A unifying concept of animal breeding programmes.

Area of Science:

• Animal Breeding and Genetics
• Computational Biology
• Bioinformatics

Background:

• Modern animal breeding programs lack a unified definition and descriptive language.
• Existing methods struggle to encompass diverse breeding strategies like transgenics or diversity maintenance.
• Formal, standardized descriptions are increasingly required, e.g., by EU regulations.

Purpose of the Study:

• To propose a general, succinct definition for breeding programs.
• To develop a unified, unambiguous, and reproducible language for describing breeding programs.
• To create a formal framework applicable to diverse breeding goals and technologies.

Main Methods:

• Representing breeding programs as directed graphs with nodes (breeding units) and edges (breeding activities).
• Defining a comprehensive set of nodes and edges to capture arbitrary program complexity.
• Implementing the concept in a web-based tool (MoBPSweb) and an R-package (MoBPS) for simulation.

Main Results:

• A modular, graph-based conceptual framework for defining breeding programs.
• Successful implementation in MoBPSweb and MoBPS for description and simulation.
• Demonstration of the approach with three breeding programs of increasing complexity.

Conclusions:

• The proposed graph-based concept provides a formal and standardized method for describing breeding programs.
• This framework accommodates various breeding goals (genetic gain, diversity) and technologies (selection, transgenics).
• The approach is extensible to crops, experimental species, and natural population dynamics.