Exogenous abscisic acid mitigates drought stress in pigeon pea by modulating morpho-physiological traits, biochemical responses and gene regulation via ABA dependent and independent pathways
Author Information
A
PadmalathaKoilkonda1,3✉Emailpadmalathakk@gmail.com
BasudebSarkar1,3✉EmailB.Sarkar@icar.gov.inEmailbasudeb70@gmail.com
MandapakaMaheswari1,3Emailmmandapaka59@gmail.com
RMythily1,3Emailmythily9084@gmail.com
VMaruthi1,3Emailv.maruthi-icar@icar.org.in
VinodKumarSingh1,3Emailvkumarsingh_01@yahoo.com
KPadmalatha1,3
MMaheshwari1
Singh1
V.K1
1Loyola Academy Degree and PG College500010Alwal, SecunderabadTelanganaIndia
2Division of Crop SciencesICAR-Central Research Institute for Dryland Agriculture500059Santoshnagar, HyderabadTelanganaIndia
3ICAR-Central Research Institute for Dryland Agriculture500059Santoshnagar, HyderabadTelanganaIndia
Padmalatha Koilkonda†,1,2,∗,
1. Present address: Loyola Academy Degree and PG College, Alwal, Secunderabad, Telangana 500010, India
2. Previous address: Division of Crop Sciences, ICAR-Central Research Institute for Dryland Agriculture, Santoshnagar, Hyderabad, Telangana 500059, India.
Email: padmalathakk@gmail.com
ORCID ID: https://orcid.org/0000-0003-4547-3760
Basudeb Sarkar†,2,∗
2. Division of Crop Sciences, ICAR-Central Research Institute for Dryland Agriculture, Santoshnagar, Hyderabad, Telangana 500059, India.
Email: B.Sarkar@icar.gov.in; basudeb70@gmail.com
ORCID ID: https://orcid.org/0000-0003-3695-8061
Mandapaka Maheswari2
2. Division of Crop Sciences, ICAR-Central Research Institute for Dryland Agriculture, Santoshnagar, Hyderabad, Telangana 500059, India.
Email: mmandapaka59@gmail.com
ORCID ID: https://orcid.org/0000-0001-9615-7552
Mythily R2
2. Division of Crop Sciences, ICAR-Central Research Institute for Dryland Agriculture, Santoshnagar, Hyderabad, Telangana 500059, India.
Email: mythily9084@gmail.com
ORCID ID: https://orcid.org/0000-0003-2415-8059
Maruthi V2
2. Division of Crop Sciences, ICAR-Central Research Institute for Dryland Agriculture, Santoshnagar, Hyderabad, Telangana 500059, India.
ORCID ID:
Email: v.maruthi-icar@icar.org.in
Vinod Kumar Singh2
2. Director, ICAR-Central Research Institute for Dryland Agriculture, Santoshnagar, Hyderabad, Telangana 500059, India.
Email: vkumarsingh_01@yahoo.com
ORCID ID:
Exogenous abscisic acid mitigates drought stress in pigeon pea by modulating morpho-physiological traits, biochemical responses and gene regulation via ABA dependent and independent pathways
Padmalatha, K†,1,2,∗,., Sarkar, B†,1,∗,, Maheshwari, M1., Mythily, R1., Maruthi, V1., Singh, V.K1.
∗Corresponding author email: basudeb70@gmail.com; padmalathakk@gmail.com
1ICAR-Central Research Institute for Dryland Agriculture, Santoshnagar, Hyderabad, Telangana 500059, India.
2Loyola Academy Degree and PG College, Alwal, Secunderabad, Telangana 500010, India
Abstract
Drought stress is a major constraint to pigeon pea production in rainfed agro-ecosystems. This study evaluates the effectiveness of exogenous abscisic acid (ABA) application in mitigating drought stress through changes in morpho-physiological, biochemical responses, and gene regulation in ABA-dependent and independent pathways in two contrasting pigeon pea varieties PRG 158 and Bahar. An optimal concentration of 100 µM ABA, applied through soil drenching, was identified as effective during the vegetative stage. Physiological and biochemical analyses revealed that ABA pretreatment improved osmotic adjustment and reduced oxidative stress, even under longer duration of water deficit conditions. In PRG 158, exogenous ABA upregulated key drought-responsive genes PYL9 and SnRK2A, indicating a strong ABA-dependent response. Conversely, Bahar exhibited a mixed response, with limited physiological changes despite gene upregulation, suggesting a reliance on ABA-dependent and independent mechanisms. The qRT PCR study also revealed the over expression of drought responsive genes PYL9 and SnRK2A in ABA treated plant as compared to non-treated. Root system architecture and recovery responses also varied between varieties, emphasizing differential adaptation strategies. Overall, the findings demonstrate that exogenous ABA application can modulate drought tolerance in a variety-specific manner by engaging distinct physiological and molecular mechanisms. Soil drenching with 100 µM ABA during early vegetative growth, coupled with minimal irrigation, is proposed as a viable strategy to enhance drought resilience in pigeon pea.
Key words:
pigeon pea
ABA
drought
morpho-physiological traits
root structure architecture
qRT-PCR
Abbreviations
ABA Abscisic acid
PYL Pyrabactin Resistance 1(PYR1)-like regulatory component
SnRK2s Serine/Threonine Kinase
MDA Malionaldehyde
MSI Membrane stability index
PRO Proline
TSS Total soluble sugars
SMC Soil moisture content
Fv/Fm Maximum fluorescence/maximum quantum efficiency
1. Introduction
A
Pigeon pea (Cajanus cajan (L.) Millsp.), suffers substantial yield losses when exposed to drought stress specially in rainfed regions of the country. However, crop employs various stress responding adaptation mechanisms to combat drought, depending on the severity of stresses. Among them, abscisic acid (ABA), a phytohormone plays a significant role during drought at different levels of physiological, biochemical and molecular signal transduction cascades. The ABA mediated signaling mechanisms includes the biosynthesis and catabolism, receptors and transporters like Pyrabactin Resistance 1(PYR1)-like regulatory component (PYL), Phosphatase 2C (PP2C), Serine/Threonine Kinase (SnRK2s), Nitroreductase (NTRs), Glyphosate Tolerance (GTG), 9-cis-epoxycarotenoid dioxygenase (NCED), Cytochrome P450 (CYPs) and transcription factors like Worky (WRKY), Basic leucine zipper protein (bZIP), Avian Myeloblastosis virus (MYB), Myelocytomatosis (MYC), No apical meristem (NAM), Arabidopsis thaliana activating factor (ATAF1–2) and Cup-shaped cotyledon CUC2 (NAC), Apetala2/ethylene responsive factor (AP2-ERF) (Yoshida et al. 2014). Both ABA dependent and independent mechanisms play a major role during drought stress. The ABA independent mechanisms include, Dehydration responsive element-binding (DREB), ABA-responsive element binding protein1 (AREB1) and ABA responsive elements-binding factor 2 (ABF2) and Apetala2/ethylene responsive factor (AP2-ERF). During drought, the stress stimulus is perceived by the roots and the signal is transmitted to the shoots and leaves to synthesize ABA endogenously. In turn, the water deficit condition is regulated by various morpho-physiological characteristics like osmolyte accumulation (proline, glycine betaine), stomatal opening and closure, reactive oxygen species (ROS) scavenging, lipid peroxidation determined by measuring Malionaldehyde content (MDA), percentage of membrane stability index (MSI), primary and secondary metabolite production (Yoshida et al. 2014).Apparently, there are reports in Arabidopsis thaliana, Nicotiana tabacum, Glycine max, Agrostis grass, etc., related to important genes or transporters for enhanced drought tolerance by modulating ABA signaling pathways. Moreover, in Arabidopsis, rice, maize and wheat, the target proteins involved in ABA mediated drought response were studied at post translational level (Aslam et al. 2022; Kosakivska et al. 2024). Whereas, in A. thaliana (Liu et al. 2018), G. max (Ma et al. 2020), Medicago truncatula (Philippe et al. 2019), N. tabacum (Rabara 2015), Cicer arietinum (Boominathan et al. 2004) many ABA independent pathways were deciphered for drought stress. Precisely, several transgenics were reported to enhance drought tolerance by increasing endogenous ABA levels through alteration of ABA biosynthetic and catabolic pathways (Sreenivasulu et al. 2012). Hence, the role of endogenous ABA regulatory genes for drought alleviation was very evidently reported.
