Antioxidant Defense Systems in Plants: Mechanisms, Regulation, and Biotechnological Strategies for Enhanced Oxidative Stress Tolerance
Abstract
1. Introduction
2. Antioxidant Defense Systems in Plants
2.1. Enzymatic and Non-Enzymatic Antioxidants
2.1.1. Enzymatic Antioxidants
2.1.2. Non-Enzymatic Antioxidants
2.2. Subcellular Localization and Dynamic Regulation
2.3. Transcriptional and Epigenetic Regulation of Antioxidant Defenses
3. Multilayered Regulation of Antioxidant Gene Expression
3.1. Transcriptional Control and Redox-Sensitive TFs
3.2. Hormonal and Epigenetic Modulation of Redox-Responsive Genes
3.3. Organelle Signaling and Biotechnological Applications
4. Omics Insights into Plant Responses to Redox Stress
4.1. Genomics and Genome-Wide Approaches
4.2. Transcriptomics and Gene Expression Profiling
4.3. Integration with Functional Validation
4.4. Proteomics and Post-Transcriptional Regulation
4.5. Metabolomics and Redox Pathway Mapping
4.6. Multi-Omics Integration and Systems Biology
4.7. From Omics to Application: Breeding and Engineering
4.8. Species-Specific Antioxidant Genes and Their Biotechnological Relevance in Crops
5. Biotechnological Strategies and Translational Breeding for Redox-Based Stress Resilience
5.1. Classical Transgenic Approaches: Overexpression of Redox Enzymes
5.2. Transcription Factor Engineering for Coordinated Antioxidant Control
5.3. Genome Editing of Redox Pathways with CRISPR/Cas
5.4. Molecular Breeding Empowered by MAS, Multi-Omics, and AI
5.5. Synthetic Biology and Ethical Considerations in Antioxidant Engineering
6. Redox-Driven Innovation: Future Directions and Strategic Challenges
6.1. From Gene Lists to Redox Networks: The Rise of Systems Biology
6.2. Artificial Intelligence and Predictive Redox Biology
6.3. Synthetic Biology for Modular Redox Engineering
6.4. Limitations and Future Challenges
6.5. Redox-Informed Strategies for Climate Resilience and Ethical Innovation
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Conflicts of Interest
References
- Mittler, R. Oxidative stress, antioxidants and stress tolerance. Trends Plant Sci. 2002, 7, 405–410. [Google Scholar] [CrossRef]
- Gill, S.S.; Tuteja, N. Reactive oxygen species and antioxidant machinery in abiotic stress tolerance in crop plants. Plant Physiol. Biochem. 2010, 48, 909–930. [Google Scholar] [CrossRef] [PubMed]
- Radi, R. Oxygen radicals, nitric oxide, and peroxynitrite: Redox pathways in molecular medicine. Proc. Natl. Acad. Sci. USA 2018, 115, 5839–5848. [Google Scholar] [CrossRef]
- Zaninotto, F.; La Camera, S.; Polverari, A.; Delledonne, M. Cross Talk between Reactive Nitrogen and Oxygen Species during the Hypersensitive Disease Resistance Response. Plant Physiol. 2006, 141, 379–383. [Google Scholar] [CrossRef] [PubMed]
- Sies, H.; Jones, D.P. Reactive oxygen species (ROS) as pleiotropic physiological signalling agents. Nat. Rev. Mol. Cell Biol. 2020, 21, 363–383. [Google Scholar] [CrossRef]
- Devireddy, A.R.; Arbogast, J.; Mittler, R. Coordinated and rapid whole-plant systemic stomatal responses to heat stress. Plant Cell Environ. 2020, 43, 2879–2890. [Google Scholar] [CrossRef]
- Foyer, C.H.; Noctor, G. Redox homeostasis and antioxidant signaling: A metabolic interface between stress perception and physiological responses. Plant Cell 2005, 17, 1866–1875. [Google Scholar] [CrossRef] [PubMed]
- Triantaphylidès, C.; Havaux, M. Singlet oxygen in plants: Production, detoxification and signaling. Trends Plant Sci. 2009, 14, 219–228. [Google Scholar] [CrossRef]
- Foyer, C.H.; Noctor, G. Redox regulation in photosynthetic organisms: Signaling, acclimation, and practical implications. Antioxid. Redox Signal. 2009, 11, 861–905. [Google Scholar] [CrossRef]
- Mullineaux, P.M.; Exposito-Rodriguez, M.; Laissue, P.P.; Smirnoff, N. ROS-dependent signalling pathways in plants and algae exposed to high light: Comparisons with other eukaryotes. Free Radic. Biol. Med. 2018, 122, 52–64. [Google Scholar] [CrossRef]
- Van Aken, O.; Ford, E.; Lister, R.; Huang, S.; Millar, A.H. Retrograde signalling caused by heritable mitochondrial dysfunction is partially mediated by ANAC017 and improves plant performance. Plant J. 2016, 88, 542–558. [Google Scholar] [CrossRef] [PubMed]
- Kaya, H.; Nakajima, R.; Iwano, M.; Kanaoka, M.M.; Kimura, S.; Takeda, S.; Kawarazaki, T.; Mori, K.; Shiba, H.; Isogai, A.; et al. Ca2+–activated reactive oxygen species production by Arabidopsis RbohH and RbohJ is essential for pollen tube growth. J. Exp. Bot. 2014, 65, 3001–3012. [Google Scholar] [CrossRef] [PubMed]
- Mubarakshina, M.M.; Ivanov, B.N.; Naydov, I.A.; Hillier, W.; Badger, M.R.; Krieger-Liszkay, A. Production and diffusion of chloroplastic H2O2 and its implication to signalling. J. Exp. Bot. 2010, 61, 3577–3587. [Google Scholar] [CrossRef]
- Nakagami, H.; Pitzschke, A.; Hirt, H. Emerging MAP kinase pathways in plant stress signalling. Trends Plant Sci. 2005, 10, 339–346. [Google Scholar] [CrossRef] [PubMed]
- Zheng, C.; Yang, Q.; Wang, X.; Chen, Y.; He, R.; Li, X.; Pan, H.; Zhuo, R.; Qu, T.; Qiu, W. Transcription Factors Involved in Plant Stress and Growth and Development: NAC. Agronomy 2025, 15, 949. [Google Scholar] [CrossRef]
- Xia, X.J.; Zhou, Y.H.; Shi, K.; Zhou, J.; Foyer, C.H.; Yu, J.Q. Interplay between reactive oxygen species and hormones in the control of plant development and stress tolerance. J. Exp. Bot. 2015, 66, 2839–2856. [Google Scholar] [CrossRef]
