Breeding and Behavior, Institute for Bee Research Hohen Neuendorf, 16540 Hohen Neuendorf, Germany.
G3 (Bethesda). 2022 Feb 4;12(2). doi: 10.1093/g3journal/jkab450.
Estimating genetic parameters of quantitative traits is a prerequisite for animal breeding. In honeybees, the genetic variance separates into queen and worker effects. However, under data paucity, parameter estimations that account for this peculiarity often yield implausible results. Consequently, simplified models that attribute all genetic contributions to either the queen (queen model) or the workers (worker model) are often used to estimate variance components in honeybees. However, the causes for estimations with the complete model (colony model) to fail and the consequences of simplified models for variance estimates are little understood. We newly developed the necessary theory to compare parameter estimates that were achieved by the colony model with those of the queen and worker models. Furthermore, we performed computer simulations to quantify the influence of model choice, estimation algorithm, true genetic parameters, rates of controlled mating, apiary sizes, and phenotype data completeness on the success of genetic parameter estimations. We found that successful estimations with the colony model were only possible if at least some of the queens mated controlled on mating stations. In that case, estimates were largely unbiased if more than 20% of the colonies had phenotype records. The simplified queen and worker models proved more stable and yielded plausible parameter estimates for almost all settings. Results obtained from these models were unbiased when mating was uncontrolled, but with controlled mating, the simplified models consistently overestimated heritabilities. This study elucidates the requirements for variance component estimation in honeybees and provides the theoretical groundwork for simplified honeybee models.
估计数量性状的遗传参数是动物育种的前提。在蜜蜂中，遗传方差分为蜂王和工蜂效应。然而，在数据匮乏的情况下，考虑到这一特殊性的参数估计往往会产生不合理的结果。因此，通常使用将所有遗传贡献归因于蜂王（蜂王模型）或工蜂（工蜂模型）的简化模型来估计蜜蜂的方差分量。然而，对于完整模型（群体模型）的估计失败的原因以及简化模型对方差估计的影响还知之甚少。我们新开发了必要的理论来比较群体模型所获得的参数估计与蜂王和工蜂模型的参数估计。此外，我们进行了计算机模拟，以量化模型选择、估计算法、真实遗传参数、受控交配率、蜂场大小和表型数据完整性对遗传参数估计成功的影响。我们发现，如果至少有一些蜂王在交配站进行了受控交配，那么群体模型的成功估计才是可能的。在这种情况下，如果超过 20%的蜂群有表型记录，那么估计值基本上是无偏的。简化的蜂王和工蜂模型被证明更稳定，并且几乎在所有情况下都能产生合理的参数估计值。当交配不受控制时，这些模型获得的结果是无偏的，但当交配受到控制时，简化模型会一直高估遗传力。本研究阐明了蜜蜂方差分量估计的要求，并为简化的蜜蜂模型提供了理论基础。