Likewise, the research associated to the exogenous application of ABA for drought tolerance was reported on many diverse crops like maize (Yao et al. 2019), rice (Ramachandran 2021), barley (Skowron and Trojak 2021), wheat (Luo et al. 2021), cotton (Hu et al. 2022), sunflower (Hussain et al. 2014). Specifically, in legumes like grass pea (Kong et al. 2022), soybean, green gram and black gram (Vijayalakshmi et al. 2014), chickpea (Boominathan et al. 2004), cowpea (Contour-Ansel et al. 2006), Arabidopsis (Wan and Li 2006), Medicago (Liu et al. 2022), faba bean (Ammar et al. 2016), ABA mediated drought response has been reported. Several genes might be activated during the exogenous application of plant hormones leading to stress tolerance by the plants (Swain et al. 2023). There is limited information available on endogenous expression of ABA mediated drought responses on pigeon pea (Buch et al. 2020). The transgenic rice plants developed by introducing the pigeon pea CcCDR gene encoding cold and drought regulatory protein, confer tolerance to major abiotic stresses, regulated by both ABA dependent and independent mechanisms (Sunitha et al. 2017). Likewise, the study by Tamirisa et al., 2014, 2017 reported the enhanced tolerance towards drought, salinity and low temperature when pigeon pea CcCDR & CcCKS (cyclin dependent kinase) genes were overexpressed in A. thaliana, which were upregulated by ABA. Apparently, effect of pigeon pea gene (CcHyPRP) in bestowing multiple abiotic stress tolerance in ABA treated plants was studied in A. thaliana (Priyanka et al. 2010).
However, to our knowledge the effects of exogenous ABA application under drought stress on signaling pathways in pigeon pea remain hardly understood. Under this background, the current study was designed with the objective of understanding the effect of exogenous applications of ABA solution under drought stress through various morpho-physiological, biochemical, root architecture and molecular analysis. The study would further contribute to an understanding of the molecular mechanism related to ABA dependent drought tolerance including the expression profile of different genes through qRT PCR, which would aid in developing methodology for improving yield specifically for the pigeon pea growers in rainfed areas.
2. Materials and Methods
A schematic depiction of the experimental details is diagrammatically represented Supplementary Figure (Fig. S1).
Fig. S1
Schematic representation of an experimental design that outlines the key steps involved during the present study.
2.1 Plant material and growth conditions
The ABA mediated drought tolerant mechanisms were studied in four selected pigeon pea varieties i.e., PRG 158, PAU 881, Asha and Bahar. Among these, PRG 158, PAU 881 and Asha were of medium maturity group (170–185 days) whereas Bahar is a long duration (210–250 days) variety. Out of these, PAU 881 was susceptible while others were reported to be drought tolerant. These varieties exhibit high yield potential and are under cultivation across diverse regions of the country having contrasting agro-climatic conditions. PRG 158, Asha grows well in Southern parts whereas, PAU 881 and Bahar are restricted to North-eastern regions of India. The experiments were carried out during the Kharif and Rabi seasons at ICAR-Central Research Institute for Dryland Agriculture, Hyderabad, India under Department of Science and Technology (DST), Government of India funded project. Seeds were sown in plastic pots (9 cm diameter × 15 cm height) containing soil, farmyard manure and cocopeat (2:1:1) at growth chamber maintaining temperature of 28-30oC and relative humidity of 60–70%. Three plants were maintained in each pot and watered regularly to maintain the soil moisture content (SMC) to 90% of field capacity (FC). Subsequent qRT PCR analysis was performed using two pigeon pea varieties, namely ‘PRG 158’ and ‘Bahar’.
2.2. Determination of effective concentration of ABA solution for exogenous application
Preliminary experiments were conducted to determine the optimal concentration of ABA on pigeon pea crop using methods viz. foliar spray and pretreatment, along with water deficit stress (WS) and well-watered i.e. control (CON) treatments. Each experiment were conducted with three replicates.
2.2.1 Foliar application of ABA solution
In the first experiment, in case of foliar spray method, thirty-day old PRG 158 seedlings were subjected to three concentrations of ABA solutions (50µM, 100µM and 150µM) containing Triton-X-100 (0.01%), while a CON with distilled water containing 0.01% Triton-X-100 and WS treatment was initiated by withholding water. The CON and ABA treated plants were irrigated regularly with an equal volume of water (1L). Soil moisture content (SMC) was determined by using the instrument Field Scout TDR 350 Soil Moisture meter (Spectrum technologies, Aurora, IL) before, during and after the treatments. The physiological and biochemical changes due to WS and ABA was recorded post five days of treatments by measuring relative water content (RWC) (Barrs and Weatherley 1962) and malondialdehyde content (MDA) (Heath and Packer 1968) at different time points i.e., at 6h, 1d, 3d, and 5d, whereas, proline accumulation (PRO) (Bates et al. 1973) was estimated after 1d and total soluble sugars (TSS) (Dubois et al. 1956) after 6h and 1d.
Following the same method, another set of experiment were carried out by exposing WS treatment for ten days. The morpho-physiological traits for WS and ABA treatments, such as leaf area (LA) by using leaf area meter (LI-3100, LI-COR), specific leaf area (SLA), stomatal conductance (gs) using AP4 Leaf Porometer, the PS II efficiency (ratio of variable and maximum fluorescence/maximum quantum efficiency (Fv/Fm)) using a Fluorpen, chlorophyl content using SPAD Chlorophyll Meter, total shoot length (SL), root fresh weight/shoot fresh weight (RFW/SHFW), total root length (TRL) and biomass were recorded.
2.2.2 Effect of pretreatment of ABA solution at root zone
To determine the effective concentration of ABA, the 30 days old PRG 158 plants were carefully uprooted and placed in distilled water overnight to reduce the uprooting shock. Following removal of excess moisture using blotting paper, the roots were subsequently pretreated with 40 ml ABA solution by dipping into 50 ml falcon tubes having different concentrations (A-50µM, A-100µM, A-150µM and A-200µM) at 8.00 am. Plants dipped in distilled water were considered as CON. Two major stress indicators, MDA content and PRO accumulation was measured at two time points i.e., 3h and 6h which revealed that A-100µM as effective concentration. To further validate its effectiveness, another set of plants were treated with 100µM of ABA to measure MDA and PRO at two time points i.e., 30 mins and 1.5h respectively.