- Apel, K.; Hirt, H. Reactive oxygen species: Metabolism, oxidative stress, and signal transduction. Annu. Rev. Plant Biol. 2004, 55, 373–399. [Google Scholar] [CrossRef]
- Abdelaal, K.A.A.; Hafez, Y.M.; Shami, A.; Albarakaty, F.; Elansary, H.O. Silicon and nano-silicon enhance growth and salinity tolerance of wheat by modulating osmoprotectants and aquaporin gene expression. Plants 2021, 10, 2483. [Google Scholar] [CrossRef]
- Ghosh, U.K.; Islam, M.N.; Siddiqui, M.N.; Cao, X.; Khan, M.A.R. Proline, a Multifaceted Signalling Molecule in Plant Responses to Abiotic Stress: Understanding the Physiological Mechanisms. Plant Biol. 2021, 23, 1–14. [Google Scholar] [CrossRef]
- Fichman, Y.; Zandalinas, S.I.; Mittler, R. Systemic signaling in plants: Mechanisms, functions, and novel insights. Trends Plant Sci. 2021, 26, 1027–1040. [Google Scholar] [CrossRef]
- Crisp, P.A.; Ganguly, D.; Eichten, S.R.; Borevitz, J.O.; Pogson, B.J. Reconsidering plant memory: Intersections between stress recovery, RNA turnover, and epigenetics. Sci. Adv. 2016, 2, e1501340. [Google Scholar] [CrossRef]
- Hasanuzzaman, M.; Alam, M.M.; Rahman, A.; Hasanuzzaman, M.; Nahar, K.; Fujita, M. Exogenous glutathione mitigates salt stress in mung bean by regulating the antioxidant defense and methylglyoxal detoxification systems. Plants 2019, 8, 575. [Google Scholar] [CrossRef]
- Alscher, R.G.; Erturk, N.; Heath, L.S. Role of superoxide dismutases (SODs) in controlling oxidative stress in plants. J. Exp. Bot. 2002, 53, 1331–1341. [Google Scholar] [CrossRef]
- Shigeoka, S.; Ishikawa, T.; Tamoi, M.; Miyagawa, Y.; Takeda, T.; Yabuta, Y.; Yoshimura, K. Regulation and function of ascorbate peroxidase isoenzymes. J. Exp. Bot. 2002, 53, 1305–1319. [Google Scholar] [CrossRef]
- Hasanuzzaman, M.; Bhuyan, M.H.M.B.; Zulfiqar, F.; Raza, A.; Mohsin, S.M.; Mahmud, J.A.; Fujita, M. Reactive oxygen species and antioxidant defense in plants under abiotic stress: Revisiting the crucial role of a universal defense regulator. Antioxidants 2020, 9, 681. [Google Scholar] [CrossRef]
- Noctor, G.; Foyer, C.H. Ascorbate and glutathione: Keeping active oxygen under control. Annu. Rev. Plant Physiol. Plant Mol. Biol. 1998, 49, 249–279. [Google Scholar] [CrossRef]
- Agati, G.; Azzarello, E.; Pollastri, S.; Tattini, M. Flavonoids as antioxidants in plants: Location and functional significance. Plant Sci. 2012, 196, 67–76. [Google Scholar] [CrossRef]
- Halliwell, B.; Gutteridge, J.M.C. Free Radicals in Biology and Medicine, 5th ed.; Oxford University Press: Oxford, UK, 2015; ISBN 978-0-19-871748-5. [Google Scholar]
- Munné-Bosch, S.; Alegre, L. The function of tocopherols and tocotrienols in plants. Crit. Rev. Plant Sci. 2002, 21, 31–57. [Google Scholar] [CrossRef]
- Young, A.J.; Lowe, G.L. Antioxidant and prooxidant properties of carotenoids. Arch. Biochem. Biophys. 2001, 385, 20–27. [Google Scholar] [CrossRef] [PubMed]
- Sharma, A.; Shahzad, B.; Rehman, A.; Bhardwaj, R.; Landi, M.; Zheng, B. Response of Phenylpropanoid Pathway and the Role of Polyphenols in Plants under Abiotic Stress. Molecules 2019, 24, 2452. [Google Scholar] [CrossRef] [PubMed]
- Palma, J.M.; Corpas, F.J.; del Río, L.A. Proteome of plant peroxisomes: New perspectives on the role of these organelles in cell biology. Proteomics 2009, 9, 2301–2312. [Google Scholar] [CrossRef]
- Hasan, M.K.; Ahammed, G.J.; Yin, L.; Shi, K.; Xia, X.; Zhou, Y.; Yu, J. Melatonin mitigates cadmium phytotoxicity through modulation of phytochelatins biosynthesis, glutathione homeostasis and antioxidant potential in Solanum lycopersicum L. Front. Plant Sci. 2015, 6, 601. [Google Scholar] [CrossRef]
- Abdel Latef, A.A.H.; Tran, L.-S.P. Impacts of priming with silicon on the growth and tolerance of plants to abiotic stress. Sci. Hortic. 2016, 199, 1–17. [Google Scholar] [CrossRef]
- Siddiqi, K.S.; Husen, A.; Zahra, N.; Moheman, A. Harnessing Silicon Nanoparticles and Various Forms of Silicon for Enhanced Plant Growth Performance under Salinity Stress: Application and Mechanism. Discov. Nano 2025, 20, 89. [Google Scholar] [CrossRef]
- Dietrich, P.; Moeder, W.; Yoshioka, K. Plant Cyclic Nucleotide-Gated Channels: New Insights on Their Functions and Regulation. Plant Physiol. 2020, 184, 27–38. [Google Scholar] [CrossRef] [PubMed]
- Foyer, C.H.; Haynes, P.A.; Noctor, G. Redox signaling and stress memory in plants. Plant Physiol. Biochem. 2020, 155, 81–93. [Google Scholar] [CrossRef]
- Waszczak, C.; Akter, S.; Jacques, S.; Huang, J.; Messens, J.; Van Breusegem, F. Oxidative post-translational modifications of cysteine residues in plant signal transduction. J. Exp. Bot. 2015, 66, 2923–2938. [Google Scholar] [CrossRef]
- Li, G.; Yu, M.; Fang, T.; Cao, Z.; Zhang, Y.; Bai, Y.; Bai, Z.; Hu, Y. Molecular mechanisms of ROS regulation of plant development and stress responses. Front. Plant Sci. 2023, 14, 1094142. [Google Scholar] [CrossRef]
- Zou, J.J.; Li, X.D.; Ratnasekera, D.; Wang, C.; Liu, W.X.; Song, L.F.; Zhang, W.Z.; Wu, W.H. Arabidopsis calcium-dependent protein kinase CPK10 functions in abscisic acid- and Ca2+-mediated stomatal regulation in response to drought stress. Plant Physiol. 2010, 154, 1232–1243. [Google Scholar] [CrossRef] [PubMed]
- Zhang, W.; Xu, Z.; Zhou, X.; Zhang, M.; Xu, C.; Liu, H.; Yu, Y. Overexpression of antioxidant genes in transgenic plants improves stress tolerance to drought and salinity. J. Exp. Bot. 2017, 68, 467–479. [Google Scholar] [CrossRef]
- Li, Y.; Zhang, Y.; Li, Z.; Liu, J.; Yang, S.; Wang, H. The role of histone modifications in regulating antioxidant defense genes under oxidative stress. J. Exp. Bot. 2020, 71, 2717–2729. [Google Scholar] [CrossRef]
