A combination of walk-back and optimum contribution selection in fish: a simulation study

Area of Science:

• Animal Breeding and Genetics
• Aquaculture
• Quantitative Genetics

Background:

• Efficient fish breeding schemes are crucial for genetic improvement in aquaculture.
• Traditional selection methods can be costly due to extensive genotyping requirements.
• Optimizing selection strategies balances genetic gain with resource management.

Purpose of the Study:

• To evaluate a novel fish breeding scheme integrating walk-back and optimum contribution selection.
• To assess the performance and cost-effectiveness of using batched genotyping versus full genotyping.
• To determine the impact of batch size on genetic gain and breeding value accuracy.

Main Methods:

• Stochastic simulation of a fish breeding program.
• Implementation of walk-back selection with varying batch sizes (50 to 10,000).
• Calculation of Best Linear Unbiased Prediction (BLUP) estimated breeding values (EBVs).
• Application of optimum contribution selection with inbreeding rate constraints (DeltaF = 0.005 or 0.01).

Main Results:

• Batched genotyping significantly reduces costs compared to genotyping all candidates.
• A batch size of 100 fish achieved 76-92% of the genetic level obtained with full genotyping.
• Accuracy of breeding values was comparable across batch sizes (~0.30) but higher with full genotyping (~0.5).
• Two batches of 50 fish were often sufficient, balancing cost and genetic gain.

Conclusions:

• The combined walk-back and optimum contribution selection scheme is effective for fish breeding.
• Batched genotyping offers a cost-saving strategy without compromising substantial genetic gains.
• Careful selection of batch size is key to optimizing resource allocation and maximizing genetic improvement in aquaculture.