A detailed study on genetic diversity, antioxidant machinery, and expression profile of drought-responsive genes in rice genotypes exposed to artificial osmotic stress

Bhattacharjee, Bijoya; Ali, Akib; Rangappa, Krishnappa; Choudhury, Burhan U.; Mishra, V. K.

doi:10.1038/s41598-023-45661-8

Download PDF

Article
Open access
Published: 26 October 2023

A detailed study on genetic diversity, antioxidant machinery, and expression profile of drought-responsive genes in rice genotypes exposed to artificial osmotic stress

Bijoya Bhattacharjee¹^na1,
Akib Ali¹^na1,
Krishnappa Rangappa¹,
Burhan U. Choudhury² &
…
V. K. Mishra³

Scientific Reports volume 13, Article number: 18388 (2023) Cite this article

868 Accesses
1 Citations
1 Altmetric
Metrics details

Subjects

Abstract

Seasonal variations in rainfall patterns, particularly during sowing, early growing season, and flowering, drastically affect rice production in northeastern India. However, sensitivity to drought stress is genotype-specific. Since 80% of the land in this region is used for rice production, it is crucial to understand how they have adapted to water stress. This study evaluated 112 rice genotypes grown in NE India for seed germination percentage and seedling development under PEG-mediated drought stress. Among the rice genotype, Sahbhagi dhan, RCPL-1-82, Bhalum-3 and RCPL-1-128 showed drought-tolerant traits, while Ketaki Joha, Chakhao, Chandan, RCPL-1-185 and IR-64 were the most drought-sensitive rice genotypes. Drought-tolerant rice also showed significantly higher seed germination potential, proline content, antioxidant activity and expression of drought-responsive genes than drought-sensitive rice genotypes. A similar expression pattern of genes was also observed in the rice genotype treated with a 50% water deficit in pot culture. In addition, drought stress reduced the pollen fertility and yield per plant in sensitive rice genotypes. Molecular markers associated with drought stress were also used to characterize genetic diversity among the rice genotypes studied.

Differential selection of yield and quality traits has shaped genomic signatures of cowpea domestication and improvement

Article 22 April 2024

An pair of an atypical NLR encoding genes confer Asian soybean rust resistance in soybean

Article Open access 17 April 2024

Climate change impacts on crop yields

Article 14 November 2023

Introduction

Rice (Oryza sativa L.) belongs to the family Poaceae (Gramineae) and is amongst the three strategic crops that form the staple diet of more than half of the world’s population. The global cultivation of rice has been evaluated to be about 850 million tons, and the rice-growing area is estimated to be 256 million hectares. Asia is the leading producer of rice in the world, accounting for around 90% of the world’s crops¹. Over 75% of global production is consumed by people in Asian countries, and, thus, rice is of great importance to the food security of Asia in precise. Northeast India alone harbours thousands of indigenous rice cultivars/genotypes and is considered the second largest centre of rice origin². Indigenous genotypes are known to constitute a rich beneficial gene pool. Although these genotypes are enriched with nutritive properties, they are susceptible to various biotic and abiotic stresses. In contrast to several other crops, rice is quite vulnerable to dryness during germination, the early stages of seedling growth and flowering stages. Due to the lack of water, severe reductions in seedling germination and growth are seen during drought stress³.

Drought causes many physiological and biochemical modifications at levels ranging from sub-cellular to the whole plant. One such modification is the production of reactive oxygen species (ROS), which are harmful to plant metabolism. ROS production is controlled by various enzymatic and non-enzymatic antioxidant defence systems, including catalase (CAT), ascorbate peroxidase (APX), proline oxidase (POX), superoxide dismutase (SOD), monodehydro ascorbate reductase (MDHAR), dehydroascorbate reductase (DHAR), and glutathione reductase (GR), while non-enzymatic catalysts include ascorbate, glutathione, carotenoids, phenolic compounds, proline, glycine betaine, and sugars. Although several QTLs have been characterized for drought tolerance/sensitivity in rice, the expression of a particular gene is genotype and habitat-specific^4,5,6. Therefore, recognizing the biochemical mechanisms associated with rice drought stress resistance is still a significant obstacle to the early identification of an effective trait that would aid plant breeders and, in particular, breeding programs. Further, the accumulation of compatible solutes, such as proline and glycine betaine, represents a basic strategy used by plants to protect against osmotic stress; proline is also reported to play a positive role in maintaining membrane integrity under various stresses^{7, 8}. Usually, proline accumulation is considered to be higher in stress-tolerant plants than in sensitive plants⁹. Additionally, it is evident that drought influences metabolite levels differently in a genotype-dependent manner. These abiotic stress conditions also influence plant growth patterns/regulations and create disparities in plant mineral nutrition, resulting in secondary consequences.

Several biotechnological tools and techniques have been well established to identify the diversity and crucial mechanism of plant defence against stressors. Molecular markers are useful tools for carefully characterizing and differentiating genotypes and determining their evolutionary relationships as they are rapid, reliable, and require less DNA. Simple Sequence Repeats (SSRs) are highly polymorphic, more reproducible, co-dominant, and dispersed across the genome¹⁰. A correlation analysis between the genotype segregation via molecular markers with the drought-induced parameters furthermore validates the evolutionary links between potent stress tolerant/sensitive genotypes. Analyses of rice plants in response to drought stress and recognition of drought tolerance mechanisms for the production of drought-adapted crops will potentially result in higher crop yields per unit of water input.

Since the selection of plants under field conditions is tedious due to low heritability, the time required, and the interaction between environmental factors and genotypes, the utility of rice drought-tolerant inside a maintained in vitro condition may be useful to improve the selection efficiency and accuracy in terms of drought tolerance in genotypes which is not affected by environmental factors. Polyethylene glycol (PEG), a non-ionic, non-plasmolyzing and high-molecular-weight compound imitates drought stress in cultured cells similar to that observed in the cells of intact plants affected by drought conditions^{11, 12}. Therefore, we used PEG-6000 to create an artificial osmotic stress and its impact on the rice genotype. Further, to check whether the results observed from PEG-mediated drought stress shows similar pattern with that of under the soil culture, we conducted a separate experiment of well-watered and 50% water stress conditions for selected rice genotypes.

Precisely, the objectives of this research were to characterise the effect of artificial drought stress on antioxidant properties and assess the genetic diversity of the local rice genotype grown in Northeast India using drought-linked SSR and RAPD markers to find out potent drought-tolerant genotype. To understand the drought-responsive machinery, we also attempted to profile the expression pattern of several drought-responsive genes in the roots, shoots and young panicles of contrasting drought-tolerant/sensitive rice genotypes.

Results

Effect of PEG-mediated drought stress on seed germination, shoot and root length and relative water content

Effect of PEG induced drought stress on seed germination percentage revealed significant differences (p < 0.05) between studied rice genotype. As shown in Table 1, while 100% seed germinated in the control (0% PEG), seed germination (%) significantly decreased with further increase in PEGconcentration in the studied rice genotype. Amongst the studied rice genotype Sahbhagi Dhan, RCPL-1-82, Bhalum-3, RCPL 1-128, Baglami and Bhutmari showed comparatively higher seed germination (%) under PEG stress. In contrast Ketaki Joha, Chakhao, Chandan, RCPL-1-185 and IR-64 showed the lowest seed germination (Table 1) under PEG-stress. Although, there was no significant difference in seed germination percentage at different concentrations of PEGtreatment of Sahbhagi Dhan, RCPL-1-82, Bhalum-3 and RCPL-1-128; in contrast, Ketaki Joha, Chakhao amubi, Chandan, RCPL-1-185 and IR-64 seed germination significantly decreased with increase in PEGpercentage (Fig. 1, Table 1). Similarly, root and shoot length (cm) were significantly decreased with increasing PEGconcentrations. Sahbhagi Dhan, RCPL-1-82, Bhalum-3 and RCPL-1-128 also showed higher shoot and root length as compared to Ketaki Joha, Chakhao amubi, Chandan, RCPL-1-185 and IR-64 (Fig. 1). However, shoot to root ratio significantly increased with increase in PEGconcentration in all studied rice genotype except Sahbhagi Dhan, RCPL-1-82, Bhalum-3 and RCPL-1-128. The relative water content studied in the present investigation also revealed similar pattern among different rice genotype (Supplementary table 1). While in control, shoot RWC ranged from 79 to 86%; 70 to 85%, 67 to 84% and 62 to 82% RWC was observed in 10% PEG, 20% PEGand 30% PEGrespectively. In roots, RWC ranged from 72 to 84% in control, 67 to 82% at 10% PEG, 65 to 80% at 20% PEGand 57 to 80% in 30% PEGtreatment. Sahbhagi dhan and RCPL-1-82 showed comparatively high RWC in root and shoots than other genotypes. However, no significant difference of RWC was observed in the Sahbhagi Dhan, RCPL-1-82 at different PEGconcentration. In contrast, RCPL-1-185 and IR-64 showed significant reduction in RWC in both root and shoots. Furthermore, roots of Sahbhagi Dhan, RCPL-1-82, Bhalum-3 and RCPL-1-128 stained light blue as compared to Chakhao amubi, Chandan, RCPL-1-185 and IR-64 under PEG-treatment (Fig. 1). Control devoid of PEG did not change colour after EVANs blue staining.

