MoBPS

MoBPS simulates complex breeding programs at the individual and haplotype level to assess genetic and economic consequences of breeding strategies.

Key Features:

• Efficient Simulation Framework: Performs computationally efficient large-scale population simulations by storing only founder haplotypes, recombination points, and mutations and calculating haplotypes dynamically.
• Bit-wise Data Storage: Uses bit-wise storage techniques to minimize memory footprint for extensive genotype and haplotype data.
• Matrix Multiplications: Executes matrix multiplications via the R-package miraculix to accelerate linear algebra operations on genetic data.
• Modular Structure: Implements a modular design allowing combination of coarse founder-population simulations with detailed contemporary breeding program modeling and integration of biotechnologies.
• Pre-implemented Functions: Includes methods such as optimum genetic contributions and single-step Genomic Best Linear Unbiased Prediction (GBLUP) for common breeding analyses.
• Customization Options: Permits replacement of simulation steps with user-written procedures to enable tailored computational workflows.

Scientific Applications:

• Agricultural and Genetic Research: Evaluating genetic and economic impacts of different breeding strategies across generations in livestock and crop programs.
• Breeding Program Optimization: Optimizing selection schemes and mating designs to increase desirable traits while controlling costs.
• Biotechnology Assessment: Assessing the incorporation and impact of modern biotechnologies within breeding schemes.
• Method Benchmarking: Benchmarking genomic evaluation and selection algorithms such as single-step GBLUP and optimum genetic contributions.

Methodology:

Computations rely on dynamic haplotype reconstruction from stored founder haplotypes, recombination points, and mutations, bit-wise data storage to reduce memory, and matrix operations using the R-package miraculix; pre-implemented algorithms include single-step GBLUP and optimum genetic contributions.