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Uncertainty-aware breeding decisions: MCMC-based optimum contribution selection increases breeding decision
Jon Ahlinder1, Patrik Waldmann2
1Department of Tree Breeding, The Forest Research Institute of Sweden (Skogforsk), Tomterna 1, Savar, SE-91833, Sweden.
Genetics
|August 3, 2026
Summary
Optimum Contribution Selection (OCS) now incorporates uncertainty using Conditional Value at Risk (CVaR) for better genetic gain and inbreeding management. This novel approach protects against worst-case outcomes in breeding decisions.
Area of Science:
- Quantitative genetics
- Animal breeding
- Forestry genetics
Background:
- Optimum Contribution Selection (OCS) balances genetic gain and inbreeding.
- Current OCS methods use point estimates of breeding values, ignoring evaluation uncertainty.
- This uncertainty can lead to suboptimal selection decisions and reduced genetic gain.
Purpose of the Study:
- Introduce a novel OCS formulation, CVaR-OCS, that incorporates uncertainty.
- Utilize Conditional Value at Risk (CVaR) to manage risk in selection.
- Evaluate CVaR-OCS performance against existing methods and oracle solutions.
Main Methods:
- Developed CVaR-OCS by integrating the full posterior distribution of estimated breeding values (EBVs) into the OCS objective.
- Applied CVaR-OCS to a simulated genomic selection dataset (QTL-MAS 2010).
- Tested CVaR-OCS on forest tree breeding data for Norway spruce and Loblolly pine.
Main Results:
- CVaR-OCS achieved comparable expected genetic gain to oracle solutions while improving tail-gain security.
- On simulated data, MAP-OCS recovered only 78% of oracle genetic gain; CVaR-OCS improved tail-gain security by 0.69%.
- In Norway spruce, CVaR-OCS improved tail-gain security by 6.60% and broadened the selection base with minimal genetic gain cost.
Conclusions:
- CVaR-OCS offers a principled, computationally efficient method for uncertainty-aware selection.
- The approach effectively balances genetic gain and risk management in breeding programs.
- Further multi-generation simulations are recommended to assess long-term impacts on genetic gain and inbreeding.
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