family was found to be upregulated in V1. In contrast, three DEGs (in the auxin pathway) were upregulated in V2. These findings suggest that auxin signaling may contribute to cell elongation and differentiation under drought, particularly in V2 (Figure 8).
In the cytokinin pathway, AHP was upregulated in V1 but downregulated in V2. This result indicates that V2 may suppress the expression of specific AHP genes, thereby reducing cytokinin signaling. As a result, the cell division rate might be lower, which would help conserve energy and resources during drought stress (Figure 8). In the gibberellin signaling pathway, GID1 was found to be upregulated in V2 but not expressed in V1. In contrast, in the ABA signaling pathway, PYR/PYL genes were downregulated in V2, while no differential expression was detected in V1. The expression of PP2C genes was upregulated in both V1 and V2, indicating that ABA synthesis is enhanced under drought conditions to help regulate stomatal closure and maintain water retention. In the ethylene signaling pathway, the gene encoded by EIN3 was upregulated in both V1 and V2, indicating that both varieties significantly enhance ethylene signaling activity to regulate stomatal closure and root growth, thereby better adapting to drought. In the BR signaling pathway, expression of BRI1 and BKI1 showed no differential expression in V1 but was downregulated in V2, suggesting that V2 may suppress the expression of BRI1 genes under drought conditions. The expression of the BSK gene remained unchanged in V1 but was found to be upregulated in V2. In the JA signaling pathway, the expression of JAR1 did not change in V1 but was downregulated in V2, indicating that V2 may suppress JAR1 gene expression under drought stress. Additionally, JAZ expression was downregulated in V1 and V2, with a more pronounced decrease in V1.

3.3.5. Response of Reactive Oxygen Species Metabolic Pathways to Drought Stress

In the ROS metabolic pathway, the expression level of the SOD gene in V1 was −2.11, while the expression level of the V2 gene showed no significant change, suggesting that V1 may inhibit the expression of the SOD gene under drought conditions. For the CAT-encoding gene LOC8069231, expression remained unchanged in V1, whereas in V2 it showed a log2FoldChange of 2.06 (Figure 9), indicating that V2 promotes the expression of the CAT gene under drought conditions. These findings are consistent with the results of previous enzyme activity assays. V1 may reduce the activity of the antioxidant defense system by inhibiting the expression of ROS scavenging enzyme genes, thereby failing to effectively scavenge ROS and leading to oxidative damage. In contrast, V2 may maintain the activity of the antioxidant defense system by regulating the expression of ROS-scavenging enzyme genes, thereby better adapting to drought conditions.

4. Discussion

4.1. Response Mechanisms of Phenotypic and Physiological Changes in Sorghum in Response to Drought Stress

Drought stress triggers ROS overproduction in plants, driving membrane lipid peroxidation that elicits catastrophic oxidative damage to subcellular components [25]. The accumulation of ROS contents MDA and O2− was more significant in V1 varieties. The more severe stress injury to V1 was also indicated by the reduction in seedling emergence, seedling success, plant height, root length, SPAD value and leaf area. In order to scavenge excess ROS, plants have evolved ROS-scavenging enzyme systems such as SOD, POD, and CAT, in addition to several low molecular weight antioxidants, such as reduced ascorbic acid and reduced glutathione [26,27]. In the present study, the drought-tolerant variety V2 effectively mitigated oxidative damage by exhibiting higher activities of protective enzymes, such as SOD, POD, and CAT. Moreover, POD enzyme activity in V1 increased by 55.86%, while in V2 increased by 46.21%, compared to the control, marking the most significant combined increase observed. This finding suggests that POD enzyme activity could be crucial for V2, a hypothesis we further verified at the molecular level. Furthermore, the study revealed that most DEGs are involved in peroxisomal functions related to ROS metabolism. In a study by Ksouri N et al., the expression of genes encoding peroxidases was also both up- and downregulated under drought stress in Prunus persica [28]. However, the upregulated genes encoding POD enzymes are the key factors responsible for increased POD enzyme activity [9]. In this study, in the CAT encoded gene LOC8069231, there was no change in expression in V1, while V2 showed an expression level of 2.06. This indicates that drought conditions enhance the expression of CAT genes, aligning with previous studies [29]. Collectively, these findings demonstrate that under drought stress, genotype V2 exhibits enhanced enzymatic and non-enzymatic antioxidant capacity relative to V1. This superior redox homeostasis maintenance results in significantly attenuated membrane lipid peroxidation, thereby mitigating oxidative cellular damage.