Table 1 Effect of PEG-mediated drought stress on seed germination percentage of 112 rice genotype/lines grown in NE-India; each value is representation of mean ± sd, N = 9 and different letters along the column are statically significant at p < 0.05.

Full size table

Diversity analysis of rice genotype using SSR and RAPD marker

Preliminary genetic relationship among 112 studied rice genotype was assessed with 57 previously reported drought stress tolerance linked Simple Sequence Repeat (SSR) and 5 Random Amplified Polymorphic DNA (RAPD) markers. A total of 1395 alleles were scored using SSR and RAPD marker. Out of which 219 (15.7%) were monomorphic and 1176 (84.3%) were polymorphic. A representing banding pattern of studied rice genotypes were shown in Fig. 2. A summary of the molecular markers used in the present study were shown in the Supplementary Table 2. In RAPD, OPB-10 showed highest range of allele size; while in SSR marker, RM3 shows more polymorphism and maximum number of alleles as compared to other primer and RM11 generated least number of alleles (Fig. 2). RM3233 showed highest range of allele size (165–269 bp). The allele frequency ranged from 0.25 to 0.71 with an average value of 0.46. The polymorphism information content (PIC) ranged from 0.48 to 0.93 averaging 0.77 (Supplementary Table 2). While RM3 showed the highest PIC value, RM204 showed the lowest PIC value, which indicates the potential use of these markers in genotyping and diversity analysis study. The model-based population structure analysis performed with STRUCTURE software revealed highest K value of 3 (Fig. 2). A phylogenetic tree generated using NTSYSpc 2.10 based on similarity index SM coefficient divided the studied rice genotype into two clades (Supplementary Fig. 1). While clade-I is further dived into three clusters. Within Cluster-I, Sahbhagi Dhan, Bhalum-3, RCPL-1-82, Banglami and V-Dhan which showed high seed germination percentage and RWC formed one sub-group; In cluster-II, Full badam, Ketaki joha and RCPL-1-185 which also showed high RWC and seed germination % formed one group. On the other hand, Clade-II includes RCPL-1-128, chandan and IR-64 which showed drought-sensitive characteristics. The population of the 112 investigated rice genotype was found to be genetically diverse from each other.

Based on the physio-morphological traits and genetic diversity analysis, we further selected four rice genotypes showing two contrasting characters i.e., putative drought-tolerant (Sahbhagi Dhan and RCPL-1-82) and putative drought-sensitive (RCPL-1-185 and IR-64) for antioxidant profiling and molecular profiling of drought-sensitive genes.

Effect of PEG-stress on proline, H₂O₂, AaS, DHA and total ascorbate content in drought-tolerant/sensitive rice

As shown in Table 2, drought-tolerant and sensitive rice genotype showed significant differences in the accumulation of proline, H₂O₂, AaS content, DHA content and total ascorbate in shoots as well as roots on 15th days after PEG treatment. While accumulation of proline and H₂O₂ in the roots and shoot of Sahbhagi Dhan and RCPL-1-82 enhanced with increase in PEG concentration, the same showed highest accumulation at 10% PEG treatment in roots and shoots of RCPL-1-185 and IR-64, thereafter declined with further increase in PEG concentration. Sahbhagi Dhan and RCPL-1-82 showed highest abundance of proline at 30% PEG treatment, while IR-64 and RCPL-1-185 showed highest proline content at 10% PEG treatment. Similarly, Sahbhagi Dhan and RCPL-1-82 also showed significantly higher accumulation of H₂O₂ as compared to RCPL-1-185 and IR-64. Unlike proline and H₂O₂ content, while AaS content declined with increasing PEG concentration, DHA content and total ascorbate increased in the roots and shoot tissues of all studied rice genotype at 0% to 30% PEG treatment. However, there were significant differences between the drought-tolerant (Sahbhagi Dhan and RCPL-1-82) and drought-sensitive (RCPL-1-185 and IR-64) rice genotypes.

Table 2 Effect of PEG mediated drought stress on proline content (µmol g⁻¹ dry weight), H₂O₂ (µmol g⁻¹ fresh weight), AaS content (nmol g⁻¹ fresh weight), DHA content (nmol g⁻¹ fresh weight) and total ascorbate (nmol g⁻¹ fresh weight).

Full size table

Antioxidant enzyme activity in drought-tolerant and sensitive rice under PEG-stress

To decipher the comparative estimation of redox potential of antioxidants between drought-tolerant and sensitive rice genotypes, we performed antioxidant enzyme activity using six different enzyme assays viz. MDHAR, DHAR, GPX, GR, SOD and CAT activity assay. As shown in Fig. 3, antioxidant enzyme activity assays of MDHAR, DHAR, GPX and GR revealed a similar pattern of enzyme activity in the rice genotype treated with different concentration of PEG. In all four assays, enzyme activity was found higher at 10% PEG treatment as compared to control. However, enzyme activity declined with further increase in PEG concentration (10% to 30%) in the root and shoots of all four rice genotype studied. The rate of declining enzyme activity in drought-sensitive rice genotypes (RCPL-1-185 and IR-64) was much higher as compared to drought-tolerant rice genotype (Sahbhagi Dhan and RCPL-1-82). Whereas SOD activity increased with increase in PEG concentration in the root and shoot of all four rice genotype, CAT activity decreased from control to 30% PEG treated plants. While shoot showed significantly higher SOD and MDHAR activity, root showed significantly higher DHAR, GR, CAT and GPX activity. Additionally, Sahbhagi Dhan and RCPL-1-82 showed significantly much higher antioxidant activity in both roots and shoots in all PEG treatments as compared to RCPL-1-185 and IR-64.

Identification and expression pattern of drought-responsive genes in drought-tolerant/sensitive rice genotypes under PEG-stress

To understand the molecular mechanism underlying drought sensitivity in drought-tolerant/sensitive rice, we first identified 12 candidate reference genes viz. DREB1, p5cs, rbcs, AAO1, SOD, WRKY11, WRKY114, SDR1, NAC9, ZFP252, ZFP182 and DRAP1 which are directly or indirectly linked to drought stress based on available literature. The expression profile of these genes showed a significant difference between the tolerant rice genotype and the sensitive rice genotype at different PEG concentrations (Fig. 4). Expressions of DREB1, p5cs, SOD and WRKY11 were significantly induced with increasing PEG treatment in the roots and shoots of Sahbhagi Dhan and RCPL-1-82. In contrast, expression of DREB1 and p5cs showed the highest at 10% and 20% PEG respectively in the shoot and roots of RCPL-1-185 and IR-64, thereafter declined in expression. While expression of SOD and WRKY11 increased with increasing PEG concentration in root and shoots of Sahbhagi Dhan and RCPL-1-82. However, it was induced weakly by the PEG-mediated drought stress in RCPL-1-185 and IR-64. Although there was no significant difference in expression of DREB1, p5cs, SOD and WRKY11 between RCPL-1-185 and IR-64, it is clearly visible that DREB1, p5cs SOD and WRKY11 expressed much higher in Sahbhagi Dhan and RCPL-1-82 as compared to RCPL-1-185 and IR-64. Similarly, while expression of WRKY114 decreased in the tolerant rice line, it was induced with increasing PEG stress in the sensitive rice line. On the other, we did not find a significant difference in the expression of SDR1 in both root and shoot tissues of treated and control plants. While the expression of NAC9, ZFP252, ZFP182, and DRAP1 was upregulated with increasing PEG-mediated drought stress in Sahbhagi Dhan and RCPL1-82, these genes showed downregulation of expression in RCPL-1-185 and IR-64.