2.3 Determination of response time for exogenous application of ABA solution
To examine the effective time point for ABA treatment, 30 days old plants were maintained at 20-25oC at 70–80% humidity and subjected to four treatments, 1. Control (CON): Watered and no ABA, 2. Water stress (WS): By progressive soil drying and withholding water before two days prior to start of the experiment and no ABA, 3. Watered and ABA (A+): Watered and soil drench using 5 ml of ABA solution (100 µM) prepared in distilled water applied at root zone, 4. Water stress and ABA (A−): Water stress and soil drench using 5 ml of ABA solution (100 µM) in distilled water applied at root zone. Before subjecting the plants to WS and ABA application, all the plants were regularly watered (500 ml in each pot) until 3rd week after germination. During the 4th week progressive soil drying was followed by eventually decreasing the volume of water (200ml to 12.5ml) in potted plants for exposing to WS and A− treatments. Whereas, for CON and A+ treatments, similar volume of water was given (200ml) regularly. Soil moisture content (SMC) was regularly monitored in all treatments. The physiological and biochemical changes due to WS and ABA treatments were recorded by measuring the leaf RWC, membrane stability index (MSI) (Sairam et al. 1997), PRO accumulation, SPAD and Fv/Fm at different time points i.e., 0d, 1d, 2d, 3d and 4d respectively.
2.4. Effect of WS and ABA on different varieties at stress point and post recovery
Additionally, to examine the impact of WS and ABA treatments on root architecture during recovery, root traits of two contrasting varieties PRG 158 and Bahar were evaluated after 21 day of recovery phase. Plants were carefully uprooted, and roots were gently washed to avoid mechanical damage. Root systems were scanned and analyzed using the WinRHIZO root analysis system (WinRHIZO 2003, Regent Instruments Inc., Quebec, Canada), following the methodology described by Tahir et al. 2021a. The root morphological traits measured includes root length (RL), root surface area (RSA), average diameter (AvDia), root length-to-volume ratio (L/Vol), root volume (RV), number of nodules, and number of root tips, forks, and crossings.
2.5 Selection of candidate genes, sequence alignment and phylogenetic analysis associated with ABA mediated drought responses
The candidate genes responsible for ABA mediated drought signaling pathways were searched by extensive survey of available literature (Daszkowska-Golec and Szarejko 2013; Nakashima et al. 2014) and genome information of pigeon pea at Kyoto Encyclopedia of genes and genomes (KEGG) and National Center for Biotechnology Information (NCBI) databases (https://www.genome.jp/kegg-bin/show_organism?menu_type=genome_info&org=ccaj; https://www.ncbi.nlm.nih.gov/genome/?term=cajanus+cajan%5Borgn%5D). The protein and nucleotide sequences of all the genes from selected gene families were subjected to multiple sequence alignment using CLUSTAL Omega tool (1.2.4). For phylogenetic analysis, protein sequences were used following neighbour-joining tree method.
2.6. Primer designing and synthesis
The identified coding sequences (CDS) of the target genes served as templates for designing primer pairs using Primer-BLAST tool (NCBI), with defined parameters (primer length: 18–22 bp, Tm: 58–62°C, GC content: 40–60%, amplicon size: 90–200 bp). The High-Performance Liquid Chromatography (HPLC) purified primers were synthesized (50nm). The primers were initially prepared as standard stock of 100pM, from which a working stock of 10pM was made and used for further experimental analysis.
2.7. RNA isolation and cDNA synthesis
The 30 days old plants of all the four treatments i.e., CON, WS, A+ and A−. The leaf samples were collected on 3rd day after treatments on basis of the data recorded for physiological and biochemical responses like RWC, MSI and proline accumulation. Total RNA was extracted from PRG 158 and Bahar using RNA isolation kit from plant GCC Biotech (Cat No: 1004A) following the manufacturer’s protocol. The RNA samples were further treated with DNase and quantified using Bio photometer Plus (Eppendorf, Germany). Around 1µg of isolated RNA was used for the synthesis of cDNA using Takara Prime Script 1st strand cDNA synthesis kit (Cat No 6110A) as per the product manual.
2.8. Quantitative Real Time PCR (qRT PCR)
qRT PCR was performed using Qiagen Rotor-Gene Q5 Plex HRM machine according to the manufacturer’s instructions. For each reaction, 1µl of cDNA (25 ng), 1µl each of forward and reverse primers (10 pm) and 10µl of TB Green Premix Ex Taq II (Takara) were used and the final reaction volume was made up to 20µl. All the reactions were performed in triplicates. The analysis was conducted using gene specific primers designed for the two key genes (PYL9 and SnRK2A), while Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was used as an endogenous control and the sequence information was obtained from previously reported study on pigeon pea (Sinha et al. 2015). The thermal cycling conditions were 95oC for 30 sec, followed by 45 cycles of 95oC for 5 sec and at 60oC for 35 sec. Relative gene expression of the samples was calculated using 2−ΔΔCT method (Livak and Schmittgen 2001).
2.9. Statistical Analysis
The data was analyzed for test of significance for different treatments and their interaction using R software. The differences among treatments and their interaction were tested using Tukey’s post hoc test for multiple comparisons.
3. Results
3.1 Determination of effective concentration of ABA solution for exogenous application
3.1.1 Foliar application of ABA solution
Fig. 1
Effect of WS and foliar application of ABA solution (50µM, 100µM and 150µM) at different time points i.e., 6h, 1d, 3d and 5d on physiological and biochemical traits (PRG 158)
The foliar spray of ABA at four time points i.e., 6h, 1d, 3d and 5d revealed significant differences among treatments in terms of physiological and biochemical changes. A representative image of the treated plants under different treatments is shown in Fig. 1a. The SMC was maintained same in CON and ABA, while significantly reduced by 28% in WS treated plants after 5d (Fig. 1b). Statistical analysis showed significant differences among treatments, time points and their interaction for RWC, MDA, PRO and TSS respectively. Under WS, the percent decrease in RWC was 15%, 37% and 79% after 1d, 3d and 5d when compared to CON (Fig. 1c). The MDA content showed significant differences for WS with reference to timepoint. However, after 5d of WS, the percent increase in MDA content was 93% compared to CON (Fig. 1d). There was 8.5 times increase in PRO accumulation in WS plants after 1d while 41% in TSS as compared to CON (Fig. 1e-f). Therefore, WS caused a significant decrease in RWC from the 1st to the 5th day, while MDA content increased notably on the 5th day. In contrast, PRO and TSS levels increased from the 1st day onward, clearly indicating that the plants were under WS stress from the beginning, although lipid peroxidation progressed gradually. Regarding the ABA treatments, there was little effect of ABA on RWC, but the PRO accumulation and TSS levels showed a significant variation for A-100 after 1st day. Additionally, the effects of ABA and WS were assessed on morpho-physiological traits at 10th day (Fig. 2a) revealing significant differences among treatments. LA decreased significantly by 42% in WS, while ABA application had no significant effect (Fig. 2b-c). SLA decreased significantly by 23% in WS but increased by 24% and 30% in A-50 and A-150 respectively compared to CON (Fig. 2d). Stomatal conductance decreased significantly by 97% in WS, whereas significant increase was observed in A-50 and A-150 by 63% and 50% (Fig. 2e) respectively. Fv/Fm, SPAD, PH and total biomass showed a significant decrease by 20%, 16%, 43%, and 80% respectively under WS, whereas ABA application showed no effect (Fig. 2f-i). Root to shoot FW ratio significantly decreased by 68% in WS as compared to CON (Fig. 2j). Significant differences were observed for tap root length when treated with A-100 and A-150 as compared to control (Fig. 2k). WS after 10 days showed a significant reduction in all the parameters except TRL. A-100 resulted in a marked decline in LA, SLA, gs, SPAD, TRL when compared among ABA treatment. Although, foliar application of ABA solution does not show considerable impact on drought-induced stress, the findings suggest that A-100 may represent a promising concentration for further detailed investigation.