- Kim, J.M.; To, T.K.; Ishida, J.; Morosawa, T.; Kawashima, M.; Matsui, A.; Kimura, H.; Shinozaki, K.; Seki, M. Alterations of lysine modifications on the histone H3 N-tail under drought stress conditions in Arabidopsis thaliana. Plant Cell Physiol. 2008, 49, 1580–1588. [Google Scholar] [CrossRef] [PubMed]
- Zhong, S.; Li, J.; Miao, Y.; Ma, T.; Cui, S.; Li, J.; Jiang, Y. DNA methylation and gene regulation in plant responses to environmental stress. Front. Plant Sci. 2020, 11, 607. [Google Scholar] [CrossRef]
- Zhang, X.; Hu, Y.; Zhang, L.; Liu, L.; Xu, F. Chromatin remodeling and transcriptional regulation during oxidative stress in plants. J. Exp. Bot. 2020, 71, 3943–3956. [Google Scholar] [CrossRef]
- Begara-Morales, J.C.; Sánchez-Calvo, B.; Chaki, M.; Valderrama, R.; Mata-Pérez, C.; López-Jaramillo, J.; Padilla, M.N.; Corpas, F.J.; Barroso, J.B. Differential Transcriptomic Analysis by RNA-Seq of Nitrosative Stress in Arabidopsis thaliana. Int. J. Mol. Sci. 2019, 20, 619. [Google Scholar] [CrossRef]
- Kiranmai, K.; Gunupuru, L.R.; Pandurangaiah, M.; Nareshkumar, A.; Amaranatha Reddy, V.; Lokesh, U.; Venkatesh, B.; Anthony Johnson, A.M.; Sudhakar, C. A Novel WRKY Transcription Factor, MuWRKY3 (Macrotyloma uniflorum Lam. Verdc.) Enhances Drought Stress Tolerance in Transgenic Groundnut (Arachis hypogaea L.) Plants. Front. Plant Sci. 2018, 9, 346. [Google Scholar] [CrossRef] [PubMed]
- Berriri, S.; Rojas, G.; Sanchez, S.; Rodriguez, D.; Martinez, S.; Velasco, A. NAC transcription factors in plants: Role in response to oxidative stress and their regulation. Plant Biol. 2019, 21, 345–355. [Google Scholar] [CrossRef]
- Zhang, L.; Zhou, Y.; Li, S.; Xu, Z.; Zheng, G. MAPK cascades and their role in ROS signaling and stress adaptation in plants. Plant Physiol. Biochem. 2020, 156, 155–165. [Google Scholar] [CrossRef]
- Guo, Z.; Dzinyela, R.; Yang, L.; Hwarari, D. bZIP Transcription Factors: Structure, Modification, Abiotic Stress Responses and Application in Plant Improvement. Plants 2024, 13, 2058. [Google Scholar] [CrossRef]
- Liu, Y.; Zhang, Z.; Wei, Y.; Hu, J.; Yan, L. Thioredoxins and glutaredoxins in redox regulation and their role in stress tolerance. Front. Plant Sci. 2019, 10, 52. [Google Scholar] [CrossRef]
- Kumar, R.R.; Arora, K.; Goswami, S.; Sakhare, A.; Singh, B.; Chinnusamy, V.; Praveen, S. MAPK Enzymes: A ROS Activated Signaling Sensors Involved in Modulating Heat Stress Response, Tolerance and Grain Stability of Wheat under Heat Stress. 3 Biotech 2020, 10, 380. [Google Scholar] [CrossRef]
- Zhang, Z.; Wu, C.; Zhang, W.; Liu, L.; Wang, H.; Yuan, P.; Poovaiah, B.W. Interplay between Ca2+/Calmodulin-Mediated Signaling and AtSR1/CAMTA3 during Increased Temperature Resulting in Compromised Immune Response in Plants. Int. J. Mol. Sci. 2022, 23, 2175. [Google Scholar] [CrossRef]
- Collin, A.; Daszkowska-Golec, A.; Kurowska, M.; Szarejko, I. Barley ABI5 (Abscisic Acid INSENSITIVE 5) Is Involved in Abscisic Acid Dependent Drought Response. Front. Plant Sci. 2020, 11, 1138. [Google Scholar] [CrossRef] [PubMed]
- Fujita, Y.; Fujita, M.; Shinozaki, K.; Yamaguchi-Shinozaki, K. ABA-mediated transcriptional regulation in response to osmotic stress in plants. J. Plant Res. 2011, 124, 509–525. [Google Scholar] [CrossRef]
- Pré, M.; Atallah, M.; Champion, A.; De Vos, M.; Pieterse, C.M.J.; Memelink, J. The AP2/ERF domain transcription factor ORA59 integrates jasmonic acid and ethylene signals in plant defense. Plant Physiol. 2008, 147, 1347–1357. [Google Scholar] [CrossRef] [PubMed]
- Qiao, W.; Fan, L.-M. Nitric Oxide Signaling in Plant Responses to Abiotic Stresses. J. Integr. Plant Biol. 2008, 50, 1238–1246. [Google Scholar] [CrossRef] [PubMed]
- Sunkar, R.; Kapoor, A.; Zhu, J.K. Posttranscriptional regulation of SOD by miR398 during oxidative stress. Plant Cell 2006, 18, 2051–2065. [Google Scholar] [CrossRef]
- Kawashima, C.G.; Yoshimoto, N.; Maruyama-Nakashita, A.; Tsuchiya, Y.N.; Saito, K.; Takahashi, H.; Dalmay, T. Sulphur Starvation Induces the Expression of microRNA-395 and One of Its Target Genes but in Different Cell Types. Plant J. 2009, 57, 313–321. [Google Scholar] [CrossRef]
- Chan, K.X.; Phua, S.Y.; Crisp, P.; McQuinn, R.; Pogson, B.J. The role of GUN1 in chloroplast-to-nucleus signaling. Trends Plant Sci. 2016, 21, 598–610. [Google Scholar] [CrossRef]
- Dmitrieva, V.A.; Tyutereva, E.V.; Voitsekhovskaja, O.V. Singlet Oxygen in Plants: Generation, Detection, and Signaling Roles. Int. J. Mol. Sci. 2020, 21, 3237. [Google Scholar] [CrossRef]
- Ng, S.; Ivanova, A.; Duncan, O.; Law, S.R.; Van Aken, O.; De Clercq, I.; Wang, Y.; Carrie, C.; Xu, L.; Kmiec, B.; et al. A membrane-bound NAC transcription factor, ANAC017, mediates mitochondrial retrograde signaling. Plant Cell 2013, 25, 3450–3471. [Google Scholar] [CrossRef] [PubMed]
- Jiang, J.; Li, J.; Xu, Y.; Han, Y.; Qin, Y.; Guo, Y. Engineering antioxidant pathways in plants for enhanced stress tolerance. Biotechnol. Adv. 2021, 50, 107782. [Google Scholar] [CrossRef]
- El-Esawi, M.A.; Al-Ghamdi, A.A.; Ali, H.M.; Ahmad, M. Overexpression of AtWRKY30 Transcription Factor Enhances Heat and Drought Stress Tolerance in Wheat (Triticum aestivum L.). Genes 2019, 10, 163. [Google Scholar] [CrossRef] [PubMed]
- Jeong, J.S.; Kim, Y.S.; Baek, K.H.; Jung, H.; Ha, S.H.; Do Choi, Y.; Kim, M.; Reuzeau, C.; Kim, J.K. Root-Specific Expression of OsNAC10 Improves Drought Tolerance and Grain Yield in Rice under Field Drought Conditions. Plant Physiol. 2010, 153, 185–197. [Google Scholar] [CrossRef]