Physio-molecular response of rice under drought stress in pot culture during seedling stage

An experiment was conducted on pot culture to check if the result acquired from PEG-mediated drought stress correlates with the drought stress under pot (soil) culture. Four rice genotypes namely Sahbhagi Dhan, RCPL 1-82, RCPL-1-185 and IR-64 were subjected to drought stress with two treatments namely Well-watered (Control; 100% water available) and 50% water deficit treated (Supplementary Fig. 2). The result revealed that RWC significantly reduced in root and shoots of RCPL-1-185 and IR-64 under drought as compared to control. Proline content significantly increased in Sahbhagi Dhan and RCPL-1-82 as compared to RCPL-1-185 and IR-64 under drought stress (Fig. 5).

Furthermore, the expression of selected drought-responsive genes such as DREB1, p5cs, rbcs, AAO1, SOD, WRKY11, WRKY114, SDR1, NAC9, ZFP252, ZFP182 and DRAP1 in the root and shoot tissues of Sahbhagi Dhan, RCPL-1-82 RCPL-1-185 and IR-64 also revealed similar pattern of expression as shown under PEG-mediated stress. While DREB1, p5cs, rbcs, AAO1, SOD, WRKY11, NAC9, ZFP252, ZFP182 and DRAP1 upregulated in the root and shoot tissues of Sahbhagi Dhan and RCPL-1-82, WRKY114 gene showed high expression in root and shoot of RCPL-1-185 and IR-64 under drought stress (Fig. 6).

Effect of drought stress on pollen fertility, rice yield and expression of drought-responsive gene under pot culture

Pollen fertility is an important aspect in screening potent drought-tolerant and sensitive genotypes as it directly impacts seed setting and grain yield. The microscopic analysis of pollens stained with Potassium Idode stain (I₂-KI) revealed a significant reduction in the pollen fertility percentage in drought-stressed RCPL-1-185 and IR-64 than in control (Fig. 5). No significant differences were observed in Sahbhagi Dhan and RCPL-1-82. As shown in Supplementary Fig. 6, Sahbhagi Dhan and RCPL-1-82 showed round-shaped, dark-coloured pollen under both control and drought stress, while RCPL-1-185 and IR-64 showed very light-coloured and broken pollen compared to control. Additionally, the number of tillers and filled grains decreased in drought-stressed RCPL-1-185 and IR-64 as compared to the control. While, less than a 5% decrease in filled grains was observed in Sahbhagi Dhan and RCPL-1-82, in contrast, a > 75% decrease in filled grains per panicle was observed in RCPL-1-185 and IR-64 (Fig. 5).

Further, to check whether the pollen fertility and grain yield correlate with the expression of previously identified drought-responsive genes between different rice genotypes, we checked transcript abundance of DREB1, LOC_Os12g04500, LOC_Os02g50970, LOC_Os12g26290, LOC_Os05g08480, MYB80 and WRKY114 genes in the young panicle (Fig. 7). The results revealed significant reduction in expression of LOC_Os12g04500, LOC_Os02g50970, LOC_Os12g26290 and MYB80 genes in treated RCPL-1-185 and IR-64 (drought-sensitive) than in Sahbhagi Dhan and RCPL-1-82 (drought-tolerant). While LOC_Os05g08480 and WRKY114 genes are upregulated in the young panicle of RCPL-1-185 and IR-64 under drought stress.

Discussion

Abiotic stresses like droughts drastically affect crop performance by impairing growth, development, and productivity. However, the most effective way to alleviate drought stress in plants is by breeding drought-tolerant cultivars. In the past few decades, rice breeders have developed many drought-tolerant rice genotypes to improve the plant’s resilience under drought conditions¹³. However, the effectiveness of any transgenic/hybrid variety depends on the adaptability to a particular habitat or environment. The primary way to achieve such a goal is by screening germplasm in the field and as well as greenhouse conditions. Since multiple factors affect the performance of a crop in the field condition, therefore, a well-maintained in-house condition may be efficient in finding better experimental results. Although drought affects the life cycle of any plant; seed germination stages, seedling stages and reproductive stages are the most critical stages that determine the growth and yield respectively^{14, 15}. According to the Indian Meteorological Department of India (IMD), NE-India has received 31% less rainfall since 2018. NE-India has also been witnessing a series of weather anomalies, which have directly affected the major staple crop of this region i.e., rice. Therefore, in this study, 112 rice genotypes grown in NE-India were taken into consideration for a detailed analysis against PEG-mediated drought stress and further validated with the field/pot culture study. The primary goal of this study was to identify some potent drought-tolerant cultivars specific to NE-India and analyse of detailed mechanism underlying drought tolerance traits. We included two rice genotypes developed by the International Rice Research Institute (IRRI) namely Sahbhagi Dhan as a positive control (drought-tolerant released genotype) and IR-64 as a negative control (drought-sensitive genotype). Our preliminary study on the effect of PEG-mediated drought stress on seed germination and relative water content showed Sahbhagi Dhan, RCPL-1-82, Bhalum-3, RCPL-1-128, Baglami and Bhutmari as potent drought-tolerant rice genotype. The increasing PEG concentration did have much impact on germination and RWC on these plants as compared to Ketaki Joha, Chakhao, Chandan, RCPL-1-185 and IR-64. These variations in phenotypic and physiological characteristics could be attributed to genotype-specific stress tolerance mechanisms¹⁵. Evan’s dye staining of the roots of the selected rice line confirmed the enhanced accumulation of antioxidants in the tolerant rice genotype as compared to the sensitive genotype.

Our study on molecular profiling using drought stress-linked markers for the studied genotypes showed a high degree of diversification. The identified allelic variants in the form of amplified product size (molecular weight) for each SSR and RAPD marker were documented to find out the allele mining set for the linked markers of the studied genotypes in relation to drought stress tolerance. Since SSR markers are abundant in the rice genome, co-dominance, and have a high polymorphism rate, they are widely utilised in rice genetics¹⁶. Although RAPD markers are less reproducible; however, RAPD technology still has several key benefits, including its suitability for work on anonymous genomes, applicability to small amounts of DNA, and low cost¹⁷. Therefore, we selected more SSR markers^18,19,20 and only a few RAPD markers^{21, 22} to check if they would produce some significant results. The result revealed that RAPD marker OPB-10 and SSR marker RM3, RM3233 were the best-suited markers to check genetic diversities under PEG-mediated drought stress in rice as these markers showed the highest range of polymorphisms and maximum number of alleles as compared to other primers. It was interesting to see that most of the rice genotypes that showed drought-tolerant/sensitivity using phenotyping and physiological screening also formed separate groups in the phylogenetic tree generated via NTSYSpc-based SSR and RAPD marker. These preliminary results indicate a possible genetic linkage between the genotypes. Since the markers used are linked to drought/water stress-related genes, the result could indicate that each group may share common alleles or haplotypes of the water stress–related genes involved. However, further research is needed to establish a proper linkage between the genotypes. Based on the cumulative results and their sensitivity to drought stress, studied rice genotypes can be categorized into three groups such as tolerant (Group I), moderately sensitive (Group II) and highly sensitive (Group III). While Group I includes Sahbhagi Dhan, RCPL-1-82, Bhalum-3, RCPL-1-128, Group III includes Ketaki Joha, Chakhao amubi, Chandan, RCPL-1-185 and IR-64 and group-II includes the rest of the studied genotype (Supplementary Table 5). Our results showed a higher drought-tolerance capacity of RCPL-1-82 apart from Sahbhagi Dhan and Baglami. Our results of sensitive rice are in conformity with the Sahoo et al.²³. They reported Ketaki joha and Chandan as among the sensitive rice genotypes. However, we also found that IR-64 and RCPL-1-185 were more drought-sensitive than Ketaki joha and Chandan. We observed purple rice var. Chakhao amubi is moderately sensitive to drought stress^{24, 25}. However, further in-depth research underlying the molecular mechanism of drought tolerance/sensitivity in pigmented rice is still required. The high level of drought stress inhibited seed germination (%), shoot and root length and RWC. This response of growth inhibition could be attributed to low osmotic potential, decreased wall extensibility, and decreased cellular expansion²⁶. In addition, while the proline content in Sahbhagi Dhan and RCPL-1-82 increased sharply with an increase in drought level via PEG stress or in pot culture, it declined in RCPL-1-185 and IR-64. Accumulation of proline under drought stress protects cells by balancing the osmotic potential of cytosol with that of vacuoles²⁷; therefore imbalance in proline content may have also affected the growth and sensitivity to drought stress between the studied plants. It was observed that rice varieties with improved resilience to abiotic stress have higher rates of proline biosynthesis²⁸. Elevation in superoxide anion production has been reported to be associated with increased drought stress in many plants²⁹. While we observed enhanced H₂O₂ content in Sahbhagi Dhan and RCPL-1-82, the same declined in RCPL-1-185 and IR-64. This phenomenon could be attributed to a breakdown of H₂O₂ into OH and OH⁻ in RCPL-1-185 and IR-64³⁰.

