Jensen Jeffrey D, Thornton Kevin R, Bustamante Carlos D, Aquadro Charles F
Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14853, USA.
Genetics. 2007 Aug;176(4):2371-9. doi: 10.1534/genetics.106.069450. Epub 2007 Jun 11.
A critically important challenge in empirical population genetics is distinguishing neutral nonequilibrium processes from selective forces that produce similar patterns of variation. We here examine the extent to which linkage disequilibrium (i.e., nonrandom associations between markers) improves this discrimination. We show that patterns of linkage disequilibrium recently proposed to be unique to hitchhiking models are replicated under nonequilibrium neutral models. We also demonstrate that jointly considering spatial patterns of association among variants alongside the site-frequency spectrum is nonetheless of value. Through a comparison of models of equilibrium neutrality, nonequilibrium neutrality, equilibrium hitchhiking, nonequilibrium hitchhiking, and recurrent hitchhiking, we evaluate a linkage disequilibrium (LD) statistic (omega(max)) that appears to have power to identify regions recently shaped by positive selection. Most notably, for demographic parameters relevant to non-African populations of Drosophila melanogaster, we demonstrate that selected loci are distinguishable from neutral loci using this statistic.
实证群体遗传学中一个极其重要的挑战是区分中性非平衡过程与产生相似变异模式的选择力。我们在此研究连锁不平衡（即标记之间的非随机关联）在多大程度上改善了这种区分。我们表明，最近提出的搭便车模型所特有的连锁不平衡模式在非平衡中性模型下也会出现。我们还证明，同时考虑变异之间的空间关联模式以及位点频率谱仍然是有价值的。通过比较平衡中性、非平衡中性、平衡搭便车、非平衡搭便车和反复搭便车模型，我们评估了一个连锁不平衡（LD）统计量（omega(max)），它似乎有能力识别最近受到正选择影响的区域。最值得注意的是，对于与黑腹果蝇非非洲种群相关的人口统计学参数，我们证明使用这个统计量可以将选择位点与中性位点区分开来。
