Exogenous application of gamma-amino butyric acid alleviates temperature stress in mungbean (Vigna radiata) and its wild non-progenitor (Vigna glabrescens) by regulating heat shock protein genes

Exogenous application of gamma-amino butyric acid alleviates temperature stress in mungbean (Vigna radiata) and its wild non-progenitor (Vigna glabrescens) by regulating heat shock protein genes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Exogenous application of gamma-amino butyric acid alleviates temperature stress in mungbean ( Vigna radiata ) and its wild non-progenitor ( Vigna glabrescens ) by regulating heat shock protein genes Poornima Singh, Brijesh Pandey, Shalini Purwar, Chandra Mohan Singh, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7194231/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Nov, 2025 Read the published version in BMC Plant Biology → Version 1 posted 11 You are reading this latest preprint version Abstract Abiotic stresses significantly affect plant growth and productivity. Identification of stress-resistant genotypes is the best and an effective mitigation strategy. The present study evaluates the thermo-sensitive Vigna radiata cultivar Shikha and the thermo-tolerant Vigna glabrescens accession TCR-20 under the controlled (35–38°C), cold (20–30°C), and heat (45–48°C) stress conditions, without any treatment or treated with indole-3-acetic acid (IAA), salicylic acid (SA), and gamma-aminobutyric acid (GABA). Chlorophyll content analysis revealed that TCR-20 maintained higher chlorophyll content under stress, whereas Shikha exhibited higher chlorophyll content upon foliar spray of GABA. Histochemical staining confirmed an increased oxidative stress under extreme temperatures, with GABA effectively mitigating superoxide accumulation in both genotypes. Further, mining and comparative analysis of 96 heat shock proteins (HSPs), including HSP20, HSP60, HSP70, HSP90, and HSP100 was also done. Physicochemical characterization revealed varied stability, solubility, and thermostability of several proteins, which exhibited higher stress tolerance potential. All 96 HSPs were found widespread across the 11 chromosomes. Notably, the HSP70 family, particularly VrHSP-70.2 in TCR-20, exhibited the most robust response under both cold and heat stress, with significant upregulation, especially with GABA and IAA treatments. The genes such as VrHSP-70.2, VrHSP-60.22 , and VrHSP-20.24 highlighted their significant upregulations in TCR-20 over Shikha. Overall, these findings provide valuable insights into the molecular and physiological mechanisms underlying thermo-tolerance in Vigna species, emphasizing the role of HSPs and stress-mitigating treatments for improving stress resilience in Vigna crops. Cold stress Heat stress HSP Candidate genes Exons protein interaction network Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Introduction The genus Vigna is a diverse group of short-duration legumes. Among them, mungbean (Vigna radiata L. Wilckzek) is one of the most important warm season and widely cultivable food legume grown across many tropical and sub-tropical regions globally, and at many places throughout the year. Changes in temperature act as a major threat to crop adaptation and productivity under emerging climate change [ 1 – 4 ]. Mungbean can ideally grow between 30–40°C, lower temperatures leading to stunted growth, leaf defoliation and prolonged maturity, whereas high temperatures cause pollen abortion, flower drop, leaf injury, low seed filling and, ultimately, drastic yield loss. Therefore, both lower and higher temperatures lead to yield penalties [ 5 ]. Therefore, there is an urgent need to improve the temperature tolerance of mungbean to realize higher yield. However, it requires a comprehensive approach from identification to exploitation of potential donors for temperature tolerance in the breeding programmes [ 6 ]. Till date, limited donors have been reported for heat tolerance in different Vigna species [ 7 – 10 ]. Bhardwaj et al. [ 11 ] studied the response of mungbean genotypes to extreme temperatures, both low and high and suggested that heat is a complex trait and can be better understood by studying gene network analysis. Bhardwaj et al. [ 12 ] identified three mungbean genotypes i.e., IC76475, IC418452 and IC489062 as heat tolerant through morpho-physiological characterization and expression of key candidates, i.e., CP47, SUT, MTR_1g062190, MTR_7g092380, LOC101499292, VrLEA-55 (DHN). Likewise, a limited study was done for cold tolerance [ 13 ], which indicated that limited donors of mungbean have been reported which possess cold and heat tolerance. As we know that crop wild relatives (CWRs) are a reservoir of many useful genes, especially for stress tolerance [ 14 – 20 ], and exploring CWRs for heat and/ or cold tolerance may be a good option. Pratap et al. [ 21 ] identified the Vigna glabrescens accession TCR-20 as a potential donor for photo-thermo-insensitivity. They reported that this accession is able to flower between 4 and 44°C and produce viable pollen grains at both extremes of temperature. Further, Singh et al. [ 22 ] reported the expression of candidate genes and delayed chlorophyll degradation in the leaves of V. glabrescens, as the key leaf function leads to adaptation under high temperature. Stress tolerance may be improved by the induction/ elicitation of various genes. An exogenous application of phytohormones or other signaling compounds is now the trend to alleviate the harmful effects of various biotic and abiotic stresses. Angon et al., [ 23 ] reviewed work on phytohormones and re-ported many phytohormones that improve heat tolerance. Shao et al., [ 24 ] suggested a versatile role of polyamines in mitigating the effects of abiotic stresses. With the availability of the whole-genome sequence of mungbean as a reference [ 25 ], molecular breeding is now a sounder approach to tackle these stresses. Many reports have explored gene families and transcription factors for the identification of suitable candidates involved in various growth and developmental activities, hormonal regulation and stress responses in mungbean [ 26 , 27 ]. Singh et al. [ 22 ] in three Vigna species and studied their expression under heat stress. Recently, Singh et al. [ 28 ] performed a comprehensive characterization of candidate genes of SBT gene family and their comparative gene expression profile under heat and cold stress in the Vigna glabrescense indicated its potential of flowering under different temperature regimes. Heat shock proteins (HSPs) are known as a key candidate which plays a critical role during abiotic stress response and their cross-talk. Li et al., [ 29 ] identified 24 Hsfs as candidates in the mung bean genome, and expression profiling was performed under heat and cold stresses. It was noticed that the HSP genes are significantly regulated under the temperature stress, but the comprehensive analysis and its cross-species expression in V. glabrescens is still unexplored due to the unavailability of its whole genome sequence. Therefore, the present study was conducted to explore the small and large HSP gene families in mungbean, V. radiata (a relative of V. glabrescens) and its cross-specific gene expression under heat and cold stresses. This study provides new insights into the me-chanism of thermo-tolerance in Vigna glabrescens. Temperature-induced morpho-physiological responses The morpho-physiological responses of Shikha and TCR-20 were recorded to assess plant growth and temperature stress tolerance under control, cold, and heat stressed conditions, eithther untreated (H₂O as control) or treated with indole-3-acetic acid (IAA), salicylic acid (SA), and gamma-aminobutyric acid (GABA) (Fig. 1 ). It was observed that the performance of both genotypes was better under temperature stress conditions upon foliar priming with IAA, SA, or GABA. Cv. Shikha exhibited severe damage and wilting in most treatments, though GABA seemed to mitigate the effects slightly than the untreated one or treatment with SA. In TCR-20, the control treatment appeared healthy, but cold stress induced noticeable yellowing and stress symptoms, with IAA and GABA treatments demonstrating higher resilience to temperature. Cold stress led to lower cell damage as compared to heat stress. The chlorophyll-a (Chl-a), chlorophyll-b (Chl-b), and total chlorophyll (Chl) content in Shikha and TCR-20 were measured under control, cold, and heat stress conditions with treatments of H₂O, IAA, SA, and GABA, and also without treatment (CK) (Fig. 2 ). Chl-a was found to be significantly declined under temperature stress in shikha, whereas GABA application was found to be the most effective treatment with 14.25 µg/g in control, 10.25 µg/g under cold, and 8.27 µg/g under heat stress conditions. In contrast, TCR-20 exhibited 12.22 µg/g in control, 11.25 µg/g under cold and 11.1 µg/g under heat stress upon GABA treatment, showing a better stability of chl even under temperature stress conditions. GABA treatment in cv. Shikha also improved the Chl-b at 6.23 µg/g in control, 5.23 µg/g under cold, and 5.27 µg/g under heat. GABA was found to be the most effective treatment for both genotypes under cold and heat stresses. In Shikha, GABA-treated plants maintained the highest level of chlorophyll with 20.48 µg/g in control, 15.48 µg/g under cold stress, and 13.54 µg/g under heat stress. TCR-20 exhibited a similar pattern, with GABA-treated plants retaining 17.37 µg/g in control, 16.35 µg/g under cold stress, and 12.27 µg/g under heat stress. TCR-20 demonstrated better resilience under both cold and heat stresses. Histochemical staining was done using NBT and DAB to visualize the accumulation of superoxide anions (O2–) and hydrogen peroxide (H2O2) under non-stress or stress (Fig. 3 and Fig. 4 ) conditions. It confirmed the increased oxidative stress under both, cold and heat stresses. The maximum cell damage was recorded in the unprimed conditions upon cold and heat stress treatments. Foliar application of phytohormones was able to alleviate the temperature stress significantly. GABA-treated genotypes showed minimum cell death under cold and heat stress in both genotypes, indicating lower oxidative stress levels. Overall, it was observed that GABA effectively mitigated the oxidative damage in Shikha and TCR-20. A further quantitative estimation of H₂O₂ and O₂ highlighted the significant differences between these genotypes under control and stress conditions, reflecting their varying oxidative stress responses and regulation. Shikha showed higher H₂O₂ levels with a sharp increase of up to 210.5 µmol/g under heat stress conditions. Likewise, TCR-20 exhibited their better regulation, with levels peaking at 150.89 µmol/g. On the contrary, treatments with IAA, SA, and GABA reduced H₂O₂ in both genotypes, whereas SA and GABA were found to be the most effective treatments, which maintained the level of H2O2 at 112.25 µmol/g and 115.25 µmol/g, respectively, in TCR-20. Likewise, a similar trend of the O₂ levels rising significantly was observed under control (53.27 to 150.38 µmol/g at 6-DAWL), indicating oxidative stress, while treatments, especially GABA (110.28 µmol/g), reduced the O2levels as TCR-20 showed lower O₂ levels under control (50.67 to 80.27 µmol/g), with GABA treatment maintaining the lowest level (51.89 µmol/g). Mining, Physicochemical Properties and Functional Insights of HSPs A total of 96 heat shock proteins (HSPs) and chaperonin proteins (Cpn60) were identified in V. radiata. These include HSP20 (VrHSP-20.1 to VrHSP-20.28), HSP60 (VrCpn60_TCP1.1 to VrCpn60_TCP1.23), HSP70 (VrHSP-70.1 to VrHSP-70.17), HSP90 (VrHSP-90.1 to VrHSP-90.7) and HSP100 proteins (VrHSP-100.1 to VrHSP-100.21), presented in Table-S1A & S1B. The analysis of key properties such as peptide sequence length, molecular weight, isoelectric point (pI), instability index, aliphatic index, and GRAVY scores provides insights into protein stability, function, and adaptation under stress conditions. The protein size ranged from 6.97 kDa (VrHSP-70.15, 62 amino acids) to 575.51 kDa (VrHSP-100.20, 5057 amino acids), reflecting its diversity from small stress-responsive proteins to large chaperonins. The pI values ranged from acidic (pI = 4.46, VrHSP-70.16) to highly basic (pI = 10.22, VrHSP-70.5). Lower pI values suggested higher acidic amino acid content, influencing solubility and function under different pH conditions, while higher pI values indicated a greater proportion of basic residues like lysine and arginine, potentially aiding nucleic acid interactions. Proteins with an instability index > 40 are considered unstable, likely functioning as transient stress-responsive proteins. The VrHSP-20.3 (36.3) and VrCpn60_TCP1.1 (30.92) were found to be the most stable, whereas VrHSP-20.1 (59.13) and VrHSP-100.5 (53.52) were found to be the most unstable. Likewise, VrCpn60_TCP1.3 (119.96) and VrHSP-70.16 (112.45) were highly stable under heat stress, while VrHSP-20 (55.37) and VrHSP-100.4 (75.47) might have reduced thermal stability. Most of the proteins, such as VrHSP-20.1 (-0.710) and VrCpn60_TCP1.12 (-0.061), had negative GRAVY scores, indicating hydrophilicity and cytoplasmic solubility. However, VrCpn60_TCP1.3 (+ 0.227) and VrCpn60_TCP1.9 (+ 0.197) were noticed to be more hydrophobic, playing roles in the membrane interactions. Distribution of HSPs The HSP genes were distributed across various chromosomes (Fig. 5 ). For instance, HSP20 genes were found across all chromosomes except LG04 and LG01. These genes have shorter genomic lengths (e.g., VrHSP-20.19, 6546 bp, 10 exons) and simpler struc-tures. Cpn60 genes were distributed across multiple scaffolds and chromosomes, with larger genomic lengths (e.g., VrCpn60_TCP1.5, 6570 bp) and longer CDS lengths (e.g., VrCpn60_TCP1.5, 6450 bp). Likewise, HSP70 genes were dispersed across different scaffolds and chromosomes (e.g., Vr06, Vr08), with genomic lengths up to 3186 bp (VrHSP-70.2). HSP90 genes were also broadly distributed (e.g., LG01, LG06, LG11). HSP100 Involved large genes (e.g., VrHSP-100.3, 8647 bp), indicating their complex structures for protein disaggregation and degradation under extreme stress conditions. This analysis highlighted the structural diversity of HSPs and Cpn60 in V. radiata, em-phasizing their importance in plant stress tolerance, protein stability, and cellular recov-ery mechanisms. Understanding these properties can aid in developing stress-resilient crops through targeted breeding and biotechnological interventions. Phylogeny, Domain, Motif, exon-intron analyses The phylogenetic relationship analysis of HSP candidates demonstrated a complex pic-ture of evolutionary adaptation, with different families (Fig. 6 ). The phylogenetic tree appeared to be linked to a specific family of proteins with domain organization alongside the tree (Fig. 7 ). The phylogeny of 28 HSP-20 candidates was grouped into five sub-families which shared similar domain architectures and evolutionary relationships, for example, ACD, for alpha-crystallin domain. The length of the domains varied across the proteins, which suggested structural diversity within the HSP-20 family. The clustering of the HSP-60 protein into seven subgroups with TCP domain was found highly conserved across the family, though the additional domains indicated potential differences in regulatory functions or protein interactions. The HSP-70 family was divided into five subclusters (A to E), with a GRAS domain, which are important in plant signaling pathways, including those related to gibberellin responses. The domain architecture included highly conserved regions with some varia-bility in other regions, which may correspond to functional differences. Likewise, the HSP 90 family was divided into two subclusters (A-B), with the GHD domain, which is related to gibberellin pathway-related proteins. The variability in the domain structure of these HSP-90 proteins was also noticed. Likewise, HSP-100 candidates were grouped into three subclusters (A-C), with a large heat shock protein family involved in protein dis-aggregation and refolding. The domain structures of these proteins demonstrated that several candidates had well-conserved functional domains (e.g., AAA + ATPase domain) essential for their role in heat stress recovery. The diversity in domain architecture across this family indicated a high degree of specialization and adaptation to different stress conditions. Each domain showed evolutionary relationships within a protein family. The closely related proteins were grouped together, while more distant branches represented proteins that have distinct functions. Across all protein families, specific domains were found to be conserved. The chromosomal localization of Vigna HSP genes revealed their widespread distribution across all 11 