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MoBPS - Modular Breeding Program Simulator.

Torsten Pook1,2, Martin Schlather2,3, Henner Simianer4,2

  • 1Department of Animal Sciences, Animal Breeding and Genetics Group, University of Goettingen, 37075 Goettingen, Germany torsten.pook@uni-goettingen.de.

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|April 2, 2020
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Summary
This summary is machine-generated.

The MoBPS R-package offers an efficient framework for simulating complex breeding programs, evaluating their economic and genetic effects. It handles large populations using advanced data storage and computation, enabling detailed modeling of modern breeding strategies.

Keywords:
R-package simulation breeding breeding program resource management population genetics

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Area of Science:

  • Animal Breeding and Genetics
  • Computational Biology
  • Bioinformatics

Background:

  • Complex breeding programs require sophisticated simulation tools to assess genetic and economic impacts.
  • Existing frameworks may lack the efficiency or flexibility needed for large-scale, modern breeding scenarios.

Purpose of the Study:

  • To introduce the R-package MoBPS as a computationally efficient and flexible framework for simulating complex breeding programs.
  • To enable comparison of economic and genetic impacts of various breeding strategies.

Main Methods:

  • Simulations based on individual-level data.
  • Utilizes bit-wise data storage and matrix multiplications via the R-package miraculix for high performance.
  • Haplotypes are dynamically derived, avoiding storage of large haplotype data.

Main Results:

  • MoBPS can handle large-scale populations efficiently.
  • The modular structure allows integration of coarse founder population simulations with detailed breeding program modeling.
  • Supports common breeding practices like optimum genetic contributions and single-step GBLUP, with user customization options.

Conclusions:

  • MoBPS provides a powerful and adaptable tool for researchers and breeders.
  • Facilitates advanced simulation and analysis of complex breeding programs, aiding in strategic decision-making.