4.2. Response of the Phenylpropanoid Biosynthesis Pathway to Drought Stress

Based on the differential gene enrichment results, the phenylpropanoid biosynthesis pathway was the most significantly enriched in the drought-tolerant sorghum variety V2 under drought stress. The phenylpropanoid pathway is one of the most important secondary metabolic pathways, producing various secondary metabolites, including flavonoids and phenolic acids. Phenolic and flavonoid compounds can suppress ROS production and are considered crucial antioxidants in plants under stress [30]. Phenylpropanoids undergo a series of enzymatic reactions, including hydroxylation, methylation, and reduction, to be converted into lignin monomers. These monomers are then transported to the cell wall, polymerizing them into lignin polymers. Under abiotic stress, lignin is crucial in reducing water permeability and transpiration in plant cell walls; this helps maintain cellular osmotic balance and protects membrane integrity [31]. Key enzymes in these reactions have been thoroughly studied, and their associated genes have been identified in various plant species [32]. Among these enzymes, PAL is the first rate-limiting enzyme in lignin biosynthesis, and its activity directly influences the entire lignin synthesis process [33]. Overexpression of PAL in Lotus japonicus significantly increased PAL enzyme activity, raising root lignin content by 46% and thickening the root cell wall by 50% compared to wild-type plants [34]. 4CL is a key enzyme linking the general phenylpropanoid pathway to the lignin-specific branch. Silencing 4CL1 in switchgrass (Panicum virgatum) reduced 4CL activity by 80% and decreased lignin content [35], while knocking out Os4CL3 in rice (Oryza sativa L.) led to a reduction in two lignin monomers [36]. CCR primarily converts hydroxycinnamoyl-CoA thioesters into their corresponding aldehydes. Downregulation of CCR in rice significantly reduced lignin content [37], and suppressing SmCCR1 in Salvia miltiorrhiza even resulted in dwarf transgenic plants [38]. CAD (cinnamyl alcohol dehydrogenase) catalyzes the final reduction step to produce lignin monomers. In transgenic switchgrass, reduced CAD expression lowered enzyme activity and lignin content [39]. Similarly, downregulating COMT, CCoAOMT, 4CL, C4H, C3H, and HCT in alfalfa decreased lignin levels [40]. Under drought stress, V2 significantly enhanced lignin biosynthesis by regulating key genes in the phenylpropanoid pathway (e.g., PAL, 4CL, CYP73A, HCT), thereby maintaining cell wall mechanical strength and reducing water loss. This provides evidence for our results that indicated that the PAL, 4CL, CCR, and CAD genes related to the lignin biosynthesis pathway are involved in the response of sorghum to drought stress and can be used as drought candidate genes in sorghum.

4.3. Response of Other Metabolic Pathways to Drought Stress

4.3.1. Starch and Sucrose Metabolism

Water loss inhibits the activity of key starch metabolic enzymes reducing starch content and subsequently affecting photosynthetic efficiency [41]. Under high-temperature drought conditions, reduced photosynthesis leads to diminished carbon fixation and cellular osmotic potential, disrupting the synthesis and transport of sugars. Sugars serve not only as energy sources but also as signaling molecules that regulate stress resistance responses [42]. In drought conditions, plants break down starch into soluble sugars to support growth or act as osmoregulatory substances and antioxidants to mitigate drought damage [43]. Beta-amylase is a key enzyme in catalyzing starch hydrolysis. Trehalose protects cellular structures, stabilizes biomolecules, and maintains membrane integrity and protein function under stress [44]. Lyu found that trehalose and similar metabolites function as signaling molecules, which enhance the expression of heat stress-responsive genes and improve stress tolerance in seeds [45]. Previous studies in Selaginella tamariscina [46], cotton [47], and maize [48] have shown that trehalose synthesis-related gene expression and trehalose accumulation improve stress resistance. This study found that genes encoding β-amylase were upregulated in both sorghum varieties under drought stress, with significantly higher expression levels in V2. The present results indicate that β-amylase plays a critical role in V2. In another important pathway for trehalose synthesis, otsA and otsB catalyze the conversion of UDP-glucose to trehalose. While all genes in this pathway were downregulated in V1, V2 showed five upregulated genes with only minor downregulation. The results suggest that V2 has a superior capacity for trehalose synthesis. Additionally, drought conditions suppressed most genes related to sucrose metabolism, such as INV and SUS, which rapidly break down sucrose into hexoses. This process helps lower osmotic potential [29]. Similar findings were reported in tea plants, where key enzyme genes involved in insoluble (starch) and soluble sugar (mannitol, trehalose, sucrose) metabolism were altered under drought [47]. Collectively, our comprehensive analysis identified INV, SUS, ostA, and ostB as pivotal genes enhancing sorghum drought resistance. The starch and sucrose metabolism pathways primarily attenuate drought stress responses through negative regulation. With the growing maturity of gene editing technologies, these genetic resources provide critical targets for developing novel drought tolerance sorghum cultivars. Future efforts should focus on precisely modulating the expression of these genes to activate sugar-metabolizing enzymes, thereby improving saccharide catabolism efficiency and ultimately strengthening drought tolerance mechanisms.

