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Related Experiment Video

Updated: Jul 15, 2026

Breeding by Design for Functional Rice with Genome Editing Technologies

Breeding by Design for Functional Rice with Genome Editing Technologies

Published on: January 3, 2025

Click Breeding: Toward programmable crop design.

Binbin Dai¹, Yifu Tian², Jingyi Chai³

¹Yazhouwan National Laboratory, Sanya, China; University of Science and Technology of China, Hefei, China.

Trends in Plant Science

|July 13, 2026

Summary

Click Breeding offers a new paradigm for crop development by focusing on designing and testing entire breeding programs. This approach enhances predictive accuracy for complex traits by integrating genetics, physiology, and environmental data.

Keywords:

breeding program design complex traits constrained multi-objective optimization digital twins governance-by-design

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Last Updated: Jul 15, 2026

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Area of Science:

Plant breeding
Genetics
Computational biology

Background:

Breeding for complex traits faces challenges with predictive accuracy and transferability.
Nonadditive genetic effects and genotype-by-environment interactions significantly impact crop performance.

Purpose of the Study:

Introduce 'Click Breeding', a design-driven paradigm for crop development.
Shift focus from individual candidate ranking to comprehensive breeding program design and testing.

Main Methods:

Encoding breeding objectives and constraints into machine-readable plans.
Evaluating candidate strategies through simulations integrating genetics, physiology, and environment.
Developing traceable experimental workflows with governance checkpoints.

Main Results:

Click Breeding connects genomic prediction, crop modeling, and laboratory automation.
Establishes a coherent, auditable design cycle complementing breeder expertise.
Identifies key challenges for operationalizing programmable crop design.

Conclusions:

Click Breeding provides a novel framework for improving crop breeding efficiency and success.
Addresses limitations in current breeding strategies for complex traits.
Highlights the need for advancements in biological, computational, and regulatory aspects to realize programmable crop design.