COMPARING EVOLVABILITIES: COMMON ERRORS SURROUNDING THE CALCULATION AND USE OF COEFFICIENTS OF ADDITIVE GENETIC VARIATION
COMPARING EVOLVABILITIES: COMMON ERRORS SURROUNDING THE CALCULATION AND USE OF COEFFICIENTS OF ADDITIVE GENETIC VARIATION
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DOI：
10.1111/j.1558-5646.2011.01565.x
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发表时间：
2012-08-01
期刊：
影响因子：
3.3
通讯作者：
Evans, Jonathan P.
中科院分区：
文献类型：
--
作者：
Garcia-Gonzalez, Francisco;Simmons, Leigh W.;Evans, Jonathan P.
1992年，David Houle证明了用性状平均值CVA(加性遗传变异系数)及其平方(IA)标准化的加性遗传变异度量是合适的进化性度量。CVA已被广泛用于比较遗传变异的模式。然而，为了比较的目的而使用CVA，关键取决于对这一参数的正确计算。我们回顾了一组数量遗传学研究的样本，重点放在父系模型上，发现45%的研究使用了不正确的方法来计算CVA，并且经常出现使这些系数变得毫无意义的做法。这可能会对比较研究得出的结论产生重要影响。我们的结果暗示了一个更广泛的问题，因为在抽样的研究中，对SIRE模型的加性遗传方差的错误计算很普遍，这意味着其他重要的数量遗传参数也可能经常被错误估计。我们讨论了影响CVA和IA使用的最突出的问题，包括规模效应，数据转换，以及不同维度的特征比较。我们的目标是提高人们对围绕进化性计算和使用的潜在错误的认识，并为未来研究中计算、报告和解释这些有用的度量编制一般指南。
In 1992, David Houle showed that measures of additive genetic variation standardized by the trait mean, CVA (the coefficient of additive genetic variation) and its square (IA), are suitable measures of evolvability. CVA has been used widely to compare patterns of genetic variation. However, the use of CVAs for comparative purposes relies critically on the correct calculation of this parameter. We reviewed a sample of quantitative genetic studies, focusing on sire models, and found that 45% of studies use incorrect methods for calculating CVA and that practices that render these coefficients meaningless are frequent. This may have important consequences for conclusions drawn from comparative studies. Our results are suggestive of a broader problem because miscalculation of the additive genetic variance from a sire model is prevalent among the studies sampled, implying that other important quantitative genetic parameters might also often be estimated incorrectly. We discuss the most prominent issues affecting the use of CVA and IA, including scale effects, data transformation, and the comparison of traits with different dimensions. Our aim is to increase awareness of the potential mistakes surrounding the calculation and use of evolvabilities, and to compile general guidelines for calculating, reporting, and interpreting these useful measures in future studies.