Optimization Strategies to Adapt Sheep Breeding Programs to Pasture-Based Production Environments: A Simulation...

Area of Science:

• Animal Breeding and Genetics
• Quantitative Genetics
• Sheep Production Systems

Background:

• Genotype-by-environment interactions (G × E) can reduce genetic gain when selection and production environments differ.
• Adapting sheep breeding programs to pasture-based systems is essential for sustainable production.
• Current breeding programs may not fully account for pasture production realities.

Purpose of the Study:

• To simulate and evaluate different progeny testing scenarios for German Merino sheep.
• To optimize sheep breeding programs for pasture-based production environments.
• To investigate strategies for maximizing genetic gain under genotype-by-environment interactions.

Main Methods:

• Simulation of German Merino sheep breeding scenarios using the Modular Breeding Program Simulator (MoBPS) R package.
• Multivariate pedigree-based Best Linear Unbiased Prediction (BLUP) for breeding value estimation.
• Comparison of reference (station progeny testing) with alternative scenarios (station and/or field progeny testing).

Main Results:

• The total merit index (TMI) showed a significant increase in genetic gain when progeny testing occurred in both field and station settings.
• Genetic gain for fattening traits was substantially enhanced in scenarios incorporating field progeny testing.
• Selection environments that align with production environments (pasture) mitigate genetic gain losses due to G × E.

Conclusions:

• Aligning selection and production environments is vital to avoid genetic gain losses caused by genotype-by-environment interactions.
• Combining field and station progeny testing maximizes genetic gain, especially when breeding goals include traits not recordable in the field.
• Optimized progeny testing strategies are key to adapting sheep breeding programs for pasture-based production.