Drought stress induces plant defence mechanisms to protect themselves from the negative effects of oxidative stress. Plants with higher levels of induced antioxidants have better resistance and tolerance to oxidative stress³¹. ABA production also plays a significant role by enhancing its production during drought; salinity, chilling, and freezing stress³². High drought conditions also promoted the antioxidant enzyme activity viz. SOD, GR, MDHAR, DHAR, and CAT activity in the tolerant rice genotype (Sahbhagi Dhan and RCPL 1-82) as compared to the sensitive genotype (RCPL-1-185 and IR-64). Our results are in conformity with Sharma and Dubey³³ and Sahoo et al.²³. They have also reported that drought-tolerant rice varieties showed higher antioxidant enzyme activity than sensitive rice. According to Mishra and Panda³⁴, increasing the expression of the antioxidant system can raise rice's tolerance to drought stress and act as a strategy against oxidative stress.

Our sub-experiment of 50% water deficit on these four rice genotypes revealed that drought stress reduced the tiller numbers, and pollen fertility, which ultimately affected the seed setting and reduction in grain yield in sensitive genotype (RCPL-1-185 and IR64), while no significant differences were observed in tolerant rice genotype (Sahbhagi Dhan and RCPL-1-82). Our results are in concurrence with Rang et al.³⁵, Praba and Thangaraj³⁶.

Recently, a number of drought-linked genes and transcription factors have been characterized in different plants^{37, 38}. It is known that the DREB1 gene is hypersensitive to ABA signalling and a positive regulator of heat, salt, and drought tolerance in rice³⁹. While P5CS is known to promote root growth and plays a significant role in plant drought resistance by enhancing proline biosynthesis^{40, 41}. To find out whether the proline accumulation and antioxidant enzymes activity is regulated by the expression of respective genes, we carried out expression profiles of DREB1, p5cs, SOD and WRKY genes. PEG-mediated osmotic stress also induced expressions of drought-tolerant genes and transcription factors such as DREB1, p5cs, SOD, and WRKY. The expression profile of these genes under PEG-mediated osmotic stress was correlated with drought stress under pot culture. These results established Sahbhagi Dhan and RCPL-1-82 potent drought-tolerant rice line as compared to other studied varieties. In higher plants, WRKY TFs are expressed during environmental stresses, seed germination, seed dormancy, and other growth-related events^{42, 43}. The WRKY proteins also play key functions in immune response mechanisms during mechanical damage and wounding⁴⁴ and stress like drought stress⁴⁵, heat shock stress⁴⁶ etc. According to Wu et al.⁴⁷, overexpression of WRKY11 enhanced temperature and drought tolerance in the transgenic rice genotype. We have also found that osmotic stress enhanced the expression of WRKY11 in the tolerant rice line; on the contrary, the expression of WRKY114 was induced due to enhanced osmotic stress in the sensitive line. This indicates the possible role of WRKY114 as a negative regulation of drought stress in rice. Bo et al.⁴⁸ and Song et al.⁴⁹ have also reported overexpression of Maize WRKY114, a GA-responsive gene that negatively regulated salt and drought tolerance in transgenic rice. OsWRKY114 limits rice stomatal closure, which negatively impacts the plant’s ability to withstand drought⁴⁸. Apart from these transcription factors expression of SOD, CAT, and GPX also determines the accumulation of respective antioxidants that enhances defence mechanisms against ROS⁴⁵. On the other hand, there was no noticeable difference in the expression of SDR1. While NAC9, ZFP252, ZFP182, and DRAP1 expression increased in Sahbhagi Dhan and RCPL-1-82 with increasing PEG-mediated drought stress, their expression decreased in RCPL-1-185 and IR-64. Hu et al.⁵⁰ reported the role of OsNAC9 in increasing grain yield and enhancing root diameter in drought-tolerant rice lines. Similarly, overexpression of ZFP252 and ZFP182 also conferred multiple stress tolerance such as drought and salt tolerance in transgenic rice⁵¹. OsDRAP1, a gene similar to DREB2, is also reported to confer drought tolerance in rice by Huang et al.⁵². Our results also support the involvement of DEGs in drought tolerance or sensitivity during flowering stages in rice^{53, 54}. In the current experiment of 50% water deficit under pot culture, the expression of LOC_Os12g04500 (response regulator receiver domain-containing protein) and LOC_Os12g26290 (alpha-DOX2), which are also known as the core of the jasmonic acid (JA) signalling pathway, was significantly increased under a prolonged drought period. Additionally, it has been shown that JA signalling genes function at key stages of drought stress⁵⁵. Five genes, DREB1, LOC_Os12g04500, LOC_Os02g50970, LOC_Os12g26290, and MYB80, were found to have upregulated expression in drought-tolerant genotypes (Sahbhagi dhan and RCPL-1-82) and downregulated expression in drought-sensitive genotypes (IR64 and RCPL-1-185), indicating a positive relationship between these genes and drought tolerance. Pan et al.⁵⁶ reported that MYB80 plays a key role in regulating anther development and enhancing pollen fertility. In sensitive rice genotypes, the genes WRKY114 and LOC_Os05g08480 (cytokinin-O-glucosyltransferase-1) showed upregulation; however, in the tolerant rice genotypes, the same genes showed downregulation. Similar results were also reported by Ahmad et al.⁵⁷ in the young panicle of sensitive/tolerant rice genotypes.

Conclusion

Our experiment on the effect of artificial osmotic stress via PEG-mediated and soil/pot culture stress established Sahbhagi Dhan and RCPL-1-82 as potent drought-tolerant rice genotypes as compared to other studied genotypes. We found multiple factors involved in conferring drought tolerance in rice at both metabolite and molecular levels. This study formed the preliminary base for selecting drought-tolerant rice collected from North-East India. The characterized rice genotypes may further be utilized for genome editing or rice breeding programs.

Materials and methods

Plant material and PEG treatment

Healthy seeds of 112 rice genotypes (Supplementary Table 4) were collected from different locations in North-East India in the year 2015–2016. Pure genotypes were grown and maintained in the greenhouse of the Department of Biotechnology, Division of Crop Science, ICAR Research Complex for NEH region, Umiam, Meghalaya, India.

