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Synergizing Genome Editing and Artificial Intelligence for Predictive Crop Design.

Gao Z, Zhu J, Xie C

Crispr

PubMed

The tomatoes, wheat, and corn you eat could soon be engineered to survive droughts, pack more nutrients, and resist pests — not through decades of slow breeding, but through AI-guided genetic design that works like a GPS for crop improvement.

Researchers propose pairing two powerful technologies — gene editing (which lets scientists make precise changes to a plant's DNA) and artificial intelligence — to design better crops faster. Instead of guessing which changes might help a plant survive heat or drought, AI can predict the best edits to make, and then gene editing tests those predictions in real plants. This back-and-forth loop could speed up the creation of crops that are more nutritious, climate-resilient, and efficient to grow.

Key Findings

1

AI can improve the accuracy of gene editing by better predicting guide RNA design and reducing unintended off-target DNA changes.

2

Gene editing in turn generates high-resolution experimental datasets that feed back into AI models, creating an iterative improvement cycle.

3

The combined approach is being applied to complex traits including climate resilience, stress tolerance, nutritional enhancement, and de novo domestication of wild plants into new crops.

chevron_right Technical Summary

Scientists are combining AI and gene editing tools to design better crops more precisely — moving from trial-and-error breeding toward predicting which genetic changes will produce desired traits before making them.

description

Abstract Preview

The convergence of genome editing (GE) and artificial intelligence (AI) is shifting crop improvement from empirical optimization toward predictive design. In this Perspective, we propose that GE an...

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Abstract copyright held by the original publisher.

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