Netherlands Institute of Ecology (NIOO-KNAW), Department of Terrestrial Ecology, Heteren, The Netherlands.
PLoS One. 2010 Aug 26;5(8):e12264. doi: 10.1371/journal.pone.0012264.
Identification of genetic loci in complex traits has focused largely on one-dimensional genome scans to search for associations between single markers and the phenotype. There is mounting evidence that locus interactions, or epistasis, are a crucial component of the genetic architecture of biologically relevant traits. However, epistasis is often viewed as a nuisance factor that reduces power for locus detection. Counter to expectations, recent work shows that fitting full models, instead of testing marker main effect and interaction components separately, in exhaustive multi-locus genome scans can have higher power to detect loci when epistasis is present than single-locus scans, and improvement that comes despite a much larger multiple testing alpha-adjustment in such searches. We demonstrate, both theoretically and via simulation, that the expected power to detect loci when fitting full models is often larger when these loci act epistatically than when they act additively. Additionally, we show that the power for single locus detection may be improved in cases of epistasis compared to the additive model. Our exploration of a two step model selection procedure shows that identifying the true model is difficult. However, this difficulty is certainly not exacerbated by the presence of epistasis, on the contrary, in some cases the presence of epistasis can aid in model selection. The impact of allele frequencies on both power and model selection is dramatic.
复杂性状的遗传基因座的鉴定主要集中在一维基因组扫描上，以搜索单个标记与表型之间的关联。越来越多的证据表明，基因座相互作用（上位性）是生物相关性状遗传结构的一个关键组成部分。然而，上位性通常被视为一种干扰因素，降低了基因座检测的能力。与预期相反，最近的研究表明，在详尽的多基因座基因组扫描中，拟合完整模型而不是分别测试标记主效应和相互作用分量，可以在存在上位性时比单基因座扫描具有更高的检测基因座的能力，这种改进是在这种搜索中进行更大的多重测试α调整的情况下实现的。我们从理论上和通过模拟证明，当拟合完整模型时，检测基因座的预期能力通常在这些基因座具有上位性时比具有加性作用时更大。此外，我们还表明，与加性模型相比，在存在上位性的情况下，单个基因座的检测能力可能会提高。我们对两步模型选择过程的探索表明，识别真实模型是困难的。然而，这种困难肯定不会因上位性的存在而加剧，相反，在某些情况下，上位性的存在可以帮助模型选择。等位基因频率对功率和模型选择的影响是巨大的。
