Detecting disease-causing mutations in the human genome by haplotype matching.
Detecting disease-causing mutations in the human genome by haplotype matching.
复制标题
通过单倍型匹配检测人类基因组中的致病突变。
DOI：
10.1086/508757
复制
发表时间：
2006
影响因子：
9.8
通讯作者：
Olson,MaynardV
中科院分区：
文献类型：
--
作者：
Spencer,DavidH;Bubb,KerryL;Olson,MaynardV
患者的单倍型与人类参考基因组之间的比较经常用于确定致病突变的候选，尽管这些比对有望揭示高水平的背景中性多态性。这将遗传研究的范围限制在相对较小的基因组区间，因为目前区分潜在因果突变和中性变异的方法效率低下。在这里，我们描述了一种检测突变的新策略，该策略基于将受影响的单倍型与来自健康个体的密切匹配的对照序列进行比较，而不是与人类参考基因组进行比较。我们使用理论，模拟和真实数据集来表明，当从只有100个对照基因组的参考面板中选择密切匹配的控制序列时，该方法有望将必须进行后续分析的序列变异数量减少至少20倍。我们还定义了一个参考数据资源，可以有效地将该策略应用于整个基因组的大临界区间。
Comparisons between haplotypes from affected patients and the human reference genome are frequently used to identify candidates for disease-causing mutations, even though these alignments are expected to reveal a high level of background neutral polymorphism. This limits the scope of genetic studies to relatively small genomic intervals, because current methods for distinguishing potential causal mutations from neutral variation are inefficient. Here we describe a new strategy for detecting mutations that is based on comparing affected haplotypes with closely matched control sequences from healthy individuals, rather than with the human reference genome. We use theory, simulation, and a real data set to show that this approach is expected to reduce the number of sequence variants that must be subjected to follow-up analysis by at least a factor of 20 when closely matched control sequences are selected from a reference panel with as few as 100 control genomes. We also define a reference data resource that would allow efficient application of this strategy to large critical intervals across the genome.