chromosomes, with distinct clustering patterns. Chromosome 7 exhibited the highest HSP gene density, featuring two major clusters: 0.0–14.6 Mb (VrHSP-20.19, VrHSP-70.6, VrHSP-70.7) and 33.8–46.9 Mb (VrHSP-70.8, VrHSP-20.21, VrHSP-100.8), in-dicating a critical role in stress adaptation. In contrast, Chromosome 3 harbored the fewest HSP genes, with only a single cluster (12.3–13.0 Mb, VrHSP-20.14, VrHSP-100.16), suggesting a limited role in stress-response gene distribution. Other chromosomes displayed varying densities, with co-localization of HSP and Cpn60 genes, indicating potential functional interactions. This uneven distribution suggests chromosome-specific roles in stress The exon-intron analysis across the different HSP genes underscores the diversity within HSP gene structures (Fig. 8 ). This structural variation likely contributed in the func-tional adaptability of these genes, allowing the plant to respond to different types of en-vironmental stresses. Genes with more exons and introns may undergo alternative splicing, which can lead to different protein isoforms, further supporting the plant’s ability to manage stress at a molecular level. In HSP-20, VrHSP-20.11 had maximum ex-ons, indicating a complex structure that may enable alternative splicing and a more sig-nificant regulation of protein expression under stress conditions, while gene VrHSP-20.5 had the fewest exons, which likely allows for faster transcription and translation, asso-ciated with quick responses to the stress. In HSP 60, VrCpn60_TCP1.7 had the highest number of exons, while VrCpn60_TC had the lowest exons. In HSP 90, VrHSP-90.5 stands out with the most exons, while VrHSP-90.4 had the fewest exons. In HSP 100, VrHSP-100.12 has the maximum exons. Across all HSP, genes with more exons, such as VrCpn60_TCP1.7 and VrHSP-100.8, exhibited structural complexity that allows for reg-ulatory versatility and potential alternative splicing. This could enable the generation of multiple protein forms, catering to different stress conditions or stages of response. In contrast, genes with fewer exons, like VrHSP-20.5 and VrHSP-20.6, have streamlined structures that support rapid transcription and may be involved in immediate or primary stress responses. The diversity in exon-intron structure across these gene families un-derscores the adaptability of the HSP gene family, balancing rapid reaction capabilities with genes suited for long-term or nuanced regulatory roles. Motif analysis of the HSP-20 family identifies the specific locations of conserved motifs within the amino acid sequence (Fig. 9 ). The consensus sequence logos for each HSP family illustrate the most conserved residues with letter sizes representing the degree of conservation. The identified motifs include RAMQGWHSQRLLGNG for HSP-20, DFM/LRQYTWDKHLETW for HSP-60, KRLIGRR/KFADPEVQ for HSP-70, and PPGYYGYE/TEGGQ/VLTE for HSP-100. These conserved sequences provide insights into the functional domains critical for heat shock protein activity across different HSP families. Protein-Protein interaction The protein-protein interaction (PPI) analysis in selected candidates representing different HSP subfamilies highlighted a well-coordinated chaperone system involving HSP-20, HSP-60, HSP-70, HSP-90, and HSP-100, which play crucial roles in stress tolerance, par-ticularly under heat and cold stress conditions (Fig. 10 ). HSP-20 proteins (HSP-20.11, HSP-20.13, and HSP-20.6) interacted with HSP-70.8, suggesting their role in preventing protein aggregation and maintaining cellular homeostasis under stress. HSP-60 (Cpn60/TCP1 family proteins) strongly interacted with HSP-70 and HSP-90, indicating their involvement in protein folding and stabilization in mitochondria and chloroplasts, essential for stress adaptation. HSP-70 proteins (HSP-70.2, HSP-70.8, and HSP-70.12), which form the core of the heat shock response, interacted with HSP-90.6 (endoplasmin homolog) and HSP-100.2 (ATP-dependent Clp protease), highlighting their role in protein refolding, degradation of misfolded proteins, and stress recovery mechanisms. The strong interaction between HSP-70.2 and HSP-90.6 (score 0.974) underscored their functional synergy in maintaining protein stability under extreme temperatures. HSP-100.2’s interaction with HSP-70 proteins suggested its function in removing irreversibly damaged proteins, which is particularly crucial during heat stress. The overall network suggested that HSP-20 prevents aggregation, HSP-60 and HSP-70 assist in folding and stabilization, HSP-90 regulates signaling pathways, and HSP-100 facilitates protein degradation, all working together to enhance the plant’s thermo-tolerance and cold stress resilience (Table S2 ). Expression of VrHSP Genes under Heat, Cold stress with treated with Salicylic Acid (SA), Auxin (IAA), and GABA Treatments The expression of various VrHSP family genes was analyzed in the susceptible genotype Shikha and the resistant genotype TCR-20 under cold and heat stress conditions, with or without hormonal priming treatments with indole-3-acetic acid (IAA), salicylic acid (SA), and gamma-aminobutyric acid (GABA) (Fig. 11 ). The comparative expression levels indicated significant differences between these two genotypes, demonstrating a robust and consistent response to both cold and heat stresses. VrHSP-20.2 and VrHSP-20.6 showed significantly higher expression levels under both cold and heat stresses in TCR-20, particularly with GABA and IAA treatments. Likewise, in Shikha, VrHSP-20.2 showed moderate induction under heat stress, while VrHSP-20.6 was highly up-regulated under cold stress and significantly down-regulated under heat stress. In comparison, the change in TCR-20 was higher under both stress conditions, especially with GABA and IAA treatments. VrHSP-20.11 showed strong heat-induced expression in both genotypes, with a higher increase in TCR-20, particularly under GABA (45.5-fold) and SA (26.7-fold) treatments. VrHSP-20.13 was highly induced by heat stress, with a significantly higher expression in TCR-20, especially with GABA and IAA treatments. Shikha exhibited moderate expression increases under heat stress. The expression of VrHSP-20.19 was completely suppressed in Shikha under both heat and cold stress conditions, whereas in TCR-20, it was upregulated under cold stress upon IAA and SA treatments. Under the heat stress, GABA highly induced the VrHSP-20.19 expression in TCR-20 (Fig. 6 a and Fig. 6 b). VrHSP-20.24 showed strong up-regulation to both cold and heat stresses in TCR-20, with the highest expression observed with GABA (64.5-fold), followed by IAA (47.8-fold) under heat stress. In Shikha, it was moderately induced under cold stress, but significantly suppressed under heat stress, with lower fold changes as compared to TCR-20. The VrHSP-60.8 exhibited higher basal expression in Shikha, with significant upregulation under cold stress, particularly with IAA (14.3-fold) and SA (19.5-fold). In TCR-20, basal expression was lower, but cold stress induced the response with higher expression upon treatment with GABA (8.6-fold) and SA (6.1-fold). Heat stress induced significant increases in VrHSP-60.8 in TCR-20, with the highest increase observed upon treatment with GABA (60.0-fold), followed by SA (52.9-fold), and IAA (40.0-fold), whereas Shikha showed lower changes (3.7-fold for IAA and 2.6-fold for GABA). VrHSP-60.11 exhibited stronger expression in TCR-20 under both cold and heat stresses, with the highest induction under cold stress, particularly with IAA (37.6-fold), SA (35.6-fold), and GABA (33.8-fold) treatment. In Shikha, IAA treatment (15.6-fold) showed the highest induction under cold stress, while heat stress induced moderate increases in the response of this gene upon treatment with SA (30.8-fold) and IAA (18.8-fold) (Fig. 6 ). VrHSP-60.20 exhibited substantial upregulation under cold stress in Shikha, especially with GABA (58.7-fold) and IAA (44.6), and moderate induction was noticed upon SA treatment (11.4-fold). Heat stress also induced a notable increase in the expression of VrHSP-60.20 upon IAA (51.2-fold), SA (52.2-fold), and GABA (48.4-fold) treatments. Likewise, in TCR-20, the significant upregulation of VrHSP-60.20 was observed under cold stress conditions upon treatment with GABA (84.4-fold) and SA (52.3-fold). Likewise, heat stress led to strong upregulation of VrHSP-60.20 upon GABA (74.7-fold) and SA (71.3-fold) treatments. VrHSP-60.22 showed higher basal expression in Shikha under control conditions, with the highest change observed with SA (11.2-fold), followed by IAA (2.0-fold). Cold stress induced the highest expression in SA (26.6-fold) and IAA (19.7-fold), while heat stress led to a decrease, particularly with SA treatment (1.0-fold). In TCR-20, the cold stress resulted in significant upregulation of IAA (81.9-fold), GABA (12.5-fold), and SA (4.2-fold). Heat stress induced dramatic increases, particularly with GABA treatment (124.2-fold), followed by SA (95.8-fold) and IAA (64.0-fold) (Fig. 6 a and 6 b). In Shikha, cold stress led to significant upregulation in VrHSP-70.12 upon IAA (8.7-fold) and SA (8.5-fold) treatments, while GABA caused a moderate increase (3.8-fold). Under heat stress, the increased expression of VrHSP-70.12 was recorded upon treatment with IAA (5.2-fold), SA (9.3-fold), and GABA (15.7-fold). In TCR-20, cold stress resulted in mild changes in expression of VrHSP-70.12, whereas heat stress caused a substantial increase in IAA (22.3-fold), SA (12.4-fold), and GABA (38.7-fold), indicating a stronger heat stress re-sponse. The gene VrHSP-70.2 showed enhanced expression in Shikha upon IAA (8.7-fold) and SA (8.5-fold) treatment, while GABA showed a 3.8-fold increase. Under heat stress, IAA (5.2-fold), SA (9.3-fold), and GABA (15.7-fold) treatments showed a significant upregulated expression pattern. In TCR-20, heat stress induced a significant increase upon IAA (42.3-fold), SA (32.4-fold), and GABA (74.7-fold) treatments, while cold stress led to notable expression upon IAA (17.4-fold) and SA (38.8-fold). VrHSP-90.6 exhibited higher expression under cold stress in Shikha, particularly upon treatment with IAA (6.6-fold), SA (4.5-fold), and GABA (5.0-fold), whereas heat stress led to moderate upre-gulation upon GABA (4.1-fold) treatment, but a decline upon SA treatment (0.6-fold). In contrast, TCR-20 showed a robust response under the heat stress, with the highest ex-pression upon SA (19.5-fold) and GABA (18.3-fold) treatment. VrHSP-100 showed strong induction under cold stress with SA (30.1-fold) and IAA (18.2-fold) treatments in Shikha, while no treatment resulted in a downregulated expression (0.4-fold). Under heat stress, increased expressions were observed upon IAA (3.4-fold) and GABA (4.1-fold) treatments, though priming with SA showed decreased expression (0.7-fold). Likewise, in TCR-20, the expression of VrHSP-100 was significantly higher under heat stress, particularly with GABA (31.3-fold) and SA (19.9-fold) treatment. Likewise, cold stress also induced strong upregulation upon SA (21.6-fold) and GABA (30.4-fold) treatment. Principal Component Analysis (PCA) for HSP candidates The PCA of HSP gene expression data provides valuable insights into the differences between the stress response of the susceptible genotype Shikha and the tolerant genotype TCR-20 (Fig. 12 ). The 3D PCA plot visually represents these differences, with each point corresponding to a gene expression pattern under temperature stress conditions. In the present study, the three principal components (PC1, PC2, and PC3) summarized the variances in gene expression, allowing for a clear distinction between the contrasting genotypes. A key observation from the PCA plot was the distinct clustering of TCR-20 and Shikha, indicating significant differences in their transcriptional responses to cold and heat stresses. TCR-20 exhibited a wider spread across all three principal components, reflecting greater variability in gene expression. This suggested that TCR-20 had a more dynamic and regulated response to the stress, likely due to the upregulation of key HSP genes such as VrHSP-60.22, VrHSP-70.2, and VrHSP-60.20. In contrast, Shikha remained tightly clustered, indicating a more uniform and less adaptable response to environmental stressors. The separation along PC1, which captured the highest variance in gene expression, highlighted the fundamental transcriptional differences between the two genotypes. PC2 and PC3 further differentiated the expression patterns based on specific stress treatments, such as SA and GABA, which are known to enhance stress tolerance. The results confirmed that TCR-20 exhibited a stronger and more varied gene expression response, aligning with its superior thermo-tolerance. It provides strong evidence that TCR-20 is better equipped to cope up with heat and cold stresses, the stress adaptation being derived from key HSP genes. Discussion Climate change continuously threatens agricultural productivity, with plants facing numerous biotic and abiotic stresses due to their dynamic nature [ 30 , 31 ]. Among the abiotic stresses, both, cold and heat are critical to plant growth, development, and re-production [ 32 , 33 ]. These adversely affect photosynthesis, plant growth, and overall re-productive success [ 34 ]. The decline in photosynthetic efficiency is primarily driven by excessive reactive oxygen species (ROS) accumulation, heat-induced protein denaturation, and disruptions in key enzymatic activities [ 35 ]. In such situations, phytohormones play a crucial role in enhancing stress resilience by regulating biochemical, molecular, and physiological responses, thereby supporting plant growth and development under adverse conditions [ 36 – 39 ]. The present study highlights the differential stress responses of V. radiata cv. Shikha and V. glabrescens genotype TCR-20 under cold and heat stresses. GABA was found to be the most effective treatment in mitigating the chlorophyll loss and oxidative stress. TCR-20 maintained higher chlorophyll levels, especially under the cold stress, while Shikha exhibited better retention under the heat stress. Histological analysis revealed an increased oxidative damage to Shikha, with higher H₂O₂ accumulation as compared to TCR-20. GABA significantly reduced the oxidative stress markers in both genotypes, suggesting its protective role in stress tolerance. TCR-20 exhibited better intrinsic stress regulation, while Shikha benefited more from GABA, making it a prom-ising treatment for enhancing resilience in Vigna species. Differential chlorophyll retention and oxidative stress responses were observed in Shikha and TCR-20 under cold and heat stresses. In mungbean, studies have shown that exogenous GABA application improves chlorophyll stability and mitigates oxidative damage under heat stress [ 40 ]. Li et al. [ 41 ] reported that GABA was able to alleviate the harmful effects of cold stress in Medicago by promoting endogenous GABA metabolism, protecting the membrane system, and improving the leaf structure. For instance, GABA-treated rice plants exhibited higher chlorophyll retention and lower H₂O₂ levels, leading to enhanced photosynthetic effi-ciency and stress tolerance [ 42 – 45 ]. Furthermore, GABA improved the rice performance under both well-watered (FC100) and drought-stressed (FC50) conditions, improving resilience and supporting global food security. Similarly, in Triticum aestivum, GABA application has been reported to enhance antioxidant enzyme activity, reducing reactive oxygen species (ROS) accumulation under drought and heat stresses [ 46 , 47 ], aligning with our findings from the present study that GABA mitigated oxidative stress (In le-guminous crops, Glycine max (soybean) and Medicago sativa (alfalfa) also showed im-proved stress tolerance with GABA treatment, mainly through the activation of stress-responsive genes and antioxidant enzymes such as superoxide dismutase (SOD) and catalase (CAT). These enzymes help regulate ROS levels, reducing H₂O₂ accumula-tion, as also observed in TCR-20 under cold stress. Similarly, studies in Arabidopsis tha-liana, and sunflower also demonstrated that GABA improved stomatal regulation and enhanced metabolic adjustments under heat, cold, and other abiotic stresses [ 48 , 49 ], which could explain its effectiveness in stabilizing chlorophyll content, antioxidant en-zymes in Vigna genotypes. Exogenous GABA enhanced the flavonoid synthesis, proline accumulation, and antioxidant enzyme activity under elevated O₃, which are able to re-duce the H₂O₂ and malondialdehyde levels. A reduction in wheat grain yield loss from 19.6–9.6%, highlighted GABA’s potential in mitigating O₃-induced crop damage [ 50 ]. The contrasting responses between Shikha and TCR-20 under stress suggested the ge-notype-specific adaptations. TCR-20 showed superior cold tolerance