CNRS UMR 7625 Écologie et Évolution, École Normale Supérieure, Paris, France.
Eur J Hum Genet. 2011 Jan;19(1):70-5. doi: 10.1038/ejhg.2010.154. Epub 2010 Sep 8.
Y-chromosome microsatellites (Y-STRs) are typically used for kinship analysis and forensic identification, as well as for inferences on population history and evolution. All applications would greatly benefit from reliable locus-specific mutation rates, to improve forensic probability calculations and interpretations of diversity data. However, estimates of mutation rate from father-son transmissions are available for few loci and have large confidence intervals, because of the small number of meiosis usually observed. By contrast, population data exist for many more Y-STRs, holding unused information about their mutation rates. To incorporate single locus diversity information into Y-STR mutation rate estimation, we performed a meta-analysis using pedigree data for 80 loci and individual haplotypes for 110 loci, from 29 and 93 published studies, respectively. By means of logistic regression we found that relative genetic diversity, motif size and repeat structure explain the variance of observed rates of mutations from meiosis. This model allowed us to predict locus-specific mutation rates (mean predicted mutation rate 2.12 × 10(-3), SD=1.58 × 10(-3)), including estimates for 30 loci lacking meiosis observations and 41 with a previous estimate of zero. These estimates are more accurate than meiosis-based estimates when a small number of meiosis is available. We argue that our methodological approach, by taking into account locus diversity, could be also adapted to estimate population or lineage-specific mutation rates. Such adjusted estimates would represent valuable information for selecting the most reliable markers for a wide range of applications.
Y 染色体微卫星(Y-STRs)通常用于亲属关系分析和法医鉴定,以及用于推断人口历史和进化。所有这些应用都将极大地受益于可靠的基因座特异性突变率,以提高法医概率计算和多样性数据的解释。然而,由于通常观察到的减数分裂次数较少,来自父子传递的突变率估计值仅适用于少数几个基因座,并且置信区间较大。相比之下,更多的 Y-STR 具有更多的种群数据,其中包含有关其突变率的未使用信息。为了将单基因座多样性信息纳入 Y-STR 突变率估计中,我们使用来自 29 项和 93 项已发表研究的 80 个基因座的家系数据和 110 个基因座的个体单倍型进行了荟萃分析。通过逻辑回归,我们发现相对遗传多样性,基序大小和重复结构解释了减数分裂中观察到的突变率的方差。该模型使我们能够预测基因座特异性突变率(平均预测突变率为 2.12×10(-3),SD=1.58×10(-3)),包括缺乏减数分裂观察的 30 个基因座和以前估计为零的 41 个基因座的估计值。当减数分裂次数较少时,这些估计值比基于减数分裂的估计值更准确。我们认为,我们的方法通过考虑基因座多样性,也可以适用于估计群体或谱系特异性突变率。这种调整后的估计值将为选择广泛应用的最可靠标记提供有价值的信息。