BACKGROUND
Scientists frequently use genetically modified animals in basic and applied research. They often combine multiple genetic modifications requiring complex breeding schemes. Some of the surplus animals that do not carry the required traits cannot be used for research or further breeding and are usually euthanized. Such supernumerary animals cannot be entirely prevented, but their numbers must be kept to the minimum possible. Therefore, we aim to optimise breeding strategies for complex genetic models, which is not possible manually. There is currently no software on the market to support us to better plan our breeding strategies.
AIMS
We aim to develop a stand-alone software tool, which will allow researchers to identify the best breeding strategies and thereby reduce the number of surplus animals. This is especially important when multiple traits are combined and the Mendelian laws lead to birth of surplus animals. The application of the software will reduce surplus animals to the essential minimum.
OUTPUT
Cohort breeding planner
Breeding genetically modified animals is time consuming, costly, and influenced by random stochastic events related to Mendelian genetics, fertility, and litter size. Careful planning is essential to achieve successful results with the smallest number of animals possible while adhering to the 3Rs principles of animal welfare. We have developed an R package, which is also available through an interactive, publicly accessible website. It optimizes breeding planning, taking into account specific breeding traits and probabilities of success, and provides information on the optimal number of breedings required to achieve specific breeding outcomes.
Our software also enables the appropriate design of experiments with an equal number of females and females or only unisexual experiments. We show that single-sex designs result in more than doubling the required number of pups born. While the tool provides preset parameters for the laboratory mouse, it can also be used for any other diploid species.