and oxidative stress regulation, resembling the findings in cold-tolerant rice cultivars that maintain better ROS homeostasis. Similar to GABA, SA is also well known for its role in systemic acquired resistance (SAR), providing long-term protection against biotic stress. Studies in Oryza sativa, Zea mays, and Triticum aestivum have demonstrated that exogenous SA application improves drought tolerance by enhancing stomatal regulation and osmoprotectant accumulation. In wheat, exposure to elevated O₃, SA might further contribute to stress mitigation by reducing lipid peroxidation and improving antioxidant defenses [ 51 , 52 ], complementing GABA’s protective effects. In our study, Shikha had greater susceptibility to oxidative stress, but a stronger response to GABA aligns with the studies on heat-tolerance in many crops, where GABA treatment enhanced tolerance by modulating metabolic and hormonal pathways for improving the heat tolerance [ 53 – 55 ]. Thus, inte-grating both SA and GABA into crop management strategies could offer a synergistic approach to enhancing resilience against environmental stressors. The plant hormone, auxin, is a key regulator of plant growth and development, playing pivotal roles in the integration of abiotic stress signals and control of downstream stress responses [ 56 ]. Recent advancements suggested that auxin influences stress mitigation by modulating pH and activating proton pumps, thereby altering transport dynamics. Models such as those by Steinacher et al. [ 57 ] and Mellor et al. [ 58 ] highlight auxin's role in regulating cellular responses, including lateral root emergence. These insights dem-onstrate the role of auxin in stress resilience by reducing lipid peroxidation, enhancing antioxidant defenses, and auxin signaling [ 59 ]. The phylogenetic tree showed a comparative evolutionary analysis of different heat shock proteins (HSPs) in Vigna radiata, as it is distinctly grouped based on their sequence similarity and relationships. The different clusters of the tree divide the families of the proteins sharing common ancestors distinctively [ 60 ]. These clusters can give insights into how these proteins may have diverged functionally while retaining core structural similarities. For instance, the VrHSP-20 gene family indicated that these small HSPs are closely related to each other and might have evolved specific functions, such as in-volvement in stress responses. These small heat shock proteins are typically involved in preventing protein aggregation during stress. The HSP-70 and 90 gene families are cha-perone proteins known for their role in protein folding, unfolding, and transport across membranes [ 61 – 63 ]. The Cpn60 chaperonins assist in protein folding, particularly under stress conditions, and maintain proteostasis. The HSP-100 family of proteins plays crucial roles in protein disaggregation and refolding during severe heat stress. In the present study, VrHSP-70 proteins formed multiple distinct branches, indicating that this family has undergone several rounds of gene duplication and specialization. This diversity is consistent with their multifaceted roles in responding to heat, cold, and other stress factors. On the contrary, Cpn60 proteins formed a close cluster, suggesting that these proteins have retained more structural and functional conservation as compared to the more diverse HSP families. Likewise, the VrHSP-100 family showed a clear cluster, with several proteins grouping together, which indicated their specialized function in high-temperature stress conditions. These proteins are known for their ability to dis-aggregate protein aggregates formed under extreme conditions. The distinct grouping of these proteins in the tree provided a framework for predicting their biological roles. Understanding the evolutionary relationships could help in studying how these proteins might have adapted to specific stresses, such as heat, drought, or pathogen attack. This phylogenetic tree revealed the evolutionary relationships among different heat shock proteins and chaperonins, highlighting how gene duplication and divergence have led to the specialization of these proteins in various stress response mechanisms [ 64 ]. This in-termixing of HSP families in the phylogeny implies that the HSP gene network adapted to environmental challenges by developing flexible and overlapping functions. Gene duplication events, especially in the HSP20 and HSP70 families, appear to have created a pool of paralogous that diversified to assume varied roles, which might explain why these families do not form exclusive clades [ 65 ]. Instead, the overlap in evolutionary branches indicated a convergence where genes from different families might perform similar functions or assist each other in maintaining protein stability during stress. This pattern of phylogenetic intermixing highlighted an evolutionary strategy in Vigna radiata where HSP genes from distinct families co-evolved to create a versatile and cooperative system for stress resilience, supporting the plant’s adaptability to diverse environmental stresses. The motifs likely represent critical domains, such as the alpha-crystallin domain in the HSP-20 family, involved in heat shock response. The major domain in HSP-20 is the α-crystallin domain, characteristic of small HSPs (HSP20 family). This domain functions as a molecular chaperone, binding to partially denatured proteins and preventing irre-versible aggregation. This protective mechanism is essential under heat and oxidative stress, as it preserves cellular integrity by stabilizing proteins that may become damaged or misfolded due to environmental challenges [ 66 , 67 ]. Motif analysis of HSP 60 revealed that it is rich in TCP transcription factor. Each motif is positioned along the protein se-quences, and the p-values indicate the statistical significance of the motif's occurrence. The TCP domain motif, along with additional motifs, may be crucial for DNA-binding and regulatory functions. The consensus logos represent key conserved residues that are essential for the function of TCP proteins [ 68 ]. The motifs are specific to DNA-binding domains or other regulatory regions. The motif of HSP 70 (GRAS Domain rich family), GRAS domain, along with other motifs, may be essential for interactions with other proteins or transcriptional regulation [ 69 ]. These motifs are probably involved in tran-scriptional regulation and signaling pathways in plants [ 70 ]. HSP 90 also k/a (GHD Fam-ily), the consensus sequence logos for the GHD family show the conserved amino acids in each motif. These are critical for the protein's role in regulating plant growth and hormone signaling [ 62 , 71 ]. The HSP 100 consensus sequences highlight the key conserved regions in the HSP-100 family. These motifs may be involved in ATP binding, protein refolding, and interaction with other chaperone proteins [ 72 ]. The VrCpn60/TCP1 family had a total of three domains, of which one is a major domain reported, which are responsible for assisting in protein folding and assembly, showing unique clustering patterns in the phylogenetic tree. The dominant domain was the TCP-1 chaperonin domain, which is crucial for the proper folding and assembly of cytoskeletal proteins, such as actin and tubulin [ 73 ]. Under the stress conditions that may lead to protein misfolding, this domain helps maintain cellular structure and stability by ensuring that these essential proteins fold correctly [ 74 ]. In VrHSP70, four domains are there, in which the core domain architecture includes the HSP70 domain, known for its ATPase activity, which allows the binding and refolding of misfolded proteins. This activity provides energy for repeated cycles of binding and release, supporting protein stability and folding, especially under conditions where proteins are prone to denaturation [ 75 , 76 ]. Some candidates of the HSP70 family also contained additional motifs, indicative of evolutionary adaptations that allow them to perform specialized cellular functions. The HSP 90 domain across these proteins, such as kinases and hormone receptors, is essential for maintaining the protein conformation and stabilizing regulatory proteins. HSP90 functions as part of multi-protein complexes and is especially critical during prolonged stress, as it helps protect essential regulatory proteins from denaturation [ 77 – 79 ]. The candidates of HSP100 family demonstrated the most complex domain architecture among the families analyzed. The AAA + ATPase and Clp domains were present in various combinations across the VrHSP100 members, enabling them to participate in multiple stress-related processes [ 80 – 82 ]. The AAA + ATPase domain is involved in the disaggregation of misfolded proteins by using ATP hydrolysis, which provides energy to disassemble protein aggregates, making it crucial for severe stress recovery. The Clp domain, often found alongside the AAA + ATPase domain, is involved in protein degradation, ensuring cellular homeostasis by removing non-functional proteins that cannot be refolded. Each HSP family retains its core functional domain, such as the α-crystallin, TCP-1, HSP70, HSP90, or AAA + ATPase and Clp domains, emphasizing the primary stress-mitigation role of each family [ 83 ]. However, variations in domain architecture within families reflected the evolutionary adaptations that allow each family to address a range of environmental stressors. In comparison to other plants, Vigna radiata HSP domain architecture displayed similar functional diversification across the HSP families, which is a common evolutionary strategy observed in plants. For instance, in many plant species, the HSP20 and HSP70 families show structural diversity that enables the protection of cellular proteins during short-term and prolonged stress, respectively. The presence of multi-domain structures in the HSP100 family, such as AAA + ATPase and Clp domains, is also typical in other plants, where these domains contribute to recovery from severe stress through disaggregation and degradation of misfolded proteins. This comparative perspective suggests that while each plant species may have unique adaptations, the fundamental HSP domain structures and functions are highly conserved across species, reflecting the critical role of these proteins in stress tolerance and survival. The expression of various VrHSP genes was analyzed in the susceptible genotype, Shikha, and the resistant genotype, TCR-20, under cold and heat stress conditions, without or with treatments of different signaling molecules such as IAA, SA, and GABA. TCR-20 exhibited a stronger and more consistent stress response compared to Shikha, particularly under heat stress. In particular, the VrHSP-20 family revealed significant genotype-specific responses, with TCR-20 showing a more robust thermo-tolerance mechanism than Shikha. In Shikha, VrHSP-20.6 was found downregulated under heat stress and upregulated under cold stress, highlighting its role in temperature adaptation. Conversely, in TCR-20, VrHSP-20.6 was strongly upregulated, especially in response to salicylic acid (SA) and γ-aminobutyric acid (GABA), indicating its involvement in heat tolerance. Similarly, VrHSP-20.11 and VrHSP-20.13 were strongly induced in TCR-20, reinforcing their role in thermo-tolerance. VrHSP-20.19 did not respond in cv. Shikha, but it was induced under cold stress in TCR-20, indicating its significance in cold adaptation. These findings are consistent with the earlier reports on the role of HSPs in stress adaptation in other crops such as Glycine max, where GmHSP17.9 and GmHSP22.0 were upregulated under heat stress, contributing to stress tolerance [ 84 , 85 ]. Similarly, Cicer arietinum (chickpea) showed differential expression of CaHSP17.6 and CaHSP20.7 under heat stress, with ABA playing a significant regulatory role [ 86 , 87 ]. Moreover, VrHSP-22.2 showed a significant upregulation in TCR-20 under heat stress, particularly upon GABA treatment, further supporting the role of HSPs in heat stress mitigation. This mirrors the findings in Zea mays (maize), where ZmHSP17.2 was reported to play a key role in thermo-tolerance, with auxin (IAA) mediating its regulation [ 88 ]. However, while cereals like maize rely more heavily on auxin-mediated responses, legumes such as Vigna radiata and Medicago truncatula exhibit stronger GABA- and SA-mediated regulation of HSP ex-pression [ 89 ]. TCR-20 exhibited a well-coordinated stress-regulatory mechanism, with significantly higher levels of IAA, SA, and GABA under heat stress, indicating its superior thermo-tolerance. The sharp increase in IAA under heat stress in TCR-20 was particularly noteworthy, as auxin is involved in thermo-tolerance. Observations were also noticed in heat-resistant soybean and maize [ 90 ]. This finding aligns with those in cereals where GABA accumulation was observed to enhance heat stress resilience [ 85 , 88 ]. The interaction network analysis of heat shock proteins (HSPs) and chaperonins (Cpn60) revealed strong functional associations among the stress-responsive proteins, particularly the resistant genotype, TCR-20. A significant interaction was observed between the HSP-70 family and Cpn60, with high interaction scores ranging from 0.682 to 0.847, which indicated a coordinated response where HSP-70 proteins collaborated with cha-peronins to facilitate protein folding and stabilization under stress conditions. Corres-pondingly, expression data confirmed that VrHSP-70.2 and VrHSP-70.12 exhibited sub-stantial upregulation in TCR-20 under heat stress, particularly with GABA (74.7-fold) and SA (32.4-fold) treatments, reinforcing their critical role in thermo-tolerance. Similarly, HSP-90.6 demonstrated strong interactions with Cpn60 proteins, with interaction scores exceeding 0.6, supporting its role in protein stabilization during heat stress. Expression analysis also aligned with these interactions, showing a marked increase in VrHSP-90.6 expression in TCR-20, particularly under IAA (15.9-fold) and SA (19.5-fold) treatments. This suggests its essential role in maintaining protein homeostasis and preventing heat-induced protein misfolding. Additionally, HSP-100 proteins exhibited strong interactions with HSP-70 and ATP-dependent Clp protease (interaction score: 0.405), highlighting their involvement in protein degradation and refolding during stress recovery. Correspondingly, VrHSP-100.2 was strongly upregulated in TCR-20 under heat stress (31.3-fold with GABA, 19.9-fold with SA), confirming its role in removing misfolded proteins and enhancing cellular stress tolerance. Furthermore, small HSPs (VrHSP-20.11, VrHSP-20.13, and VrHSP-20.6) exhibited interactions with VrHSP-70.8 (scores: 0.402–0.585), suggesting their role in early stress response and preventing protein aggregation. Their higher expression levels in TCR-20 compared to Shikha reinforced their contribution to thermo-tolerance and early stress adaptation mechanisms. The interaction data aligned well with the expression analysis, revealing that TCR-20 exhibited stronger co-expression and interaction among key HSPs, which contributed to its enhanced stress adaptation to temperature stress. Chaperonins (Cpn60) emerge as central regulators, particularly in coordination with HSP-70 and HSP-90 proteins, supporting their essential role in stress protection. The combined expression and interaction analysis highlighted the superior ability of TCR-20 to withstand temperature stress as compared to Shikha, driven by higher gene upregulation and stronger protein-protein interactions. Materials and Methods Plant material, stress treatments, and experimentations The experiments were performed with Shikha, a high-yielding and popular but ther-mo-sensitive cultivar of mungbean, and a thermo-tolerant wild accession, TCR-20 (IC 251372) of V. glabrescens [ 21 , 22 ]. Initially, the seeds of both these genotypes were sown in the seedling bags in three sets. These sets were treated as control, cold-stressed, and heat-stressed, respectively. Each set of experiments comprised of four pots as control and treated with indole acetic acid (IAA), salicylic acid (SA), and gama aminobuyric acid GABA. Four different foliar primings were done before 24h of stress as follows. Control was primed with double-distilled water, whereas the rest three treatments were sprayed with phyto-hormones viz., IAA (50 µMol), SA (50 µMol), and GABA (50 µMol), respec-tively. The experiments were laid out in a randomized block design (RBD) with four replications in the Plant Tissue Culture Laboratory, Department of Basic and Social Sciences, Banda University of Agriculture and Technology, Banda, India. To ensure con-trolled environmental conditions, the plants were kept in the plant growth chamber at 300°C under a 14h light and 10h dark cycle. The