- Gupta, S.; Kaur, R.; Sharma, T.; Bhardwaj, A.; Sharma, S.; Sohal, J.S.; Singh, S.V. Multi-Omics Approaches for Understanding Stressor-Induced Physiological Changes in Plants: An Updated Overview. Physiol. Mol. Plant Pathol. 2023, 126, 102047. [Google Scholar] [CrossRef]
- Mittler, R.; Blumwald, E. Genetic engineering for modern agriculture: Challenges and perspectives. Genomic approaches to stress tolerance in crops. Curr. Opin. Plant Biol. 2010, 13, 161–165. [Google Scholar] [CrossRef]
- Cao, Y.; Han, Y.; Jin, Q.; Lin, Y.; Cai, Y. Genome-wide identification of SOD gene family in tomato and expression under abiotic stress. Int. J. Mol. Sci. 2020, 21, 6032. [Google Scholar] [CrossRef]
- Luo, J.; Zhou, J.J.; Zhang, J.Z. Comparative genomics reveals lineage-specific gene family expansion of antioxidant enzymes in rice. Front. Genet. 2019, 10, 776. [Google Scholar] [CrossRef]
- Wang, H.; Qin, F. Genome-Wide Association Study Reveals Natural Variations Contributing to Drought Resistance in Crops. Front. Plant Sci. 2017, 8, 1110. [Google Scholar] [CrossRef]
- Thu, T.; Takeo, Y. Identification of QTLs by Genome-Wide Association Study in Rice for Salt Tolerance. Vietnam J. Agric. Sci. 2025, 8, 2343–2358. [Google Scholar] [CrossRef]
- Wang, X.; An, Y.; Xu, P.; Xu, Y.; Ma, X.; Li, X. QTL mapping and GWAS identify loci for ascorbate and glutathione content in Arabidopsis. Plant Cell Environ. 2018, 41, 2607–2620. [Google Scholar] [CrossRef]
- Xie, Y.; Feng, Y.; Chen, Q.; Zhao, F.; Zhou, S.; Ding, Y.; Wang, B. Genome-Wide Association Analysis of Salt Tolerance QTLs with SNP Markers in Maize (Zea mays L.). Genes Genom. 2019, 41, 1135–1145. [Google Scholar] [CrossRef]
- Li, W.; Chen, J.; Liu, Y.; Chen, G.; Zhang, Q. Comparative transcriptomic and genomic analyses reveal redox gene diversity in C3 and C4 plants. Plant J. 2022, 110, 1445–1459. [Google Scholar] [CrossRef]
- Yu, T.; Ma, X.; Zhang, J.; Cao, S.; Li, W.; Yang, G.; He, C. Progress in Transcriptomics and Metabolomics in Plant Responses to Abiotic Stresses. Curr. Issues Mol. Biol. 2025, 47, 421. [Google Scholar] [CrossRef] [PubMed]
- Xu, X.; Liu, Y.; Li, M.; Li, X.; Xu, M. Transcriptomic analysis of WRKY and NAC transcription factors in drought-stressed tomato. Genes 2020, 11, 52. [Google Scholar] [CrossRef]
- Yu, C.; Cao, Y.; Zhang, D.; Wang, Q.; Li, Y. Comprehensive transcriptomic profiling of high light stress in Arabidopsis reveals oxidative regulatory modules. Plant Sci. 2021, 307, 111136. [Google Scholar] [CrossRef]
- Mi, W.; Liu, Z.; Jin, J.; Dong, X.; Xu, C.; Zou, Y.; Xu, M.; Zheng, G.; Cao, X.; Fang, X.; et al. Comparative Proteomics Analysis Reveals the Molecular Mechanism of Enhanced Cold Tolerance through ROS Scavenging in Winter Rapeseed (Brassica napus L.). PLoS ONE 2021, 16, e0243292. [Google Scholar] [CrossRef]
- Huang, D.; Wu, W.; Abrams, S.R.; Cutler, A.J. Integration of transcriptomics and proteomics reveals stress- responsive antioxidant pathways in maize. J. Proteome Res. 2016, 15, 3895–3907. [Google Scholar] [CrossRef]
- Shukla, V.; Varun, S.; Yadav, G. CRISPR/Cas9-mediated targeted editing in plants: Advances and applications. Plant Physiol. Biochem. 2020, 156, 204–216. [Google Scholar] [CrossRef]
- Chen, L.; Xiang, S.; Chen, Y.; Li, D.; Yu, D. Arabidopsis WRKY45 Interacts with the DELLA Protein RGL1 to Positively Regulate Age-Triggered Leaf Senescence. Mol. Plant 2017, 10, 1174–1189. [Google Scholar] [CrossRef]
- Andrade Galan, A.G.; Doll, J.; von Roepenack-Lahaye, E.; Hatzig, S.V.; Mueller-Roeber, B.; Krupinska, K.; Miao, Y. The Transcription Factor WRKY25 Can Act as Redox Switch to Drive the Expression of WRKY53 during Leaf Senescence in Arabidopsis. Sci. Rep. 2025, 15, 27623. [Google Scholar] [CrossRef]
- Jung, Y.J.; Kim, J.Y.; Cho, Y.G.; Kang, K.K. CRISPR/Cas9-Mediated Knockout of OsbZIP76 Reveals Its Role in ABA-Associated Immune Signaling in Rice. Int. J. Mol. Sci. 2025, 26, 6374. [Google Scholar] [CrossRef]
- Tiwari, J.K.; Singh, A.K.; Behera, T.K. CRISPR/Cas Genome Editing in Tomato Improvement: Advances and Applications. Front. Plant Sci. 2023, 14, 1121209. [Google Scholar] [CrossRef] [PubMed]
- Chakraborty, A.; Wylie, S.J. CRISPR/Cas9 for Heat Stress Tolerance in Rice: A Review. Plant Mol. Biol. Rep. 2025. [Google Scholar] [CrossRef]
- Shawky, A.; Hatawsh, A.; Al-Saadi, N.; Farzan, R.; Eltawy, N.; Francis, M.; Abousamra, S.; Ismail, Y.Y.; Attia, K.; Fakhouri, A.S.; et al. Revolutionizing Tomato Cultivation: CRISPR/Cas9 Mediated Biotic Stress Resistance. Plants 2024, 13, 2269. [Google Scholar] [CrossRef] [PubMed]
- Shalem, O.; Sanjana, N.E.; Zhang, F. High-Throughput Functional Genomics Using CRISPR-Cas9. Nat. Rev. Genet. 2015, 16, 299–311. [Google Scholar] [CrossRef]
- Jones, A.M.E.; De Smet, I. Editorial: Proteomics of Plant Development and Hormonal Responses, Volume II. Front. Plant Sci. 2023, 14, 1340170. [Google Scholar] [CrossRef]
- Niu, Z.; Liu, L.; Pu, Y.; Zhang, Y.; Gao, J.; Zhang, C.; Gong, J.; Wang, Y.; Wang, C.; Zhang, L.; et al. iTRAQ-Based Quantitative Proteome Analysis Insights into Cold Stress of Winter Rapeseed (Brassica rapa L.) Grown in the Field. Sci. Rep. 2021, 11, 23434. [Google Scholar] [CrossRef] [PubMed]
- Martínez-Esteso, M.J.; Morante-Carriel, J.; Samper-Herrero, A.; Martínez-Márquez, A.; Sellés-Marchart, S.; Nájera, H.; Bru-Martínez, R. Proteomics: An Essential Tool to Study Plant-Specialized Metabolism. Biomolecules 2024, 14, 1539. [Google Scholar] [CrossRef]
