Data from: Keeping pace with the Red Queen: identifying the genetic basis of susceptibility to infectious disease

<b>Abstract</b><br/>Genome-wide association studies are widely used to identify "disease genes" conferring resistance/susceptibility to infectious diseases. Using a combination of mathematical models and simulations we demonstrate that genetic interactions between hosts and parasites (GxG interactions) can drastically affect the results of these association scans and hamper our ability to detect genetic variation in susceptibility. When hosts and parasites coevolve, these GxG interactions often make Genome-wide association studies unrepeatable over time or across host populations. Reanalyzing previously published data on Daphnia magna susceptibility to infection by Pastueria ramosa, we identify genomic regions consistent with GxG interactions. We conclude by outlining possible avenues for designing more powerful and more repeatable association studies.

<b>摘要</b><br/>全基因组关联研究（Genome-wide association studies）被广泛用于识别赋予传染病抗性或易感性的“疾病基因”。本研究结合数学模型与模拟实验证实，宿主与寄生虫间的遗传互作（GxG interactions）会显著干扰此类关联扫描的结果，并阻碍我们检测易感性相关遗传变异的能力。当宿主与寄生虫协同进化时，此类GxG互作往往会导致全基因组关联研究的结果无法在时间维度或不同宿主种群间重复。我们重新分析了已发表的大型溞（Daphnia magna）感染分枝巴斯德菌（Pasteuria ramosa）的易感性相关数据，鉴定出了与GxG互作相符的基因组区域。最后，我们概述了设计更高效、更具可重复性的关联研究的可行路径。