temperature was maintained at 100°C for 3 days for cold stress treatment and 450°C for 3 days for heat stress treatment. Estimation of chlorophyll content 100 mg of leaf sample was homogenized in 80% acetone and centrifuged at 8000 rpm for 5 min at room temperature for chlorophyll estimation. Absorbance was measured in a spectrophotometer at 663 nm, 645 nm, and 470 nm from 2 mL of supernatant. Chloro-phyll content was calculated as per Arnon [ 91 ] and expressed as mg/g FW. Visualization of H2O2 and O2 The leaf samples from both the control and the stress environments were subjected to histochemical staining. The H2O2 and O2 were localized histochemically by the method suggested by Chen et al. [ 92 ]. After staining and bleaching, the photographs of the sam-ples were taken using a Sony DSLR camera. Identification of small and large HSP protein sequences The Hidden Markov models (HMMs) profiles of Hsp20 (PF00011), Hsp40 (PF00226), Hsp70 (PF00012), Hsp90 (PF00183), HSP100 (PF02861 and PF10431) were downloaded from the protein database (PFAM) and legume information system. This analysis was used for the search to recognize candidate proteins with an E-value of 1e-5 by HMMER v3.2.1. Further, each of the selected candidates was examined for the conserved structure domain using NCBI-CDD [ 93 ]. ExPASy was used to calculate the molecular weight (MW) and isoelectric points (pI) [ 94 ]. The sub-cellular localization and signal peptide were predicted by using online software Cello Life, Wolfpsort ( http://cello.life.nctu.edu.tw/ , https://wolfpsort.hgc.jp/ ) and SignalP ( https://services.healthtech.dtu.dk/service.php?SignalP-5.0 ), respectively [ 95 – 97 ]. Phylogenetic tree, domain analyses, and chromosomal distribution The identified VrHSP protein sequences were aligned using Clustal Omega with default parameters. The phylogeny was prepared using MEGA 11.0 with the Neighbor-joining method with default parameters [ 98 ]. The bootstrap replications were kept as n = 1000. The intron and exon structure was visualized by using GSDS software V. 2.0. The protein domain and active motif function were analyzed in the Pfam database (pfan.xfam.org). The web-based motif identification servers MEME-Suit (Multiple Em for Motif Elicitation, meme-suite.org/meme/) were used to detect potential motifs with the following parameters as motif width < 50, motifs < 20, and e-value < e − 5 [ 99 ]. The physical position of all the identified HSP genes was obtained from the V. radiata genome database and visu-alized by TBtools [ 100 ] ( http://services.cbu.uib.no/tools/kaks ). Protein Protein interaction network analyses The interacting networks of HSP proteins were integrated into the STRING software ac-cessed on Feb 07, 2025 [ 101 ] ( https://www.string-db.org/ ), followed by an export of the co-expression network data. RNA extraction, cDNA synthesis and gene expression profiling 100 mg of frozen leaf samples in the liquid nitrogen were homogenized using tissue lys-er-II (Qiagen, Germany), and RNA was extracted using plant RNA extraction kit (RNeasy Mini Kit, Qiagen) following the manufacturer’s instructions. Subsequently, RNA was subjected to DNase treatment to remove the DNA contaminants and 1µg of purified RNA was reverse-transcribed by using the RevertAid First Strand cDNA Synthesis Kit (Thermo Fisher Scientific). The cDNA was quantified on a micro volume spectrophotometer (QIAExpert, Qiagen) and normalized to 50 ng/ µL for qRT-PCR analysis. Fifteen candidate genes representing different HSPs were subjected to expression analysis (Table S3 ). The qPCR reactions comprised of 10 µL 2X SYBR green q-PCR master mix (Thermo Fisher Scientific), 1 µL of 10 pmol each forward and reverse primers (Eurofins, India), 6 µL nuclease-free water, and 2 µL of cDNA were used. The fast-cycling approach was adopted with 2 min. Initial denaturation at 96oC, 40 cycles of 20 sec. denaturation at 96oC, 45 sec. annealing and extension at 60oC. The Actin gene was used as an internal control. qPCR analysis was carried out using a RealTime PCR machine, Quant Studio 5 (Thermo Fisher Scientific). Three biological replicates were taken, and two technical replicates were used for the expression analysis. The relative expression levels of the genes were calculated via the delta-delta CT method [ 102 ]. Conclusions The findings of the present study emphasized the species-specific differences in HSP regulation, hormonal signaling, and metabolic adaptation, with TCR-20 demonstrating superior hormonal modulation and stress resilience. The results further demonstrated the molecular mechanism of heat tolerance in Vigna species and the intricate phytohormone and metabolic networks, with auxin, salicylic acid (SA), and gamma-aminobutyric acid (GABA) playing pivotal roles in thermo-tolerance. The physico-chemical and molecular responses of TCR-20 uncovered the stress adaptation mechanisms, which can be leveraged to develop stress-resilient varieties through targeted breeding and biotechno-logical interventions. Declarations Data Availability Statement: All the data generated in this experiment were presented in the manuscript and its supplement files. Acknowledgments: The authors are thanks to Project Incharge, Center of Excellence in Dryland Agriculture for providing partial research support. Funding: The present work was financially supported by the Ministry of Agriculture, Agriculture Education and Research, Govt. of Uttar Pradesh, under the project “Center of Excellence in Dryland Agriculture (CEDA/2018)”. Author Contributions: C.M.S., B.P., S.P., Conceptualization; P.S., methodology, investigation, validation; A.K.M., data curation, C.M.S., S.P., formal analysis, supervision; P.S., S.P., writing—original draft preparation; C.M.S., funding acquisition; A.P., review and editing. All authors have read and agreed to the published version of the manuscript. Clinical trial number: Not applicable Ethics approval and consent to participate: Not applicable Consent for publication: Not applicable Conflicts of Interest: The authors declare no conflict of interest. References Bangar P, Chaudhury A, Tiwari B, Kumar S, Kumari R, Bhat KV. Morphophysiological and biochemical response of mungbean [Vigna radiata (L.) Wilczek] varieties at different developmental stages under drought stress. Turkish J Biol. 2019;43:58–69. Basu PS, Pratap A, Gupta S, Sharma K, Tomar R, Singh NP. Physiological Traits for Shortening Crop Duration and Improving Productivity of Greengram (Vigna radiata L. 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Supplementary Files TableS1.docx TableS2.docx TableS3.docx Cite Share Download PDF Status: Published Journal Publication published 27 Nov, 2025 Read the published version in BMC Plant Biology → Version 1 posted Editorial decision: Revision requested 18 Aug, 2025 Reviews received at journal 17 Aug, 2025 Reviewers agreed at journal 04 Aug, 2025 Reviews received at journal 04 Aug, 2025 Reviewers agreed at journal 03 Aug, 2025 Reviewers agreed at journal 03 Aug, 2025 Reviewers invited by journal 02 Aug, 2025 Editor invited by journal 01 Aug, 2025 Editor assigned by journal 31 Jul, 2025 Submission checks completed at journal 31 Jul, 2025 First submitted to journal 23 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7194231","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":495725306,"identity":"61c73259-9379-43da-9032-eec9e4118c47","order_by":0,"name":"Poornima Singh","email":"","orcid":"","institution":"Mahatma Gandhi Central University","correspondingAuthor":false,"prefix":"","firstName":"Poornima","middleName":"","lastName":"Singh","suffix":""},{"id":495725307,"identity":"9a3b02e0-7de9-4eaf-a78c-2bb8c6eeaf5d","order_by":1,"name":"Brijesh Pandey","email":"","orcid":"","institution":"Mahatma Gandhi Central University","correspondingAuthor":false,"prefix":"","firstName":"Brijesh","middleName":"","lastName":"Pandey","suffix":""},{"id":495725308,"identity":"73cf4188-2fd9-4486-b40f-d2e5b6f75a6c","order_by":2,"name":"Shalini Purwar","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFUlEQVRIiWNgGAWjYDACCQbGAwlAEgwYG4AEO4gwsMCnhQFVCw/PAZAWCfxa4BywFokEqDgOID+7+cGBhzss8gxunzH8XLnjsLy95POrG34USDDwt3cnYNNicOeYwYHEMxLFBudyjCXPnjls2COdU3azB+gwiTNnN2DVIpEA1NImkbjhDO8Gyca2w4xALWk3eIBaDCRysWqRn5H+AaZl80+gFvseyTNpN//g0cJwIwduyzaQLYk9EuzHbuOzxeBGTgFIS7HkGf5vlo1n0pN7zuSw3ZYxkODB5RegwzY+/NlWl8d3hi35ZuMOa9v29uPPbr75YyPH396L3WFQkIDE5jEAk/iUo2thf0BI9SgYBaNgFIwsAAAULWwxbm2TGQAAAABJRU5ErkJggg==","orcid":"","institution":"Banda University of Agriculture and Technology","correspondingAuthor":true,"prefix":"","firstName":"Shalini","middleName":"","lastName":"Purwar","suffix":""},{"id":495725309,"identity":"592b6f6f-0ae7-462f-9f36-48889271173a","order_by":3,"name":"Chandra Mohan Singh","email":"","orcid":"","institution":"Banda University of Agriculture and Technology","correspondingAuthor":false,"prefix":"","firstName":"Chandra","middleName":"Mohan","lastName":"Singh","suffix":""},{"id":495725310,"identity":"25c967a7-34dc-4695-af2d-21fc017076f5","order_by":4,"name":"Aditya Pratap","email":"","orcid":"","institution":"ICAR-Indian Institute of Pulses Research","correspondingAuthor":false,"prefix":"","firstName":"Aditya","middleName":"","lastName":"Pratap","suffix":""},{"id":495725311,"identity":"a42d94a1-72b9-4374-a361-761ce1f46484","order_by":5,"name":"Awdhesh Kumar Mishra","email":"","orcid":"","institution":"Yeungnam University","correspondingAuthor":false,"prefix":"","firstName":"Awdhesh","middleName":"Kumar","lastName":"Mishra","suffix":""}],"badges":[],"createdAt":"2025-07-23 08:53:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7194231/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7194231/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12870-025-07627-y","type":"published","date":"2025-11-27T15:57:43+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":88608372,"identity":"4c53cbda-0ef0-4878-87a4-96c49f175a79","added_by":"auto","created_at":"2025-08-08 09:10:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":966109,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of foliar priming or without priming on the morphology of Shikha and TCR-20 under ideal (control), cold, and heat stress\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-7194231/v1/37326c28b8ac9556a7f6ed01.png"},{"id":88608692,"identity":"e349447b-a420-48a0-9b9d-8a564b3e42a3","added_by":"auto","created_at":"2025-08-08 09:18:46","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":351049,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of unprimed or foliar priming on chlorophyll content of Shikha and TCR-20 under ideal (control), cold, and heat stress\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-7194231/v1/fc9a0f20927b4049e4374324.png"},{"id":88608395,"identity":"11264a94-b807-4c6b-bbea-e755c187c5db","added_by":"auto","created_at":"2025-08-08 09:10:48","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1118790,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of unprimed or folier priming on reactive oxygen species generation of Shikha and TCR-20 under ideal (control), cold, and heat stress; (A) histochemical staining, (B) Spectrophotometric quantification of H2O2\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-7194231/v1/b2fb8f1461b68e0beb9e2648.png"},{"id":88608387,"identity":"11997519-68b2-4996-89c3-2d7f225bc09b","added_by":"auto","created_at":"2025-08-08 09:10:47","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":617022,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of unprimed or folier priming on oxygen ion generation of Shikha and TCR-20 under ideal (control), cold, and heat stress; (A) histochemical staining, (B) Spectrophotometric quantification of O2\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-7194231/v1/d788395630d2b086f6a6e917.png"},{"id":88608397,"identity":"6c7e420d-491b-4373-a089-b956bdb94ac5","added_by":"auto","created_at":"2025-08-08 09:10:48","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":76823,"visible":true,"origin":"","legend":"\u003cp\u003eChromosomal distribution of the VrHSP (VrHSP-20, VrHSP-60, VrHSP-70, VrHSP-90, VrHSP-100) genes on the 11 chromosomes.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-7194231/v1/a03b5d2e56aba547e5a4f176.png"},{"id":88608400,"identity":"875c2366-7e1f-4b34-b053-83f504fe2c77","added_by":"auto","created_at":"2025-08-08 09:10:48","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":44503,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogenetic tree of the VrHSP genes. VrHSP-20 (red circle), VrHSP-60 (green circle), VrHSP-70 (blue circle), VrHSP-90 (dark blue circle), VrHSP-100 (brown circle). The phylogenetic tree was generated via neighbor-joining with 1,000 bootstraps.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-7194231/v1/67bed6458a6da4ac9ac1a1e0.png"},{"id":88608696,"identity":"758ddf67-e1fc-4b45-84b4-10c718d775a1","added_by":"auto","created_at":"2025-08-08 09:18:47","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":467867,"visible":true,"origin":"","legend":"\u003cp\u003eThe architecture of the conserved protein domain of VrHSPs. The different domains were presented with different colors.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-7194231/v1/2e1ed447b8e3ec899c3e5098.png"},{"id":88608380,"identity":"afa50275-25c1-4f64-9f11-b65da49491ac","added_by":"auto","created_at":"2025-08-08 09:10:47","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":85845,"visible":true,"origin":"","legend":"\u003cp\u003eGene structure analysis of VrHSP candidates. The yellow boxes represent CDS regions, the blue boxes represent UTR regions, and the black lines represent untranslated introns.\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-7194231/v1/ced4dffef774ee7ed0ce881e.png"},{"id":88608379,"identity":"8bf1c735-3dcb-4c0c-b0e5-8080a2f5c8c2","added_by":"auto","created_at":"2025-08-08 09:10:47","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":463937,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of conserved protein motifs of VrHSPs. A total of 20 motifs were predicted. Different motifs are represented by boxes of different colors.\u003c/p\u003e","description":"","filename":"image9.png","url":"https://assets-eu.researchsquare.com/files/rs-7194231/v1/f3f62f98b2551674c917e57a.png"},{"id":88608700,"identity":"5c383e25-2c83-4c29-905d-4454d79988c9","added_by":"auto","created_at":"2025-08-08 09:18:48","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":174229,"visible":true,"origin":"","legend":"\u003cp\u003eNetwork prediction of selected candidates of VrHSPs and its interacting pro-teins via the STRING database\u003c/p\u003e","description":"","filename":"image10.png","url":"https://assets-eu.researchsquare.com/files/rs-7194231/v1/02b5606476339db87424be8f.png"},{"id":88609686,"identity":"508b260d-d218-43b3-8b68-e273155f22af","added_by":"auto","created_at":"2025-08-08 09:26:46","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":245417,"visible":true,"origin":"","legend":"\u003cp\u003eExpression analysis of different VrHSP genes ideal and under different temperature stresses without priming or priming with different phyto-hormones\u003c/p\u003e","description":"","filename":"image11.png","url":"https://assets-eu.researchsquare.com/files/rs-7194231/v1/1bcf65520fbf9ef29af252b6.png"},{"id":88608694,"identity":"9b4b877d-759c-4edb-af12-a52f527e0fcc","added_by":"auto","created_at":"2025-08-08 09:18:47","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":250921,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal component plot of gene expression profile of selected HSP candidates\u003c/p\u003e","description":"","filename":"image12.png","url":"https://assets-eu.researchsquare.com/files/rs-7194231/v1/85c1a7f6aa561cdf5c0e0290.png"},{"id":97178731,"identity":"2176b8d9-cf84-4deb-8704-24adb4c09a32","added_by":"auto","created_at":"2025-12-01 16:13:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5498157,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7194231/v1/d2a3a2ba-b076-49fa-9386-b74f0038e6cf.pdf"},{"id":88609687,"identity":"7af4f7a8-73ad-4b0c-a5d1-a343a2c0507c","added_by":"auto","created_at":"2025-08-08 09:26:48","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":37312,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7194231/v1/1ba9625d7a0bc2792ba12ea1.docx"},{"id":88608398,"identity":"92b60903-78f7-4481-bde0-3e78a7477299","added_by":"auto","created_at":"2025-08-08 09:10:48","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":29984,"visible":true,"origin":"","legend":"","description":"","filename":"TableS2.docx","url":"https://assets-eu.researchsquare.com/files/rs-7194231/v1/709aaa186a53d64f99634603.docx"},{"id":88608691,"identity":"2fce71f4-ec2d-4e30-ae6a-5cb9a24d894f","added_by":"auto","created_at":"2025-08-08 09:18:46","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":16834,"visible":true,"origin":"","legend":"","description":"","filename":"TableS3.docx","url":"https://assets-eu.researchsquare.com/files/rs-7194231/v1/ef070d55fc108b7f4d4446e7.