Fig. 2
Effect of WS, foliar application of ABA solution (50µM, 100µM and 150µM) after 10 days on morphophysiological responses (PRG 158)
3.1.2. Effect of pretreatment with ABA solution
The roots of PRG 158 were pretreated with 40 ml ABA solution at varying concentrations (Fig. 3a-d). The MDA content increased significantly by 13% and 14% at A-50 and A-100 after 3h, whereas with A-150 and A-200 it was less than CON after 6h (Fig. 3e). The PRO accumulation increased by 78% and 32% under A-150 and A-200 after 3h and by 78% with A-100 after 6h, whereas with A-150 and A-200 it was lower than CON at 6h (Fig. 3f). Further, when the 30 days old plants were treated only with A-100 for its responses in short time (30 min & 1.5 h). The MDA content was lower whereas there was 1.5 and 6.8 fold increase in PRO accumulation at 30 min and 1.5h respectively compared to CON (Fig. 3g-h). MDA content significantly increased at A-50 and A-100 after 3h, whereas the PRO accumulation showed a significant increase when A-100 was used at 6h. Even when the experiment was carried at short span of time the PRO content started accumulating significantly at a higher level since 30 min after A-100 treatment. The statistical analysis showed a significant interaction effect between time and treatment on MDA and PRO from 30 min to 6h. The results indicate that using A-100 was an effective concentration of stress indicator specifically for PRO accumulation. Therefore, A-100 was used as a standard concentration for further studies.
Fig. 3
Effect of pretreatment with ABA solution (50µM, 100µM, 150µM and 200µM) on 30d old plants of PRG 158 and PAU 881. Specifically, with A-100µM for 30 min and 1.5h (PRG 158)
3.2. Defining the response onset time to exogenous ABA application
The effective response onset time for ABA application was assessed in 30-day old plants at vegetative stage (Fig. 4a). SMC declined by 30% in both WS and A− treatments by day 4, whereas it remained stable in CON and A+ plants (Fig. 4b). RWC declined significantly by 28% on the 3rd and 4th day under WS and by 40% under A− treatment (Fig. 4c). Similarly, MSI decreased by 39% in A− treatment (Fig. 4d). In contrast, PRO accumulation increased rapidly under stress. PRO levels increased significantly on the 3rd and 4th day in A− plants compared to WS plants respectively (Fig. 4e). No significant temporal variations in RWC, MSI, or PRO were observed in CON and A+ treatments. These findings suggest that the most pronounced physiological responses to drought stress, marked by increased PRO and decreased RWC and MSI occurred around the third day, highlighting this time point as critical for the activation of ABA-mediated drought tolerance mechanisms.
Fig. 4
Effect of WS and soil drench of ABA solution (100 µM) at different time points (6h, 1d, 2d, 3d, 4d) on physiological and biochemical traits in PRG 158
3.3. Effect of ABA application on four varieties after prolonged water stress
Prolonged effect of WS and soil drenching of ABA at 0d, 3d, 7d was investigated on four varieties i.e., PAU 881, Asha, Bahar, and PRG 158 varying in crop maturity and drought tolerance. Genotypic variation was observed for biochemical and morpho-physiological traits. Thirty days old plants of all the four varieties before and after treatments were shown in Fig. S2. Analysis of variance revealed significant differences for all varieties with respect to RWC, MSI, PRO and Fv/Fm, whereas the interaction among treatments were statistically significant for all the evaluated traits except for RWC (Table S1).
Fig. S2
Effect of WS and soil drench of ABA solution (100µm) at different time points (0d, 3d, 7d) on physiological and biochemical responses of four genotypes.
In PRG 158, RWC was significantly lower for WS, A− at 3d and 7d by 23%, 21% and 65%, 64% respectively. PAU 881 showed a reduction by 27%, 30% on 3d and 83% on day 7. Whereas for Asha it decreased by 43%, 21% on 3rd day and 80% by 7th day. Bahar showed a reduction by 31%, 15% and 87%, 57% from 3rd to 7th day. Significant differences were observed for MSI and PRO among all varieties at 3d and 7d in WS and A− treatments. For Fv/Fm on 7th day, there was significant differences among the varieties. There was a significant reduction of SMC from 3rd day to 7th day for all the varieties (Fig. S3). Notably, no significant changes were observed in RWC, MSI, PRO, or Fv/Fm in control (CON) and ABA-treated (A+) plants throughout the study period. In contrast, WS and A− treatments led to progressive reductions in RWC, MSI, and Fv/Fm, accompanied by a sharp increase in PRO, highlighting ABA’s role in mitigating drought-induced damage when applied at early stages.
Fig. 5
Morpho-physiological effects of WS and soil drench of ABA solution (100µm) on four varieties of pigeon pea
Fig. S3
Physiological effect of ABA application on four genotypes after prolonged water stress.
3.4. Effect of WS and application of ABA after stress recovery
To determine the long-term effect, four varieties subjected to WS and ABA were recovered by regular watering and changes in biochemical and morpho-physiological traits were recorded after 21 days. All the observations were noted in comparison to their respective control plants. Statistical analysis among treatments showed significant differences for PH, MSI, PRO, SPAD, gs, IL and PL, while treatment × variety interaction was significant for MSI, PRO and IL (Fig. 5a-d) (Table S2). For PRG 158, the RWC among the WS plants was low, whereas for Bahar it was lower in A−. For PRG 158, MSI in WS was significantly higher whereas for Asha and Bahar it was higher in A+. For PRG 158, proline accumulation in A+ was significantly lower by whereas for Asha in WS it increased in A+ and A−. Similar pattern of SPAD value was observed across all treatments among the studied varieties. in Plant height (PH) exhibited a significant increase under A+, whereas WS and A− showed a significant decrease. Significant decline was observed for LA under WS, A+ and A−. In the case of SLA, PRG 158 and Bahar showed a decrease in all three treatments compared to CON, whereas for PAU 881 and Asha the increase in SLA was observe for WS and A+ respectively. Among the varieties, IL showed a prominent increase in Asha under A+. PL showed a variation with WS and A− treatments across the different varieties. No significant variations were observed for PAU 881 for gs with treatments, whereas there was a decline of stomatal conductance for PRG 158, Asha and Bahar under WS.
Fig. 6
Long term effects of WS and soil drench of ABA solution (100µm) on root architecture after 21 days of recovery of PRG158 and Bahar
3.5. Varietal differences in root architecture following recovery from WS and ABA application
Root architecture of PRG 158 and Bahar was analyzed following long-term effects of WS and ABA treatments (Fig. 6a-d) and observation was recorded for RL, RSA, Diameter, Len/Vol, Root Vol, Nodule No, Tips, forks and Crossings (Fig. 7a-d) (Table S3). ANOVA revealed significant differences for treatments, varieties and their interaction for all the parameters except Tips, Forks and Crossings. In PRG 158, the root length for WS and in A− significantly decreased by 28% and 46% respectively whereas, in Bahar it was higher by 26% and 21%. Similarly, root surface area, in WS and A− significantly decreased by 15% and 40% in PRG 158, whereas in Bahar by 24% and 36%. While in PRG 158, there was no significant differences in average root diameter whereas for Bahar in WS, A+ and A− it was lower by 25%, 17% and 37% respectively. The total root length per volume in WS and A− was significantly lower by 29% and 47% in PRG 158, whereas in Bahar, in WS and A− it was higher by 22% and 21%.