- Liu, X.; Yang, M.-F.; Zhu, Y.; Liang, Y. Proteomic Analysis of Salt Stress Responses in Rice Shoot. J. Plant Biol. 2011, 54, 384–395. [Google Scholar] [CrossRef]
- Martí-Guillén, J.M.; Pardo-Hernández, M.; Martínez-Lorente, S.E.; Almagro, L.; Rivero, R.M. Redox Post-Translational Modifications and Their Interplay in Plant Abiotic Stress Tolerance. Front. Plant Sci. 2022, 13, 1027730. [Google Scholar] [CrossRef]
- Sun, F.; Wang, J.; Geng, S.; Liang, Y.; Gong, Z.; Yang, N.; Qian, S.; Zhang, N.; Li, X.; Wang, J.; et al. Comprehensive Transcriptomic and Metabolomic Analysis Revealed Drought Tolerance Regulatory Pathways in Upland Cotton. Front. Plant Sci. 2025, 16, 1571944. [Google Scholar] [CrossRef]
- Serag, A.; Salem, M.A.; Gong, S.; Wu, J.L.; Farag, M.A. Decoding Metabolic Reprogramming in Plants under Pathogen Attacks: A Comprehensive Review of Emerging Metabolomics Technologies to Maximize Their Applications. Metabolites 2023, 13, 424. [Google Scholar] [CrossRef]
- Carrera, F.P.; Noceda, C.; Maridueña-Zavala, M.G.; Cevallos-Cevallos, J.M. Metabolomics, a Powerful Tool for Understanding Plant Abiotic Stress. Agronomy 2021, 11, 824. [Google Scholar] [CrossRef]
- Zhang, D.; Liu, J.; Zhang, Y.; Wang, H.; Wei, S.; Zhang, X.; Zhang, D.; Ma, H.; Ding, Q.; Ma, L. Morphophysiological, Proteomic and Metabolomic Analyses Reveal Cadmium Tolerance Mechanism in Common Wheat (Triticum aestivum L.). J. Hazard. Mater. 2023, 445, 130499. [Google Scholar] [CrossRef]
- Wang, Z.; Xu, J.; Chen, L.; Liu, B. Multi-omics integration in plant systems biology: Key concepts and future perspectives. Plant J. 2021, 107, 1–17. [Google Scholar] [CrossRef]
- Martínez-Márquez, A.; Ortega-Muñoz, M.; Nieto, L.; Sánchez, M.; Dorado, G. OmicsNet: A web-based platform for visualizing multi-omics interaction networks. Nucleic Acids Res. 2020, 48, W700–W705. [Google Scholar] [CrossRef]
- Usadel, B.; Poree, F.; Nagel, A.; Lohse, M.; Czedik-Eysenberg, A.; Stitt, M. MapMan 4: A refined tool for pathway-based analysis of omics data. Mol. Plant 2018, 11, 943–944. [Google Scholar] [CrossRef]
- Shannon, P.; Markiel, A.; Ozier, O.; Baliga, N.S.; Wang, J.T.; Ramage, D.; Ideker, T. Cytoscape 3.9: New features for network biology. Nucleic Acids Res. 2021, 49, W364–W368. [Google Scholar] [CrossRef]
- Zhou, G.; Xia, J. OmicsNet: A Web-Based Tool for Creation and Visual Analysis of Biological Networks in 3D Space. Nucleic Acids Res. 2018, 46, W514–W522. [Google Scholar] [CrossRef]
- Wagan, S.; Ali, M.; Khoso, M.A.; Alam, I.; Dinislam, K.; Hussain, A.; Brohi, N.A.; Manghwar, H.; Liu, F. Deciphering the Role of WRKY Transcription Factors in Plant Resilience to Alkaline Salt Stress. Plant Stress 2024, 13, 100526. [Google Scholar] [CrossRef]
- Li, J.; Yu, Q.; Liu, C.; Zhang, N.; Xu, W. Flavonoids as Key Players in Cold Tolerance: Molecular Insights and Applications in Horticultural Crops. Hortic. Res. 2025, 12, uhae366. [Google Scholar] [CrossRef]
- Nazari, L.; Ghotbi, V.; Nadimi, M.; Paliwal, J. A Novel Machine-Learning Approach to Predict Stress-Responsive Genes in Arabidopsis. Algorithms 2023, 16, 407. [Google Scholar] [CrossRef]
- Le Roux, M.-S.; Kunert, K.J.; Cullis, C.A.; Botha, A.-M. Unlocking Wheat Drought Tolerance: The Synergy of Omics Data and Computational Intelligence. Food Energy Secur. 2024, 13, e70024. [Google Scholar] [CrossRef]
- Farooq, M.A.; Gao, S.; Hassan, M.A.; Huang, Z.; Rasheed, A.; Hearne, S.; Prasanna, B.; Li, X.; Li, H. Artificial Intelligence in Plant Breeding. Trends Genet. 2024, 40, 891–908. [Google Scholar] [CrossRef]
- Roychowdhury, R.; Das, S.P.; Gupta, A.; Parihar, P.; Chandrasekhar, K.; Sarker, U.; Kumar, A.; Ramrao, D.P.; Sudhakar, C. Multi-Omics Pipeline and Omics-Integration Approach to Decipher Plant’s Abiotic Stress Tolerance Responses. Genes 2023, 14, 1281. [Google Scholar] [CrossRef]
- Majumder, R.R.; Sakhale, S.; Yadav, S.; Sandhu, N.; Hassan, L.; Hossain, M.A.; Kumar, A. Molecular Breeding for Improving Drought Tolerance in Rice: Recent Progress and Future Perspectives. In Molecular Breeding for Rice Abiotic Stress Tolerance and Nutritional Quality; Wiley: Hoboken, NJ, USA, 2021; pp. 39–72. [Google Scholar] [CrossRef]
- Si, X.; Huawei, Z.; Wang, Y.; Chen, K.; Gao, C. Manipulating Gene Translation in Plants by CRISPR–Cas9-Mediated Genome Editing of Upstream Open Reading Frames. Nat. Protoc. 2020, 15, 338–363. [Google Scholar] [CrossRef]
- Liu, W.; Yuan, J.S.; Stewart, C.N., Jr. Advanced genetic tools for plant biotechnology. Nat. Rev. Genet. 2013, 14, 781–793. [Google Scholar] [CrossRef] [PubMed]
- Liu, W.; Stewart, C.N., Jr. Plant synthetic promoters and transcription factors. Curr. Opin. Biotechnol. 2016, 37, 36–44. [Google Scholar] [CrossRef]
- Kummari, D.; Palakolanu, S.R.; Kishor, P.B.K.; Bhatnagar-Mathur, P.; Sharma, K.K.; Vadez, V.; Singam, P. An update and perspectives on the use of promoters in plant genetic engineering. J. Biosci. 2020, 45, 87. [Google Scholar] [CrossRef]
- Mazur, J. Automated Decision-Making and the Precautionary Principle in EU Law. Balt. J. Eur. Stud. 2019, 9, 3–18. [Google Scholar] [CrossRef]
- Sackey, O.K.; Feng, N.; Mohammed, Y.Z.; Dzou, C.F.; Zheng, D.; Zhao, L.; Shen, X. A Comprehensive Review on Rice Responses and Tolerance to Salt Stress. Front. Plant Sci. 2025, 16, 1561280. [Google Scholar] [CrossRef] [PubMed]