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eExogenous application of gamma-amino butyric acid alleviates temperature stress in mungbean (\u003cem\u003eVigna radiata\u003c/em\u003e) and its wild non-progenitor (\u003cem\u003eVigna glabrescens\u003c/em\u003e) by regulating heat shock protein genes\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe genus Vigna is a diverse group of short-duration legumes. Among them, mungbean (Vigna radiata L. Wilckzek) is one of the most important warm season and widely cultivable food legume grown across many tropical and sub-tropical regions globally, and at many places throughout the year. Changes in temperature act as a major threat to crop adaptation and productivity under emerging climate change [\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Mungbean can ideally grow between 30\u0026ndash;40\u0026deg;C, lower temperatures leading to stunted growth, leaf defoliation and prolonged maturity, whereas high temperatures cause pollen abortion, flower drop, leaf injury, low seed filling and, ultimately, drastic yield loss. Therefore, both lower and higher temperatures lead to yield penalties [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Therefore, there is an urgent need to improve the temperature tolerance of mungbean to realize higher yield. However, it requires a comprehensive approach from identification to exploitation of potential donors for temperature tolerance in the breeding programmes [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Till date, limited donors have been reported for heat tolerance in different Vigna species [\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Bhardwaj et al. [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] studied the response of mungbean genotypes to extreme temperatures, both low and high and suggested that heat is a complex trait and can be better understood by studying gene network analysis. Bhardwaj et al. [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] identified three mungbean genotypes i.e., IC76475, IC418452 and IC489062 as heat tolerant through morpho-physiological characterization and expression of key candidates, i.e., CP47, SUT, MTR_1g062190, MTR_7g092380, LOC101499292, VrLEA-55 (DHN). Likewise, a limited study was done for cold tolerance [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], which indicated that limited donors of mungbean have been reported which possess cold and heat tolerance.\u003c/p\u003e\u003cp\u003eAs we know that crop wild relatives (CWRs) are a reservoir of many useful genes, especially for stress tolerance [\u003cspan additionalcitationids=\"CR15 CR16 CR17 CR18 CR19\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], and exploring CWRs for heat and/ or cold tolerance may be a good option. Pratap et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] identified the Vigna glabrescens accession TCR-20 as a potential donor for photo-thermo-insensitivity. They reported that this accession is able to flower between 4 and 44\u0026deg;C and produce viable pollen grains at both extremes of temperature. Further, Singh et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] reported the expression of candidate genes and delayed chlorophyll degradation in the leaves of V. glabrescens, as the key leaf function leads to adaptation under high temperature. Stress tolerance may be improved by the induction/ elicitation of various genes. An exogenous application of phytohormones or other signaling compounds is now the trend to alleviate the harmful effects of various biotic and abiotic stresses. Angon et al., [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] reviewed work on phytohormones and re-ported many phytohormones that improve heat tolerance. Shao et al., [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] suggested a versatile role of polyamines in mitigating the effects of abiotic stresses. With the availability of the whole-genome sequence of mungbean as a reference [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], molecular breeding is now a sounder approach to tackle these stresses. Many reports have explored gene families and transcription factors for the identification of suitable candidates involved in various growth and developmental activities, hormonal regulation and stress responses in mungbean [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Singh et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] in three Vigna species and studied their expression under heat stress. Recently, Singh et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] performed a comprehensive characterization of candidate genes of SBT gene family and their comparative gene expression profile under heat and cold stress in the \u003cem\u003eVigna glabrescense\u003c/em\u003e indicated its potential of flowering under different temperature regimes.\u003c/p\u003e\u003cp\u003eHeat shock proteins (HSPs) are known as a key candidate which plays a critical role during abiotic stress response and their cross-talk. Li et al., [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] identified 24 Hsfs as candidates in the mung bean genome, and expression profiling was performed under heat and cold stresses. It was noticed that the HSP genes are significantly regulated under the temperature stress, but the comprehensive analysis and its cross-species expression in V. glabrescens is still unexplored due to the unavailability of its whole genome sequence. Therefore, the present study was conducted to explore the small and large HSP gene families in mungbean, V. radiata (a relative of V. glabrescens) and its cross-specific gene expression under heat and cold stresses. This study provides new insights into the me-chanism of thermo-tolerance in Vigna glabrescens.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTemperature-induced morpho-physiological responses\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe morpho-physiological responses of Shikha and TCR-20 were recorded to assess plant growth and temperature stress tolerance under control, cold, and heat stressed conditions, eithther untreated (H₂O as control) or treated with indole-3-acetic acid (IAA), salicylic acid (SA), and gamma-aminobutyric acid (GABA) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). It was observed that the performance of both genotypes was better under temperature stress conditions upon foliar priming with IAA, SA, or GABA. Cv. Shikha exhibited severe damage and wilting in most treatments, though GABA seemed to mitigate the effects slightly than the untreated one or treatment with SA. In TCR-20, the control treatment appeared healthy, but cold stress induced noticeable yellowing and stress symptoms, with IAA and GABA treatments demonstrating higher resilience to temperature. Cold stress led to lower cell damage as compared to heat stress.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe chlorophyll-a (Chl-a), chlorophyll-b (Chl-b), and total chlorophyll (Chl) content in Shikha and TCR-20 were measured under control, cold, and heat stress conditions with treatments of H₂O, IAA, SA, and GABA, and also without treatment (CK) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Chl-a was found to be significantly declined under temperature stress in shikha, whereas GABA application was found to be the most effective treatment with 14.25 \u0026micro;g/g in control, 10.25 \u0026micro;g/g under cold, and 8.27 \u0026micro;g/g under heat stress conditions. In contrast, TCR-20 exhibited 12.22 \u0026micro;g/g in control, 11.25 \u0026micro;g/g under cold and 11.1 \u0026micro;g/g under heat stress upon GABA treatment, showing a better stability of chl even under temperature stress conditions. GABA treatment in cv. Shikha also improved the Chl-b at 6.23 \u0026micro;g/g in control, 5.23 \u0026micro;g/g under cold, and 5.27 \u0026micro;g/g under heat. GABA was found to be the most effective treatment for both genotypes under cold and heat stresses. In Shikha, GABA-treated plants maintained the highest level of chlorophyll with 20.48 \u0026micro;g/g in control, 15.48 \u0026micro;g/g under cold stress, and 13.54 \u0026micro;g/g under heat stress. TCR-20 exhibited a similar pattern, with GABA-treated plants retaining 17.37 \u0026micro;g/g in control, 16.35 \u0026micro;g/g under cold stress, and 12.27 \u0026micro;g/g under heat stress. TCR-20 demonstrated better resilience under both cold and heat stresses.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eHistochemical staining was done using NBT and DAB to visualize the accumulation of superoxide anions (O2\u0026ndash;) and hydrogen peroxide (H2O2) under non-stress or stress (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) conditions. It confirmed the increased oxidative stress under both, cold and heat stresses. The maximum cell damage was recorded in the unprimed conditions upon cold and heat stress treatments. Foliar application of phytohormones was able to alleviate the temperature stress significantly. GABA-treated genotypes showed minimum cell death under cold and heat stress in both genotypes, indicating lower oxidative stress levels. Overall, it was observed that GABA effectively mitigated the oxidative damage in Shikha and TCR-20.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eA further quantitative estimation of H₂O₂ and O₂ highlighted the significant differences between these genotypes under control and stress conditions, reflecting their varying oxidative stress responses and regulation. Shikha showed higher H₂O₂ levels with a sharp increase of up to 210.5 \u0026micro;mol/g under heat stress conditions. Likewise, TCR-20 exhibited their better regulation, with levels peaking at 150.89 \u0026micro;mol/g. On the contrary, treatments with IAA, SA, and GABA reduced H₂O₂ in both genotypes, whereas SA and GABA were found to be the most effective treatments, which maintained the level of H2O2 at 112.25 \u0026micro;mol/g and 115.25 \u0026micro;mol/g, respectively, in TCR-20. Likewise, a similar trend of the O₂ levels rising significantly was observed under control (53.27 to 150.38 \u0026micro;mol/g at 6-DAWL), indicating oxidative stress, while treatments, especially GABA (110.28 \u0026micro;mol/g), reduced the O2levels as TCR-20 showed lower O₂ levels under control (50.67 to 80.27 \u0026micro;mol/g), with GABA treatment maintaining the lowest level (51.89 \u0026micro;mol/g).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eMining, Physicochemical Properties and Functional Insights of HSPs\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA total of 96 heat shock proteins (HSPs) and chaperonin proteins (Cpn60) were identified in V. radiata. These include HSP20 (VrHSP-20.1 to VrHSP-20.28), HSP60 (VrCpn60_TCP1.1 to VrCpn60_TCP1.23), HSP70 (VrHSP-70.1 to VrHSP-70.17), HSP90 (VrHSP-90.1 to VrHSP-90.7) and HSP100 proteins (VrHSP-100.1 to VrHSP-100.21), presented in Table-S1A \u0026amp; S1B. The analysis of key properties such as peptide sequence length, molecular weight, isoelectric point (pI), instability index, aliphatic index, and GRAVY scores provides insights into protein stability, function, and adaptation under stress conditions. The protein size ranged from 6.97 kDa (VrHSP-70.15, 62 amino acids) to 575.51 kDa (VrHSP-100.20, 5057 amino acids), reflecting its diversity from small stress-responsive proteins to large chaperonins. The pI values ranged from acidic (pI\u0026thinsp;=\u0026thinsp;4.46, VrHSP-70.16) to highly basic (pI\u0026thinsp;=\u0026thinsp;10.22, VrHSP-70.5). Lower pI values suggested higher acidic amino acid content, influencing solubility and function under different pH conditions, while higher pI values indicated a greater proportion of basic residues like lysine and arginine, potentially aiding nucleic acid interactions. Proteins with an instability index\u0026thinsp;\u0026gt;\u0026thinsp;40 are considered unstable, likely functioning as transient stress-responsive proteins. The VrHSP-20.3 (36.3) and VrCpn60_TCP1.1 (30.92) were found to be the most stable, whereas VrHSP-20.1 (59.13) and VrHSP-100.5 (53.52) were found to be the most unstable. Likewise, VrCpn60_TCP1.3 (119.96) and VrHSP-70.16 (112.45) were highly stable under heat stress, while VrHSP-20 (55.37) and VrHSP-100.4 (75.47) might have reduced thermal stability. Most of the proteins, such as VrHSP-20.1 (-0.710) and VrCpn60_TCP1.12 (-0.061), had negative GRAVY scores, indicating hydrophilicity and cytoplasmic solubility. However, VrCpn60_TCP1.3 (+\u0026thinsp;0.227) and VrCpn60_TCP1.9 (+\u0026thinsp;0.197) were noticed to be more hydrophobic, playing roles in the membrane interactions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eDistribution of HSPs\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe HSP genes were distributed across various chromosomes (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). For instance, HSP20 genes were found across all chromosomes except LG04 and LG01. These genes have shorter genomic lengths (e.g., VrHSP-20.19, 6546 bp, 10 exons) and simpler struc-tures. Cpn60 genes were distributed across multiple scaffolds and chromosomes, with larger genomic lengths (e.g., VrCpn60_TCP1.5, 6570 bp) and longer CDS lengths (e.g., VrCpn60_TCP1.5, 6450 bp). Likewise, HSP70 genes were dispersed across different scaffolds and chromosomes (e.g., Vr06, Vr08), with genomic lengths up to 3186 bp (VrHSP-70.2). HSP90 genes were also broadly distributed (e.g., LG01, LG06, LG11). HSP100 Involved large genes (e.g., VrHSP-100.3, 8647 bp), indicating their complex structures for protein disaggregation and degradation under extreme stress conditions. This analysis highlighted the structural diversity of HSPs and Cpn60 in V. radiata, em-phasizing their importance in plant stress tolerance, protein stability, and cellular recov-ery mechanisms. Understanding these properties can aid in developing stress-resilient crops through targeted breeding and biotechnological interventions.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003ePhylogeny, Domain, Motif, exon-intron analyses\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe phylogenetic relationship analysis of HSP candidates demonstrated a complex pic-ture of evolutionary adaptation, with different families (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The phylogenetic tree appeared to be linked to a specific family of proteins with domain organization alongside the tree (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). The phylogeny of 28 HSP-20 candidates was grouped into five sub-families which shared similar domain architectures and evolutionary relationships, for example, ACD, for alpha-crystallin domain. The length of the domains varied across the proteins, which suggested structural diversity within the HSP-20 family. The clustering of the HSP-60 protein into seven subgroups with TCP domain was found highly conserved across the family, though the additional domains indicated potential differences in regulatory functions or protein interactions.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe HSP-70 family was divided into five subclusters (A to E), with a GRAS domain, which are important in plant signaling pathways, including those related to gibberellin responses. The domain architecture included highly conserved regions with some varia-bility in other regions, which may correspond to functional differences. Likewise, the HSP 90 family was divided into two subclusters (A-B), with the GHD domain, which is related to gibberellin pathway-related proteins. The variability in the domain structure of these HSP-90 proteins was also noticed. Likewise, HSP-100 candidates were grouped into three subclusters (A-C), with a large heat shock protein family involved in protein dis-aggregation and refolding. The domain structures of these proteins demonstrated that several candidates had well-conserved functional domains (e.g., AAA\u0026thinsp;+\u0026thinsp;ATPase domain) essential for their role in heat stress recovery. The diversity in domain architecture across this family indicated a high degree of specialization and adaptation to different stress conditions. Each domain showed evolutionary relationships within a protein family. The closely related proteins were grouped together, while more distant branches represented proteins that have distinct functions. Across all protein families, specific domains were found to be conserved.