4.3.2. Plant Hormone Signal Transduction

Various hormones such as ABA, CTK, IAA, SA, ETH, JA, BR, and GA accumulate under dehydration, acting as signaling molecules to regulate physiological responses to drought [49]. ABA is a key hormone in the drought response [50]. It stimulates the production of osmolytes, helps regulate stomatal closure to minimize water loss, and alters root architecture. During drought conditions, increased levels of ABA bind to receptor proteins known as PYR/PYLs. This binding forms a transient complex with the negative regulator PP2C, which releases SnRK2 for phosphorylation. Once activated, SnRK2 initiates stomatal closure and triggers the expression of genes that respond to drought stress [51,52].
PYR/PYLs were downregulated in V2, while PP2C was upregulated in both varieties. Overexpressed PP2C may bind SnRK2 instead of PYR/PYLs, inhibiting SnRK2 activation and ABA signaling. These results suggest a negative feedback mechanism due to prolonged ABA over accumulation in V2. JA biosynthesis and signaling interact with ABA. JAR1, which persists in leaves, cooperates with ABA to induce stomatal closure [49]. In V2, certain genes were downregulated, while they were absent in V1. Notably, JAZ, a repressor of JA signaling, was downregulated in both V1 and V2, which contrasts with the typical upregulation of JA seen during drought stress. This discrepancy may be due to prolonged stress leading to co-suppression of JA and ABA. Additionally, the stress-response gene ARF showed downregulation in the IAA signaling pathway in V2. Similarly, genes involved in the GA pathway, such as GID1 and DELLA, as well as BR signaling genes, were also downregulated in V2. DELLA proteins play a role in inhibiting growth to enhance drought survival [53], while BR signaling has an antagonistic effect on ABA [54]. These changes indicate that V2 conserves energy by limiting growth during drought conditions. Notably, the GA receptor GID1c-like protein was upregulated in V2, highlighting the role of GA in drought adaptation. Additionally, ethylene (ETH) plays a key role in regulating stress responses and leaf senescence. The senescence of older leaves enables cereals to redistribute nutrients to younger leaves and grains, which helps reduce water demand and promotes drought tolerance [55]. Ethylene also plays a role in regulating stomata alongside ABA [56]. The expression of EIN3 was significantly increased in both varieties, with a higher level observed in V2, indicating its importance in responding to severe drought conditions. While V1 maintains pathways for auxin and cytokinin to promote growth, V2 utilizes crosstalk among multiple hormones to reallocate resources effectively. Under drought conditions, V1 increased cell elongation, division, and growth by upregulating the auxin and cytokinin signaling pathways and regulating stomatal closure to cope with drought stress. In contrast, V2 increased root growth and antioxidant defense by upregulating the auxin, gibberellin, ethylene, and BR signaling pathways, allowing adaptation to drought. V1 and V2 also increased the ABA signaling pathway to regulate stomatal closure.