- Rossatto, T.; do Amaral, M.N.; Benitez, L.C.; Vighi, I.L.; Braga, E.J.B.; de Magalhães Júnior, A.M.; Maia, M.A.C.; Pinto, L.S. Gene Expression and Activity of Antioxidant Enzymes in Rice Plants, cv. BRS AG, under Saline Stress. Physiol. Mol. Biol. Plants 2017, 23, 865–875. [Google Scholar] [CrossRef] [PubMed]
- Yuan, L.; Gai, W.; Xuan, X.; Ahiakpa, J.K.; Li, F.; Ge, P.; Zhang, X.; Tao, J.; Yang, Y.; Zhang, Y. Advances in Improving Tomato Fruit Quality by Gene Editing. Hortic. Plant J. 2024. [Google Scholar] [CrossRef]
- Jiao, C.; Sun, J.; Wei, Y. SlWRKY31 Enhances Chilling Tolerance by Interacting with SlSIZ1 in Tomato Fruit. Postharvest Biol. Technol. 2024, 207, 112631. [Google Scholar] [CrossRef]
- Kumar, A.; Sichov, N.; Bucki, P.; Miyara, S.B. SlWRKY16 and SlWRKY31 of Tomato, Negative Regulators of Plant Defense, Involved in Susceptibility Activation Following Root-Knot Nematode Meloidogyne javanica Infection. Sci. Rep. 2023, 13, 14592. [Google Scholar] [CrossRef]
- Liu, N.; Wu, H.; Wang, M.; Zhang, H. Recent Developments in Enzymatic Antioxidant Defense Systems in Plants under Abiotic Stress: Overexpression Studies and Genetic Engineering Strategies. Antioxidants 2021, 10, 1531. [Google Scholar] [CrossRef]
- Khalid, F.; Rasheed, Y.; Asif, K.; Ashraf, H.; Maqsood, M.F.; Shahbaz, M.; Zulfiqar, U.; Sardar, R.; Haider, F.U. Plant Biostimulants: Mechanisms and Applications for Enhancing Plant Resilience to Abiotic Stresses. J. Soil Sci. Plant Nutr. 2024, 24, 6641–6690. [Google Scholar] [CrossRef]
- Mishra, N.; Jiang, C.; Chen, L.; Paul, A.; Chatterjee, A.; Shen, G. Achieving Abiotic Stress Tolerance in Plants through Antioxidative Defense Mechanisms: A Comprehensive Review. Front. Plant Sci. 2023, 14, 1110622. [Google Scholar] [CrossRef]
- Baranova, E.N.; Kononenko, N.V.; Lapshin, P.V.; Nechaeva, T.L.; Khaliluev, M.R.; Zagoskina, N.V.; Smirnova, E.A.; Yuorieva, N.O.; Raldugina, G.N.; Chaban, I.A.; et al. Superoxide Dismutase Premodulates Oxidative Stress in Plastids for Protection of Tobacco Plants from Cold Damage. Int. J. Mol. Sci. 2024, 25, 5544. [Google Scholar] [CrossRef]
- Leng, X.; Wang, H.; Zhang, S.; Qu, C.; Yang, C.; Xu, Z.; Liu, G. Identification and Characterization of the APX Gene Family and Its Expression Pattern under Phytohormone Treatment and Abiotic Stress in Populus trichocarpa. Genes 2021, 12, 334. [Google Scholar] [CrossRef]
- Cheng, M.C.; Liao, P.M.; Kuo, W.W.; Lin, T.P. The Arabidopsis ETHYLENE RESPONSE FACTOR1 Regulates Abiotic Stress-Responsive Gene Expression by Binding to Different cis-Acting Elements in Response to Different Stress Signals. Plant Physiol. 2013, 162, 1566–1582. [Google Scholar] [CrossRef]
- Sakuma, Y.; Maruyama, K.; Qin, F.; Osakabe, Y.; Shinozaki, K.; Yamaguchi-Shinozaki, K. Dual Function of an Arabidopsis Transcription Factor DREB2A in Water-Stress-Responsive and Heat-Stress-Responsive Gene Expression. Proc. Natl. Acad. Sci. USA 2006, 103, 18822–18827. [Google Scholar] [CrossRef]
- Rahmat, A.; Nugroho, S.; Sukma, D.; Aswidinnoor, H. Overexpression of OsNAC6 Transcription Factor from Indonesia Rice Cultivar Enhances Drought and Salt Tolerance. Emir. J. Food Agric. 2014, 26, 502–510. [Google Scholar] [CrossRef]
- Bandyopadhyay, A.; Kancharla, N.; Javalkote, V.; Dasgupta, S.; Brutnell, T.P. CRISPR-Cas12a (Cpf1): A Versatile Tool in the Plant Genome Editing Toolbox for Agricultural Advancement. Front. Plant Sci. 2020, 11, 584151. [Google Scholar] [CrossRef] [PubMed]
- Tran, M.T.; Son, G.H.; Song, Y.J.; Nguyen, N.T.; Park, S.; Thach, T.V.; Kim, J.; Sung, Y.W.; Das, S.; Pramanik, D.; et al. CRISPR-Cas9-Based Precise Engineering of SlHyPRP1 Protein towards Multi-Stress Tolerance in Tomato. Front. Plant Sci. 2023, 14, 1186932. [Google Scholar] [CrossRef] [PubMed]
- Xu, S.; Chen, T.; Tian, M.; Rahantaniaina, M.S. Genetic Manipulation of Reactive Oxygen Species (ROS) Homeostasis Utilizing CRISPR/Cas9-Based Gene Editing in Rice. In Reactive Oxygen Species in Plants; Gupta, D.K., Palma, J.M., Corpas, F.J., Eds.; Methods in Molecular Biology; Humana: New York, NY, USA, 2022; Volume 2526, pp. 25–41. [Google Scholar] [CrossRef]
- Wang, Y.; Liu, Z.; Li, L.; Pan, X.; Yao, K.; Wei, W.; Liao, W.; Wang, C. The Characteristics and Expression Analysis of the Tomato SlRBOH Gene Family under Exogenous Phytohormone Treatments and Abiotic Stresses. Int. J. Mol. Sci. 2024, 25, 5780. [Google Scholar] [CrossRef]
- Li, C.; Iqbal, M.A. Leveraging the Sugarcane CRISPR/Cas9 Technique for Genetic Improvement of Non-Cultivated Grasses. Front. Plant Sci. 2024, 15, 1369416. [Google Scholar] [CrossRef]
- Martins, L.; Knuesting, J.; Bariat, L.; Dard, A.; Freibert, S.A.; Marchand, C.H.; Young, D.; Dung, N.H.T.; Voth, W.; Debures, A.; et al. Redox Modification of the Iron-Sulfur Glutaredoxin GRXS17 Activates Holdase Activity and Protects Plants from Heat Stress. Plant Physiol. 2020, 184, 676–692. [Google Scholar] [CrossRef]
- Krishnamurthy, S.L.; Pundir, P.; Warraich, A.S.; Rathor, S.; Lokeshkumar, B.M.; Singh, N.K.; Sharma, P.C. Introgressed Saltol QTL Lines Improve the Salinity Tolerance in Rice at Seedling Stage. Front. Plant Sci. 2020, 11, 833. [Google Scholar] [CrossRef]
- Bai, W.; Li, C.; Li, W.; Wang, H.; Han, X.; Wang, P.; Wang, H. Machine learning assists prediction of genes responsible for plant specialized metabolite biosynthesis by integrating multi-omics data. BMC Genom. 2024, 25, 418. [Google Scholar] [CrossRef]
- Mushtaq, M.A.; Ahmed, H.G.M.-D.; Zeng, Y. Applications of Artificial Intelligence in Wheat Breeding for Sustainable Food Security. Sustainability 2024, 16, 5688. [Google Scholar] [CrossRef]
