Department of Mathematics, Texas A&M University, College Station, Texas.
Department of Biology, Texas A&M University, College Station, Texas.
J Evol Biol. 2019 Apr;32(4):369-379. doi: 10.1111/jeb.13421. Epub 2019 Feb 21.
Genetic architecture fundamentally affects the way that traits evolve. However, the mapping of genotype to phenotype includes complex interactions with the environment or even the sex of an organism that can modulate the expressed phenotype. Line-cross analysis is a powerful quantitative genetics method to infer genetic architecture by analysing the mean phenotype value of two diverged strains and a series of subsequent crosses and backcrosses. However, it has been difficult to account for complex interactions with the environment or sex within this framework. We have developed extensions to line-cross analysis that allow for gene by environment and gene by sex interactions. Using extensive simulation studies and reanalysis of empirical data, we show that our approach can account for both unintended environmental variation when crosses cannot be reared in a common garden and can be used to test for the presence of gene by environment or gene by sex interactions. In analyses that fail to account for environmental variation between crosses, we find that line-cross analysis has low power and high false-positive rates. However, we illustrate that accounting for environmental variation allows for the inference of adaptive divergence, and that accounting for sex differences in phenotypes allows practitioners to infer the genetic architecture of sexual dimorphism.
遗传结构从根本上影响了特征的进化方式。然而，基因型到表型的映射包含与环境的复杂相互作用，甚至生物体的性别也可以调节表现型。线交叉分析是一种强大的数量遗传学方法，通过分析两种分化菌株的平均表型值以及一系列后续的杂交和回交，推断遗传结构。然而，在这个框架内很难解释与环境或性别之间的复杂相互作用。我们对线交叉分析进行了扩展，使其能够考虑基因与环境以及基因与性别的相互作用。通过广泛的模拟研究和对经验数据的重新分析，我们表明我们的方法可以解释杂交不能在共同花园中饲养时出现的意外环境变化，并且可以用于测试基因与环境或基因与性别的相互作用的存在。在未能解释杂交之间环境变化的分析中，我们发现线交叉分析的功效较低，假阳性率较高。然而，我们说明，考虑环境变化可以推断适应性分歧，并且考虑表型的性别差异可以使从业者推断性二态性的遗传结构。
