MoBPS-GC

MoBPS-GC simulates horse breeding programs to model complex breeding schemes and evaluate selection strategies that integrate health traits such as Osteochondrosis dissecans (OCD) for genetic management and decision support.

Key Features:

• Implementation: Implemented in R using the MoBPS package for population and breeding program simulation.
• Realistic simulation: Simulates realistic age structures and selection steps to mirror real-world breeding environments.
• Complex breeding-scheme modeling: Models complex breeding schemes reflecting real-world scenarios, including German Warmblood horses.
• Health trait integration: Integrates health traits such as Osteochondrosis dissecans (OCD) into selection and breeding value calculations.
• Selection strategy analysis: Compares threshold selection, index selection, and genomic index selection to assess effects on health and performance traits.
• Scenario evaluation: Evaluates scenarios to quantify trade-offs between reducing OCD prevalence and maintaining or improving performance, including assessing inclusion of OCD in breeding values at stages such as stallion licensing.

Scientific Applications:

• Sustainable breeding strategy development: Supports development of breeding strategies that balance health (e.g., OCD) and performance objectives.
• Evidence-based decision support: Provides quantitative comparisons of selection strategies for researchers and breeders, particularly in German Warmblood horses, to reduce OCD prevalence without compromising riding-horse quality.
• Welfare and economic assessment: Enables assessment of the welfare and economic impacts of selection strategies in equine breeding programs.

Methodology:

Implemented in R using the MoBPS package; employs a detailed simulation framework with realistic age structures and selection steps, incorporates health trait data such as Osteochondrosis dissecans (OCD) into breeding values and selection, and performs comparative analyses of threshold selection, index selection, and genomic index selection across scenarios.