4.3.3. Ribosome Metabolism

RPs constitute the primary structural components of ribosomal small and large subunits, which together with rRNA form the catalytic machinery for protein synthesis [57]. Under drought stress, plants initiate complex physiological and molecular adaptations requiring extensive gene regulation for synthesizing functional and regulatory proteins [58]. As complexes of rRNA and RPs, ribosomes play pivotal roles not only in translation but also in DNA repair and growth regulation. In V1, the ribosome pathway demonstrated the most significant enrichment, exhibiting substantially more upregulated RP genes than V2. RP family members are established mediators of abiotic stress responses [59]. We propose that V1 upregulates RPs to meet the increased demand for stress-responsive protein synthesis under drought; however, this energetically demanding strategy may exacerbate metabolic burden and ROS generation. Conversely, V2’s limited ribosomal gene expression remodeling suggests a metabolically conservative adaptation strategy prioritizing energy preservation over high-volume protein production.

5. Conclusions

To elucidate the molecular mechanisms underlying sorghum drought resistance, a comparative physiological and transcriptomic analysis was conducted between V1 and V2 at the seedling stage under drought stress. Under drought conditions, V2 exhibited more extensive transcriptomic reprogramming (as indicated by a higher number of DEGs) than V1, demonstrating that the V2 cultivar possesses stronger genetic defense capabilities against drought stress. In V2, drought stress response was mediated through alterations in basal metabolism, whereas V1 primarily relied on ribosomal pathways an adaptation that may confer drought resistance. Overall, these findings provide valuable resources for uncovering genotype-dependent molecular mechanisms of drought resistance in sorghum and for developing effective drought tolerance breeding strategies.

Author Contributions

Conceptualization, G.Z. (Guanglong Zhu). and G.Z. (Guisheng Zhou); methodology, M.W. and B.Q.; Investigation, M.W. and I.A.; Data curation, H.Z.; Software and visualization, H.Z.; and M.E.H.I.; Resources, M.W. and I.A.; Writing—original draft, M.W. and I.A.; Writing—review and editing, I.A., G.Z. (Guisheng Zhou) and G.Z. (Guanglong Zhu); Funding acquisition, G.Z. (Guisheng Zhou). All authors have read and agreed to the published version of the manuscript.

Funding

This study is financially supported by the China National Key R&D Program (2022YFE0113400), Jiangsu Provincial Fund for Realizing Carbon Emission Peaking and Neutralization (BE2022305-1), “Zhongshan Biological Breeding Laboratory” Program (ZSBBL-KY2023-03-05-04), and “Qinglan Project” Talent program of Yangzhou University.

