Department of Evolutionary Biology and Environmental Studies, University of Zürich, Winterthurerstrasse 190, 8057 Zürich, Switzerland.
Department of Biostatistics, Epidemiology, Biostatistics and Prevention Institute, University of Zürich, Hirschengraben 84, 8001 Zürich, Switzerland.
Evolution. 2018 Oct;72(10):1992-2004. doi: 10.1111/evo.13573. Epub 2018 Aug 29.
Quantitative genetic analyses require extensive measurements of phenotypic traits, a task that is often not trivial, especially in wild populations. On top of instrumental measurement error, some traits may undergo transient (i.e., nonpersistent) fluctuations that are biologically irrelevant for selection processes. These two sources of variability, which we denote here as measurement error in a broad sense, are possible causes for bias in the estimation of quantitative genetic parameters. We illustrate how in a continuous trait transient effects with a classical measurement error structure may bias estimates of heritability, selection gradients, and the predicted response to selection. We propose strategies to obtain unbiased estimates with the help of repeated measurements taken at an appropriate temporal scale. However, the fact that in quantitative genetic analyses repeated measurements are also used to isolate permanent environmental instead of transient effects requires that the information content of repeated measurements is carefully assessed. To this end, we propose to distinguish "short-term" from "long-term" repeats, where the former capture transient variability and the latter help isolate permanent effects. We show how the inclusion of the corresponding variance components in quantitative genetic models yields unbiased estimates of all quantities of interest, and we illustrate the application of the method to data from a Swiss snow vole population.
定量遗传学分析需要对表型特征进行广泛的测量，这一任务通常并不简单，尤其是在野生种群中。除了仪器测量误差之外，某些特征可能会经历短暂（即非持久）的波动，而这些波动对选择过程没有生物学意义。这两种来源的可变性，我们在这里广义地称为测量误差，可能是定量遗传参数估计中出现偏差的原因。我们通过具有经典测量误差结构的连续特征的瞬态效应来说明这种偏差是如何产生的，这种偏差可能会影响遗传力、选择梯度以及对选择的预测反应的估计。我们提出了一些策略，通过在适当的时间尺度上进行重复测量来获得无偏估计。然而，在定量遗传学分析中，重复测量也被用于分离持久的环境效应而不是瞬态效应这一事实，要求仔细评估重复测量的信息含量。为此，我们建议将“短期”和“长期”重复区分开来，前者捕捉瞬态可变性，后者有助于分离持久效应。我们展示了如何在定量遗传模型中包含相应的方差分量，从而对所有感兴趣的数量进行无偏估计，并说明了该方法在瑞士雪兔种群数据中的应用。