Fig. 7
Comparison of root traits after 21 days of recovery from WS and soil drench of ABA solution (100µm) for PRG 158 and Bahar
In PRG 158, the root volume in A+ was higher by 22% and in A− it decreased by 35%. In Bahar in WS, A+ and A− it was lower by 41%, 39% and 57%. In PRG 158, the nodule number in WS was significantly lower by 28% whereas in Bahar in A+ it was lower by 40% and in A− higher by 28%. In PRG 158, number of root tips were reduced by 15%, 12% and 8% in WS, A+ and A− respectively whereas in Bahar in WS, A+, A− it was lower by 15%. In PRG 158, the number of forks in A+ significantly increased by 28% and in A− decreased by 45% whereas, a decrease of 20% in A+ for Bahar was observed. In PRG 158 the number of crossings decreased significantly by 60% in A−.
3.6. Candidate genes selection and primer designing associated with ABA mediated drought response
Six gene families were identified based on its association with ABA-mediated drought responses through extensive literature survey, KEGG pathway analysis and NCBI database searches. Out of these seven genes of PYR/PYL were identified. Phylogenetic analysis of the corresponding protein sequences classified these into three major classes (I, II and II). Notably, Class I was again classified into two main sub classes I and II while, class II and III did not show any major sub classes. Based on their phylogenetic positioning, PYL5 and PYL9 genes were selected for primer design both belong to subclass II of class I and expression analysis (Fig. 8).
Similarly, seven genes of PP2C were identified and classified into three major classes (Class I, II and III). Each class is categorized into two subclasses (I and II). The PP2C37 and PP2C8 genes belong to sub class I from class I and class III respectively. Primers were designed for both PP2C37 and PP2C8 (Fig. S4). Four genes were identified from SnRK gene family which was classified into three major classes (I, II and III), which was further subdivided into two major sub classes. The primers were designed for SnRK2A and SAPK belong to subclass I of class I and class III respectively (Fig. S5). Two genes of ABI were identified from ABF gene family, was further divided into 3 major classes (Class I, II, III). All the major classes were divided into two subclasses. The selected genes bZIP and ABI5 belong to subclasses I and II of class I respectively for which primers were designed (Fig. S6). Three genes of NCED and four genes of CYP were identified from NCED and CYP gene family respectively. The selected genes NCED1 belong to class III and CYP707A1 belong to class II respectively. The primers were designed for both the genes as shown in the Fig. S7; S8. Fig. S9 represents the phylogeny of all the selected genes. Out of 10 primers designed from 6 gene families, two primers of PYL9 and SnRK2A genes were used for qRT PCR analysis having key role in ABA mediated drought responses. The primers were designed with appropriate primer sequence, amplicon length and GC content (Table 1) using NCBI primer BLAST.
S.No. | Gene family | Gene | Gene ID | Primer sequence (5’-3’) | size | TmoC |
|---|---|---|---|---|---|---|
1 | PYR/PYL | PYL5 | XM_020356986.2 | GGGGCAAAGAGAGGGTGAAA (F) | 114 | 60 |
GGGCCTTTATGTGCTTGACG (R) | 60 | |||||
PYL9 | XM_020372171.2 | GAACCGAGGGAGAACCAGTG (F) | 81 | 60 | ||
TCTAACCAGCGACCACACAA (R) | 60 | |||||
2 | PP2C | PP2C8 | XM_020374556.2 | GAAAGTGTCCTTGCGACGTG (F) | 81 | 60 |
GCACCTTGATGCACTTGTCG (R) | 60 | |||||
PP2C37 | XM_020346647.2 | CCTCTCGATTCCACCTCACG (F) | 115 | 60 | ||
GAAGCTTGGGACGTTTGCAG (R) | 60 | |||||
3 | SNRK | SNRK2A | XM_020346370.2 | CTTTCTAGGCGAGAGTACGACG (F) | 107 | 60 |
GGGTCATCCTGGTCCTCAAA (R) | 60 | |||||
SAPK1 | XM_020353519.2 | GTCCTGCTGACACCAACACA (F) | 106 | 60 | ||
TCGCCTCATCCTCACTGAATC (R) | 60 | |||||
4 | ABI | ABI5 | XM_020346400.2 | ACAGTGGACGAGGTTTGGTC (F) | 117 | 60 |
GCAAGGGGCAGATTCGGTAT (R) | 60 | |||||
bZIP | XM_020378972.2 | TGCTCCCTTCTCTCCGATCT (F) | 103 | 60 | ||
CGACGATCTCCTTCCAGACG (R) | 60 | |||||
5 | NCED | NCED1 | XM_020369229.2 | CCCACATCATCATCCCCCAC (F) | 90 | 60 |
TTTGGGGAAGTGGAGCGTTT (R) | 60 | |||||
6 | CYP | CYP707A1 | XM_020376248.2 | GGGTGACGGCCAACTCATTA (F) | 105 | 60 |
TCTTCCCTCAAACGTGGCTC (R) | 60 | |||||
7 | GAPDH | GAPDH | Sinha et al. 2015 | ATGGCATTCCGTGTTCCTAC (F) | 95 | 60 |
CCTTCAACTTGCCCTCTGAC (R) | 60 |
Fig. 8
Schematic representation of methodology for primer designing of Pyl9 gene for qRT PCR
Fig. 8
Schematic representation of methodology for primer designing of Pyl9 gene for qRT PCR
SOV | DF | RWC | MSI | PRO | Fv/Fm | SMC |
|---|---|---|---|---|---|---|
Time | 2 | 10670.4** | 569.20** | 127.30** | 0.39** | 907.81** |
Treatment | 3 | 7740.5** | 1733.83** | 59.06** | 0.1** | 388.88** |
Variety | 3 | 903.5** | 513.44** | 0.86** | 0.01* | 11.29 |
Time*Treatment | 6 | 3376.4** | 1070.26** | 43.44** | 0.08** | 99.17** |
Time*Variety | 6 | 151.1** | 306.66** | 2.97** | 0.01** | 9.44 |
Treatment*Variety | 9 | 75.7** | 143.90** | 2.26** | 0.01** | 5.64 |
Time*Treatment*Variety | 18 | 43.90 | 106.14** | 2.57** | 0.004** | 3.40 |
Error | 96 | 27.80 | 46.61 | 0.001 | 0.001 | 10.30 |
GM | 63.51 | 17.64 | 1.16 | 0.62 | 20.49 | |
CV | 8.29 | 38.71 | 4.63 | 6.78 | 15.67 | |
SEm (Time) | 0.76 | 0.99 | 0.01 | 0.01 | 0.46 | |
SEm (Treatment) | 0.88 | 1.14 | 0.01 | 0.01 | 0.54 | |
SEm (Variety) | 0.88 | 1.14 | 0.01 | 0.01 | 0.54 | |
SEm (Time*Treatment) | 1.52 | 1.97 | 0.02 | 0.01 | 0.93 | |
SEm (Time*Variety) | 1.52 | 1.97 | 0.02 | 0.01 | 0.93 | |
SEm (Treatment*Variety) | 1.76 | 2.28 | 0.02 | 0.01 | 1.07 | |
