Intelligent Gene Editing in Plants analyzes how AI-enabled design and CRISPR-based genome engineering are reshaping plant genetics, with a clear functional focus on delivering durable gains in crop productivity, stress tolerance, and nutritional quality.
The work unfolds in three parts: [i] a foundational survey of genome-editing technologies and the evolving role of AI in precise trait modifications and outcome prediction; [ii] a thorough exploration of applications and synergies, including AI-assisted gRNA optimization, off-target mitigation, regulatory-network analysis, and trait enhancement for disease resistance and climate resilience; and [iii] an emerging-horizons section on cis-regulatory edits, omics integration, synthetic biology, and next-generation editing.
Throughout, the volume interweaves practical experiences, cutting-edge methodologies, and case studies, alongside discussions of biosafety, ethical concerns, governance, and public perception, providing a holistic, decision-ready resource for students, researchers, practitioners, and regulatory authorities to navigate the opportunities and responsibilities of plant gene editing, with significant implications for sustainable agriculture and global food security.
1. Part I. An introduction to gene editing technologies - p. P1 2. Chapter 1. Gene editing technologies: A comprehensive overview - p. 3 3. Chapter 2. Revolution of CRISPR–Cas: Advancements in genome editing for agriculture - p. 35 4. Chapter 3. The CRISPR–Cas toolkit for gene editing in plants - p. 55 5. Chapter 4. CRISPR cargo delivery systems for intelligent plant genome engineering - p. 91 6. Chapter 5. Evolution of CRISPR technology, progress, and its future implications for crop improvement - p. 117 7. Chapter 6. Gene editing beyond food crops - p. 139 8. Chapter 7. Convergence of gene editing and AI: The future of gene editing in plants - p. 171 9. Chapter 8. From data to discovery: The role of AI in advancing gene editing - p. 191 10. Chapter 9. Machine learning approaches in gene editing - p. 227 11. Part II. Applications and synergies of CRISPR and AI for plant gene editing - p. P2 12. Chapter 10. Practical design of gRNA: AI combined with CRISPR - p. 247 13. Chapter 11. AI for accurate prediction of on-target efficiency and minimization of off-targets in plants - p. 261 14. Chapter 12. AI for improved prediction of CRISPR repair outcomes - p. 291 15. Chapter 13. AI and CRISPR: Studying gene functions and regulatory networks in plants - p. 317 16. Chapter 14. AI-driven gene editing for disease resistance in plants - p. 341 17. Chapter 15. Artificial intelligence tools for predicting off-targets in plant genome editing - p. 361 18. Chapter 16. AI and multiplex gene editing: The future of gene editing in plants - p. 377 19. Chapter 17. Artificial intelligence and CRISPR technologies for enhancing food security - p. 401 20. Chapter 18. Intelligent gene editing for stress tolerance in plants - p. 429 21. Chapter 19. AI-guided CRISPR in crop yield enhancement - p. 451 22. Chapter 20. AI-assisted regulation of gene-edited plants: Opportunities and challenges - p. 487 23. Chapter 21. AI and CRISPR: Biosafety, governance, and public perception of gene-edited organisms - p. 523 24. Chapter 22. CRISPR meets AI: New frontiers in developing insect-resistant crops - p. 541 25. Part III. Emerging horizons of CRISPR - p. P3 26. Chapter 23. Editing cis-regulatory elements to enhance desired traits in plants - p. 563 27. Chapter 24. AI integration with omics and CRISPR to decipher complex traits in plants - p. 591 28. Chapter 25. AI and next-generation gene editing tools - p. 627 29. Chapter 26. Future landscape of CRISPR and AI in plant gene editing - p. 657 30. Index - p. 693
Intelligent Gene Editing in Plants analyzes how AI-enabled design and CRISPR-based genome engineering are reshaping plant genetics, with a clear functional focus on delivering durable gains in crop productivity, stress tolerance, and nutritional quality.
The work unfolds in three parts: [i] a foundational survey of genome-editing technologies and the evolving role of AI in precise trait modifications and outcome prediction; [ii] a thorough exploration of applications and synergies, including AI-assisted gRNA optimization, off-target mitigation, regulatory-network analysis, and trait enhancement for disease resistance and climate resilience; and [iii] an emerging-horizons section on cis-regulatory edits, omics integration, synthetic biology, and next-generation editing.
Throughout, the volume interweaves practical experiences, cutting-edge methodologies, and case studies, alongside discussions of biosafety, ethical concerns, governance, and public perception, providing a holistic, decision-ready resource for students, researchers, practitioners, and regulatory authorities to navigate the opportunities and responsibilities of plant gene editing, with significant implications for sustainable agriculture and global food security.
1. Part I. An introduction to gene editing technologies - p. P1 2. Chapter 1. Gene editing technologies: A comprehensive overview - p. 3 3. Chapter 2. Revolution of CRISPR–Cas: Advancements in genome editing for agriculture - p. 35 4. Chapter 3. The CRISPR–Cas toolkit for gene editing in plants - p. 55 5. Chapter 4. CRISPR cargo delivery systems for intelligent plant genome engineering - p. 91 6. Chapter 5. Evolution of CRISPR technology, progress, and its future implications for crop improvement - p. 117 7. Chapter 6. Gene editing beyond food crops - p. 139 8. Chapter 7. Convergence of gene editing and AI: The future of gene editing in plants - p. 171 9. Chapter 8. From data to discovery: The role of AI in advancing gene editing - p. 191 10. Chapter 9. Machine learning approaches in gene editing - p. 227 11. Part II. Applications and synergies of CRISPR and AI for plant gene editing - p. P2 12. Chapter 10. Practical design of gRNA: AI combined with CRISPR - p. 247 13. Chapter 11. AI for accurate prediction of on-target efficiency and minimization of off-targets in plants - p. 261 14. Chapter 12. AI for improved prediction of CRISPR repair outcomes - p. 291 15. Chapter 13. AI and CRISPR: Studying gene functions and regulatory networks in plants - p. 317 16. Chapter 14. AI-driven gene editing for disease resistance in plants - p. 341 17. Chapter 15. Artificial intelligence tools for predicting off-targets in plant genome editing - p. 361 18. Chapter 16. AI and multiplex gene editing: The future of gene editing in plants - p. 377 19. Chapter 17. Artificial intelligence and CRISPR technologies for enhancing food security - p. 401 20. Chapter 18. Intelligent gene editing for stress tolerance in plants - p. 429 21. Chapter 19. AI-guided CRISPR in crop yield enhancement - p. 451 22. Chapter 20. AI-assisted regulation of gene-edited plants: Opportunities and challenges - p. 487 23. Chapter 21. AI and CRISPR: Biosafety, governance, and public perception of gene-edited organisms - p. 523 24. Chapter 22. CRISPR meets AI: New frontiers in developing insect-resistant crops - p. 541 25. Part III. Emerging horizons of CRISPR - p. P3 26. Chapter 23. Editing cis-regulatory elements to enhance desired traits in plants - p. 563 27. Chapter 24. AI integration with omics and CRISPR to decipher complex traits in plants - p. 591 28. Chapter 25. AI and next-generation gene editing tools - p. 627 29. Chapter 26. Future landscape of CRISPR and AI in plant gene editing - p. 657 30. Index - p. 693