- Khan, M.H.U.; Wang, S.; Wang, J.; Ahmar, S.; Saeed, S.; Khan, S.U.; Xu, X.; Chen, H.; Bhat, J.A.; Feng, X. Applications of Artificial Intelligence in Climate-Resilient Smart-Crop Breeding. Int. J. Mol. Sci. 2022, 23, 11156. [Google Scholar] [CrossRef]
- Costa-Neto, G.; Fritsche-Neto, R.; Crossa, J. The Modern Plant Breeding Triangle: Optimizing the Use of Genomics, Phenomics, and Enviromics Data. Front. Plant Sci. 2021, 12, 651480. [Google Scholar] [CrossRef]
- de los Campos, G.; Pérez-Rodríguez, P.; Bogard, M.; Gouache, D.; Crossa, J. A Data-Driven Simulation Platform to Predict Cultivars’ Performances under Uncertain Weather Conditions. Nat. Commun. 2020, 11, 4876. [Google Scholar] [CrossRef]
- Misra, S.; Ganesan, M. The Impact of Inducible Promoters in Transgenic Plant Production and Crop Improvement. Plant Gene 2021, 27, 100300. [Google Scholar] [CrossRef]
- Vazquez-Vilar, M.; Selma, S.; Orzaez, D. The Design of Synthetic Gene Circuits in Plants: New Components, Old Challenges. J. Exp. Bot. 2023, 74, 3791–3805. [Google Scholar] [CrossRef]
- Turnbull, C.; Lillemo, M.; Hvoslef-Eide, T.A.K. Global Regulation of Genetically Modified Crops Amid the Gene Edited Crop Boom—A Review. Front. Plant Sci. 2021, 12, 630396. [Google Scholar] [CrossRef]
- Whelan, A.I.; Lema, M.A. Regulatory Framework for Gene Editing and Other New Breeding Techniques (NBTs) in Argentina. GM Crops Food 2015, 6, 253–265. [Google Scholar] [CrossRef]
- Moldogazieva, N.T.; Mokhosoev, I.M.; Feldman, N.B.; Lutsenko, S.V. ROS and RNS Signalling: Adaptive Redox Switches through Oxidative/Nitrosative Protein Modifications. Free Radic. Res. 2018, 52, 507–543. [Google Scholar] [CrossRef] [PubMed]
- Godoy-Sanches, P.H.; de Melo, N.C.; Porcari, A.M.; de Carvalho, L.M. Integrating Molecular Perspectives: Strategies for Comprehensive Multi-Omics Integrative Data Analysis and Machine Learning Applications in Transcriptomics, Proteomics, and Metabolomics. Biology 2024, 13, 848. [Google Scholar] [CrossRef] [PubMed]
- Zhong, T.; Zhu, M.; Zhang, Q.; Zhang, Y.; Deng, S.; Guo, C.; Xu, L.; Liu, T.; Li, Y.; Bi, Y.; et al. The ZmWAKL–ZmWIK–ZmBLK1–ZmRBOH4 Module Provides Quantitative Resistance to Gray Leaf Spot in Maize. Nat. Genet. 2024, 56, 315–326. [Google Scholar] [CrossRef] [PubMed]
- Wang, J.; Liu, X.; Kang, Y.; Liu, A.; Li, P. Functional Analysis and Interaction Networks of Rboh in Poplar under Abiotic Stress. Front. Plant Sci. 2025, 16, 1553057. [Google Scholar] [CrossRef] [PubMed]
- Chen, Y.; Hu, W. Changes in the Phosphoproteome and Metabolome Link Early Signaling Events to Rearrangement of Photosynthesis and Central Metabolism in Salinity and Oxidative Stress Response in Arabidopsis thaliana. Plant Physiol. 2015, 169, 1686–1704. [Google Scholar] [CrossRef]
- Monfort-Lanzas, P.; Rungger, K.; Madersbacher, L.; Hackl, H. Machine Learning to Dissect Perturbations in Complex Cellular Systems. Comput. Struct. Biotechnol. J. 2025, 27, 832–842. [Google Scholar] [CrossRef]
- Cembrowska-Lech, D.; Krzemińska, A.; Miller, T.; Nowakowska, A.; Adamski, C.; Radaczyńska, M.; Mikiciuk, G.; Mikiciuk, M. An Integrated Multi-Omics and Artificial Intelligence Framework for Advance Plant Phenotyping in Horticulture. Biology 2023, 12, 1298. [Google Scholar] [CrossRef]
- Zhang, N.; Tang, L.; Li, S.; Liu, Y.; Gao, M.; Wang, S.; Chen, D.; Zhao, Y.; Zheng, R.; Soleymaniniya, A.; et al. Integration of Multi-Omics Data Accelerates Molecular Analysis of Common Wheat Traits. Nat. Commun. 2025, 16, 2200. [Google Scholar] [CrossRef]
- Zhang, Y.; Fan, W.; Kinkema, M.; Li, X.; Dong, X. Interaction of NPR1 with Basic Leucine Zipper Protein Transcription Factors That Bind Sequences Required for Salicylic Acid Induction of the PR-1 Gene. Proc. Natl. Acad. Sci. USA 1999, 96, 6523–6528. [Google Scholar] [CrossRef]
- Dixit, S.; Kumar, A.; Srinivasan, K.; Vincent, P.M.D.R.; Krishnan, N.R. Advancing Genome Editing with Artificial Intelligence: Opportunities, Challenges, and Future Directions. Front. Bioeng. Biotechnol. 2024, 11, 1335901. [Google Scholar] [CrossRef]
- Hesami, M.; Alizadeh, M.; Jones, A.M.P.; Torkamaneh, D. Machine Learning: Its Challenges and Opportunities in Plant System Biology. Appl. Microbiol. Biotechnol. 2022, 106, 3507–3530. [Google Scholar] [CrossRef]
- Jaganathan, D.; Ramasamy, K.; Sellamuthu, G.; Jayabalan, S.; Venkataraman, G. CRISPR for Crop Improvement: An Update Review. Front. Plant Sci. 2018, 9, 985. [Google Scholar] [CrossRef] [PubMed]
- Yadav, R.K.; Tripathi, M.K.; Tiwari, S.; Tripathi, N.; Asati, R.; Chauhan, S.; Tiwari, P.N.; Payasi, D.K. Genome Editing and Improvement of Abiotic Stress Tolerance in Crop Plants. Life 2023, 13, 1456. [Google Scholar] [CrossRef] [PubMed]
- Zhang, Z.; Qu, Y.; Ma, F.; Lv, Q.; Zhu, X.; Guo, G.; Li, M.; Yang, W.; Que, B.; Zhang, Y.; et al. Integrating High-Throughput Phenotyping and Genome-Wide Association Studies for Enhanced Drought Resistance and Yield Prediction in Wheat. New Phytol. 2024, 243, 1758–1775. [Google Scholar] [CrossRef]
- Zaghum, M.J.; Ali, K.; Teng, S. Integrated Genetic and Omics Approaches for the Regulation of Nutritional Activities in Rice (Oryza sativa L.). Agriculture 2022, 12, 1757. [Google Scholar] [CrossRef]
- Kong, C.; Yang, Y.; Zhang, S. Predictive genetic circuit design for phenotype reprogramming in plants. Nat. Commun. 2025, 16, 1234. [Google Scholar] [CrossRef]
