Limited role of generation time changes in driving the evolution of the mutation spectrum in humans.
Limited role of generation time changes in driving the evolution of the mutation spectrum in humans.
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DOI：
10.7554/elife.81188
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发表时间：
2023-02-13
期刊：
影响因子：
7.7
通讯作者：
Moorjani P
中科院分区：
文献类型：
--
作者：
Gao Z;Zhang Y;Cramer N;Przeworski M;Moorjani P
最近的研究表明，人类种系突变率和谱系发展迅速。世代时间的变化与这些变化有关，尽管其贡献仍不清楚。我们开发了一个框架来表征群体内部和群体之间多态性的时间变化，同时控制自然选择和有偏见的基因转换的影响。对千人基因组计划数据集的应用揭示了大陆群体分裂后出现的多个独立变化，包括先前报道的欧洲人 TCC>TTC 突变的短暂升高以及人群样本中 C>G 和 T>A 突变率差异的新信号。我们还发现非洲境内和境外采样的群体之间在非洲迁徙之前的旧 T>C 多态性方面存在显着差异。这种令人惊讶的信号是由 TpG>CpG 突变驱动的，部分源于错误极化的 CpG 转变，这种转变更有可能发生反复突变。最后，通过将多态性的突变谱与父母年龄对新生突变的影响联系起来，我们表明，世代时间的合理变化不能共同解释不同突变类型观察到的模式。因此，其他因素——基因修饰剂或环境暴露——一定对人类突变景观产生了不可忽视的影响。每个人都有 23 对染色体，从父母各遗传一组。但孩子的染色体并不是父母染色体的精确副本。在卵子或精子细胞的形成过程中，或者在胚胎的早期发育过程中，DNA 的自发变化或突变可能会改变构成 DNA 的一小部分核苷酸或“字母”。这些修饰是人类遗传多样性的重要来源，有助于新性状的进化。当今人类群体中的每一种遗传变异都代表着他们祖先之一的突变。变异的类型和频率因人群而异，并且随着时间的推移而变化，这表明突变模式在过去已经进化。但造成这些人口水平差异的过程仍然难以捉摸。一个可能的因素可能是人口平均繁殖年龄或世代时间的变化。例如，年长的父母比年轻的父母为孩子带来更多且不同类型的新突变。因此，习惯上晚育的人群可能具有不同的突变情况。为了查明情况是否确实如此，Gao 等人。使用计算机算法分析了生活在三大洲的数百名参与“千人基因组计划”的人的基因组。该分析确定了各大陆群体突变模式的差异，并估计了这些变化发生的时间。此外，他们表明，尽管繁殖年龄对突变景观有影响，但仅世代时间的差异并不能解释观察到的人类突变谱的变化。除了世代时间之外的因素，例如环境暴露，可能在改变这些模式方面发挥了作用。这项研究为人类进化过程中突变景观的变化提供了新的见解。绘制全世界人类的这些模式可能有助于科学家了解这些变化背后的原因。高等人使用的技术。还可能有助于分析其他生物体突变模式的变化。
Recent studies have suggested that the human germline mutation rate and spectrum evolve rapidly. Variation in generation time has been linked to these changes, though its contribution remains unclear. We develop a framework to characterize temporal changes in polymorphisms within and between populations, while controlling for the effects of natural selection and biased gene conversion. Application to the 1000 Genomes Project dataset reveals multiple independent changes that arose after the split of continental groups, including a previously reported, transient elevation in TCC>TTC mutations in Europeans and novel signals of divergence in C>Gand T>A mutation rates among population samples. We also find a significant difference between groups sampled in and outside of Africa in old T>C polymorphisms that predate the out-of-Africa migration. This surprising signal is driven by TpG>CpG mutations and stems in part from mis-polarized CpG transitions, which are more likely to undergo recurrent mutations. Finally, by relating the mutation spectrum of polymorphisms to parental age effects on de novo mutations, we show that plausible changes in the generation time cannot explain the patterns observed for different mutation types jointly. Thus, other factors – genetic modifiers or environmental exposures – must have had a non-negligible impact on the human mutation landscape. Each human has 23 pairs of chromosomes, one set inherited from each parent. But the child's chromosomes are not an exact copy of their parents' chromosomes. Spontaneous changes or mutations in the DNA during the formation of the egg or sperm cells, or early development of the embryo, can change a small fraction of the nucleotides or ‘letters’ that make up the DNA. These modifications are an important source of genetic diversity in human populations and contribute to the evolution of new traits. Each genetic variant in present-day human populations represents a mutation in one of their ancestors. The types and frequencies of variants vary across human populations and have changed over time, suggesting that mutation patterns have evolved in the past. But the processes driving these population-level differences remain elusive. One possible factor may be changes in the average age of reproduction or the generation time in a population . For example, older parents contribute more – and also different types of – new mutations to their children than younger parents do. Populations, where it is customary to have children at older ages, may therefore have a different mutation landscape. To find out if this is indeed the case, Gao et al. used computer algorithms to analyze the genomes of hundreds of people living on three continents who participated in ‘the 1,000 Genomes Project’. The analysis identified differences in mutation patterns across continental groups and estimated when these changes occurred. Further, they showed that although the age of reproduction had an impact on the mutation landscape, differences in generation time alone could not explain the observed changes in the human mutation spectrum. Factors other than generation time, such as environmental exposures, may have played a role in shifting these patterns. The study provides new insights into the changes in the mutation landscape over the course of human evolution. Mapping these patterns in humans worldwide may help scientists understand the causes underlying these changes. The techniques used by Gao et al. may also help analyze changes in mutation patterns in other organisms.