In this experiment, these rice genotypes including Sahbhagi Dhan (drought-tolerant control) and IR-64 (drought-sensitive control) were subjected to osmotic stress. Healthy grains of each genotype were germinated on the individual Petri dishes. To induce osmotic stress, PEG-6000 (Merck-Schuchardt, Hohenbrunn, Germany) was used. The impact of PEG-induced osmotic stress was investigated using four treatments—T0 = 0% PEG (control condition), T1 = 10% PEG (− 0.19 MPa), T2 = 20% PEG (− 0.69 MPa), and T3 = 30% PEG (− 1.12 MPa) and applied in accordance with a completely randomised design⁵⁸. The seed germination test was measured on the 7th DAT (Day After Treatment). After 1 week, seedlings with synchronized leaf emergence, healthy roots, and shoots were hydroponically grown (5 × Yoshida medium; diluted from 10 × Yoshida medium) in individual trays under the same PEG treatment for an additional 8 days⁵⁸. Ten replicates were maintained for each genotype per treatment. We evaluated the water potentials prior to and following the addition of PEG to determine the osmotic stability of the nutrient solutions. Individual plant of each genotype under each treatment was taken into account for the physio-molecular analysis of root and shoot tissues, making each plant a separate experimental unit. pH was adjusted at 6.0 ± 0. 2 °C. Antioxidant activity and gene expression profiles on root and leaf tissue were conducted on the 15th DAT.

To check the expression profile of genes under PEG-mediated drought stress correlates with field experiments, a separate experiment was conducted on pot culture with a 50% water deficit^{59, 60} for four genotypes. A control (well-watered) was maintained for each genotype. Water was given on each pot (50% deficit and control) at 3–4 days intervals until seed set. Root and shoot samples were harvested on the 15th day after germination under control and drought-stressed plants. The entire experiment was conducted inside the greenhouse of the Biotechnology Department of ICAR-Umiam, maintained at 28 ± 2 °C temperature with a photoperiod of 16 h of light and 8 h of darkness.

Percentage of seed germination and ratio of shoot to root length

The percentage of seed germination was measured after one week of treatment with PEG. The percentage of germination was calculated as follows:

$${\text{Germination}}\;(\% ) = \frac{{{\text{Number}}\;{\text{of}}\;{\text{germinated}}\;{\text{seed}}s}}{{{\text{Number}}\;{\text{of}}\;{\text{inoculated}}\;{\text{seeds}}}} \times 100.$$

Root and shoot length (cm) and root to shoot ratio were measured on 15th day after treatment.

Estimation of relative water content (RWC)

Relative water content (RWC) was estimated in the root and shoot tissues of control and PEG-treated rice genotype on 15th DAT as described by Baldoni et al.⁶¹. Briefly, Relative Water Content (RWC) was determined by weighing the fresh tissues (FW), followed by floating it on deionized water for 6 h under dim light at room temperature. Fully pompous tissues were re-weighed (PW), oven dried and again weight (DW) was measured. RWC was calculated using the formula:

$${\text{RWC }} = \, \left( {{\text{FW }} - {\text{ DW}}} \right)/\left( {{\text{PW }} - {\text{ DW}}} \right) \, \times { 1}00,$$

where FW Fresh weight, DW Dry weight and PW Pompous weight

Histochemical study using EVANs blue

Roots from the PEG-treated rice genotype were collected and stained with EVANs blue (Sigma-Aldrich) according to the method described by Vijayaraghavareddy et al.⁶². Briefly, 0.25 g of Evan’s blue dye was dissolved in 100 ml of 0.1 M CaCl₂ solution at pH 5.6. Control and PEG-treated roots were excised and treated with EVANs blue for 30 min followed by rinsing with deionized water until the excess dye was removed. Qualitative estimation of EVANs staining performed under the light microscope.

Pollen fertility test

Five mature spikelets from three panicles each of Sahbhagi dhan, RCPL-1-82, RCPL-1-185 and IR64 were collected in the morning time (6–7 am) before anthesis. The collected samples were immediately fixed in FAA solution (formaldehyde: ethanol: acetic acid in the ratio of 1:18:1). Anthers were gently crushed, stained using I₂-KI solution and observed under an optical microscope (LEICA). Circular dark-stained pollens were considered viable pollen, while irregular light-stained/destained pollens were considered infertile.

Estimation of total proline, hydrogen peroxide (H₂O₂) and ascorbate content

Total Proline was extracted according to the method of Dien et al.²⁸ and estimated spectrophotometrically according to the method of Bates et al.⁶³. Briefly, 100 mg root and shoot tissues were ground into fine powders using mortar and pestle. 10 ml of 80% ethanol was mixed with a 100 mg powder sample and heated in the water bath at 80 °C for 45 min. The extracted materials were filtered and used for proline estimation. 1 ml of extract was mixed with 200 µl of acid ninhydrin and 500 200 µl of glacial acetic acid in a test tube. The mixer was boiled in the water bath for 45 min followed by being cooled in an ice bath for 5 min. 1 ml of toluene was added and the mixer was vortexed. The upper layer was measured at 520 nm using toluene as a blank. Proline content was determined using the proline (Sigma-Aldrich) standard curve at 520 nm and expressed as µmol g⁻¹ DW.

H₂O₂ concentration was measured colorimetrically as described by Jana and Choudhuri⁶⁴.

H₂O₂ was extracted by homogenizing 100 mg tissues with 1 ml of phosphate buffer (pH 6.5) at low temperature followed by centrifugation at 6000×g for 25 min at 4 °C. The supernatant was taken in a fresh tube made up of 1 ml with phosphate buffer. H₂O₂ content was estimated by mixing 500 µl extract with 500 µl of 0.1% titanium sulphate in 20% H₂SO₄ (v/v) followed by centrifugation at 6000×g for 15 min at 4 °C. The yellowish colour intensity of the supernatant was measured at 410 nm using the H₂O₂ (Sigma-Aldrich) standard curve. H₂O₂ concentration was calculated using the extinction coefficient 0.28 mM⁻¹ cm⁻¹ and expressed as µmol g⁻¹ tissue fresh weight.

Reduced ascorbate (AsA), dehydroascorbate (DHA), and total ascorbate (AsA + DHA) were extracted and quantified spectrophotometrically according to the method of Law et al.⁶⁵.

The assay is based on AsA in an acidic solution reducing Fe3+ to Fe2+. The Fe2+ then combines with bipyridyl to produce a complex that absorbs at 525 nm and is coloured pink. The conversion of DHAs to AsA by dithiothreitol yields the measurement of total ascorbate (AsA + DHAs).

100 µl sample extract was mixed with 200 µl of 10% (w/v) trichloroacetic acid followed by standing in the ice bath for 5 min. After adding 10 µl NaOH (1 M), the mixture was centrifuged for two minutes in a Microfuge. While 100 µl supernatant was mixed with 100 µl of water and 150 mM NaH₂PO₄ buffer (pH 7.4). Another 100 µl supernatant was mixed with 100 µl of l 0 mM-dithiothreitol, and 100 µl of 0.5% (w/v) N-ethylmaleimide and kept at room temperature for 15 min. Then, 200 µl 1% (w/v) trichloroacetic acid, 200 µl 44% (v/v) H₃PO₄, 200 µl 4% (w/v) bipyridyl in 70% (v/v) ethanol, and 100 µl 3% (w/v) FeCl₃ were added to each tube. Following vortex mixing, samples were incubated for 60 min at 37 °C and AaS was measured at 525 nm. 5% (w/v) m-phosphoric acid was used to develop standards for AsA and DHA in the range of 0–10 mM. DHA was calculated for each sample based on the variances between total ascorbate and AsA.