Data Availability Statement

Dataset available on request from the authors. The raw data supporting the conclusions of this article will be made available by the authors on request.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Phenotypic analysis of differences in two sorghum varieties under drought stress. Different lowercase letters indicate significant differences at the p < 0.05 level among the same variety under different treatments, while ** indicates significant differences at the p < 0.05 level among different varieties under the same treatment, and ns indicates no significant differences between varieties (p > 0.05). (A): Seedling emergence, (B): Survival rate of seedlings, (C): Plant height, (D): Total root length, (E): Relative chlorophyll content, (F): Leaf area.
Figure 1. Phenotypic analysis of differences in two sorghum varieties under drought stress. Different lowercase letters indicate significant differences at the p < 0.05 level among the same variety under different treatments, while ** indicates significant differences at the p < 0.05 level among different varieties under the same treatment, and ns indicates no significant differences between varieties (p > 0.05). (A): Seedling emergence, (B): Survival rate of seedlings, (C): Plant height, (D): Total root length, (E): Relative chlorophyll content, (F): Leaf area.
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Figure 2. Physiological analysis of differences in two sorghum varieties under drought stress. Different lowercase letters indicate significant differences at the p < 0.05 level among the same variety under different treatments, while ** indicates significant differences at the p < 0.05 level among different varieties under the same treatment, and ns indicates no significant differences between varieties (p > 0.05). (A) MDA: malondialdehyde, (B) SOD: superoxide dismutase, (C) CAT: catalase, (D) POD: peroxidase, (E) Sp: Soluble protein, (F) O2−: superoxide anion production.
Figure 2. Physiological analysis of differences in two sorghum varieties under drought stress. Different lowercase letters indicate significant differences at the p < 0.05 level among the same variety under different treatments, while ** indicates significant differences at the p < 0.05 level among different varieties under the same treatment, and ns indicates no significant differences between varieties (p > 0.05). (A) MDA: malondialdehyde, (B) SOD: superoxide dismutase, (C) CAT: catalase, (D) POD: peroxidase, (E) Sp: Soluble protein, (F) O2−: superoxide anion production.
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Figure 3. Relationship between identified DEGs. (A): Number of DEGs between different comparison groups (B): Venn diagram analysis of the DEGs; (C): Principal component analysis of all samples, (D): Correlation analysis between all samples.
Figure 3. Relationship between identified DEGs. (A): Number of DEGs between different comparison groups (B): Venn diagram analysis of the DEGs; (C): Principal component analysis of all samples, (D): Correlation analysis between all samples.
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Figure 4. Enrichment analysis of GEGs: (A): Enrichment analysis of DEGs by GO in Jinza35. (B): Enrichment analysis of DEGs by GO in Longza24. (C): Enrichment analysis of DEGs by KEGG in Jinza35. (D): Enrichment analysis of DEGs by KEGG in Longza24.
Figure 4. Enrichment analysis of GEGs: (A): Enrichment analysis of DEGs by GO in Jinza35. (B): Enrichment analysis of DEGs by GO in Longza24. (C): Enrichment analysis of DEGs by KEGG in Jinza35. (D): Enrichment analysis of DEGs by KEGG in Longza24.
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Figure 5. Phenylpropane biosynthetic pathway in response to drought stress. The differential genes in the figure are all under drought treatment compared to normal conditions.
Figure 5. Phenylpropane biosynthetic pathway in response to drought stress. The differential genes in the figure are all under drought treatment compared to normal conditions.
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Figure 6. Ribosome pathway in response to drought stress.
Figure 6. Ribosome pathway in response to drought stress.
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Figure 7. Sucrose and starch synthesis pathways in response to drought stress. The differential genes in the figure are all under drought treatment compared to normal conditions.
Figure 7. Sucrose and starch synthesis pathways in response to drought stress. The differential genes in the figure are all under drought treatment compared to normal conditions.
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Figure 8. Phytohormone signaling pathways in response to drought stress. The differential genes in the figure are all under drought treatment compared to normal conditions.
Figure 8. Phytohormone signaling pathways in response to drought stress. The differential genes in the figure are all under drought treatment compared to normal conditions.
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Figure 9. Reactive oxygen species signaling pathway in response to drought stress. The differential genes in the figure are all under drought treatment compared to normal conditions.
Figure 9. Reactive oxygen species signaling pathway in response to drought stress. The differential genes in the figure are all under drought treatment compared to normal conditions.
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Wang, M.; Ahmad, I.; Hussien Ibrahim, M.E.; Qin, B.; Zhu, H.; Zhu, G.; Zhou, G. Differential Responses of Two Sorghum Genotypes to Drought Stress at Seedling Stage Revealed by Integrated Physiological and Transcriptional Analysis. Agriculture 2025, 15, 1780. https://doi.org/10.3390/agriculture15161780

AMA Style

Wang M, Ahmad I, Hussien Ibrahim ME, Qin B, Zhu H, Zhu G, Zhou G. Differential Responses of Two Sorghum Genotypes to Drought Stress at Seedling Stage Revealed by Integrated Physiological and Transcriptional Analysis. Agriculture. 2025; 15(16):1780. https://doi.org/10.3390/agriculture15161780

Chicago/Turabian Style

Wang, Manhong, Irshad Ahmad, Muhi Eldeen Hussien Ibrahim, Bin Qin, Hailu Zhu, Guanglong Zhu, and Guisheng Zhou. 2025. "Differential Responses of Two Sorghum Genotypes to Drought Stress at Seedling Stage Revealed by Integrated Physiological and Transcriptional Analysis" Agriculture 15, no. 16: 1780. https://doi.org/10.3390/agriculture15161780

APA Style

Wang, M., Ahmad, I., Hussien Ibrahim, M. E., Qin, B., Zhu, H., Zhu, G., & Zhou, G. (2025). Differential Responses of Two Sorghum Genotypes to Drought Stress at Seedling Stage Revealed by Integrated Physiological and Transcriptional Analysis. Agriculture, 15(16), 1780. https://doi.org/10.3390/agriculture15161780

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