Sindi Suzanne S, Raphael Benjamin J
Division of Applied Mathematics, Brown University, Providence, Rhode Island 02912, USA.
J Comput Biol. 2010 Mar;17(3):517-31. doi: 10.1089/cmb.2009.0185.
Structural rearrangements, including copy-number alterations and inversions, are increasingly recognized as an important contributor to human genetic variation. Copy number variants are readily measured via array-based techniques like comparative genomic hybridization, but copy-neutral variants such as inversion polymorphisms remain difficult to identify without whole genome sequencing. We introduce a method to identify inversion polymorphisms and estimate their frequency in a population using readily available single nucleotide polymorphism (SNP) data. Our method uses a probabilistic model to describe a population as a mixture of forward and inverted chromosomes and identifies putative inversions by characteristic differences in haplotype frequencies around inversion breakpoints. On simulated data, our method accurately predicts inversions with frequencies as low as 25% in the population and reliably estimates inversion frequencies over a wide range. On the human HapMap Phase 2 data, we predict between 88 and 142 inversion polymorphisms with frequency ranging from 20 to 81 percent. Many of these correspond to known inversions or have other evidence supporting them, and the predicted inversion frequencies largely agree with the limited information presently available.
包括拷贝数改变和倒位在内的结构重排，日益被认为是人类遗传变异的一个重要因素。拷贝数变异可通过基于阵列的技术（如比较基因组杂交）轻松测量，但诸如倒位多态性等拷贝中性变异，在没有全基因组测序的情况下仍难以识别。我们引入了一种方法，利用现成的单核苷酸多态性（SNP）数据来识别倒位多态性并估计其在群体中的频率。我们的方法使用概率模型将群体描述为正向和反向染色体的混合体，并通过倒位断点周围单倍型频率的特征差异来识别假定的倒位。在模拟数据上，我们的方法能够准确预测群体中频率低至25%的倒位，并在很宽的范围内可靠地估计倒位频率。在人类HapMap二期数据上，我们预测出88至142个倒位多态性，频率范围为20%至81%。其中许多与已知倒位相对应或有其他证据支持，并且预测的倒位频率与目前有限的可用信息在很大程度上相符。