Antioxidant enzymes assay

SOD was extracted by homogenizing 500 mg of fresh root and shoot samples in 5 ml of a buffer solution containing 100 mM potassium phosphate buffer (pH 7.5), 1.0 mM EDTA, 0.1 mM Triton X-100, and 2% polyvinylpyrrolidone (PVP). After centrifugation at 22,000×g for 10 min at 4 °C, the supernatant was dialyzed in cellophane membrane tubes against the cold extraction buffer. SOD was then measured by the method of Mishra and Fridovich⁶⁶ by observing epinephrine-dependent adrenochrome formation at 475 nm in a UV–Vis spectrophotometer. The Extraction media used for GR, DHAR and MDHAR were similar to SOD. GR activity assay was estimated using the method described by Foyer and Halliwell¹⁰ using a reaction mixture of 80 mM Tris–HCl buffer (pH 8.5), 2.5 mM oxidized glutathione (GSSG), 1.5 mM EDTA, and 100 µl enzyme extract. The specific activity of the enzyme is expressed as nmol NADPH oxidised min⁻¹ mg⁻¹ protein. DHAR activity was determined according to the method described by Doulis et al.¹¹ using a reaction mixture containing 90 mM sodium potassium phosphate buffer (pH 7.0), 5.0 mM reduced glutathione (GSH), 0.1 mM EDTA and 100 µl enzyme extract. The enzyme-specific activity was expressed as nmol dehydroascorbate reduced min⁻¹ mg⁻¹ protein. MDHAR activity was estimated by the method of Hossain et al.¹² using a reaction mixture of 90 mM potassium phosphate buffer (pH 7.5), 0.2 mM NADH, 0.01 mM EDTA, 0.25 U ascorbate oxidase (Sigma), 0.0125% Triton X-100 and 100 µl enzyme extract. The MDHAR-specific activity was expressed as nmol NADH oxidised min⁻¹ mg⁻¹ protein. CAT activity was estimated according to the method of Aebi¹³ using 50 mM Tris-NaOH buffer. The rate of H₂O₂ degradation was determined at 240 nm with an extinction coefficient of 0.036 mM⁻¹ cm⁻¹. The specific activity of the enzyme was calculated as µmol H₂O₂ oxidised min⁻¹ mg⁻¹ protein. GPX was extracted in 5 ml of cold 50 mM Na-phosphate buffer (pH 7.0) and measured according to the method given by Egley et al.¹⁴. Specific enzyme activity was expressed as µmol H₂O₂ oxidized min⁻¹ mg⁻¹ protein.

DNA isolation, PCR amplification and genetic data analysis

Total genomic DNA was extracted from young leaves by the CTAB (cethyltrimethylammonium bromide, Himedia) method. To evaluate the degree of genetic diversity among 112 rice accessions, a total of 62 (57 SSR and 5 RAPD) molecular markers encompassing all 12 chromosomes were utilized. These markers were specific for drought-linked QTLs (Supplementary Table 2). SSR amplification reactions were prepared for a 25 µl reaction mixture containing 2 µl of DNA (20 ng), 1 unit of Taq DNA polymerase enzyme (Promega), 2 µl of 10× buffer, 2 µl of MgCl₂ (25 mM), 2 µl of dNTPs (2.5 mM each), 1 µl of primers (forward and reverse each), and 14.8 µl of H₂O. SSR amplifications were performed with an initial denaturation step at 94 °C for 5 min, followed by 45 cycles of denaturation at 94 °C for 30 s, a primer annealing step at 62 °C for 45 s, an extension at 72 °C for 2 min and a final extension at 72 °C for 5 min. RAPD amplification reactions were prepared for a 25 μl reaction mixture containing 20 ng μl⁻¹ template DNA, 10× buffer (NH₄)₂SO₄, 2.5 mM MgCl₂, 3.0 mM dNTPs, 0.25 μM primers, and 1 unit of Taq DNA polymerase. RAPD amplifications were performed with an initial denaturation step at 94 °C for 7 min and 30 cycles at 94 °C for 1 min, 35 °C for 1 min, and 72 °C for 2 min; the final elongation step was performed at 72 °C for 6 min. The annealing temperature varied depending on the melting temperature of each primer. Each reaction was repeated thrice. The reaction products were analyzed by electrophoresis on 1.4% agarose gels, stained with ethidium bromide, and photographed under a UV transilluminator using a digital camera with a UV filter adapter. Synthetic DNA ladder 100 bp was used as a molecular marker for the molecular weight of the bands. Each amplified band profile was defined by the presence or absence of bands at specific positions on the gel. Profiles were considered distinct if at least one polymorphic band was identified. Fragments were scored as 1 if present or 0 if absent. Allele frequency and PIC (polymorphism information content) were calculated using PowerMarker V3.25 software⁶⁷. A model-based population structure analysis was performed using STRUCTURE software⁶⁸. A phylogenetic tree was generated using NTSYSpc 2.10 based on the similarity index SM coefficient using 100,00 burn-in period length and 100,000 Markov Chain Monte Carlo (MCMC) repeats after burn-in⁶⁹.

RNA isolation, cDNA synthesis and qRT-PCR

Total RNA was isolated from the root, shoot and young panicle tissues of control and treated rice genotype using TRIzol™ RNA purification kit (Thermofisher scientific) as per manufacturer’s protocol. cDNA was synthesized using iScript cDNA synthesis kit (Biorad) following manufacturer’s protocol. Identification of target drought-responsive genes was performed based on the available literature. Transcript abundance of DREB1 (Dehydration responsive element binding), p5cs (Pyrroline-5-carboxylate synthase), WRKY11, WRKY114, rcbs (Rubisco containing bodies), AAO1 (Aldehyde oxidase 1), SOD (Superoxide dismutase), SDR1, NAC9, ZFP252, ZFP182 and DRAP1 (Dr1-associated polypeptide-1), LOC_Os12g04500, LOC_Os02g50970, LOC_Os12g26290, LOC_Os05g08480, MYB80 were performed using quantitative real time PCR (qRT-PCR) and calculated as ΔCt (2^−ΔΔCT) method⁷⁰. The oligonucleotide primer pairs used for the amplification of drought-respective genes were designed using Primer3Plus software based on the gene sequence retrieved from NCBI and Rice Genome Database (http://rice.plantbiology.msu.edu/cgi-bin/gbrowse/rice/). Rice Actin gene was used to normalize the expression of drought responsive genes. A list of oligonucleotide sequences of these primers is shown in Supplementary Table 6.

Statistical analysis

Each experiment was conducted with nine replications and represented as Mean ± SD. Tukey’s HSD test was used to determine the significant difference at p < 0.05 level using XL-STAT software, and analysis of variance was employed to test for differences.

Ethical approval

The authors confirm that permissions or licences were obtained to collect 112 rice genotypes for the experimental purpose. All materials and methods were carried out according to the relevant guide genotype at the “Materials and methods” section.

Data availability

All data supporting the findings of this study are available within the paper and within its Supplementary Materials.