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe chromosomal localization of Vigna HSP genes revealed their widespread distribution across all 11 chromosomes, with distinct clustering patterns. Chromosome 7 exhibited the highest HSP gene density, featuring two major clusters: 0.0\u0026ndash;14.6 Mb (VrHSP-20.19, VrHSP-70.6, VrHSP-70.7) and 33.8\u0026ndash;46.9 Mb (VrHSP-70.8, VrHSP-20.21, VrHSP-100.8), in-dicating a critical role in stress adaptation. In contrast, Chromosome 3 harbored the fewest HSP genes, with only a single cluster (12.3\u0026ndash;13.0 Mb, VrHSP-20.14, VrHSP-100.16), suggesting a limited role in stress-response gene distribution. Other chromosomes displayed varying densities, with co-localization of HSP and Cpn60 genes, indicating potential functional interactions. This uneven distribution suggests chromosome-specific roles in stress\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe exon-intron analysis across the different HSP genes underscores the diversity within HSP gene structures (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). This structural variation likely contributed in the func-tional adaptability of these genes, allowing the plant to respond to different types of en-vironmental stresses. Genes with more exons and introns may undergo alternative splicing, which can lead to different protein isoforms, further supporting the plant\u0026rsquo;s ability to manage stress at a molecular level. In HSP-20, VrHSP-20.11 had maximum ex-ons, indicating a complex structure that may enable alternative splicing and a more sig-nificant regulation of protein expression under stress conditions, while gene VrHSP-20.5 had the fewest exons, which likely allows for faster transcription and translation, asso-ciated with quick responses to the stress. In HSP 60, VrCpn60_TCP1.7 had the highest number of exons, while VrCpn60_TC had the lowest exons. In HSP 90, VrHSP-90.5 stands out with the most exons, while VrHSP-90.4 had the fewest exons. In HSP 100, VrHSP-100.12 has the maximum exons. Across all HSP, genes with more exons, such as VrCpn60_TCP1.7 and VrHSP-100.8, exhibited structural complexity that allows for reg-ulatory versatility and potential alternative splicing. This could enable the generation of multiple protein forms, catering to different stress conditions or stages of response. In contrast, genes with fewer exons, like VrHSP-20.5 and VrHSP-20.6, have streamlined structures that support rapid transcription and may be involved in immediate or primary stress responses. The diversity in exon-intron structure across these gene families un-derscores the adaptability of the HSP gene family, balancing rapid reaction capabilities with genes suited for long-term or nuanced regulatory roles. Motif analysis of the HSP-20 family identifies the specific locations of conserved motifs within the amino acid sequence (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). The consensus sequence logos for each HSP family illustrate the most conserved residues with letter sizes representing the degree of conservation. The identified motifs include RAMQGWHSQRLLGNG for HSP-20, DFM/LRQYTWDKHLETW for HSP-60, KRLIGRR/KFADPEVQ for HSP-70, and PPGYYGYE/TEGGQ/VLTE for HSP-100. These conserved sequences provide insights into the functional domains critical for heat shock protein activity across different HSP families.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eProtein-Protein interaction\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe protein-protein interaction (PPI) analysis in selected candidates representing different HSP subfamilies highlighted a well-coordinated chaperone system involving HSP-20, HSP-60, HSP-70, HSP-90, and HSP-100, which play crucial roles in stress tolerance, par-ticularly under heat and cold stress conditions (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e). HSP-20 proteins (HSP-20.11, HSP-20.13, and HSP-20.6) interacted with HSP-70.8, suggesting their role in preventing protein aggregation and maintaining cellular homeostasis under stress. HSP-60 (Cpn60/TCP1 family proteins) strongly interacted with HSP-70 and HSP-90, indicating their involvement in protein folding and stabilization in mitochondria and chloroplasts, essential for stress adaptation. HSP-70 proteins (HSP-70.2, HSP-70.8, and HSP-70.12), which form the core of the heat shock response, interacted with HSP-90.6 (endoplasmin homolog) and HSP-100.2 (ATP-dependent Clp protease), highlighting their role in protein refolding, degradation of misfolded proteins, and stress recovery mechanisms. The strong interaction between HSP-70.2 and HSP-90.6 (score 0.974) underscored their functional synergy in maintaining protein stability under extreme temperatures. HSP-100.2\u0026rsquo;s interaction with HSP-70 proteins suggested its function in removing irreversibly damaged proteins, which is particularly crucial during heat stress. The overall network suggested that HSP-20 prevents aggregation, HSP-60 and HSP-70 assist in folding and stabilization, HSP-90 regulates signaling pathways, and HSP-100 facilitates protein degradation, all working together to enhance the plant\u0026rsquo;s thermo-tolerance and cold stress resilience (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eExpression of VrHSP Genes under Heat, Cold stress with treated with Salicylic Acid (SA), Auxin (IAA), and GABA Treatments\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe expression of various VrHSP family genes was analyzed in the susceptible genotype Shikha and the resistant genotype TCR-20 under cold and heat stress conditions, with or without hormonal priming treatments with indole-3-acetic acid (IAA), salicylic acid (SA), and gamma-aminobutyric acid (GABA) (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e). The comparative expression levels indicated significant differences between these two genotypes, demonstrating a robust and consistent response to both cold and heat stresses. VrHSP-20.2 and VrHSP-20.6 showed significantly higher expression levels under both cold and heat stresses in TCR-20, particularly with GABA and IAA treatments. Likewise, in Shikha, VrHSP-20.2 showed moderate induction under heat stress, while VrHSP-20.6 was highly up-regulated under cold stress and significantly down-regulated under heat stress. In comparison, the change in TCR-20 was higher under both stress conditions, especially with GABA and IAA treatments. VrHSP-20.11 showed strong heat-induced expression in both genotypes, with a higher increase in TCR-20, particularly under GABA (45.5-fold) and SA (26.7-fold) treatments. VrHSP-20.13 was highly induced by heat stress, with a significantly higher expression in TCR-20, especially with GABA and IAA treatments. Shikha exhibited moderate expression increases under heat stress. The expression of VrHSP-20.19 was completely suppressed in Shikha under both heat and cold stress conditions, whereas in TCR-20, it was upregulated under cold stress upon IAA and SA treatments. Under the heat stress, GABA highly induced the VrHSP-20.19 expression in TCR-20 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea and Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb). VrHSP-20.24 showed strong up-regulation to both cold and heat stresses in TCR-20, with the highest expression observed with GABA (64.5-fold), followed by IAA (47.8-fold) under heat stress. In Shikha, it was moderately induced under cold stress, but significantly suppressed under heat stress, with lower fold changes as compared to TCR-20. The VrHSP-60.8 exhibited higher basal expression in Shikha, with significant upregulation under cold stress, particularly with IAA (14.3-fold) and SA (19.5-fold). In TCR-20, basal expression was lower, but cold stress induced the response with higher expression upon treatment with GABA (8.6-fold) and SA (6.1-fold). Heat stress induced significant increases in VrHSP-60.8 in TCR-20, with the highest increase observed upon treatment with GABA (60.0-fold), followed by SA (52.9-fold), and IAA (40.0-fold), whereas Shikha showed lower changes (3.7-fold for IAA and 2.6-fold for GABA).\u003c/p\u003e\u003cp\u003eVrHSP-60.11 exhibited stronger expression in TCR-20 under both cold and heat stresses, with the highest induction under cold stress, particularly with IAA (37.6-fold), SA (35.6-fold), and GABA (33.8-fold) treatment. In Shikha, IAA treatment (15.6-fold) showed the highest induction under cold stress, while heat stress induced moderate increases in the response of this gene upon treatment with SA (30.8-fold) and IAA (18.8-fold) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). VrHSP-60.20 exhibited substantial upregulation under cold stress in Shikha, especially with GABA (58.7-fold) and IAA (44.6), and moderate induction was noticed upon SA treatment (11.4-fold). Heat stress also induced a notable increase in the expression of VrHSP-60.20 upon IAA (51.2-fold), SA (52.2-fold), and GABA (48.4-fold) treatments. Likewise, in TCR-20, the significant upregulation of VrHSP-60.20 was observed under cold stress conditions upon treatment with GABA (84.4-fold) and SA (52.3-fold). Likewise, heat stress led to strong upregulation of VrHSP-60.20 upon GABA (74.7-fold) and SA (71.3-fold) treatments. VrHSP-60.22 showed higher basal expression in Shikha under control conditions, with the highest change observed with SA (11.2-fold), followed by IAA (2.0-fold). Cold stress induced the highest expression in SA (26.6-fold) and IAA (19.7-fold), while heat stress led to a decrease, particularly with SA treatment (1.0-fold). In TCR-20, the cold stress resulted in significant upregulation of IAA (81.9-fold), GABA (12.5-fold), and SA (4.2-fold).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eHeat stress induced dramatic increases, particularly with GABA treatment (124.2-fold), followed by SA (95.8-fold) and IAA (64.0-fold) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb). In Shikha, cold stress led to significant upregulation in VrHSP-70.12 upon IAA (8.7-fold) and SA (8.5-fold) treatments, while GABA caused a moderate increase (3.8-fold). Under heat stress, the increased expression of VrHSP-70.12 was recorded upon treatment with IAA (5.2-fold), SA (9.3-fold), and GABA (15.7-fold). In TCR-20, cold stress resulted in mild changes in expression of VrHSP-70.12, whereas heat stress caused a substantial increase in IAA (22.3-fold), SA (12.4-fold), and GABA (38.7-fold), indicating a stronger heat stress re-sponse. The gene VrHSP-70.2 showed enhanced expression in Shikha upon IAA (8.7-fold) and SA (8.5-fold) treatment, while GABA showed a 3.8-fold increase. Under heat stress, IAA (5.2-fold), SA (9.3-fold), and GABA (15.7-fold) treatments showed a significant upregulated expression pattern. In TCR-20, heat stress induced a significant increase upon IAA (42.3-fold), SA (32.4-fold), and GABA (74.7-fold) treatments, while cold stress led to notable expression upon IAA (17.4-fold) and SA (38.8-fold). VrHSP-90.6 exhibited higher expression under cold stress in Shikha, particularly upon treatment with IAA (6.6-fold), SA (4.5-fold), and GABA (5.0-fold), whereas heat stress led to moderate upre-gulation upon GABA (4.1-fold) treatment, but a decline upon SA treatment (0.6-fold). In contrast, TCR-20 showed a robust response under the heat stress, with the highest ex-pression upon SA (19.5-fold) and GABA (18.3-fold) treatment. VrHSP-100 showed strong induction under cold stress with SA (30.1-fold) and IAA (18.2-fold) treatments in Shikha, while no treatment resulted in a downregulated expression (0.4-fold). Under heat stress, increased expressions were observed upon IAA (3.4-fold) and GABA (4.1-fold) treatments, though priming with SA showed decreased expression (0.7-fold). Likewise, in TCR-20, the expression of VrHSP-100 was significantly higher under heat stress, particularly with GABA (31.3-fold) and SA (19.9-fold) treatment. Likewise, cold stress also induced strong upregulation upon SA (21.6-fold) and GABA (30.4-fold) treatment.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePrincipal Component Analysis (PCA) for HSP candidates\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe PCA of HSP gene expression data provides valuable insights into the differences between the stress response of the susceptible genotype Shikha and the tolerant genotype TCR-20 (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e). The 3D PCA plot visually represents these differences, with each point corresponding to a gene expression pattern under temperature stress conditions. In the present study, the three principal components (PC1, PC2, and PC3) summarized the variances in gene expression, allowing for a clear distinction between the contrasting genotypes. A key observation from the PCA plot was the distinct clustering of TCR-20 and Shikha, indicating significant differences in their transcriptional responses to cold and heat stresses. TCR-20 exhibited a wider spread across all three principal components, reflecting greater variability in gene expression. This suggested that TCR-20 had a more dynamic and regulated response to the stress, likely due to the upregulation of key HSP genes such as VrHSP-60.22, VrHSP-70.2, and VrHSP-60.20. In contrast, Shikha remained tightly clustered, indicating a more uniform and less adaptable response to environmental stressors. The separation along PC1, which captured the highest variance in gene expression, highlighted the fundamental transcriptional differences between the two genotypes. PC2 and PC3 further differentiated the expression patterns based on specific stress treatments, such as SA and GABA, which are known to enhance stress tolerance. The results confirmed that TCR-20 exhibited a stronger and more varied gene expression response, aligning with its superior thermo-tolerance. It provides strong evidence that TCR-20 is better equipped to cope up with heat and cold stresses, the stress adaptation being derived from key HSP genes.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eClimate change continuously threatens agricultural productivity, with plants facing numerous biotic and abiotic stresses due to their dynamic nature [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Among the abiotic stresses, both, cold and heat are critical to plant growth, development, and re-production [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. These adversely affect photosynthesis, plant growth, and overall re-productive success [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The decline in photosynthetic efficiency is primarily driven by excessive reactive oxygen species (ROS) accumulation, heat-induced protein denaturation, and disruptions in key enzymatic activities [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. In such situations, phytohormones play a crucial role in enhancing stress resilience by regulating biochemical, molecular, and physiological responses, thereby supporting plant growth and development under adverse conditions [\u003cspan additionalcitationids=\"CR37 CR38\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The present study highlights the differential stress responses of V. radiata cv. Shikha and V. glabrescens genotype TCR-20 under cold and heat stresses. GABA was found to be the most effective treatment in mitigating the chlorophyll loss and oxidative stress. TCR-20 maintained higher chlorophyll levels, especially under the cold stress, while Shikha exhibited better retention under the heat stress. Histological analysis revealed an increased oxidative damage to Shikha, with higher H₂O₂ accumulation as compared to TCR-20. GABA significantly reduced the oxidative stress markers in both genotypes, suggesting its protective role in stress tolerance. TCR-20 exhibited better intrinsic stress regulation, while Shikha benefited more from GABA, making it a prom-ising treatment for enhancing resilience in Vigna species. Differential chlorophyll retention and oxidative stress responses were observed in Shikha and TCR-20 under cold and heat stresses. In mungbean, studies have shown that exogenous GABA application improves chlorophyll stability and mitigates oxidative damage under heat stress [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Li et al. [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] reported that GABA was able to alleviate the harmful effects of cold stress in Medicago by promoting endogenous GABA metabolism, protecting the membrane system, and improving the leaf structure. For instance, GABA-treated rice plants exhibited higher chlorophyll retention and lower H₂O₂ levels, leading to enhanced photosynthetic effi-ciency and stress tolerance [\u003cspan additionalcitationids=\"CR43 CR44\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Furthermore, GABA improved the rice performance under both well-watered (FC100) and drought-stressed (FC50) conditions, improving resilience and supporting global food security. Similarly, in Triticum aestivum, GABA application has been reported to enhance antioxidant enzyme activity, reducing reactive oxygen species (ROS) accumulation under drought and heat stresses [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], aligning with our findings from the present study that GABA mitigated oxidative stress (In le-guminous crops, Glycine max (soybean) and Medicago sativa (alfalfa) also showed im-proved stress tolerance with GABA treatment, mainly through the activation of stress-responsive genes and antioxidant enzymes such as superoxide dismutase (SOD) and catalase (CAT). These enzymes help regulate ROS levels, reducing H₂O₂ accumula-tion, as also observed in TCR-20 under cold stress. Similarly, studies in Arabidopsis tha-liana, and sunflower also demonstrated that GABA improved stomatal regulation and enhanced metabolic adjustments under heat, cold, and other abiotic stresses [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e], which could explain its effectiveness in stabilizing chlorophyll content, antioxidant en-zymes in Vigna genotypes. Exogenous GABA enhanced the flavonoid synthesis, proline accumulation, and antioxidant enzyme activity under elevated O₃, which are able to re-duce the H₂O₂ and malondialdehyde levels. A reduction in wheat grain yield loss from 19.6\u0026ndash;9.6%, highlighted GABA\u0026rsquo;s potential in mitigating O₃-induced crop damage [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe contrasting responses between Shikha and TCR-20 under stress suggested the ge-notype-specific adaptations. TCR-20 showed superior cold tolerance and oxidative stress regulation, resembling the findings in cold-tolerant rice cultivars that maintain better ROS homeostasis. Similar to GABA, SA is also well known for its role in systemic acquired resistance (SAR), providing long-term protection against biotic stress. Studies in Oryza sativa, Zea mays, and Triticum aestivum have demonstrated that exogenous SA application improves drought tolerance by enhancing stomatal regulation and osmoprotectant accumulation. In wheat, exposure to elevated O₃, SA might further contribute to stress mitigation by reducing lipid peroxidation and improving antioxidant defenses [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e], complementing GABA\u0026rsquo;s protective effects. In our study, Shikha had greater susceptibility to oxidative stress, but a stronger response to GABA aligns with the studies on heat-tolerance in many crops, where GABA treatment enhanced tolerance by modulating metabolic and hormonal pathways for improving the heat tolerance [\u003cspan additionalcitationids=\"CR54\" citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Thus, inte-grating both SA and GABA into crop management strategies could offer a synergistic approach to enhancing resilience against environmental stressors.\u003c/p\u003e\u003cp\u003eThe plant hormone, auxin, is a key regulator of plant growth and development, playing pivotal roles in the integration of abiotic stress signals and control of downstream stress responses [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Recent advancements suggested that auxin influences stress mitigation by modulating pH and activating proton pumps, thereby altering transport dynamics. Models such as those by Steinacher et al. [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e] and Mellor et al. [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e] highlight auxin's role in regulating cellular responses, including lateral root emergence. These insights dem-onstrate the role of auxin in stress resilience by reducing lipid peroxidation, enhancing antioxidant defenses, and auxin signaling [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe phylogenetic tree showed a comparative evolutionary analysis of different heat shock proteins (HSPs) in Vigna radiata, as it is distinctly grouped based on their sequence similarity and relationships. The different clusters of the tree divide the families of the proteins sharing common ancestors distinctively [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. These clusters can give insights into how these proteins may have diverged functionally while retaining core structural similarities. For instance, the VrHSP-20 gene family indicated that these small HSPs are closely related to each other and might have evolved specific functions, such as in-volvement in stress responses. These small heat shock proteins are typically involved in preventing protein aggregation during stress. The HSP-70 and 90 gene families are cha-perone proteins known for their role in protein folding, unfolding, and transport across membranes [\u003cspan additionalcitationids=\"CR62\" citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. The Cpn60 chaperonins assist in protein folding, particularly under stress conditions, and maintain proteostasis. The HSP-100 family of proteins plays crucial roles in protein disaggregation and refolding during severe heat stress.\u003c/p\u003e\u003cp\u003eIn the present study, VrHSP-70 proteins formed multiple distinct branches, indicating that this family has undergone several rounds of gene duplication and specialization. This diversity is consistent with their multifaceted roles in responding to heat, cold, and other stress factors. On the contrary, Cpn60 proteins formed a close cluster, suggesting that these proteins have retained more structural and functional conservation as compared to the more diverse HSP families. Likewise, the VrHSP-100 family showed a clear cluster, with several proteins grouping together, which indicated their specialized function in high-temperature stress conditions. These proteins are known for their ability to dis-aggregate protein aggregates formed under extreme conditions. The distinct grouping of these proteins in the tree provided a framework for predicting their biological roles. Understanding the evolutionary relationships could help in studying how these proteins might have adapted to specific stresses, such as heat, drought, or pathogen attack. This phylogenetic tree revealed the evolutionary relationships among different heat shock proteins and chaperonins, highlighting how gene duplication and divergence have led to the specialization of these proteins in various stress response mechanisms [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. This in-termixing of HSP families in the phylogeny implies that the HSP gene network adapted to environmental challenges by developing flexible and overlapping functions. Gene duplication events, especially in the HSP20 and HSP70 families, appear to have created a pool of paralogous that diversified to assume varied roles, which might explain why these families do not form exclusive clades [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. Instead, the overlap in evolutionary branches indicated a convergence where genes from different families might perform similar functions or assist each other in maintaining protein stability during stress. This pattern of phylogenetic intermixing highlighted an evolutionary strategy in Vigna radiata where HSP genes from distinct families co-evolved to create a versatile and cooperative system for stress resilience, supporting the plant\u0026rsquo;s adaptability to diverse environmental stresses.\u003c/p\u003e\u003cp\u003eThe motifs likely represent critical domains, such as the alpha-crystallin domain in the HSP-20 family, involved in heat shock response. The major domain in HSP-20 is the α-crystallin domain, characteristic of small HSPs (HSP20 family). This domain functions as a molecular chaperone, binding to partially denatured proteins and preventing irre-versible aggregation. This protective mechanism is essential under heat and oxidative stress, as it preserves cellular integrity by stabilizing proteins that may become damaged or misfolded due to environmental challenges [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. Motif analysis of HSP 60 revealed that it is rich in TCP transcription factor. Each motif is positioned along the protein se-quences, and the p-values indicate the statistical significance of the motif's occurrence. The TCP domain motif, along with additional motifs, may be crucial for DNA-binding and regulatory functions. The consensus logos represent key conserved residues that are essential for the function of TCP proteins [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. The motifs are specific to DNA-binding domains or other regulatory regions. The motif of HSP 70 (GRAS Domain rich family), GRAS domain, along with other motifs, may be essential for interactions with other proteins or transcriptional regulation [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. These motifs are probably involved in tran-scriptional regulation and signaling pathways in plants [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e]. HSP 90 also k/a (GHD Fam-ily), the consensus sequence logos for the GHD family show the conserved amino acids in each motif. These are critical for the protein's role in regulating plant growth and hormone signaling [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. The HSP 100 consensus sequences highlight the key conserved regions in the HSP-100 family. These motifs may be involved in ATP binding, protein refolding, and interaction with other chaperone proteins [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. The VrCpn60/TCP1 family had a total of three domains, of which one is a major domain reported, which are responsible for assisting in protein folding and assembly, showing unique clustering patterns in the phylogenetic tree. The dominant domain was the TCP-1 chaperonin domain, which is crucial for the proper folding and assembly of cytoskeletal proteins, such as actin and tubulin [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e]. Under the stress conditions that may lead to protein misfolding, this domain helps maintain cellular structure and stability by ensuring that these essential proteins fold correctly [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. In VrHSP70, four domains are there, in which the core domain architecture includes the HSP70 domain, known for its ATPase activity, which allows the binding and refolding of misfolded proteins. This activity provides energy for repeated cycles of binding and release, supporting protein stability and folding, especially under conditions where proteins are prone to denaturation [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e]. Some candidates of the HSP70 family also contained additional motifs, indicative of evolutionary adaptations that allow them to perform specialized cellular functions. The HSP 90 domain across these proteins, such as kinases and hormone receptors, is essential for maintaining the protein conformation and stabilizing regulatory proteins. HSP90 functions as part of multi-protein complexes and is especially critical during prolonged stress, as it helps protect essential regulatory proteins from denaturation [\u003cspan additionalcitationids=\"CR78\" citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e]. The candidates of HSP100 family demonstrated the most complex domain architecture among the families analyzed. The AAA\u0026thinsp;+\u0026thinsp;ATPase and Clp domains were present in various combinations across the VrHSP100 members, enabling them to participate in multiple stress-related processes [\u003cspan additionalcitationids=\"CR81\" citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e]. The AAA\u0026thinsp;+\u0026thinsp;ATPase domain is involved in the disaggregation of misfolded proteins by using ATP hydrolysis, which provides energy to disassemble protein aggregates, making it crucial for severe stress recovery. The Clp domain, often found alongside the AAA\u0026thinsp;+\u0026thinsp;ATPase domain, is involved in protein degradation, ensuring cellular homeostasis by removing non-functional proteins that cannot be refolded. Each HSP family retains its core functional domain, such as the α-crystallin, TCP-1, HSP70, HSP90, or AAA\u0026thinsp;+\u0026thinsp;ATPase and Clp domains, emphasizing the primary stress-mitigation role of each family [\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e]. However, variations in domain architecture within families reflected the evolutionary adaptations that allow each family to address a range of environmental stressors. In comparison to other plants, Vigna radiata HSP domain architecture displayed similar functional diversification across the HSP families, which is a common evolutionary strategy observed in plants. For instance, in many plant species, the HSP20 and HSP70 families show structural diversity that enables the protection of cellular proteins during short-term and prolonged stress, respectively. The presence of multi-domain structures in the HSP100 family, such as AAA\u0026thinsp;+\u0026thinsp;ATPase and Clp domains, is also typical in other plants, where these domains contribute to recovery from severe stress through disaggregation and degradation of misfolded proteins. This comparative perspective suggests that while each plant species may have unique adaptations, the fundamental HSP domain structures and functions are highly conserved across species, reflecting the critical role of these proteins in stress tolerance and survival.\u003c/p\u003e\u003cp\u003eThe expression of various VrHSP genes was analyzed in the susceptible genotype, Shikha, and the resistant genotype, TCR-20, under cold and heat stress conditions, without or with treatments of different signaling molecules such as IAA, SA, and GABA. TCR-20 exhibited a stronger and more consistent stress response compared to Shikha, particularly under heat stress. In particular, the VrHSP-20 family revealed significant genotype-specific responses, with TCR-20 showing a more robust thermo-tolerance mechanism than Shikha. In Shikha, VrHSP-20.6 was found downregulated under heat stress and upregulated under cold stress, highlighting its role in temperature adaptation. Conversely, in TCR-20, VrHSP-20.6 was strongly upregulated, especially in response to salicylic acid (SA) and γ-aminobutyric acid (GABA), indicating its involvement in heat tolerance. Similarly, VrHSP-20.11 and VrHSP-20.13 were strongly induced in TCR-20, reinforcing their role in thermo-tolerance. VrHSP-20.19 did not respond in cv. Shikha, but it was induced under cold stress in TCR-20, indicating its significance in cold adaptation. These findings are consistent with the earlier reports on the role of HSPs in stress adaptation in other crops such as Glycine max, where GmHSP17.9 and GmHSP22.0 were upregulated under heat stress, contributing to stress tolerance [\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e, \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e]. Similarly, Cicer arietinum (chickpea) showed differential expression of CaHSP17.6 and CaHSP20.7 under heat stress, with ABA playing a significant regulatory role [\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e, \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e]. Moreover, VrHSP-22.2 showed a significant upregulation in TCR-20 under heat stress, particularly upon GABA treatment, further supporting the role of HSPs in heat stress mitigation. This mirrors the findings in Zea mays (maize), where ZmHSP17.2 was reported to play a key role in thermo-tolerance, with auxin (IAA) mediating its regulation [\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e]. However, while cereals like maize rely more heavily on auxin-mediated responses, legumes such as Vigna radiata and Medicago truncatula exhibit stronger GABA- and SA-mediated regulation of HSP ex-pression [\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e]. TCR-20 exhibited a well-coordinated stress-regulatory mechanism, with significantly higher levels of IAA, SA, and GABA under heat stress, indicating its superior thermo-tolerance. The sharp increase in IAA under heat stress in TCR-20 was particularly noteworthy, as auxin is involved in thermo-tolerance. Observations were also noticed in heat-resistant soybean and maize [\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e]. This finding aligns with those in cereals where GABA accumulation was observed to enhance heat stress resilience [\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e, \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe interaction network analysis of heat shock proteins (HSPs) and chaperonins (Cpn60) revealed strong functional associations among the stress-responsive proteins, particularly the resistant genotype, TCR-20. A significant interaction was observed between the HSP-70 family and Cpn60, with high interaction scores ranging from 0.682 to 0.847, which indicated a coordinated response where HSP-70 proteins collaborated with cha-peronins to facilitate protein folding and stabilization under stress conditions. Corres-pondingly, expression data confirmed that VrHSP-70.2 and VrHSP-70.12 exhibited sub-stantial upregulation in TCR-20 under heat stress, particularly with GABA (74.7-fold) and SA (32.4-fold) treatments, reinforcing their critical role in thermo-tolerance. Similarly, HSP-90.6 demonstrated strong interactions with Cpn60 proteins, with interaction scores exceeding 0.6, supporting its role in protein stabilization during heat stress. Expression analysis also aligned with these interactions, showing a marked increase in VrHSP-90.6 expression in TCR-20, particularly under IAA (15.9-fold) and SA (19.5-fold) treatments. This suggests its essential role in maintaining protein homeostasis and preventing heat-induced protein misfolding. Additionally, HSP-100 proteins exhibited strong interactions with HSP-70 and ATP-dependent Clp protease (interaction score: 0.405), highlighting their involvement in protein degradation and refolding during stress recovery. Correspondingly, VrHSP-100.2 was strongly upregulated in TCR-20 under heat stress (31.3-fold with GABA, 19.9-fold with SA), confirming its role in removing misfolded proteins and enhancing cellular stress tolerance. Furthermore, small HSPs (VrHSP-20.11, VrHSP-20.13, and VrHSP-20.6) exhibited interactions with VrHSP-70.8 (scores: 0.402\u0026ndash;0.585), suggesting their role in early stress response and preventing protein aggregation. Their higher expression levels in TCR-20 compared to Shikha reinforced their contribution to thermo-tolerance and early stress adaptation mechanisms. The interaction data aligned well with the expression analysis, revealing that TCR-20 exhibited stronger co-expression and interaction among key HSPs, which contributed to its enhanced stress adaptation to temperature stress. Chaperonins (Cpn60) emerge as central regulators, particularly in coordination with HSP-70 and HSP-90 proteins, supporting their essential role in stress protection. The combined expression and interaction analysis highlighted the superior ability of TCR-20 to withstand temperature stress as compared to Shikha, driven by higher gene upregulation and stronger protein-protein interactions.