Gonser R, Donnelly P, Nicholson G, Di Rienzo A
Department of Human Genetics, University of Chicago, Illinois 60637, USA.
Genetics. 2000 Apr;154(4):1793-807. doi: 10.1093/genetics/154.4.1793.
Microsatellites have been widely used as tools for population studies. However, inference about population processes relies on the specification of mutation parameters that are largely unknown and likely to differ across loci. Here, we use data on somatic mutations to investigate the mutation process at 14 tetranucleotide repeats and carry out an advanced multilocus analysis of different demographic scenarios on worldwide population samples. We use a method based on less restrictive assumptions about the mutation process, which is more powerful to detect departures from the null hypothesis of constant population size than other methods previously applied to similar data sets. We detect a signal of population expansion in all samples examined, except for one African sample. As part of this analysis, we identify an "anomalous" locus whose extreme pattern of variation cannot be explained by variability in mutation size. Exaggerated mutation rate is proposed as a possible cause for its unusual variation pattern. We evaluate the effect of using it to infer population histories and show that inferences about demographic histories are markedly affected by its inclusion. In fact, exclusion of the anomalous locus reduces interlocus variability of statistics summarizing population variation and strengthens the evidence in favor of demographic growth.
微卫星已被广泛用作群体研究的工具。然而,关于群体过程的推断依赖于突变参数的设定,而这些参数在很大程度上是未知的,并且可能因基因座而异。在这里,我们利用体细胞突变数据来研究14个四核苷酸重复序列的突变过程,并对全球群体样本的不同人口统计学情景进行了高级多位点分析。我们使用了一种基于对突变过程假设限制较少的方法,该方法在检测与恒定群体大小的零假设的偏差方面比以前应用于类似数据集的其他方法更强大。在所有检测的样本中,除了一个非洲样本外,我们都检测到了群体扩张的信号。作为该分析的一部分,我们识别出一个“异常”基因座,其极端的变异模式无法用突变大小的变异性来解释。提出过高的突变率可能是其异常变异模式的一个原因。我们评估了使用它来推断群体历史的影响,并表明关于人口统计学历史的推断受到其纳入的显著影响。事实上,排除异常基因座会降低总结群体变异的统计量的基因座间变异性,并加强支持人口增长的证据。