Optimum contribution selection in large general tree breeding populations with an application to Scots pine

Area of Science:

• Plant breeding
• Quantitative genetics
• Forestry

Background:

• Optimizing selection methods to balance genetic gain and inbreeding is crucial for breeding programs.
• Optimum Contribution (OC) dynamic selection is a key method in animal breeding.

Purpose of the Study:

• To implement and evaluate the Optimum Contribution (OC) algorithm for Scots pine (Pinus sylvestris L.) breeding.
• To compare OC selection with standard restricted selection for total tree height and stem diameter.

Main Methods:

• Applied the OC algorithm to a diallel progeny trial of Scots pine.
• Focused on two traits: total tree height and stem diameter.
• Compared OC selection with standard restricted selection and unrestricted truncation selection.

Main Results:

• OC selection achieved 8-30% higher genetic gain than standard restricted selection at equivalent coancestry levels.
• OC selection was most beneficial under strict coancestry constraints.
• OC selection reduced coancestry by 56% (diameter) and 39% (height) at the same genetic merit compared to truncation selection.
• Including a dominance term altered tree contribution ranks but resulted in lower genetic gain than a pure additive model for both traits.

Conclusions:

• Optimum Contribution (OC) selection is a highly effective method for enhancing genetic gain in Scots pine breeding while controlling inbreeding.
• The benefits of OC selection are amplified under stringent coancestry restrictions.
• Additive genetic models appear more effective for maximizing genetic gain in this context compared to models including dominance.