References

Tripathi, K. K., Govila, O. P., Ranjini, W. & Vibha, A. Biology of okra [Abelmoschus esculentus (L.) (Moench]. Serious of Crop Specific Biology Document (Ministry of Environment and Forests Government of India and Department of Biotechnology Ministry of Science and Technology Government of India, 2011).
Google Scholar
Verma, R. K. et al. Identification and characterization of genes for drought tolerance in upland rice cultivar ‘Banglami’ of North East India. Mol. Biol. Rep. 12, 1–9 (2022).
Google Scholar
Vibhuti, C. S., Bargali, K. & Bargali, S. S. Seed germination and seedling growth parameters of rice (Oryza sativa L.) varieties as affected by salt and water stress. Indian J. Agric. Sci. 85(1), 102–108 (2015).
Article Google Scholar
Lv, Y. et al. Identification of putative drought-responsive genes in rice using gene co-expression analysis. Bioinformatics 15(7), 480 (2019).
Google Scholar
Khan, M. I. et al. Improving drought tolerance in rice: Ensuring food security through multi-dimensional approaches. Physiol. Plant 172(2), 645–689 (2021).
Article CAS PubMed Google Scholar
Freeg, H. A. et al. Physio-biochemical responses and expressional profiling analysis of drought tolerant genes in new promising rice genotype. PLoS ONE 17(3), e0266087 (2022).
Article CAS PubMed PubMed Central Google Scholar
Salehi-Lisar, S. Y. & Bakhshayeshan-Agdam, H. Drought stress in plants: Causes, consequences, and tolerance. Physiol. Biochem. 1, 1–6 (2016).
Google Scholar
Kumar, S., Sachdeva, S., Bhat, K. V. & Vats, S. Plant responses to drought stress: Physiological, biochemical and molecular basis. In Biotic and Abiotic Stress Tolerance in Plants (ed. Vats, S.) 1–25 (Springer, 2018).
Google Scholar
Ashraf, M. F. M. R. & Foolad, M. R. Roles of glycine betaine and proline in improving plant abiotic stress resistance. Environ. Exp. Bot. 59(2), 206–216 (2007).
Article CAS Google Scholar
Foyer, C. H. & Halliwell, B. The presence of glutathione and glutathione reductase in chloroplasts: A proposed role in ascorbic acid metabolism. Planta 133, 21–25 (1976).
Article CAS PubMed Google Scholar
Doulis, A. G., Debian, N., Kingston-Smith, A. H. & Foyer, C. H. Differential localization of antioxidants in maize leaves. Plant Physiol. 114(3), 1031–1037 (1997).
Article CAS PubMed PubMed Central Google Scholar
Hossain, M. A., Nakano, Y. & Asada, K. Monodehydroascorbate reductase in spinach chloroplasts and its participation in regeneration of ascorbate for scavenging hydrogen peroxide. Plant Cell Physiol. 25(3), 385–395 (1984).
CAS Google Scholar
Aebi, H. E. Catalase. In Methods of Enzymatic Analysis (ed. Aebi, H. E.) 273–86 (Elsevier, 1983).
MATH Google Scholar
Egley, G. H., Paul, R. N., Vaughn, K. C. & Duke, S. O. Role of peroxidase in the development of water-impermeable seed coats in Sida spinosa L.. Planta 157, 224–232 (1983).
Article CAS PubMed Google Scholar
Panda, D., Mishra, S. S. & Behera, P. K. Drought tolerance in rice: Focus on recent mechanisms and approaches. Rice Sci. 28(2), 119–132 (2021).
Article Google Scholar
Powell, W. et al. The comparison of RFLP, RAPD, AFLP and SSR (microsatellite) markers for germplasm analysis. Mol. Breed. 2, 225–238 (1996).
Article CAS Google Scholar
Hadrys, H., Balick, M. & Schierwater, B. Applications of random amplified polymorphic DNA (RAPD) in molecular ecology. Mol. Ecol. 1(1), 55–63 (1992).
Article CAS PubMed Google Scholar
Verma, H., Borah, J. L. & Sarma, R. N. Variability assessment for root and drought tolerance traits and genetic diversity analysis of rice germplasm using SSR markers. Sci. Rep. 9(1), 16513 (2019).
Article ADS CAS PubMed PubMed Central Google Scholar
Freeg, H. A., Anis, G. B., Abo-Shousha, A. A., El-Banna, A. N. & El-Sabagh, A. Genetic diversity among some rice genotypes with different drought tolerance based on SSR markers. Cercetări Agron. Moldova 3(167), 39–50 (2016).
Article Google Scholar
Bernier, J., Kumar, A., Ramaiah, V., Spaner, D. & Atlin, G. A large-effect QTL for grain yield under reproductive-stage drought stress in upland rice. Crop Sci. 47(2), 507–516 (2007).
Article Google Scholar
Islam, M. S. et al. Assessment of genetic diversity among moderately drought tolerant landraces of rice using RAPD markers. J. Biosci. Biotechnol. 2, 3 (2013).
Google Scholar
Yu, L. X. & Nguyen, H. T. Genetic variation detected with RAPD markers among upland and lowland rice cultivars (Oryza sativa L.). Theor. Appl. Genet. 87, 668–672 (1994).
Article CAS PubMed Google Scholar
Sahoo, S. et al. Physiological introspection into differential drought tolerance in rice cultivars of North East India. Acta Physiol. Plant 41, 1–15 (2019).
Article CAS Google Scholar
Sagar, A. et al. Polyethylene Glycol (PEG) induced drought stress on five rice genotypes at early seedling stage. J. Bangl. Agric. Univ. 18(3), 606–614 (2020).
Google Scholar
Awanis, S., Purwanto, E. & Rahayu, M. The potential of Central Java local black rice and red rice as drought tolerant cultivars. In E3S Web of Conferences Vol. 361 (eds Widodo, S. et al.) (EDP Sciences, 2022).
Google Scholar
Mohammadkhani, N. & Heidari, R. Drought-induced accumulation of soluble sugars and proline in two maize varieties. World Appl. Sci. J. 3(3), 448–453 (2008).
Google Scholar
Shakeri, E., Mozafari, A. A., Sohrabi, F. & Saed-Moucheshi, A. Role of proline and other osmoregulatory compounds in plant responses to abiotic stresses. In Handbook of Plant and Crop Stress 4th edn (eds Pessarakli, M. & Pessarakli, M.) 165–173 (CRC Press, 2019).
Google Scholar
Dien, D. C., Mochizuki, T. & Yamakawa, T. Effect of various drought stresses and subsequent recovery on proline, total soluble sugar and starch metabolisms in Rice (Oryza sativa L.) varieties. Plant Prod. Sci. 22(4), 530–545 (2019).
Article CAS Google Scholar
Halliwell, B. & Gutteridge, J. M. Free Radicals in Biology and Medicine (Oxford University Press, 2015).
Book Google Scholar
Moran, J. F. et al. Drought induces oxidative stress in pea plants. Planta 194, 346–352 (1994).
Article CAS Google Scholar
Lum, M. S., Hanafi, M. M., Rafii, Y. M. & Akmar, A. S. N. Effect of drought stress on growth, proline and antioxidant enzyme activities of upland rice. J Anim. Plant Sci. 24, 5 (2014).
Google Scholar
Kanwal, S., Tahir, M. H. N., Sadaqat, H. A. & Sadia, B. U. S. H. R. A. Development of high yielding types of Brassica napus L. under salinity stress. Pak. J. Bot. 51(4), 1185–1190 (2019).
Article CAS Google Scholar
Sharma, P. & Dubey, R. S. Drought induces oxidative stress and enhances the activities of antioxidant enzymes in growing rice seedlings. Plant Growth Regul. 46, 209–221 (2005).
Article CAS Google Scholar
Mishra, S. S. & Panda, D. Leaf traits and antioxidant defense for drought tolerance during early growth stage in some popular traditional rice landraces from Koraput, India. Rice Sci. 24(4), 207–217 (2017).
Article Google Scholar
Rang, Z. W., Jagadish, S. V. K., Zhou, Q. M., Craufurd, P. Q. & Heuer, S. Effect of high temperature and water stress on pollen germination and spikelet fertility in rice. Environ. Exp. Bot. 70(1), 58–65 (2011).
Article Google Scholar
Lakshmi Praba, M. & Thangaraj, M. Effect of growth regulators and chemicals on pollen sterility in TGMS genotype of rice. Plant Growth Regul. 46, 117–124 (2005).
Article Google Scholar
Hoang, G. T. et al. Genome-wide association study of a panel of Vietnamese rice landraces reveals new QTLs for tolerance to water deficit during the vegetative phase. Rice 12(1), 1–20 (2019).
Article Google Scholar
Pham, A. T. et al. Genome-wide association of barley plant growth under drought stress using a nested association mapping population. BMC Plant Biol. 19(1), 1–16 (2019).
Article CAS Google Scholar
Wang, H. et al. Dehydration-responsive element binding protein 1C, 1E, and 1G promote stress tolerance to chilling, heat, drought, and salt in rice. Front. Plant Sci. 13, 1731 (2022).
CAS Google Scholar
Yang, D. et al. Functional characterization of the Stipa purpurea P5CS gene under drought stress conditions. J. Mol. Sci. 22(17), 9599 (2021).
Article CAS Google Scholar
Ghosh, U. K., Islam, M. N., Siddiqui, M. N., Cao, X. & Khan, M. A. R. Proline, a multifaceted signalling molecule in plant responses to abiotic stress: Understanding the physiological mechanisms. Plant Biol. 24(2), 227–239 (2022).
Article CAS PubMed Google Scholar
Rushton, P. J., Somssich, I. E., Ringler, P. & Shen, Q. J. WRKY transcription factors. Trends Plant Sci. 15(5), 247–258 (2010).
Article CAS PubMed Google Scholar
Li, W., Pang, S., Lu, Z. & Jin, B. Function and mechanism of WRKY transcription factors in abiotic stress responses of plants. Plants 9(11), 1515 (2020).
Article CAS PubMed PubMed Central Google Scholar
Hara, K., Yagi, M., Kusano, T. & Sano, H. Rapid systemic accumulation of transcripts encoding a tobacco WRKY transcription factor upon wounding. Mol. Genet. 263, 30–37 (2000).
Article CAS Google Scholar
Zhang, T., Tan, D., Zhang, L., Zhang, X. & Han, Z. Phylogenetic analysis and drought-responsive expression profiles of the WRKY transcription factor family in maize. Agric. Gene 3, 99–108 (2017).
Article Google Scholar
Li, S., Zhou, X., Chen, L., Huang, W. & Yu, D. Functional characterization of Arabidopsis thaliana WRKY39 in heat stress. Mol. Cells 29(5), 475 (2010).
Article CAS PubMed Google Scholar
Wu, X., Shiroto, Y., Kishitani, S., Ito, Y. & Toriyama, K. Enhanced heat and drought tolerance in transgenic rice seedlings overexpressing OsWRKY11 under the control of HSP101 promoter. Plant Cell Rep. 28, 21–30 (2009).
Article CAS PubMed Google Scholar
Bo, C. et al. Maize WRKY114 gene negatively regulates salt-stress tolerance in transgenic rice. Plant Cell Rep. 39, 135–148 (2020).
Article CAS PubMed Google Scholar
Song, G. et al. OsWRKY114 negatively regulates drought tolerance by restricting stomatal closure in rice. Plants 11(15), 1938 (2022).
Article CAS PubMed PubMed Central Google Scholar
Hu, H. et al. Overexpressing a NAM, ATAF, and CUC (NAC) transcription factor enhances drought resistance and salt tolerance in rice. Proc. Natl. Acad. Sci. 103(35), 12987–12992 (2006).
Article ADS CAS PubMed PubMed Central Google Scholar
Xu, D. Q. et al. Overexpression of a TFIIIA-type zinc finger protein gene ZFP252 enhances drought and salt tolerance in rice (Oryza sativa L.). FEBS Lett. 582(7), 1037–1043 (2008).
Article CAS PubMed Google Scholar
Huang, L. et al. Characterization of transcription factor gene OsDRAP1 conferring drought tolerance in rice. Front. Plant Sci. 9, 94 (2018).
Article PubMed PubMed Central Google Scholar
Chen, S. et al. Genes and pathways induced in early response to defoliation in rice seedlings. Curr. Issues Mol. Biol. 11(2), 81–100 (2009).
CAS PubMed Google Scholar
Narsai, R. et al. Antagonistic, overlapping and distinct responses to biotic stress in rice (Oryza sativa) and interactions with abiotic stress. BMC Genom. 14, 1–21 (2013).
Article Google Scholar
Du, L. et al. The two-component signal system in rice (Oryza sativa L.): A genome-wide study of cytokinin signal perception and transduction. Genomics 89(6), 697–707 (2007).
Article CAS PubMed Google Scholar
Pan, X. et al. OsMYB80 regulates anther development and pollen fertility by targeting multiple biological pathways. Plant Cell Physiol. 61(5), 988–1004 (2020).
Article CAS PubMed PubMed Central Google Scholar
Ahmad, H. et al. Impact of pre-anthesis drought stress on physiology, yield-related traits, and drought-responsive genes in green super rice. Front. Genet. 1, 256 (2022).
Google Scholar
Robin, A. H. K., Ghosh, S. & Shahed, M. A. PEG-induced osmotic stress alters root morphology and root hair traits in wheat genotypes. Plants 10(6), 1042 (2021).
Article CAS PubMed PubMed Central Google Scholar
Nezar, H. S. Effects of drought stress on growth and yield of barley. Agron. Sustain. Dev. 25(1), 145–149 (2005).
Article Google Scholar
Imakumbili, M. L. Making water stress treatments in pot experiments: An illustrated step-by-step guide. Helion 1, 1 (2019).
Google Scholar
Baldoni, E. et al. Analysis of transcript and metabolite levels in Italian rice (Oryza sativa L.) cultivars subjected to osmotic stress or benzothiadiazole treatment. Plant Physiol. Biochem. 70, 492–503 (2013).
Article CAS PubMed Google Scholar
Vijayaraghavareddy, P., Adhinarayanreddy, V., Vemanna, R. S., Sreeman, S. & Makarla, U. Quantification of membrane damage/cell death using Evan’s blue staining technique. Bio-protocol 7(16), e2519 (2017).
PubMed PubMed Central Google Scholar
Bates, L. S., Waldren, R. A. & Teare, I. D. Rapid determination of free proline for water-stress studies. Plant Soil 39, 205–207 (1973).
Article CAS Google Scholar
Jana, S. & Choudhuri, M. A. Glycolate metabolism of three submersed aquatic angiosperms: Effect of heavy metals. Aquat. Bot. 11, 67–77 (1981).
Article CAS Google Scholar
Law, M. Y., Charles, S. A. & Halliwell, B. Glutathione and ascorbic acid in spinach (Spinacia oleracea) chloroplasts. The effect of hydrogen peroxide and of paraquat. Biochem. J. 210(3), 899–903 (1983).
Article CAS PubMed PubMed Central Google Scholar
Misra, H. P. & Fridovich, I. The role of superoxide anion in the autoxidation of epinephrine and a simple assay for superoxide dismutase. J. Biol. Chem. 247(10), 3170–3175 (1972).
Article CAS PubMed Google Scholar
Tanavar, M., Kelestanie, A. R. A. & Hoseni, S. A. Software programs for analyzing genetic diversity. Int. J. Farming Allied Sci. 3(5), 462–466 (2014).
Google Scholar
Pritchard, J. K., Wen, X. & Falush, D. Documentation for Structure Software: Version 2.3 1–37 (University of Chicago, 2010).
Google Scholar
Gong, Y. M. et al. Genetic diversity analysis of faba bean (Vicia faba L.) based on EST-SSR markers. Agric. Sci. China 10(6), 838–844 (2011).
Article CAS Google Scholar
Livak, K. J. & Schmittgen, T. D. Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCT method. Methods 25(4), 402–408 (2001).
Article CAS PubMed Google Scholar

