Department of Integrative Biology, University of Wisconsin-Madison, Madison, WI, USA.
Department of Ecology and Evolutionary Biology, University of California, Irvine, CA, USA.
Mol Biol Evol. 2023 Aug 3;40(8). doi: 10.1093/molbev/msad160.
Wang et al. (2023) recently proposed an approach to infer the history of human generation intervals from changes in mutation profiles over time. As the relative proportions of different mutation types depend on the ages of parents, binning variants by the time they arose allows for the inference of changes in average paternal and maternal generation intervals. Applying this approach to published allele age estimates, Wang et al. (2023) inferred long-lasting sex differences in average generation times and surprisingly found that ancestral generation times of West African populations remained substantially higher than those of Eurasian populations extending tens of thousands of generations into the past. Here, we argue that the results and interpretations in Wang et al. (2023) are primarily driven by noise and biases in input data and a lack of validation using independent approaches for estimating allele ages. With the recent development of methods to reconstruct genome-wide gene genealogies, coalescence times, and allele ages, we caution that downstream analyses may be strongly influenced by uncharacterized biases in their output.
Wang 等人（2023 年）最近提出了一种从随时间变化的突变特征推断人类世代间隔历史的方法。由于不同突变类型的相对比例取决于父母的年龄，因此按出现时间对变体进行分类可以推断出平均父代和母代世代间隔的变化。Wang 等人（2023 年）将这种方法应用于已发表的等位基因年龄估计值，推断出世代时间的长期性别差异，令人惊讶的是，他们发现，数万年以前的西非人群的祖先世代时间仍然明显高于欧亚人群。在这里，我们认为 Wang 等人（2023 年）的结果和解释主要是由输入数据中的噪声和偏差以及使用独立方法估计等位基因年龄的验证不足驱动的。随着重建全基因组基因谱系、合并时间和等位基因年龄的方法的最新发展，我们警告说，下游分析可能会受到其输出中未表征的偏差的强烈影响。