- Khakhar, A.; Leydon, A.R.; Lemmex, A.C.; Klavins, E.; Nemhauser, J.L. Synthetic Hormone-Responsive Transcription Factors Can Monitor and Re-Program Plant Development. eLife 2018, 7, e34702. [Google Scholar] [CrossRef]
- Singh, S.; Koyama, H.; Bhati, K.K.; Alok, A. The Biotechnological Importance of the Plant-Specific NAC Transcription Factor Family in Crop Improvement. J. Plant Res. 2021, 134, 475–495. [Google Scholar] [CrossRef] [PubMed]
- Kan, Y.; He, Z.; Keyhani, N.O.; Li, N.; Huang, S.; Zhao, X.; Liu, P.; Zeng, F.; Li, M.; Luo, Z.; et al. A Network of Transcription Factors in Complex with a Regulating Cell Cycle Cyclin Orchestrates Fungal Oxidative Stress Responses. BMC Biol. 2024, 22, 81. [Google Scholar] [CrossRef] [PubMed]
- Wachter, A.; Tunc-Ozdemir, M.; Grove, B.C.; Green, P.J.; Shintani, D.K.; Breaker, R.R. Riboswitch Control of Gene Expression in Plants by Splicing and Alternative 3′ End Processing of mRNAs. Plant Cell 2007, 19, 3437–3450. [Google Scholar] [CrossRef]
- Bocobza, S.E.; Aharoni, A. Switching the Light on Plant Riboswitches. Trends Plant Sci. 2008, 13, 526–533. [Google Scholar] [CrossRef]
- Bocobza, S.; Adato, A.; Mandel, T.; Shapira, M.; Nudler, E.; Aharoni, A. Riboswitch-Dependent Gene Regulation and Its Evolution in the Plant Kingdom. Genes Dev. 2007, 21, 2874–2879. [Google Scholar] [CrossRef]
- Andres, J.; Blomeier, T.; Zurbriggen, M.D. Synthetic Switches and Regulatory Circuits in Plants. Plant Physiol. 2019, 179, 862–884. [Google Scholar] [CrossRef]
- Ding, X.; Yin, Z.; Wang, S.; Liu, H.; Chu, X.; Liu, J.; Zhao, H.; Wang, X.; Li, Y.; Ding, X. Different Fruit-Specific Promoters Drive AtMYB12 Expression to Improve Phenylpropanoid Accumulation in Tomato. Molecules 2022, 27, 317. [Google Scholar] [CrossRef]
- Kar, S.; Bordiya, Y.; Rodriguez, N.; Kim, J.; Sung, S.; Gardner, E.C.; Gollihar, J.; Ellington, A.D. Orthogonal Control of Gene Expression in Plants Using Synthetic Promoters and CRISPR-Based Transcription Factors. Plant Methods 2022, 18, 42. [Google Scholar] [CrossRef]
- McCarty, N.S.; Graham, A.E.; Studená, L.; Ledesma-Amaro, R. Multiplexed CRISPR Technologies for Gene Editing and Transcriptional Regulation. Nat. Commun. 2020, 11, 1281. [Google Scholar] [CrossRef]
- Paleologo, M.; Lanubile, A.; Camardo Leggieri, M.; Graffigna, G.; Gomarasca, P.; Barello, S. Public Perception of New Plant Breeding Techniques and the Psychosocial Determinants of Acceptance: A Systematic Review. Public Underst. Sci. 2024, 33, 795–812. [Google Scholar] [CrossRef] [PubMed]
- Kormos, A.; Lanzaro, G.C.; Bier, E.; Santos, V.; Nazaré, L.; Pinto, J.; dos Santos, A.A.; James, A.A. Ethical Considerations for Gene Drive: Challenges of Balancing Inclusion, Power and Perspectives. Front. Bioeng. Biotechnol. 2022, 10, 826727. [Google Scholar] [CrossRef]
- Lämke, J.; Bäurle, I. Epigenetic and Chromatin-Based Mechanisms in Environmental Stress Adaptation and Stress Memory in Plants. Genome Biol. 2017, 18, 124. [Google Scholar] [CrossRef]
- Hauser, M.T.; Aufsatz, W.; Jonak, C.; Luschnig, C. Transgenerational Epigenetic Inheritance in Plants. Biochim. Biophys. Acta 2011, 1809, 459–468. [Google Scholar] [CrossRef]
- Iram, A.; Dong, Y.; Ignea, C. Synthetic Biology Advances towards a Bio-Based Society in the Era of Artificial Intelligence. Curr. Opin. Biotechnol. 2024, 87, 103143. [Google Scholar] [CrossRef]
- Harikrishnan, S.; Kaushik, D.; Rasane, P.; Kumar, A.; Kaur, N.; Reddy, C.K.; Kumar, M. Artificial Intelligence in Sustainable Food Design: Technological, Ethical Considerations, and Future. Trends Food Sci. Technol. 2025, 141, 105152. [Google Scholar] [CrossRef]
- Wójcik-Gront, E.; Zieniuk, B.; Pawełkowicz, M. Harnessing AI-Powered Genomic Research for Sustainable Crop Improvement. Agriculture 2024, 14, 2299. [Google Scholar] [CrossRef]
ROS | Full Name | Main Source | Abiotic Stress | Biotic Stress | Function |
---|---|---|---|---|---|
1O2 | Singlet Oxygen | Chloroplasts (PSII, chlorophyll excitation) | High light, drought, cold | Indirectly via signaling during infection | Highly reactive and signaling [8,9] |
O2−• | Superoxide Anion | Mitochondria, chloroplasts, NADPH oxidases | Cold, salinity, heavy metals | Pathogen-induced oxidative burst | ROS precursor, signaling [2,5] |
H2O2 | Hydrogen Peroxide | SOD activity, oxidases, photosystems | All abiotic stresses | Elicitor-induced signaling | Central signaling molecule [5,6,12] |
•OH | Hydroxyl Radical | Fenton reaction (Fe2+ + H2O2) | UV, heavy metals | Localized cell death (hypersensitive response) | Extremely toxic, causes damage [28] |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Cannea, F.B.; Padiglia, A. Antioxidant Defense Systems in Plants: Mechanisms, Regulation, and Biotechnological Strategies for Enhanced Oxidative Stress Tolerance. Life 2025, 15, 1293. https://doi.org/10.3390/life15081293
Cannea FB, Padiglia A. Antioxidant Defense Systems in Plants: Mechanisms, Regulation, and Biotechnological Strategies for Enhanced Oxidative Stress Tolerance. Life. 2025; 15(8):1293. https://doi.org/10.3390/life15081293
Chicago/Turabian StyleCannea, Faustina Barbara, and Alessandra Padiglia. 2025. "Antioxidant Defense Systems in Plants: Mechanisms, Regulation, and Biotechnological Strategies for Enhanced Oxidative Stress Tolerance" Life 15, no. 8: 1293. https://doi.org/10.3390/life15081293
APA StyleCannea, F. B., & Padiglia, A. (2025). Antioxidant Defense Systems in Plants: Mechanisms, Regulation, and Biotechnological Strategies for Enhanced Oxidative Stress Tolerance. Life, 15(8), 1293. https://doi.org/10.3390/life15081293