SEm (Time*Treatment*Variety) | 3.04 | 3.94 | 0.03 | 0.02 | 1.85 | |
| *, ** = significant at the 5% and 1% level of significance respectively, (Where df = degrees of freedom, RWC = relative water content (%), MSI = membrane stability index (%), PRO = proline (µg/g FW). Fv/Fm = ratio of variable and maximum fluorescence/maximum quantum efficiency, SMC = Soil moisture content, GM = grand mean, CV = coefficient of variation) | ||||||
Treatments | Variety | LA | SLA | PH | RWC | MSI | PRO | SPAD | gs | IL | PL | SMC |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
A100NW | Asha | 29.82 | 10.11 | 0.23 | 76.37 | 12.08 | 0.22 | 35.33 | 38.22 | 0.93 | 2.56 | 25.32 |
A100W | Asha | 28.92 | 16.13 | 0.29 | 71.85 | 28.68 | 0.27 | 37.34 | 38.11 | 0.89 | 2.22 | 24.68 |
CON | Asha | 30.42 | 16.03 | 0.26 | 73.24 | 12.80 | 0.18 | 35.03 | 37.70 | 0.86 | 2.22 | 24.10 |
WS | Asha | 28.65 | 11.02 | 0.19 | 71.78 | 21.75 | 0.23 | 31.67 | 37.67 | 0.85 | 2.17 | 24.05 |
A100NW | Bahar | 30.32 | 12.00 | 0.18 | 69.10 | 14.03 | 0.12 | 35.47 | 37.33 | 0.81 | 2.17 | 23.71 |
A100W | Bahar | 31.17 | 16.61 | 0.22 | 77.78 | 15.70 | 0.11 | 37.33 | 34.67 | 0.73 | 2.13 | 23.60 |
CON | Bahar | 29.97 | 23.51 | 0.26 | 76.80 | 11.82 | 0.15 | 40.23 | 34.11 | 0.72 | 2.13 | 23.12 |
WS | Bahar | 29.28 | 17.70 | 0.44 | 75.86 | 12.51 | 0.13 | 32.03 | 31.56 | 0.69 | 2.09 | 23.10 |
A100NW | PAU881 | 30.47 | 7.72 | 0.20 | 76.17 | 8.89 | 0.21 | 36.78 | 26.67 | 0.69 | 2.08 | 21.65 |
A100W | PAU881 | 30.12 | 14.69 | 0.23 | 75.82 | 12.85 | 0.21 | 39.24 | 26.44 | 0.68 | 2.03 | 21.20 |
CON | PAU881 | 30.50 | 17.83 | 0.26 | 77.81 | 9.97 | 0.33 | 38.09 | 26.44 | 0.65 | 2.02 | 19.76 |
WS | PAU881 | 30.85 | 14.38 | 0.31 | 73.39 | 12.14 | 0.30 | 34.30 | 25.50 | 0.65 | 1.79 | 19.71 |
A100NW | PRG158 | 30.23 | 6.58 | 0.25 | 81.99 | 8.05 | 0.24 | 34.40 | 24.89 | 0.62 | 1.63 | 16.90 |
A100W | PRG158 | 30.67 | 13.78 | 0.23 | 73.32 | 13.86 | 1.32 | 36.06 | 24.11 | 0.62 | 1.60 | 15.50 |
CON | PRG158 | 30.92 | 21.93 | 0.45 | 82.65 | 9.98 | 0.30 | 37.29 | 23.22 | 0.60 | 1.58 | 14.87 |
WS | PRG158 | 31.00 | 8.35 | 0.23 | 67.60 | 32.09 | 0.32 | 32.61 | 23.11 | 0.54 | 1.25 | 14.50 |
GM | 30.21 | 14.27 | 0.26 | 75.10 | 14.82 | 0.29 | 35.83 | 30.61 | 0.72 | 1.98 | 20.99 | |
CV | 2.78 | 35.22 | 52.67 | 6.90 | 33.92 | 31.95 | 5.62 | 9.19 | 8.66 | 29.65 | 0.41 | |
LSD | 1.40 | 8.36 | 0.23 | 8.61 | 8.36 | 0.15 | 3.35 | 4.68 | 0.10 | 0.98 | 0.14 | |
| (Where, A100NW = ABA without water, A100W = ABA and water, CON = Control, WS = Water stress, SLA = specific leaf area, LA = leaf area, RWC = relative water content (%), MSI = membrane stability index (%), PRO = proline (µg/g FW), SPAD = chlorophyll meter reading (SCMR), PH = plant height (cm), gs = stomatal conductance (cm/s), IL = internode length (cm), PL = petiole length (cm), and SMC = soil moisture content, GM = grand mean, CV = coefficient of variation, LSD = Least significant difference) | ||||||||||||
Treatment | Variety | RL | RSA | AvDia | L/Vol | RV | Nodules | Tips | Forks | Crossings |
|---|---|---|---|---|---|---|---|---|---|---|
A100NW | Bahar | 376.28 | 84.88 | 0.73 | 417971.30 | 1.58 | 18.33 | 289.00 | 1223.00 | 135.67 |
A100W | Bahar | 303.73 | 84.48 | 0.96 | 325366.20 | 2.25 | 8.67 | 289.67 | 1017.67 | 130.00 |
CON | Bahar | 311.33 | 132.30 | 1.16 | 346850.00 | 3.71 | 14.33 | 338.33 | 1279.67 | 147.00 |
WS | Bahar | 391.03 | 100.35 | 0.87 | 423763.00 | 2.18 | 13.00 | 288.67 | 1297.67 | 146.00 |
A100NW | PRG158 | 306.87 | 79.05 | 0.78 | 342136.20 | 1.66 | 17.33 | 312.33 | 1134.00 | 115.00 |
A100W | PRG158 | 573.68 | 155.22 | 0.82 | 638783.80 | 3.08 | 20.33 | 355.33 | 1603.00 | 187.67 |
CON | PRG158 | 566.86 | 132.09 | 0.76 | 640890.70 | 2.54 | 19.33 | 386.33 | 596.00 | 801.33 |
WS | PRG158 | 406.54 | 111.88 | 0.81 | 455704.90 | 2.29 | 14.00 | 309.00 | 1147.67 | 117.00 |
GM | 404.54 | 110.03 | 0.86 | 448933.30 | 2.41 | 15.67 | 321.08 | 1162.33 | 222.46 | |
CV | 10.84 | 10.13 | 13.29 | 10.94 | 11.89 | 20.44 | 44.36 | 33.66 | 133.72 | |
LSD | 75.92 | 19.29 | 0.20 | 84996.78 | 0.50 | 5.54 | 246.53 | 677.14 | 514.90 | |
| (Where, A100NW = ABA without water, A100W = ABA and water, CON = Control, WS = Water stress, RL = root length, RSA = root surface area, AvDia = average diameter, L/Vol = root length/volume ratio, RV = root volume, number of nodules, number of root tips, forks, and crossings, GM = grand mean, CV = coefficient of variation, LSD = Least significant difference) | ||||||||||
3.7. Quantitative Real Time PCR
To investigate the relative expression levels PYL9 and SnRK2A genes involved in ABA mediated drought signaling, specifically targeting the stomatal and root architectural traits, RNA isolation, cDNA synthesis and qRT PCR were performed for PRG 158 and Bahar varying in crop maturity duration. In PRG 158, the fold difference under WS, A+ and A− was 48, 208, and 90 compared to control for PYL9 gene. Similarly, for SnRK2A the fold difference was 6, 17, and 7 respectively. Hence, WS, A+ and A− treatments showed an upregulation of PYL9 and SnRK2A expression levels. When we compared the quantitative expression between PYL9 and SnRK2A, PYL9 showed higher levels of gene expression compared to SnRK2A. In contrast, the Bahar genotype exhibited a markedly lower expression of PYL9, with fold changes of 0.003, 0.01, and 3.57 under WS, A+, and A–, respectively. For SnRK2A, the fold changes were 0.15, 0.07, and 4, respectively. Notably, A– treatment resulted in significant upregulation of both genes in Bahar (Fig. 9a–d), while WS and A + treatments had minimal impact.
