Evidence map›Paper›PMID 36779395›Full record

ArticleeLife2023

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

Ziyue Gao, Yulin Zhang, Nathan Cramer, Molly Przeworski, Priya Moorjani

Open access · goldFull text read
In one paragraph

Article in eLife, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
7.2field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. What sets the mutation rate of a cell type in an animal species?bioRxiv : the preprint server for biology · 2025
    Article
  5. A general framework for branch length estimation in Ancestral Recombination Graphs.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Review
  11. Article
  12. Reconstructing generation intervals over time.Nature reviews. Genetics · 2024
    Article
  13. The Evolutionary Interplay of Somatic and Germline Mutation Rates.Annual review of biomedical data science · 2024
    Review
  14. Review
  15. Article
  16. Methods for Assessing Population Relationships and History Using Genomic Data.Annual review of genomics and human genetics · 2023
    Review
  17. Article
  18. Article
  19. "Evolution of the mutation spectrum across a mammalian phylogeny".bioRxiv : the preprint server for biology · 2023
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 1 country.

Ziyue GaoDepartment of Genetics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, United States.ORCID 0000-0001-9244-0238
Yulin ZhangCenter for Computational Biology, University of California, Berkeley, Berkeley, United States.ORCID 0009-0002-8899-5411
Nathan CramerDepartment of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States.
Molly PrzeworskiDepartment of Biological Sciences, Columbia University, New York, United States.ORCID 0000-0002-5369-9009
Priya MoorjaniCenter for Computational Biology, University of California, Berkeley, Berkeley, United States.ORCID 0000-0002-0947-5673
University of California, Berkeley · USColumbia University · USUniversity of Pennsylvania · US

Funding

Genomic Insights into Human Population Mixture and its Role in Adaptation and DiseaseR35GM142978 · NIGMS · UNIVERSITY OF CALIFORNIA BERKELEY · PI Priya Moorjani · 2021 to 2026
$2.5M
Mechanisms and consequences of sequence context-dependency of human mutation rateR35GM146810 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI Ziyue Gao · 2022 to 2026
$2.0M
Mutation rate variation in primatesR01GM122975 · NIGMS · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI PRZEWORSKI, MOLLY F · 2017 to 2020
$1.6M
NIGMS NIH HHS R01 GM122975NIGMS NIH HHS R35 GM142978NIGMS NIH HHS R35 GM146810NIH HHS GM122975NIH HHS R35GM142978NIH HHS R35GM146810
6 · The paper itself

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>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.

Indexed as

Germ-Line MutationMutation RateGenomeHumansMutationSelection, Geneticbiased gene conversiondemographyevolutionary biologygeneration timegeneticsgenomicshumanmutation spectrumnatural selection

Identifiers

PMID36779395
PMCPMC10014080
OpenAlexW4320491870

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read68
identifiers read2
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.