Data from: Comparison of infinitesimal and finite locus models for long-term breeding simulations with direct and maternal effects at the example of honeybees

Stochastic simulation studies of animal breeding have mostly relied on
either the infinitesimal genetic model or finite polygenic models. In this
study, we investigated the long-term effects of the chosen model on
honeybee breeding schemes. We implemented the infinitesimal model, as well
as finite locus models, with 200 and 400 gene loci and simulated
populations of 300 and 1000 colonies per year over the course of 100
years. The selection was of a directly and maternally influenced trait
with maternal heritability of h²_m = 0.42, direct heritability of h² d =
0.27, and a negative correlation between the effects of r_md = −0.18.
Another set of simulations was run with parameters h²_m = 0.53, h²_d =
0.34, and r_md = −0.53. All models showed similar behavior for the first
20 years. Throughout the study, we observed a higher genetic gain in the
direct than in the maternal effects and a smaller gain with a stronger
negative covariance. In thelong-term, however, only the infinitesimal
model predicted sustainable linear genetic progress, while the finite
locus models showed sublinear behavior and, after 100 years, only reached
between 58% and 62% of the mean breeding values in the infinitesimal
model. While the infinitesimal model suggested a reduction of genetic
variance by 33% to 49% after 100 years, the finite locus models saw a more
drastic loss of 76% to 92%. When designing sustainable breeding
strategies, one should, therefore, not blindly trust the infinitesimal
model as the predictions may be overly optimistic. Instead, the more
conservative choice of the finite locus model should be favored.