Limited role of generation time changes in driving the evolution of the mutation spectrum in humans
- University of Pennsylvania, United States
- University of California, Berkeley, United States
- Columbia University, United States
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)
Article and author information
Author details
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
© 2023, Gao et al.
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.
Metrics
-
- 1,974
- views
-
- 244
- downloads
-
- 12
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Limited role of generation time changes in driving the evolution of the mutation spectrum in humans
eLife 12:e81188.
https://doi.org/10.7554/eLife.81188
Further reading
-
- Evolutionary Biology
The majority of highly polymorphic genes are related to immune functions and with over 100 alleles within a population, genes of the major histocompatibility complex (MHC) are the most polymorphic loci in vertebrates. How such extraordinary polymorphism arose and is maintained is controversial. One possibility is heterozygote advantage (HA), which can in principle maintain any number of alleles, but biologically explicit models based on this mechanism have so far failed to reliably predict the coexistence of significantly more than ten alleles. We here present an eco-evolutionary model showing that evolution can result in the emergence and maintenance of more than 100 alleles under HA if the following two assumptions are fulfilled: first, pathogens are lethal in the absence of an appropriate immune defence; second, the effect of pathogens depends on host condition, with hosts in poorer condition being affected more strongly. Thus, our results show that HA can be a more potent force in explaining the extraordinary polymorphism found at MHC loci than currently recognized.
-
- Evolutionary Biology
Spatial patterns in genetic diversity are shaped by individuals dispersing from their parents and larger-scale population movements. It has long been appreciated that these patterns of movement shape the underlying genealogies along the genome leading to geographic patterns of isolation by distance in contemporary population genetic data. However, extracting the enormous amount of information contained in genealogies along recombining sequences has, until recently, not been computationally feasible. Here we capitalize on important recent advances in genome-wide gene-genealogy reconstruction and develop methods to use thousands of trees to estimate per-generation dispersal rates and to locate the genetic ancestors of a sample back through time. We take a likelihood approach in continuous space using a simple approximate model (branching Brownian motion) as our prior distribution of spatial genealogies. After testing our method with simulations we apply it to Arabidopsis thaliana. We estimate a dispersal rate of roughly 60km2 per generation, slightly higher across latitude than across longitude, potentially reflecting a northward post-glacial expansion. Locating ancestors allows us to visualize major geographic movements, alternative geographic histories, and admixture. Our method highlights the huge amount of information about past dispersal events and population movements contained in genome-wide genealogies.