Fig. 9
Relative expression (RE) of Pyl9 and SnRK2A genes from leaves after WS and ABA treatments at 3d time point in PRG 158 and Bahar
4. Discussion
Since drought is the major abiotic stresses which affects plant growth, development and productivity, the underlying morpho-physiological and biochemical adaptations at molecular level are activated. Among them, stomatal alterations, deep root system, drought resistant gene activation, production of soluble proteins, sugars, proline and glycine betaine, etc. plays a key role (Ozturk et al. 2021). Thus, to tolerate drought stress, plant cells undergo osmotic adjustment, detoxification of reactive oxygen species, partial stomatal closure and cellular signaling (Diouf et al. 2018).
It is well known among plants that both endogenous and exogenous ABA plays a major role during biotic and abiotic stresses through a crosstalk of metabolic pathways. In many crops, during drought stress it is identified that the ABA levels are altered to adverse environmental conditions (Mahajan and Tuteja 2005). Apparently, keeping in view the impact of exogenous application of ABA in mitigating drought, it was proposed as a useful approach (Sharma et al. 2023). Exogenous ABA application and their response on various crops during drought stress was reviewed by Rai et al. 2024. In A. thaliana, ABA led to the prevention of ethylene production and upregulation of transcriptional factors, whereas in C. lanatus an increased level of ClHSP70 were noted (Wang et al. 2023). However, there are certain ABA independent mechanisms also which play a vital role to alleviate the drought stress (Mathur and Roy 2021).
A
As we know, pigeon pea is an important grain legume, but in many rainfed areas the survival and yield of pigeon pea is severely challenged (Song et al. 2020). Recent study in pigeon pea showed that ABA could enhance the drought tolerance by regulating the genes related to flavonoid metabolism (Yang et al. 2021). Henceforth, as there are no reports relevant to the significance of exogenous application of ABA to overcome drought, current research was initiated to investigate both ABA dependent and independent mechanisms for varieties varying in maturity.4.1. Optimization of effective ABA concentration and method of application
It was very important to optimize the concentration of ABA, as a higher concentration of ABA would impose a negative effect on auxin flux and a lower concentration would promote root growth (Aslam et al. 2022). Although previous reports suggested various concentrations of ABA solution to be used for external application on different crops like maize − 100µM, 500µM (Jiang et al. 2022), wheat − 10µM, 0.1µM (Kosakivska et al. 2024), pearl millet − 100µM (Awan et al. 2021), soybean, green gram, black gram − 10µM (Vijayalakshmi et al. 2014; He et al. 2019) etc., yet pigeon pea persisted to be unexplored. Thus, to determine the effective concentration of ABA on pigeon pea two methods were implemented on 30 days old plants using ABA solution. 1. Foliar application 2. Pretreatment. Foliar spray of A-100 solution decreased the gs, TRL, LA, SLA compared to A-50 and A-150 which might be a positive adaptation towards drought stress as reported by Murali et al. 2025. However, foliar spray of ABA solution might not be an effective method for pigeon pea varieties with waxy coating on leaves.
When the plant roots were pretreated with ABA solution to check the effective concentration using two indicators i.e., MDA and proline, a significant elevation in MDA levels was observed after 3h when compared with the control. Proline, an osmolyte increased significantly after 6h of ABA treatment (100µM) which proves that pretreatment of 100µM significantly increases the MDA content from 3h and subsides by 6h, whereas, proline has accumulated enough, might be due to exogenous application of ABA, clearly indicates the improvement of water status via the integrated mechanisms related to lipid peroxidation and osmotic adjustment similar to the findings in barley (Skowron and Trojak 2021).
Thus, based on the morpho-physiological and biochemical analysis during foliar and pretreatment methods, the effective concentration of ABA was found to be 100µM for exogenous application for pigeon pea crop at vegetative stage, which is also in accordance with previous reports in pearl millet, rice, Arabidopsis and maize etc., (Awan et al. 2021; Ramachandran et al. 2021; Jiang et al. 2022).
During vegetative phase, in PRG 158 drought stress decreased RWC and increased proline and sugars similar to ICPL 151 (Nandwal et al. 1993). Drought stress for five days, led to a gradual increase in MDA content, a marker of lipid peroxidation and oxidative stress indicating the varietal adaptation to stress conditions. However, there was no significant difference in RWC in ABA treated plants compared to control. Whereas exogenous ABA applied plants were similar to control for PRO accumulation, TSS and MDA content as reported in O. sativa, L. esculentum, P. sativum and M. sativa (Rai et al. 2024).
However, when pigeon pea plants were exposed to WS for ten days, gs, LA, SLA, Fv/Fm, SPAD, SL, RFW/SFW, total biomass significantly decreased which is on par with previous reports (Suresh et al. 2016; Ouma et al. 2024; Murali et al. 2025). The substantial decrease in various morpho-physiological parameters clearly depicts the photosynthetic sensitivity and water regulation of pigeon pea during WS. Apparently, similar study was reported in soybean by Magdaong and Blankenship 2018.
4.2. Response time for ABA activation
Apart from effective concentration of ABA, it is also important to understand the response time frame of ABA activation for imparting stress tolerance. The leaf RWC and MSI decreases, and the proline accumulation increases to combat the water stress for survival in crops (Sakya et al. 2018). In current study, it was observed that under A−, there was decrease in leaf RWC and MSI and increase in PRO accumulation when compared to the plants under WS. It indicates that, exogenous ABA application showed a progressive impact on RWC, MSI and PRO accumulation from 3rd to 4th day of treatment similar to the study in barley (Skowron and Trojak 2021). Hence, keeping in view the results obtained, 3rd day was noted as an appropriate response time for molecular analysis.
The hypothesis was further tested on different varieties varying in crop maturity and drought tolerance. Three time points were designated i.e., 0d, 3d, 7d. All the varieties showed similar physiological and biochemical responses except Bahar which showed an increase in RWC and a decrease in PRO accumulation in A− (Fig. S3). These findings were similar to that in maize which showed a decrease in proline accumulation when ABA was applied under water stress (Dallmier and Stewart 1992). But increased RWC content might be due to the exogenous ABA which is affecting the stomata thereby maintaining the relative water content in leaves thus balancing the osmotic and oxidative stress (Diouf et al. 2018). Thus, in Bahar both the ABA dependent and independent pathways might be mitigating the water stress respectively.
The plant response to drought and subsequent rehydration is multifaceted which varies among different varieties. After rehydration, the plants might go through an adaptive change in morphology, structure, physiology, and biochemistry. These adjustments are the result of a complex interplay between stress stimuli, signal transduction, hormonal regulation, stomatal movement, and alterations in growth patterns (Xubo et al. 2025). Following rehydration, in WS and A− treatments, a decrease in gs in PRG 158 and Asha was observed. Possibly due to the adaptive changes during WS and A− might remain active even after rehydration (Xubo et al. 2025). As reported in many crops by Yi et al. 2016; Gao et al. 2024, certain morphological parameters like PH, LA, SLA and PL did not resume their responses after rehydration in tested pigeon pea varieties. During drought and rehydration, shift in the ABA levels can serve as a valuable bioindicator (Xubo et al. 2025).
