Limited role of generation time changes in driving the evolution of the mutation spectrum in humans

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Abstract

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>G and 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.

Data availability

All data generated or analyzed during this study were based on publicly available datasets like the 1000 Genomes Project. Source data for Figures 1-4 contain the numerical data used to generate the figures. Source data for figure 1 is available at the following URL: https://doi.org/10.6078/D19B0H. (Note, For private access prior to publication, the dataset is available at the URL: https://datadryad.org/stash/share/JK1BdqPhl6azkQru6gLTi6_dA-6lobKUxzpUM7mW69Y)

The following previously published data sets were used

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Ziyue Gao

Department of Genetics, University of Pennsylvania, Philadelphia, United States

For correspondence
ziyuegao@pennmedicine.upenn.edu

Competing interests
No competing interests declared.

"This ORCID iD identifies the author of this article:" 0000-0001-9244-0238
Yulin Zhang

Center for Computational Biology, University of California, Berkeley, Berkeley, United States

Competing interests
No competing interests declared.
Nathan Cramer

Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States

Competing interests
No competing interests declared.
Molly Przeworski

Department of Systems Biology, Columbia University, New York, United States

Competing interests
Molly Przeworski, Reviewing editor, eLife.

"This ORCID iD identifies the author of this article:" 0000-0002-5369-9009
Priya Moorjani

Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States

For correspondence
moorjani@berkeley.edu

Competing interests
No competing interests declared.

"This ORCID iD identifies the author of this article:" 0000-0002-0947-5673

Funding

National Institutes of Health (R35GM146810)

Ziyue Gao

Alfred P. Sloan Foundation

Ziyue Gao

National Institutes of Health (R35GM142978)

Priya Moorjani

Alfred P. Sloan Foundation

Priya Moorjani

National Institutes of Health (GM122975)

Molly Przeworski

National Science Foundation (DGE 2146752)

Nathan Cramer

Hellman Family Foundation

Priya Moorjani

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.