Download references

Acknowledgements

Authors would like to acknowledge Mr. Mihin Targu, Department of Botany, North-Eastern Hill University for his guidance in population study analysis.

Funding

This work was supported by NICRA (National Innovation on Climate Resilient Agriculture) project, ICAR research complex for NEH, India.

Author information

These authors contributed equally: Bijoya Bhattacharjee and Akib Ali.

Authors and Affiliations

Division of Crop Sciences, ICAR Research Complex for NER, Umiam, Meghalaya, 793103, India
Bijoya Bhattacharjee, Akib Ali & Krishnappa Rangappa
Division of System Research and Engineering, ICAR Research Complex for NER, Umiam, Meghalaya, 793103, India
Burhan U. Choudhury
ICAR Research Complex for NER, Umiam, Meghalaya, 793103, India
V. K. Mishra

Authors

Bijoya Bhattacharjee
View author publications
You can also search for this author in PubMed Google Scholar
Akib Ali
View author publications
You can also search for this author in PubMed Google Scholar
Krishnappa Rangappa
View author publications
You can also search for this author in PubMed Google Scholar
Burhan U. Choudhury
View author publications
You can also search for this author in PubMed Google Scholar
V. K. Mishra
View author publications
You can also search for this author in PubMed Google Scholar

Contributions

B.B.: Conceptualization, seed collection, germination experiments, SSR/RAPD marker PCR experiment, manuscript writing; A.A.: Metabolite profile, antioxidant enzyme activity assays, RT-PCR, SSR/RAPD marker & all bioinformatics work data analysis, figures, manuscript writing and editing. BB and AA equally contributed and share first authorship; K.R., B.U.C. and V.K.M.: guidance and revision. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Bijoya Bhattacharjee.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Supplementary Figures.

Supplementary Tables.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Cite this article

Bhattacharjee, B., Ali, A., Rangappa, K. et al. A detailed study on genetic diversity, antioxidant machinery, and expression profile of drought-responsive genes in rice genotypes exposed to artificial osmotic stress. Sci Rep 13, 18388 (2023). https://doi.org/10.1038/s41598-023-45661-8

Download citation

Received: 24 April 2023
Accepted: 22 October 2023
Published: 26 October 2023
DOI: https://doi.org/10.1038/s41598-023-45661-8

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.