4.3. Changes in root architecture
Roots exhibit an essential role in plant survival, growth and reproduction during drought (Kou et al. 2022). The modulation of RSA traits in response to water deficit is governed by sensing, signaling and gene expression (Janiak et al. 2016). Several reviews highlighted key genes and QTLs associated with drought adaptation (Siddiqui et al. 2021), particularly in major crops such as rice (Kim et al. 2020), wheat (Kulkarni et al. 2017) and grain legumes (Ye et al. 2018). Among varieties Bahar, a long duration variety showed a differential response in most of the parameters. Therefore, PRG 158 and Bahar were chosen for further study. In PRG 158, all the plants showed a significant variation for surface area, root volume, number of forks, tips and crossings in CON and A+. WS negatively impacted all the root traits while, under A−, exogenous ABA might impede or modify the RSA to sustain with the available water indicating the changes in root environment (Rai et al. 2024).
In Bahar, no significant variation was detected for RSA among all the plants in CON and A+ except surface area, diameter, root volume, number of nodules, number of tips and forks, which showed a significant increase in CON compared to A+ treatment. In A+, the exogenous ABA exhibited a negative impact on few root traits which clearly depicts that water availability, excess ABA and root traits are interconnected. It may be considered as biphasic effect as lower conc of ABA may act positively, whereas a higher conc of ABA may inhibit the RSA similar to a study in maize reported by Friero et al. 2022 stating the significance of ABA-Auxin interactions.
Compared to WS in A−, root surface area, diameter and volume decreased to sustain the local water availability indicating that changes to the root environment would directly affect ABA mediated responses in plants. Thus, higher levels of ABA restrict growth of lateral roots during water stress (Rai et al. 2024). Apparently, in maize a positive impact of ABA during WS was observed (Sharp et al. 2004), while a negative effect was observed in rice, Medicago and Arabidopsis (Yan et al. 2011; Gao et al. 2024). Therefore, a dual role of exogenous ABA could be detected during drought stress. When we compared PRG 158 and Bahar, there is an opposite effect observed in A+ treatment with relevance to SA, root volume, number of nodules, forks and crossings which could be due to the genotypic effect on hormonal interplay. Interestingly, exogenous ABA in the absence of water (A−), Bahar showed an increase in number of nodules which is an important finding in the current study.
4.6. Expression of genes associated with ABA
The PYR/PYL/RCAR proteins are involved in improving drought tolerance in Arabidopsis, tomato and rice (Aslam et al. 2022). In the presence of ABA, PYL9 suppresses the activity of PP2C, thereby facilitating the activation of SnRK2s. The activated SnRK2s trigger stomatal closure to minimize transpiration and might influence the root system architecture (Zhao et al. 2016; Aslam et al. 2022). In current study, we tried to decipher the ABA dependent and independent mechanisms by applying ABA solution exogenously under water stress (A−) and regularly watered conditions (A+) in two varieties. In PRG 158, the exogenous ABA could upregulate the expression of two major genes i.e., PYL9 and SnRK2A in A+ and A− conditions. When we compare the WS, A+ and A− treatments with CON, the PYL9 and SnRK2A gene expression was upregulated, physiologically there was no difference detected in tested parameters after 3rd day. Complex biphasic effects of exogenous ABA on root growth under regularly watered conditions were demonstrated by Li et al. 2017. But after recovery it was noted that WS treated plants showed a significant decrease in stomatal conductance and internode length but A− treated plants were similar to CON. It clearly indicated that ABA application has resumed the stomatal conductance after 21 days while WS plants did not show the normal stomatal conductance. A schematic representation of the morpho-physiological, biochemical and molecular responses with relevance to WS and ABA treatments in PRG 158 was shown in Fig. S10. A hypothetical model illustrating the effect of exogenous ABA in regularly watered, and water stressed conditions in PRG 158 representing the tentative ABA dependent pathway in Fig. 10.
Fig. 10
Representation of a hypothetic model illustrating the effect of exogenous ABA on well-watered and water stressed conditions in PRG 158. Depiction of ABA dependent mechanism in PRG 158
In case of Bahar, the expression of PYL9 and SnRK2A was significantly lesser in WS and A+ plants, whereas in A− an upregulation was observed. Comparative analysis of CON and A+ treatments revealed reduced expression of both the genes under A+, which indicates that exogenous ABA in the presence of water exerted no physiological impact on Bahar. However, the study after recovery showed that in A+ treatment, MSI was high, LA and SLA have decreased which could be a mark of sustaining the long-term benefit of leaf water status. When we compare the WS and A− treatments, though A− showed an upregulation for expression of two genes and surprisingly most of the physiological parameters tested showed similar responses as that of WS plants. But after recovery, RWC and LA were lesser compared to WS which depicts the survival rate of Bahar under WS conditions. A schematic representation of the morpho-physiological, biochemical and molecular responses with relevance to WS and ABA treatments in Bahar was shown in Fig. S11. A hypothetical model illustrating the effect of exogenous ABA in regularly watered, and water stress conditions in Bahar representing the tentative ABA dependent and independent pathways in Fig. 11.
Fig. 11
Representation of a hypothetic model illustrating the effect of exogenous ABA on well-watered and water stressed conditions in BAHAR. Depiction of ABA independent mechanism in BAHAR.
5. Conclusion
In current study, soil drenching with ABA solution has influenced ABA dependent and independent mechanisms either in the presence or absence of water which were variety specific. In PRG 158, during vegetative phase, soil drenching with 100µm of ABA solution along with minimal amount of water might help in the long-term drought response, whereas in the absence of water, the exogenous ABA application has shown a positive impact. In Bahar, under water stress a minimal amount of endogenous ABA was secreted but still could combat the stress condition. Whereas more prominent positive response was observed by application of exogenous ABA. The results indicated that it could be due to the multiple hormones leading to crosstalk mechanism. The study demonstrates that exogenous ABA application modulates drought responses through variety-specific ABA-dependent and independent pathways, with PRG 158 primarily engaging an ABA-dependent mechanism involving PYL9 and SnRK2A upregulation, while Bahar exhibits a mixed response with limited physiological benefits, suggesting differential strategies of drought adaptation in pigeon pea. As pigeon pea is a rainfed crop, it is suggested that during vegetative stage soil drenching of only 100µm ABA solution along with along with minimal irrigation would increase the drought tolerance and help in long term survival of the crop.
Supplementary Information
The supplementary material associated with this article is given as a separate links.
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Author Contributions
PK: Conceptualization, Methodology, Investigation & Writing Original draft. SB: Conceptualization, Methodology, Analysis, Review & Editing. MM: Conceptualization & Review. MR: Review and Editing. MV: Analysis. SVK: Institutional and Infrastructure support, review and editing.
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Declarationsand competing interests
The authors declare that they have no known financial interests or personal interest that could have inappropriately influenced the work reported.
Acknowledgements
The study was undertaken as part of the project on DST Women Scientist A, No. SR/WOS-A/LS-434/2017 (G), supported by the Department of Science and Technology (DST), Ministry of Science and Technology, Govt. of India. The authors gratefully acknowledge the support provided by DST.
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Data availability
The datasets generated or analyzed during the current study, including weather and crop season data, are available from the corresponding author upon reasonable request.
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Funding sources
This work was fully supported by the research grant from the Department of Science and Technology (DST), Ministry of Science and Technology, Govt. of India.
Additional Information
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All plant experiments were performed in compliance with relevant institutional, national, and international guidelines and legislation. All authors have reviewed and approved the final version of this manuscript for publication.References
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