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cb\u003ePlant material, stress treatments, and experimentations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe experiments were performed with Shikha, a high-yielding and popular but ther-mo-sensitive cultivar of mungbean, and a thermo-tolerant wild accession, TCR-20 (IC 251372) of V. glabrescens [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Initially, the seeds of both these genotypes were sown in the seedling bags in three sets. These sets were treated as control, cold-stressed, and heat-stressed, respectively. Each set of experiments comprised of four pots as control and treated with indole acetic acid (IAA), salicylic acid (SA), and gama aminobuyric acid GABA. Four different foliar primings were done before 24h of stress as follows. Control was primed with double-distilled water, whereas the rest three treatments were sprayed with phyto-hormones viz., IAA (50 \u0026micro;Mol), SA (50 \u0026micro;Mol), and GABA (50 \u0026micro;Mol), respec-tively. The experiments were laid out in a randomized block design (RBD) with four replications in the Plant Tissue Culture Laboratory, Department of Basic and Social Sciences, Banda University of Agriculture and Technology, Banda, India. To ensure con-trolled environmental conditions, the plants were kept in the plant growth chamber at 300\u0026deg;C under a 14h light and 10h dark cycle. The temperature was maintained at 100\u0026deg;C for 3 days for cold stress treatment and 450\u0026deg;C for 3 days for heat stress treatment.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEstimation of chlorophyll content\u003c/b\u003e\u003c/p\u003e\u003cp\u003e100 mg of leaf sample was homogenized in 80% acetone and centrifuged at 8000 rpm for 5 min at room temperature for chlorophyll estimation. Absorbance was measured in a spectrophotometer at 663 nm, 645 nm, and 470 nm from 2 mL of supernatant. Chloro-phyll content was calculated as per Arnon [\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e] and expressed as mg/g FW.\u003c/p\u003e\u003cp\u003e\u003cb\u003eVisualization of H2O2 and O2\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe leaf samples from both the control and the stress environments were subjected to histochemical staining. The H2O2 and O2 were localized histochemically by the method suggested by Chen et al. [\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e]. After staining and bleaching, the photographs of the sam-ples were taken using a Sony DSLR camera.\u003c/p\u003e\u003cp\u003e\u003cb\u003eIdentification of small and large HSP protein sequences\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe Hidden Markov models (HMMs) profiles of Hsp20 (PF00011), Hsp40 (PF00226), Hsp70 (PF00012), Hsp90 (PF00183), HSP100 (PF02861 and PF10431) were downloaded from the protein database (PFAM) and legume information system. This analysis was used for the search to recognize candidate proteins with an E-value of 1e-5 by HMMER v3.2.1. Further, each of the selected candidates was examined for the conserved structure domain using NCBI-CDD [\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e]. ExPASy was used to calculate the molecular weight (MW) and isoelectric points (pI) [\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e]. The sub-cellular localization and signal peptide were predicted by using online software Cello Life, Wolfpsort (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://cello.life.nctu.edu.tw/\u003c/span\u003e\u003cspan address=\"http://cello.life.nctu.edu.tw/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://wolfpsort.hgc.jp/\u003c/span\u003e\u003cspan address=\"https://wolfpsort.hgc.jp/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and SignalP (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://services.healthtech.dtu.dk/service.php?SignalP-5.0\u003c/span\u003e\u003cspan address=\"https://services.healthtech.dtu.dk/service.php?SignalP-5.0\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), respectively [\u003cspan additionalcitationids=\"CR96\" citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003ePhylogenetic tree, domain analyses, and chromosomal distribution\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe identified VrHSP protein sequences were aligned using Clustal Omega with default parameters. The phylogeny was prepared using MEGA 11.0 with the Neighbor-joining method with default parameters [\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e]. The bootstrap replications were kept as n\u0026thinsp;=\u0026thinsp;1000. The intron and exon structure was visualized by using GSDS software V. 2.0. The protein domain and active motif function were analyzed in the Pfam database (pfan.xfam.org). The web-based motif identification servers MEME-Suit (Multiple Em for Motif Elicitation, meme-suite.org/meme/) were used to detect potential motifs with the following parameters as motif width\u0026thinsp;\u0026lt;\u0026thinsp;50, motifs\u0026thinsp;\u0026lt;\u0026thinsp;20, and e-value\u0026thinsp;\u0026lt;\u0026thinsp;e\u0026thinsp;\u0026minus;\u0026thinsp;5 [\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e]. The physical position of all the identified HSP genes was obtained from the V. radiata genome database and visu-alized by TBtools [\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e] (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://services.cbu.uib.no/tools/kaks\u003c/span\u003e\u003cspan address=\"http://services.cbu.uib.no/tools/kaks\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eProtein Protein interaction network analyses\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe interacting networks of HSP proteins were integrated into the STRING software ac-cessed on Feb 07, 2025 [\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e] (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.string-db.org/\u003c/span\u003e\u003cspan address=\"https://www.string-db.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), followed by an export of the co-expression network data.\u003c/p\u003e\u003cp\u003e\u003cb\u003eRNA extraction, cDNA synthesis and gene expression profiling\u003c/b\u003e\u003c/p\u003e\u003cp\u003e100 mg of frozen leaf samples in the liquid nitrogen were homogenized using tissue lys-er-II (Qiagen, Germany), and RNA was extracted using plant RNA extraction kit (RNeasy Mini Kit, Qiagen) following the manufacturer\u0026rsquo;s instructions. Subsequently, RNA was subjected to DNase treatment to remove the DNA contaminants and 1\u0026micro;g of purified RNA was reverse-transcribed by using the RevertAid First Strand cDNA Synthesis Kit (Thermo Fisher Scientific). The cDNA was quantified on a micro volume spectrophotometer (QIAExpert, Qiagen) and normalized to 50 ng/ \u0026micro;L for qRT-PCR analysis. Fifteen candidate genes representing different HSPs were subjected to expression analysis (Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). The qPCR reactions comprised of 10 \u0026micro;L 2X SYBR green q-PCR master mix (Thermo Fisher Scientific), 1 \u0026micro;L of 10 pmol each forward and reverse primers (Eurofins, India), 6 \u0026micro;L nuclease-free water, and 2 \u0026micro;L of cDNA were used. The fast-cycling approach was adopted with 2 min. Initial denaturation at 96oC, 40 cycles of 20 sec. denaturation at 96oC, 45 sec. annealing and extension at 60oC. The Actin gene was used as an internal control. qPCR analysis was carried out using a RealTime PCR machine, Quant Studio 5 (Thermo Fisher Scientific). Three biological replicates were taken, and two technical replicates were used for the expression analysis. The relative expression levels of the genes were calculated via the delta-delta CT method [\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e].\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe findings of the present study emphasized the species-specific differences in HSP regulation, hormonal signaling, and metabolic adaptation, with TCR-20 demonstrating superior hormonal modulation and stress resilience. The results further demonstrated the molecular mechanism of heat tolerance in Vigna species and the intricate phytohormone and metabolic networks, with auxin, salicylic acid (SA), and gamma-aminobutyric acid (GABA) playing pivotal roles in thermo-tolerance. The physico-chemical and molecular responses of TCR-20 uncovered the stress adaptation mechanisms, which can be leveraged to develop stress-resilient varieties through targeted breeding and biotechno-logical interventions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e All the data generated in this experiment were presented in the manuscript and its supplement files.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e The authors are thanks to Project Incharge, Center of Excellence in Dryland Agriculture for providing partial research support.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThe present work was financially supported by the Ministry of Agriculture, Agriculture Education and Research, Govt. of Uttar Pradesh, under the project “Center of Excellence in Dryland Agriculture (CEDA/2018)”.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003eC.M.S., B.P., S.P., Conceptualization; P.S., methodology, investigation, validation; A.K.M., data curation, C.M.S., S.P., formal analysis, supervision; P.S., S.P., writing—original draft preparation; C.M.S., funding acquisition; A.P., review and editing. All authors have read and agreed to the published version of the manuscript.\u0026nbsp;\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eClinical trial number:\u0026nbsp;\u003c/strong\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e Not applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u003c/strong\u003e The authors declare no conflict of interest.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBangar P, Chaudhury A, Tiwari B, Kumar S, Kumari R, Bhat KV. Morphophysiological and biochemical response of mungbean [Vigna radiata (L.) Wilczek] varieties at different developmental stages under drought stress. 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The STRING database in 2023: protein\u0026ndash;protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Res. 2023;51:D638\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLivak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2\u0026thinsp;\u0026ndash; ∆∆CT method. Methods. 2001;25:402\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Cold stress, Heat stress, HSP, Candidate genes, Exons, protein interaction network","lastPublishedDoi":"10.21203/rs.3.rs-7194231/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7194231/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAbiotic stresses significantly affect plant growth and productivity. Identification of stress-resistant genotypes is the best and an effective mitigation strategy. The present study evaluates the thermo-sensitive \u003cem\u003eVigna radiata\u003c/em\u003e cultivar Shikha and the thermo-tolerant \u003cem\u003eVigna glabrescens\u003c/em\u003e accession TCR-20 under the controlled (35\u0026ndash;38\u0026deg;C), cold (20\u0026ndash;30\u0026deg;C), and heat (45\u0026ndash;48\u0026deg;C) stress conditions, without any treatment or treated with indole-3-acetic acid (IAA), salicylic acid (SA), and gamma-aminobutyric acid (GABA). Chlorophyll content analysis revealed that TCR-20 maintained higher chlorophyll content under stress, whereas Shikha exhibited higher chlorophyll content upon foliar spray of GABA. Histochemical staining confirmed an increased oxidative stress under extreme temperatures, with GABA effectively mitigating superoxide accumulation in both genotypes. Further, mining and comparative analysis of 96 heat shock proteins (HSPs), including HSP20, HSP60, HSP70, HSP90, and HSP100 was also done. Physicochemical characterization revealed varied stability, solubility, and thermostability of several proteins, which exhibited higher stress tolerance potential. All 96 HSPs were found widespread across the 11 chromosomes. Notably, the HSP70 family, particularly VrHSP-70.2 in TCR-20, exhibited the most robust response under both cold and heat stress, with significant upregulation, especially with GABA and IAA treatments. The genes such as \u003cem\u003eVrHSP-70.2, VrHSP-60.22\u003c/em\u003e, and \u003cem\u003eVrHSP-20.24\u003c/em\u003e highlighted their significant upregulations in TCR-20 over Shikha. Overall, these findings provide valuable insights into the molecular and physiological mechanisms underlying thermo-tolerance in \u003cem\u003eVigna\u003c/em\u003e species, emphasizing the role of HSPs and stress-mitigating treatments for improving stress resilience in \u003cem\u003eVigna\u003c/em\u003e crops.\u003c/p\u003e","manuscriptTitle":"Exogenous application of gamma-amino butyric acid alleviates temperature stress in mungbean (Vigna radiata) and its wild non-progenitor (Vigna glabrescens) by regulating heat shock protein genes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-08 09:10:41","doi":"10.21203/rs.3.rs-7194231/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-18T21:49:42+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-17T18:29:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"77399020566261022168217766732116679010","date":"2025-08-05T03:37:30+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-04T20:24:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"166376826435053559992140916238826724068","date":"2025-08-03T16:07:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"1510336698538868656362800609369280966","date":"2025-08-03T04:03:36+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-03T03:37:52+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-01T22:38:55+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-31T13:11:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-31T13:10:41+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Plant Biology","date":"2025-07-23T08:50:10+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ebce99b3-622c-41fd-9e71-1ac7248335a2","owner":[],"postedDate":"August 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-01T16:06:04+00:00","versionOfRecord":{"articleIdentity":"rs-7194231","link":"https://doi.org/10.1186/s12870-025-07627-y","journal":{"identity":"bmc-plant-biology","isVorOnly":false,"title":"BMC Plant Biology"},"publishedOn":"2025-11-27 15:57:43","publishedOnDateReadable":"November 27th, 2025"},"versionCreatedAt":"2025-08-08 09:10:41","video":"","vorDoi":"10.1186/s12870-025-07627-y","vorDoiUrl":"https://doi.org/10.1186/s12870-025-07627-y","workflowStages":[]},"version":"v1","identity":"rs-7194231","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7194231","identity":"rs-7194231","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}